| AdaColmap |  | | 97.23 130 | 96.80 138 | 98.51 133 | 99.99 1 | 95.60 202 | 99.09 332 | 98.84 65 | 93.32 210 | 96.74 224 | 99.72 95 | 86.04 264 | 100.00 1 | 98.01 153 | 99.43 129 | 99.94 87 |
|
| CNVR-MVS | | | 99.40 1 | 99.26 1 | 99.84 7 | 99.98 2 | 99.51 7 | 99.98 24 | 98.69 82 | 98.20 9 | 99.93 3 | 99.98 2 | 96.82 26 | 100.00 1 | 99.75 41 | 100.00 1 | 99.99 26 |
|
| TestfortrainingZip | | | | | 99.90 5 | 99.97 3 | 99.70 5 | 99.97 42 | 98.89 52 | 96.02 99 | 99.99 1 | 99.96 3 | 97.97 5 | 100.00 1 | | 99.65 96 | 100.00 1 |
|
| MCST-MVS | | | 99.32 3 | 99.14 4 | 99.86 6 | 99.97 3 | 99.59 6 | 99.97 42 | 98.64 91 | 98.47 3 | 99.13 107 | 99.92 16 | 96.38 36 | 100.00 1 | 99.74 43 | 100.00 1 | 100.00 1 |
|
| mPP-MVS | | | 98.39 56 | 98.20 54 | 98.97 93 | 99.97 3 | 96.92 139 | 99.95 75 | 98.38 184 | 95.04 124 | 98.61 141 | 99.80 59 | 93.39 117 | 100.00 1 | 98.64 114 | 100.00 1 | 99.98 57 |
|
| CPTT-MVS | | | 97.64 110 | 97.32 114 | 98.58 122 | 99.97 3 | 95.77 191 | 99.96 56 | 98.35 190 | 89.90 355 | 98.36 156 | 99.79 63 | 91.18 180 | 99.99 39 | 98.37 131 | 99.99 21 | 99.99 26 |
|
| DP-MVS Recon | | | 98.41 53 | 98.02 68 | 99.56 30 | 99.97 3 | 98.70 53 | 99.92 103 | 98.44 148 | 92.06 282 | 98.40 155 | 99.84 49 | 95.68 48 | 100.00 1 | 98.19 142 | 99.71 91 | 99.97 67 |
|
| PAPR | | | 98.52 43 | 98.16 58 | 99.58 29 | 99.97 3 | 98.77 47 | 99.95 75 | 98.43 156 | 95.35 118 | 98.03 171 | 99.75 81 | 94.03 102 | 99.98 51 | 98.11 147 | 99.83 80 | 99.99 26 |
|
| MED-MVS test | | | | | 99.60 24 | 99.96 9 | 98.79 42 | 99.97 42 | 98.88 55 | 96.36 90 | 99.07 112 | 99.93 12 | | 100.00 1 | 99.98 9 | 99.96 46 | 99.99 26 |
|
| MED-MVS | | | 99.24 8 | 99.11 7 | 99.60 24 | 99.96 9 | 98.79 42 | 99.97 42 | 98.88 55 | 96.91 62 | 99.07 112 | 99.92 16 | 97.36 18 | 100.00 1 | 99.98 9 | 99.96 46 | 100.00 1 |
|
| TestfortrainingZip a | | | 99.01 16 | 98.78 21 | 99.69 17 | 99.96 9 | 99.09 25 | 99.97 42 | 98.74 76 | 96.91 62 | 99.86 16 | 99.92 16 | 96.29 37 | 99.99 39 | 98.32 134 | 99.09 149 | 100.00 1 |
|
| HFP-MVS | | | 98.56 39 | 98.37 43 | 99.14 73 | 99.96 9 | 97.43 115 | 99.95 75 | 98.61 99 | 94.77 134 | 99.31 95 | 99.85 38 | 94.22 95 | 100.00 1 | 98.70 109 | 99.98 32 | 99.98 57 |
|
| region2R | | | 98.54 41 | 98.37 43 | 99.05 83 | 99.96 9 | 97.18 125 | 99.96 56 | 98.55 119 | 94.87 131 | 99.45 81 | 99.85 38 | 94.07 101 | 100.00 1 | 98.67 111 | 100.00 1 | 99.98 57 |
|
| ACMMPR | | | 98.50 44 | 98.32 47 | 99.05 83 | 99.96 9 | 97.18 125 | 99.95 75 | 98.60 101 | 94.77 134 | 99.31 95 | 99.84 49 | 93.73 111 | 100.00 1 | 98.70 109 | 99.98 32 | 99.98 57 |
|
| NCCC | | | 99.37 2 | 99.25 2 | 99.71 16 | 99.96 9 | 99.15 23 | 99.97 42 | 98.62 98 | 98.02 22 | 99.90 7 | 99.95 4 | 97.33 19 | 100.00 1 | 99.54 58 | 100.00 1 | 100.00 1 |
|
| CP-MVS | | | 98.45 48 | 98.32 47 | 98.87 98 | 99.96 9 | 96.62 154 | 99.97 42 | 98.39 180 | 94.43 152 | 98.90 121 | 99.87 32 | 94.30 92 | 100.00 1 | 99.04 85 | 99.99 21 | 99.99 26 |
|
| test_one_0601 | | | | | | 99.94 17 | 99.30 13 | | 98.41 173 | 96.63 75 | 99.75 42 | 99.93 12 | 97.49 11 | | | | |
|
| test_0728_SECOND | | | | | 99.82 8 | 99.94 17 | 99.47 8 | 99.95 75 | 98.43 156 | | | | | 100.00 1 | 99.99 5 | 100.00 1 | 100.00 1 |
|
| XVS | | | 98.70 32 | 98.55 31 | 99.15 71 | 99.94 17 | 97.50 111 | 99.94 93 | 98.42 168 | 96.22 93 | 99.41 87 | 99.78 67 | 94.34 89 | 99.96 76 | 98.92 94 | 99.95 53 | 99.99 26 |
|
| X-MVStestdata | | | 93.83 289 | 92.06 324 | 99.15 71 | 99.94 17 | 97.50 111 | 99.94 93 | 98.42 168 | 96.22 93 | 99.41 87 | 41.37 547 | 94.34 89 | 99.96 76 | 98.92 94 | 99.95 53 | 99.99 26 |
|
| test_prior | | | | | 99.43 41 | 99.94 17 | 98.49 66 | | 98.65 88 | | | | | 99.80 143 | | | 99.99 26 |
|
| MSLP-MVS++ | | | 99.13 9 | 99.01 12 | 99.49 37 | 99.94 17 | 98.46 67 | 99.98 24 | 98.86 59 | 97.10 53 | 99.80 28 | 99.94 5 | 95.92 44 | 100.00 1 | 99.51 59 | 100.00 1 | 100.00 1 |
|
| APDe-MVS |  | | 99.06 13 | 98.91 15 | 99.51 34 | 99.94 17 | 98.76 50 | 99.91 111 | 98.39 180 | 97.20 51 | 99.46 80 | 99.85 38 | 95.53 52 | 99.79 145 | 99.86 27 | 100.00 1 | 99.99 26 |
| Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition |
| MP-MVS |  | | 98.23 71 | 97.97 72 | 99.03 85 | 99.94 17 | 97.17 128 | 99.95 75 | 98.39 180 | 94.70 138 | 98.26 162 | 99.81 58 | 91.84 171 | 100.00 1 | 98.85 100 | 99.97 42 | 99.93 88 |
| Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
| CDPH-MVS | | | 98.65 35 | 98.36 45 | 99.49 37 | 99.94 17 | 98.73 51 | 99.87 133 | 98.33 195 | 93.97 179 | 99.76 41 | 99.87 32 | 94.99 68 | 99.75 154 | 98.55 118 | 100.00 1 | 99.98 57 |
|
| PAPM_NR | | | 98.12 75 | 97.93 78 | 98.70 109 | 99.94 17 | 96.13 180 | 99.82 167 | 98.43 156 | 94.56 142 | 97.52 190 | 99.70 101 | 94.40 84 | 99.98 51 | 97.00 197 | 99.98 32 | 99.99 26 |
|
| MG-MVS | | | 98.91 22 | 98.65 27 | 99.68 18 | 99.94 17 | 99.07 26 | 99.64 240 | 99.44 19 | 97.33 44 | 99.00 117 | 99.72 95 | 94.03 102 | 99.98 51 | 98.73 108 | 100.00 1 | 100.00 1 |
|
| ME-MVS | | | 99.07 11 | 98.89 17 | 99.59 27 | 99.93 28 | 98.79 42 | 99.95 75 | 98.80 71 | 95.89 103 | 99.28 99 | 99.93 12 | 96.28 38 | 99.98 51 | 99.98 9 | 99.96 46 | 99.99 26 |
|
| SED-MVS | | | 99.28 5 | 99.11 7 | 99.77 9 | 99.93 28 | 99.30 13 | 99.96 56 | 98.43 156 | 97.27 47 | 99.80 28 | 99.94 5 | 96.71 29 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
| IU-MVS | | | | | | 99.93 28 | 99.31 11 | | 98.41 173 | 97.71 31 | 99.84 23 | | | | 100.00 1 | 100.00 1 | 100.00 1 |
|
| test_241102_ONE | | | | | | 99.93 28 | 99.30 13 | | 98.43 156 | 97.26 49 | 99.80 28 | 99.88 29 | 96.71 29 | 100.00 1 | | | |
|
| DVP-MVS |  | | 99.30 4 | 99.16 3 | 99.73 13 | 99.93 28 | 99.29 16 | 99.95 75 | 98.32 197 | 97.28 45 | 99.83 24 | 99.91 19 | 97.22 21 | 100.00 1 | 99.99 5 | 100.00 1 | 99.89 97 |
| Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025 |
| test0726 | | | | | | 99.93 28 | 99.29 16 | 99.96 56 | 98.42 168 | 97.28 45 | 99.86 16 | 99.94 5 | 97.22 21 | | | | |
|
| MSP-MVS | | | 99.09 10 | 99.12 5 | 98.98 92 | 99.93 28 | 97.24 122 | 99.95 75 | 98.42 168 | 97.50 38 | 99.52 76 | 99.88 29 | 97.43 17 | 99.71 160 | 99.50 61 | 99.98 32 | 100.00 1 |
| Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025 |
| agg_prior | | | | | | 99.93 28 | 98.77 47 | | 98.43 156 | | 99.63 59 | | | 99.85 130 | | | |
|
| FOURS1 | | | | | | 99.92 36 | 97.66 105 | 99.95 75 | 98.36 188 | 95.58 112 | 99.52 76 | | | | | | |
|
| ZD-MVS | | | | | | 99.92 36 | 98.57 61 | | 98.52 128 | 92.34 270 | 99.31 95 | 99.83 51 | 95.06 63 | 99.80 143 | 99.70 49 | 99.97 42 | |
|
| GST-MVS | | | 98.27 63 | 97.97 72 | 99.17 66 | 99.92 36 | 97.57 107 | 99.93 100 | 98.39 180 | 94.04 177 | 98.80 126 | 99.74 88 | 92.98 133 | 100.00 1 | 98.16 144 | 99.76 88 | 99.93 88 |
|
| TEST9 | | | | | | 99.92 36 | 98.92 31 | 99.96 56 | 98.43 156 | 93.90 185 | 99.71 49 | 99.86 34 | 95.88 45 | 99.85 130 | | | |
|
| train_agg | | | 98.88 23 | 98.65 27 | 99.59 27 | 99.92 36 | 98.92 31 | 99.96 56 | 98.43 156 | 94.35 157 | 99.71 49 | 99.86 34 | 95.94 42 | 99.85 130 | 99.69 50 | 99.98 32 | 99.99 26 |
|
| test_8 | | | | | | 99.92 36 | 98.88 34 | 99.96 56 | 98.43 156 | 94.35 157 | 99.69 51 | 99.85 38 | 95.94 42 | 99.85 130 | | | |
|
| PGM-MVS | | | 98.34 58 | 98.13 60 | 98.99 90 | 99.92 36 | 97.00 135 | 99.75 199 | 99.50 17 | 93.90 185 | 99.37 92 | 99.76 73 | 93.24 126 | 100.00 1 | 97.75 174 | 99.96 46 | 99.98 57 |
|
| ACMMP |  | | 97.74 103 | 97.44 107 | 98.66 113 | 99.92 36 | 96.13 180 | 99.18 324 | 99.45 18 | 94.84 132 | 96.41 243 | 99.71 98 | 91.40 174 | 99.99 39 | 97.99 155 | 98.03 190 | 99.87 100 |
| Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence |
| DVP-MVS++ | | | 99.26 6 | 99.09 10 | 99.77 9 | 99.91 44 | 99.31 11 | 99.95 75 | 98.43 156 | 96.48 80 | 99.80 28 | 99.93 12 | 97.44 15 | 100.00 1 | 99.92 16 | 99.98 32 | 100.00 1 |
|
| MSC_two_6792asdad | | | | | 99.93 2 | 99.91 44 | 99.80 2 | | 98.41 173 | | | | | 100.00 1 | 99.96 12 | 100.00 1 | 100.00 1 |
|
| No_MVS | | | | | 99.93 2 | 99.91 44 | 99.80 2 | | 98.41 173 | | | | | 100.00 1 | 99.96 12 | 100.00 1 | 100.00 1 |
|
| HPM-MVS++ |  | | 99.07 11 | 98.88 18 | 99.63 19 | 99.90 47 | 99.02 27 | 99.95 75 | 98.56 113 | 97.56 37 | 99.44 82 | 99.85 38 | 95.38 56 | 100.00 1 | 99.31 71 | 99.99 21 | 99.87 100 |
|
| APD-MVS |  | | 98.62 36 | 98.35 46 | 99.41 44 | 99.90 47 | 98.51 64 | 99.87 133 | 98.36 188 | 94.08 172 | 99.74 45 | 99.73 92 | 94.08 100 | 99.74 156 | 99.42 67 | 99.99 21 | 99.99 26 |
| Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
| DeepC-MVS_fast | | 96.59 1 | 98.81 26 | 98.54 32 | 99.62 22 | 99.90 47 | 98.85 37 | 99.24 319 | 98.47 140 | 98.14 16 | 99.08 110 | 99.91 19 | 93.09 130 | 100.00 1 | 99.04 85 | 99.99 21 | 100.00 1 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| OPU-MVS | | | | | 99.93 2 | 99.89 50 | 99.80 2 | 99.96 56 | | | | 99.80 59 | 97.44 15 | 100.00 1 | 100.00 1 | 99.98 32 | 100.00 1 |
|
| DPE-MVS |  | | 99.26 6 | 99.10 9 | 99.74 12 | 99.89 50 | 99.24 20 | 99.87 133 | 98.44 148 | 97.48 39 | 99.64 58 | 99.94 5 | 96.68 31 | 99.99 39 | 99.99 5 | 100.00 1 | 99.99 26 |
| Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
| test_part2 | | | | | | 99.89 50 | 99.25 19 | | | | 99.49 79 | | | | | | |
|
| CSCG | | | 97.10 136 | 97.04 126 | 97.27 243 | 99.89 50 | 91.92 339 | 99.90 117 | 99.07 37 | 88.67 379 | 95.26 276 | 99.82 54 | 93.17 129 | 99.98 51 | 98.15 145 | 99.47 124 | 99.90 96 |
|
| ZNCC-MVS | | | 98.31 60 | 98.03 67 | 99.17 66 | 99.88 54 | 97.59 106 | 99.94 93 | 98.44 148 | 94.31 160 | 98.50 148 | 99.82 54 | 93.06 131 | 99.99 39 | 98.30 136 | 99.99 21 | 99.93 88 |
|
| SR-MVS | | | 98.46 47 | 98.30 50 | 98.93 96 | 99.88 54 | 97.04 134 | 99.84 152 | 98.35 190 | 94.92 128 | 99.32 94 | 99.80 59 | 93.35 119 | 99.78 147 | 99.30 72 | 99.95 53 | 99.96 75 |
|
| 9.14 | | | | 98.38 41 | | 99.87 56 | | 99.91 111 | 98.33 195 | 93.22 213 | 99.78 39 | 99.89 27 | 94.57 80 | 99.85 130 | 99.84 29 | 99.97 42 | |
|
| SMA-MVS |  | | 98.76 29 | 98.48 35 | 99.62 22 | 99.87 56 | 98.87 35 | 99.86 144 | 98.38 184 | 93.19 215 | 99.77 40 | 99.94 5 | 95.54 50 | 100.00 1 | 99.74 43 | 99.99 21 | 100.00 1 |
| Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology |
| NormalMVS | | | 97.90 85 | 97.85 85 | 98.04 166 | 99.86 58 | 95.39 212 | 99.61 247 | 97.78 270 | 96.52 78 | 98.61 141 | 99.31 157 | 92.73 141 | 99.67 168 | 96.77 213 | 99.48 121 | 99.06 254 |
|
| lecture | | | 98.67 33 | 98.46 36 | 99.28 53 | 99.86 58 | 97.88 92 | 99.97 42 | 99.25 30 | 96.07 97 | 99.79 37 | 99.70 101 | 92.53 150 | 99.98 51 | 99.51 59 | 99.48 121 | 99.97 67 |
|
| PHI-MVS | | | 98.41 53 | 98.21 53 | 99.03 85 | 99.86 58 | 97.10 132 | 99.98 24 | 98.80 71 | 90.78 332 | 99.62 62 | 99.78 67 | 95.30 57 | 100.00 1 | 99.80 32 | 99.93 64 | 99.99 26 |
|
| MTAPA | | | 98.29 62 | 97.96 75 | 99.30 52 | 99.85 61 | 97.93 90 | 99.39 292 | 98.28 204 | 95.76 106 | 97.18 205 | 99.88 29 | 92.74 140 | 100.00 1 | 98.67 111 | 99.88 76 | 99.99 26 |
|
| LS3D | | | 95.84 212 | 95.11 229 | 98.02 167 | 99.85 61 | 95.10 232 | 98.74 382 | 98.50 137 | 87.22 404 | 93.66 299 | 99.86 34 | 87.45 239 | 99.95 85 | 90.94 335 | 99.81 86 | 99.02 262 |
|
| HPM-MVS |  | | 97.96 80 | 97.72 90 | 98.68 110 | 99.84 63 | 96.39 166 | 99.90 117 | 98.17 222 | 92.61 251 | 98.62 140 | 99.57 131 | 91.87 170 | 99.67 168 | 98.87 99 | 99.99 21 | 99.99 26 |
| Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
| EI-MVSNet-Vis-set | | | 98.27 63 | 98.11 62 | 98.75 106 | 99.83 64 | 96.59 158 | 99.40 288 | 98.51 131 | 95.29 120 | 98.51 147 | 99.76 73 | 93.60 115 | 99.71 160 | 98.53 121 | 99.52 114 | 99.95 83 |
|
| save fliter | | | | | | 99.82 65 | 98.79 42 | 99.96 56 | 98.40 177 | 97.66 33 | | | | | | | |
|
| PLC |  | 95.54 3 | 97.93 83 | 97.89 82 | 98.05 165 | 99.82 65 | 94.77 245 | 99.92 103 | 98.46 142 | 93.93 182 | 97.20 203 | 99.27 165 | 95.44 55 | 99.97 64 | 97.41 181 | 99.51 117 | 99.41 198 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| APD-MVS_3200maxsize | | | 98.25 68 | 98.08 64 | 98.78 103 | 99.81 67 | 96.60 156 | 99.82 167 | 98.30 202 | 93.95 181 | 99.37 92 | 99.77 71 | 92.84 137 | 99.76 153 | 98.95 90 | 99.92 67 | 99.97 67 |
|
| EI-MVSNet-UG-set | | | 98.14 74 | 97.99 70 | 98.60 118 | 99.80 68 | 96.27 169 | 99.36 298 | 98.50 137 | 95.21 122 | 98.30 159 | 99.75 81 | 93.29 123 | 99.73 159 | 98.37 131 | 99.30 138 | 99.81 109 |
|
| SR-MVS-dyc-post | | | 98.31 60 | 98.17 57 | 98.71 108 | 99.79 69 | 96.37 167 | 99.76 193 | 98.31 199 | 94.43 152 | 99.40 89 | 99.75 81 | 93.28 124 | 99.78 147 | 98.90 97 | 99.92 67 | 99.97 67 |
|
| RE-MVS-def | | | | 98.13 60 | | 99.79 69 | 96.37 167 | 99.76 193 | 98.31 199 | 94.43 152 | 99.40 89 | 99.75 81 | 92.95 134 | | 98.90 97 | 99.92 67 | 99.97 67 |
|
| HPM-MVS_fast | | | 97.80 97 | 97.50 103 | 98.68 110 | 99.79 69 | 96.42 162 | 99.88 130 | 98.16 227 | 91.75 294 | 98.94 119 | 99.54 134 | 91.82 172 | 99.65 172 | 97.62 178 | 99.99 21 | 99.99 26 |
|
| SF-MVS | | | 98.67 33 | 98.40 39 | 99.50 35 | 99.77 72 | 98.67 54 | 99.90 117 | 98.21 217 | 93.53 197 | 99.81 26 | 99.89 27 | 94.70 76 | 99.86 129 | 99.84 29 | 99.93 64 | 99.96 75 |
|
| MGCNet | | | 99.06 13 | 98.84 19 | 99.72 14 | 99.76 73 | 99.21 22 | 99.99 8 | 99.34 25 | 98.70 2 | 99.44 82 | 99.75 81 | 93.24 126 | 99.99 39 | 99.94 14 | 99.41 131 | 99.95 83 |
|
| 旧先验1 | | | | | | 99.76 73 | 97.52 109 | | 98.64 91 | | | 99.85 38 | 95.63 49 | | | 99.94 58 | 99.99 26 |
|
| OMC-MVS | | | 97.28 126 | 97.23 118 | 97.41 232 | 99.76 73 | 93.36 305 | 99.65 236 | 97.95 249 | 96.03 98 | 97.41 196 | 99.70 101 | 89.61 206 | 99.51 178 | 96.73 215 | 98.25 180 | 99.38 201 |
|
| 新几何1 | | | | | 99.42 43 | 99.75 76 | 98.27 71 | | 98.63 97 | 92.69 246 | 99.55 71 | 99.82 54 | 94.40 84 | 100.00 1 | 91.21 327 | 99.94 58 | 99.99 26 |
|
| MP-MVS-pluss | | | 98.07 78 | 97.64 96 | 99.38 49 | 99.74 77 | 98.41 69 | 99.74 203 | 98.18 221 | 93.35 208 | 96.45 236 | 99.85 38 | 92.64 145 | 99.97 64 | 98.91 96 | 99.89 73 | 99.77 116 |
| MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
| TSAR-MVS + MP. | | | 98.93 20 | 98.77 22 | 99.41 44 | 99.74 77 | 98.67 54 | 99.77 187 | 98.38 184 | 96.73 71 | 99.88 13 | 99.74 88 | 94.89 70 | 99.59 174 | 99.80 32 | 99.98 32 | 99.97 67 |
| Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
| test12 | | | | | 99.43 41 | 99.74 77 | 98.56 62 | | 98.40 177 | | 99.65 55 | | 94.76 73 | 99.75 154 | | 99.98 32 | 99.99 26 |
|
| 原ACMM1 | | | | | 98.96 94 | 99.73 80 | 96.99 136 | | 98.51 131 | 94.06 175 | 99.62 62 | 99.85 38 | 94.97 69 | 99.96 76 | 95.11 247 | 99.95 53 | 99.92 93 |
|
| TSAR-MVS + GP. | | | 98.60 37 | 98.51 34 | 98.86 99 | 99.73 80 | 96.63 153 | 99.97 42 | 97.92 254 | 98.07 19 | 98.76 132 | 99.55 132 | 95.00 67 | 99.94 94 | 99.91 19 | 97.68 197 | 99.99 26 |
|
| CANet | | | 98.27 63 | 97.82 87 | 99.63 19 | 99.72 82 | 99.10 24 | 99.98 24 | 98.51 131 | 97.00 59 | 98.52 145 | 99.71 98 | 87.80 230 | 99.95 85 | 99.75 41 | 99.38 133 | 99.83 105 |
|
| reproduce_model | | | 98.75 30 | 98.66 26 | 99.03 85 | 99.71 83 | 97.10 132 | 99.73 210 | 98.23 212 | 97.02 58 | 99.18 105 | 99.90 23 | 94.54 81 | 99.99 39 | 99.77 37 | 99.90 72 | 99.99 26 |
|
| F-COLMAP | | | 96.93 148 | 96.95 129 | 96.87 261 | 99.71 83 | 91.74 349 | 99.85 147 | 97.95 249 | 93.11 223 | 95.72 265 | 99.16 186 | 92.35 156 | 99.94 94 | 95.32 243 | 99.35 136 | 98.92 270 |
|
| reproduce-ours | | | 98.78 27 | 98.67 24 | 99.09 80 | 99.70 85 | 97.30 119 | 99.74 203 | 98.25 208 | 97.10 53 | 99.10 108 | 99.90 23 | 94.59 77 | 99.99 39 | 99.77 37 | 99.91 70 | 99.99 26 |
|
| our_new_method | | | 98.78 27 | 98.67 24 | 99.09 80 | 99.70 85 | 97.30 119 | 99.74 203 | 98.25 208 | 97.10 53 | 99.10 108 | 99.90 23 | 94.59 77 | 99.99 39 | 99.77 37 | 99.91 70 | 99.99 26 |
|
| SD-MVS | | | 98.92 21 | 98.70 23 | 99.56 30 | 99.70 85 | 98.73 51 | 99.94 93 | 98.34 194 | 96.38 86 | 99.81 26 | 99.76 73 | 94.59 77 | 99.98 51 | 99.84 29 | 99.96 46 | 99.97 67 |
| Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024 |
| patch_mono-2 | | | 98.24 69 | 99.12 5 | 95.59 305 | 99.67 88 | 86.91 436 | 99.95 75 | 98.89 52 | 97.60 34 | 99.90 7 | 99.76 73 | 96.54 34 | 99.98 51 | 99.94 14 | 99.82 84 | 99.88 98 |
|
| ACMMP_NAP | | | 98.49 45 | 98.14 59 | 99.54 32 | 99.66 89 | 98.62 60 | 99.85 147 | 98.37 187 | 94.68 139 | 99.53 74 | 99.83 51 | 92.87 136 | 100.00 1 | 98.66 113 | 99.84 79 | 99.99 26 |
|
| DeepPCF-MVS | | 95.94 2 | 97.71 107 | 98.98 13 | 93.92 378 | 99.63 90 | 81.76 471 | 99.96 56 | 98.56 113 | 99.47 1 | 99.19 104 | 99.99 1 | 94.16 99 | 100.00 1 | 99.92 16 | 99.93 64 | 100.00 1 |
|
| EPNet | | | 98.49 45 | 98.40 39 | 98.77 105 | 99.62 91 | 96.80 147 | 99.90 117 | 99.51 16 | 97.60 34 | 99.20 102 | 99.36 152 | 93.71 112 | 99.91 111 | 97.99 155 | 98.71 165 | 99.61 151 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| MM | | | 98.83 24 | 98.53 33 | 99.76 11 | 99.59 92 | 99.33 9 | 99.99 8 | 99.76 6 | 98.39 4 | 99.39 91 | 99.80 59 | 90.49 195 | 99.96 76 | 99.89 21 | 99.43 129 | 99.98 57 |
|
| PVSNet_BlendedMVS | | | 96.05 202 | 95.82 194 | 96.72 267 | 99.59 92 | 96.99 136 | 99.95 75 | 99.10 34 | 94.06 175 | 98.27 160 | 95.80 374 | 89.00 218 | 99.95 85 | 99.12 79 | 87.53 362 | 93.24 436 |
|
| PVSNet_Blended | | | 97.94 82 | 97.64 96 | 98.83 100 | 99.59 92 | 96.99 136 | 100.00 1 | 99.10 34 | 95.38 117 | 98.27 160 | 99.08 191 | 89.00 218 | 99.95 85 | 99.12 79 | 99.25 140 | 99.57 162 |
|
| PatchMatch-RL | | | 96.04 203 | 95.40 212 | 97.95 170 | 99.59 92 | 95.22 226 | 99.52 269 | 99.07 37 | 93.96 180 | 96.49 234 | 98.35 285 | 82.28 326 | 99.82 142 | 90.15 351 | 99.22 143 | 98.81 278 |
|
| dcpmvs_2 | | | 97.42 121 | 98.09 63 | 95.42 312 | 99.58 96 | 87.24 432 | 99.23 320 | 96.95 406 | 94.28 163 | 98.93 120 | 99.73 92 | 94.39 87 | 99.16 207 | 99.89 21 | 99.82 84 | 99.86 102 |
|
| test222 | | | | | | 99.55 97 | 97.41 117 | 99.34 300 | 98.55 119 | 91.86 288 | 99.27 100 | 99.83 51 | 93.84 109 | | | 99.95 53 | 99.99 26 |
|
| CNLPA | | | 97.76 101 | 97.38 110 | 98.92 97 | 99.53 98 | 96.84 141 | 99.87 133 | 98.14 231 | 93.78 189 | 96.55 232 | 99.69 105 | 92.28 158 | 99.98 51 | 97.13 192 | 99.44 128 | 99.93 88 |
|
| API-MVS | | | 97.86 88 | 97.66 94 | 98.47 135 | 99.52 99 | 95.41 210 | 99.47 279 | 98.87 58 | 91.68 296 | 98.84 123 | 99.85 38 | 92.34 157 | 99.99 39 | 98.44 126 | 99.96 46 | 100.00 1 |
|
| PVSNet | | 91.05 13 | 97.13 135 | 96.69 144 | 98.45 138 | 99.52 99 | 95.81 189 | 99.95 75 | 99.65 12 | 94.73 136 | 99.04 115 | 99.21 178 | 84.48 301 | 99.95 85 | 94.92 253 | 98.74 164 | 99.58 160 |
|
| 114514_t | | | 97.41 122 | 96.83 135 | 99.14 73 | 99.51 101 | 97.83 94 | 99.89 127 | 98.27 206 | 88.48 384 | 99.06 114 | 99.66 116 | 90.30 198 | 99.64 173 | 96.32 227 | 99.97 42 | 99.96 75 |
|
| cl22 | | | 93.77 294 | 93.25 294 | 95.33 316 | 99.49 102 | 94.43 257 | 99.61 247 | 98.09 234 | 90.38 343 | 89.16 371 | 95.61 383 | 90.56 193 | 97.34 355 | 91.93 318 | 84.45 385 | 94.21 374 |
|
| testdata | | | | | 98.42 142 | 99.47 103 | 95.33 216 | | 98.56 113 | 93.78 189 | 99.79 37 | 99.85 38 | 93.64 114 | 99.94 94 | 94.97 251 | 99.94 58 | 100.00 1 |
|
| MAR-MVS | | | 97.43 117 | 97.19 120 | 98.15 158 | 99.47 103 | 94.79 244 | 99.05 343 | 98.76 73 | 92.65 249 | 98.66 137 | 99.82 54 | 88.52 224 | 99.98 51 | 98.12 146 | 99.63 98 | 99.67 133 |
| Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020 |
| DP-MVS | | | 94.54 262 | 93.42 284 | 97.91 176 | 99.46 105 | 94.04 276 | 98.93 361 | 97.48 307 | 81.15 461 | 90.04 342 | 99.55 132 | 87.02 247 | 99.95 85 | 88.97 366 | 98.11 186 | 99.73 120 |
|
| MVS_111021_LR | | | 98.42 52 | 98.38 41 | 98.53 130 | 99.39 106 | 95.79 190 | 99.87 133 | 99.86 2 | 96.70 72 | 98.78 127 | 99.79 63 | 92.03 167 | 99.90 113 | 99.17 78 | 99.86 78 | 99.88 98 |
|
| CHOSEN 280x420 | | | 99.01 16 | 99.03 11 | 98.95 95 | 99.38 107 | 98.87 35 | 98.46 401 | 99.42 21 | 97.03 57 | 99.02 116 | 99.09 190 | 99.35 2 | 98.21 317 | 99.73 45 | 99.78 87 | 99.77 116 |
|
| MVS_111021_HR | | | 98.72 31 | 98.62 29 | 99.01 89 | 99.36 108 | 97.18 125 | 99.93 100 | 99.90 1 | 96.81 69 | 98.67 136 | 99.77 71 | 93.92 104 | 99.89 118 | 99.27 74 | 99.94 58 | 99.96 75 |
|
| fmvsm_s_conf0.5_n_11 | | | 98.03 79 | 97.89 82 | 98.46 137 | 99.35 109 | 97.76 98 | 99.99 8 | 98.04 240 | 98.20 9 | 99.90 7 | 99.78 67 | 86.21 262 | 99.95 85 | 99.89 21 | 99.68 93 | 97.65 317 |
|
| DPM-MVS | | | 98.83 24 | 98.46 36 | 99.97 1 | 99.33 110 | 99.92 1 | 99.96 56 | 98.44 148 | 97.96 23 | 99.55 71 | 99.94 5 | 97.18 23 | 100.00 1 | 93.81 284 | 99.94 58 | 99.98 57 |
|
| TAPA-MVS | | 92.12 8 | 94.42 270 | 93.60 276 | 96.90 260 | 99.33 110 | 91.78 348 | 99.78 181 | 98.00 243 | 89.89 356 | 94.52 284 | 99.47 138 | 91.97 168 | 99.18 204 | 69.90 484 | 99.52 114 | 99.73 120 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| reproduce_monomvs | | | 95.38 234 | 95.07 231 | 96.32 282 | 99.32 112 | 96.60 156 | 99.76 193 | 98.85 62 | 96.65 74 | 87.83 400 | 96.05 371 | 99.52 1 | 98.11 322 | 96.58 219 | 81.07 414 | 94.25 367 |
|
| fmvsm_s_conf0.5_n_9 | | | 98.15 73 | 98.02 68 | 98.55 124 | 99.28 113 | 95.84 188 | 99.99 8 | 98.57 107 | 98.17 13 | 99.93 3 | 99.74 88 | 87.04 246 | 99.97 64 | 99.86 27 | 99.59 108 | 99.83 105 |
|
| SPE-MVS-test | | | 97.88 86 | 97.94 77 | 97.70 196 | 99.28 113 | 95.20 227 | 99.98 24 | 97.15 365 | 95.53 114 | 99.62 62 | 99.79 63 | 92.08 166 | 98.38 299 | 98.75 107 | 99.28 139 | 99.52 173 |
|
| test_fmvsm_n_1920 | | | 98.44 49 | 98.61 30 | 97.92 174 | 99.27 115 | 95.18 228 | 100.00 1 | 98.90 50 | 98.05 20 | 99.80 28 | 99.73 92 | 92.64 145 | 99.99 39 | 99.58 57 | 99.51 117 | 98.59 288 |
|
| fmvsm_s_conf0.5_n_10 | | | 98.24 69 | 97.90 80 | 99.26 55 | 99.24 116 | 97.88 92 | 99.99 8 | 98.76 73 | 98.20 9 | 99.92 5 | 99.74 88 | 85.97 266 | 99.94 94 | 99.72 46 | 99.53 113 | 99.96 75 |
|
| fmvsm_l_conf0.5_n_a | | | 99.00 18 | 98.91 15 | 99.28 53 | 99.21 117 | 97.91 91 | 99.98 24 | 98.85 62 | 98.25 5 | 99.92 5 | 99.75 81 | 94.72 74 | 99.97 64 | 99.87 25 | 99.64 97 | 99.95 83 |
|
| fmvsm_s_conf0.5_n_8 | | | 98.38 57 | 98.05 66 | 99.35 50 | 99.20 118 | 98.12 77 | 99.98 24 | 98.81 67 | 98.22 7 | 99.80 28 | 99.71 98 | 87.37 241 | 99.97 64 | 99.91 19 | 99.48 121 | 99.97 67 |
|
| test_yl | | | 97.83 92 | 97.37 111 | 99.21 60 | 99.18 119 | 97.98 86 | 99.64 240 | 99.27 27 | 91.43 305 | 97.88 180 | 98.99 208 | 95.84 46 | 99.84 138 | 98.82 101 | 95.32 289 | 99.79 112 |
|
| DCV-MVSNet | | | 97.83 92 | 97.37 111 | 99.21 60 | 99.18 119 | 97.98 86 | 99.64 240 | 99.27 27 | 91.43 305 | 97.88 180 | 98.99 208 | 95.84 46 | 99.84 138 | 98.82 101 | 95.32 289 | 99.79 112 |
|
| fmvsm_l_conf0.5_n | | | 98.94 19 | 98.84 19 | 99.25 56 | 99.17 121 | 97.81 96 | 99.98 24 | 98.86 59 | 98.25 5 | 99.90 7 | 99.76 73 | 94.21 97 | 99.97 64 | 99.87 25 | 99.52 114 | 99.98 57 |
|
| DeepC-MVS | | 94.51 4 | 96.92 149 | 96.40 160 | 98.45 138 | 99.16 122 | 95.90 186 | 99.66 235 | 98.06 237 | 96.37 89 | 94.37 290 | 99.49 137 | 83.29 319 | 99.90 113 | 97.63 177 | 99.61 104 | 99.55 164 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| DELS-MVS | | | 98.54 41 | 98.22 52 | 99.50 35 | 99.15 123 | 98.65 58 | 100.00 1 | 98.58 105 | 97.70 32 | 98.21 166 | 99.24 174 | 92.58 148 | 99.94 94 | 98.63 116 | 99.94 58 | 99.92 93 |
| Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023 |
| fmvsm_l_conf0.5_n_3 | | | 98.41 53 | 98.08 64 | 99.39 46 | 99.12 124 | 98.29 70 | 99.98 24 | 98.64 91 | 98.14 16 | 99.86 16 | 99.76 73 | 87.99 229 | 99.97 64 | 99.72 46 | 99.54 111 | 99.91 95 |
|
| fmvsm_l_conf0.5_n_9 | | | 98.55 40 | 98.23 51 | 99.49 37 | 99.10 125 | 98.50 65 | 99.99 8 | 98.70 80 | 98.14 16 | 99.94 2 | 99.68 112 | 89.02 217 | 99.98 51 | 99.89 21 | 99.61 104 | 99.99 26 |
|
| CS-MVS | | | 97.79 99 | 97.91 79 | 97.43 228 | 99.10 125 | 94.42 258 | 99.99 8 | 97.10 379 | 95.07 123 | 99.68 52 | 99.75 81 | 92.95 134 | 98.34 303 | 98.38 129 | 99.14 145 | 99.54 168 |
|
| Anonymous202405211 | | | 93.10 312 | 91.99 325 | 96.40 278 | 99.10 125 | 89.65 401 | 98.88 367 | 97.93 251 | 83.71 444 | 94.00 296 | 98.75 246 | 68.79 440 | 99.88 124 | 95.08 248 | 91.71 322 | 99.68 131 |
|
| fmvsm_s_conf0.5_n | | | 97.80 97 | 97.85 85 | 97.67 197 | 99.06 128 | 94.41 259 | 99.98 24 | 98.97 43 | 97.34 42 | 99.63 59 | 99.69 105 | 87.27 242 | 99.97 64 | 99.62 55 | 99.06 151 | 98.62 287 |
|
| HyFIR lowres test | | | 96.66 167 | 96.43 157 | 97.36 237 | 99.05 129 | 93.91 282 | 99.70 226 | 99.80 3 | 90.54 338 | 96.26 246 | 98.08 297 | 92.15 164 | 98.23 316 | 96.84 207 | 95.46 284 | 99.93 88 |
|
| LFMVS | | | 94.75 256 | 93.56 279 | 98.30 148 | 99.03 130 | 95.70 196 | 98.74 382 | 97.98 246 | 87.81 397 | 98.47 149 | 99.39 149 | 67.43 449 | 99.53 175 | 98.01 153 | 95.20 292 | 99.67 133 |
|
| fmvsm_s_conf0.5_n_4 | | | 97.75 102 | 97.86 84 | 97.42 229 | 99.01 131 | 94.69 248 | 99.97 42 | 98.76 73 | 97.91 25 | 99.87 14 | 99.76 73 | 86.70 253 | 99.93 104 | 99.67 52 | 99.12 148 | 97.64 318 |
|
| fmvsm_s_conf0.5_n_2 | | | 97.59 112 | 97.28 115 | 98.53 130 | 99.01 131 | 98.15 72 | 99.98 24 | 98.59 103 | 98.17 13 | 99.75 42 | 99.63 122 | 81.83 332 | 99.94 94 | 99.78 35 | 98.79 162 | 97.51 326 |
|
| AllTest | | | 92.48 329 | 91.64 332 | 95.00 325 | 99.01 131 | 88.43 419 | 98.94 359 | 96.82 421 | 86.50 414 | 88.71 376 | 98.47 280 | 74.73 414 | 99.88 124 | 85.39 413 | 96.18 258 | 96.71 332 |
|
| TestCases | | | | | 95.00 325 | 99.01 131 | 88.43 419 | | 96.82 421 | 86.50 414 | 88.71 376 | 98.47 280 | 74.73 414 | 99.88 124 | 85.39 413 | 96.18 258 | 96.71 332 |
|
| COLMAP_ROB |  | 90.47 14 | 92.18 336 | 91.49 338 | 94.25 359 | 99.00 135 | 88.04 425 | 98.42 407 | 96.70 428 | 82.30 456 | 88.43 388 | 99.01 201 | 76.97 389 | 99.85 130 | 86.11 409 | 96.50 249 | 94.86 343 |
| Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
| fmvsm_s_conf0.5_n_3 | | | 97.95 81 | 97.66 94 | 98.81 101 | 98.99 136 | 98.07 80 | 99.98 24 | 98.81 67 | 98.18 12 | 99.89 11 | 99.70 101 | 84.15 305 | 99.97 64 | 99.76 40 | 99.50 119 | 98.39 295 |
|
| test_fmvs1 | | | 95.35 235 | 95.68 201 | 94.36 355 | 98.99 136 | 84.98 447 | 99.96 56 | 96.65 430 | 97.60 34 | 99.73 47 | 98.96 214 | 71.58 430 | 99.93 104 | 98.31 135 | 99.37 134 | 98.17 301 |
|
| HY-MVS | | 92.50 7 | 97.79 99 | 97.17 122 | 99.63 19 | 98.98 138 | 99.32 10 | 97.49 437 | 99.52 14 | 95.69 109 | 98.32 158 | 97.41 318 | 93.32 121 | 99.77 150 | 98.08 150 | 95.75 274 | 99.81 109 |
|
| VNet | | | 97.21 131 | 96.57 149 | 99.13 77 | 98.97 139 | 97.82 95 | 99.03 346 | 99.21 32 | 94.31 160 | 99.18 105 | 98.88 227 | 86.26 261 | 99.89 118 | 98.93 92 | 94.32 302 | 99.69 130 |
|
| thres200 | | | 96.96 145 | 96.21 168 | 99.22 59 | 98.97 139 | 98.84 38 | 99.85 147 | 99.71 7 | 93.17 217 | 96.26 246 | 98.88 227 | 89.87 203 | 99.51 178 | 94.26 272 | 94.91 294 | 99.31 219 |
|
| tfpn200view9 | | | 96.79 154 | 95.99 177 | 99.19 62 | 98.94 141 | 98.82 39 | 99.78 181 | 99.71 7 | 92.86 233 | 96.02 256 | 98.87 234 | 89.33 210 | 99.50 180 | 93.84 281 | 94.57 298 | 99.27 229 |
|
| thres400 | | | 96.78 156 | 95.99 177 | 99.16 69 | 98.94 141 | 98.82 39 | 99.78 181 | 99.71 7 | 92.86 233 | 96.02 256 | 98.87 234 | 89.33 210 | 99.50 180 | 93.84 281 | 94.57 298 | 99.16 242 |
|
| sasdasda | | | 97.09 138 | 96.32 162 | 99.39 46 | 98.93 143 | 98.95 29 | 99.72 214 | 97.35 321 | 94.45 148 | 97.88 180 | 99.42 142 | 86.71 251 | 99.52 176 | 98.48 123 | 93.97 308 | 99.72 122 |
|
| Anonymous20231211 | | | 89.86 387 | 88.44 395 | 94.13 367 | 98.93 143 | 90.68 379 | 98.54 398 | 98.26 207 | 76.28 479 | 86.73 414 | 95.54 387 | 70.60 436 | 97.56 348 | 90.82 338 | 80.27 423 | 94.15 383 |
|
| canonicalmvs | | | 97.09 138 | 96.32 162 | 99.39 46 | 98.93 143 | 98.95 29 | 99.72 214 | 97.35 321 | 94.45 148 | 97.88 180 | 99.42 142 | 86.71 251 | 99.52 176 | 98.48 123 | 93.97 308 | 99.72 122 |
|
| SDMVSNet | | | 94.80 251 | 93.96 266 | 97.33 240 | 98.92 146 | 95.42 209 | 99.59 252 | 98.99 40 | 92.41 266 | 92.55 314 | 97.85 309 | 75.81 404 | 98.93 221 | 97.90 162 | 91.62 323 | 97.64 318 |
|
| sd_testset | | | 93.55 301 | 92.83 305 | 95.74 303 | 98.92 146 | 90.89 375 | 98.24 415 | 98.85 62 | 92.41 266 | 92.55 314 | 97.85 309 | 71.07 435 | 98.68 262 | 93.93 278 | 91.62 323 | 97.64 318 |
|
| EPNet_dtu | | | 95.71 223 | 95.39 213 | 96.66 269 | 98.92 146 | 93.41 301 | 99.57 258 | 98.90 50 | 96.19 95 | 97.52 190 | 98.56 270 | 92.65 144 | 97.36 353 | 77.89 465 | 98.33 175 | 99.20 239 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| WTY-MVS | | | 98.10 76 | 97.60 98 | 99.60 24 | 98.92 146 | 99.28 18 | 99.89 127 | 99.52 14 | 95.58 112 | 98.24 164 | 99.39 149 | 93.33 120 | 99.74 156 | 97.98 157 | 95.58 283 | 99.78 115 |
|
| CHOSEN 1792x2688 | | | 96.81 153 | 96.53 150 | 97.64 201 | 98.91 150 | 93.07 308 | 99.65 236 | 99.80 3 | 95.64 110 | 95.39 272 | 98.86 236 | 84.35 303 | 99.90 113 | 96.98 199 | 99.16 144 | 99.95 83 |
|
| thres100view900 | | | 96.74 162 | 95.92 189 | 99.18 63 | 98.90 151 | 98.77 47 | 99.74 203 | 99.71 7 | 92.59 253 | 95.84 259 | 98.86 236 | 89.25 212 | 99.50 180 | 93.84 281 | 94.57 298 | 99.27 229 |
|
| thres600view7 | | | 96.69 165 | 95.87 193 | 99.14 73 | 98.90 151 | 98.78 46 | 99.74 203 | 99.71 7 | 92.59 253 | 95.84 259 | 98.86 236 | 89.25 212 | 99.50 180 | 93.44 294 | 94.50 301 | 99.16 242 |
|
| MSDG | | | 94.37 272 | 93.36 291 | 97.40 233 | 98.88 153 | 93.95 281 | 99.37 296 | 97.38 316 | 85.75 425 | 90.80 333 | 99.17 183 | 84.11 307 | 99.88 124 | 86.35 405 | 98.43 173 | 98.36 297 |
|
| MGCFI-Net | | | 97.00 143 | 96.22 167 | 99.34 51 | 98.86 154 | 98.80 41 | 99.67 234 | 97.30 333 | 94.31 160 | 97.77 186 | 99.41 146 | 86.36 259 | 99.50 180 | 98.38 129 | 93.90 310 | 99.72 122 |
|
| h-mvs33 | | | 94.92 248 | 94.36 251 | 96.59 271 | 98.85 155 | 91.29 367 | 98.93 361 | 98.94 44 | 95.90 101 | 98.77 129 | 98.42 283 | 90.89 188 | 99.77 150 | 97.80 167 | 70.76 469 | 98.72 284 |
|
| Anonymous20240529 | | | 92.10 337 | 90.65 349 | 96.47 273 | 98.82 156 | 90.61 381 | 98.72 384 | 98.67 87 | 75.54 483 | 93.90 298 | 98.58 268 | 66.23 454 | 99.90 113 | 94.70 262 | 90.67 326 | 98.90 273 |
|
| PVSNet_Blended_VisFu | | | 97.27 127 | 96.81 137 | 98.66 113 | 98.81 157 | 96.67 152 | 99.92 103 | 98.64 91 | 94.51 144 | 96.38 244 | 98.49 276 | 89.05 216 | 99.88 124 | 97.10 194 | 98.34 174 | 99.43 194 |
|
| PS-MVSNAJ | | | 98.44 49 | 98.20 54 | 99.16 69 | 98.80 158 | 98.92 31 | 99.54 267 | 98.17 222 | 97.34 42 | 99.85 20 | 99.85 38 | 91.20 177 | 99.89 118 | 99.41 68 | 99.67 94 | 98.69 285 |
|
| CANet_DTU | | | 96.76 157 | 96.15 171 | 98.60 118 | 98.78 159 | 97.53 108 | 99.84 152 | 97.63 284 | 97.25 50 | 99.20 102 | 99.64 119 | 81.36 338 | 99.98 51 | 92.77 306 | 98.89 156 | 98.28 299 |
|
| mvsany_test1 | | | 97.82 95 | 97.90 80 | 97.55 212 | 98.77 160 | 93.04 311 | 99.80 175 | 97.93 251 | 96.95 61 | 99.61 69 | 99.68 112 | 90.92 185 | 99.83 140 | 99.18 77 | 98.29 179 | 99.80 111 |
|
| alignmvs | | | 97.81 96 | 97.33 113 | 99.25 56 | 98.77 160 | 98.66 56 | 99.99 8 | 98.44 148 | 94.40 156 | 98.41 153 | 99.47 138 | 93.65 113 | 99.42 190 | 98.57 117 | 94.26 304 | 99.67 133 |
|
| SymmetryMVS | | | 97.64 110 | 97.46 104 | 98.17 154 | 98.74 162 | 95.39 212 | 99.61 247 | 99.26 29 | 96.52 78 | 98.61 141 | 99.31 157 | 92.73 141 | 99.67 168 | 96.77 213 | 95.63 281 | 99.45 190 |
|
| SteuartSystems-ACMMP | | | 99.02 15 | 98.97 14 | 99.18 63 | 98.72 163 | 97.71 100 | 99.98 24 | 98.44 148 | 96.85 64 | 99.80 28 | 99.91 19 | 97.57 9 | 99.85 130 | 99.44 66 | 99.99 21 | 99.99 26 |
| Skip Steuart: Steuart Systems R&D Blog. |
| xiu_mvs_v2_base | | | 98.23 71 | 97.97 72 | 99.02 88 | 98.69 164 | 98.66 56 | 99.52 269 | 98.08 236 | 97.05 56 | 99.86 16 | 99.86 34 | 90.65 190 | 99.71 160 | 99.39 70 | 98.63 166 | 98.69 285 |
|
| miper_enhance_ethall | | | 94.36 274 | 93.98 265 | 95.49 306 | 98.68 165 | 95.24 224 | 99.73 210 | 97.29 341 | 93.28 212 | 89.86 347 | 95.97 372 | 94.37 88 | 97.05 376 | 92.20 310 | 84.45 385 | 94.19 375 |
|
| fmvsm_s_conf0.5_n_5 | | | 98.08 77 | 97.71 92 | 99.17 66 | 98.67 166 | 97.69 104 | 99.99 8 | 98.57 107 | 97.40 40 | 99.89 11 | 99.69 105 | 85.99 265 | 99.96 76 | 99.80 32 | 99.40 132 | 99.85 103 |
|
| ETVMVS | | | 97.03 142 | 96.64 145 | 98.20 153 | 98.67 166 | 97.12 129 | 99.89 127 | 98.57 107 | 91.10 318 | 98.17 167 | 98.59 265 | 93.86 108 | 98.19 318 | 95.64 240 | 95.24 291 | 99.28 226 |
|
| test2506 | | | 97.53 114 | 97.19 120 | 98.58 122 | 98.66 168 | 96.90 140 | 98.81 376 | 99.77 5 | 94.93 126 | 97.95 174 | 98.96 214 | 92.51 151 | 99.20 202 | 94.93 252 | 98.15 183 | 99.64 139 |
|
| ECVR-MVS |  | | 95.66 226 | 95.05 232 | 97.51 217 | 98.66 168 | 93.71 286 | 98.85 373 | 98.45 143 | 94.93 126 | 96.86 217 | 98.96 214 | 75.22 410 | 99.20 202 | 95.34 242 | 98.15 183 | 99.64 139 |
|
| BridgeMVS | | | 98.27 63 | 97.99 70 | 99.11 78 | 98.64 170 | 98.43 68 | 99.47 279 | 97.79 266 | 94.56 142 | 99.74 45 | 98.35 285 | 94.33 91 | 99.25 196 | 99.12 79 | 99.96 46 | 99.64 139 |
|
| fmvsm_s_conf0.5_n_a | | | 97.73 105 | 97.72 90 | 97.77 189 | 98.63 171 | 94.26 267 | 99.96 56 | 98.92 49 | 97.18 52 | 99.75 42 | 99.69 105 | 87.00 248 | 99.97 64 | 99.46 64 | 98.89 156 | 99.08 252 |
|
| MVSMamba_PlusPlus | | | 97.83 92 | 97.45 106 | 98.99 90 | 98.60 172 | 98.15 72 | 99.58 254 | 97.74 275 | 90.34 346 | 99.26 101 | 98.32 288 | 94.29 93 | 99.23 197 | 99.03 88 | 99.89 73 | 99.58 160 |
|
| balanced_ft_v1 | | | 96.88 150 | 96.52 151 | 97.96 169 | 98.60 172 | 94.94 237 | 99.41 287 | 97.56 296 | 93.53 197 | 99.42 86 | 97.89 308 | 83.33 318 | 99.31 193 | 99.29 73 | 99.62 99 | 99.64 139 |
|
| testing222 | | | 97.08 141 | 96.75 140 | 98.06 164 | 98.56 174 | 96.82 142 | 99.85 147 | 98.61 99 | 92.53 261 | 98.84 123 | 98.84 240 | 93.36 118 | 98.30 308 | 95.84 236 | 94.30 303 | 99.05 256 |
|
| test1111 | | | 95.57 229 | 94.98 235 | 97.37 235 | 98.56 174 | 93.37 304 | 98.86 371 | 98.45 143 | 94.95 125 | 96.63 226 | 98.95 219 | 75.21 411 | 99.11 208 | 95.02 249 | 98.14 185 | 99.64 139 |
|
| MVSTER | | | 95.53 230 | 95.22 224 | 96.45 276 | 98.56 174 | 97.72 99 | 99.91 111 | 97.67 280 | 92.38 269 | 91.39 324 | 97.14 325 | 97.24 20 | 97.30 360 | 94.80 258 | 87.85 355 | 94.34 362 |
|
| testing3-2 | | | 97.72 106 | 97.43 109 | 98.60 118 | 98.55 177 | 97.11 131 | 100.00 1 | 99.23 31 | 93.78 189 | 97.90 176 | 98.73 248 | 95.50 53 | 99.69 164 | 98.53 121 | 94.63 296 | 98.99 264 |
|
| VDD-MVS | | | 93.77 294 | 92.94 303 | 96.27 283 | 98.55 177 | 90.22 390 | 98.77 381 | 97.79 266 | 90.85 324 | 96.82 221 | 99.42 142 | 61.18 474 | 99.77 150 | 98.95 90 | 94.13 305 | 98.82 277 |
|
| tpmvs | | | 94.28 276 | 93.57 278 | 96.40 278 | 98.55 177 | 91.50 365 | 95.70 476 | 98.55 119 | 87.47 399 | 92.15 317 | 94.26 441 | 91.42 173 | 98.95 220 | 88.15 383 | 95.85 269 | 98.76 280 |
|
| UGNet | | | 95.33 236 | 94.57 247 | 97.62 205 | 98.55 177 | 94.85 239 | 98.67 390 | 99.32 26 | 95.75 107 | 96.80 223 | 96.27 361 | 72.18 427 | 99.96 76 | 94.58 265 | 99.05 152 | 98.04 306 |
| Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022 |
| PCF-MVS | | 94.20 5 | 95.18 239 | 94.10 259 | 98.43 140 | 98.55 177 | 95.99 184 | 97.91 430 | 97.31 332 | 90.35 345 | 89.48 360 | 99.22 175 | 85.19 283 | 99.89 118 | 90.40 348 | 98.47 172 | 99.41 198 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| UWE-MVS-28 | | | 95.95 206 | 96.49 152 | 94.34 356 | 98.51 182 | 89.99 395 | 99.39 292 | 98.57 107 | 93.14 220 | 97.33 199 | 98.31 290 | 93.44 116 | 94.68 466 | 93.69 291 | 95.98 263 | 98.34 298 |
|
| UWE-MVS | | | 96.79 154 | 96.72 142 | 97.00 254 | 98.51 182 | 93.70 287 | 99.71 219 | 98.60 101 | 92.96 228 | 97.09 207 | 98.34 287 | 96.67 33 | 98.85 228 | 92.11 316 | 96.50 249 | 98.44 293 |
|
| myMVS_eth3d28 | | | 97.86 88 | 97.59 100 | 98.68 110 | 98.50 184 | 97.26 121 | 99.92 103 | 98.55 119 | 93.79 188 | 98.26 162 | 98.75 246 | 95.20 58 | 99.48 186 | 98.93 92 | 96.40 252 | 99.29 224 |
|
| test_vis1_n_1920 | | | 95.44 232 | 95.31 220 | 95.82 300 | 98.50 184 | 88.74 413 | 99.98 24 | 97.30 333 | 97.84 28 | 99.85 20 | 99.19 181 | 66.82 452 | 99.97 64 | 98.82 101 | 99.46 126 | 98.76 280 |
|
| BH-w/o | | | 95.71 223 | 95.38 218 | 96.68 268 | 98.49 186 | 92.28 330 | 99.84 152 | 97.50 305 | 92.12 279 | 92.06 320 | 98.79 244 | 84.69 296 | 98.67 264 | 95.29 244 | 99.66 95 | 99.09 250 |
|
| baseline1 | | | 95.78 219 | 94.86 238 | 98.54 128 | 98.47 187 | 98.07 80 | 99.06 339 | 97.99 244 | 92.68 247 | 94.13 295 | 98.62 262 | 93.28 124 | 98.69 261 | 93.79 286 | 85.76 372 | 98.84 276 |
|
| fmvsm_s_conf0.5_n_7 | | | 97.70 108 | 97.74 89 | 97.59 210 | 98.44 188 | 95.16 230 | 99.97 42 | 98.65 88 | 97.95 24 | 99.62 62 | 99.78 67 | 86.09 263 | 99.94 94 | 99.69 50 | 99.50 119 | 97.66 316 |
|
| EPMVS | | | 96.53 176 | 96.01 176 | 98.09 162 | 98.43 189 | 96.12 182 | 96.36 463 | 99.43 20 | 93.53 197 | 97.64 188 | 95.04 415 | 94.41 83 | 98.38 299 | 91.13 329 | 98.11 186 | 99.75 118 |
|
| kuosan | | | 93.17 309 | 92.60 311 | 94.86 332 | 98.40 190 | 89.54 403 | 98.44 403 | 98.53 126 | 84.46 439 | 88.49 383 | 97.92 305 | 90.57 192 | 97.05 376 | 83.10 430 | 93.49 313 | 97.99 307 |
|
| WBMVS | | | 94.52 265 | 94.03 263 | 95.98 290 | 98.38 191 | 96.68 151 | 99.92 103 | 97.63 284 | 90.75 333 | 89.64 355 | 95.25 408 | 96.77 27 | 96.90 389 | 94.35 270 | 83.57 392 | 94.35 360 |
|
| UBG | | | 97.84 91 | 97.69 93 | 98.29 149 | 98.38 191 | 96.59 158 | 99.90 117 | 98.53 126 | 93.91 184 | 98.52 145 | 98.42 283 | 96.77 27 | 99.17 205 | 98.54 119 | 96.20 257 | 99.11 249 |
|
| sss | | | 97.57 113 | 97.03 127 | 99.18 63 | 98.37 193 | 98.04 83 | 99.73 210 | 99.38 22 | 93.46 202 | 98.76 132 | 99.06 195 | 91.21 176 | 99.89 118 | 96.33 226 | 97.01 235 | 99.62 147 |
|
| testing11 | | | 97.48 116 | 97.27 116 | 98.10 161 | 98.36 194 | 96.02 183 | 99.92 103 | 98.45 143 | 93.45 204 | 98.15 168 | 98.70 252 | 95.48 54 | 99.22 198 | 97.85 164 | 95.05 293 | 99.07 253 |
|
| BH-untuned | | | 95.18 239 | 94.83 239 | 96.22 284 | 98.36 194 | 91.22 368 | 99.80 175 | 97.32 331 | 90.91 322 | 91.08 327 | 98.67 254 | 83.51 311 | 98.54 281 | 94.23 273 | 99.61 104 | 98.92 270 |
|
| testing91 | | | 97.16 133 | 96.90 131 | 97.97 168 | 98.35 196 | 95.67 199 | 99.91 111 | 98.42 168 | 92.91 231 | 97.33 199 | 98.72 249 | 94.81 72 | 99.21 199 | 96.98 199 | 94.63 296 | 99.03 261 |
|
| testing99 | | | 97.17 132 | 96.91 130 | 97.95 170 | 98.35 196 | 95.70 196 | 99.91 111 | 98.43 156 | 92.94 229 | 97.36 197 | 98.72 249 | 94.83 71 | 99.21 199 | 97.00 197 | 94.64 295 | 98.95 266 |
|
| ET-MVSNet_ETH3D | | | 94.37 272 | 93.28 293 | 97.64 201 | 98.30 198 | 97.99 85 | 99.99 8 | 97.61 290 | 94.35 157 | 71.57 491 | 99.45 141 | 96.23 39 | 95.34 455 | 96.91 205 | 85.14 379 | 99.59 154 |
|
| AUN-MVS | | | 93.28 306 | 92.60 311 | 95.34 315 | 98.29 199 | 90.09 393 | 99.31 306 | 98.56 113 | 91.80 292 | 96.35 245 | 98.00 300 | 89.38 209 | 98.28 311 | 92.46 307 | 69.22 476 | 97.64 318 |
|
| FMVSNet3 | | | 92.69 324 | 91.58 334 | 95.99 289 | 98.29 199 | 97.42 116 | 99.26 318 | 97.62 287 | 89.80 357 | 89.68 351 | 95.32 402 | 81.62 336 | 96.27 430 | 87.01 401 | 85.65 373 | 94.29 364 |
|
| PMMVS | | | 96.76 157 | 96.76 139 | 96.76 265 | 98.28 201 | 92.10 334 | 99.91 111 | 97.98 246 | 94.12 170 | 99.53 74 | 99.39 149 | 86.93 249 | 98.73 252 | 96.95 202 | 97.73 194 | 99.45 190 |
|
| hse-mvs2 | | | 94.38 271 | 94.08 262 | 95.31 317 | 98.27 202 | 90.02 394 | 99.29 313 | 98.56 113 | 95.90 101 | 98.77 129 | 98.00 300 | 90.89 188 | 98.26 315 | 97.80 167 | 69.20 477 | 97.64 318 |
|
| PVSNet_0 | | 88.03 19 | 91.80 344 | 90.27 358 | 96.38 280 | 98.27 202 | 90.46 385 | 99.94 93 | 99.61 13 | 93.99 178 | 86.26 424 | 97.39 320 | 71.13 434 | 99.89 118 | 98.77 105 | 67.05 483 | 98.79 279 |
|
| UA-Net | | | 96.54 175 | 95.96 183 | 98.27 150 | 98.23 204 | 95.71 195 | 98.00 427 | 98.45 143 | 93.72 193 | 98.41 153 | 99.27 165 | 88.71 223 | 99.66 171 | 91.19 328 | 97.69 195 | 99.44 193 |
|
| test_cas_vis1_n_1920 | | | 96.59 171 | 96.23 165 | 97.65 200 | 98.22 205 | 94.23 269 | 99.99 8 | 97.25 347 | 97.77 29 | 99.58 70 | 99.08 191 | 77.10 384 | 99.97 64 | 97.64 176 | 99.45 127 | 98.74 282 |
|
| FE-MVS | | | 95.70 225 | 95.01 234 | 97.79 185 | 98.21 206 | 94.57 250 | 95.03 477 | 98.69 82 | 88.90 373 | 97.50 192 | 96.19 363 | 92.60 147 | 99.49 185 | 89.99 353 | 97.94 192 | 99.31 219 |
|
| GG-mvs-BLEND | | | | | 98.54 128 | 98.21 206 | 98.01 84 | 93.87 482 | 98.52 128 | | 97.92 175 | 97.92 305 | 99.02 3 | 97.94 335 | 98.17 143 | 99.58 109 | 99.67 133 |
|
| mvs_anonymous | | | 95.65 227 | 95.03 233 | 97.53 214 | 98.19 208 | 95.74 193 | 99.33 301 | 97.49 306 | 90.87 323 | 90.47 336 | 97.10 327 | 88.23 226 | 97.16 367 | 95.92 234 | 97.66 198 | 99.68 131 |
|
| MVS_Test | | | 96.46 179 | 95.74 197 | 98.61 117 | 98.18 209 | 97.23 123 | 99.31 306 | 97.15 365 | 91.07 319 | 98.84 123 | 97.05 331 | 88.17 227 | 98.97 217 | 94.39 267 | 97.50 200 | 99.61 151 |
|
| BH-RMVSNet | | | 95.18 239 | 94.31 254 | 97.80 183 | 98.17 210 | 95.23 225 | 99.76 193 | 97.53 301 | 92.52 262 | 94.27 293 | 99.25 172 | 76.84 391 | 98.80 241 | 90.89 337 | 99.54 111 | 99.35 209 |
|
| dongtai | | | 91.55 350 | 91.13 343 | 92.82 408 | 98.16 211 | 86.35 437 | 99.47 279 | 98.51 131 | 83.24 447 | 85.07 435 | 97.56 314 | 90.33 197 | 94.94 461 | 76.09 473 | 91.73 321 | 97.18 329 |
|
| RPSCF | | | 91.80 344 | 92.79 307 | 88.83 451 | 98.15 212 | 69.87 495 | 98.11 423 | 96.60 432 | 83.93 442 | 94.33 291 | 99.27 165 | 79.60 362 | 99.46 189 | 91.99 317 | 93.16 318 | 97.18 329 |
|
| ETV-MVS | | | 97.92 84 | 97.80 88 | 98.25 151 | 98.14 213 | 96.48 160 | 99.98 24 | 97.63 284 | 95.61 111 | 99.29 98 | 99.46 140 | 92.55 149 | 98.82 232 | 99.02 89 | 98.54 170 | 99.46 185 |
|
| IS-MVSNet | | | 96.29 192 | 95.90 190 | 97.45 224 | 98.13 214 | 94.80 243 | 99.08 334 | 97.61 290 | 92.02 284 | 95.54 270 | 98.96 214 | 90.64 191 | 98.08 324 | 93.73 289 | 97.41 204 | 99.47 183 |
|
| test_fmvsmconf_n | | | 98.43 51 | 98.32 47 | 98.78 103 | 98.12 215 | 96.41 163 | 99.99 8 | 98.83 66 | 98.22 7 | 99.67 53 | 99.64 119 | 91.11 181 | 99.94 94 | 99.67 52 | 99.62 99 | 99.98 57 |
|
| fmvsm_s_conf0.1_n_2 | | | 97.25 128 | 96.85 134 | 98.43 140 | 98.08 216 | 98.08 79 | 99.92 103 | 97.76 274 | 98.05 20 | 99.65 55 | 99.58 128 | 80.88 346 | 99.93 104 | 99.59 56 | 98.17 181 | 97.29 327 |
|
| ab-mvs | | | 94.69 257 | 93.42 284 | 98.51 133 | 98.07 217 | 96.26 170 | 96.49 461 | 98.68 84 | 90.31 347 | 94.54 283 | 97.00 334 | 76.30 399 | 99.71 160 | 95.98 233 | 93.38 316 | 99.56 163 |
|
| XVG-OURS-SEG-HR | | | 94.79 252 | 94.70 246 | 95.08 322 | 98.05 218 | 89.19 405 | 99.08 334 | 97.54 299 | 93.66 194 | 94.87 279 | 99.58 128 | 78.78 370 | 99.79 145 | 97.31 184 | 93.40 315 | 96.25 336 |
|
| EIA-MVS | | | 97.53 114 | 97.46 104 | 97.76 191 | 98.04 219 | 94.84 240 | 99.98 24 | 97.61 290 | 94.41 155 | 97.90 176 | 99.59 125 | 92.40 155 | 98.87 225 | 98.04 152 | 99.13 146 | 99.59 154 |
|
| XVG-OURS | | | 94.82 249 | 94.74 245 | 95.06 323 | 98.00 220 | 89.19 405 | 99.08 334 | 97.55 297 | 94.10 171 | 94.71 281 | 99.62 123 | 80.51 353 | 99.74 156 | 96.04 232 | 93.06 320 | 96.25 336 |
|
| mvsmamba | | | 96.94 146 | 96.73 141 | 97.55 212 | 97.99 221 | 94.37 263 | 99.62 243 | 97.70 277 | 93.13 221 | 98.42 152 | 97.92 305 | 88.02 228 | 98.75 250 | 98.78 104 | 99.01 153 | 99.52 173 |
|
| dp | | | 95.05 243 | 94.43 249 | 96.91 258 | 97.99 221 | 92.73 319 | 96.29 466 | 97.98 246 | 89.70 358 | 95.93 258 | 94.67 430 | 93.83 110 | 98.45 287 | 86.91 404 | 96.53 248 | 99.54 168 |
|
| tpmrst | | | 96.27 194 | 95.98 179 | 97.13 249 | 97.96 223 | 93.15 307 | 96.34 464 | 98.17 222 | 92.07 280 | 98.71 135 | 95.12 412 | 93.91 105 | 98.73 252 | 94.91 255 | 96.62 246 | 99.50 179 |
|
| TR-MVS | | | 94.54 262 | 93.56 279 | 97.49 222 | 97.96 223 | 94.34 265 | 98.71 385 | 97.51 304 | 90.30 348 | 94.51 285 | 98.69 253 | 75.56 405 | 98.77 246 | 92.82 305 | 95.99 262 | 99.35 209 |
|
| Vis-MVSNet (Re-imp) | | | 96.32 189 | 95.98 179 | 97.35 239 | 97.93 225 | 94.82 242 | 99.47 279 | 98.15 230 | 91.83 289 | 95.09 277 | 99.11 189 | 91.37 175 | 97.47 351 | 93.47 293 | 97.43 201 | 99.74 119 |
|
| MDTV_nov1_ep13 | | | | 95.69 199 | | 97.90 226 | 94.15 273 | 95.98 472 | 98.44 148 | 93.12 222 | 97.98 173 | 95.74 376 | 95.10 61 | 98.58 274 | 90.02 352 | 96.92 237 | |
|
| Fast-Effi-MVS+ | | | 95.02 245 | 94.19 257 | 97.52 216 | 97.88 227 | 94.55 251 | 99.97 42 | 97.08 383 | 88.85 375 | 94.47 286 | 97.96 304 | 84.59 298 | 98.41 291 | 89.84 355 | 97.10 225 | 99.59 154 |
|
| ADS-MVSNet2 | | | 93.80 293 | 93.88 269 | 93.55 391 | 97.87 228 | 85.94 441 | 94.24 478 | 96.84 418 | 90.07 351 | 96.43 241 | 94.48 435 | 90.29 199 | 95.37 454 | 87.44 390 | 97.23 212 | 99.36 205 |
|
| ADS-MVSNet | | | 94.79 252 | 94.02 264 | 97.11 251 | 97.87 228 | 93.79 283 | 94.24 478 | 98.16 227 | 90.07 351 | 96.43 241 | 94.48 435 | 90.29 199 | 98.19 318 | 87.44 390 | 97.23 212 | 99.36 205 |
|
| Effi-MVS+ | | | 96.30 191 | 95.69 199 | 98.16 155 | 97.85 230 | 96.26 170 | 97.41 440 | 97.21 355 | 90.37 344 | 98.65 139 | 98.58 268 | 86.61 255 | 98.70 259 | 97.11 193 | 97.37 206 | 99.52 173 |
|
| PatchmatchNet |  | | 95.94 207 | 95.45 208 | 97.39 234 | 97.83 231 | 94.41 259 | 96.05 470 | 98.40 177 | 92.86 233 | 97.09 207 | 95.28 407 | 94.21 97 | 98.07 326 | 89.26 364 | 98.11 186 | 99.70 125 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| cascas | | | 94.64 260 | 93.61 274 | 97.74 193 | 97.82 232 | 96.26 170 | 99.96 56 | 97.78 270 | 85.76 423 | 94.00 296 | 97.54 315 | 76.95 390 | 99.21 199 | 97.23 189 | 95.43 286 | 97.76 315 |
|
| 1112_ss | | | 96.01 204 | 95.20 225 | 98.42 142 | 97.80 233 | 96.41 163 | 99.65 236 | 96.66 429 | 92.71 244 | 92.88 310 | 99.40 147 | 92.16 163 | 99.30 194 | 91.92 319 | 93.66 311 | 99.55 164 |
|
| E3new | | | 96.75 159 | 96.43 157 | 97.71 194 | 97.79 234 | 94.83 241 | 99.80 175 | 97.33 325 | 93.52 200 | 97.49 193 | 99.31 157 | 87.73 231 | 98.83 229 | 97.52 179 | 97.40 205 | 99.48 182 |
|
| Test_1112_low_res | | | 95.72 221 | 94.83 239 | 98.42 142 | 97.79 234 | 96.41 163 | 99.65 236 | 96.65 430 | 92.70 245 | 92.86 311 | 96.13 367 | 92.15 164 | 99.30 194 | 91.88 320 | 93.64 312 | 99.55 164 |
|
| Effi-MVS+-dtu | | | 94.53 264 | 95.30 221 | 92.22 416 | 97.77 236 | 82.54 464 | 99.59 252 | 97.06 392 | 94.92 128 | 95.29 274 | 95.37 400 | 85.81 267 | 97.89 336 | 94.80 258 | 97.07 226 | 96.23 338 |
|
| tpm cat1 | | | 93.51 302 | 92.52 317 | 96.47 273 | 97.77 236 | 91.47 366 | 96.13 468 | 98.06 237 | 80.98 462 | 92.91 309 | 93.78 446 | 89.66 204 | 98.87 225 | 87.03 400 | 96.39 253 | 99.09 250 |
|
| FA-MVS(test-final) | | | 95.86 210 | 95.09 230 | 98.15 158 | 97.74 238 | 95.62 201 | 96.31 465 | 98.17 222 | 91.42 307 | 96.26 246 | 96.13 367 | 90.56 193 | 99.47 188 | 92.18 311 | 97.07 226 | 99.35 209 |
|
| xiu_mvs_v1_base_debu | | | 97.43 117 | 97.06 123 | 98.55 124 | 97.74 238 | 98.14 74 | 99.31 306 | 97.86 260 | 96.43 83 | 99.62 62 | 99.69 105 | 85.56 275 | 99.68 165 | 99.05 82 | 98.31 176 | 97.83 311 |
|
| xiu_mvs_v1_base | | | 97.43 117 | 97.06 123 | 98.55 124 | 97.74 238 | 98.14 74 | 99.31 306 | 97.86 260 | 96.43 83 | 99.62 62 | 99.69 105 | 85.56 275 | 99.68 165 | 99.05 82 | 98.31 176 | 97.83 311 |
|
| xiu_mvs_v1_base_debi | | | 97.43 117 | 97.06 123 | 98.55 124 | 97.74 238 | 98.14 74 | 99.31 306 | 97.86 260 | 96.43 83 | 99.62 62 | 99.69 105 | 85.56 275 | 99.68 165 | 99.05 82 | 98.31 176 | 97.83 311 |
|
| EPP-MVSNet | | | 96.69 165 | 96.60 147 | 96.96 256 | 97.74 238 | 93.05 310 | 99.37 296 | 98.56 113 | 88.75 377 | 95.83 261 | 99.01 201 | 96.01 40 | 98.56 277 | 96.92 203 | 97.20 214 | 99.25 233 |
|
| gg-mvs-nofinetune | | | 93.51 302 | 91.86 329 | 98.47 135 | 97.72 243 | 97.96 89 | 92.62 493 | 98.51 131 | 74.70 486 | 97.33 199 | 69.59 520 | 98.91 4 | 97.79 339 | 97.77 172 | 99.56 110 | 99.67 133 |
|
| IB-MVS | | 92.85 6 | 94.99 246 | 93.94 267 | 98.16 155 | 97.72 243 | 95.69 198 | 99.99 8 | 98.81 67 | 94.28 163 | 92.70 312 | 96.90 338 | 95.08 62 | 99.17 205 | 96.07 231 | 73.88 457 | 99.60 153 |
| Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
| thisisatest0515 | | | 97.41 122 | 97.02 128 | 98.59 121 | 97.71 245 | 97.52 109 | 99.97 42 | 98.54 123 | 91.83 289 | 97.45 194 | 99.04 197 | 97.50 10 | 99.10 209 | 94.75 260 | 96.37 254 | 99.16 242 |
|
| VortexMVS | | | 94.11 280 | 93.50 281 | 95.94 292 | 97.70 246 | 96.61 155 | 99.35 299 | 97.18 358 | 93.52 200 | 89.57 358 | 95.74 376 | 87.55 236 | 96.97 384 | 95.76 239 | 85.13 380 | 94.23 369 |
|
| viewdifsd2359ckpt09 | | | 96.21 197 | 95.77 195 | 97.53 214 | 97.69 247 | 94.50 254 | 99.78 181 | 97.23 352 | 92.88 232 | 96.58 229 | 99.26 169 | 84.85 289 | 98.66 267 | 96.61 217 | 97.02 233 | 99.43 194 |
|
| Syy-MVS | | | 90.00 385 | 90.63 350 | 88.11 460 | 97.68 248 | 74.66 491 | 99.71 219 | 98.35 190 | 90.79 330 | 92.10 318 | 98.67 254 | 79.10 368 | 93.09 482 | 63.35 500 | 95.95 266 | 96.59 334 |
|
| myMVS_eth3d | | | 94.46 269 | 94.76 244 | 93.55 391 | 97.68 248 | 90.97 370 | 99.71 219 | 98.35 190 | 90.79 330 | 92.10 318 | 98.67 254 | 92.46 154 | 93.09 482 | 87.13 397 | 95.95 266 | 96.59 334 |
|
| test_fmvs1_n | | | 94.25 277 | 94.36 251 | 93.92 378 | 97.68 248 | 83.70 454 | 99.90 117 | 96.57 433 | 97.40 40 | 99.67 53 | 98.88 227 | 61.82 471 | 99.92 110 | 98.23 141 | 99.13 146 | 98.14 304 |
|
| fmvsm_s_conf0.5_n_6 | | | 98.27 63 | 97.96 75 | 99.23 58 | 97.66 251 | 98.11 78 | 99.98 24 | 98.64 91 | 97.85 27 | 99.87 14 | 99.72 95 | 88.86 220 | 99.93 104 | 99.64 54 | 99.36 135 | 99.63 146 |
|
| RRT-MVS | | | 96.24 196 | 95.68 201 | 97.94 173 | 97.65 252 | 94.92 238 | 99.27 316 | 97.10 379 | 92.79 239 | 97.43 195 | 97.99 302 | 81.85 331 | 99.37 192 | 98.46 125 | 98.57 167 | 99.53 172 |
|
| diffmvs |  | | 97.00 143 | 96.64 145 | 98.09 162 | 97.64 253 | 96.17 179 | 99.81 169 | 97.19 356 | 94.67 140 | 98.95 118 | 99.28 161 | 86.43 256 | 98.76 248 | 98.37 131 | 97.42 203 | 99.33 212 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| viewcassd2359sk11 | | | 96.59 171 | 96.23 165 | 97.66 199 | 97.63 254 | 94.70 246 | 99.77 187 | 97.33 325 | 93.41 205 | 97.34 198 | 99.17 183 | 86.72 250 | 98.83 229 | 97.40 182 | 97.32 209 | 99.46 185 |
|
| viewdifsd2359ckpt13 | | | 96.19 198 | 95.77 195 | 97.45 224 | 97.62 255 | 94.40 261 | 99.70 226 | 97.23 352 | 92.76 241 | 96.63 226 | 99.05 196 | 84.96 288 | 98.64 270 | 96.65 216 | 97.35 207 | 99.31 219 |
|
| Vis-MVSNet |  | | 95.72 221 | 95.15 228 | 97.45 224 | 97.62 255 | 94.28 266 | 99.28 314 | 98.24 210 | 94.27 165 | 96.84 219 | 98.94 221 | 79.39 363 | 98.76 248 | 93.25 296 | 98.49 171 | 99.30 222 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| thisisatest0530 | | | 97.10 136 | 96.72 142 | 98.22 152 | 97.60 257 | 96.70 148 | 99.92 103 | 98.54 123 | 91.11 317 | 97.07 209 | 98.97 212 | 97.47 13 | 99.03 212 | 93.73 289 | 96.09 260 | 98.92 270 |
|
| GDP-MVS | | | 97.88 86 | 97.59 100 | 98.75 106 | 97.59 258 | 97.81 96 | 99.95 75 | 97.37 319 | 94.44 151 | 99.08 110 | 99.58 128 | 97.13 25 | 99.08 210 | 94.99 250 | 98.17 181 | 99.37 203 |
|
| miper_ehance_all_eth | | | 93.16 310 | 92.60 311 | 94.82 333 | 97.57 259 | 93.56 296 | 99.50 273 | 97.07 391 | 88.75 377 | 88.85 375 | 95.52 389 | 90.97 184 | 96.74 400 | 90.77 339 | 84.45 385 | 94.17 377 |
|
| guyue | | | 97.15 134 | 96.82 136 | 98.15 158 | 97.56 260 | 96.25 174 | 99.71 219 | 97.84 263 | 95.75 107 | 98.13 169 | 98.65 257 | 87.58 235 | 98.82 232 | 98.29 137 | 97.91 193 | 99.36 205 |
|
| viewmanbaseed2359cas | | | 96.45 180 | 96.07 173 | 97.59 210 | 97.55 261 | 94.59 249 | 99.70 226 | 97.33 325 | 93.62 196 | 97.00 213 | 99.32 154 | 85.57 274 | 98.71 256 | 97.26 188 | 97.33 208 | 99.47 183 |
|
| testing3 | | | 93.92 286 | 94.23 256 | 92.99 405 | 97.54 262 | 90.23 389 | 99.99 8 | 99.16 33 | 90.57 337 | 91.33 326 | 98.63 261 | 92.99 132 | 92.52 486 | 82.46 435 | 95.39 287 | 96.22 339 |
|
| SSM_0404 | | | 95.75 220 | 95.16 227 | 97.50 219 | 97.53 263 | 95.39 212 | 99.11 330 | 97.25 347 | 90.81 326 | 95.27 275 | 98.83 241 | 84.74 293 | 98.67 264 | 95.24 245 | 97.69 195 | 98.45 292 |
|
| LCM-MVSNet-Re | | | 92.31 333 | 92.60 311 | 91.43 425 | 97.53 263 | 79.27 482 | 99.02 348 | 91.83 500 | 92.07 280 | 80.31 461 | 94.38 439 | 83.50 312 | 95.48 451 | 97.22 190 | 97.58 199 | 99.54 168 |
|
| GBi-Net | | | 90.88 361 | 89.82 367 | 94.08 369 | 97.53 263 | 91.97 335 | 98.43 404 | 96.95 406 | 87.05 405 | 89.68 351 | 94.72 426 | 71.34 431 | 96.11 436 | 87.01 401 | 85.65 373 | 94.17 377 |
|
| test1 | | | 90.88 361 | 89.82 367 | 94.08 369 | 97.53 263 | 91.97 335 | 98.43 404 | 96.95 406 | 87.05 405 | 89.68 351 | 94.72 426 | 71.34 431 | 96.11 436 | 87.01 401 | 85.65 373 | 94.17 377 |
|
| FMVSNet2 | | | 91.02 358 | 89.56 372 | 95.41 313 | 97.53 263 | 95.74 193 | 98.98 351 | 97.41 314 | 87.05 405 | 88.43 388 | 95.00 420 | 71.34 431 | 96.24 432 | 85.12 416 | 85.21 378 | 94.25 367 |
|
| tttt0517 | | | 96.85 151 | 96.49 152 | 97.92 174 | 97.48 268 | 95.89 187 | 99.85 147 | 98.54 123 | 90.72 334 | 96.63 226 | 98.93 224 | 97.47 13 | 99.02 213 | 93.03 303 | 95.76 273 | 98.85 275 |
|
| onestephybrid01 | | | 96.75 159 | 96.44 156 | 97.71 194 | 97.47 269 | 95.03 233 | 99.83 160 | 97.27 343 | 94.15 168 | 98.66 137 | 99.25 172 | 85.72 269 | 98.81 236 | 98.42 127 | 97.17 220 | 99.28 226 |
|
| cashybrid2 | | | 96.25 195 | 95.89 191 | 97.32 242 | 97.45 270 | 93.68 289 | 99.80 175 | 97.22 354 | 93.38 206 | 96.86 217 | 99.28 161 | 84.64 297 | 98.87 225 | 97.18 191 | 97.19 215 | 99.41 198 |
|
| BP-MVS1 | | | 98.33 59 | 98.18 56 | 98.81 101 | 97.44 271 | 97.98 86 | 99.96 56 | 98.17 222 | 94.88 130 | 98.77 129 | 99.59 125 | 97.59 8 | 99.08 210 | 98.24 140 | 98.93 155 | 99.36 205 |
|
| casdiffmvs_mvg |  | | 96.43 181 | 95.94 187 | 97.89 178 | 97.44 271 | 95.47 205 | 99.86 144 | 97.29 341 | 93.35 208 | 96.03 254 | 99.19 181 | 85.39 279 | 98.72 255 | 97.89 163 | 97.04 230 | 99.49 181 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| E2 | | | 96.36 186 | 95.95 185 | 97.60 207 | 97.41 273 | 94.52 252 | 99.71 219 | 97.33 325 | 93.20 214 | 97.02 210 | 99.07 193 | 85.37 280 | 98.82 232 | 97.27 185 | 97.14 222 | 99.46 185 |
|
| EC-MVSNet | | | 97.38 124 | 97.24 117 | 97.80 183 | 97.41 273 | 95.64 200 | 99.99 8 | 97.06 392 | 94.59 141 | 99.63 59 | 99.32 154 | 89.20 215 | 98.14 320 | 98.76 106 | 99.23 142 | 99.62 147 |
|
| viewdifsd2359ckpt07 | | | 95.83 213 | 95.42 210 | 97.07 252 | 97.40 275 | 93.04 311 | 99.60 250 | 97.24 350 | 92.39 268 | 96.09 253 | 99.14 188 | 83.07 322 | 98.93 221 | 97.02 196 | 96.87 238 | 99.23 236 |
|
| c3_l | | | 92.53 328 | 91.87 328 | 94.52 345 | 97.40 275 | 92.99 313 | 99.40 288 | 96.93 411 | 87.86 395 | 88.69 378 | 95.44 394 | 89.95 202 | 96.44 418 | 90.45 345 | 80.69 419 | 94.14 387 |
|
| hybrid | | | 96.53 176 | 96.15 171 | 97.67 197 | 97.39 277 | 95.12 231 | 99.80 175 | 97.15 365 | 93.38 206 | 98.23 165 | 99.16 186 | 85.20 282 | 98.70 259 | 97.92 159 | 97.15 221 | 99.20 239 |
|
| viewmambaseed2359dif | | | 95.92 209 | 95.55 206 | 97.04 253 | 97.38 278 | 93.41 301 | 99.78 181 | 96.97 404 | 91.14 316 | 96.58 229 | 99.27 165 | 84.85 289 | 98.75 250 | 96.87 206 | 97.12 224 | 98.97 265 |
|
| fmvsm_s_conf0.1_n | | | 97.30 125 | 97.21 119 | 97.60 207 | 97.38 278 | 94.40 261 | 99.90 117 | 98.64 91 | 96.47 82 | 99.51 78 | 99.65 118 | 84.99 287 | 99.93 104 | 99.22 76 | 99.09 149 | 98.46 291 |
|
| hybridcas | | | 96.09 201 | 95.62 203 | 97.50 219 | 97.37 280 | 94.44 255 | 99.84 152 | 97.16 362 | 93.16 218 | 96.03 254 | 99.21 178 | 84.19 304 | 98.65 269 | 96.53 221 | 97.07 226 | 99.42 197 |
|
| E3 | | | 96.36 186 | 95.95 185 | 97.60 207 | 97.37 280 | 94.52 252 | 99.71 219 | 97.33 325 | 93.18 216 | 97.02 210 | 99.07 193 | 85.45 278 | 98.82 232 | 97.27 185 | 97.14 222 | 99.46 185 |
|
| CDS-MVSNet | | | 96.34 188 | 96.07 173 | 97.13 249 | 97.37 280 | 94.96 235 | 99.53 268 | 97.91 255 | 91.55 299 | 95.37 273 | 98.32 288 | 95.05 64 | 97.13 370 | 93.80 285 | 95.75 274 | 99.30 222 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| hybridnocas07 | | | 96.57 173 | 96.16 170 | 97.81 182 | 97.36 283 | 95.32 217 | 99.81 169 | 97.12 371 | 94.17 167 | 98.02 172 | 98.90 225 | 85.05 285 | 98.80 241 | 97.85 164 | 97.18 216 | 99.32 214 |
|
| TESTMET0.1,1 | | | 96.74 162 | 96.26 164 | 98.16 155 | 97.36 283 | 96.48 160 | 99.96 56 | 98.29 203 | 91.93 285 | 95.77 262 | 98.07 298 | 95.54 50 | 98.29 309 | 90.55 343 | 98.89 156 | 99.70 125 |
|
| miper_lstm_enhance | | | 91.81 341 | 91.39 340 | 93.06 404 | 97.34 285 | 89.18 407 | 99.38 294 | 96.79 423 | 86.70 413 | 87.47 406 | 95.22 409 | 90.00 201 | 95.86 445 | 88.26 379 | 81.37 408 | 94.15 383 |
|
| baseline | | | 96.43 181 | 95.98 179 | 97.76 191 | 97.34 285 | 95.17 229 | 99.51 271 | 97.17 360 | 93.92 183 | 96.90 216 | 99.28 161 | 85.37 280 | 98.64 270 | 97.50 180 | 96.86 240 | 99.46 185 |
|
| cl____ | | | 92.31 333 | 91.58 334 | 94.52 345 | 97.33 287 | 92.77 315 | 99.57 258 | 96.78 424 | 86.97 409 | 87.56 404 | 95.51 390 | 89.43 208 | 96.62 407 | 88.60 369 | 82.44 400 | 94.16 382 |
|
| SD_0403 | | | 92.63 327 | 93.38 288 | 90.40 439 | 97.32 288 | 77.91 484 | 97.75 435 | 98.03 242 | 91.89 286 | 90.83 332 | 98.29 292 | 82.00 328 | 93.79 475 | 88.51 374 | 95.75 274 | 99.52 173 |
|
| DIV-MVS_self_test | | | 92.32 332 | 91.60 333 | 94.47 349 | 97.31 289 | 92.74 317 | 99.58 254 | 96.75 425 | 86.99 408 | 87.64 402 | 95.54 387 | 89.55 207 | 96.50 413 | 88.58 370 | 82.44 400 | 94.17 377 |
|
| casdiffmvs |  | | 96.42 183 | 95.97 182 | 97.77 189 | 97.30 290 | 94.98 234 | 99.84 152 | 97.09 382 | 93.75 192 | 96.58 229 | 99.26 169 | 85.07 284 | 98.78 245 | 97.77 172 | 97.04 230 | 99.54 168 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| GeoE | | | 94.36 274 | 93.48 282 | 96.99 255 | 97.29 291 | 93.54 297 | 99.96 56 | 96.72 427 | 88.35 388 | 93.43 300 | 98.94 221 | 82.05 327 | 98.05 327 | 88.12 385 | 96.48 251 | 99.37 203 |
|
| eth_miper_zixun_eth | | | 92.41 331 | 91.93 326 | 93.84 382 | 97.28 292 | 90.68 379 | 98.83 374 | 96.97 404 | 88.57 382 | 89.19 370 | 95.73 379 | 89.24 214 | 96.69 405 | 89.97 354 | 81.55 406 | 94.15 383 |
|
| MVSFormer | | | 96.94 146 | 96.60 147 | 97.95 170 | 97.28 292 | 97.70 102 | 99.55 265 | 97.27 343 | 91.17 313 | 99.43 84 | 99.54 134 | 90.92 185 | 96.89 390 | 94.67 263 | 99.62 99 | 99.25 233 |
|
| lupinMVS | | | 97.85 90 | 97.60 98 | 98.62 116 | 97.28 292 | 97.70 102 | 99.99 8 | 97.55 297 | 95.50 116 | 99.43 84 | 99.67 114 | 90.92 185 | 98.71 256 | 98.40 128 | 99.62 99 | 99.45 190 |
|
| nocashy02 | | | 96.61 169 | 96.34 161 | 97.42 229 | 97.26 295 | 94.37 263 | 99.83 160 | 97.16 362 | 94.51 144 | 97.89 178 | 99.26 169 | 86.38 257 | 98.66 267 | 97.70 175 | 97.06 229 | 99.23 236 |
|
| dtuplus | | | 95.79 218 | 95.42 210 | 96.93 257 | 97.24 296 | 93.16 306 | 99.78 181 | 96.93 411 | 91.69 295 | 96.18 251 | 99.29 160 | 83.80 309 | 98.73 252 | 96.83 208 | 97.02 233 | 98.89 274 |
|
| diffmvs_AUTHOR | | | 96.75 159 | 96.41 159 | 97.79 185 | 97.20 297 | 95.46 206 | 99.69 229 | 97.15 365 | 94.46 147 | 98.78 127 | 99.21 178 | 85.64 272 | 98.77 246 | 98.27 138 | 97.31 210 | 99.13 246 |
|
| mamba_0408 | | | 94.98 247 | 94.09 260 | 97.64 201 | 97.14 298 | 95.31 218 | 93.48 488 | 97.08 383 | 90.48 340 | 94.40 287 | 98.62 262 | 84.49 299 | 98.67 264 | 93.99 276 | 97.18 216 | 98.93 267 |
|
| SSM_04072 | | | 94.77 254 | 94.09 260 | 96.82 262 | 97.14 298 | 95.31 218 | 93.48 488 | 97.08 383 | 90.48 340 | 94.40 287 | 98.62 262 | 84.49 299 | 96.21 433 | 93.99 276 | 97.18 216 | 98.93 267 |
|
| SSM_0407 | | | 95.62 228 | 94.95 236 | 97.61 206 | 97.14 298 | 95.31 218 | 99.00 349 | 97.25 347 | 90.81 326 | 94.40 287 | 98.83 241 | 84.74 293 | 98.58 274 | 95.24 245 | 97.18 216 | 98.93 267 |
|
| SCA | | | 94.69 257 | 93.81 271 | 97.33 240 | 97.10 301 | 94.44 255 | 98.86 371 | 98.32 197 | 93.30 211 | 96.17 252 | 95.59 385 | 76.48 397 | 97.95 333 | 91.06 331 | 97.43 201 | 99.59 154 |
|
| viewmacassd2359aftdt | | | 95.93 208 | 95.45 208 | 97.36 237 | 97.09 302 | 94.12 275 | 99.57 258 | 97.26 346 | 93.05 226 | 96.50 233 | 99.17 183 | 82.76 323 | 98.68 262 | 96.61 217 | 97.04 230 | 99.28 226 |
|
| KinetiMVS | | | 96.10 199 | 95.29 222 | 98.53 130 | 97.08 303 | 97.12 129 | 99.56 262 | 98.12 233 | 94.78 133 | 98.44 150 | 98.94 221 | 80.30 357 | 99.39 191 | 91.56 324 | 98.79 162 | 99.06 254 |
|
| TAMVS | | | 95.85 211 | 95.58 204 | 96.65 270 | 97.07 304 | 93.50 298 | 99.17 325 | 97.82 265 | 91.39 309 | 95.02 278 | 98.01 299 | 92.20 162 | 97.30 360 | 93.75 288 | 95.83 270 | 99.14 245 |
|
| Fast-Effi-MVS+-dtu | | | 93.72 297 | 93.86 270 | 93.29 396 | 97.06 305 | 86.16 438 | 99.80 175 | 96.83 419 | 92.66 248 | 92.58 313 | 97.83 311 | 81.39 337 | 97.67 344 | 89.75 356 | 96.87 238 | 96.05 341 |
|
| E4 | | | 96.01 204 | 95.53 207 | 97.44 227 | 97.05 306 | 94.23 269 | 99.57 258 | 97.30 333 | 92.72 242 | 96.47 235 | 99.03 198 | 83.98 308 | 98.83 229 | 96.92 203 | 96.77 241 | 99.27 229 |
|
| E5new | | | 95.83 213 | 95.39 213 | 97.15 245 | 97.03 307 | 93.59 291 | 99.32 304 | 97.30 333 | 92.58 255 | 96.45 236 | 99.00 205 | 83.37 315 | 98.81 236 | 96.81 209 | 96.65 244 | 99.04 257 |
|
| E5 | | | 95.83 213 | 95.39 213 | 97.15 245 | 97.03 307 | 93.59 291 | 99.32 304 | 97.30 333 | 92.58 255 | 96.45 236 | 99.00 205 | 83.37 315 | 98.81 236 | 96.81 209 | 96.65 244 | 99.04 257 |
|
| CostFormer | | | 96.10 199 | 95.88 192 | 96.78 264 | 97.03 307 | 92.55 325 | 97.08 449 | 97.83 264 | 90.04 353 | 98.72 134 | 94.89 424 | 95.01 66 | 98.29 309 | 96.54 220 | 95.77 272 | 99.50 179 |
|
| test_fmvsmvis_n_1920 | | | 97.67 109 | 97.59 100 | 97.91 176 | 97.02 310 | 95.34 215 | 99.95 75 | 98.45 143 | 97.87 26 | 97.02 210 | 99.59 125 | 89.64 205 | 99.98 51 | 99.41 68 | 99.34 137 | 98.42 294 |
|
| test-LLR | | | 96.47 178 | 96.04 175 | 97.78 187 | 97.02 310 | 95.44 207 | 99.96 56 | 98.21 217 | 94.07 173 | 95.55 268 | 96.38 356 | 93.90 106 | 98.27 313 | 90.42 346 | 98.83 160 | 99.64 139 |
|
| test-mter | | | 96.39 184 | 95.93 188 | 97.78 187 | 97.02 310 | 95.44 207 | 99.96 56 | 98.21 217 | 91.81 291 | 95.55 268 | 96.38 356 | 95.17 59 | 98.27 313 | 90.42 346 | 98.83 160 | 99.64 139 |
|
| casdiffseed414692147 | | | 95.07 242 | 94.26 255 | 97.50 219 | 97.01 313 | 94.70 246 | 99.58 254 | 97.02 396 | 91.27 311 | 94.66 282 | 98.82 243 | 80.79 348 | 98.55 280 | 93.39 295 | 95.79 271 | 99.27 229 |
|
| E6new | | | 95.83 213 | 95.39 213 | 97.14 247 | 97.00 314 | 93.58 293 | 99.31 306 | 97.30 333 | 92.57 257 | 96.45 236 | 99.01 201 | 83.44 313 | 98.81 236 | 96.80 211 | 96.66 242 | 99.04 257 |
|
| E6 | | | 95.83 213 | 95.39 213 | 97.14 247 | 97.00 314 | 93.58 293 | 99.31 306 | 97.30 333 | 92.57 257 | 96.45 236 | 99.01 201 | 83.44 313 | 98.81 236 | 96.80 211 | 96.66 242 | 99.04 257 |
|
| icg_test_0407_2 | | | 95.04 244 | 94.78 243 | 95.84 299 | 96.97 316 | 91.64 357 | 98.63 393 | 97.12 371 | 92.33 271 | 95.60 266 | 98.88 227 | 85.65 270 | 96.56 410 | 92.12 312 | 95.70 277 | 99.32 214 |
|
| IMVS_0407 | | | 95.21 238 | 94.80 242 | 96.46 275 | 96.97 316 | 91.64 357 | 98.81 376 | 97.12 371 | 92.33 271 | 95.60 266 | 98.88 227 | 85.65 270 | 98.42 289 | 92.12 312 | 95.70 277 | 99.32 214 |
|
| IMVS_0404 | | | 93.83 289 | 93.17 295 | 95.80 301 | 96.97 316 | 91.64 357 | 97.78 434 | 97.12 371 | 92.33 271 | 90.87 331 | 98.88 227 | 76.78 392 | 96.43 419 | 92.12 312 | 95.70 277 | 99.32 214 |
|
| IMVS_0403 | | | 95.25 237 | 94.81 241 | 96.58 272 | 96.97 316 | 91.64 357 | 98.97 356 | 97.12 371 | 92.33 271 | 95.43 271 | 98.88 227 | 85.78 268 | 98.79 243 | 92.12 312 | 95.70 277 | 99.32 214 |
|
| gm-plane-assit | | | | | | 96.97 316 | 93.76 285 | | | 91.47 303 | | 98.96 214 | | 98.79 243 | 94.92 253 | | |
|
| WB-MVSnew | | | 92.90 316 | 92.77 308 | 93.26 398 | 96.95 321 | 93.63 290 | 99.71 219 | 98.16 227 | 91.49 300 | 94.28 292 | 98.14 295 | 81.33 339 | 96.48 416 | 79.47 454 | 95.46 284 | 89.68 484 |
|
| QAPM | | | 95.40 233 | 94.17 258 | 99.10 79 | 96.92 322 | 97.71 100 | 99.40 288 | 98.68 84 | 89.31 361 | 88.94 374 | 98.89 226 | 82.48 325 | 99.96 76 | 93.12 302 | 99.83 80 | 99.62 147 |
|
| KD-MVS_2432*1600 | | | 88.00 407 | 86.10 411 | 93.70 387 | 96.91 323 | 94.04 276 | 97.17 446 | 97.12 371 | 84.93 434 | 81.96 450 | 92.41 462 | 92.48 152 | 94.51 468 | 79.23 456 | 52.68 514 | 92.56 448 |
|
| miper_refine_blended | | | 88.00 407 | 86.10 411 | 93.70 387 | 96.91 323 | 94.04 276 | 97.17 446 | 97.12 371 | 84.93 434 | 81.96 450 | 92.41 462 | 92.48 152 | 94.51 468 | 79.23 456 | 52.68 514 | 92.56 448 |
|
| tpm2 | | | 95.47 231 | 95.18 226 | 96.35 281 | 96.91 323 | 91.70 354 | 96.96 452 | 97.93 251 | 88.04 393 | 98.44 150 | 95.40 396 | 93.32 121 | 97.97 330 | 94.00 275 | 95.61 282 | 99.38 201 |
|
| FMVSNet5 | | | 88.32 403 | 87.47 405 | 90.88 428 | 96.90 326 | 88.39 421 | 97.28 443 | 95.68 455 | 82.60 455 | 84.67 437 | 92.40 464 | 79.83 360 | 91.16 492 | 76.39 472 | 81.51 407 | 93.09 439 |
|
| 3Dnovator+ | | 91.53 11 | 96.31 190 | 95.24 223 | 99.52 33 | 96.88 327 | 98.64 59 | 99.72 214 | 98.24 210 | 95.27 121 | 88.42 390 | 98.98 210 | 82.76 323 | 99.94 94 | 97.10 194 | 99.83 80 | 99.96 75 |
|
| Patchmatch-test | | | 92.65 326 | 91.50 337 | 96.10 287 | 96.85 328 | 90.49 384 | 91.50 499 | 97.19 356 | 82.76 454 | 90.23 337 | 95.59 385 | 95.02 65 | 98.00 329 | 77.41 467 | 96.98 236 | 99.82 107 |
|
| MVS | | | 96.60 170 | 95.56 205 | 99.72 14 | 96.85 328 | 99.22 21 | 98.31 411 | 98.94 44 | 91.57 298 | 90.90 330 | 99.61 124 | 86.66 254 | 99.96 76 | 97.36 183 | 99.88 76 | 99.99 26 |
|
| 3Dnovator | | 91.47 12 | 96.28 193 | 95.34 219 | 99.08 82 | 96.82 330 | 97.47 114 | 99.45 284 | 98.81 67 | 95.52 115 | 89.39 361 | 99.00 205 | 81.97 329 | 99.95 85 | 97.27 185 | 99.83 80 | 99.84 104 |
|
| EI-MVSNet | | | 93.73 296 | 93.40 287 | 94.74 334 | 96.80 331 | 92.69 320 | 99.06 339 | 97.67 280 | 88.96 370 | 91.39 324 | 99.02 199 | 88.75 222 | 97.30 360 | 91.07 330 | 87.85 355 | 94.22 372 |
|
| CVMVSNet | | | 94.68 259 | 94.94 237 | 93.89 381 | 96.80 331 | 86.92 435 | 99.06 339 | 98.98 41 | 94.45 148 | 94.23 294 | 99.02 199 | 85.60 273 | 95.31 456 | 90.91 336 | 95.39 287 | 99.43 194 |
|
| IterMVS-LS | | | 92.69 324 | 92.11 322 | 94.43 353 | 96.80 331 | 92.74 317 | 99.45 284 | 96.89 415 | 88.98 368 | 89.65 354 | 95.38 399 | 88.77 221 | 96.34 426 | 90.98 334 | 82.04 403 | 94.22 372 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| AstraMVS | | | 96.57 173 | 96.46 155 | 96.91 258 | 96.79 334 | 92.50 326 | 99.90 117 | 97.38 316 | 96.02 99 | 97.79 185 | 99.32 154 | 86.36 259 | 98.99 214 | 98.26 139 | 96.33 255 | 99.23 236 |
|
| IterMVS | | | 90.91 360 | 90.17 362 | 93.12 401 | 96.78 335 | 90.42 387 | 98.89 365 | 97.05 395 | 89.03 365 | 86.49 419 | 95.42 395 | 76.59 395 | 95.02 458 | 87.22 396 | 84.09 388 | 93.93 410 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| 1314 | | | 96.84 152 | 95.96 183 | 99.48 40 | 96.74 336 | 98.52 63 | 98.31 411 | 98.86 59 | 95.82 104 | 89.91 345 | 98.98 210 | 87.49 238 | 99.96 76 | 97.80 167 | 99.73 90 | 99.96 75 |
|
| IterMVS-SCA-FT | | | 90.85 363 | 90.16 363 | 92.93 406 | 96.72 337 | 89.96 396 | 98.89 365 | 96.99 400 | 88.95 371 | 86.63 416 | 95.67 380 | 76.48 397 | 95.00 459 | 87.04 399 | 84.04 391 | 93.84 417 |
|
| MVS-HIRNet | | | 86.22 420 | 83.19 436 | 95.31 317 | 96.71 338 | 90.29 388 | 92.12 495 | 97.33 325 | 62.85 503 | 86.82 413 | 70.37 518 | 69.37 439 | 97.49 350 | 75.12 475 | 97.99 191 | 98.15 302 |
|
| viewdifsd2359ckpt11 | | | 94.09 282 | 93.63 273 | 95.46 310 | 96.68 339 | 88.92 410 | 99.62 243 | 97.12 371 | 93.07 224 | 95.73 263 | 99.22 175 | 77.05 385 | 98.88 224 | 96.52 222 | 87.69 360 | 98.58 289 |
|
| viewmsd2359difaftdt | | | 94.09 282 | 93.64 272 | 95.46 310 | 96.68 339 | 88.92 410 | 99.62 243 | 97.13 370 | 93.07 224 | 95.73 263 | 99.22 175 | 77.05 385 | 98.89 223 | 96.52 222 | 87.70 359 | 98.58 289 |
|
| VDDNet | | | 93.12 311 | 91.91 327 | 96.76 265 | 96.67 341 | 92.65 323 | 98.69 388 | 98.21 217 | 82.81 453 | 97.75 187 | 99.28 161 | 61.57 472 | 99.48 186 | 98.09 149 | 94.09 306 | 98.15 302 |
|
| dmvs_re | | | 93.20 308 | 93.15 297 | 93.34 394 | 96.54 342 | 83.81 453 | 98.71 385 | 98.51 131 | 91.39 309 | 92.37 316 | 98.56 270 | 78.66 372 | 97.83 338 | 93.89 279 | 89.74 327 | 98.38 296 |
|
| Elysia | | | 94.50 266 | 93.38 288 | 97.85 180 | 96.49 343 | 96.70 148 | 98.98 351 | 97.78 270 | 90.81 326 | 96.19 249 | 98.55 272 | 73.63 422 | 98.98 215 | 89.41 357 | 98.56 168 | 97.88 309 |
|
| StellarMVS | | | 94.50 266 | 93.38 288 | 97.85 180 | 96.49 343 | 96.70 148 | 98.98 351 | 97.78 270 | 90.81 326 | 96.19 249 | 98.55 272 | 73.63 422 | 98.98 215 | 89.41 357 | 98.56 168 | 97.88 309 |
|
| MIMVSNet | | | 90.30 376 | 88.67 391 | 95.17 321 | 96.45 345 | 91.64 357 | 92.39 494 | 97.15 365 | 85.99 420 | 90.50 335 | 93.19 455 | 66.95 450 | 94.86 464 | 82.01 439 | 93.43 314 | 99.01 263 |
|
| CR-MVSNet | | | 93.45 305 | 92.62 310 | 95.94 292 | 96.29 346 | 92.66 321 | 92.01 496 | 96.23 441 | 92.62 250 | 96.94 214 | 93.31 452 | 91.04 182 | 96.03 441 | 79.23 456 | 95.96 264 | 99.13 246 |
|
| RPMNet | | | 89.76 389 | 87.28 406 | 97.19 244 | 96.29 346 | 92.66 321 | 92.01 496 | 98.31 199 | 70.19 494 | 96.94 214 | 85.87 503 | 87.25 243 | 99.78 147 | 62.69 502 | 95.96 264 | 99.13 246 |
|
| tt0805 | | | 91.28 353 | 90.18 361 | 94.60 340 | 96.26 348 | 87.55 428 | 98.39 409 | 98.72 78 | 89.00 367 | 89.22 367 | 98.47 280 | 62.98 467 | 98.96 219 | 90.57 342 | 88.00 354 | 97.28 328 |
|
| Patchmtry | | | 89.70 390 | 88.49 394 | 93.33 395 | 96.24 349 | 89.94 399 | 91.37 500 | 96.23 441 | 78.22 476 | 87.69 401 | 93.31 452 | 91.04 182 | 96.03 441 | 80.18 453 | 82.10 402 | 94.02 400 |
|
| test_vis1_rt | | | 86.87 417 | 86.05 414 | 89.34 447 | 96.12 350 | 78.07 483 | 99.87 133 | 83.54 517 | 92.03 283 | 78.21 473 | 89.51 484 | 45.80 495 | 99.91 111 | 96.25 228 | 93.11 319 | 90.03 480 |
|
| JIA-IIPM | | | 91.76 347 | 90.70 348 | 94.94 327 | 96.11 351 | 87.51 429 | 93.16 491 | 98.13 232 | 75.79 482 | 97.58 189 | 77.68 513 | 92.84 137 | 97.97 330 | 88.47 375 | 96.54 247 | 99.33 212 |
|
| OpenMVS |  | 90.15 15 | 94.77 254 | 93.59 277 | 98.33 146 | 96.07 352 | 97.48 113 | 99.56 262 | 98.57 107 | 90.46 342 | 86.51 418 | 98.95 219 | 78.57 373 | 99.94 94 | 93.86 280 | 99.74 89 | 97.57 323 |
|
| PAPM | | | 98.60 37 | 98.42 38 | 99.14 73 | 96.05 353 | 98.96 28 | 99.90 117 | 99.35 24 | 96.68 73 | 98.35 157 | 99.66 116 | 96.45 35 | 98.51 282 | 99.45 65 | 99.89 73 | 99.96 75 |
|
| CLD-MVS | | | 94.06 285 | 93.90 268 | 94.55 344 | 96.02 354 | 90.69 378 | 99.98 24 | 97.72 276 | 96.62 77 | 91.05 329 | 98.85 239 | 77.21 383 | 98.47 283 | 98.11 147 | 89.51 333 | 94.48 348 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| PatchT | | | 90.38 373 | 88.75 390 | 95.25 319 | 95.99 355 | 90.16 391 | 91.22 501 | 97.54 299 | 76.80 478 | 97.26 202 | 86.01 502 | 91.88 169 | 96.07 440 | 66.16 494 | 95.91 268 | 99.51 177 |
|
| ACMH+ | | 89.98 16 | 90.35 374 | 89.54 373 | 92.78 410 | 95.99 355 | 86.12 439 | 98.81 376 | 97.18 358 | 89.38 360 | 83.14 446 | 97.76 312 | 68.42 444 | 98.43 288 | 89.11 365 | 86.05 371 | 93.78 420 |
|
| DeepMVS_CX |  | | | | 82.92 476 | 95.98 357 | 58.66 511 | | 96.01 447 | 92.72 242 | 78.34 472 | 95.51 390 | 58.29 479 | 98.08 324 | 82.57 433 | 85.29 376 | 92.03 459 |
|
| ACMP | | 92.05 9 | 92.74 322 | 92.42 319 | 93.73 383 | 95.91 358 | 88.72 414 | 99.81 169 | 97.53 301 | 94.13 169 | 87.00 412 | 98.23 293 | 74.07 418 | 98.47 283 | 96.22 229 | 88.86 340 | 93.99 405 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| test_vis1_n | | | 93.61 300 | 93.03 300 | 95.35 314 | 95.86 359 | 86.94 434 | 99.87 133 | 96.36 439 | 96.85 64 | 99.54 73 | 98.79 244 | 52.41 487 | 99.83 140 | 98.64 114 | 98.97 154 | 99.29 224 |
|
| HQP-NCC | | | | | | 95.78 360 | | 99.87 133 | | 96.82 66 | 93.37 301 | | | | | | |
|
| ACMP_Plane | | | | | | 95.78 360 | | 99.87 133 | | 96.82 66 | 93.37 301 | | | | | | |
|
| HQP-MVS | | | 94.61 261 | 94.50 248 | 94.92 328 | 95.78 360 | 91.85 342 | 99.87 133 | 97.89 256 | 96.82 66 | 93.37 301 | 98.65 257 | 80.65 351 | 98.39 295 | 97.92 159 | 89.60 328 | 94.53 344 |
|
| NP-MVS | | | | | | 95.77 363 | 91.79 346 | | | | | 98.65 257 | | | | | |
|
| test_fmvsmconf0.1_n | | | 97.74 103 | 97.44 107 | 98.64 115 | 95.76 364 | 96.20 176 | 99.94 93 | 98.05 239 | 98.17 13 | 98.89 122 | 99.42 142 | 87.65 233 | 99.90 113 | 99.50 61 | 99.60 107 | 99.82 107 |
|
| plane_prior6 | | | | | | 95.76 364 | 91.72 353 | | | | | | 80.47 355 | | | | |
|
| ACMM | | 91.95 10 | 92.88 317 | 92.52 317 | 93.98 377 | 95.75 366 | 89.08 409 | 99.77 187 | 97.52 303 | 93.00 227 | 89.95 344 | 97.99 302 | 76.17 401 | 98.46 286 | 93.63 292 | 88.87 339 | 94.39 356 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| GA-MVS | | | 93.83 289 | 92.84 304 | 96.80 263 | 95.73 367 | 93.57 295 | 99.88 130 | 97.24 350 | 92.57 257 | 92.92 308 | 96.66 348 | 78.73 371 | 97.67 344 | 87.75 388 | 94.06 307 | 99.17 241 |
|
| plane_prior1 | | | | | | 95.73 367 | | | | | | | | | | | |
|
| jason | | | 97.24 129 | 96.86 133 | 98.38 145 | 95.73 367 | 97.32 118 | 99.97 42 | 97.40 315 | 95.34 119 | 98.60 144 | 99.54 134 | 87.70 232 | 98.56 277 | 97.94 158 | 99.47 124 | 99.25 233 |
| jason: jason. |
| mmtdpeth | | | 88.52 401 | 87.75 403 | 90.85 430 | 95.71 370 | 83.47 459 | 98.94 359 | 94.85 473 | 88.78 376 | 97.19 204 | 89.58 483 | 63.29 465 | 98.97 217 | 98.54 119 | 62.86 492 | 90.10 479 |
|
| HQP_MVS | | | 94.49 268 | 94.36 251 | 94.87 329 | 95.71 370 | 91.74 349 | 99.84 152 | 97.87 258 | 96.38 86 | 93.01 306 | 98.59 265 | 80.47 355 | 98.37 301 | 97.79 170 | 89.55 331 | 94.52 346 |
|
| plane_prior7 | | | | | | 95.71 370 | 91.59 363 | | | | | | | | | | |
|
| ITE_SJBPF | | | | | 92.38 413 | 95.69 373 | 85.14 445 | | 95.71 454 | 92.81 236 | 89.33 364 | 98.11 296 | 70.23 437 | 98.42 289 | 85.91 411 | 88.16 352 | 93.59 428 |
|
| fmvsm_s_conf0.1_n_a | | | 97.09 138 | 96.90 131 | 97.63 204 | 95.65 374 | 94.21 271 | 99.83 160 | 98.50 137 | 96.27 92 | 99.65 55 | 99.64 119 | 84.72 295 | 99.93 104 | 99.04 85 | 98.84 159 | 98.74 282 |
|
| ACMH | | 89.72 17 | 90.64 367 | 89.63 370 | 93.66 389 | 95.64 375 | 88.64 417 | 98.55 396 | 97.45 308 | 89.03 365 | 81.62 453 | 97.61 313 | 69.75 438 | 98.41 291 | 89.37 359 | 87.62 361 | 93.92 411 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| baseline2 | | | 96.71 164 | 96.49 152 | 97.37 235 | 95.63 376 | 95.96 185 | 99.74 203 | 98.88 55 | 92.94 229 | 91.61 322 | 98.97 212 | 97.72 7 | 98.62 272 | 94.83 257 | 98.08 189 | 97.53 325 |
|
| FMVSNet1 | | | 88.50 402 | 86.64 409 | 94.08 369 | 95.62 377 | 91.97 335 | 98.43 404 | 96.95 406 | 83.00 451 | 86.08 426 | 94.72 426 | 59.09 478 | 96.11 436 | 81.82 441 | 84.07 389 | 94.17 377 |
|
| LuminaMVS | | | 96.63 168 | 96.21 168 | 97.87 179 | 95.58 378 | 96.82 142 | 99.12 328 | 97.67 280 | 94.47 146 | 97.88 180 | 98.31 290 | 87.50 237 | 98.71 256 | 98.07 151 | 97.29 211 | 98.10 305 |
|
| 0.3-1-1-0.015 | | | 94.22 278 | 93.13 299 | 97.49 222 | 95.50 379 | 94.17 272 | 100.00 1 | 98.22 213 | 88.44 386 | 97.14 206 | 97.04 333 | 92.73 141 | 98.59 273 | 96.45 224 | 72.65 463 | 99.70 125 |
|
| 0.4-1-1-0.2 | | | 94.14 279 | 93.02 301 | 97.51 217 | 95.45 380 | 94.25 268 | 100.00 1 | 98.22 213 | 88.53 383 | 96.83 220 | 96.95 336 | 92.25 160 | 98.57 276 | 96.34 225 | 72.65 463 | 99.70 125 |
|
| LPG-MVS_test | | | 92.96 314 | 92.71 309 | 93.71 385 | 95.43 381 | 88.67 415 | 99.75 199 | 97.62 287 | 92.81 236 | 90.05 340 | 98.49 276 | 75.24 408 | 98.40 293 | 95.84 236 | 89.12 335 | 94.07 396 |
|
| LGP-MVS_train | | | | | 93.71 385 | 95.43 381 | 88.67 415 | | 97.62 287 | 92.81 236 | 90.05 340 | 98.49 276 | 75.24 408 | 98.40 293 | 95.84 236 | 89.12 335 | 94.07 396 |
|
| tpm | | | 93.70 298 | 93.41 286 | 94.58 342 | 95.36 383 | 87.41 430 | 97.01 450 | 96.90 414 | 90.85 324 | 96.72 225 | 94.14 443 | 90.40 196 | 96.84 394 | 90.75 340 | 88.54 347 | 99.51 177 |
|
| 0.4-1-1-0.1 | | | 94.07 284 | 92.95 302 | 97.42 229 | 95.24 384 | 94.00 279 | 100.00 1 | 98.22 213 | 88.27 390 | 96.81 222 | 96.93 337 | 92.27 159 | 98.56 277 | 96.21 230 | 72.63 465 | 99.70 125 |
|
| D2MVS | | | 92.76 321 | 92.59 315 | 93.27 397 | 95.13 385 | 89.54 403 | 99.69 229 | 99.38 22 | 92.26 276 | 87.59 403 | 94.61 432 | 85.05 285 | 97.79 339 | 91.59 323 | 88.01 353 | 92.47 452 |
|
| VPA-MVSNet | | | 92.70 323 | 91.55 336 | 96.16 285 | 95.09 386 | 96.20 176 | 98.88 367 | 99.00 39 | 91.02 321 | 91.82 321 | 95.29 406 | 76.05 403 | 97.96 332 | 95.62 241 | 81.19 409 | 94.30 363 |
|
| LTVRE_ROB | | 88.28 18 | 90.29 377 | 89.05 384 | 94.02 372 | 95.08 387 | 90.15 392 | 97.19 445 | 97.43 310 | 84.91 436 | 83.99 442 | 97.06 330 | 74.00 419 | 98.28 311 | 84.08 422 | 87.71 357 | 93.62 427 |
| Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016 |
| TinyColmap | | | 87.87 409 | 86.51 410 | 91.94 419 | 95.05 388 | 85.57 443 | 97.65 436 | 94.08 485 | 84.40 440 | 81.82 452 | 96.85 342 | 62.14 470 | 98.33 304 | 80.25 452 | 86.37 368 | 91.91 461 |
|
| test0.0.03 1 | | | 93.86 288 | 93.61 274 | 94.64 338 | 95.02 389 | 92.18 333 | 99.93 100 | 98.58 105 | 94.07 173 | 87.96 398 | 98.50 275 | 93.90 106 | 94.96 460 | 81.33 442 | 93.17 317 | 96.78 331 |
|
| UniMVSNet (Re) | | | 93.07 313 | 92.13 321 | 95.88 296 | 94.84 390 | 96.24 175 | 99.88 130 | 98.98 41 | 92.49 264 | 89.25 365 | 95.40 396 | 87.09 245 | 97.14 369 | 93.13 301 | 78.16 434 | 94.26 365 |
|
| USDC | | | 90.00 385 | 88.96 385 | 93.10 403 | 94.81 391 | 88.16 423 | 98.71 385 | 95.54 459 | 93.66 194 | 83.75 444 | 97.20 324 | 65.58 456 | 98.31 306 | 83.96 425 | 87.49 363 | 92.85 445 |
|
| VPNet | | | 91.81 341 | 90.46 352 | 95.85 298 | 94.74 392 | 95.54 204 | 98.98 351 | 98.59 103 | 92.14 278 | 90.77 334 | 97.44 317 | 68.73 442 | 97.54 349 | 94.89 256 | 77.89 436 | 94.46 349 |
|
| FIs | | | 94.10 281 | 93.43 283 | 96.11 286 | 94.70 393 | 96.82 142 | 99.58 254 | 98.93 48 | 92.54 260 | 89.34 363 | 97.31 321 | 87.62 234 | 97.10 373 | 94.22 274 | 86.58 366 | 94.40 355 |
|
| UniMVSNet_ETH3D | | | 90.06 384 | 88.58 393 | 94.49 348 | 94.67 394 | 88.09 424 | 97.81 433 | 97.57 295 | 83.91 443 | 88.44 385 | 97.41 318 | 57.44 480 | 97.62 346 | 91.41 325 | 88.59 346 | 97.77 314 |
|
| UniMVSNet_NR-MVSNet | | | 92.95 315 | 92.11 322 | 95.49 306 | 94.61 395 | 95.28 222 | 99.83 160 | 99.08 36 | 91.49 300 | 89.21 368 | 96.86 341 | 87.14 244 | 96.73 401 | 93.20 297 | 77.52 439 | 94.46 349 |
|
| test_fmvs2 | | | 89.47 394 | 89.70 369 | 88.77 454 | 94.54 396 | 75.74 487 | 99.83 160 | 94.70 479 | 94.71 137 | 91.08 327 | 96.82 346 | 54.46 483 | 97.78 341 | 92.87 304 | 88.27 350 | 92.80 446 |
|
| MonoMVSNet | | | 94.82 249 | 94.43 249 | 95.98 290 | 94.54 396 | 90.73 377 | 99.03 346 | 97.06 392 | 93.16 218 | 93.15 305 | 95.47 393 | 88.29 225 | 97.57 347 | 97.85 164 | 91.33 325 | 99.62 147 |
|
| WR-MVS | | | 92.31 333 | 91.25 341 | 95.48 309 | 94.45 398 | 95.29 221 | 99.60 250 | 98.68 84 | 90.10 350 | 88.07 397 | 96.89 339 | 80.68 350 | 96.80 398 | 93.14 300 | 79.67 426 | 94.36 357 |
|
| dtuonly | | | 93.89 287 | 93.16 296 | 96.08 288 | 94.37 399 | 91.67 356 | 99.15 327 | 95.04 471 | 91.79 293 | 94.74 280 | 98.72 249 | 81.01 343 | 98.31 306 | 87.29 394 | 96.33 255 | 98.27 300 |
|
| nrg030 | | | 93.51 302 | 92.53 316 | 96.45 276 | 94.36 400 | 97.20 124 | 99.81 169 | 97.16 362 | 91.60 297 | 89.86 347 | 97.46 316 | 86.37 258 | 97.68 343 | 95.88 235 | 80.31 422 | 94.46 349 |
|
| tfpnnormal | | | 89.29 397 | 87.61 404 | 94.34 356 | 94.35 401 | 94.13 274 | 98.95 358 | 98.94 44 | 83.94 441 | 84.47 438 | 95.51 390 | 74.84 413 | 97.39 352 | 77.05 470 | 80.41 420 | 91.48 464 |
|
| FC-MVSNet-test | | | 93.81 292 | 93.15 297 | 95.80 301 | 94.30 402 | 96.20 176 | 99.42 286 | 98.89 52 | 92.33 271 | 89.03 373 | 97.27 323 | 87.39 240 | 96.83 396 | 93.20 297 | 86.48 367 | 94.36 357 |
|
| SSC-MVS3.2 | | | 89.59 392 | 88.66 392 | 92.38 413 | 94.29 403 | 86.12 439 | 99.49 275 | 97.66 283 | 90.28 349 | 88.63 381 | 95.18 410 | 64.46 461 | 96.88 392 | 85.30 415 | 82.66 397 | 94.14 387 |
|
| MS-PatchMatch | | | 90.65 366 | 90.30 357 | 91.71 424 | 94.22 404 | 85.50 444 | 98.24 415 | 97.70 277 | 88.67 379 | 86.42 421 | 96.37 358 | 67.82 447 | 98.03 328 | 83.62 427 | 99.62 99 | 91.60 462 |
|
| WR-MVS_H | | | 91.30 351 | 90.35 355 | 94.15 363 | 94.17 405 | 92.62 324 | 99.17 325 | 98.94 44 | 88.87 374 | 86.48 420 | 94.46 437 | 84.36 302 | 96.61 408 | 88.19 381 | 78.51 431 | 93.21 437 |
|
| DU-MVS | | | 92.46 330 | 91.45 339 | 95.49 306 | 94.05 406 | 95.28 222 | 99.81 169 | 98.74 76 | 92.25 277 | 89.21 368 | 96.64 350 | 81.66 334 | 96.73 401 | 93.20 297 | 77.52 439 | 94.46 349 |
|
| NR-MVSNet | | | 91.56 349 | 90.22 359 | 95.60 304 | 94.05 406 | 95.76 192 | 98.25 414 | 98.70 80 | 91.16 315 | 80.78 460 | 96.64 350 | 83.23 320 | 96.57 409 | 91.41 325 | 77.73 438 | 94.46 349 |
|
| CP-MVSNet | | | 91.23 355 | 90.22 359 | 94.26 358 | 93.96 408 | 92.39 329 | 99.09 332 | 98.57 107 | 88.95 371 | 86.42 421 | 96.57 353 | 79.19 366 | 96.37 424 | 90.29 349 | 78.95 428 | 94.02 400 |
|
| XXY-MVS | | | 91.82 340 | 90.46 352 | 95.88 296 | 93.91 409 | 95.40 211 | 98.87 370 | 97.69 279 | 88.63 381 | 87.87 399 | 97.08 328 | 74.38 417 | 97.89 336 | 91.66 322 | 84.07 389 | 94.35 360 |
|
| PS-CasMVS | | | 90.63 368 | 89.51 375 | 93.99 375 | 93.83 410 | 91.70 354 | 98.98 351 | 98.52 128 | 88.48 384 | 86.15 425 | 96.53 355 | 75.46 406 | 96.31 429 | 88.83 367 | 78.86 430 | 93.95 408 |
|
| test_0402 | | | 85.58 424 | 83.94 430 | 90.50 436 | 93.81 411 | 85.04 446 | 98.55 396 | 95.20 468 | 76.01 480 | 79.72 466 | 95.13 411 | 64.15 463 | 96.26 431 | 66.04 496 | 86.88 365 | 90.21 476 |
|
| XVG-ACMP-BASELINE | | | 91.22 356 | 90.75 347 | 92.63 412 | 93.73 412 | 85.61 442 | 98.52 400 | 97.44 309 | 92.77 240 | 89.90 346 | 96.85 342 | 66.64 453 | 98.39 295 | 92.29 309 | 88.61 344 | 93.89 413 |
|
| TranMVSNet+NR-MVSNet | | | 91.68 348 | 90.61 351 | 94.87 329 | 93.69 413 | 93.98 280 | 99.69 229 | 98.65 88 | 91.03 320 | 88.44 385 | 96.83 345 | 80.05 359 | 96.18 434 | 90.26 350 | 76.89 447 | 94.45 354 |
|
| TransMVSNet (Re) | | | 87.25 415 | 85.28 423 | 93.16 400 | 93.56 414 | 91.03 369 | 98.54 398 | 94.05 487 | 83.69 445 | 81.09 457 | 96.16 364 | 75.32 407 | 96.40 423 | 76.69 471 | 68.41 479 | 92.06 458 |
|
| v10 | | | 90.25 378 | 88.82 387 | 94.57 343 | 93.53 415 | 93.43 300 | 99.08 334 | 96.87 417 | 85.00 433 | 87.34 410 | 94.51 433 | 80.93 345 | 97.02 383 | 82.85 432 | 79.23 427 | 93.26 435 |
|
| testgi | | | 89.01 399 | 88.04 400 | 91.90 420 | 93.49 416 | 84.89 448 | 99.73 210 | 95.66 456 | 93.89 187 | 85.14 432 | 98.17 294 | 59.68 476 | 94.66 467 | 77.73 466 | 88.88 338 | 96.16 340 |
|
| v8 | | | 90.54 370 | 89.17 380 | 94.66 337 | 93.43 417 | 93.40 303 | 99.20 322 | 96.94 410 | 85.76 423 | 87.56 404 | 94.51 433 | 81.96 330 | 97.19 366 | 84.94 418 | 78.25 433 | 93.38 433 |
|
| V42 | | | 91.28 353 | 90.12 364 | 94.74 334 | 93.42 418 | 93.46 299 | 99.68 232 | 97.02 396 | 87.36 401 | 89.85 349 | 95.05 414 | 81.31 340 | 97.34 355 | 87.34 393 | 80.07 424 | 93.40 431 |
|
| pm-mvs1 | | | 89.36 396 | 87.81 402 | 94.01 373 | 93.40 419 | 91.93 338 | 98.62 394 | 96.48 437 | 86.25 418 | 83.86 443 | 96.14 366 | 73.68 421 | 97.04 379 | 86.16 408 | 75.73 452 | 93.04 441 |
|
| v1144 | | | 91.09 357 | 89.83 366 | 94.87 329 | 93.25 420 | 93.69 288 | 99.62 243 | 96.98 402 | 86.83 411 | 89.64 355 | 94.99 421 | 80.94 344 | 97.05 376 | 85.08 417 | 81.16 410 | 93.87 415 |
|
| v1192 | | | 90.62 369 | 89.25 379 | 94.72 336 | 93.13 421 | 93.07 308 | 99.50 273 | 97.02 396 | 86.33 417 | 89.56 359 | 95.01 418 | 79.22 365 | 97.09 375 | 82.34 437 | 81.16 410 | 94.01 402 |
|
| v2v482 | | | 91.30 351 | 90.07 365 | 95.01 324 | 93.13 421 | 93.79 283 | 99.77 187 | 97.02 396 | 88.05 392 | 89.25 365 | 95.37 400 | 80.73 349 | 97.15 368 | 87.28 395 | 80.04 425 | 94.09 395 |
|
| OPM-MVS | | | 93.21 307 | 92.80 306 | 94.44 351 | 93.12 423 | 90.85 376 | 99.77 187 | 97.61 290 | 96.19 95 | 91.56 323 | 98.65 257 | 75.16 412 | 98.47 283 | 93.78 287 | 89.39 334 | 93.99 405 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| v144192 | | | 90.79 364 | 89.52 374 | 94.59 341 | 93.11 424 | 92.77 315 | 99.56 262 | 96.99 400 | 86.38 416 | 89.82 350 | 94.95 423 | 80.50 354 | 97.10 373 | 83.98 424 | 80.41 420 | 93.90 412 |
|
| PEN-MVS | | | 90.19 380 | 89.06 383 | 93.57 390 | 93.06 425 | 90.90 374 | 99.06 339 | 98.47 140 | 88.11 391 | 85.91 427 | 96.30 360 | 76.67 393 | 95.94 444 | 87.07 398 | 76.91 446 | 93.89 413 |
|
| v1240 | | | 90.20 379 | 88.79 388 | 94.44 351 | 93.05 426 | 92.27 331 | 99.38 294 | 96.92 413 | 85.89 421 | 89.36 362 | 94.87 425 | 77.89 380 | 97.03 381 | 80.66 447 | 81.08 413 | 94.01 402 |
|
| usedtu_dtu_shiyan1 | | | 92.78 319 | 91.73 330 | 95.92 294 | 93.03 427 | 96.82 142 | 99.83 160 | 97.79 266 | 90.58 335 | 90.09 338 | 95.04 415 | 84.75 291 | 96.72 403 | 88.19 381 | 86.23 369 | 94.23 369 |
|
| FE-MVSNET3 | | | 92.78 319 | 91.73 330 | 95.92 294 | 93.03 427 | 96.82 142 | 99.83 160 | 97.79 266 | 90.58 335 | 90.09 338 | 95.04 415 | 84.75 291 | 96.72 403 | 88.20 380 | 86.23 369 | 94.23 369 |
|
| ArgMatch-SfM | | | 85.25 429 | 84.17 427 | 88.48 456 | 92.99 429 | 77.23 486 | 97.92 428 | 94.24 483 | 90.50 339 | 85.08 434 | 95.65 382 | 49.84 491 | 95.83 446 | 81.06 445 | 70.22 470 | 92.39 454 |
|
| v148 | | | 90.70 365 | 89.63 370 | 93.92 378 | 92.97 430 | 90.97 370 | 99.75 199 | 96.89 415 | 87.51 398 | 88.27 394 | 95.01 418 | 81.67 333 | 97.04 379 | 87.40 392 | 77.17 444 | 93.75 421 |
|
| v1921920 | | | 90.46 371 | 89.12 381 | 94.50 347 | 92.96 431 | 92.46 327 | 99.49 275 | 96.98 402 | 86.10 419 | 89.61 357 | 95.30 403 | 78.55 374 | 97.03 381 | 82.17 438 | 80.89 418 | 94.01 402 |
|
| MVStest1 | | | 85.03 431 | 82.76 440 | 91.83 421 | 92.95 432 | 89.16 408 | 98.57 395 | 94.82 474 | 71.68 491 | 68.54 496 | 95.11 413 | 83.17 321 | 95.66 449 | 74.69 476 | 65.32 486 | 90.65 471 |
|
| tt0320-xc | | | 82.94 446 | 80.35 453 | 90.72 434 | 92.90 433 | 83.54 457 | 96.85 455 | 94.73 477 | 63.12 502 | 79.85 465 | 93.77 447 | 49.43 493 | 95.46 452 | 80.98 446 | 71.54 467 | 93.16 438 |
|
| ArgMatch-Sym | | | 85.85 422 | 85.07 425 | 88.21 458 | 92.84 434 | 77.63 485 | 98.42 407 | 94.70 479 | 89.91 354 | 84.33 439 | 96.72 347 | 51.42 490 | 94.89 463 | 82.48 434 | 74.80 455 | 92.10 456 |
|
| Baseline_NR-MVSNet | | | 90.33 375 | 89.51 375 | 92.81 409 | 92.84 434 | 89.95 397 | 99.77 187 | 93.94 488 | 84.69 438 | 89.04 372 | 95.66 381 | 81.66 334 | 96.52 412 | 90.99 333 | 76.98 445 | 91.97 460 |
|
| test_method | | | 80.79 452 | 79.70 455 | 84.08 471 | 92.83 436 | 67.06 499 | 99.51 271 | 95.42 461 | 54.34 513 | 81.07 458 | 93.53 449 | 44.48 496 | 92.22 489 | 78.90 461 | 77.23 443 | 92.94 443 |
|
| pmmvs4 | | | 92.10 337 | 91.07 345 | 95.18 320 | 92.82 437 | 94.96 235 | 99.48 278 | 96.83 419 | 87.45 400 | 88.66 380 | 96.56 354 | 83.78 310 | 96.83 396 | 89.29 362 | 84.77 383 | 93.75 421 |
|
| LF4IMVS | | | 89.25 398 | 88.85 386 | 90.45 438 | 92.81 438 | 81.19 474 | 98.12 422 | 94.79 475 | 91.44 304 | 86.29 423 | 97.11 326 | 65.30 459 | 98.11 322 | 88.53 372 | 85.25 377 | 92.07 457 |
|
| tt0320 | | | 83.56 445 | 81.15 448 | 90.77 432 | 92.77 439 | 83.58 456 | 96.83 456 | 95.52 460 | 63.26 501 | 81.36 455 | 92.54 459 | 53.26 485 | 95.77 447 | 80.45 448 | 74.38 456 | 92.96 442 |
|
| DTE-MVSNet | | | 89.40 395 | 88.24 398 | 92.88 407 | 92.66 440 | 89.95 397 | 99.10 331 | 98.22 213 | 87.29 402 | 85.12 433 | 96.22 362 | 76.27 400 | 95.30 457 | 83.56 428 | 75.74 451 | 93.41 430 |
|
| EU-MVSNet | | | 90.14 382 | 90.34 356 | 89.54 446 | 92.55 441 | 81.06 475 | 98.69 388 | 98.04 240 | 91.41 308 | 86.59 417 | 96.84 344 | 80.83 347 | 93.31 480 | 86.20 407 | 81.91 404 | 94.26 365 |
|
| APD_test1 | | | 81.15 450 | 80.92 450 | 81.86 477 | 92.45 442 | 59.76 510 | 96.04 471 | 93.61 492 | 73.29 489 | 77.06 476 | 96.64 350 | 44.28 497 | 96.16 435 | 72.35 480 | 82.52 398 | 89.67 485 |
|
| sc_t1 | | | 85.01 432 | 82.46 442 | 92.67 411 | 92.44 443 | 83.09 460 | 97.39 441 | 95.72 453 | 65.06 499 | 85.64 430 | 96.16 364 | 49.50 492 | 97.34 355 | 84.86 419 | 75.39 453 | 97.57 323 |
|
| our_test_3 | | | 90.39 372 | 89.48 377 | 93.12 401 | 92.40 444 | 89.57 402 | 99.33 301 | 96.35 440 | 87.84 396 | 85.30 431 | 94.99 421 | 84.14 306 | 96.09 439 | 80.38 450 | 84.56 384 | 93.71 426 |
|
| ppachtmachnet_test | | | 89.58 393 | 88.35 396 | 93.25 399 | 92.40 444 | 90.44 386 | 99.33 301 | 96.73 426 | 85.49 428 | 85.90 428 | 95.77 375 | 81.09 342 | 96.00 443 | 76.00 474 | 82.49 399 | 93.30 434 |
|
| v7n | | | 89.65 391 | 88.29 397 | 93.72 384 | 92.22 446 | 90.56 383 | 99.07 338 | 97.10 379 | 85.42 430 | 86.73 414 | 94.72 426 | 80.06 358 | 97.13 370 | 81.14 443 | 78.12 435 | 93.49 429 |
|
| dmvs_testset | | | 83.79 441 | 86.07 413 | 76.94 484 | 92.14 447 | 48.60 524 | 96.75 457 | 90.27 504 | 89.48 359 | 78.65 470 | 98.55 272 | 79.25 364 | 86.65 507 | 66.85 492 | 82.69 396 | 95.57 342 |
|
| PS-MVSNAJss | | | 93.64 299 | 93.31 292 | 94.61 339 | 92.11 448 | 92.19 332 | 99.12 328 | 97.38 316 | 92.51 263 | 88.45 384 | 96.99 335 | 91.20 177 | 97.29 363 | 94.36 268 | 87.71 357 | 94.36 357 |
|
| pmmvs5 | | | 90.17 381 | 89.09 382 | 93.40 393 | 92.10 449 | 89.77 400 | 99.74 203 | 95.58 458 | 85.88 422 | 87.24 411 | 95.74 376 | 73.41 424 | 96.48 416 | 88.54 371 | 83.56 393 | 93.95 408 |
|
| N_pmnet | | | 80.06 455 | 80.78 451 | 77.89 482 | 91.94 450 | 45.28 529 | 98.80 379 | 56.82 531 | 78.10 477 | 80.08 463 | 93.33 450 | 77.03 387 | 95.76 448 | 68.14 489 | 82.81 395 | 92.64 447 |
|
| test_djsdf | | | 92.83 318 | 92.29 320 | 94.47 349 | 91.90 451 | 92.46 327 | 99.55 265 | 97.27 343 | 91.17 313 | 89.96 343 | 96.07 370 | 81.10 341 | 96.89 390 | 94.67 263 | 88.91 337 | 94.05 399 |
|
| SixPastTwentyTwo | | | 88.73 400 | 88.01 401 | 90.88 428 | 91.85 452 | 82.24 466 | 98.22 419 | 95.18 469 | 88.97 369 | 82.26 449 | 96.89 339 | 71.75 429 | 96.67 406 | 84.00 423 | 82.98 394 | 93.72 425 |
|
| dtuonlycased | | | 86.10 421 | 85.82 416 | 86.95 463 | 91.84 453 | 79.57 481 | 99.27 316 | 94.89 472 | 86.79 412 | 79.46 467 | 94.46 437 | 66.85 451 | 90.93 495 | 80.41 449 | 78.44 432 | 90.34 473 |
|
| K. test v3 | | | 88.05 406 | 87.24 407 | 90.47 437 | 91.82 454 | 82.23 467 | 98.96 357 | 97.42 312 | 89.05 364 | 76.93 478 | 95.60 384 | 68.49 443 | 95.42 453 | 85.87 412 | 81.01 416 | 93.75 421 |
|
| OurMVSNet-221017-0 | | | 89.81 388 | 89.48 377 | 90.83 431 | 91.64 455 | 81.21 473 | 98.17 421 | 95.38 463 | 91.48 302 | 85.65 429 | 97.31 321 | 72.66 425 | 97.29 363 | 88.15 383 | 84.83 382 | 93.97 407 |
|
| mvs_tets | | | 91.81 341 | 91.08 344 | 94.00 374 | 91.63 456 | 90.58 382 | 98.67 390 | 97.43 310 | 92.43 265 | 87.37 409 | 97.05 331 | 71.76 428 | 97.32 358 | 94.75 260 | 88.68 343 | 94.11 394 |
|
| Gipuma |  | | 66.95 477 | 65.00 477 | 72.79 492 | 91.52 457 | 67.96 496 | 66.16 529 | 95.15 470 | 47.89 516 | 58.54 507 | 67.99 525 | 29.74 506 | 87.54 506 | 50.20 516 | 77.83 437 | 62.87 524 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| test_fmvsmconf0.01_n | | | 96.39 184 | 95.74 197 | 98.32 147 | 91.47 458 | 95.56 203 | 99.84 152 | 97.30 333 | 97.74 30 | 97.89 178 | 99.35 153 | 79.62 361 | 99.85 130 | 99.25 75 | 99.24 141 | 99.55 164 |
|
| jajsoiax | | | 91.92 339 | 91.18 342 | 94.15 363 | 91.35 459 | 90.95 373 | 99.00 349 | 97.42 312 | 92.61 251 | 87.38 408 | 97.08 328 | 72.46 426 | 97.36 353 | 94.53 266 | 88.77 341 | 94.13 392 |
|
| MDA-MVSNet-bldmvs | | | 84.09 439 | 81.52 446 | 91.81 422 | 91.32 460 | 88.00 426 | 98.67 390 | 95.92 449 | 80.22 465 | 55.60 510 | 93.32 451 | 68.29 445 | 93.60 478 | 73.76 477 | 76.61 448 | 93.82 419 |
|
| MVP-Stereo | | | 90.93 359 | 90.45 354 | 92.37 415 | 91.25 461 | 88.76 412 | 98.05 426 | 96.17 443 | 87.27 403 | 84.04 440 | 95.30 403 | 78.46 375 | 97.27 365 | 83.78 426 | 99.70 92 | 91.09 465 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| MDA-MVSNet_test_wron | | | 85.51 426 | 83.32 435 | 92.10 417 | 90.96 462 | 88.58 418 | 99.20 322 | 96.52 435 | 79.70 467 | 57.12 509 | 92.69 458 | 79.11 367 | 93.86 474 | 77.10 469 | 77.46 441 | 93.86 416 |
|
| YYNet1 | | | 85.50 427 | 83.33 434 | 92.00 418 | 90.89 463 | 88.38 422 | 99.22 321 | 96.55 434 | 79.60 468 | 57.26 508 | 92.72 457 | 79.09 369 | 93.78 476 | 77.25 468 | 77.37 442 | 93.84 417 |
|
| ALIKED-NN | | | 54.48 488 | 52.67 490 | 59.89 510 | 90.79 464 | 45.45 527 | 81.25 522 | 55.75 535 | 34.99 525 | 44.87 521 | 71.98 516 | 25.50 514 | 74.36 524 | 21.88 534 | 47.04 518 | 59.85 526 |
|
| anonymousdsp | | | 91.79 346 | 90.92 346 | 94.41 354 | 90.76 465 | 92.93 314 | 98.93 361 | 97.17 360 | 89.08 363 | 87.46 407 | 95.30 403 | 78.43 376 | 96.92 387 | 92.38 308 | 88.73 342 | 93.39 432 |
|
| lessismore_v0 | | | | | 90.53 435 | 90.58 466 | 80.90 476 | | 95.80 450 | | 77.01 477 | 95.84 373 | 66.15 455 | 96.95 385 | 83.03 431 | 75.05 454 | 93.74 424 |
|
| EG-PatchMatch MVS | | | 85.35 428 | 83.81 432 | 89.99 444 | 90.39 467 | 81.89 469 | 98.21 420 | 96.09 445 | 81.78 458 | 74.73 484 | 93.72 448 | 51.56 489 | 97.12 372 | 79.16 459 | 88.61 344 | 90.96 468 |
|
| EGC-MVSNET | | | 69.38 468 | 63.76 480 | 86.26 467 | 90.32 468 | 81.66 472 | 96.24 467 | 93.85 489 | 0.99 551 | 3.22 552 | 92.33 469 | 52.44 486 | 92.92 484 | 59.53 509 | 84.90 381 | 84.21 505 |
|
| CMPMVS |  | 61.59 21 | 84.75 435 | 85.14 424 | 83.57 472 | 90.32 468 | 62.54 504 | 96.98 451 | 97.59 294 | 74.33 487 | 69.95 493 | 96.66 348 | 64.17 462 | 98.32 305 | 87.88 387 | 88.41 349 | 89.84 482 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| ALIKED-MNN | | | 52.51 492 | 50.15 497 | 59.60 512 | 90.05 470 | 44.33 531 | 81.60 520 | 54.93 537 | 32.36 528 | 40.96 529 | 68.77 522 | 20.90 525 | 75.30 522 | 20.00 535 | 41.78 523 | 59.18 527 |
|
| new_pmnet | | | 84.49 438 | 82.92 438 | 89.21 448 | 90.03 471 | 82.60 463 | 96.89 454 | 95.62 457 | 80.59 463 | 75.77 483 | 89.17 485 | 65.04 460 | 94.79 465 | 72.12 481 | 81.02 415 | 90.23 475 |
|
| pmmvs6 | | | 85.69 423 | 83.84 431 | 91.26 427 | 90.00 472 | 84.41 451 | 97.82 432 | 96.15 444 | 75.86 481 | 81.29 456 | 95.39 398 | 61.21 473 | 96.87 393 | 83.52 429 | 73.29 459 | 92.50 451 |
|
| ttmdpeth | | | 88.23 405 | 87.06 408 | 91.75 423 | 89.91 473 | 87.35 431 | 98.92 364 | 95.73 452 | 87.92 394 | 84.02 441 | 96.31 359 | 68.23 446 | 96.84 394 | 86.33 406 | 76.12 449 | 91.06 466 |
|
| DSMNet-mixed | | | 88.28 404 | 88.24 398 | 88.42 457 | 89.64 474 | 75.38 490 | 98.06 425 | 89.86 505 | 85.59 427 | 88.20 396 | 92.14 471 | 76.15 402 | 91.95 490 | 78.46 463 | 96.05 261 | 97.92 308 |
|
| DenseAffine | | | 75.91 461 | 73.39 465 | 83.47 473 | 89.52 475 | 71.86 493 | 93.39 490 | 89.29 510 | 71.44 492 | 66.83 497 | 90.32 480 | 30.65 503 | 89.67 499 | 68.20 488 | 60.88 501 | 88.88 493 |
|
| UnsupCasMVSNet_eth | | | 85.52 425 | 83.99 428 | 90.10 442 | 89.36 476 | 83.51 458 | 96.65 458 | 97.99 244 | 89.14 362 | 75.89 482 | 93.83 445 | 63.25 466 | 93.92 472 | 81.92 440 | 67.90 482 | 92.88 444 |
|
| Anonymous20231206 | | | 86.32 419 | 85.42 422 | 89.02 450 | 89.11 477 | 80.53 479 | 99.05 343 | 95.28 464 | 85.43 429 | 82.82 447 | 93.92 444 | 74.40 416 | 93.44 479 | 66.99 491 | 81.83 405 | 93.08 440 |
|
| ALIKED-LG | | | 54.29 489 | 52.28 491 | 60.32 506 | 88.90 478 | 45.51 526 | 81.66 519 | 56.33 532 | 38.60 518 | 42.62 527 | 70.81 517 | 25.00 516 | 75.20 523 | 19.87 536 | 46.76 520 | 60.24 525 |
|
| Anonymous20240521 | | | 85.15 430 | 83.81 432 | 89.16 449 | 88.32 479 | 82.69 462 | 98.80 379 | 95.74 451 | 79.72 466 | 81.53 454 | 90.99 474 | 65.38 458 | 94.16 470 | 72.69 479 | 81.11 412 | 90.63 472 |
|
| OpenMVS_ROB |  | 79.82 20 | 83.77 442 | 81.68 445 | 90.03 443 | 88.30 480 | 82.82 461 | 98.46 401 | 95.22 467 | 73.92 488 | 76.00 481 | 91.29 473 | 55.00 482 | 96.94 386 | 68.40 487 | 88.51 348 | 90.34 473 |
|
| test20.03 | | | 84.72 436 | 83.99 428 | 86.91 464 | 88.19 481 | 80.62 478 | 98.88 367 | 95.94 448 | 88.36 387 | 78.87 468 | 94.62 431 | 68.75 441 | 89.11 501 | 66.52 493 | 75.82 450 | 91.00 467 |
|
| RoMa-SfM | | | 74.91 464 | 72.77 466 | 81.35 478 | 88.00 482 | 67.35 498 | 93.55 487 | 86.23 515 | 68.27 497 | 66.79 498 | 92.92 456 | 30.40 504 | 87.68 503 | 66.14 495 | 62.62 493 | 89.02 491 |
|
| gbinet_0.2-2-1-0.02 | | | 87.63 414 | 85.51 421 | 93.99 375 | 87.22 483 | 91.56 364 | 99.81 169 | 97.36 320 | 79.54 469 | 88.60 382 | 93.29 454 | 73.76 420 | 96.34 426 | 89.27 363 | 60.78 502 | 94.06 398 |
|
| blend_shiyan4 | | | 90.13 383 | 88.79 388 | 94.17 360 | 87.12 484 | 91.83 344 | 99.75 199 | 97.08 383 | 79.27 474 | 88.69 378 | 92.53 460 | 92.25 160 | 96.50 413 | 89.35 360 | 73.04 461 | 94.18 376 |
|
| KD-MVS_self_test | | | 83.59 443 | 82.06 443 | 88.20 459 | 86.93 485 | 80.70 477 | 97.21 444 | 96.38 438 | 82.87 452 | 82.49 448 | 88.97 486 | 67.63 448 | 92.32 487 | 73.75 478 | 62.30 495 | 91.58 463 |
|
| DKM | | | 72.18 466 | 69.80 469 | 79.34 481 | 86.79 486 | 65.15 500 | 92.70 492 | 84.00 516 | 67.67 498 | 61.97 502 | 89.63 482 | 23.69 520 | 85.17 509 | 67.39 490 | 54.35 512 | 87.70 497 |
|
| MIMVSNet1 | | | 82.58 447 | 80.51 452 | 88.78 452 | 86.68 487 | 84.20 452 | 96.65 458 | 95.41 462 | 78.75 475 | 78.59 471 | 92.44 461 | 51.88 488 | 89.76 498 | 65.26 497 | 78.95 428 | 92.38 455 |
|
| wanda-best-256-512 | | | 87.82 410 | 85.71 417 | 94.15 363 | 86.66 488 | 91.88 340 | 99.76 193 | 97.08 383 | 79.46 470 | 88.37 391 | 92.36 465 | 78.01 377 | 96.43 419 | 88.39 376 | 61.26 497 | 94.14 387 |
|
| FE-blended-shiyan7 | | | 87.82 410 | 85.71 417 | 94.15 363 | 86.66 488 | 91.88 340 | 99.76 193 | 97.08 383 | 79.46 470 | 88.37 391 | 92.36 465 | 78.01 377 | 96.43 419 | 88.39 376 | 61.26 497 | 94.14 387 |
|
| usedtu_blend_shiyan5 | | | 86.75 418 | 84.29 426 | 94.16 361 | 86.66 488 | 91.83 344 | 97.42 438 | 95.23 466 | 69.94 495 | 88.37 391 | 92.36 465 | 78.01 377 | 96.50 413 | 89.35 360 | 61.26 497 | 94.14 387 |
|
| SP-NN | | | 55.28 487 | 53.59 489 | 60.34 505 | 86.63 491 | 39.01 536 | 86.70 512 | 56.31 533 | 31.08 530 | 43.77 524 | 68.45 523 | 23.39 521 | 60.24 529 | 29.19 529 | 56.76 509 | 81.77 511 |
|
| LoFTR | | | 74.41 465 | 70.88 468 | 84.99 470 | 86.56 492 | 67.85 497 | 93.74 483 | 89.63 507 | 69.46 496 | 54.95 511 | 87.39 497 | 30.76 502 | 96.92 387 | 61.37 504 | 64.06 489 | 90.19 477 |
|
| blended_shiyan8 | | | 87.82 410 | 85.71 417 | 94.16 361 | 86.54 493 | 91.79 346 | 99.72 214 | 97.08 383 | 79.32 472 | 88.44 385 | 92.35 468 | 77.88 381 | 96.56 410 | 88.53 372 | 61.51 496 | 94.15 383 |
|
| blended_shiyan6 | | | 87.74 413 | 85.62 420 | 94.09 368 | 86.53 494 | 91.73 352 | 99.72 214 | 97.08 383 | 79.32 472 | 88.22 395 | 92.31 470 | 77.82 382 | 96.43 419 | 88.31 378 | 61.26 497 | 94.13 392 |
|
| CL-MVSNet_self_test | | | 84.50 437 | 83.15 437 | 88.53 455 | 86.00 495 | 81.79 470 | 98.82 375 | 97.35 321 | 85.12 432 | 83.62 445 | 90.91 476 | 76.66 394 | 91.40 491 | 69.53 485 | 60.36 503 | 92.40 453 |
|
| MatchFormer | | | 70.84 467 | 66.72 474 | 83.19 475 | 85.99 496 | 64.61 501 | 93.58 486 | 88.62 511 | 59.32 508 | 50.64 514 | 82.31 510 | 28.00 509 | 96.79 399 | 52.52 515 | 59.50 505 | 88.18 494 |
|
| UnsupCasMVSNet_bld | | | 79.97 457 | 77.03 463 | 88.78 452 | 85.62 497 | 81.98 468 | 93.66 484 | 97.35 321 | 75.51 484 | 70.79 492 | 83.05 506 | 48.70 494 | 94.91 462 | 78.31 464 | 60.29 504 | 89.46 488 |
|
| mvs5depth | | | 84.87 433 | 82.90 439 | 90.77 432 | 85.59 498 | 84.84 449 | 91.10 502 | 93.29 494 | 83.14 449 | 85.07 435 | 94.33 440 | 62.17 469 | 97.32 358 | 78.83 462 | 72.59 466 | 90.14 478 |
|
| SP-LightGlue | | | 55.29 485 | 53.65 488 | 60.20 507 | 85.58 499 | 39.12 535 | 86.36 515 | 57.52 530 | 32.34 529 | 44.34 523 | 67.75 526 | 24.36 518 | 59.32 532 | 29.62 527 | 54.98 510 | 82.17 509 |
|
| SP-SuperGlue | | | 55.29 485 | 53.71 487 | 60.00 509 | 85.11 500 | 38.86 537 | 86.96 511 | 57.95 529 | 32.77 527 | 44.54 522 | 68.00 524 | 23.90 519 | 59.51 531 | 29.61 528 | 54.59 511 | 81.63 512 |
|
| SP-MNN | | | 53.97 490 | 52.04 494 | 59.73 511 | 84.72 501 | 38.63 538 | 86.51 513 | 55.94 534 | 29.25 531 | 40.20 530 | 67.48 527 | 22.18 523 | 59.59 530 | 27.79 530 | 54.33 513 | 80.98 513 |
|
| Patchmatch-RL test | | | 86.90 416 | 85.98 415 | 89.67 445 | 84.45 502 | 75.59 488 | 89.71 507 | 92.43 496 | 86.89 410 | 77.83 475 | 90.94 475 | 94.22 95 | 93.63 477 | 87.75 388 | 69.61 473 | 99.79 112 |
|
| DKM-HiRes | | | 68.91 470 | 66.34 476 | 76.62 486 | 84.17 503 | 60.69 507 | 90.78 506 | 78.55 520 | 62.17 505 | 58.82 506 | 87.54 494 | 20.94 524 | 82.56 513 | 63.05 501 | 51.00 516 | 86.61 501 |
|
| MASt3R-SfM | | | 78.94 458 | 79.57 456 | 77.07 483 | 84.15 504 | 50.74 520 | 91.56 498 | 92.34 497 | 83.22 448 | 80.84 459 | 94.16 442 | 36.67 500 | 92.30 488 | 79.45 455 | 73.71 458 | 88.16 495 |
|
| pmmvs-eth3d | | | 84.03 440 | 81.97 444 | 90.20 440 | 84.15 504 | 87.09 433 | 98.10 424 | 94.73 477 | 83.05 450 | 74.10 488 | 87.77 493 | 65.56 457 | 94.01 471 | 81.08 444 | 69.24 475 | 89.49 487 |
|
| test_fmvs3 | | | 79.99 456 | 80.17 454 | 79.45 480 | 84.02 506 | 62.83 502 | 99.05 343 | 93.49 493 | 88.29 389 | 80.06 464 | 86.65 500 | 28.09 508 | 88.00 502 | 88.63 368 | 73.27 460 | 87.54 499 |
|
| PM-MVS | | | 80.47 453 | 78.88 458 | 85.26 468 | 83.79 507 | 72.22 492 | 95.89 474 | 91.08 502 | 85.71 426 | 76.56 480 | 88.30 489 | 36.64 501 | 93.90 473 | 82.39 436 | 69.57 474 | 89.66 486 |
|
| RoMa-HiRes | | | 69.18 469 | 67.02 471 | 75.65 488 | 83.52 508 | 60.31 509 | 90.80 505 | 76.82 522 | 62.46 504 | 62.85 500 | 90.44 479 | 24.75 517 | 83.07 511 | 60.58 506 | 50.97 517 | 83.58 506 |
|
| new-patchmatchnet | | | 81.19 449 | 79.34 457 | 86.76 465 | 82.86 509 | 80.36 480 | 97.92 428 | 95.27 465 | 82.09 457 | 72.02 490 | 86.87 499 | 62.81 468 | 90.74 496 | 71.10 482 | 63.08 491 | 89.19 490 |
|
| FE-MVSNET2 | | | 83.57 444 | 81.36 447 | 90.20 440 | 82.83 510 | 87.59 427 | 98.28 413 | 96.04 446 | 85.33 431 | 74.13 487 | 87.45 495 | 59.16 477 | 93.26 481 | 79.12 460 | 69.91 471 | 89.77 483 |
|
| FE-MVSNET | | | 81.05 451 | 78.81 459 | 87.79 461 | 81.98 511 | 83.70 454 | 98.23 417 | 91.78 501 | 81.27 460 | 74.29 486 | 87.44 496 | 60.92 475 | 90.67 497 | 64.92 498 | 68.43 478 | 89.01 492 |
|
| mvsany_test3 | | | 82.12 448 | 81.14 449 | 85.06 469 | 81.87 512 | 70.41 494 | 97.09 448 | 92.14 498 | 91.27 311 | 77.84 474 | 88.73 487 | 39.31 498 | 95.49 450 | 90.75 340 | 71.24 468 | 89.29 489 |
|
| WB-MVS | | | 76.28 460 | 77.28 462 | 73.29 491 | 81.18 513 | 54.68 515 | 97.87 431 | 94.19 484 | 81.30 459 | 69.43 494 | 90.70 477 | 77.02 388 | 82.06 514 | 35.71 523 | 68.11 481 | 83.13 507 |
|
| test_f | | | 78.40 459 | 77.59 461 | 80.81 479 | 80.82 514 | 62.48 505 | 96.96 452 | 93.08 495 | 83.44 446 | 74.57 485 | 84.57 505 | 27.95 510 | 92.63 485 | 84.15 421 | 72.79 462 | 87.32 500 |
|
| SSC-MVS | | | 75.42 463 | 76.40 464 | 72.49 496 | 80.68 515 | 53.62 516 | 97.42 438 | 94.06 486 | 80.42 464 | 68.75 495 | 90.14 481 | 76.54 396 | 81.66 515 | 33.25 524 | 66.34 485 | 82.19 508 |
|
| pmmvs3 | | | 80.27 454 | 77.77 460 | 87.76 462 | 80.32 516 | 82.43 465 | 98.23 417 | 91.97 499 | 72.74 490 | 78.75 469 | 87.97 492 | 57.30 481 | 90.99 494 | 70.31 483 | 62.37 494 | 89.87 481 |
|
| testf1 | | | 68.38 473 | 66.92 472 | 72.78 493 | 78.80 517 | 50.36 521 | 90.95 503 | 87.35 513 | 55.47 511 | 58.95 504 | 88.14 490 | 20.64 527 | 87.60 504 | 57.28 510 | 64.69 487 | 80.39 515 |
|
| APD_test2 | | | 68.38 473 | 66.92 472 | 72.78 493 | 78.80 517 | 50.36 521 | 90.95 503 | 87.35 513 | 55.47 511 | 58.95 504 | 88.14 490 | 20.64 527 | 87.60 504 | 57.28 510 | 64.69 487 | 80.39 515 |
|
| ambc | | | | | 83.23 474 | 77.17 519 | 62.61 503 | 87.38 509 | 94.55 482 | | 76.72 479 | 86.65 500 | 30.16 505 | 96.36 425 | 84.85 420 | 69.86 472 | 90.73 470 |
|
| test_vis3_rt | | | 68.82 471 | 66.69 475 | 75.21 490 | 76.24 520 | 60.41 508 | 96.44 462 | 68.71 525 | 75.13 485 | 50.54 515 | 69.52 521 | 16.42 533 | 96.32 428 | 80.27 451 | 66.92 484 | 68.89 521 |
|
| PDCNetPlus | | | 59.83 481 | 57.26 484 | 67.55 501 | 76.18 521 | 56.71 513 | 87.01 510 | 45.27 540 | 59.54 507 | 48.80 517 | 83.01 507 | 26.63 512 | 76.54 521 | 62.12 503 | 26.78 532 | 69.40 520 |
|
| usedtu_dtu_shiyan2 | | | 75.87 462 | 72.37 467 | 86.39 466 | 76.18 521 | 75.49 489 | 96.53 460 | 93.82 490 | 64.74 500 | 72.53 489 | 88.48 488 | 37.67 499 | 91.12 493 | 64.13 499 | 57.22 507 | 92.56 448 |
|
| TDRefinement | | | 84.76 434 | 82.56 441 | 91.38 426 | 74.58 523 | 84.80 450 | 97.36 442 | 94.56 481 | 84.73 437 | 80.21 462 | 96.12 369 | 63.56 464 | 98.39 295 | 87.92 386 | 63.97 490 | 90.95 469 |
|
| PMatch-SfM | | | 62.12 480 | 58.57 483 | 72.76 495 | 74.34 524 | 52.97 518 | 84.95 516 | 65.57 526 | 56.89 510 | 46.61 519 | 85.70 504 | 9.51 543 | 80.54 517 | 60.53 507 | 43.03 522 | 84.77 502 |
|
| SIFT-NN | | | 35.94 501 | 36.54 504 | 34.16 517 | 73.93 525 | 29.52 540 | 62.74 530 | 37.28 541 | 19.65 535 | 27.91 537 | 49.19 536 | 11.66 536 | 46.35 536 | 9.19 537 | 37.30 524 | 26.61 534 |
|
| ELoFTR | | | 64.32 479 | 60.56 482 | 75.60 489 | 73.46 526 | 53.20 517 | 86.50 514 | 80.09 519 | 60.74 506 | 45.95 520 | 82.48 509 | 16.05 534 | 89.20 500 | 56.48 514 | 43.34 521 | 84.38 504 |
|
| E-PMN | | | 52.30 493 | 52.18 493 | 52.67 513 | 71.51 527 | 45.40 528 | 93.62 485 | 76.60 523 | 36.01 522 | 43.50 525 | 64.13 530 | 27.11 511 | 67.31 527 | 31.06 525 | 26.06 533 | 45.30 533 |
|
| EMVS | | | 51.44 495 | 51.22 496 | 52.11 514 | 70.71 528 | 44.97 530 | 94.04 480 | 75.66 524 | 35.34 524 | 42.40 528 | 61.56 534 | 28.93 507 | 65.87 528 | 27.64 531 | 24.73 534 | 45.49 531 |
|
| PMMVS2 | | | 67.15 476 | 64.15 479 | 76.14 487 | 70.56 529 | 62.07 506 | 93.89 481 | 87.52 512 | 58.09 509 | 60.02 503 | 78.32 512 | 22.38 522 | 84.54 510 | 59.56 508 | 47.03 519 | 81.80 510 |
|
| PMatch-Up-SfM | | | 57.92 482 | 53.93 486 | 69.90 498 | 69.97 530 | 46.69 525 | 81.36 521 | 55.29 536 | 51.90 514 | 43.17 526 | 82.54 508 | 7.86 548 | 78.44 520 | 57.13 512 | 36.17 526 | 84.58 503 |
|
| SIFT-MNN | | | 34.10 502 | 34.41 505 | 33.17 519 | 68.99 531 | 28.51 541 | 60.22 532 | 36.81 542 | 19.08 538 | 24.04 539 | 47.28 539 | 10.06 540 | 45.04 537 | 8.72 538 | 34.47 527 | 25.97 537 |
|
| SIFT-NCM-Cal | | | 31.73 504 | 31.67 507 | 31.91 522 | 67.18 532 | 27.55 547 | 58.36 534 | 33.09 546 | 18.38 541 | 14.93 546 | 45.16 545 | 8.60 544 | 43.82 539 | 7.62 547 | 31.68 530 | 24.36 540 |
|
| SIFT-NN-NCMNet | | | 33.88 503 | 34.14 506 | 33.10 520 | 66.88 533 | 28.42 542 | 60.42 531 | 36.72 543 | 19.15 536 | 24.06 538 | 47.14 540 | 10.24 538 | 44.77 538 | 8.72 538 | 33.94 529 | 26.10 536 |
|
| FPMVS | | | 68.72 472 | 68.72 470 | 68.71 499 | 65.95 534 | 44.27 532 | 95.97 473 | 94.74 476 | 51.13 515 | 53.26 512 | 90.50 478 | 25.11 515 | 83.00 512 | 60.80 505 | 80.97 417 | 78.87 517 |
|
| SP-DiffGlue | | | 56.84 483 | 55.72 485 | 60.19 508 | 65.70 535 | 40.86 533 | 81.89 518 | 60.28 528 | 34.62 526 | 50.39 516 | 76.88 514 | 26.61 513 | 58.81 533 | 48.21 517 | 56.94 508 | 80.90 514 |
|
| wuyk23d | | | 20.37 516 | 20.84 519 | 18.99 533 | 65.34 536 | 27.73 545 | 50.43 542 | 7.67 557 | 9.50 550 | 8.01 551 | 6.34 551 | 6.13 553 | 26.24 550 | 23.40 533 | 10.69 548 | 2.99 548 |
|
| SIFT-ConvMatch | | | 30.09 507 | 29.76 511 | 31.09 524 | 65.16 537 | 27.56 546 | 54.13 538 | 31.17 547 | 18.55 540 | 17.88 542 | 45.89 542 | 8.40 545 | 42.26 543 | 8.11 543 | 18.51 539 | 23.46 542 |
|
| SIFT-CM-Cal | | | 28.34 510 | 27.90 514 | 29.63 526 | 63.75 538 | 25.98 551 | 50.66 541 | 26.18 551 | 18.12 544 | 16.88 544 | 44.64 546 | 8.08 547 | 39.70 544 | 7.65 546 | 15.19 544 | 23.22 543 |
|
| LCM-MVSNet | | | 67.77 475 | 64.73 478 | 76.87 485 | 62.95 539 | 56.25 514 | 89.37 508 | 93.74 491 | 44.53 517 | 61.99 501 | 80.74 511 | 20.42 529 | 86.53 508 | 69.37 486 | 59.50 505 | 87.84 496 |
|
| SIFT-NN-CMatch | | | 31.71 505 | 31.56 508 | 32.16 521 | 62.58 540 | 27.53 548 | 56.45 535 | 33.28 545 | 19.00 539 | 23.65 540 | 47.34 537 | 10.05 541 | 42.72 541 | 8.71 540 | 22.96 537 | 26.24 535 |
|
| SIFT-UM-Cal | | | 27.47 511 | 27.02 515 | 28.83 529 | 62.12 541 | 24.58 553 | 53.60 539 | 23.46 552 | 18.14 543 | 12.85 548 | 45.56 543 | 7.49 549 | 39.45 545 | 7.68 545 | 12.30 545 | 22.45 544 |
|
| SIFT-UMatch | | | 29.40 509 | 28.87 513 | 30.98 525 | 62.08 542 | 26.57 550 | 56.09 536 | 29.45 549 | 18.31 542 | 15.86 545 | 46.00 541 | 8.23 546 | 42.54 542 | 7.99 544 | 15.81 542 | 23.85 541 |
|
| GLUNet-SfM | | | 51.10 496 | 46.61 499 | 64.56 502 | 61.54 543 | 39.88 534 | 79.38 525 | 65.13 527 | 36.09 521 | 33.36 534 | 69.94 519 | 14.50 535 | 78.76 518 | 42.46 521 | 17.10 541 | 75.02 519 |
|
| SIFT-NN-UMatch | | | 31.23 506 | 31.05 510 | 31.79 523 | 60.08 544 | 27.23 549 | 58.49 533 | 33.65 544 | 19.14 537 | 17.30 543 | 47.31 538 | 10.12 539 | 42.88 540 | 8.67 541 | 24.67 535 | 25.27 538 |
|
| XFeat-NN | | | 42.54 497 | 42.87 501 | 41.54 516 | 59.73 545 | 27.86 544 | 69.53 527 | 45.34 539 | 24.36 532 | 37.16 531 | 64.79 528 | 20.84 526 | 51.40 535 | 30.01 526 | 34.12 528 | 45.36 532 |
|
| MVE |  | 53.74 22 | 51.54 494 | 47.86 498 | 62.60 503 | 59.56 546 | 50.93 519 | 79.41 524 | 77.69 521 | 35.69 523 | 36.27 532 | 61.76 533 | 5.79 554 | 69.63 525 | 37.97 522 | 36.61 525 | 67.24 522 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| SIFT-NN-PointCN | | | 29.63 508 | 29.72 512 | 29.36 527 | 57.55 547 | 23.55 554 | 56.07 537 | 30.57 548 | 17.99 545 | 20.99 541 | 45.21 544 | 9.94 542 | 39.33 546 | 8.40 542 | 20.81 538 | 25.20 539 |
|
| SIFT-PointCN | | | 25.49 512 | 25.71 516 | 24.84 530 | 56.17 548 | 18.65 555 | 51.37 540 | 26.53 550 | 16.31 546 | 12.78 549 | 39.87 549 | 6.41 552 | 34.09 548 | 6.51 549 | 15.42 543 | 21.77 545 |
|
| SIFT-PCN-Cal | | | 24.67 513 | 24.81 517 | 24.24 531 | 56.13 549 | 18.04 556 | 49.05 543 | 23.39 553 | 16.07 547 | 12.99 547 | 40.17 548 | 6.97 551 | 34.68 547 | 6.71 548 | 11.81 546 | 19.99 546 |
|
| XFeat-MNN | | | 41.51 498 | 41.24 502 | 42.32 515 | 55.40 550 | 28.19 543 | 69.39 528 | 46.53 538 | 23.57 533 | 34.47 533 | 63.21 532 | 20.04 530 | 52.41 534 | 27.43 532 | 31.08 531 | 46.37 530 |
|
| SIFT-NCMNet | | | 21.21 515 | 21.22 518 | 21.17 532 | 52.99 551 | 16.41 557 | 42.12 544 | 14.05 555 | 15.89 548 | 10.70 550 | 35.85 550 | 5.14 555 | 29.82 549 | 5.80 550 | 8.44 549 | 17.28 547 |
|
| ANet_high | | | 56.10 484 | 52.24 492 | 67.66 500 | 49.27 552 | 56.82 512 | 83.94 517 | 82.02 518 | 70.47 493 | 33.28 535 | 64.54 529 | 17.23 532 | 69.16 526 | 45.59 519 | 23.85 536 | 77.02 518 |
|
| tmp_tt | | | 65.23 478 | 62.94 481 | 72.13 497 | 44.90 553 | 50.03 523 | 81.05 523 | 89.42 509 | 38.45 519 | 48.51 518 | 99.90 23 | 54.09 484 | 78.70 519 | 91.84 321 | 18.26 540 | 87.64 498 |
|
| PMVS |  | 49.05 23 | 53.75 491 | 51.34 495 | 60.97 504 | 40.80 554 | 34.68 539 | 74.82 526 | 89.62 508 | 37.55 520 | 28.67 536 | 72.12 515 | 7.09 550 | 81.63 516 | 43.17 520 | 68.21 480 | 66.59 523 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| test123 | | | 37.68 500 | 39.14 503 | 33.31 518 | 19.94 555 | 24.83 552 | 98.36 410 | 9.75 556 | 15.53 549 | 51.31 513 | 87.14 498 | 19.62 531 | 17.74 551 | 47.10 518 | 3.47 550 | 57.36 528 |
|
| testmvs | | | 40.60 499 | 44.45 500 | 29.05 528 | 19.49 556 | 14.11 558 | 99.68 232 | 18.47 554 | 20.74 534 | 64.59 499 | 98.48 279 | 10.95 537 | 17.09 552 | 56.66 513 | 11.01 547 | 55.94 529 |
|
| mmdepth | | | 0.00 519 | 0.00 522 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 0.00 553 | 0.00 556 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| monomultidepth | | | 0.00 519 | 0.00 522 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 0.00 553 | 0.00 556 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| test_blank | | | 0.00 519 | 0.00 522 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 0.02 552 | 0.00 556 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| eth-test2 | | | | | | 0.00 557 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 557 | | | | | | | | | | | |
|
| uanet_test | | | 0.00 519 | 0.00 522 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 0.00 553 | 0.00 556 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| DCPMVS | | | 0.00 519 | 0.00 522 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 0.00 553 | 0.00 556 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| cdsmvs_eth3d_5k | | | 23.43 514 | 31.24 509 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 98.09 234 | 0.00 552 | 0.00 553 | 99.67 114 | 83.37 315 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| pcd_1.5k_mvsjas | | | 7.60 518 | 10.13 521 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 0.00 553 | 91.20 177 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| sosnet-low-res | | | 0.00 519 | 0.00 522 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 0.00 553 | 0.00 556 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| sosnet | | | 0.00 519 | 0.00 522 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 0.00 553 | 0.00 556 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| uncertanet | | | 0.00 519 | 0.00 522 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 0.00 553 | 0.00 556 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| Regformer | | | 0.00 519 | 0.00 522 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 0.00 553 | 0.00 556 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| ab-mvs-re | | | 8.28 517 | 11.04 520 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 99.40 147 | 0.00 556 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| uanet | | | 0.00 519 | 0.00 522 | 0.00 534 | 0.00 557 | 0.00 559 | 0.00 545 | 0.00 558 | 0.00 552 | 0.00 553 | 0.00 553 | 0.00 556 | 0.00 553 | 0.00 551 | 0.00 551 | 0.00 549 |
|
| WAC-MVS | | | | | | | 90.97 370 | | | | | | | | 86.10 410 | | |
|
| PC_three_1452 | | | | | | | | | | 96.96 60 | 99.80 28 | 99.79 63 | 97.49 11 | 100.00 1 | 99.99 5 | 99.98 32 | 100.00 1 |
|
| test_241102_TWO | | | | | | | | | 98.43 156 | 97.27 47 | 99.80 28 | 99.94 5 | 97.18 23 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
| test_0728_THIRD | | | | | | | | | | 96.48 80 | 99.83 24 | 99.91 19 | 97.87 6 | 100.00 1 | 99.92 16 | 100.00 1 | 100.00 1 |
|
| GSMVS | | | | | | | | | | | | | | | | | 99.59 154 |
|
| sam_mvs1 | | | | | | | | | | | | | 94.72 74 | | | | 99.59 154 |
|
| sam_mvs | | | | | | | | | | | | | 94.25 94 | | | | |
|
| MTGPA |  | | | | | | | | 98.28 204 | | | | | | | | |
|
| test_post1 | | | | | | | | 95.78 475 | | | | 59.23 535 | 93.20 128 | 97.74 342 | 91.06 331 | | |
|
| test_post | | | | | | | | | | | | 63.35 531 | 94.43 82 | 98.13 321 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 91.70 472 | 95.12 60 | 97.95 333 | | | |
|
| MTMP | | | | | | | | 99.87 133 | 96.49 436 | | | | | | | | |
|
| test9_res | | | | | | | | | | | | | | | 99.71 48 | 99.99 21 | 100.00 1 |
|
| agg_prior2 | | | | | | | | | | | | | | | 99.48 63 | 100.00 1 | 100.00 1 |
|
| test_prior4 | | | | | | | 98.05 82 | 99.94 93 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 99.95 75 | | 95.78 105 | 99.73 47 | 99.76 73 | 96.00 41 | | 99.78 35 | 100.00 1 | |
|
| 旧先验2 | | | | | | | | 99.46 283 | | 94.21 166 | 99.85 20 | | | 99.95 85 | 96.96 201 | | |
|
| 新几何2 | | | | | | | | 99.40 288 | | | | | | | | | |
|
| 无先验 | | | | | | | | 99.49 275 | 98.71 79 | 93.46 202 | | | | 100.00 1 | 94.36 268 | | 99.99 26 |
|
| 原ACMM2 | | | | | | | | 99.90 117 | | | | | | | | | |
|
| testdata2 | | | | | | | | | | | | | | 99.99 39 | 90.54 344 | | |
|
| segment_acmp | | | | | | | | | | | | | 96.68 31 | | | | |
|
| testdata1 | | | | | | | | 99.28 314 | | 96.35 91 | | | | | | | |
|
| plane_prior5 | | | | | | | | | 97.87 258 | | | | | 98.37 301 | 97.79 170 | 89.55 331 | 94.52 346 |
|
| plane_prior4 | | | | | | | | | | | | 98.59 265 | | | | | |
|
| plane_prior3 | | | | | | | 91.64 357 | | | 96.63 75 | 93.01 306 | | | | | | |
|
| plane_prior2 | | | | | | | | 99.84 152 | | 96.38 86 | | | | | | | |
|
| plane_prior | | | | | | | 91.74 349 | 99.86 144 | | 96.76 70 | | | | | | 89.59 330 | |
|
| n2 | | | | | | | | | 0.00 558 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 558 | | | | | | | | |
|
| door-mid | | | | | | | | | 89.69 506 | | | | | | | | |
|
| test11 | | | | | | | | | 98.44 148 | | | | | | | | |
|
| door | | | | | | | | | 90.31 503 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 91.85 342 | | | | | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 97.92 159 | | |
|
| HQP4-MVS | | | | | | | | | | | 93.37 301 | | | 98.39 295 | | | 94.53 344 |
|
| HQP3-MVS | | | | | | | | | 97.89 256 | | | | | | | 89.60 328 | |
|
| HQP2-MVS | | | | | | | | | | | | | 80.65 351 | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 96.26 170 | 96.11 469 | | 91.89 286 | 98.06 170 | | 94.40 84 | | 94.30 271 | | 99.67 133 |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 87.04 364 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 88.23 351 | |
|
| Test By Simon | | | | | | | | | | | | | 92.82 139 | | | | |
|