| AdaColmap |  | | 97.23 126 | 96.80 135 | 98.51 128 | 99.99 1 | 95.60 194 | 99.09 296 | 98.84 62 | 93.32 197 | 96.74 206 | 99.72 89 | 86.04 254 | 100.00 1 | 98.01 147 | 99.43 124 | 99.94 82 |
|
| CNVR-MVS | | | 99.40 1 | 99.26 1 | 99.84 6 | 99.98 2 | 99.51 6 | 99.98 20 | 98.69 77 | 98.20 9 | 99.93 2 | 99.98 2 | 96.82 24 | 100.00 1 | 99.75 37 | 100.00 1 | 99.99 23 |
|
| MCST-MVS | | | 99.32 3 | 99.14 4 | 99.86 5 | 99.97 3 | 99.59 5 | 99.97 38 | 98.64 86 | 98.47 3 | 99.13 102 | 99.92 13 | 96.38 34 | 100.00 1 | 99.74 39 | 100.00 1 | 100.00 1 |
|
| mPP-MVS | | | 98.39 53 | 98.20 51 | 98.97 88 | 99.97 3 | 96.92 133 | 99.95 67 | 98.38 179 | 95.04 118 | 98.61 133 | 99.80 54 | 93.39 114 | 100.00 1 | 98.64 110 | 100.00 1 | 99.98 52 |
|
| CPTT-MVS | | | 97.64 106 | 97.32 110 | 98.58 117 | 99.97 3 | 95.77 183 | 99.96 48 | 98.35 185 | 89.90 328 | 98.36 148 | 99.79 58 | 91.18 173 | 99.99 36 | 98.37 126 | 99.99 21 | 99.99 23 |
|
| DP-MVS Recon | | | 98.41 50 | 98.02 65 | 99.56 25 | 99.97 3 | 98.70 48 | 99.92 94 | 98.44 143 | 92.06 261 | 98.40 147 | 99.84 44 | 95.68 44 | 100.00 1 | 98.19 136 | 99.71 88 | 99.97 62 |
|
| PAPR | | | 98.52 40 | 98.16 55 | 99.58 24 | 99.97 3 | 98.77 42 | 99.95 67 | 98.43 151 | 95.35 112 | 98.03 162 | 99.75 75 | 94.03 99 | 99.98 47 | 98.11 141 | 99.83 77 | 99.99 23 |
|
| HFP-MVS | | | 98.56 36 | 98.37 40 | 99.14 68 | 99.96 8 | 97.43 109 | 99.95 67 | 98.61 94 | 94.77 128 | 99.31 91 | 99.85 33 | 94.22 92 | 100.00 1 | 98.70 105 | 99.98 32 | 99.98 52 |
|
| region2R | | | 98.54 38 | 98.37 40 | 99.05 78 | 99.96 8 | 97.18 119 | 99.96 48 | 98.55 114 | 94.87 125 | 99.45 78 | 99.85 33 | 94.07 98 | 100.00 1 | 98.67 107 | 100.00 1 | 99.98 52 |
|
| ACMMPR | | | 98.50 41 | 98.32 44 | 99.05 78 | 99.96 8 | 97.18 119 | 99.95 67 | 98.60 96 | 94.77 128 | 99.31 91 | 99.84 44 | 93.73 108 | 100.00 1 | 98.70 105 | 99.98 32 | 99.98 52 |
|
| NCCC | | | 99.37 2 | 99.25 2 | 99.71 15 | 99.96 8 | 99.15 22 | 99.97 38 | 98.62 93 | 98.02 21 | 99.90 6 | 99.95 3 | 97.33 17 | 100.00 1 | 99.54 54 | 100.00 1 | 100.00 1 |
|
| CP-MVS | | | 98.45 45 | 98.32 44 | 98.87 93 | 99.96 8 | 96.62 146 | 99.97 38 | 98.39 175 | 94.43 145 | 98.90 114 | 99.87 27 | 94.30 89 | 100.00 1 | 99.04 80 | 99.99 21 | 99.99 23 |
|
| test_one_0601 | | | | | | 99.94 13 | 99.30 12 | | 98.41 168 | 96.63 72 | 99.75 39 | 99.93 11 | 97.49 10 | | | | |
|
| test_0728_SECOND | | | | | 99.82 7 | 99.94 13 | 99.47 7 | 99.95 67 | 98.43 151 | | | | | 100.00 1 | 99.99 5 | 100.00 1 | 100.00 1 |
|
| XVS | | | 98.70 29 | 98.55 28 | 99.15 66 | 99.94 13 | 97.50 105 | 99.94 84 | 98.42 163 | 96.22 89 | 99.41 83 | 99.78 62 | 94.34 86 | 99.96 71 | 98.92 90 | 99.95 50 | 99.99 23 |
|
| X-MVStestdata | | | 93.83 265 | 92.06 300 | 99.15 66 | 99.94 13 | 97.50 105 | 99.94 84 | 98.42 163 | 96.22 89 | 99.41 83 | 41.37 473 | 94.34 86 | 99.96 71 | 98.92 90 | 99.95 50 | 99.99 23 |
|
| test_prior | | | | | 99.43 36 | 99.94 13 | 98.49 61 | | 98.65 83 | | | | | 99.80 137 | | | 99.99 23 |
|
| MSLP-MVS++ | | | 99.13 8 | 99.01 11 | 99.49 32 | 99.94 13 | 98.46 62 | 99.98 20 | 98.86 56 | 97.10 52 | 99.80 25 | 99.94 4 | 95.92 40 | 100.00 1 | 99.51 55 | 100.00 1 | 100.00 1 |
|
| APDe-MVS |  | | 99.06 11 | 98.91 14 | 99.51 29 | 99.94 13 | 98.76 45 | 99.91 102 | 98.39 175 | 97.20 50 | 99.46 77 | 99.85 33 | 95.53 48 | 99.79 139 | 99.86 23 | 100.00 1 | 99.99 23 |
| Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition |
| MP-MVS |  | | 98.23 68 | 97.97 69 | 99.03 80 | 99.94 13 | 97.17 122 | 99.95 67 | 98.39 175 | 94.70 132 | 98.26 154 | 99.81 53 | 91.84 164 | 100.00 1 | 98.85 96 | 99.97 42 | 99.93 83 |
| Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
| CDPH-MVS | | | 98.65 32 | 98.36 42 | 99.49 32 | 99.94 13 | 98.73 46 | 99.87 124 | 98.33 190 | 93.97 170 | 99.76 38 | 99.87 27 | 94.99 64 | 99.75 148 | 98.55 114 | 100.00 1 | 99.98 52 |
|
| PAPM_NR | | | 98.12 72 | 97.93 75 | 98.70 104 | 99.94 13 | 96.13 172 | 99.82 153 | 98.43 151 | 94.56 136 | 97.52 179 | 99.70 95 | 94.40 81 | 99.98 47 | 97.00 184 | 99.98 32 | 99.99 23 |
|
| MG-MVS | | | 98.91 19 | 98.65 24 | 99.68 16 | 99.94 13 | 99.07 24 | 99.64 213 | 99.44 19 | 97.33 43 | 99.00 110 | 99.72 89 | 94.03 99 | 99.98 47 | 98.73 104 | 100.00 1 | 100.00 1 |
|
| SED-MVS | | | 99.28 5 | 99.11 7 | 99.77 8 | 99.93 24 | 99.30 12 | 99.96 48 | 98.43 151 | 97.27 46 | 99.80 25 | 99.94 4 | 96.71 27 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
| IU-MVS | | | | | | 99.93 24 | 99.31 10 | | 98.41 168 | 97.71 30 | 99.84 20 | | | | 100.00 1 | 100.00 1 | 100.00 1 |
|
| test_241102_ONE | | | | | | 99.93 24 | 99.30 12 | | 98.43 151 | 97.26 48 | 99.80 25 | 99.88 24 | 96.71 27 | 100.00 1 | | | |
|
| DVP-MVS |  | | 99.30 4 | 99.16 3 | 99.73 12 | 99.93 24 | 99.29 15 | 99.95 67 | 98.32 192 | 97.28 44 | 99.83 21 | 99.91 14 | 97.22 19 | 100.00 1 | 99.99 5 | 100.00 1 | 99.89 92 |
| 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 24 | 99.29 15 | 99.96 48 | 98.42 163 | 97.28 44 | 99.86 14 | 99.94 4 | 97.22 19 | | | | |
|
| MSP-MVS | | | 99.09 9 | 99.12 5 | 98.98 87 | 99.93 24 | 97.24 116 | 99.95 67 | 98.42 163 | 97.50 37 | 99.52 73 | 99.88 24 | 97.43 16 | 99.71 154 | 99.50 57 | 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 24 | 98.77 42 | | 98.43 151 | | 99.63 56 | | | 99.85 124 | | | |
|
| FOURS1 | | | | | | 99.92 31 | 97.66 99 | 99.95 67 | 98.36 183 | 95.58 106 | 99.52 73 | | | | | | |
|
| ZD-MVS | | | | | | 99.92 31 | 98.57 56 | | 98.52 123 | 92.34 249 | 99.31 91 | 99.83 46 | 95.06 59 | 99.80 137 | 99.70 45 | 99.97 42 | |
|
| GST-MVS | | | 98.27 60 | 97.97 69 | 99.17 61 | 99.92 31 | 97.57 101 | 99.93 91 | 98.39 175 | 94.04 168 | 98.80 119 | 99.74 82 | 92.98 130 | 100.00 1 | 98.16 138 | 99.76 85 | 99.93 83 |
|
| TEST9 | | | | | | 99.92 31 | 98.92 29 | 99.96 48 | 98.43 151 | 93.90 176 | 99.71 46 | 99.86 29 | 95.88 41 | 99.85 124 | | | |
|
| train_agg | | | 98.88 20 | 98.65 24 | 99.59 23 | 99.92 31 | 98.92 29 | 99.96 48 | 98.43 151 | 94.35 150 | 99.71 46 | 99.86 29 | 95.94 38 | 99.85 124 | 99.69 46 | 99.98 32 | 99.99 23 |
|
| test_8 | | | | | | 99.92 31 | 98.88 32 | 99.96 48 | 98.43 151 | 94.35 150 | 99.69 48 | 99.85 33 | 95.94 38 | 99.85 124 | | | |
|
| PGM-MVS | | | 98.34 55 | 98.13 57 | 98.99 85 | 99.92 31 | 97.00 129 | 99.75 177 | 99.50 17 | 93.90 176 | 99.37 88 | 99.76 67 | 93.24 123 | 100.00 1 | 97.75 166 | 99.96 46 | 99.98 52 |
|
| ACMMP |  | | 97.74 99 | 97.44 103 | 98.66 108 | 99.92 31 | 96.13 172 | 99.18 289 | 99.45 18 | 94.84 126 | 96.41 220 | 99.71 92 | 91.40 167 | 99.99 36 | 97.99 149 | 98.03 184 | 99.87 95 |
| 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 9 | 99.77 8 | 99.91 39 | 99.31 10 | 99.95 67 | 98.43 151 | 96.48 77 | 99.80 25 | 99.93 11 | 97.44 14 | 100.00 1 | 99.92 13 | 99.98 32 | 100.00 1 |
|
| MSC_two_6792asdad | | | | | 99.93 2 | 99.91 39 | 99.80 2 | | 98.41 168 | | | | | 100.00 1 | 99.96 9 | 100.00 1 | 100.00 1 |
|
| No_MVS | | | | | 99.93 2 | 99.91 39 | 99.80 2 | | 98.41 168 | | | | | 100.00 1 | 99.96 9 | 100.00 1 | 100.00 1 |
|
| HPM-MVS++ |  | | 99.07 10 | 98.88 16 | 99.63 17 | 99.90 42 | 99.02 25 | 99.95 67 | 98.56 108 | 97.56 36 | 99.44 79 | 99.85 33 | 95.38 52 | 100.00 1 | 99.31 67 | 99.99 21 | 99.87 95 |
|
| APD-MVS |  | | 98.62 33 | 98.35 43 | 99.41 39 | 99.90 42 | 98.51 59 | 99.87 124 | 98.36 183 | 94.08 163 | 99.74 42 | 99.73 86 | 94.08 97 | 99.74 150 | 99.42 63 | 99.99 21 | 99.99 23 |
| Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
| DeepC-MVS_fast | | 96.59 1 | 98.81 23 | 98.54 29 | 99.62 20 | 99.90 42 | 98.85 35 | 99.24 284 | 98.47 135 | 98.14 15 | 99.08 105 | 99.91 14 | 93.09 127 | 100.00 1 | 99.04 80 | 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 45 | 99.80 2 | 99.96 48 | | | | 99.80 54 | 97.44 14 | 100.00 1 | 100.00 1 | 99.98 32 | 100.00 1 |
|
| DPE-MVS |  | | 99.26 6 | 99.10 8 | 99.74 11 | 99.89 45 | 99.24 19 | 99.87 124 | 98.44 143 | 97.48 38 | 99.64 55 | 99.94 4 | 96.68 29 | 99.99 36 | 99.99 5 | 100.00 1 | 99.99 23 |
| Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
| test_part2 | | | | | | 99.89 45 | 99.25 18 | | | | 99.49 76 | | | | | | |
|
| CSCG | | | 97.10 132 | 97.04 122 | 97.27 222 | 99.89 45 | 91.92 311 | 99.90 108 | 99.07 37 | 88.67 352 | 95.26 252 | 99.82 49 | 93.17 126 | 99.98 47 | 98.15 139 | 99.47 119 | 99.90 91 |
|
| ZNCC-MVS | | | 98.31 57 | 98.03 64 | 99.17 61 | 99.88 49 | 97.59 100 | 99.94 84 | 98.44 143 | 94.31 153 | 98.50 140 | 99.82 49 | 93.06 128 | 99.99 36 | 98.30 130 | 99.99 21 | 99.93 83 |
|
| SR-MVS | | | 98.46 44 | 98.30 47 | 98.93 91 | 99.88 49 | 97.04 128 | 99.84 143 | 98.35 185 | 94.92 122 | 99.32 90 | 99.80 54 | 93.35 116 | 99.78 141 | 99.30 68 | 99.95 50 | 99.96 70 |
|
| 9.14 | | | | 98.38 38 | | 99.87 51 | | 99.91 102 | 98.33 190 | 93.22 200 | 99.78 36 | 99.89 22 | 94.57 77 | 99.85 124 | 99.84 25 | 99.97 42 | |
|
| SMA-MVS |  | | 98.76 26 | 98.48 32 | 99.62 20 | 99.87 51 | 98.87 33 | 99.86 135 | 98.38 179 | 93.19 201 | 99.77 37 | 99.94 4 | 95.54 46 | 100.00 1 | 99.74 39 | 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 81 | 97.85 81 | 98.04 160 | 99.86 53 | 95.39 204 | 99.61 220 | 97.78 259 | 96.52 75 | 98.61 133 | 99.31 151 | 92.73 138 | 99.67 162 | 96.77 194 | 99.48 116 | 99.06 235 |
|
| lecture | | | 98.67 30 | 98.46 33 | 99.28 48 | 99.86 53 | 97.88 87 | 99.97 38 | 99.25 30 | 96.07 93 | 99.79 34 | 99.70 95 | 92.53 146 | 99.98 47 | 99.51 55 | 99.48 116 | 99.97 62 |
|
| PHI-MVS | | | 98.41 50 | 98.21 50 | 99.03 80 | 99.86 53 | 97.10 126 | 99.98 20 | 98.80 68 | 90.78 308 | 99.62 59 | 99.78 62 | 95.30 53 | 100.00 1 | 99.80 28 | 99.93 61 | 99.99 23 |
|
| MTAPA | | | 98.29 59 | 97.96 72 | 99.30 47 | 99.85 56 | 97.93 85 | 99.39 262 | 98.28 199 | 95.76 100 | 97.18 193 | 99.88 24 | 92.74 137 | 100.00 1 | 98.67 107 | 99.88 73 | 99.99 23 |
|
| LS3D | | | 95.84 197 | 95.11 210 | 98.02 161 | 99.85 56 | 95.10 222 | 98.74 346 | 98.50 132 | 87.22 374 | 93.66 273 | 99.86 29 | 87.45 231 | 99.95 80 | 90.94 311 | 99.81 83 | 99.02 239 |
|
| HPM-MVS |  | | 97.96 76 | 97.72 86 | 98.68 105 | 99.84 58 | 96.39 158 | 99.90 108 | 98.17 214 | 92.61 234 | 98.62 132 | 99.57 125 | 91.87 163 | 99.67 162 | 98.87 95 | 99.99 21 | 99.99 23 |
| 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 60 | 98.11 59 | 98.75 101 | 99.83 59 | 96.59 150 | 99.40 258 | 98.51 126 | 95.29 114 | 98.51 139 | 99.76 67 | 93.60 112 | 99.71 154 | 98.53 117 | 99.52 109 | 99.95 78 |
|
| save fliter | | | | | | 99.82 60 | 98.79 40 | 99.96 48 | 98.40 172 | 97.66 32 | | | | | | | |
|
| PLC |  | 95.54 3 | 97.93 79 | 97.89 79 | 98.05 159 | 99.82 60 | 94.77 232 | 99.92 94 | 98.46 137 | 93.93 173 | 97.20 191 | 99.27 156 | 95.44 51 | 99.97 59 | 97.41 171 | 99.51 112 | 99.41 186 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| APD-MVS_3200maxsize | | | 98.25 65 | 98.08 61 | 98.78 98 | 99.81 62 | 96.60 148 | 99.82 153 | 98.30 197 | 93.95 172 | 99.37 88 | 99.77 65 | 92.84 134 | 99.76 147 | 98.95 86 | 99.92 64 | 99.97 62 |
|
| EI-MVSNet-UG-set | | | 98.14 71 | 97.99 67 | 98.60 113 | 99.80 63 | 96.27 161 | 99.36 268 | 98.50 132 | 95.21 116 | 98.30 151 | 99.75 75 | 93.29 120 | 99.73 153 | 98.37 126 | 99.30 133 | 99.81 104 |
|
| SR-MVS-dyc-post | | | 98.31 57 | 98.17 54 | 98.71 103 | 99.79 64 | 96.37 159 | 99.76 173 | 98.31 194 | 94.43 145 | 99.40 85 | 99.75 75 | 93.28 121 | 99.78 141 | 98.90 93 | 99.92 64 | 99.97 62 |
|
| RE-MVS-def | | | | 98.13 57 | | 99.79 64 | 96.37 159 | 99.76 173 | 98.31 194 | 94.43 145 | 99.40 85 | 99.75 75 | 92.95 131 | | 98.90 93 | 99.92 64 | 99.97 62 |
|
| HPM-MVS_fast | | | 97.80 93 | 97.50 99 | 98.68 105 | 99.79 64 | 96.42 154 | 99.88 121 | 98.16 219 | 91.75 272 | 98.94 112 | 99.54 128 | 91.82 165 | 99.65 166 | 97.62 169 | 99.99 21 | 99.99 23 |
|
| SF-MVS | | | 98.67 30 | 98.40 36 | 99.50 30 | 99.77 67 | 98.67 49 | 99.90 108 | 98.21 209 | 93.53 188 | 99.81 23 | 99.89 22 | 94.70 73 | 99.86 123 | 99.84 25 | 99.93 61 | 99.96 70 |
|
| MGCNet | | | 99.06 11 | 98.84 17 | 99.72 13 | 99.76 68 | 99.21 21 | 99.99 5 | 99.34 25 | 98.70 2 | 99.44 79 | 99.75 75 | 93.24 123 | 99.99 36 | 99.94 11 | 99.41 126 | 99.95 78 |
|
| 旧先验1 | | | | | | 99.76 68 | 97.52 103 | | 98.64 86 | | | 99.85 33 | 95.63 45 | | | 99.94 55 | 99.99 23 |
|
| OMC-MVS | | | 97.28 122 | 97.23 114 | 97.41 212 | 99.76 68 | 93.36 278 | 99.65 209 | 97.95 240 | 96.03 94 | 97.41 184 | 99.70 95 | 89.61 199 | 99.51 172 | 96.73 196 | 98.25 174 | 99.38 188 |
|
| 新几何1 | | | | | 99.42 38 | 99.75 71 | 98.27 66 | | 98.63 92 | 92.69 229 | 99.55 68 | 99.82 49 | 94.40 81 | 100.00 1 | 91.21 303 | 99.94 55 | 99.99 23 |
|
| MP-MVS-pluss | | | 98.07 75 | 97.64 92 | 99.38 44 | 99.74 72 | 98.41 64 | 99.74 180 | 98.18 213 | 93.35 195 | 96.45 217 | 99.85 33 | 92.64 141 | 99.97 59 | 98.91 92 | 99.89 70 | 99.77 111 |
| MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
| TSAR-MVS + MP. | | | 98.93 17 | 98.77 19 | 99.41 39 | 99.74 72 | 98.67 49 | 99.77 167 | 98.38 179 | 96.73 68 | 99.88 11 | 99.74 82 | 94.89 66 | 99.59 168 | 99.80 28 | 99.98 32 | 99.97 62 |
| 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 36 | 99.74 72 | 98.56 57 | | 98.40 172 | | 99.65 52 | | 94.76 69 | 99.75 148 | | 99.98 32 | 99.99 23 |
|
| 原ACMM1 | | | | | 98.96 89 | 99.73 75 | 96.99 130 | | 98.51 126 | 94.06 166 | 99.62 59 | 99.85 33 | 94.97 65 | 99.96 71 | 95.11 224 | 99.95 50 | 99.92 88 |
|
| TSAR-MVS + GP. | | | 98.60 34 | 98.51 31 | 98.86 94 | 99.73 75 | 96.63 145 | 99.97 38 | 97.92 245 | 98.07 18 | 98.76 125 | 99.55 126 | 95.00 63 | 99.94 88 | 99.91 16 | 97.68 191 | 99.99 23 |
|
| CANet | | | 98.27 60 | 97.82 83 | 99.63 17 | 99.72 77 | 99.10 23 | 99.98 20 | 98.51 126 | 97.00 58 | 98.52 137 | 99.71 92 | 87.80 223 | 99.95 80 | 99.75 37 | 99.38 128 | 99.83 100 |
|
| reproduce_model | | | 98.75 27 | 98.66 23 | 99.03 80 | 99.71 78 | 97.10 126 | 99.73 187 | 98.23 207 | 97.02 57 | 99.18 100 | 99.90 18 | 94.54 78 | 99.99 36 | 99.77 33 | 99.90 69 | 99.99 23 |
|
| F-COLMAP | | | 96.93 144 | 96.95 125 | 96.87 235 | 99.71 78 | 91.74 316 | 99.85 138 | 97.95 240 | 93.11 207 | 95.72 241 | 99.16 174 | 92.35 152 | 99.94 88 | 95.32 220 | 99.35 131 | 98.92 247 |
|
| reproduce-ours | | | 98.78 24 | 98.67 21 | 99.09 75 | 99.70 80 | 97.30 113 | 99.74 180 | 98.25 203 | 97.10 52 | 99.10 103 | 99.90 18 | 94.59 74 | 99.99 36 | 99.77 33 | 99.91 67 | 99.99 23 |
|
| our_new_method | | | 98.78 24 | 98.67 21 | 99.09 75 | 99.70 80 | 97.30 113 | 99.74 180 | 98.25 203 | 97.10 52 | 99.10 103 | 99.90 18 | 94.59 74 | 99.99 36 | 99.77 33 | 99.91 67 | 99.99 23 |
|
| SD-MVS | | | 98.92 18 | 98.70 20 | 99.56 25 | 99.70 80 | 98.73 46 | 99.94 84 | 98.34 189 | 96.38 83 | 99.81 23 | 99.76 67 | 94.59 74 | 99.98 47 | 99.84 25 | 99.96 46 | 99.97 62 |
| 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 66 | 99.12 5 | 95.59 276 | 99.67 83 | 86.91 399 | 99.95 67 | 98.89 52 | 97.60 33 | 99.90 6 | 99.76 67 | 96.54 32 | 99.98 47 | 99.94 11 | 99.82 81 | 99.88 93 |
|
| ACMMP_NAP | | | 98.49 42 | 98.14 56 | 99.54 27 | 99.66 84 | 98.62 55 | 99.85 138 | 98.37 182 | 94.68 133 | 99.53 71 | 99.83 46 | 92.87 133 | 100.00 1 | 98.66 109 | 99.84 76 | 99.99 23 |
|
| DeepPCF-MVS | | 95.94 2 | 97.71 103 | 98.98 12 | 93.92 342 | 99.63 85 | 81.76 434 | 99.96 48 | 98.56 108 | 99.47 1 | 99.19 99 | 99.99 1 | 94.16 96 | 100.00 1 | 99.92 13 | 99.93 61 | 100.00 1 |
|
| EPNet | | | 98.49 42 | 98.40 36 | 98.77 100 | 99.62 86 | 96.80 139 | 99.90 108 | 99.51 16 | 97.60 33 | 99.20 97 | 99.36 146 | 93.71 109 | 99.91 105 | 97.99 149 | 98.71 159 | 99.61 142 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| MM | | | 98.83 21 | 98.53 30 | 99.76 10 | 99.59 87 | 99.33 8 | 99.99 5 | 99.76 6 | 98.39 4 | 99.39 87 | 99.80 54 | 90.49 188 | 99.96 71 | 99.89 18 | 99.43 124 | 99.98 52 |
|
| PVSNet_BlendedMVS | | | 96.05 188 | 95.82 182 | 96.72 241 | 99.59 87 | 96.99 130 | 99.95 67 | 99.10 34 | 94.06 166 | 98.27 152 | 95.80 347 | 89.00 211 | 99.95 80 | 99.12 74 | 87.53 339 | 93.24 401 |
|
| PVSNet_Blended | | | 97.94 78 | 97.64 92 | 98.83 95 | 99.59 87 | 96.99 130 | 100.00 1 | 99.10 34 | 95.38 111 | 98.27 152 | 99.08 178 | 89.00 211 | 99.95 80 | 99.12 74 | 99.25 135 | 99.57 153 |
|
| PatchMatch-RL | | | 96.04 189 | 95.40 197 | 97.95 163 | 99.59 87 | 95.22 217 | 99.52 240 | 99.07 37 | 93.96 171 | 96.49 216 | 98.35 262 | 82.28 300 | 99.82 136 | 90.15 327 | 99.22 138 | 98.81 254 |
|
| dcpmvs_2 | | | 97.42 117 | 98.09 60 | 95.42 283 | 99.58 91 | 87.24 395 | 99.23 285 | 96.95 374 | 94.28 156 | 98.93 113 | 99.73 86 | 94.39 84 | 99.16 200 | 99.89 18 | 99.82 81 | 99.86 97 |
|
| test222 | | | | | | 99.55 92 | 97.41 111 | 99.34 270 | 98.55 114 | 91.86 267 | 99.27 95 | 99.83 46 | 93.84 106 | | | 99.95 50 | 99.99 23 |
|
| CNLPA | | | 97.76 97 | 97.38 106 | 98.92 92 | 99.53 93 | 96.84 135 | 99.87 124 | 98.14 223 | 93.78 180 | 96.55 214 | 99.69 99 | 92.28 154 | 99.98 47 | 97.13 179 | 99.44 123 | 99.93 83 |
|
| API-MVS | | | 97.86 84 | 97.66 90 | 98.47 130 | 99.52 94 | 95.41 202 | 99.47 250 | 98.87 55 | 91.68 273 | 98.84 116 | 99.85 33 | 92.34 153 | 99.99 36 | 98.44 122 | 99.96 46 | 100.00 1 |
|
| PVSNet | | 91.05 13 | 97.13 131 | 96.69 141 | 98.45 132 | 99.52 94 | 95.81 181 | 99.95 67 | 99.65 12 | 94.73 130 | 99.04 108 | 99.21 167 | 84.48 283 | 99.95 80 | 94.92 230 | 98.74 158 | 99.58 151 |
|
| 114514_t | | | 97.41 118 | 96.83 132 | 99.14 68 | 99.51 96 | 97.83 89 | 99.89 118 | 98.27 201 | 88.48 356 | 99.06 107 | 99.66 110 | 90.30 191 | 99.64 167 | 96.32 205 | 99.97 42 | 99.96 70 |
|
| cl22 | | | 93.77 270 | 93.25 274 | 95.33 287 | 99.49 97 | 94.43 240 | 99.61 220 | 98.09 226 | 90.38 316 | 89.16 343 | 95.61 355 | 90.56 186 | 97.34 329 | 91.93 294 | 84.45 360 | 94.21 346 |
|
| testdata | | | | | 98.42 136 | 99.47 98 | 95.33 208 | | 98.56 108 | 93.78 180 | 99.79 34 | 99.85 33 | 93.64 111 | 99.94 88 | 94.97 228 | 99.94 55 | 100.00 1 |
|
| MAR-MVS | | | 97.43 113 | 97.19 116 | 98.15 152 | 99.47 98 | 94.79 231 | 99.05 307 | 98.76 69 | 92.65 232 | 98.66 130 | 99.82 49 | 88.52 217 | 99.98 47 | 98.12 140 | 99.63 94 | 99.67 125 |
| 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 | | | 94.54 242 | 93.42 264 | 97.91 169 | 99.46 100 | 94.04 255 | 98.93 325 | 97.48 296 | 81.15 428 | 90.04 314 | 99.55 126 | 87.02 239 | 99.95 80 | 88.97 339 | 98.11 180 | 99.73 115 |
|
| MVS_111021_LR | | | 98.42 49 | 98.38 38 | 98.53 125 | 99.39 101 | 95.79 182 | 99.87 124 | 99.86 2 | 96.70 69 | 98.78 120 | 99.79 58 | 92.03 160 | 99.90 107 | 99.17 73 | 99.86 75 | 99.88 93 |
|
| CHOSEN 280x420 | | | 99.01 14 | 99.03 10 | 98.95 90 | 99.38 102 | 98.87 33 | 98.46 365 | 99.42 21 | 97.03 56 | 99.02 109 | 99.09 177 | 99.35 2 | 98.21 291 | 99.73 41 | 99.78 84 | 99.77 111 |
|
| MVS_111021_HR | | | 98.72 28 | 98.62 26 | 99.01 84 | 99.36 103 | 97.18 119 | 99.93 91 | 99.90 1 | 96.81 66 | 98.67 129 | 99.77 65 | 93.92 101 | 99.89 112 | 99.27 69 | 99.94 55 | 99.96 70 |
|
| DPM-MVS | | | 98.83 21 | 98.46 33 | 99.97 1 | 99.33 104 | 99.92 1 | 99.96 48 | 98.44 143 | 97.96 22 | 99.55 68 | 99.94 4 | 97.18 21 | 100.00 1 | 93.81 261 | 99.94 55 | 99.98 52 |
|
| TAPA-MVS | | 92.12 8 | 94.42 250 | 93.60 256 | 96.90 234 | 99.33 104 | 91.78 315 | 99.78 162 | 98.00 234 | 89.89 329 | 94.52 258 | 99.47 132 | 91.97 161 | 99.18 197 | 69.90 445 | 99.52 109 | 99.73 115 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| reproduce_monomvs | | | 95.38 214 | 95.07 212 | 96.32 256 | 99.32 106 | 96.60 148 | 99.76 173 | 98.85 59 | 96.65 71 | 87.83 365 | 96.05 344 | 99.52 1 | 98.11 296 | 96.58 200 | 81.07 389 | 94.25 341 |
|
| fmvsm_s_conf0.5_n_9 | | | 98.15 70 | 98.02 65 | 98.55 119 | 99.28 107 | 95.84 180 | 99.99 5 | 98.57 102 | 98.17 12 | 99.93 2 | 99.74 82 | 87.04 238 | 99.97 59 | 99.86 23 | 99.59 103 | 99.83 100 |
|
| SPE-MVS-test | | | 97.88 82 | 97.94 74 | 97.70 186 | 99.28 107 | 95.20 218 | 99.98 20 | 97.15 341 | 95.53 108 | 99.62 59 | 99.79 58 | 92.08 159 | 98.38 274 | 98.75 103 | 99.28 134 | 99.52 165 |
|
| test_fmvsm_n_1920 | | | 98.44 46 | 98.61 27 | 97.92 167 | 99.27 109 | 95.18 219 | 100.00 1 | 98.90 50 | 98.05 19 | 99.80 25 | 99.73 86 | 92.64 141 | 99.99 36 | 99.58 53 | 99.51 112 | 98.59 264 |
|
| fmvsm_s_conf0.5_n_10 | | | 98.24 66 | 97.90 77 | 99.26 50 | 99.24 110 | 97.88 87 | 99.99 5 | 98.76 69 | 98.20 9 | 99.92 4 | 99.74 82 | 85.97 256 | 99.94 88 | 99.72 42 | 99.53 108 | 99.96 70 |
|
| fmvsm_l_conf0.5_n_a | | | 99.00 15 | 98.91 14 | 99.28 48 | 99.21 111 | 97.91 86 | 99.98 20 | 98.85 59 | 98.25 5 | 99.92 4 | 99.75 75 | 94.72 71 | 99.97 59 | 99.87 21 | 99.64 92 | 99.95 78 |
|
| fmvsm_s_conf0.5_n_8 | | | 98.38 54 | 98.05 63 | 99.35 45 | 99.20 112 | 98.12 72 | 99.98 20 | 98.81 64 | 98.22 7 | 99.80 25 | 99.71 92 | 87.37 233 | 99.97 59 | 99.91 16 | 99.48 116 | 99.97 62 |
|
| test_yl | | | 97.83 88 | 97.37 107 | 99.21 55 | 99.18 113 | 97.98 81 | 99.64 213 | 99.27 27 | 91.43 282 | 97.88 169 | 98.99 188 | 95.84 42 | 99.84 132 | 98.82 97 | 95.32 266 | 99.79 107 |
|
| DCV-MVSNet | | | 97.83 88 | 97.37 107 | 99.21 55 | 99.18 113 | 97.98 81 | 99.64 213 | 99.27 27 | 91.43 282 | 97.88 169 | 98.99 188 | 95.84 42 | 99.84 132 | 98.82 97 | 95.32 266 | 99.79 107 |
|
| fmvsm_l_conf0.5_n | | | 98.94 16 | 98.84 17 | 99.25 51 | 99.17 115 | 97.81 91 | 99.98 20 | 98.86 56 | 98.25 5 | 99.90 6 | 99.76 67 | 94.21 94 | 99.97 59 | 99.87 21 | 99.52 109 | 99.98 52 |
|
| DeepC-MVS | | 94.51 4 | 96.92 145 | 96.40 154 | 98.45 132 | 99.16 116 | 95.90 178 | 99.66 208 | 98.06 229 | 96.37 86 | 94.37 264 | 99.49 131 | 83.29 293 | 99.90 107 | 97.63 168 | 99.61 99 | 99.55 155 |
| 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 38 | 98.22 49 | 99.50 30 | 99.15 117 | 98.65 53 | 100.00 1 | 98.58 100 | 97.70 31 | 98.21 157 | 99.24 163 | 92.58 144 | 99.94 88 | 98.63 112 | 99.94 55 | 99.92 88 |
| 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 50 | 98.08 61 | 99.39 41 | 99.12 118 | 98.29 65 | 99.98 20 | 98.64 86 | 98.14 15 | 99.86 14 | 99.76 67 | 87.99 222 | 99.97 59 | 99.72 42 | 99.54 106 | 99.91 90 |
|
| fmvsm_l_conf0.5_n_9 | | | 98.55 37 | 98.23 48 | 99.49 32 | 99.10 119 | 98.50 60 | 99.99 5 | 98.70 75 | 98.14 15 | 99.94 1 | 99.68 106 | 89.02 210 | 99.98 47 | 99.89 18 | 99.61 99 | 99.99 23 |
|
| CS-MVS | | | 97.79 95 | 97.91 76 | 97.43 210 | 99.10 119 | 94.42 241 | 99.99 5 | 97.10 353 | 95.07 117 | 99.68 49 | 99.75 75 | 92.95 131 | 98.34 278 | 98.38 124 | 99.14 140 | 99.54 159 |
|
| Anonymous202405211 | | | 93.10 288 | 91.99 301 | 96.40 252 | 99.10 119 | 89.65 365 | 98.88 331 | 97.93 242 | 83.71 412 | 94.00 270 | 98.75 224 | 68.79 406 | 99.88 118 | 95.08 225 | 91.71 299 | 99.68 123 |
|
| fmvsm_s_conf0.5_n | | | 97.80 93 | 97.85 81 | 97.67 187 | 99.06 122 | 94.41 242 | 99.98 20 | 98.97 43 | 97.34 41 | 99.63 56 | 99.69 99 | 87.27 234 | 99.97 59 | 99.62 51 | 99.06 145 | 98.62 263 |
|
| HyFIR lowres test | | | 96.66 160 | 96.43 152 | 97.36 217 | 99.05 123 | 93.91 260 | 99.70 199 | 99.80 3 | 90.54 312 | 96.26 223 | 98.08 275 | 92.15 157 | 98.23 290 | 96.84 193 | 95.46 261 | 99.93 83 |
|
| LFMVS | | | 94.75 236 | 93.56 259 | 98.30 142 | 99.03 124 | 95.70 188 | 98.74 346 | 97.98 237 | 87.81 367 | 98.47 141 | 99.39 143 | 67.43 415 | 99.53 169 | 98.01 147 | 95.20 269 | 99.67 125 |
|
| fmvsm_s_conf0.5_n_4 | | | 97.75 98 | 97.86 80 | 97.42 211 | 99.01 125 | 94.69 234 | 99.97 38 | 98.76 69 | 97.91 24 | 99.87 12 | 99.76 67 | 86.70 245 | 99.93 98 | 99.67 48 | 99.12 143 | 97.64 292 |
|
| fmvsm_s_conf0.5_n_2 | | | 97.59 108 | 97.28 111 | 98.53 125 | 99.01 125 | 98.15 67 | 99.98 20 | 98.59 98 | 98.17 12 | 99.75 39 | 99.63 116 | 81.83 306 | 99.94 88 | 99.78 31 | 98.79 156 | 97.51 300 |
|
| AllTest | | | 92.48 303 | 91.64 306 | 95.00 296 | 99.01 125 | 88.43 383 | 98.94 323 | 96.82 388 | 86.50 383 | 88.71 348 | 98.47 257 | 74.73 381 | 99.88 118 | 85.39 379 | 96.18 236 | 96.71 306 |
|
| TestCases | | | | | 95.00 296 | 99.01 125 | 88.43 383 | | 96.82 388 | 86.50 383 | 88.71 348 | 98.47 257 | 74.73 381 | 99.88 118 | 85.39 379 | 96.18 236 | 96.71 306 |
|
| COLMAP_ROB |  | 90.47 14 | 92.18 310 | 91.49 312 | 94.25 330 | 99.00 129 | 88.04 389 | 98.42 371 | 96.70 395 | 82.30 423 | 88.43 357 | 99.01 185 | 76.97 356 | 99.85 124 | 86.11 375 | 96.50 228 | 94.86 317 |
| 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 77 | 97.66 90 | 98.81 96 | 98.99 130 | 98.07 75 | 99.98 20 | 98.81 64 | 98.18 11 | 99.89 9 | 99.70 95 | 84.15 286 | 99.97 59 | 99.76 36 | 99.50 114 | 98.39 271 |
|
| test_fmvs1 | | | 95.35 215 | 95.68 189 | 94.36 326 | 98.99 130 | 84.98 410 | 99.96 48 | 96.65 397 | 97.60 33 | 99.73 44 | 98.96 194 | 71.58 396 | 99.93 98 | 98.31 129 | 99.37 129 | 98.17 276 |
|
| HY-MVS | | 92.50 7 | 97.79 95 | 97.17 118 | 99.63 17 | 98.98 132 | 99.32 9 | 97.49 399 | 99.52 14 | 95.69 103 | 98.32 150 | 97.41 295 | 93.32 118 | 99.77 144 | 98.08 144 | 95.75 251 | 99.81 104 |
|
| VNet | | | 97.21 127 | 96.57 146 | 99.13 72 | 98.97 133 | 97.82 90 | 99.03 310 | 99.21 32 | 94.31 153 | 99.18 100 | 98.88 206 | 86.26 252 | 99.89 112 | 98.93 88 | 94.32 279 | 99.69 122 |
|
| thres200 | | | 96.96 141 | 96.21 161 | 99.22 54 | 98.97 133 | 98.84 36 | 99.85 138 | 99.71 7 | 93.17 202 | 96.26 223 | 98.88 206 | 89.87 196 | 99.51 172 | 94.26 249 | 94.91 271 | 99.31 205 |
|
| tfpn200view9 | | | 96.79 149 | 95.99 168 | 99.19 57 | 98.94 135 | 98.82 37 | 99.78 162 | 99.71 7 | 92.86 217 | 96.02 231 | 98.87 213 | 89.33 203 | 99.50 174 | 93.84 258 | 94.57 275 | 99.27 214 |
|
| thres400 | | | 96.78 151 | 95.99 168 | 99.16 64 | 98.94 135 | 98.82 37 | 99.78 162 | 99.71 7 | 92.86 217 | 96.02 231 | 98.87 213 | 89.33 203 | 99.50 174 | 93.84 258 | 94.57 275 | 99.16 223 |
|
| sasdasda | | | 97.09 134 | 96.32 155 | 99.39 41 | 98.93 137 | 98.95 27 | 99.72 191 | 97.35 309 | 94.45 141 | 97.88 169 | 99.42 136 | 86.71 243 | 99.52 170 | 98.48 119 | 93.97 285 | 99.72 117 |
|
| Anonymous20231211 | | | 89.86 360 | 88.44 368 | 94.13 333 | 98.93 137 | 90.68 343 | 98.54 362 | 98.26 202 | 76.28 440 | 86.73 379 | 95.54 359 | 70.60 402 | 97.56 322 | 90.82 314 | 80.27 398 | 94.15 354 |
|
| canonicalmvs | | | 97.09 134 | 96.32 155 | 99.39 41 | 98.93 137 | 98.95 27 | 99.72 191 | 97.35 309 | 94.45 141 | 97.88 169 | 99.42 136 | 86.71 243 | 99.52 170 | 98.48 119 | 93.97 285 | 99.72 117 |
|
| SDMVSNet | | | 94.80 231 | 93.96 246 | 97.33 220 | 98.92 140 | 95.42 201 | 99.59 225 | 98.99 40 | 92.41 245 | 92.55 288 | 97.85 286 | 75.81 371 | 98.93 215 | 97.90 155 | 91.62 300 | 97.64 292 |
|
| sd_testset | | | 93.55 277 | 92.83 281 | 95.74 274 | 98.92 140 | 90.89 339 | 98.24 378 | 98.85 59 | 92.41 245 | 92.55 288 | 97.85 286 | 71.07 401 | 98.68 243 | 93.93 255 | 91.62 300 | 97.64 292 |
|
| EPNet_dtu | | | 95.71 203 | 95.39 198 | 96.66 243 | 98.92 140 | 93.41 274 | 99.57 230 | 98.90 50 | 96.19 91 | 97.52 179 | 98.56 247 | 92.65 140 | 97.36 327 | 77.89 426 | 98.33 169 | 99.20 221 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| WTY-MVS | | | 98.10 73 | 97.60 94 | 99.60 22 | 98.92 140 | 99.28 17 | 99.89 118 | 99.52 14 | 95.58 106 | 98.24 156 | 99.39 143 | 93.33 117 | 99.74 150 | 97.98 151 | 95.58 260 | 99.78 110 |
|
| CHOSEN 1792x2688 | | | 96.81 148 | 96.53 147 | 97.64 190 | 98.91 144 | 93.07 280 | 99.65 209 | 99.80 3 | 95.64 104 | 95.39 248 | 98.86 215 | 84.35 285 | 99.90 107 | 96.98 186 | 99.16 139 | 99.95 78 |
|
| thres100view900 | | | 96.74 155 | 95.92 178 | 99.18 58 | 98.90 145 | 98.77 42 | 99.74 180 | 99.71 7 | 92.59 236 | 95.84 235 | 98.86 215 | 89.25 205 | 99.50 174 | 93.84 258 | 94.57 275 | 99.27 214 |
|
| thres600view7 | | | 96.69 158 | 95.87 181 | 99.14 68 | 98.90 145 | 98.78 41 | 99.74 180 | 99.71 7 | 92.59 236 | 95.84 235 | 98.86 215 | 89.25 205 | 99.50 174 | 93.44 271 | 94.50 278 | 99.16 223 |
|
| MSDG | | | 94.37 252 | 93.36 271 | 97.40 213 | 98.88 147 | 93.95 259 | 99.37 266 | 97.38 305 | 85.75 394 | 90.80 307 | 99.17 171 | 84.11 288 | 99.88 118 | 86.35 371 | 98.43 167 | 98.36 273 |
|
| MGCFI-Net | | | 97.00 139 | 96.22 160 | 99.34 46 | 98.86 148 | 98.80 39 | 99.67 207 | 97.30 318 | 94.31 153 | 97.77 175 | 99.41 140 | 86.36 250 | 99.50 174 | 98.38 124 | 93.90 287 | 99.72 117 |
|
| h-mvs33 | | | 94.92 228 | 94.36 232 | 96.59 245 | 98.85 149 | 91.29 331 | 98.93 325 | 98.94 44 | 95.90 96 | 98.77 122 | 98.42 260 | 90.89 181 | 99.77 144 | 97.80 159 | 70.76 437 | 98.72 260 |
|
| Anonymous20240529 | | | 92.10 311 | 90.65 323 | 96.47 247 | 98.82 150 | 90.61 345 | 98.72 348 | 98.67 82 | 75.54 444 | 93.90 272 | 98.58 245 | 66.23 419 | 99.90 107 | 94.70 239 | 90.67 303 | 98.90 250 |
|
| PVSNet_Blended_VisFu | | | 97.27 123 | 96.81 134 | 98.66 108 | 98.81 151 | 96.67 144 | 99.92 94 | 98.64 86 | 94.51 138 | 96.38 221 | 98.49 253 | 89.05 209 | 99.88 118 | 97.10 181 | 98.34 168 | 99.43 183 |
|
| PS-MVSNAJ | | | 98.44 46 | 98.20 51 | 99.16 64 | 98.80 152 | 98.92 29 | 99.54 238 | 98.17 214 | 97.34 41 | 99.85 17 | 99.85 33 | 91.20 170 | 99.89 112 | 99.41 64 | 99.67 90 | 98.69 261 |
|
| CANet_DTU | | | 96.76 152 | 96.15 163 | 98.60 113 | 98.78 153 | 97.53 102 | 99.84 143 | 97.63 274 | 97.25 49 | 99.20 97 | 99.64 113 | 81.36 312 | 99.98 47 | 92.77 282 | 98.89 150 | 98.28 275 |
|
| mvsany_test1 | | | 97.82 91 | 97.90 77 | 97.55 199 | 98.77 154 | 93.04 283 | 99.80 159 | 97.93 242 | 96.95 60 | 99.61 66 | 99.68 106 | 90.92 178 | 99.83 134 | 99.18 72 | 98.29 173 | 99.80 106 |
|
| alignmvs | | | 97.81 92 | 97.33 109 | 99.25 51 | 98.77 154 | 98.66 51 | 99.99 5 | 98.44 143 | 94.40 149 | 98.41 145 | 99.47 132 | 93.65 110 | 99.42 184 | 98.57 113 | 94.26 281 | 99.67 125 |
|
| SymmetryMVS | | | 97.64 106 | 97.46 100 | 98.17 148 | 98.74 156 | 95.39 204 | 99.61 220 | 99.26 29 | 96.52 75 | 98.61 133 | 99.31 151 | 92.73 138 | 99.67 162 | 96.77 194 | 95.63 258 | 99.45 179 |
|
| SteuartSystems-ACMMP | | | 99.02 13 | 98.97 13 | 99.18 58 | 98.72 157 | 97.71 94 | 99.98 20 | 98.44 143 | 96.85 61 | 99.80 25 | 99.91 14 | 97.57 8 | 99.85 124 | 99.44 62 | 99.99 21 | 99.99 23 |
| Skip Steuart: Steuart Systems R&D Blog. |
| xiu_mvs_v2_base | | | 98.23 68 | 97.97 69 | 99.02 83 | 98.69 158 | 98.66 51 | 99.52 240 | 98.08 228 | 97.05 55 | 99.86 14 | 99.86 29 | 90.65 183 | 99.71 154 | 99.39 66 | 98.63 160 | 98.69 261 |
|
| miper_enhance_ethall | | | 94.36 254 | 93.98 245 | 95.49 277 | 98.68 159 | 95.24 215 | 99.73 187 | 97.29 321 | 93.28 199 | 89.86 319 | 95.97 345 | 94.37 85 | 97.05 350 | 92.20 286 | 84.45 360 | 94.19 347 |
|
| fmvsm_s_conf0.5_n_5 | | | 98.08 74 | 97.71 88 | 99.17 61 | 98.67 160 | 97.69 98 | 99.99 5 | 98.57 102 | 97.40 39 | 99.89 9 | 99.69 99 | 85.99 255 | 99.96 71 | 99.80 28 | 99.40 127 | 99.85 98 |
|
| ETVMVS | | | 97.03 138 | 96.64 142 | 98.20 147 | 98.67 160 | 97.12 123 | 99.89 118 | 98.57 102 | 91.10 294 | 98.17 158 | 98.59 242 | 93.86 105 | 98.19 292 | 95.64 217 | 95.24 268 | 99.28 212 |
|
| test2506 | | | 97.53 110 | 97.19 116 | 98.58 117 | 98.66 162 | 96.90 134 | 98.81 340 | 99.77 5 | 94.93 120 | 97.95 164 | 98.96 194 | 92.51 147 | 99.20 195 | 94.93 229 | 98.15 177 | 99.64 131 |
|
| ECVR-MVS |  | | 95.66 206 | 95.05 213 | 97.51 204 | 98.66 162 | 93.71 264 | 98.85 337 | 98.45 138 | 94.93 120 | 96.86 202 | 98.96 194 | 75.22 377 | 99.20 195 | 95.34 219 | 98.15 177 | 99.64 131 |
|
| mamv4 | | | 95.24 218 | 96.90 127 | 90.25 404 | 98.65 164 | 72.11 452 | 98.28 376 | 97.64 273 | 89.99 327 | 95.93 233 | 98.25 270 | 94.74 70 | 99.11 201 | 99.01 85 | 99.64 92 | 99.53 163 |
|
| balanced_conf03 | | | 98.27 60 | 97.99 67 | 99.11 73 | 98.64 165 | 98.43 63 | 99.47 250 | 97.79 257 | 94.56 136 | 99.74 42 | 98.35 262 | 94.33 88 | 99.25 189 | 99.12 74 | 99.96 46 | 99.64 131 |
|
| fmvsm_s_conf0.5_n_a | | | 97.73 101 | 97.72 86 | 97.77 181 | 98.63 166 | 94.26 249 | 99.96 48 | 98.92 49 | 97.18 51 | 99.75 39 | 99.69 99 | 87.00 240 | 99.97 59 | 99.46 60 | 98.89 150 | 99.08 233 |
|
| MVSMamba_PlusPlus | | | 97.83 88 | 97.45 102 | 98.99 85 | 98.60 167 | 98.15 67 | 99.58 227 | 97.74 264 | 90.34 319 | 99.26 96 | 98.32 265 | 94.29 90 | 99.23 190 | 99.03 83 | 99.89 70 | 99.58 151 |
|
| testing222 | | | 97.08 137 | 96.75 137 | 98.06 158 | 98.56 168 | 96.82 136 | 99.85 138 | 98.61 94 | 92.53 240 | 98.84 116 | 98.84 219 | 93.36 115 | 98.30 282 | 95.84 213 | 94.30 280 | 99.05 237 |
|
| test1111 | | | 95.57 209 | 94.98 216 | 97.37 215 | 98.56 168 | 93.37 277 | 98.86 335 | 98.45 138 | 94.95 119 | 96.63 208 | 98.95 199 | 75.21 378 | 99.11 201 | 95.02 226 | 98.14 179 | 99.64 131 |
|
| MVSTER | | | 95.53 210 | 95.22 205 | 96.45 250 | 98.56 168 | 97.72 93 | 99.91 102 | 97.67 269 | 92.38 248 | 91.39 298 | 97.14 302 | 97.24 18 | 97.30 334 | 94.80 235 | 87.85 332 | 94.34 336 |
|
| testing3-2 | | | 97.72 102 | 97.43 105 | 98.60 113 | 98.55 171 | 97.11 125 | 100.00 1 | 99.23 31 | 93.78 180 | 97.90 166 | 98.73 226 | 95.50 49 | 99.69 158 | 98.53 117 | 94.63 273 | 98.99 241 |
|
| VDD-MVS | | | 93.77 270 | 92.94 279 | 96.27 257 | 98.55 171 | 90.22 354 | 98.77 345 | 97.79 257 | 90.85 300 | 96.82 204 | 99.42 136 | 61.18 439 | 99.77 144 | 98.95 86 | 94.13 282 | 98.82 253 |
|
| tpmvs | | | 94.28 256 | 93.57 258 | 96.40 252 | 98.55 171 | 91.50 329 | 95.70 436 | 98.55 114 | 87.47 369 | 92.15 291 | 94.26 410 | 91.42 166 | 98.95 214 | 88.15 350 | 95.85 247 | 98.76 256 |
|
| UGNet | | | 95.33 216 | 94.57 228 | 97.62 194 | 98.55 171 | 94.85 227 | 98.67 354 | 99.32 26 | 95.75 101 | 96.80 205 | 96.27 334 | 72.18 393 | 99.96 71 | 94.58 242 | 99.05 146 | 98.04 281 |
| 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 | 95.18 220 | 94.10 239 | 98.43 134 | 98.55 171 | 95.99 176 | 97.91 392 | 97.31 317 | 90.35 318 | 89.48 332 | 99.22 164 | 85.19 269 | 99.89 112 | 90.40 324 | 98.47 166 | 99.41 186 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| UWE-MVS-28 | | | 95.95 191 | 96.49 148 | 94.34 327 | 98.51 176 | 89.99 359 | 99.39 262 | 98.57 102 | 93.14 204 | 97.33 187 | 98.31 267 | 93.44 113 | 94.68 427 | 93.69 268 | 95.98 241 | 98.34 274 |
|
| UWE-MVS | | | 96.79 149 | 96.72 139 | 97.00 229 | 98.51 176 | 93.70 265 | 99.71 194 | 98.60 96 | 92.96 212 | 97.09 194 | 98.34 264 | 96.67 31 | 98.85 221 | 92.11 292 | 96.50 228 | 98.44 269 |
|
| myMVS_eth3d28 | | | 97.86 84 | 97.59 96 | 98.68 105 | 98.50 178 | 97.26 115 | 99.92 94 | 98.55 114 | 93.79 179 | 98.26 154 | 98.75 224 | 95.20 54 | 99.48 180 | 98.93 88 | 96.40 231 | 99.29 210 |
|
| test_vis1_n_1920 | | | 95.44 212 | 95.31 201 | 95.82 271 | 98.50 178 | 88.74 377 | 99.98 20 | 97.30 318 | 97.84 27 | 99.85 17 | 99.19 169 | 66.82 417 | 99.97 59 | 98.82 97 | 99.46 121 | 98.76 256 |
|
| BH-w/o | | | 95.71 203 | 95.38 199 | 96.68 242 | 98.49 180 | 92.28 302 | 99.84 143 | 97.50 294 | 92.12 258 | 92.06 294 | 98.79 222 | 84.69 279 | 98.67 245 | 95.29 221 | 99.66 91 | 99.09 231 |
|
| baseline1 | | | 95.78 199 | 94.86 219 | 98.54 123 | 98.47 181 | 98.07 75 | 99.06 303 | 97.99 235 | 92.68 230 | 94.13 269 | 98.62 239 | 93.28 121 | 98.69 242 | 93.79 263 | 85.76 347 | 98.84 252 |
|
| fmvsm_s_conf0.5_n_7 | | | 97.70 104 | 97.74 85 | 97.59 197 | 98.44 182 | 95.16 221 | 99.97 38 | 98.65 83 | 97.95 23 | 99.62 59 | 99.78 62 | 86.09 253 | 99.94 88 | 99.69 46 | 99.50 114 | 97.66 291 |
|
| EPMVS | | | 96.53 167 | 96.01 167 | 98.09 156 | 98.43 183 | 96.12 174 | 96.36 423 | 99.43 20 | 93.53 188 | 97.64 177 | 95.04 387 | 94.41 80 | 98.38 274 | 91.13 305 | 98.11 180 | 99.75 113 |
|
| kuosan | | | 93.17 285 | 92.60 287 | 94.86 303 | 98.40 184 | 89.54 367 | 98.44 367 | 98.53 121 | 84.46 407 | 88.49 353 | 97.92 283 | 90.57 185 | 97.05 350 | 83.10 396 | 93.49 290 | 97.99 282 |
|
| WBMVS | | | 94.52 245 | 94.03 243 | 95.98 263 | 98.38 185 | 96.68 143 | 99.92 94 | 97.63 274 | 90.75 309 | 89.64 327 | 95.25 380 | 96.77 25 | 96.90 362 | 94.35 247 | 83.57 367 | 94.35 334 |
|
| UBG | | | 97.84 87 | 97.69 89 | 98.29 143 | 98.38 185 | 96.59 150 | 99.90 108 | 98.53 121 | 93.91 175 | 98.52 137 | 98.42 260 | 96.77 25 | 99.17 198 | 98.54 115 | 96.20 235 | 99.11 230 |
|
| sss | | | 97.57 109 | 97.03 123 | 99.18 58 | 98.37 187 | 98.04 78 | 99.73 187 | 99.38 22 | 93.46 191 | 98.76 125 | 99.06 180 | 91.21 169 | 99.89 112 | 96.33 204 | 97.01 219 | 99.62 138 |
|
| testing11 | | | 97.48 112 | 97.27 112 | 98.10 155 | 98.36 188 | 96.02 175 | 99.92 94 | 98.45 138 | 93.45 193 | 98.15 159 | 98.70 229 | 95.48 50 | 99.22 191 | 97.85 157 | 95.05 270 | 99.07 234 |
|
| BH-untuned | | | 95.18 220 | 94.83 220 | 96.22 258 | 98.36 188 | 91.22 332 | 99.80 159 | 97.32 316 | 90.91 298 | 91.08 301 | 98.67 231 | 83.51 290 | 98.54 256 | 94.23 250 | 99.61 99 | 98.92 247 |
|
| testing91 | | | 97.16 129 | 96.90 127 | 97.97 162 | 98.35 190 | 95.67 191 | 99.91 102 | 98.42 163 | 92.91 215 | 97.33 187 | 98.72 227 | 94.81 68 | 99.21 192 | 96.98 186 | 94.63 273 | 99.03 238 |
|
| testing99 | | | 97.17 128 | 96.91 126 | 97.95 163 | 98.35 190 | 95.70 188 | 99.91 102 | 98.43 151 | 92.94 213 | 97.36 185 | 98.72 227 | 94.83 67 | 99.21 192 | 97.00 184 | 94.64 272 | 98.95 243 |
|
| ET-MVSNet_ETH3D | | | 94.37 252 | 93.28 273 | 97.64 190 | 98.30 192 | 97.99 80 | 99.99 5 | 97.61 280 | 94.35 150 | 71.57 450 | 99.45 135 | 96.23 35 | 95.34 417 | 96.91 191 | 85.14 354 | 99.59 145 |
|
| AUN-MVS | | | 93.28 282 | 92.60 287 | 95.34 286 | 98.29 193 | 90.09 357 | 99.31 274 | 98.56 108 | 91.80 271 | 96.35 222 | 98.00 278 | 89.38 202 | 98.28 285 | 92.46 283 | 69.22 442 | 97.64 292 |
|
| FMVSNet3 | | | 92.69 298 | 91.58 308 | 95.99 262 | 98.29 193 | 97.42 110 | 99.26 283 | 97.62 277 | 89.80 330 | 89.68 323 | 95.32 374 | 81.62 310 | 96.27 393 | 87.01 367 | 85.65 348 | 94.29 338 |
|
| PMMVS | | | 96.76 152 | 96.76 136 | 96.76 239 | 98.28 195 | 92.10 306 | 99.91 102 | 97.98 237 | 94.12 161 | 99.53 71 | 99.39 143 | 86.93 241 | 98.73 235 | 96.95 189 | 97.73 188 | 99.45 179 |
|
| hse-mvs2 | | | 94.38 251 | 94.08 242 | 95.31 288 | 98.27 196 | 90.02 358 | 99.29 279 | 98.56 108 | 95.90 96 | 98.77 122 | 98.00 278 | 90.89 181 | 98.26 289 | 97.80 159 | 69.20 443 | 97.64 292 |
|
| PVSNet_0 | | 88.03 19 | 91.80 318 | 90.27 332 | 96.38 254 | 98.27 196 | 90.46 349 | 99.94 84 | 99.61 13 | 93.99 169 | 86.26 389 | 97.39 297 | 71.13 400 | 99.89 112 | 98.77 101 | 67.05 449 | 98.79 255 |
|
| UA-Net | | | 96.54 166 | 95.96 174 | 98.27 144 | 98.23 198 | 95.71 187 | 98.00 390 | 98.45 138 | 93.72 184 | 98.41 145 | 99.27 156 | 88.71 216 | 99.66 165 | 91.19 304 | 97.69 189 | 99.44 182 |
|
| test_cas_vis1_n_1920 | | | 96.59 163 | 96.23 158 | 97.65 189 | 98.22 199 | 94.23 250 | 99.99 5 | 97.25 326 | 97.77 28 | 99.58 67 | 99.08 178 | 77.10 351 | 99.97 59 | 97.64 167 | 99.45 122 | 98.74 258 |
|
| FE-MVS | | | 95.70 205 | 95.01 215 | 97.79 177 | 98.21 200 | 94.57 236 | 95.03 437 | 98.69 77 | 88.90 346 | 97.50 181 | 96.19 336 | 92.60 143 | 99.49 179 | 89.99 329 | 97.94 186 | 99.31 205 |
|
| GG-mvs-BLEND | | | | | 98.54 123 | 98.21 200 | 98.01 79 | 93.87 442 | 98.52 123 | | 97.92 165 | 97.92 283 | 99.02 3 | 97.94 309 | 98.17 137 | 99.58 104 | 99.67 125 |
|
| mvs_anonymous | | | 95.65 207 | 95.03 214 | 97.53 201 | 98.19 202 | 95.74 185 | 99.33 271 | 97.49 295 | 90.87 299 | 90.47 310 | 97.10 304 | 88.23 219 | 97.16 341 | 95.92 211 | 97.66 192 | 99.68 123 |
|
| MVS_Test | | | 96.46 169 | 95.74 185 | 98.61 112 | 98.18 203 | 97.23 117 | 99.31 274 | 97.15 341 | 91.07 295 | 98.84 116 | 97.05 308 | 88.17 220 | 98.97 211 | 94.39 244 | 97.50 194 | 99.61 142 |
|
| BH-RMVSNet | | | 95.18 220 | 94.31 235 | 97.80 175 | 98.17 204 | 95.23 216 | 99.76 173 | 97.53 290 | 92.52 241 | 94.27 267 | 99.25 162 | 76.84 358 | 98.80 225 | 90.89 313 | 99.54 106 | 99.35 196 |
|
| dongtai | | | 91.55 324 | 91.13 317 | 92.82 372 | 98.16 205 | 86.35 400 | 99.47 250 | 98.51 126 | 83.24 415 | 85.07 399 | 97.56 291 | 90.33 190 | 94.94 423 | 76.09 434 | 91.73 298 | 97.18 303 |
|
| RPSCF | | | 91.80 318 | 92.79 283 | 88.83 415 | 98.15 206 | 69.87 454 | 98.11 386 | 96.60 399 | 83.93 410 | 94.33 265 | 99.27 156 | 79.60 334 | 99.46 183 | 91.99 293 | 93.16 295 | 97.18 303 |
|
| ETV-MVS | | | 97.92 80 | 97.80 84 | 98.25 145 | 98.14 207 | 96.48 152 | 99.98 20 | 97.63 274 | 95.61 105 | 99.29 94 | 99.46 134 | 92.55 145 | 98.82 223 | 99.02 84 | 98.54 164 | 99.46 176 |
|
| IS-MVSNet | | | 96.29 180 | 95.90 179 | 97.45 207 | 98.13 208 | 94.80 230 | 99.08 298 | 97.61 280 | 92.02 263 | 95.54 246 | 98.96 194 | 90.64 184 | 98.08 298 | 93.73 266 | 97.41 198 | 99.47 174 |
|
| test_fmvsmconf_n | | | 98.43 48 | 98.32 44 | 98.78 98 | 98.12 209 | 96.41 155 | 99.99 5 | 98.83 63 | 98.22 7 | 99.67 50 | 99.64 113 | 91.11 174 | 99.94 88 | 99.67 48 | 99.62 95 | 99.98 52 |
|
| fmvsm_s_conf0.1_n_2 | | | 97.25 124 | 96.85 131 | 98.43 134 | 98.08 210 | 98.08 74 | 99.92 94 | 97.76 263 | 98.05 19 | 99.65 52 | 99.58 122 | 80.88 319 | 99.93 98 | 99.59 52 | 98.17 175 | 97.29 301 |
|
| ab-mvs | | | 94.69 237 | 93.42 264 | 98.51 128 | 98.07 211 | 96.26 162 | 96.49 421 | 98.68 79 | 90.31 320 | 94.54 257 | 97.00 310 | 76.30 366 | 99.71 154 | 95.98 210 | 93.38 293 | 99.56 154 |
|
| XVG-OURS-SEG-HR | | | 94.79 232 | 94.70 227 | 95.08 293 | 98.05 212 | 89.19 369 | 99.08 298 | 97.54 288 | 93.66 185 | 94.87 255 | 99.58 122 | 78.78 342 | 99.79 139 | 97.31 174 | 93.40 292 | 96.25 310 |
|
| EIA-MVS | | | 97.53 110 | 97.46 100 | 97.76 183 | 98.04 213 | 94.84 228 | 99.98 20 | 97.61 280 | 94.41 148 | 97.90 166 | 99.59 119 | 92.40 151 | 98.87 219 | 98.04 146 | 99.13 141 | 99.59 145 |
|
| XVG-OURS | | | 94.82 229 | 94.74 226 | 95.06 294 | 98.00 214 | 89.19 369 | 99.08 298 | 97.55 286 | 94.10 162 | 94.71 256 | 99.62 117 | 80.51 325 | 99.74 150 | 96.04 209 | 93.06 297 | 96.25 310 |
|
| mvsmamba | | | 96.94 142 | 96.73 138 | 97.55 199 | 97.99 215 | 94.37 246 | 99.62 216 | 97.70 266 | 93.13 205 | 98.42 144 | 97.92 283 | 88.02 221 | 98.75 233 | 98.78 100 | 99.01 147 | 99.52 165 |
|
| dp | | | 95.05 223 | 94.43 230 | 96.91 232 | 97.99 215 | 92.73 291 | 96.29 426 | 97.98 237 | 89.70 331 | 95.93 233 | 94.67 400 | 93.83 107 | 98.45 262 | 86.91 370 | 96.53 227 | 99.54 159 |
|
| tpmrst | | | 96.27 182 | 95.98 170 | 97.13 224 | 97.96 217 | 93.15 279 | 96.34 424 | 98.17 214 | 92.07 259 | 98.71 128 | 95.12 384 | 93.91 102 | 98.73 235 | 94.91 232 | 96.62 225 | 99.50 171 |
|
| TR-MVS | | | 94.54 242 | 93.56 259 | 97.49 206 | 97.96 217 | 94.34 247 | 98.71 349 | 97.51 293 | 90.30 321 | 94.51 259 | 98.69 230 | 75.56 372 | 98.77 229 | 92.82 281 | 95.99 240 | 99.35 196 |
|
| Vis-MVSNet (Re-imp) | | | 96.32 177 | 95.98 170 | 97.35 219 | 97.93 219 | 94.82 229 | 99.47 250 | 98.15 222 | 91.83 268 | 95.09 253 | 99.11 176 | 91.37 168 | 97.47 325 | 93.47 270 | 97.43 195 | 99.74 114 |
|
| MDTV_nov1_ep13 | | | | 95.69 187 | | 97.90 220 | 94.15 252 | 95.98 432 | 98.44 143 | 93.12 206 | 97.98 163 | 95.74 349 | 95.10 57 | 98.58 252 | 90.02 328 | 96.92 221 | |
|
| Fast-Effi-MVS+ | | | 95.02 225 | 94.19 237 | 97.52 203 | 97.88 221 | 94.55 237 | 99.97 38 | 97.08 357 | 88.85 348 | 94.47 260 | 97.96 282 | 84.59 280 | 98.41 266 | 89.84 331 | 97.10 212 | 99.59 145 |
|
| ADS-MVSNet2 | | | 93.80 269 | 93.88 249 | 93.55 355 | 97.87 222 | 85.94 404 | 94.24 438 | 96.84 385 | 90.07 324 | 96.43 218 | 94.48 405 | 90.29 192 | 95.37 416 | 87.44 357 | 97.23 205 | 99.36 192 |
|
| ADS-MVSNet | | | 94.79 232 | 94.02 244 | 97.11 226 | 97.87 222 | 93.79 261 | 94.24 438 | 98.16 219 | 90.07 324 | 96.43 218 | 94.48 405 | 90.29 192 | 98.19 292 | 87.44 357 | 97.23 205 | 99.36 192 |
|
| Effi-MVS+ | | | 96.30 179 | 95.69 187 | 98.16 149 | 97.85 224 | 96.26 162 | 97.41 401 | 97.21 333 | 90.37 317 | 98.65 131 | 98.58 245 | 86.61 247 | 98.70 241 | 97.11 180 | 97.37 199 | 99.52 165 |
|
| PatchmatchNet |  | | 95.94 192 | 95.45 194 | 97.39 214 | 97.83 225 | 94.41 242 | 96.05 430 | 98.40 172 | 92.86 217 | 97.09 194 | 95.28 379 | 94.21 94 | 98.07 300 | 89.26 337 | 98.11 180 | 99.70 120 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| cascas | | | 94.64 240 | 93.61 254 | 97.74 185 | 97.82 226 | 96.26 162 | 99.96 48 | 97.78 259 | 85.76 392 | 94.00 270 | 97.54 292 | 76.95 357 | 99.21 192 | 97.23 177 | 95.43 263 | 97.76 290 |
|
| 1112_ss | | | 96.01 190 | 95.20 206 | 98.42 136 | 97.80 227 | 96.41 155 | 99.65 209 | 96.66 396 | 92.71 227 | 92.88 284 | 99.40 141 | 92.16 156 | 99.30 187 | 91.92 295 | 93.66 288 | 99.55 155 |
|
| Test_1112_low_res | | | 95.72 201 | 94.83 220 | 98.42 136 | 97.79 228 | 96.41 155 | 99.65 209 | 96.65 397 | 92.70 228 | 92.86 285 | 96.13 340 | 92.15 157 | 99.30 187 | 91.88 296 | 93.64 289 | 99.55 155 |
|
| Effi-MVS+-dtu | | | 94.53 244 | 95.30 202 | 92.22 380 | 97.77 229 | 82.54 427 | 99.59 225 | 97.06 361 | 94.92 122 | 95.29 250 | 95.37 372 | 85.81 257 | 97.89 310 | 94.80 235 | 97.07 213 | 96.23 312 |
|
| tpm cat1 | | | 93.51 278 | 92.52 293 | 96.47 247 | 97.77 229 | 91.47 330 | 96.13 428 | 98.06 229 | 80.98 429 | 92.91 283 | 93.78 414 | 89.66 197 | 98.87 219 | 87.03 366 | 96.39 232 | 99.09 231 |
|
| FA-MVS(test-final) | | | 95.86 195 | 95.09 211 | 98.15 152 | 97.74 231 | 95.62 193 | 96.31 425 | 98.17 214 | 91.42 284 | 96.26 223 | 96.13 340 | 90.56 186 | 99.47 182 | 92.18 287 | 97.07 213 | 99.35 196 |
|
| xiu_mvs_v1_base_debu | | | 97.43 113 | 97.06 119 | 98.55 119 | 97.74 231 | 98.14 69 | 99.31 274 | 97.86 251 | 96.43 80 | 99.62 59 | 99.69 99 | 85.56 264 | 99.68 159 | 99.05 77 | 98.31 170 | 97.83 286 |
|
| xiu_mvs_v1_base | | | 97.43 113 | 97.06 119 | 98.55 119 | 97.74 231 | 98.14 69 | 99.31 274 | 97.86 251 | 96.43 80 | 99.62 59 | 99.69 99 | 85.56 264 | 99.68 159 | 99.05 77 | 98.31 170 | 97.83 286 |
|
| xiu_mvs_v1_base_debi | | | 97.43 113 | 97.06 119 | 98.55 119 | 97.74 231 | 98.14 69 | 99.31 274 | 97.86 251 | 96.43 80 | 99.62 59 | 99.69 99 | 85.56 264 | 99.68 159 | 99.05 77 | 98.31 170 | 97.83 286 |
|
| EPP-MVSNet | | | 96.69 158 | 96.60 144 | 96.96 231 | 97.74 231 | 93.05 282 | 99.37 266 | 98.56 108 | 88.75 350 | 95.83 237 | 99.01 185 | 96.01 36 | 98.56 254 | 96.92 190 | 97.20 207 | 99.25 216 |
|
| gg-mvs-nofinetune | | | 93.51 278 | 91.86 305 | 98.47 130 | 97.72 236 | 97.96 84 | 92.62 448 | 98.51 126 | 74.70 447 | 97.33 187 | 69.59 464 | 98.91 4 | 97.79 313 | 97.77 164 | 99.56 105 | 99.67 125 |
|
| IB-MVS | | 92.85 6 | 94.99 226 | 93.94 247 | 98.16 149 | 97.72 236 | 95.69 190 | 99.99 5 | 98.81 64 | 94.28 156 | 92.70 286 | 96.90 312 | 95.08 58 | 99.17 198 | 96.07 208 | 73.88 430 | 99.60 144 |
| 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 | | | 97.41 118 | 97.02 124 | 98.59 116 | 97.71 238 | 97.52 103 | 99.97 38 | 98.54 118 | 91.83 268 | 97.45 182 | 99.04 182 | 97.50 9 | 99.10 203 | 94.75 237 | 96.37 233 | 99.16 223 |
|
| VortexMVS | | | 94.11 258 | 93.50 261 | 95.94 265 | 97.70 239 | 96.61 147 | 99.35 269 | 97.18 336 | 93.52 190 | 89.57 330 | 95.74 349 | 87.55 228 | 96.97 358 | 95.76 216 | 85.13 355 | 94.23 343 |
|
| viewdifsd2359ckpt09 | | | 96.21 184 | 95.77 183 | 97.53 201 | 97.69 240 | 94.50 238 | 99.78 162 | 97.23 331 | 92.88 216 | 96.58 211 | 99.26 160 | 84.85 274 | 98.66 248 | 96.61 198 | 97.02 218 | 99.43 183 |
|
| Syy-MVS | | | 90.00 358 | 90.63 324 | 88.11 422 | 97.68 241 | 74.66 450 | 99.71 194 | 98.35 185 | 90.79 306 | 92.10 292 | 98.67 231 | 79.10 340 | 93.09 442 | 63.35 457 | 95.95 244 | 96.59 308 |
|
| myMVS_eth3d | | | 94.46 249 | 94.76 225 | 93.55 355 | 97.68 241 | 90.97 334 | 99.71 194 | 98.35 185 | 90.79 306 | 92.10 292 | 98.67 231 | 92.46 150 | 93.09 442 | 87.13 363 | 95.95 244 | 96.59 308 |
|
| test_fmvs1_n | | | 94.25 257 | 94.36 232 | 93.92 342 | 97.68 241 | 83.70 417 | 99.90 108 | 96.57 400 | 97.40 39 | 99.67 50 | 98.88 206 | 61.82 436 | 99.92 104 | 98.23 135 | 99.13 141 | 98.14 279 |
|
| fmvsm_s_conf0.5_n_6 | | | 98.27 60 | 97.96 72 | 99.23 53 | 97.66 244 | 98.11 73 | 99.98 20 | 98.64 86 | 97.85 26 | 99.87 12 | 99.72 89 | 88.86 213 | 99.93 98 | 99.64 50 | 99.36 130 | 99.63 137 |
|
| RRT-MVS | | | 96.24 183 | 95.68 189 | 97.94 166 | 97.65 245 | 94.92 226 | 99.27 282 | 97.10 353 | 92.79 223 | 97.43 183 | 97.99 280 | 81.85 305 | 99.37 186 | 98.46 121 | 98.57 161 | 99.53 163 |
|
| diffmvs |  | | 97.00 139 | 96.64 142 | 98.09 156 | 97.64 246 | 96.17 171 | 99.81 155 | 97.19 334 | 94.67 134 | 98.95 111 | 99.28 153 | 86.43 248 | 98.76 231 | 98.37 126 | 97.42 197 | 99.33 199 |
| 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 | | | 96.59 163 | 96.23 158 | 97.66 188 | 97.63 247 | 94.70 233 | 99.77 167 | 97.33 313 | 93.41 194 | 97.34 186 | 99.17 171 | 86.72 242 | 98.83 222 | 97.40 172 | 97.32 202 | 99.46 176 |
|
| viewdifsd2359ckpt13 | | | 96.19 185 | 95.77 183 | 97.45 207 | 97.62 248 | 94.40 244 | 99.70 199 | 97.23 331 | 92.76 225 | 96.63 208 | 99.05 181 | 84.96 273 | 98.64 249 | 96.65 197 | 97.35 200 | 99.31 205 |
|
| Vis-MVSNet |  | | 95.72 201 | 95.15 209 | 97.45 207 | 97.62 248 | 94.28 248 | 99.28 280 | 98.24 205 | 94.27 158 | 96.84 203 | 98.94 201 | 79.39 335 | 98.76 231 | 93.25 272 | 98.49 165 | 99.30 208 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| thisisatest0530 | | | 97.10 132 | 96.72 139 | 98.22 146 | 97.60 250 | 96.70 140 | 99.92 94 | 98.54 118 | 91.11 293 | 97.07 196 | 98.97 192 | 97.47 12 | 99.03 206 | 93.73 266 | 96.09 238 | 98.92 247 |
|
| GDP-MVS | | | 97.88 82 | 97.59 96 | 98.75 101 | 97.59 251 | 97.81 91 | 99.95 67 | 97.37 308 | 94.44 144 | 99.08 105 | 99.58 122 | 97.13 23 | 99.08 204 | 94.99 227 | 98.17 175 | 99.37 190 |
|
| miper_ehance_all_eth | | | 93.16 286 | 92.60 287 | 94.82 304 | 97.57 252 | 93.56 269 | 99.50 244 | 97.07 360 | 88.75 350 | 88.85 347 | 95.52 361 | 90.97 177 | 96.74 372 | 90.77 315 | 84.45 360 | 94.17 348 |
|
| guyue | | | 97.15 130 | 96.82 133 | 98.15 152 | 97.56 253 | 96.25 166 | 99.71 194 | 97.84 254 | 95.75 101 | 98.13 160 | 98.65 234 | 87.58 227 | 98.82 223 | 98.29 131 | 97.91 187 | 99.36 192 |
|
| viewmanbaseed2359cas | | | 96.45 170 | 96.07 164 | 97.59 197 | 97.55 254 | 94.59 235 | 99.70 199 | 97.33 313 | 93.62 187 | 97.00 198 | 99.32 148 | 85.57 263 | 98.71 238 | 97.26 176 | 97.33 201 | 99.47 174 |
|
| testing3 | | | 93.92 263 | 94.23 236 | 92.99 369 | 97.54 255 | 90.23 353 | 99.99 5 | 99.16 33 | 90.57 311 | 91.33 300 | 98.63 238 | 92.99 129 | 92.52 446 | 82.46 400 | 95.39 264 | 96.22 313 |
|
| SSM_0404 | | | 95.75 200 | 95.16 208 | 97.50 205 | 97.53 256 | 95.39 204 | 99.11 294 | 97.25 326 | 90.81 302 | 95.27 251 | 98.83 220 | 84.74 276 | 98.67 245 | 95.24 222 | 97.69 189 | 98.45 268 |
|
| LCM-MVSNet-Re | | | 92.31 307 | 92.60 287 | 91.43 389 | 97.53 256 | 79.27 444 | 99.02 312 | 91.83 459 | 92.07 259 | 80.31 423 | 94.38 408 | 83.50 291 | 95.48 413 | 97.22 178 | 97.58 193 | 99.54 159 |
|
| GBi-Net | | | 90.88 335 | 89.82 341 | 94.08 334 | 97.53 256 | 91.97 307 | 98.43 368 | 96.95 374 | 87.05 375 | 89.68 323 | 94.72 396 | 71.34 397 | 96.11 399 | 87.01 367 | 85.65 348 | 94.17 348 |
|
| test1 | | | 90.88 335 | 89.82 341 | 94.08 334 | 97.53 256 | 91.97 307 | 98.43 368 | 96.95 374 | 87.05 375 | 89.68 323 | 94.72 396 | 71.34 397 | 96.11 399 | 87.01 367 | 85.65 348 | 94.17 348 |
|
| FMVSNet2 | | | 91.02 332 | 89.56 346 | 95.41 284 | 97.53 256 | 95.74 185 | 98.98 315 | 97.41 303 | 87.05 375 | 88.43 357 | 95.00 390 | 71.34 397 | 96.24 395 | 85.12 382 | 85.21 353 | 94.25 341 |
|
| tttt0517 | | | 96.85 146 | 96.49 148 | 97.92 167 | 97.48 261 | 95.89 179 | 99.85 138 | 98.54 118 | 90.72 310 | 96.63 208 | 98.93 204 | 97.47 12 | 99.02 207 | 93.03 279 | 95.76 250 | 98.85 251 |
|
| BP-MVS1 | | | 98.33 56 | 98.18 53 | 98.81 96 | 97.44 262 | 97.98 81 | 99.96 48 | 98.17 214 | 94.88 124 | 98.77 122 | 99.59 119 | 97.59 7 | 99.08 204 | 98.24 134 | 98.93 149 | 99.36 192 |
|
| casdiffmvs_mvg |  | | 96.43 171 | 95.94 176 | 97.89 171 | 97.44 262 | 95.47 197 | 99.86 135 | 97.29 321 | 93.35 195 | 96.03 230 | 99.19 169 | 85.39 267 | 98.72 237 | 97.89 156 | 97.04 215 | 99.49 173 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| EC-MVSNet | | | 97.38 120 | 97.24 113 | 97.80 175 | 97.41 264 | 95.64 192 | 99.99 5 | 97.06 361 | 94.59 135 | 99.63 56 | 99.32 148 | 89.20 208 | 98.14 294 | 98.76 102 | 99.23 137 | 99.62 138 |
|
| viewdifsd2359ckpt07 | | | 95.83 198 | 95.42 196 | 97.07 227 | 97.40 265 | 93.04 283 | 99.60 223 | 97.24 329 | 92.39 247 | 96.09 229 | 99.14 175 | 83.07 296 | 98.93 215 | 97.02 183 | 96.87 222 | 99.23 219 |
|
| c3_l | | | 92.53 302 | 91.87 304 | 94.52 316 | 97.40 265 | 92.99 285 | 99.40 258 | 96.93 379 | 87.86 365 | 88.69 350 | 95.44 366 | 89.95 195 | 96.44 385 | 90.45 321 | 80.69 394 | 94.14 357 |
|
| viewmambaseed2359dif | | | 95.92 194 | 95.55 193 | 97.04 228 | 97.38 267 | 93.41 274 | 99.78 162 | 96.97 372 | 91.14 292 | 96.58 211 | 99.27 156 | 84.85 274 | 98.75 233 | 96.87 192 | 97.12 211 | 98.97 242 |
|
| fmvsm_s_conf0.1_n | | | 97.30 121 | 97.21 115 | 97.60 196 | 97.38 267 | 94.40 244 | 99.90 108 | 98.64 86 | 96.47 79 | 99.51 75 | 99.65 112 | 84.99 272 | 99.93 98 | 99.22 71 | 99.09 144 | 98.46 267 |
|
| CDS-MVSNet | | | 96.34 176 | 96.07 164 | 97.13 224 | 97.37 269 | 94.96 224 | 99.53 239 | 97.91 246 | 91.55 276 | 95.37 249 | 98.32 265 | 95.05 60 | 97.13 344 | 93.80 262 | 95.75 251 | 99.30 208 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| TESTMET0.1,1 | | | 96.74 155 | 96.26 157 | 98.16 149 | 97.36 270 | 96.48 152 | 99.96 48 | 98.29 198 | 91.93 264 | 95.77 238 | 98.07 276 | 95.54 46 | 98.29 283 | 90.55 319 | 98.89 150 | 99.70 120 |
|
| miper_lstm_enhance | | | 91.81 315 | 91.39 314 | 93.06 368 | 97.34 271 | 89.18 371 | 99.38 264 | 96.79 390 | 86.70 382 | 87.47 371 | 95.22 381 | 90.00 194 | 95.86 408 | 88.26 348 | 81.37 383 | 94.15 354 |
|
| baseline | | | 96.43 171 | 95.98 170 | 97.76 183 | 97.34 271 | 95.17 220 | 99.51 242 | 97.17 338 | 93.92 174 | 96.90 201 | 99.28 153 | 85.37 268 | 98.64 249 | 97.50 170 | 96.86 224 | 99.46 176 |
|
| cl____ | | | 92.31 307 | 91.58 308 | 94.52 316 | 97.33 273 | 92.77 287 | 99.57 230 | 96.78 391 | 86.97 379 | 87.56 369 | 95.51 362 | 89.43 201 | 96.62 377 | 88.60 342 | 82.44 375 | 94.16 353 |
|
| SD_0403 | | | 92.63 301 | 93.38 268 | 90.40 403 | 97.32 274 | 77.91 446 | 97.75 397 | 98.03 233 | 91.89 265 | 90.83 306 | 98.29 269 | 82.00 302 | 93.79 436 | 88.51 346 | 95.75 251 | 99.52 165 |
|
| DIV-MVS_self_test | | | 92.32 306 | 91.60 307 | 94.47 320 | 97.31 275 | 92.74 289 | 99.58 227 | 96.75 392 | 86.99 378 | 87.64 367 | 95.54 359 | 89.55 200 | 96.50 382 | 88.58 343 | 82.44 375 | 94.17 348 |
|
| casdiffmvs |  | | 96.42 173 | 95.97 173 | 97.77 181 | 97.30 276 | 94.98 223 | 99.84 143 | 97.09 356 | 93.75 183 | 96.58 211 | 99.26 160 | 85.07 270 | 98.78 228 | 97.77 164 | 97.04 215 | 99.54 159 |
| 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 | | | 94.36 254 | 93.48 262 | 96.99 230 | 97.29 277 | 93.54 270 | 99.96 48 | 96.72 394 | 88.35 359 | 93.43 274 | 98.94 201 | 82.05 301 | 98.05 301 | 88.12 352 | 96.48 230 | 99.37 190 |
|
| eth_miper_zixun_eth | | | 92.41 305 | 91.93 302 | 93.84 346 | 97.28 278 | 90.68 343 | 98.83 338 | 96.97 372 | 88.57 355 | 89.19 342 | 95.73 352 | 89.24 207 | 96.69 375 | 89.97 330 | 81.55 381 | 94.15 354 |
|
| MVSFormer | | | 96.94 142 | 96.60 144 | 97.95 163 | 97.28 278 | 97.70 96 | 99.55 236 | 97.27 323 | 91.17 289 | 99.43 81 | 99.54 128 | 90.92 178 | 96.89 363 | 94.67 240 | 99.62 95 | 99.25 216 |
|
| lupinMVS | | | 97.85 86 | 97.60 94 | 98.62 111 | 97.28 278 | 97.70 96 | 99.99 5 | 97.55 286 | 95.50 110 | 99.43 81 | 99.67 108 | 90.92 178 | 98.71 238 | 98.40 123 | 99.62 95 | 99.45 179 |
|
| diffmvs_AUTHOR | | | 96.75 154 | 96.41 153 | 97.79 177 | 97.20 281 | 95.46 198 | 99.69 202 | 97.15 341 | 94.46 140 | 98.78 120 | 99.21 167 | 85.64 261 | 98.77 229 | 98.27 132 | 97.31 203 | 99.13 227 |
|
| mamba_0408 | | | 94.98 227 | 94.09 240 | 97.64 190 | 97.14 282 | 95.31 209 | 93.48 445 | 97.08 357 | 90.48 313 | 94.40 261 | 98.62 239 | 84.49 281 | 98.67 245 | 93.99 253 | 97.18 208 | 98.93 244 |
|
| SSM_04072 | | | 94.77 234 | 94.09 240 | 96.82 236 | 97.14 282 | 95.31 209 | 93.48 445 | 97.08 357 | 90.48 313 | 94.40 261 | 98.62 239 | 84.49 281 | 96.21 396 | 93.99 253 | 97.18 208 | 98.93 244 |
|
| SSM_0407 | | | 95.62 208 | 94.95 217 | 97.61 195 | 97.14 282 | 95.31 209 | 99.00 313 | 97.25 326 | 90.81 302 | 94.40 261 | 98.83 220 | 84.74 276 | 98.58 252 | 95.24 222 | 97.18 208 | 98.93 244 |
|
| SCA | | | 94.69 237 | 93.81 251 | 97.33 220 | 97.10 285 | 94.44 239 | 98.86 335 | 98.32 192 | 93.30 198 | 96.17 228 | 95.59 357 | 76.48 364 | 97.95 307 | 91.06 307 | 97.43 195 | 99.59 145 |
|
| viewmacassd2359aftdt | | | 95.93 193 | 95.45 194 | 97.36 217 | 97.09 286 | 94.12 254 | 99.57 230 | 97.26 325 | 93.05 210 | 96.50 215 | 99.17 171 | 82.76 297 | 98.68 243 | 96.61 198 | 97.04 215 | 99.28 212 |
|
| KinetiMVS | | | 96.10 186 | 95.29 203 | 98.53 125 | 97.08 287 | 97.12 123 | 99.56 233 | 98.12 225 | 94.78 127 | 98.44 142 | 98.94 201 | 80.30 329 | 99.39 185 | 91.56 300 | 98.79 156 | 99.06 235 |
|
| TAMVS | | | 95.85 196 | 95.58 191 | 96.65 244 | 97.07 288 | 93.50 271 | 99.17 290 | 97.82 256 | 91.39 286 | 95.02 254 | 98.01 277 | 92.20 155 | 97.30 334 | 93.75 265 | 95.83 248 | 99.14 226 |
|
| Fast-Effi-MVS+-dtu | | | 93.72 273 | 93.86 250 | 93.29 360 | 97.06 289 | 86.16 401 | 99.80 159 | 96.83 386 | 92.66 231 | 92.58 287 | 97.83 288 | 81.39 311 | 97.67 318 | 89.75 332 | 96.87 222 | 96.05 315 |
|
| CostFormer | | | 96.10 186 | 95.88 180 | 96.78 238 | 97.03 290 | 92.55 297 | 97.08 410 | 97.83 255 | 90.04 326 | 98.72 127 | 94.89 394 | 95.01 62 | 98.29 283 | 96.54 201 | 95.77 249 | 99.50 171 |
|
| test_fmvsmvis_n_1920 | | | 97.67 105 | 97.59 96 | 97.91 169 | 97.02 291 | 95.34 207 | 99.95 67 | 98.45 138 | 97.87 25 | 97.02 197 | 99.59 119 | 89.64 198 | 99.98 47 | 99.41 64 | 99.34 132 | 98.42 270 |
|
| test-LLR | | | 96.47 168 | 96.04 166 | 97.78 179 | 97.02 291 | 95.44 199 | 99.96 48 | 98.21 209 | 94.07 164 | 95.55 244 | 96.38 329 | 93.90 103 | 98.27 287 | 90.42 322 | 98.83 154 | 99.64 131 |
|
| test-mter | | | 96.39 174 | 95.93 177 | 97.78 179 | 97.02 291 | 95.44 199 | 99.96 48 | 98.21 209 | 91.81 270 | 95.55 244 | 96.38 329 | 95.17 55 | 98.27 287 | 90.42 322 | 98.83 154 | 99.64 131 |
|
| icg_test_0407_2 | | | 95.04 224 | 94.78 224 | 95.84 270 | 96.97 294 | 91.64 322 | 98.63 357 | 97.12 346 | 92.33 250 | 95.60 242 | 98.88 206 | 85.65 259 | 96.56 380 | 92.12 288 | 95.70 254 | 99.32 201 |
|
| IMVS_0407 | | | 95.21 219 | 94.80 223 | 96.46 249 | 96.97 294 | 91.64 322 | 98.81 340 | 97.12 346 | 92.33 250 | 95.60 242 | 98.88 206 | 85.65 259 | 98.42 264 | 92.12 288 | 95.70 254 | 99.32 201 |
|
| IMVS_0404 | | | 93.83 265 | 93.17 275 | 95.80 272 | 96.97 294 | 91.64 322 | 97.78 396 | 97.12 346 | 92.33 250 | 90.87 305 | 98.88 206 | 76.78 359 | 96.43 386 | 92.12 288 | 95.70 254 | 99.32 201 |
|
| IMVS_0403 | | | 95.25 217 | 94.81 222 | 96.58 246 | 96.97 294 | 91.64 322 | 98.97 320 | 97.12 346 | 92.33 250 | 95.43 247 | 98.88 206 | 85.78 258 | 98.79 226 | 92.12 288 | 95.70 254 | 99.32 201 |
|
| gm-plane-assit | | | | | | 96.97 294 | 93.76 263 | | | 91.47 280 | | 98.96 194 | | 98.79 226 | 94.92 230 | | |
|
| WB-MVSnew | | | 92.90 292 | 92.77 284 | 93.26 362 | 96.95 299 | 93.63 267 | 99.71 194 | 98.16 219 | 91.49 277 | 94.28 266 | 98.14 273 | 81.33 313 | 96.48 383 | 79.47 417 | 95.46 261 | 89.68 443 |
|
| QAPM | | | 95.40 213 | 94.17 238 | 99.10 74 | 96.92 300 | 97.71 94 | 99.40 258 | 98.68 79 | 89.31 334 | 88.94 346 | 98.89 205 | 82.48 299 | 99.96 71 | 93.12 278 | 99.83 77 | 99.62 138 |
|
| KD-MVS_2432*1600 | | | 88.00 380 | 86.10 384 | 93.70 351 | 96.91 301 | 94.04 255 | 97.17 407 | 97.12 346 | 84.93 402 | 81.96 413 | 92.41 427 | 92.48 148 | 94.51 429 | 79.23 418 | 52.68 463 | 92.56 413 |
|
| miper_refine_blended | | | 88.00 380 | 86.10 384 | 93.70 351 | 96.91 301 | 94.04 255 | 97.17 407 | 97.12 346 | 84.93 402 | 81.96 413 | 92.41 427 | 92.48 148 | 94.51 429 | 79.23 418 | 52.68 463 | 92.56 413 |
|
| tpm2 | | | 95.47 211 | 95.18 207 | 96.35 255 | 96.91 301 | 91.70 320 | 96.96 413 | 97.93 242 | 88.04 363 | 98.44 142 | 95.40 368 | 93.32 118 | 97.97 304 | 94.00 252 | 95.61 259 | 99.38 188 |
|
| FMVSNet5 | | | 88.32 376 | 87.47 378 | 90.88 392 | 96.90 304 | 88.39 385 | 97.28 404 | 95.68 421 | 82.60 422 | 84.67 401 | 92.40 429 | 79.83 332 | 91.16 451 | 76.39 433 | 81.51 382 | 93.09 404 |
|
| 3Dnovator+ | | 91.53 11 | 96.31 178 | 95.24 204 | 99.52 28 | 96.88 305 | 98.64 54 | 99.72 191 | 98.24 205 | 95.27 115 | 88.42 359 | 98.98 190 | 82.76 297 | 99.94 88 | 97.10 181 | 99.83 77 | 99.96 70 |
|
| Patchmatch-test | | | 92.65 300 | 91.50 311 | 96.10 261 | 96.85 306 | 90.49 348 | 91.50 453 | 97.19 334 | 82.76 421 | 90.23 311 | 95.59 357 | 95.02 61 | 98.00 303 | 77.41 428 | 96.98 220 | 99.82 102 |
|
| MVS | | | 96.60 162 | 95.56 192 | 99.72 13 | 96.85 306 | 99.22 20 | 98.31 374 | 98.94 44 | 91.57 275 | 90.90 304 | 99.61 118 | 86.66 246 | 99.96 71 | 97.36 173 | 99.88 73 | 99.99 23 |
|
| 3Dnovator | | 91.47 12 | 96.28 181 | 95.34 200 | 99.08 77 | 96.82 308 | 97.47 108 | 99.45 255 | 98.81 64 | 95.52 109 | 89.39 333 | 99.00 187 | 81.97 303 | 99.95 80 | 97.27 175 | 99.83 77 | 99.84 99 |
|
| EI-MVSNet | | | 93.73 272 | 93.40 267 | 94.74 305 | 96.80 309 | 92.69 292 | 99.06 303 | 97.67 269 | 88.96 343 | 91.39 298 | 99.02 183 | 88.75 215 | 97.30 334 | 91.07 306 | 87.85 332 | 94.22 344 |
|
| CVMVSNet | | | 94.68 239 | 94.94 218 | 93.89 345 | 96.80 309 | 86.92 398 | 99.06 303 | 98.98 41 | 94.45 141 | 94.23 268 | 99.02 183 | 85.60 262 | 95.31 418 | 90.91 312 | 95.39 264 | 99.43 183 |
|
| IterMVS-LS | | | 92.69 298 | 92.11 298 | 94.43 324 | 96.80 309 | 92.74 289 | 99.45 255 | 96.89 382 | 88.98 341 | 89.65 326 | 95.38 371 | 88.77 214 | 96.34 390 | 90.98 310 | 82.04 378 | 94.22 344 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| AstraMVS | | | 96.57 165 | 96.46 151 | 96.91 232 | 96.79 312 | 92.50 298 | 99.90 108 | 97.38 305 | 96.02 95 | 97.79 174 | 99.32 148 | 86.36 250 | 98.99 208 | 98.26 133 | 96.33 234 | 99.23 219 |
|
| IterMVS | | | 90.91 334 | 90.17 336 | 93.12 365 | 96.78 313 | 90.42 351 | 98.89 329 | 97.05 364 | 89.03 338 | 86.49 384 | 95.42 367 | 76.59 362 | 95.02 420 | 87.22 362 | 84.09 363 | 93.93 375 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| 1314 | | | 96.84 147 | 95.96 174 | 99.48 35 | 96.74 314 | 98.52 58 | 98.31 374 | 98.86 56 | 95.82 98 | 89.91 317 | 98.98 190 | 87.49 230 | 99.96 71 | 97.80 159 | 99.73 87 | 99.96 70 |
|
| IterMVS-SCA-FT | | | 90.85 337 | 90.16 337 | 92.93 370 | 96.72 315 | 89.96 360 | 98.89 329 | 96.99 368 | 88.95 344 | 86.63 381 | 95.67 353 | 76.48 364 | 95.00 421 | 87.04 365 | 84.04 366 | 93.84 382 |
|
| MVS-HIRNet | | | 86.22 387 | 83.19 400 | 95.31 288 | 96.71 316 | 90.29 352 | 92.12 450 | 97.33 313 | 62.85 458 | 86.82 378 | 70.37 463 | 69.37 405 | 97.49 324 | 75.12 436 | 97.99 185 | 98.15 277 |
|
| viewdifsd2359ckpt11 | | | 94.09 260 | 93.63 253 | 95.46 281 | 96.68 317 | 88.92 374 | 99.62 216 | 97.12 346 | 93.07 208 | 95.73 239 | 99.22 164 | 77.05 352 | 98.88 218 | 96.52 202 | 87.69 337 | 98.58 265 |
|
| viewmsd2359difaftdt | | | 94.09 260 | 93.64 252 | 95.46 281 | 96.68 317 | 88.92 374 | 99.62 216 | 97.13 345 | 93.07 208 | 95.73 239 | 99.22 164 | 77.05 352 | 98.89 217 | 96.52 202 | 87.70 336 | 98.58 265 |
|
| VDDNet | | | 93.12 287 | 91.91 303 | 96.76 239 | 96.67 319 | 92.65 295 | 98.69 352 | 98.21 209 | 82.81 420 | 97.75 176 | 99.28 153 | 61.57 437 | 99.48 180 | 98.09 143 | 94.09 283 | 98.15 277 |
|
| dmvs_re | | | 93.20 284 | 93.15 276 | 93.34 358 | 96.54 320 | 83.81 416 | 98.71 349 | 98.51 126 | 91.39 286 | 92.37 290 | 98.56 247 | 78.66 344 | 97.83 312 | 93.89 256 | 89.74 304 | 98.38 272 |
|
| Elysia | | | 94.50 246 | 93.38 268 | 97.85 173 | 96.49 321 | 96.70 140 | 98.98 315 | 97.78 259 | 90.81 302 | 96.19 226 | 98.55 249 | 73.63 388 | 98.98 209 | 89.41 333 | 98.56 162 | 97.88 284 |
|
| StellarMVS | | | 94.50 246 | 93.38 268 | 97.85 173 | 96.49 321 | 96.70 140 | 98.98 315 | 97.78 259 | 90.81 302 | 96.19 226 | 98.55 249 | 73.63 388 | 98.98 209 | 89.41 333 | 98.56 162 | 97.88 284 |
|
| MIMVSNet | | | 90.30 350 | 88.67 364 | 95.17 292 | 96.45 323 | 91.64 322 | 92.39 449 | 97.15 341 | 85.99 389 | 90.50 309 | 93.19 422 | 66.95 416 | 94.86 425 | 82.01 404 | 93.43 291 | 99.01 240 |
|
| CR-MVSNet | | | 93.45 281 | 92.62 286 | 95.94 265 | 96.29 324 | 92.66 293 | 92.01 451 | 96.23 408 | 92.62 233 | 96.94 199 | 93.31 420 | 91.04 175 | 96.03 404 | 79.23 418 | 95.96 242 | 99.13 227 |
|
| RPMNet | | | 89.76 362 | 87.28 379 | 97.19 223 | 96.29 324 | 92.66 293 | 92.01 451 | 98.31 194 | 70.19 454 | 96.94 199 | 85.87 456 | 87.25 235 | 99.78 141 | 62.69 458 | 95.96 242 | 99.13 227 |
|
| tt0805 | | | 91.28 327 | 90.18 335 | 94.60 311 | 96.26 326 | 87.55 391 | 98.39 372 | 98.72 73 | 89.00 340 | 89.22 339 | 98.47 257 | 62.98 432 | 98.96 213 | 90.57 318 | 88.00 331 | 97.28 302 |
|
| Patchmtry | | | 89.70 363 | 88.49 367 | 93.33 359 | 96.24 327 | 89.94 363 | 91.37 454 | 96.23 408 | 78.22 437 | 87.69 366 | 93.31 420 | 91.04 175 | 96.03 404 | 80.18 416 | 82.10 377 | 94.02 365 |
|
| test_vis1_rt | | | 86.87 385 | 86.05 387 | 89.34 411 | 96.12 328 | 78.07 445 | 99.87 124 | 83.54 471 | 92.03 262 | 78.21 434 | 89.51 441 | 45.80 457 | 99.91 105 | 96.25 206 | 93.11 296 | 90.03 440 |
|
| JIA-IIPM | | | 91.76 321 | 90.70 322 | 94.94 298 | 96.11 329 | 87.51 392 | 93.16 447 | 98.13 224 | 75.79 443 | 97.58 178 | 77.68 461 | 92.84 134 | 97.97 304 | 88.47 347 | 96.54 226 | 99.33 199 |
|
| OpenMVS |  | 90.15 15 | 94.77 234 | 93.59 257 | 98.33 140 | 96.07 330 | 97.48 107 | 99.56 233 | 98.57 102 | 90.46 315 | 86.51 383 | 98.95 199 | 78.57 345 | 99.94 88 | 93.86 257 | 99.74 86 | 97.57 297 |
|
| PAPM | | | 98.60 34 | 98.42 35 | 99.14 68 | 96.05 331 | 98.96 26 | 99.90 108 | 99.35 24 | 96.68 70 | 98.35 149 | 99.66 110 | 96.45 33 | 98.51 257 | 99.45 61 | 99.89 70 | 99.96 70 |
|
| CLD-MVS | | | 94.06 262 | 93.90 248 | 94.55 315 | 96.02 332 | 90.69 342 | 99.98 20 | 97.72 265 | 96.62 74 | 91.05 303 | 98.85 218 | 77.21 350 | 98.47 258 | 98.11 141 | 89.51 310 | 94.48 322 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| PatchT | | | 90.38 347 | 88.75 363 | 95.25 290 | 95.99 333 | 90.16 355 | 91.22 455 | 97.54 288 | 76.80 439 | 97.26 190 | 86.01 455 | 91.88 162 | 96.07 403 | 66.16 453 | 95.91 246 | 99.51 169 |
|
| ACMH+ | | 89.98 16 | 90.35 348 | 89.54 347 | 92.78 374 | 95.99 333 | 86.12 402 | 98.81 340 | 97.18 336 | 89.38 333 | 83.14 409 | 97.76 289 | 68.42 410 | 98.43 263 | 89.11 338 | 86.05 346 | 93.78 385 |
|
| DeepMVS_CX |  | | | | 82.92 433 | 95.98 335 | 58.66 464 | | 96.01 413 | 92.72 226 | 78.34 433 | 95.51 362 | 58.29 443 | 98.08 298 | 82.57 399 | 85.29 351 | 92.03 421 |
|
| ACMP | | 92.05 9 | 92.74 296 | 92.42 295 | 93.73 347 | 95.91 336 | 88.72 378 | 99.81 155 | 97.53 290 | 94.13 160 | 87.00 377 | 98.23 271 | 74.07 385 | 98.47 258 | 96.22 207 | 88.86 317 | 93.99 370 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| test_vis1_n | | | 93.61 276 | 93.03 278 | 95.35 285 | 95.86 337 | 86.94 397 | 99.87 124 | 96.36 406 | 96.85 61 | 99.54 70 | 98.79 222 | 52.41 451 | 99.83 134 | 98.64 110 | 98.97 148 | 99.29 210 |
|
| HQP-NCC | | | | | | 95.78 338 | | 99.87 124 | | 96.82 63 | 93.37 275 | | | | | | |
|
| ACMP_Plane | | | | | | 95.78 338 | | 99.87 124 | | 96.82 63 | 93.37 275 | | | | | | |
|
| HQP-MVS | | | 94.61 241 | 94.50 229 | 94.92 299 | 95.78 338 | 91.85 312 | 99.87 124 | 97.89 247 | 96.82 63 | 93.37 275 | 98.65 234 | 80.65 323 | 98.39 270 | 97.92 153 | 89.60 305 | 94.53 318 |
|
| NP-MVS | | | | | | 95.77 341 | 91.79 314 | | | | | 98.65 234 | | | | | |
|
| test_fmvsmconf0.1_n | | | 97.74 99 | 97.44 103 | 98.64 110 | 95.76 342 | 96.20 168 | 99.94 84 | 98.05 231 | 98.17 12 | 98.89 115 | 99.42 136 | 87.65 225 | 99.90 107 | 99.50 57 | 99.60 102 | 99.82 102 |
|
| plane_prior6 | | | | | | 95.76 342 | 91.72 319 | | | | | | 80.47 327 | | | | |
|
| ACMM | | 91.95 10 | 92.88 293 | 92.52 293 | 93.98 341 | 95.75 344 | 89.08 373 | 99.77 167 | 97.52 292 | 93.00 211 | 89.95 316 | 97.99 280 | 76.17 368 | 98.46 261 | 93.63 269 | 88.87 316 | 94.39 330 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| GA-MVS | | | 93.83 265 | 92.84 280 | 96.80 237 | 95.73 345 | 93.57 268 | 99.88 121 | 97.24 329 | 92.57 238 | 92.92 282 | 96.66 321 | 78.73 343 | 97.67 318 | 87.75 355 | 94.06 284 | 99.17 222 |
|
| plane_prior1 | | | | | | 95.73 345 | | | | | | | | | | | |
|
| jason | | | 97.24 125 | 96.86 130 | 98.38 139 | 95.73 345 | 97.32 112 | 99.97 38 | 97.40 304 | 95.34 113 | 98.60 136 | 99.54 128 | 87.70 224 | 98.56 254 | 97.94 152 | 99.47 119 | 99.25 216 |
| jason: jason. |
| mmtdpeth | | | 88.52 374 | 87.75 376 | 90.85 394 | 95.71 348 | 83.47 422 | 98.94 323 | 94.85 436 | 88.78 349 | 97.19 192 | 89.58 440 | 63.29 430 | 98.97 211 | 98.54 115 | 62.86 457 | 90.10 439 |
|
| HQP_MVS | | | 94.49 248 | 94.36 232 | 94.87 300 | 95.71 348 | 91.74 316 | 99.84 143 | 97.87 249 | 96.38 83 | 93.01 280 | 98.59 242 | 80.47 327 | 98.37 276 | 97.79 162 | 89.55 308 | 94.52 320 |
|
| plane_prior7 | | | | | | 95.71 348 | 91.59 328 | | | | | | | | | | |
|
| ITE_SJBPF | | | | | 92.38 377 | 95.69 351 | 85.14 408 | | 95.71 420 | 92.81 220 | 89.33 336 | 98.11 274 | 70.23 403 | 98.42 264 | 85.91 377 | 88.16 329 | 93.59 393 |
|
| fmvsm_s_conf0.1_n_a | | | 97.09 134 | 96.90 127 | 97.63 193 | 95.65 352 | 94.21 251 | 99.83 150 | 98.50 132 | 96.27 88 | 99.65 52 | 99.64 113 | 84.72 278 | 99.93 98 | 99.04 80 | 98.84 153 | 98.74 258 |
|
| ACMH | | 89.72 17 | 90.64 341 | 89.63 344 | 93.66 353 | 95.64 353 | 88.64 381 | 98.55 360 | 97.45 297 | 89.03 338 | 81.62 416 | 97.61 290 | 69.75 404 | 98.41 266 | 89.37 335 | 87.62 338 | 93.92 376 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| baseline2 | | | 96.71 157 | 96.49 148 | 97.37 215 | 95.63 354 | 95.96 177 | 99.74 180 | 98.88 54 | 92.94 213 | 91.61 296 | 98.97 192 | 97.72 6 | 98.62 251 | 94.83 234 | 98.08 183 | 97.53 299 |
|
| FMVSNet1 | | | 88.50 375 | 86.64 382 | 94.08 334 | 95.62 355 | 91.97 307 | 98.43 368 | 96.95 374 | 83.00 418 | 86.08 391 | 94.72 396 | 59.09 442 | 96.11 399 | 81.82 406 | 84.07 364 | 94.17 348 |
|
| LuminaMVS | | | 96.63 161 | 96.21 161 | 97.87 172 | 95.58 356 | 96.82 136 | 99.12 292 | 97.67 269 | 94.47 139 | 97.88 169 | 98.31 267 | 87.50 229 | 98.71 238 | 98.07 145 | 97.29 204 | 98.10 280 |
|
| LPG-MVS_test | | | 92.96 290 | 92.71 285 | 93.71 349 | 95.43 357 | 88.67 379 | 99.75 177 | 97.62 277 | 92.81 220 | 90.05 312 | 98.49 253 | 75.24 375 | 98.40 268 | 95.84 213 | 89.12 312 | 94.07 362 |
|
| LGP-MVS_train | | | | | 93.71 349 | 95.43 357 | 88.67 379 | | 97.62 277 | 92.81 220 | 90.05 312 | 98.49 253 | 75.24 375 | 98.40 268 | 95.84 213 | 89.12 312 | 94.07 362 |
|
| tpm | | | 93.70 274 | 93.41 266 | 94.58 313 | 95.36 359 | 87.41 393 | 97.01 411 | 96.90 381 | 90.85 300 | 96.72 207 | 94.14 411 | 90.40 189 | 96.84 367 | 90.75 316 | 88.54 324 | 99.51 169 |
|
| D2MVS | | | 92.76 295 | 92.59 291 | 93.27 361 | 95.13 360 | 89.54 367 | 99.69 202 | 99.38 22 | 92.26 255 | 87.59 368 | 94.61 402 | 85.05 271 | 97.79 313 | 91.59 299 | 88.01 330 | 92.47 416 |
|
| VPA-MVSNet | | | 92.70 297 | 91.55 310 | 96.16 259 | 95.09 361 | 96.20 168 | 98.88 331 | 99.00 39 | 91.02 297 | 91.82 295 | 95.29 378 | 76.05 370 | 97.96 306 | 95.62 218 | 81.19 384 | 94.30 337 |
|
| LTVRE_ROB | | 88.28 18 | 90.29 351 | 89.05 358 | 94.02 337 | 95.08 362 | 90.15 356 | 97.19 406 | 97.43 299 | 84.91 404 | 83.99 405 | 97.06 307 | 74.00 386 | 98.28 285 | 84.08 388 | 87.71 334 | 93.62 392 |
| 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 | | | 87.87 382 | 86.51 383 | 91.94 383 | 95.05 363 | 85.57 406 | 97.65 398 | 94.08 446 | 84.40 408 | 81.82 415 | 96.85 316 | 62.14 435 | 98.33 279 | 80.25 415 | 86.37 345 | 91.91 423 |
|
| test0.0.03 1 | | | 93.86 264 | 93.61 254 | 94.64 309 | 95.02 364 | 92.18 305 | 99.93 91 | 98.58 100 | 94.07 164 | 87.96 363 | 98.50 252 | 93.90 103 | 94.96 422 | 81.33 407 | 93.17 294 | 96.78 305 |
|
| UniMVSNet (Re) | | | 93.07 289 | 92.13 297 | 95.88 267 | 94.84 365 | 96.24 167 | 99.88 121 | 98.98 41 | 92.49 243 | 89.25 337 | 95.40 368 | 87.09 237 | 97.14 343 | 93.13 277 | 78.16 408 | 94.26 339 |
|
| USDC | | | 90.00 358 | 88.96 359 | 93.10 367 | 94.81 366 | 88.16 387 | 98.71 349 | 95.54 425 | 93.66 185 | 83.75 407 | 97.20 301 | 65.58 421 | 98.31 281 | 83.96 391 | 87.49 340 | 92.85 410 |
|
| VPNet | | | 91.81 315 | 90.46 326 | 95.85 269 | 94.74 367 | 95.54 196 | 98.98 315 | 98.59 98 | 92.14 257 | 90.77 308 | 97.44 294 | 68.73 408 | 97.54 323 | 94.89 233 | 77.89 410 | 94.46 323 |
|
| FIs | | | 94.10 259 | 93.43 263 | 96.11 260 | 94.70 368 | 96.82 136 | 99.58 227 | 98.93 48 | 92.54 239 | 89.34 335 | 97.31 298 | 87.62 226 | 97.10 347 | 94.22 251 | 86.58 343 | 94.40 329 |
|
| UniMVSNet_ETH3D | | | 90.06 357 | 88.58 366 | 94.49 319 | 94.67 369 | 88.09 388 | 97.81 395 | 97.57 285 | 83.91 411 | 88.44 355 | 97.41 295 | 57.44 444 | 97.62 320 | 91.41 301 | 88.59 323 | 97.77 289 |
|
| UniMVSNet_NR-MVSNet | | | 92.95 291 | 92.11 298 | 95.49 277 | 94.61 370 | 95.28 213 | 99.83 150 | 99.08 36 | 91.49 277 | 89.21 340 | 96.86 315 | 87.14 236 | 96.73 373 | 93.20 273 | 77.52 413 | 94.46 323 |
|
| test_fmvs2 | | | 89.47 367 | 89.70 343 | 88.77 418 | 94.54 371 | 75.74 447 | 99.83 150 | 94.70 442 | 94.71 131 | 91.08 301 | 96.82 320 | 54.46 447 | 97.78 315 | 92.87 280 | 88.27 327 | 92.80 411 |
|
| MonoMVSNet | | | 94.82 229 | 94.43 230 | 95.98 263 | 94.54 371 | 90.73 341 | 99.03 310 | 97.06 361 | 93.16 203 | 93.15 279 | 95.47 365 | 88.29 218 | 97.57 321 | 97.85 157 | 91.33 302 | 99.62 138 |
|
| WR-MVS | | | 92.31 307 | 91.25 315 | 95.48 280 | 94.45 373 | 95.29 212 | 99.60 223 | 98.68 79 | 90.10 323 | 88.07 362 | 96.89 313 | 80.68 322 | 96.80 371 | 93.14 276 | 79.67 401 | 94.36 331 |
|
| nrg030 | | | 93.51 278 | 92.53 292 | 96.45 250 | 94.36 374 | 97.20 118 | 99.81 155 | 97.16 340 | 91.60 274 | 89.86 319 | 97.46 293 | 86.37 249 | 97.68 317 | 95.88 212 | 80.31 397 | 94.46 323 |
|
| tfpnnormal | | | 89.29 370 | 87.61 377 | 94.34 327 | 94.35 375 | 94.13 253 | 98.95 322 | 98.94 44 | 83.94 409 | 84.47 402 | 95.51 362 | 74.84 380 | 97.39 326 | 77.05 431 | 80.41 395 | 91.48 426 |
|
| FC-MVSNet-test | | | 93.81 268 | 93.15 276 | 95.80 272 | 94.30 376 | 96.20 168 | 99.42 257 | 98.89 52 | 92.33 250 | 89.03 345 | 97.27 300 | 87.39 232 | 96.83 369 | 93.20 273 | 86.48 344 | 94.36 331 |
|
| SSC-MVS3.2 | | | 89.59 365 | 88.66 365 | 92.38 377 | 94.29 377 | 86.12 402 | 99.49 246 | 97.66 272 | 90.28 322 | 88.63 352 | 95.18 382 | 64.46 426 | 96.88 365 | 85.30 381 | 82.66 372 | 94.14 357 |
|
| MS-PatchMatch | | | 90.65 340 | 90.30 331 | 91.71 388 | 94.22 378 | 85.50 407 | 98.24 378 | 97.70 266 | 88.67 352 | 86.42 386 | 96.37 331 | 67.82 413 | 98.03 302 | 83.62 393 | 99.62 95 | 91.60 424 |
|
| WR-MVS_H | | | 91.30 325 | 90.35 329 | 94.15 331 | 94.17 379 | 92.62 296 | 99.17 290 | 98.94 44 | 88.87 347 | 86.48 385 | 94.46 407 | 84.36 284 | 96.61 378 | 88.19 349 | 78.51 406 | 93.21 402 |
|
| DU-MVS | | | 92.46 304 | 91.45 313 | 95.49 277 | 94.05 380 | 95.28 213 | 99.81 155 | 98.74 72 | 92.25 256 | 89.21 340 | 96.64 323 | 81.66 308 | 96.73 373 | 93.20 273 | 77.52 413 | 94.46 323 |
|
| NR-MVSNet | | | 91.56 323 | 90.22 333 | 95.60 275 | 94.05 380 | 95.76 184 | 98.25 377 | 98.70 75 | 91.16 291 | 80.78 422 | 96.64 323 | 83.23 294 | 96.57 379 | 91.41 301 | 77.73 412 | 94.46 323 |
|
| CP-MVSNet | | | 91.23 329 | 90.22 333 | 94.26 329 | 93.96 382 | 92.39 301 | 99.09 296 | 98.57 102 | 88.95 344 | 86.42 386 | 96.57 326 | 79.19 338 | 96.37 388 | 90.29 325 | 78.95 403 | 94.02 365 |
|
| XXY-MVS | | | 91.82 314 | 90.46 326 | 95.88 267 | 93.91 383 | 95.40 203 | 98.87 334 | 97.69 268 | 88.63 354 | 87.87 364 | 97.08 305 | 74.38 384 | 97.89 310 | 91.66 298 | 84.07 364 | 94.35 334 |
|
| PS-CasMVS | | | 90.63 342 | 89.51 349 | 93.99 340 | 93.83 384 | 91.70 320 | 98.98 315 | 98.52 123 | 88.48 356 | 86.15 390 | 96.53 328 | 75.46 373 | 96.31 392 | 88.83 340 | 78.86 405 | 93.95 373 |
|
| test_0402 | | | 85.58 389 | 83.94 394 | 90.50 400 | 93.81 385 | 85.04 409 | 98.55 360 | 95.20 433 | 76.01 441 | 79.72 428 | 95.13 383 | 64.15 428 | 96.26 394 | 66.04 454 | 86.88 342 | 90.21 437 |
|
| XVG-ACMP-BASELINE | | | 91.22 330 | 90.75 321 | 92.63 376 | 93.73 386 | 85.61 405 | 98.52 364 | 97.44 298 | 92.77 224 | 89.90 318 | 96.85 316 | 66.64 418 | 98.39 270 | 92.29 285 | 88.61 321 | 93.89 378 |
|
| TranMVSNet+NR-MVSNet | | | 91.68 322 | 90.61 325 | 94.87 300 | 93.69 387 | 93.98 258 | 99.69 202 | 98.65 83 | 91.03 296 | 88.44 355 | 96.83 319 | 80.05 331 | 96.18 397 | 90.26 326 | 76.89 421 | 94.45 328 |
|
| TransMVSNet (Re) | | | 87.25 383 | 85.28 390 | 93.16 364 | 93.56 388 | 91.03 333 | 98.54 362 | 94.05 448 | 83.69 413 | 81.09 420 | 96.16 337 | 75.32 374 | 96.40 387 | 76.69 432 | 68.41 445 | 92.06 420 |
|
| v10 | | | 90.25 352 | 88.82 361 | 94.57 314 | 93.53 389 | 93.43 273 | 99.08 298 | 96.87 384 | 85.00 401 | 87.34 375 | 94.51 403 | 80.93 318 | 97.02 357 | 82.85 398 | 79.23 402 | 93.26 400 |
|
| testgi | | | 89.01 372 | 88.04 373 | 91.90 384 | 93.49 390 | 84.89 411 | 99.73 187 | 95.66 422 | 93.89 178 | 85.14 397 | 98.17 272 | 59.68 441 | 94.66 428 | 77.73 427 | 88.88 315 | 96.16 314 |
|
| v8 | | | 90.54 344 | 89.17 354 | 94.66 308 | 93.43 391 | 93.40 276 | 99.20 287 | 96.94 378 | 85.76 392 | 87.56 369 | 94.51 403 | 81.96 304 | 97.19 340 | 84.94 384 | 78.25 407 | 93.38 398 |
|
| V42 | | | 91.28 327 | 90.12 338 | 94.74 305 | 93.42 392 | 93.46 272 | 99.68 205 | 97.02 365 | 87.36 371 | 89.85 321 | 95.05 386 | 81.31 314 | 97.34 329 | 87.34 360 | 80.07 399 | 93.40 396 |
|
| pm-mvs1 | | | 89.36 369 | 87.81 375 | 94.01 338 | 93.40 393 | 91.93 310 | 98.62 358 | 96.48 404 | 86.25 387 | 83.86 406 | 96.14 339 | 73.68 387 | 97.04 353 | 86.16 374 | 75.73 426 | 93.04 406 |
|
| v1144 | | | 91.09 331 | 89.83 340 | 94.87 300 | 93.25 394 | 93.69 266 | 99.62 216 | 96.98 370 | 86.83 381 | 89.64 327 | 94.99 391 | 80.94 317 | 97.05 350 | 85.08 383 | 81.16 385 | 93.87 380 |
|
| v1192 | | | 90.62 343 | 89.25 353 | 94.72 307 | 93.13 395 | 93.07 280 | 99.50 244 | 97.02 365 | 86.33 386 | 89.56 331 | 95.01 388 | 79.22 337 | 97.09 349 | 82.34 402 | 81.16 385 | 94.01 367 |
|
| v2v482 | | | 91.30 325 | 90.07 339 | 95.01 295 | 93.13 395 | 93.79 261 | 99.77 167 | 97.02 365 | 88.05 362 | 89.25 337 | 95.37 372 | 80.73 321 | 97.15 342 | 87.28 361 | 80.04 400 | 94.09 361 |
|
| OPM-MVS | | | 93.21 283 | 92.80 282 | 94.44 322 | 93.12 397 | 90.85 340 | 99.77 167 | 97.61 280 | 96.19 91 | 91.56 297 | 98.65 234 | 75.16 379 | 98.47 258 | 93.78 264 | 89.39 311 | 93.99 370 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| v144192 | | | 90.79 338 | 89.52 348 | 94.59 312 | 93.11 398 | 92.77 287 | 99.56 233 | 96.99 368 | 86.38 385 | 89.82 322 | 94.95 393 | 80.50 326 | 97.10 347 | 83.98 390 | 80.41 395 | 93.90 377 |
|
| PEN-MVS | | | 90.19 354 | 89.06 357 | 93.57 354 | 93.06 399 | 90.90 338 | 99.06 303 | 98.47 135 | 88.11 361 | 85.91 392 | 96.30 333 | 76.67 360 | 95.94 407 | 87.07 364 | 76.91 420 | 93.89 378 |
|
| v1240 | | | 90.20 353 | 88.79 362 | 94.44 322 | 93.05 400 | 92.27 303 | 99.38 264 | 96.92 380 | 85.89 390 | 89.36 334 | 94.87 395 | 77.89 349 | 97.03 355 | 80.66 411 | 81.08 388 | 94.01 367 |
|
| v148 | | | 90.70 339 | 89.63 344 | 93.92 342 | 92.97 401 | 90.97 334 | 99.75 177 | 96.89 382 | 87.51 368 | 88.27 360 | 95.01 388 | 81.67 307 | 97.04 353 | 87.40 359 | 77.17 418 | 93.75 386 |
|
| v1921920 | | | 90.46 345 | 89.12 355 | 94.50 318 | 92.96 402 | 92.46 299 | 99.49 246 | 96.98 370 | 86.10 388 | 89.61 329 | 95.30 375 | 78.55 346 | 97.03 355 | 82.17 403 | 80.89 393 | 94.01 367 |
|
| MVStest1 | | | 85.03 395 | 82.76 404 | 91.83 385 | 92.95 403 | 89.16 372 | 98.57 359 | 94.82 437 | 71.68 452 | 68.54 455 | 95.11 385 | 83.17 295 | 95.66 411 | 74.69 437 | 65.32 452 | 90.65 433 |
|
| tt0320-xc | | | 82.94 409 | 80.35 416 | 90.72 398 | 92.90 404 | 83.54 420 | 96.85 416 | 94.73 440 | 63.12 457 | 79.85 427 | 93.77 415 | 49.43 455 | 95.46 414 | 80.98 410 | 71.54 435 | 93.16 403 |
|
| Baseline_NR-MVSNet | | | 90.33 349 | 89.51 349 | 92.81 373 | 92.84 405 | 89.95 361 | 99.77 167 | 93.94 449 | 84.69 406 | 89.04 344 | 95.66 354 | 81.66 308 | 96.52 381 | 90.99 309 | 76.98 419 | 91.97 422 |
|
| test_method | | | 80.79 415 | 79.70 418 | 84.08 430 | 92.83 406 | 67.06 456 | 99.51 242 | 95.42 427 | 54.34 462 | 81.07 421 | 93.53 417 | 44.48 458 | 92.22 448 | 78.90 422 | 77.23 417 | 92.94 408 |
|
| pmmvs4 | | | 92.10 311 | 91.07 319 | 95.18 291 | 92.82 407 | 94.96 224 | 99.48 249 | 96.83 386 | 87.45 370 | 88.66 351 | 96.56 327 | 83.78 289 | 96.83 369 | 89.29 336 | 84.77 358 | 93.75 386 |
|
| LF4IMVS | | | 89.25 371 | 88.85 360 | 90.45 402 | 92.81 408 | 81.19 437 | 98.12 385 | 94.79 438 | 91.44 281 | 86.29 388 | 97.11 303 | 65.30 424 | 98.11 296 | 88.53 345 | 85.25 352 | 92.07 419 |
|
| tt0320 | | | 83.56 408 | 81.15 411 | 90.77 396 | 92.77 409 | 83.58 419 | 96.83 417 | 95.52 426 | 63.26 456 | 81.36 418 | 92.54 425 | 53.26 449 | 95.77 409 | 80.45 412 | 74.38 429 | 92.96 407 |
|
| DTE-MVSNet | | | 89.40 368 | 88.24 371 | 92.88 371 | 92.66 410 | 89.95 361 | 99.10 295 | 98.22 208 | 87.29 372 | 85.12 398 | 96.22 335 | 76.27 367 | 95.30 419 | 83.56 394 | 75.74 425 | 93.41 395 |
|
| EU-MVSNet | | | 90.14 356 | 90.34 330 | 89.54 410 | 92.55 411 | 81.06 438 | 98.69 352 | 98.04 232 | 91.41 285 | 86.59 382 | 96.84 318 | 80.83 320 | 93.31 441 | 86.20 373 | 81.91 379 | 94.26 339 |
|
| APD_test1 | | | 81.15 413 | 80.92 413 | 81.86 434 | 92.45 412 | 59.76 463 | 96.04 431 | 93.61 452 | 73.29 450 | 77.06 437 | 96.64 323 | 44.28 459 | 96.16 398 | 72.35 441 | 82.52 373 | 89.67 444 |
|
| sc_t1 | | | 85.01 396 | 82.46 406 | 92.67 375 | 92.44 413 | 83.09 423 | 97.39 402 | 95.72 419 | 65.06 455 | 85.64 395 | 96.16 337 | 49.50 454 | 97.34 329 | 84.86 385 | 75.39 427 | 97.57 297 |
|
| our_test_3 | | | 90.39 346 | 89.48 351 | 93.12 365 | 92.40 414 | 89.57 366 | 99.33 271 | 96.35 407 | 87.84 366 | 85.30 396 | 94.99 391 | 84.14 287 | 96.09 402 | 80.38 413 | 84.56 359 | 93.71 391 |
|
| ppachtmachnet_test | | | 89.58 366 | 88.35 369 | 93.25 363 | 92.40 414 | 90.44 350 | 99.33 271 | 96.73 393 | 85.49 397 | 85.90 393 | 95.77 348 | 81.09 316 | 96.00 406 | 76.00 435 | 82.49 374 | 93.30 399 |
|
| v7n | | | 89.65 364 | 88.29 370 | 93.72 348 | 92.22 416 | 90.56 347 | 99.07 302 | 97.10 353 | 85.42 399 | 86.73 379 | 94.72 396 | 80.06 330 | 97.13 344 | 81.14 408 | 78.12 409 | 93.49 394 |
|
| dmvs_testset | | | 83.79 405 | 86.07 386 | 76.94 438 | 92.14 417 | 48.60 473 | 96.75 418 | 90.27 463 | 89.48 332 | 78.65 431 | 98.55 249 | 79.25 336 | 86.65 461 | 66.85 451 | 82.69 371 | 95.57 316 |
|
| PS-MVSNAJss | | | 93.64 275 | 93.31 272 | 94.61 310 | 92.11 418 | 92.19 304 | 99.12 292 | 97.38 305 | 92.51 242 | 88.45 354 | 96.99 311 | 91.20 170 | 97.29 337 | 94.36 245 | 87.71 334 | 94.36 331 |
|
| pmmvs5 | | | 90.17 355 | 89.09 356 | 93.40 357 | 92.10 419 | 89.77 364 | 99.74 180 | 95.58 424 | 85.88 391 | 87.24 376 | 95.74 349 | 73.41 390 | 96.48 383 | 88.54 344 | 83.56 368 | 93.95 373 |
|
| N_pmnet | | | 80.06 418 | 80.78 414 | 77.89 437 | 91.94 420 | 45.28 475 | 98.80 343 | 56.82 477 | 78.10 438 | 80.08 425 | 93.33 418 | 77.03 354 | 95.76 410 | 68.14 449 | 82.81 370 | 92.64 412 |
|
| test_djsdf | | | 92.83 294 | 92.29 296 | 94.47 320 | 91.90 421 | 92.46 299 | 99.55 236 | 97.27 323 | 91.17 289 | 89.96 315 | 96.07 343 | 81.10 315 | 96.89 363 | 94.67 240 | 88.91 314 | 94.05 364 |
|
| SixPastTwentyTwo | | | 88.73 373 | 88.01 374 | 90.88 392 | 91.85 422 | 82.24 429 | 98.22 382 | 95.18 434 | 88.97 342 | 82.26 412 | 96.89 313 | 71.75 395 | 96.67 376 | 84.00 389 | 82.98 369 | 93.72 390 |
|
| K. test v3 | | | 88.05 379 | 87.24 380 | 90.47 401 | 91.82 423 | 82.23 430 | 98.96 321 | 97.42 301 | 89.05 337 | 76.93 439 | 95.60 356 | 68.49 409 | 95.42 415 | 85.87 378 | 81.01 391 | 93.75 386 |
|
| OurMVSNet-221017-0 | | | 89.81 361 | 89.48 351 | 90.83 395 | 91.64 424 | 81.21 436 | 98.17 384 | 95.38 429 | 91.48 279 | 85.65 394 | 97.31 298 | 72.66 391 | 97.29 337 | 88.15 350 | 84.83 357 | 93.97 372 |
|
| mvs_tets | | | 91.81 315 | 91.08 318 | 94.00 339 | 91.63 425 | 90.58 346 | 98.67 354 | 97.43 299 | 92.43 244 | 87.37 374 | 97.05 308 | 71.76 394 | 97.32 332 | 94.75 237 | 88.68 320 | 94.11 360 |
|
| Gipuma |  | | 66.95 431 | 65.00 431 | 72.79 443 | 91.52 426 | 67.96 455 | 66.16 466 | 95.15 435 | 47.89 464 | 58.54 461 | 67.99 466 | 29.74 463 | 87.54 460 | 50.20 465 | 77.83 411 | 62.87 466 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| test_fmvsmconf0.01_n | | | 96.39 174 | 95.74 185 | 98.32 141 | 91.47 427 | 95.56 195 | 99.84 143 | 97.30 318 | 97.74 29 | 97.89 168 | 99.35 147 | 79.62 333 | 99.85 124 | 99.25 70 | 99.24 136 | 99.55 155 |
|
| jajsoiax | | | 91.92 313 | 91.18 316 | 94.15 331 | 91.35 428 | 90.95 337 | 99.00 313 | 97.42 301 | 92.61 234 | 87.38 373 | 97.08 305 | 72.46 392 | 97.36 327 | 94.53 243 | 88.77 318 | 94.13 359 |
|
| MDA-MVSNet-bldmvs | | | 84.09 403 | 81.52 410 | 91.81 386 | 91.32 429 | 88.00 390 | 98.67 354 | 95.92 415 | 80.22 432 | 55.60 464 | 93.32 419 | 68.29 411 | 93.60 439 | 73.76 438 | 76.61 422 | 93.82 384 |
|
| MVP-Stereo | | | 90.93 333 | 90.45 328 | 92.37 379 | 91.25 430 | 88.76 376 | 98.05 389 | 96.17 410 | 87.27 373 | 84.04 403 | 95.30 375 | 78.46 347 | 97.27 339 | 83.78 392 | 99.70 89 | 91.09 427 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| MDA-MVSNet_test_wron | | | 85.51 391 | 83.32 399 | 92.10 381 | 90.96 431 | 88.58 382 | 99.20 287 | 96.52 402 | 79.70 434 | 57.12 463 | 92.69 424 | 79.11 339 | 93.86 435 | 77.10 430 | 77.46 415 | 93.86 381 |
|
| YYNet1 | | | 85.50 392 | 83.33 398 | 92.00 382 | 90.89 432 | 88.38 386 | 99.22 286 | 96.55 401 | 79.60 435 | 57.26 462 | 92.72 423 | 79.09 341 | 93.78 437 | 77.25 429 | 77.37 416 | 93.84 382 |
|
| anonymousdsp | | | 91.79 320 | 90.92 320 | 94.41 325 | 90.76 433 | 92.93 286 | 98.93 325 | 97.17 338 | 89.08 336 | 87.46 372 | 95.30 375 | 78.43 348 | 96.92 361 | 92.38 284 | 88.73 319 | 93.39 397 |
|
| lessismore_v0 | | | | | 90.53 399 | 90.58 434 | 80.90 439 | | 95.80 416 | | 77.01 438 | 95.84 346 | 66.15 420 | 96.95 359 | 83.03 397 | 75.05 428 | 93.74 389 |
|
| EG-PatchMatch MVS | | | 85.35 393 | 83.81 396 | 89.99 408 | 90.39 435 | 81.89 432 | 98.21 383 | 96.09 412 | 81.78 425 | 74.73 445 | 93.72 416 | 51.56 453 | 97.12 346 | 79.16 421 | 88.61 321 | 90.96 430 |
|
| EGC-MVSNET | | | 69.38 424 | 63.76 434 | 86.26 427 | 90.32 436 | 81.66 435 | 96.24 427 | 93.85 450 | 0.99 474 | 3.22 475 | 92.33 430 | 52.44 450 | 92.92 444 | 59.53 461 | 84.90 356 | 84.21 455 |
|
| CMPMVS |  | 61.59 21 | 84.75 399 | 85.14 391 | 83.57 431 | 90.32 436 | 62.54 459 | 96.98 412 | 97.59 284 | 74.33 448 | 69.95 452 | 96.66 321 | 64.17 427 | 98.32 280 | 87.88 354 | 88.41 326 | 89.84 442 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| new_pmnet | | | 84.49 402 | 82.92 402 | 89.21 412 | 90.03 438 | 82.60 426 | 96.89 415 | 95.62 423 | 80.59 430 | 75.77 444 | 89.17 442 | 65.04 425 | 94.79 426 | 72.12 442 | 81.02 390 | 90.23 436 |
|
| pmmvs6 | | | 85.69 388 | 83.84 395 | 91.26 391 | 90.00 439 | 84.41 414 | 97.82 394 | 96.15 411 | 75.86 442 | 81.29 419 | 95.39 370 | 61.21 438 | 96.87 366 | 83.52 395 | 73.29 431 | 92.50 415 |
|
| ttmdpeth | | | 88.23 378 | 87.06 381 | 91.75 387 | 89.91 440 | 87.35 394 | 98.92 328 | 95.73 418 | 87.92 364 | 84.02 404 | 96.31 332 | 68.23 412 | 96.84 367 | 86.33 372 | 76.12 423 | 91.06 428 |
|
| DSMNet-mixed | | | 88.28 377 | 88.24 371 | 88.42 420 | 89.64 441 | 75.38 449 | 98.06 388 | 89.86 464 | 85.59 396 | 88.20 361 | 92.14 431 | 76.15 369 | 91.95 449 | 78.46 424 | 96.05 239 | 97.92 283 |
|
| UnsupCasMVSNet_eth | | | 85.52 390 | 83.99 392 | 90.10 406 | 89.36 442 | 83.51 421 | 96.65 419 | 97.99 235 | 89.14 335 | 75.89 443 | 93.83 413 | 63.25 431 | 93.92 433 | 81.92 405 | 67.90 448 | 92.88 409 |
|
| Anonymous20231206 | | | 86.32 386 | 85.42 389 | 89.02 414 | 89.11 443 | 80.53 442 | 99.05 307 | 95.28 430 | 85.43 398 | 82.82 410 | 93.92 412 | 74.40 383 | 93.44 440 | 66.99 450 | 81.83 380 | 93.08 405 |
|
| Anonymous20240521 | | | 85.15 394 | 83.81 396 | 89.16 413 | 88.32 444 | 82.69 425 | 98.80 343 | 95.74 417 | 79.72 433 | 81.53 417 | 90.99 434 | 65.38 423 | 94.16 431 | 72.69 440 | 81.11 387 | 90.63 434 |
|
| OpenMVS_ROB |  | 79.82 20 | 83.77 406 | 81.68 409 | 90.03 407 | 88.30 445 | 82.82 424 | 98.46 365 | 95.22 432 | 73.92 449 | 76.00 442 | 91.29 433 | 55.00 446 | 96.94 360 | 68.40 448 | 88.51 325 | 90.34 435 |
|
| test20.03 | | | 84.72 400 | 83.99 392 | 86.91 425 | 88.19 446 | 80.62 441 | 98.88 331 | 95.94 414 | 88.36 358 | 78.87 429 | 94.62 401 | 68.75 407 | 89.11 456 | 66.52 452 | 75.82 424 | 91.00 429 |
|
| KD-MVS_self_test | | | 83.59 407 | 82.06 407 | 88.20 421 | 86.93 447 | 80.70 440 | 97.21 405 | 96.38 405 | 82.87 419 | 82.49 411 | 88.97 443 | 67.63 414 | 92.32 447 | 73.75 439 | 62.30 459 | 91.58 425 |
|
| MIMVSNet1 | | | 82.58 410 | 80.51 415 | 88.78 416 | 86.68 448 | 84.20 415 | 96.65 419 | 95.41 428 | 78.75 436 | 78.59 432 | 92.44 426 | 51.88 452 | 89.76 455 | 65.26 455 | 78.95 403 | 92.38 418 |
|
| CL-MVSNet_self_test | | | 84.50 401 | 83.15 401 | 88.53 419 | 86.00 449 | 81.79 433 | 98.82 339 | 97.35 309 | 85.12 400 | 83.62 408 | 90.91 436 | 76.66 361 | 91.40 450 | 69.53 446 | 60.36 460 | 92.40 417 |
|
| UnsupCasMVSNet_bld | | | 79.97 420 | 77.03 425 | 88.78 416 | 85.62 450 | 81.98 431 | 93.66 443 | 97.35 309 | 75.51 445 | 70.79 451 | 83.05 458 | 48.70 456 | 94.91 424 | 78.31 425 | 60.29 461 | 89.46 447 |
|
| mvs5depth | | | 84.87 397 | 82.90 403 | 90.77 396 | 85.59 451 | 84.84 412 | 91.10 456 | 93.29 454 | 83.14 416 | 85.07 399 | 94.33 409 | 62.17 434 | 97.32 332 | 78.83 423 | 72.59 434 | 90.14 438 |
|
| Patchmatch-RL test | | | 86.90 384 | 85.98 388 | 89.67 409 | 84.45 452 | 75.59 448 | 89.71 459 | 92.43 456 | 86.89 380 | 77.83 436 | 90.94 435 | 94.22 92 | 93.63 438 | 87.75 355 | 69.61 439 | 99.79 107 |
|
| pmmvs-eth3d | | | 84.03 404 | 81.97 408 | 90.20 405 | 84.15 453 | 87.09 396 | 98.10 387 | 94.73 440 | 83.05 417 | 74.10 448 | 87.77 449 | 65.56 422 | 94.01 432 | 81.08 409 | 69.24 441 | 89.49 446 |
|
| test_fmvs3 | | | 79.99 419 | 80.17 417 | 79.45 436 | 84.02 454 | 62.83 457 | 99.05 307 | 93.49 453 | 88.29 360 | 80.06 426 | 86.65 453 | 28.09 465 | 88.00 457 | 88.63 341 | 73.27 432 | 87.54 453 |
|
| PM-MVS | | | 80.47 416 | 78.88 420 | 85.26 428 | 83.79 455 | 72.22 451 | 95.89 434 | 91.08 461 | 85.71 395 | 76.56 441 | 88.30 445 | 36.64 461 | 93.90 434 | 82.39 401 | 69.57 440 | 89.66 445 |
|
| new-patchmatchnet | | | 81.19 412 | 79.34 419 | 86.76 426 | 82.86 456 | 80.36 443 | 97.92 391 | 95.27 431 | 82.09 424 | 72.02 449 | 86.87 452 | 62.81 433 | 90.74 453 | 71.10 443 | 63.08 456 | 89.19 449 |
|
| FE-MVSNET | | | 81.05 414 | 78.81 421 | 87.79 423 | 81.98 457 | 83.70 417 | 98.23 380 | 91.78 460 | 81.27 427 | 74.29 447 | 87.44 450 | 60.92 440 | 90.67 454 | 64.92 456 | 68.43 444 | 89.01 450 |
|
| mvsany_test3 | | | 82.12 411 | 81.14 412 | 85.06 429 | 81.87 458 | 70.41 453 | 97.09 409 | 92.14 457 | 91.27 288 | 77.84 435 | 88.73 444 | 39.31 460 | 95.49 412 | 90.75 316 | 71.24 436 | 89.29 448 |
|
| WB-MVS | | | 76.28 422 | 77.28 424 | 73.29 442 | 81.18 459 | 54.68 467 | 97.87 393 | 94.19 445 | 81.30 426 | 69.43 453 | 90.70 437 | 77.02 355 | 82.06 465 | 35.71 470 | 68.11 447 | 83.13 456 |
|
| test_f | | | 78.40 421 | 77.59 423 | 80.81 435 | 80.82 460 | 62.48 460 | 96.96 413 | 93.08 455 | 83.44 414 | 74.57 446 | 84.57 457 | 27.95 466 | 92.63 445 | 84.15 387 | 72.79 433 | 87.32 454 |
|
| SSC-MVS | | | 75.42 423 | 76.40 426 | 72.49 446 | 80.68 461 | 53.62 468 | 97.42 400 | 94.06 447 | 80.42 431 | 68.75 454 | 90.14 439 | 76.54 363 | 81.66 466 | 33.25 471 | 66.34 451 | 82.19 457 |
|
| pmmvs3 | | | 80.27 417 | 77.77 422 | 87.76 424 | 80.32 462 | 82.43 428 | 98.23 380 | 91.97 458 | 72.74 451 | 78.75 430 | 87.97 448 | 57.30 445 | 90.99 452 | 70.31 444 | 62.37 458 | 89.87 441 |
|
| testf1 | | | 68.38 427 | 66.92 428 | 72.78 444 | 78.80 463 | 50.36 470 | 90.95 457 | 87.35 469 | 55.47 460 | 58.95 459 | 88.14 446 | 20.64 470 | 87.60 458 | 57.28 462 | 64.69 453 | 80.39 459 |
|
| APD_test2 | | | 68.38 427 | 66.92 428 | 72.78 444 | 78.80 463 | 50.36 470 | 90.95 457 | 87.35 469 | 55.47 460 | 58.95 459 | 88.14 446 | 20.64 470 | 87.60 458 | 57.28 462 | 64.69 453 | 80.39 459 |
|
| ambc | | | | | 83.23 432 | 77.17 465 | 62.61 458 | 87.38 461 | 94.55 444 | | 76.72 440 | 86.65 453 | 30.16 462 | 96.36 389 | 84.85 386 | 69.86 438 | 90.73 432 |
|
| test_vis3_rt | | | 68.82 425 | 66.69 430 | 75.21 441 | 76.24 466 | 60.41 462 | 96.44 422 | 68.71 476 | 75.13 446 | 50.54 467 | 69.52 465 | 16.42 475 | 96.32 391 | 80.27 414 | 66.92 450 | 68.89 463 |
|
| TDRefinement | | | 84.76 398 | 82.56 405 | 91.38 390 | 74.58 467 | 84.80 413 | 97.36 403 | 94.56 443 | 84.73 405 | 80.21 424 | 96.12 342 | 63.56 429 | 98.39 270 | 87.92 353 | 63.97 455 | 90.95 431 |
|
| E-PMN | | | 52.30 435 | 52.18 437 | 52.67 452 | 71.51 468 | 45.40 474 | 93.62 444 | 76.60 474 | 36.01 468 | 43.50 469 | 64.13 468 | 27.11 467 | 67.31 471 | 31.06 472 | 26.06 467 | 45.30 470 |
|
| EMVS | | | 51.44 437 | 51.22 439 | 52.11 453 | 70.71 469 | 44.97 476 | 94.04 440 | 75.66 475 | 35.34 470 | 42.40 470 | 61.56 471 | 28.93 464 | 65.87 472 | 27.64 473 | 24.73 468 | 45.49 469 |
|
| PMMVS2 | | | 67.15 430 | 64.15 433 | 76.14 440 | 70.56 470 | 62.07 461 | 93.89 441 | 87.52 468 | 58.09 459 | 60.02 458 | 78.32 460 | 22.38 469 | 84.54 463 | 59.56 460 | 47.03 465 | 81.80 458 |
|
| FPMVS | | | 68.72 426 | 68.72 427 | 68.71 448 | 65.95 471 | 44.27 477 | 95.97 433 | 94.74 439 | 51.13 463 | 53.26 465 | 90.50 438 | 25.11 468 | 83.00 464 | 60.80 459 | 80.97 392 | 78.87 461 |
|
| wuyk23d | | | 20.37 441 | 20.84 444 | 18.99 456 | 65.34 472 | 27.73 479 | 50.43 467 | 7.67 480 | 9.50 473 | 8.01 474 | 6.34 474 | 6.13 478 | 26.24 473 | 23.40 474 | 10.69 472 | 2.99 471 |
|
| LCM-MVSNet | | | 67.77 429 | 64.73 432 | 76.87 439 | 62.95 473 | 56.25 466 | 89.37 460 | 93.74 451 | 44.53 465 | 61.99 457 | 80.74 459 | 20.42 472 | 86.53 462 | 69.37 447 | 59.50 462 | 87.84 451 |
|
| MVE |  | 53.74 22 | 51.54 436 | 47.86 440 | 62.60 450 | 59.56 474 | 50.93 469 | 79.41 464 | 77.69 473 | 35.69 469 | 36.27 471 | 61.76 470 | 5.79 479 | 69.63 469 | 37.97 469 | 36.61 466 | 67.24 464 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| ANet_high | | | 56.10 433 | 52.24 436 | 67.66 449 | 49.27 475 | 56.82 465 | 83.94 462 | 82.02 472 | 70.47 453 | 33.28 472 | 64.54 467 | 17.23 474 | 69.16 470 | 45.59 467 | 23.85 469 | 77.02 462 |
|
| tmp_tt | | | 65.23 432 | 62.94 435 | 72.13 447 | 44.90 476 | 50.03 472 | 81.05 463 | 89.42 467 | 38.45 466 | 48.51 468 | 99.90 18 | 54.09 448 | 78.70 468 | 91.84 297 | 18.26 470 | 87.64 452 |
|
| PMVS |  | 49.05 23 | 53.75 434 | 51.34 438 | 60.97 451 | 40.80 477 | 34.68 478 | 74.82 465 | 89.62 466 | 37.55 467 | 28.67 473 | 72.12 462 | 7.09 477 | 81.63 467 | 43.17 468 | 68.21 446 | 66.59 465 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| test123 | | | 37.68 439 | 39.14 442 | 33.31 454 | 19.94 478 | 24.83 480 | 98.36 373 | 9.75 479 | 15.53 472 | 51.31 466 | 87.14 451 | 19.62 473 | 17.74 474 | 47.10 466 | 3.47 473 | 57.36 467 |
|
| testmvs | | | 40.60 438 | 44.45 441 | 29.05 455 | 19.49 479 | 14.11 481 | 99.68 205 | 18.47 478 | 20.74 471 | 64.59 456 | 98.48 256 | 10.95 476 | 17.09 475 | 56.66 464 | 11.01 471 | 55.94 468 |
|
| mmdepth | | | 0.00 444 | 0.00 447 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 0.00 476 | 0.00 480 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| monomultidepth | | | 0.00 444 | 0.00 447 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 0.00 476 | 0.00 480 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| test_blank | | | 0.00 444 | 0.00 447 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 0.02 475 | 0.00 480 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| eth-test2 | | | | | | 0.00 480 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 480 | | | | | | | | | | | |
|
| uanet_test | | | 0.00 444 | 0.00 447 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 0.00 476 | 0.00 480 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| DCPMVS | | | 0.00 444 | 0.00 447 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 0.00 476 | 0.00 480 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| cdsmvs_eth3d_5k | | | 23.43 440 | 31.24 443 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 98.09 226 | 0.00 475 | 0.00 476 | 99.67 108 | 83.37 292 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| pcd_1.5k_mvsjas | | | 7.60 443 | 10.13 446 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 0.00 476 | 91.20 170 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| sosnet-low-res | | | 0.00 444 | 0.00 447 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 0.00 476 | 0.00 480 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| sosnet | | | 0.00 444 | 0.00 447 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 0.00 476 | 0.00 480 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| uncertanet | | | 0.00 444 | 0.00 447 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 0.00 476 | 0.00 480 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| Regformer | | | 0.00 444 | 0.00 447 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 0.00 476 | 0.00 480 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| ab-mvs-re | | | 8.28 442 | 11.04 445 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 99.40 141 | 0.00 480 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| uanet | | | 0.00 444 | 0.00 447 | 0.00 457 | 0.00 480 | 0.00 482 | 0.00 468 | 0.00 481 | 0.00 475 | 0.00 476 | 0.00 476 | 0.00 480 | 0.00 476 | 0.00 475 | 0.00 474 | 0.00 472 |
|
| WAC-MVS | | | | | | | 90.97 334 | | | | | | | | 86.10 376 | | |
|
| PC_three_1452 | | | | | | | | | | 96.96 59 | 99.80 25 | 99.79 58 | 97.49 10 | 100.00 1 | 99.99 5 | 99.98 32 | 100.00 1 |
|
| test_241102_TWO | | | | | | | | | 98.43 151 | 97.27 46 | 99.80 25 | 99.94 4 | 97.18 21 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
| test_0728_THIRD | | | | | | | | | | 96.48 77 | 99.83 21 | 99.91 14 | 97.87 5 | 100.00 1 | 99.92 13 | 100.00 1 | 100.00 1 |
|
| GSMVS | | | | | | | | | | | | | | | | | 99.59 145 |
|
| sam_mvs1 | | | | | | | | | | | | | 94.72 71 | | | | 99.59 145 |
|
| sam_mvs | | | | | | | | | | | | | 94.25 91 | | | | |
|
| MTGPA |  | | | | | | | | 98.28 199 | | | | | | | | |
|
| test_post1 | | | | | | | | 95.78 435 | | | | 59.23 472 | 93.20 125 | 97.74 316 | 91.06 307 | | |
|
| test_post | | | | | | | | | | | | 63.35 469 | 94.43 79 | 98.13 295 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 91.70 432 | 95.12 56 | 97.95 307 | | | |
|
| MTMP | | | | | | | | 99.87 124 | 96.49 403 | | | | | | | | |
|
| test9_res | | | | | | | | | | | | | | | 99.71 44 | 99.99 21 | 100.00 1 |
|
| agg_prior2 | | | | | | | | | | | | | | | 99.48 59 | 100.00 1 | 100.00 1 |
|
| test_prior4 | | | | | | | 98.05 77 | 99.94 84 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 99.95 67 | | 95.78 99 | 99.73 44 | 99.76 67 | 96.00 37 | | 99.78 31 | 100.00 1 | |
|
| 旧先验2 | | | | | | | | 99.46 254 | | 94.21 159 | 99.85 17 | | | 99.95 80 | 96.96 188 | | |
|
| 新几何2 | | | | | | | | 99.40 258 | | | | | | | | | |
|
| 无先验 | | | | | | | | 99.49 246 | 98.71 74 | 93.46 191 | | | | 100.00 1 | 94.36 245 | | 99.99 23 |
|
| 原ACMM2 | | | | | | | | 99.90 108 | | | | | | | | | |
|
| testdata2 | | | | | | | | | | | | | | 99.99 36 | 90.54 320 | | |
|
| segment_acmp | | | | | | | | | | | | | 96.68 29 | | | | |
|
| testdata1 | | | | | | | | 99.28 280 | | 96.35 87 | | | | | | | |
|
| plane_prior5 | | | | | | | | | 97.87 249 | | | | | 98.37 276 | 97.79 162 | 89.55 308 | 94.52 320 |
|
| plane_prior4 | | | | | | | | | | | | 98.59 242 | | | | | |
|
| plane_prior3 | | | | | | | 91.64 322 | | | 96.63 72 | 93.01 280 | | | | | | |
|
| plane_prior2 | | | | | | | | 99.84 143 | | 96.38 83 | | | | | | | |
|
| plane_prior | | | | | | | 91.74 316 | 99.86 135 | | 96.76 67 | | | | | | 89.59 307 | |
|
| n2 | | | | | | | | | 0.00 481 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 481 | | | | | | | | |
|
| door-mid | | | | | | | | | 89.69 465 | | | | | | | | |
|
| test11 | | | | | | | | | 98.44 143 | | | | | | | | |
|
| door | | | | | | | | | 90.31 462 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 91.85 312 | | | | | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 97.92 153 | | |
|
| HQP4-MVS | | | | | | | | | | | 93.37 275 | | | 98.39 270 | | | 94.53 318 |
|
| HQP3-MVS | | | | | | | | | 97.89 247 | | | | | | | 89.60 305 | |
|
| HQP2-MVS | | | | | | | | | | | | | 80.65 323 | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 96.26 162 | 96.11 429 | | 91.89 265 | 98.06 161 | | 94.40 81 | | 94.30 248 | | 99.67 125 |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 87.04 341 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 88.23 328 | |
|
| Test By Simon | | | | | | | | | | | | | 92.82 136 | | | | |
|