| AdaColmap |  | | 97.23 126 | 96.80 135 | 98.51 128 | 99.99 1 | 95.60 194 | 99.09 295 | 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 | 89.90 327 | 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 | 92.06 260 | 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 | | | 93.83 264 | 92.06 299 | 99.15 66 | 99.94 13 | 97.50 105 | 99.94 84 | 98.42 163 | 96.22 89 | 99.41 83 | 41.37 472 | 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 | 99.64 212 | 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 | 92.34 248 | 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 | 99.75 176 | 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 | 99.18 288 | 99.45 18 | 94.84 126 | 96.41 219 | 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 | 99.24 283 | 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 | 97.27 221 | 99.89 45 | 91.92 310 | 99.90 108 | 99.07 37 | 88.67 351 | 95.26 251 | 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 | 99.61 219 | 97.78 259 | 96.52 75 | 98.61 133 | 99.31 151 | 92.73 138 | 99.67 162 | 96.77 194 | 99.48 116 | 99.06 234 |
|
| 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 | 90.78 307 | 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 | 99.39 261 | 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 | | | 95.84 196 | 95.11 209 | 98.02 161 | 99.85 56 | 95.10 222 | 98.74 345 | 98.50 132 | 87.22 373 | 93.66 272 | 99.86 29 | 87.45 231 | 99.95 80 | 90.94 310 | 99.81 83 | 99.02 238 |
|
| HPM-MVS |  | | 97.96 76 | 97.72 86 | 98.68 105 | 99.84 58 | 96.39 158 | 99.90 108 | 98.17 214 | 92.61 233 | 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 | 99.40 257 | 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 | 99.41 185 |
| 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 | 99.36 267 | 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 | 99.76 172 | 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 | 99.76 172 | 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 | 91.75 271 | 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 |
|
| MVS_0304 | | | 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 | 97.41 211 | 99.76 68 | 93.36 277 | 99.65 208 | 97.95 240 | 96.03 94 | 97.41 184 | 99.70 95 | 89.61 199 | 99.51 172 | 96.73 196 | 98.25 174 | 99.38 187 |
|
| 新几何1 | | | | | 99.42 38 | 99.75 71 | 98.27 66 | | 98.63 92 | 92.69 228 | 99.55 68 | 99.82 49 | 94.40 81 | 100.00 1 | 91.21 302 | 99.94 55 | 99.99 23 |
|
| MP-MVS-pluss | | | 98.07 75 | 97.64 92 | 99.38 44 | 99.74 72 | 98.41 64 | 99.74 179 | 98.18 213 | 93.35 195 | 96.45 216 | 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 | 99.77 166 | 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 | 95.11 223 | 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 | 99.73 186 | 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 | 96.87 234 | 99.71 78 | 91.74 315 | 99.85 138 | 97.95 240 | 93.11 207 | 95.72 240 | 99.16 173 | 92.35 152 | 99.94 88 | 95.32 219 | 99.35 131 | 98.92 246 |
|
| reproduce-ours | | | 98.78 24 | 98.67 21 | 99.09 75 | 99.70 80 | 97.30 113 | 99.74 179 | 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 | 99.74 179 | 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 | 95.59 275 | 99.67 83 | 86.91 398 | 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 | 93.92 341 | 99.63 85 | 81.76 433 | 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 | | | 96.05 187 | 95.82 182 | 96.72 240 | 99.59 87 | 96.99 130 | 99.95 67 | 99.10 34 | 94.06 166 | 98.27 152 | 95.80 346 | 89.00 211 | 99.95 80 | 99.12 74 | 87.53 338 | 93.24 400 |
|
| 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 | 99.08 177 | 89.00 211 | 99.95 80 | 99.12 74 | 99.25 135 | 99.57 153 |
|
| PatchMatch-RL | | | 96.04 188 | 95.40 196 | 97.95 163 | 99.59 87 | 95.22 217 | 99.52 239 | 99.07 37 | 93.96 171 | 96.49 215 | 98.35 261 | 82.28 299 | 99.82 136 | 90.15 326 | 99.22 138 | 98.81 253 |
|
| dcpmvs_2 | | | 97.42 117 | 98.09 60 | 95.42 282 | 99.58 91 | 87.24 394 | 99.23 284 | 96.95 373 | 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 | 99.34 269 | 98.55 114 | 91.86 266 | 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 | 96.55 213 | 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 | 99.47 249 | 98.87 55 | 91.68 272 | 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 | 99.21 166 | 84.48 282 | 99.95 80 | 94.92 229 | 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 | 88.48 355 | 99.06 107 | 99.66 110 | 90.30 191 | 99.64 167 | 96.32 204 | 99.97 42 | 99.96 70 |
|
| cl22 | | | 93.77 269 | 93.25 273 | 95.33 286 | 99.49 97 | 94.43 239 | 99.61 219 | 98.09 226 | 90.38 315 | 89.16 342 | 95.61 354 | 90.56 186 | 97.34 328 | 91.93 293 | 84.45 359 | 94.21 345 |
|
| 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 | 94.97 227 | 99.94 55 | 100.00 1 |
|
| MAR-MVS | | | 97.43 113 | 97.19 116 | 98.15 152 | 99.47 98 | 94.79 231 | 99.05 306 | 98.76 69 | 92.65 231 | 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 | | | 94.54 241 | 93.42 263 | 97.91 169 | 99.46 100 | 94.04 254 | 98.93 324 | 97.48 296 | 81.15 427 | 90.04 313 | 99.55 126 | 87.02 239 | 99.95 80 | 88.97 338 | 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 | 98.46 364 | 99.42 21 | 97.03 56 | 99.02 109 | 99.09 176 | 99.35 2 | 98.21 290 | 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 | 93.81 260 | 99.94 55 | 99.98 52 |
|
| TAPA-MVS | | 92.12 8 | 94.42 249 | 93.60 255 | 96.90 233 | 99.33 104 | 91.78 314 | 99.78 162 | 98.00 234 | 89.89 328 | 94.52 257 | 99.47 132 | 91.97 161 | 99.18 197 | 69.90 444 | 99.52 109 | 99.73 115 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| reproduce_monomvs | | | 95.38 213 | 95.07 211 | 96.32 255 | 99.32 106 | 96.60 148 | 99.76 172 | 98.85 59 | 96.65 71 | 87.83 364 | 96.05 343 | 99.52 1 | 98.11 295 | 96.58 199 | 81.07 388 | 94.25 340 |
|
| 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 | 97.15 340 | 95.53 108 | 99.62 59 | 99.79 58 | 92.08 159 | 98.38 273 | 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 | 98.59 263 |
|
| 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 | 99.64 212 | 99.27 27 | 91.43 281 | 97.88 169 | 98.99 187 | 95.84 42 | 99.84 132 | 98.82 97 | 95.32 265 | 99.79 107 |
|
| DCV-MVSNet | | | 97.83 88 | 97.37 107 | 99.21 55 | 99.18 113 | 97.98 81 | 99.64 212 | 99.27 27 | 91.43 281 | 97.88 169 | 98.99 187 | 95.84 42 | 99.84 132 | 98.82 97 | 95.32 265 | 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 | 99.66 207 | 98.06 229 | 96.37 86 | 94.37 263 | 99.49 131 | 83.29 292 | 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 | 99.24 162 | 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 | 97.43 209 | 99.10 119 | 94.42 240 | 99.99 5 | 97.10 352 | 95.07 117 | 99.68 49 | 99.75 75 | 92.95 131 | 98.34 277 | 98.38 124 | 99.14 140 | 99.54 159 |
|
| Anonymous202405211 | | | 93.10 287 | 91.99 300 | 96.40 251 | 99.10 119 | 89.65 364 | 98.88 330 | 97.93 242 | 83.71 411 | 94.00 269 | 98.75 223 | 68.79 405 | 99.88 118 | 95.08 224 | 91.71 298 | 99.68 123 |
|
| fmvsm_s_conf0.5_n | | | 97.80 93 | 97.85 81 | 97.67 187 | 99.06 122 | 94.41 241 | 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 | 98.62 262 |
|
| HyFIR lowres test | | | 96.66 160 | 96.43 152 | 97.36 216 | 99.05 123 | 93.91 259 | 99.70 198 | 99.80 3 | 90.54 311 | 96.26 222 | 98.08 274 | 92.15 157 | 98.23 289 | 96.84 193 | 95.46 260 | 99.93 83 |
|
| LFMVS | | | 94.75 235 | 93.56 258 | 98.30 142 | 99.03 124 | 95.70 188 | 98.74 345 | 97.98 237 | 87.81 366 | 98.47 141 | 99.39 143 | 67.43 414 | 99.53 169 | 98.01 147 | 95.20 268 | 99.67 125 |
|
| fmvsm_s_conf0.5_n_4 | | | 97.75 98 | 97.86 80 | 97.42 210 | 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 | 97.64 291 |
|
| 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 | 81.83 305 | 99.94 88 | 99.78 31 | 98.79 156 | 97.51 299 |
|
| AllTest | | | 92.48 302 | 91.64 305 | 95.00 295 | 99.01 125 | 88.43 382 | 98.94 322 | 96.82 387 | 86.50 382 | 88.71 347 | 98.47 256 | 74.73 380 | 99.88 118 | 85.39 378 | 96.18 235 | 96.71 305 |
|
| TestCases | | | | | 95.00 295 | 99.01 125 | 88.43 382 | | 96.82 387 | 86.50 382 | 88.71 347 | 98.47 256 | 74.73 380 | 99.88 118 | 85.39 378 | 96.18 235 | 96.71 305 |
|
| COLMAP_ROB |  | 90.47 14 | 92.18 309 | 91.49 311 | 94.25 329 | 99.00 129 | 88.04 388 | 98.42 370 | 96.70 394 | 82.30 422 | 88.43 356 | 99.01 184 | 76.97 355 | 99.85 124 | 86.11 374 | 96.50 227 | 94.86 316 |
| 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 | 84.15 285 | 99.97 59 | 99.76 36 | 99.50 114 | 98.39 270 |
|
| test_fmvs1 | | | 95.35 214 | 95.68 188 | 94.36 325 | 98.99 130 | 84.98 409 | 99.96 48 | 96.65 396 | 97.60 33 | 99.73 44 | 98.96 193 | 71.58 395 | 99.93 98 | 98.31 129 | 99.37 129 | 98.17 275 |
|
| HY-MVS | | 92.50 7 | 97.79 95 | 97.17 118 | 99.63 17 | 98.98 132 | 99.32 9 | 97.49 398 | 99.52 14 | 95.69 103 | 98.32 150 | 97.41 294 | 93.32 118 | 99.77 144 | 98.08 144 | 95.75 250 | 99.81 104 |
|
| VNet | | | 97.21 127 | 96.57 146 | 99.13 72 | 98.97 133 | 97.82 90 | 99.03 309 | 99.21 32 | 94.31 153 | 99.18 100 | 98.88 205 | 86.26 252 | 99.89 112 | 98.93 88 | 94.32 278 | 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 | 96.26 222 | 98.88 205 | 89.87 196 | 99.51 172 | 94.26 248 | 94.91 270 | 99.31 204 |
|
| tfpn200view9 | | | 96.79 149 | 95.99 168 | 99.19 57 | 98.94 135 | 98.82 37 | 99.78 162 | 99.71 7 | 92.86 216 | 96.02 230 | 98.87 212 | 89.33 203 | 99.50 174 | 93.84 257 | 94.57 274 | 99.27 213 |
|
| thres400 | | | 96.78 151 | 95.99 168 | 99.16 64 | 98.94 135 | 98.82 37 | 99.78 162 | 99.71 7 | 92.86 216 | 96.02 230 | 98.87 212 | 89.33 203 | 99.50 174 | 93.84 257 | 94.57 274 | 99.16 222 |
|
| sasdasda | | | 97.09 134 | 96.32 155 | 99.39 41 | 98.93 137 | 98.95 27 | 99.72 190 | 97.35 309 | 94.45 141 | 97.88 169 | 99.42 136 | 86.71 243 | 99.52 170 | 98.48 119 | 93.97 284 | 99.72 117 |
|
| Anonymous20231211 | | | 89.86 359 | 88.44 367 | 94.13 332 | 98.93 137 | 90.68 342 | 98.54 361 | 98.26 202 | 76.28 439 | 86.73 378 | 95.54 358 | 70.60 401 | 97.56 321 | 90.82 313 | 80.27 397 | 94.15 353 |
|
| canonicalmvs | | | 97.09 134 | 96.32 155 | 99.39 41 | 98.93 137 | 98.95 27 | 99.72 190 | 97.35 309 | 94.45 141 | 97.88 169 | 99.42 136 | 86.71 243 | 99.52 170 | 98.48 119 | 93.97 284 | 99.72 117 |
|
| SDMVSNet | | | 94.80 230 | 93.96 245 | 97.33 219 | 98.92 140 | 95.42 201 | 99.59 224 | 98.99 40 | 92.41 244 | 92.55 287 | 97.85 285 | 75.81 370 | 98.93 215 | 97.90 155 | 91.62 299 | 97.64 291 |
|
| sd_testset | | | 93.55 276 | 92.83 280 | 95.74 273 | 98.92 140 | 90.89 338 | 98.24 377 | 98.85 59 | 92.41 244 | 92.55 287 | 97.85 285 | 71.07 400 | 98.68 243 | 93.93 254 | 91.62 299 | 97.64 291 |
|
| EPNet_dtu | | | 95.71 202 | 95.39 197 | 96.66 242 | 98.92 140 | 93.41 273 | 99.57 229 | 98.90 50 | 96.19 91 | 97.52 179 | 98.56 246 | 92.65 140 | 97.36 326 | 77.89 425 | 98.33 169 | 99.20 220 |
| 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 | 95.58 259 | 99.78 110 |
|
| CHOSEN 1792x2688 | | | 96.81 148 | 96.53 147 | 97.64 190 | 98.91 144 | 93.07 279 | 99.65 208 | 99.80 3 | 95.64 104 | 95.39 247 | 98.86 214 | 84.35 284 | 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 | 99.74 179 | 99.71 7 | 92.59 235 | 95.84 234 | 98.86 214 | 89.25 205 | 99.50 174 | 93.84 257 | 94.57 274 | 99.27 213 |
|
| thres600view7 | | | 96.69 158 | 95.87 181 | 99.14 68 | 98.90 145 | 98.78 41 | 99.74 179 | 99.71 7 | 92.59 235 | 95.84 234 | 98.86 214 | 89.25 205 | 99.50 174 | 93.44 270 | 94.50 277 | 99.16 222 |
|
| MSDG | | | 94.37 251 | 93.36 270 | 97.40 212 | 98.88 147 | 93.95 258 | 99.37 265 | 97.38 305 | 85.75 393 | 90.80 306 | 99.17 170 | 84.11 287 | 99.88 118 | 86.35 370 | 98.43 167 | 98.36 272 |
|
| MGCFI-Net | | | 97.00 139 | 96.22 160 | 99.34 46 | 98.86 148 | 98.80 39 | 99.67 206 | 97.30 318 | 94.31 153 | 97.77 175 | 99.41 140 | 86.36 250 | 99.50 174 | 98.38 124 | 93.90 286 | 99.72 117 |
|
| h-mvs33 | | | 94.92 227 | 94.36 231 | 96.59 244 | 98.85 149 | 91.29 330 | 98.93 324 | 98.94 44 | 95.90 96 | 98.77 122 | 98.42 259 | 90.89 181 | 99.77 144 | 97.80 159 | 70.76 436 | 98.72 259 |
|
| Anonymous20240529 | | | 92.10 310 | 90.65 322 | 96.47 246 | 98.82 150 | 90.61 344 | 98.72 347 | 98.67 82 | 75.54 443 | 93.90 271 | 98.58 244 | 66.23 418 | 99.90 107 | 94.70 238 | 90.67 302 | 98.90 249 |
|
| 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 | 96.38 220 | 98.49 252 | 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 | 99.54 237 | 98.17 214 | 97.34 41 | 99.85 17 | 99.85 33 | 91.20 170 | 99.89 112 | 99.41 64 | 99.67 90 | 98.69 260 |
|
| 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 | 81.36 311 | 99.98 47 | 92.77 281 | 98.89 150 | 98.28 274 |
|
| mvsany_test1 | | | 97.82 91 | 97.90 77 | 97.55 199 | 98.77 154 | 93.04 282 | 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 | 94.26 280 | 99.67 125 |
|
| SymmetryMVS | | | 97.64 106 | 97.46 100 | 98.17 148 | 98.74 156 | 95.39 204 | 99.61 219 | 99.26 29 | 96.52 75 | 98.61 133 | 99.31 151 | 92.73 138 | 99.67 162 | 96.77 194 | 95.63 257 | 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 | 99.52 239 | 98.08 228 | 97.05 55 | 99.86 14 | 99.86 29 | 90.65 183 | 99.71 154 | 99.39 66 | 98.63 160 | 98.69 260 |
|
| miper_enhance_ethall | | | 94.36 253 | 93.98 244 | 95.49 276 | 98.68 159 | 95.24 215 | 99.73 186 | 97.29 321 | 93.28 199 | 89.86 318 | 95.97 344 | 94.37 85 | 97.05 349 | 92.20 285 | 84.45 359 | 94.19 346 |
|
| 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 | 91.10 293 | 98.17 158 | 98.59 241 | 93.86 105 | 98.19 291 | 95.64 216 | 95.24 267 | 99.28 211 |
|
| test2506 | | | 97.53 110 | 97.19 116 | 98.58 117 | 98.66 162 | 96.90 134 | 98.81 339 | 99.77 5 | 94.93 120 | 97.95 164 | 98.96 193 | 92.51 147 | 99.20 195 | 94.93 228 | 98.15 177 | 99.64 131 |
|
| ECVR-MVS |  | | 95.66 205 | 95.05 212 | 97.51 203 | 98.66 162 | 93.71 263 | 98.85 336 | 98.45 138 | 94.93 120 | 96.86 202 | 98.96 193 | 75.22 376 | 99.20 195 | 95.34 218 | 98.15 177 | 99.64 131 |
|
| mamv4 | | | 95.24 217 | 96.90 127 | 90.25 403 | 98.65 164 | 72.11 451 | 98.28 375 | 97.64 273 | 89.99 326 | 95.93 232 | 98.25 269 | 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 | 99.47 249 | 97.79 257 | 94.56 136 | 99.74 42 | 98.35 261 | 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 | 94.26 248 | 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 | 99.08 232 |
|
| MVSMamba_PlusPlus | | | 97.83 88 | 97.45 102 | 98.99 85 | 98.60 167 | 98.15 67 | 99.58 226 | 97.74 264 | 90.34 318 | 99.26 96 | 98.32 264 | 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 | 92.53 239 | 98.84 116 | 98.84 218 | 93.36 115 | 98.30 281 | 95.84 212 | 94.30 279 | 99.05 236 |
|
| test1111 | | | 95.57 208 | 94.98 215 | 97.37 214 | 98.56 168 | 93.37 276 | 98.86 334 | 98.45 138 | 94.95 119 | 96.63 208 | 98.95 198 | 75.21 377 | 99.11 201 | 95.02 225 | 98.14 179 | 99.64 131 |
|
| MVSTER | | | 95.53 209 | 95.22 204 | 96.45 249 | 98.56 168 | 97.72 93 | 99.91 102 | 97.67 269 | 92.38 247 | 91.39 297 | 97.14 301 | 97.24 18 | 97.30 333 | 94.80 234 | 87.85 331 | 94.34 335 |
|
| 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 | 98.73 225 | 95.50 49 | 99.69 158 | 98.53 117 | 94.63 272 | 98.99 240 |
|
| VDD-MVS | | | 93.77 269 | 92.94 278 | 96.27 256 | 98.55 171 | 90.22 353 | 98.77 344 | 97.79 257 | 90.85 299 | 96.82 204 | 99.42 136 | 61.18 438 | 99.77 144 | 98.95 86 | 94.13 281 | 98.82 252 |
|
| tpmvs | | | 94.28 255 | 93.57 257 | 96.40 251 | 98.55 171 | 91.50 328 | 95.70 435 | 98.55 114 | 87.47 368 | 92.15 290 | 94.26 409 | 91.42 166 | 98.95 214 | 88.15 349 | 95.85 246 | 98.76 255 |
|
| UGNet | | | 95.33 215 | 94.57 227 | 97.62 194 | 98.55 171 | 94.85 227 | 98.67 353 | 99.32 26 | 95.75 101 | 96.80 205 | 96.27 333 | 72.18 392 | 99.96 71 | 94.58 241 | 99.05 146 | 98.04 280 |
| 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 | 95.18 219 | 94.10 238 | 98.43 134 | 98.55 171 | 95.99 176 | 97.91 391 | 97.31 317 | 90.35 317 | 89.48 331 | 99.22 163 | 85.19 269 | 99.89 112 | 90.40 323 | 98.47 166 | 99.41 185 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| UWE-MVS-28 | | | 95.95 190 | 96.49 148 | 94.34 326 | 98.51 176 | 89.99 358 | 99.39 261 | 98.57 102 | 93.14 204 | 97.33 187 | 98.31 266 | 93.44 113 | 94.68 426 | 93.69 267 | 95.98 240 | 98.34 273 |
|
| UWE-MVS | | | 96.79 149 | 96.72 139 | 97.00 228 | 98.51 176 | 93.70 264 | 99.71 193 | 98.60 96 | 92.96 212 | 97.09 194 | 98.34 263 | 96.67 31 | 98.85 221 | 92.11 291 | 96.50 227 | 98.44 268 |
|
| 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 | 98.75 223 | 95.20 54 | 99.48 180 | 98.93 88 | 96.40 230 | 99.29 209 |
|
| test_vis1_n_1920 | | | 95.44 211 | 95.31 200 | 95.82 270 | 98.50 178 | 88.74 376 | 99.98 20 | 97.30 318 | 97.84 27 | 99.85 17 | 99.19 168 | 66.82 416 | 99.97 59 | 98.82 97 | 99.46 121 | 98.76 255 |
|
| BH-w/o | | | 95.71 202 | 95.38 198 | 96.68 241 | 98.49 180 | 92.28 301 | 99.84 143 | 97.50 294 | 92.12 257 | 92.06 293 | 98.79 221 | 84.69 278 | 98.67 245 | 95.29 220 | 99.66 91 | 99.09 230 |
|
| baseline1 | | | 95.78 198 | 94.86 218 | 98.54 123 | 98.47 181 | 98.07 75 | 99.06 302 | 97.99 235 | 92.68 229 | 94.13 268 | 98.62 238 | 93.28 121 | 98.69 242 | 93.79 262 | 85.76 346 | 98.84 251 |
|
| 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 | 97.66 290 |
|
| EPMVS | | | 96.53 167 | 96.01 167 | 98.09 156 | 98.43 183 | 96.12 174 | 96.36 422 | 99.43 20 | 93.53 188 | 97.64 177 | 95.04 386 | 94.41 80 | 98.38 273 | 91.13 304 | 98.11 180 | 99.75 113 |
|
| kuosan | | | 93.17 284 | 92.60 286 | 94.86 302 | 98.40 184 | 89.54 366 | 98.44 366 | 98.53 121 | 84.46 406 | 88.49 352 | 97.92 282 | 90.57 185 | 97.05 349 | 83.10 395 | 93.49 289 | 97.99 281 |
|
| WBMVS | | | 94.52 244 | 94.03 242 | 95.98 262 | 98.38 185 | 96.68 143 | 99.92 94 | 97.63 274 | 90.75 308 | 89.64 326 | 95.25 379 | 96.77 25 | 96.90 361 | 94.35 246 | 83.57 366 | 94.35 333 |
|
| 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 | 98.42 259 | 96.77 25 | 99.17 198 | 98.54 115 | 96.20 234 | 99.11 229 |
|
| sss | | | 97.57 109 | 97.03 123 | 99.18 58 | 98.37 187 | 98.04 78 | 99.73 186 | 99.38 22 | 93.46 191 | 98.76 125 | 99.06 179 | 91.21 169 | 99.89 112 | 96.33 203 | 97.01 218 | 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 | 98.70 228 | 95.48 50 | 99.22 191 | 97.85 157 | 95.05 269 | 99.07 233 |
|
| BH-untuned | | | 95.18 219 | 94.83 219 | 96.22 257 | 98.36 188 | 91.22 331 | 99.80 159 | 97.32 316 | 90.91 297 | 91.08 300 | 98.67 230 | 83.51 289 | 98.54 255 | 94.23 249 | 99.61 99 | 98.92 246 |
|
| 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 | 98.72 226 | 94.81 68 | 99.21 192 | 96.98 186 | 94.63 272 | 99.03 237 |
|
| 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 | 98.72 226 | 94.83 67 | 99.21 192 | 97.00 184 | 94.64 271 | 98.95 242 |
|
| ET-MVSNet_ETH3D | | | 94.37 251 | 93.28 272 | 97.64 190 | 98.30 192 | 97.99 80 | 99.99 5 | 97.61 280 | 94.35 150 | 71.57 449 | 99.45 135 | 96.23 35 | 95.34 416 | 96.91 191 | 85.14 353 | 99.59 145 |
|
| AUN-MVS | | | 93.28 281 | 92.60 286 | 95.34 285 | 98.29 193 | 90.09 356 | 99.31 273 | 98.56 108 | 91.80 270 | 96.35 221 | 98.00 277 | 89.38 202 | 98.28 284 | 92.46 282 | 69.22 441 | 97.64 291 |
|
| FMVSNet3 | | | 92.69 297 | 91.58 307 | 95.99 261 | 98.29 193 | 97.42 110 | 99.26 282 | 97.62 277 | 89.80 329 | 89.68 322 | 95.32 373 | 81.62 309 | 96.27 392 | 87.01 366 | 85.65 347 | 94.29 337 |
|
| PMMVS | | | 96.76 152 | 96.76 136 | 96.76 238 | 98.28 195 | 92.10 305 | 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 | | | 94.38 250 | 94.08 241 | 95.31 287 | 98.27 196 | 90.02 357 | 99.29 278 | 98.56 108 | 95.90 96 | 98.77 122 | 98.00 277 | 90.89 181 | 98.26 288 | 97.80 159 | 69.20 442 | 97.64 291 |
|
| PVSNet_0 | | 88.03 19 | 91.80 317 | 90.27 331 | 96.38 253 | 98.27 196 | 90.46 348 | 99.94 84 | 99.61 13 | 93.99 169 | 86.26 388 | 97.39 296 | 71.13 399 | 99.89 112 | 98.77 101 | 67.05 448 | 98.79 254 |
|
| UA-Net | | | 96.54 166 | 95.96 174 | 98.27 144 | 98.23 198 | 95.71 187 | 98.00 389 | 98.45 138 | 93.72 184 | 98.41 145 | 99.27 156 | 88.71 216 | 99.66 165 | 91.19 303 | 97.69 189 | 99.44 182 |
|
| test_cas_vis1_n_1920 | | | 96.59 163 | 96.23 158 | 97.65 189 | 98.22 199 | 94.23 249 | 99.99 5 | 97.25 326 | 97.77 28 | 99.58 67 | 99.08 177 | 77.10 350 | 99.97 59 | 97.64 167 | 99.45 122 | 98.74 257 |
|
| FE-MVS | | | 95.70 204 | 95.01 214 | 97.79 177 | 98.21 200 | 94.57 236 | 95.03 436 | 98.69 77 | 88.90 345 | 97.50 181 | 96.19 335 | 92.60 143 | 99.49 179 | 89.99 328 | 97.94 186 | 99.31 204 |
|
| GG-mvs-BLEND | | | | | 98.54 123 | 98.21 200 | 98.01 79 | 93.87 441 | 98.52 123 | | 97.92 165 | 97.92 282 | 99.02 3 | 97.94 308 | 98.17 137 | 99.58 104 | 99.67 125 |
|
| mvs_anonymous | | | 95.65 206 | 95.03 213 | 97.53 201 | 98.19 202 | 95.74 185 | 99.33 270 | 97.49 295 | 90.87 298 | 90.47 309 | 97.10 303 | 88.23 219 | 97.16 340 | 95.92 210 | 97.66 192 | 99.68 123 |
|
| MVS_Test | | | 96.46 169 | 95.74 184 | 98.61 112 | 98.18 203 | 97.23 117 | 99.31 273 | 97.15 340 | 91.07 294 | 98.84 116 | 97.05 307 | 88.17 220 | 98.97 211 | 94.39 243 | 97.50 194 | 99.61 142 |
|
| BH-RMVSNet | | | 95.18 219 | 94.31 234 | 97.80 175 | 98.17 204 | 95.23 216 | 99.76 172 | 97.53 290 | 92.52 240 | 94.27 266 | 99.25 161 | 76.84 357 | 98.80 225 | 90.89 312 | 99.54 106 | 99.35 195 |
|
| dongtai | | | 91.55 323 | 91.13 316 | 92.82 371 | 98.16 205 | 86.35 399 | 99.47 249 | 98.51 126 | 83.24 414 | 85.07 398 | 97.56 290 | 90.33 190 | 94.94 422 | 76.09 433 | 91.73 297 | 97.18 302 |
|
| RPSCF | | | 91.80 317 | 92.79 282 | 88.83 414 | 98.15 206 | 69.87 453 | 98.11 385 | 96.60 398 | 83.93 409 | 94.33 264 | 99.27 156 | 79.60 333 | 99.46 183 | 91.99 292 | 93.16 294 | 97.18 302 |
|
| 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 | 97.45 206 | 98.13 208 | 94.80 230 | 99.08 297 | 97.61 280 | 92.02 262 | 95.54 245 | 98.96 193 | 90.64 184 | 98.08 297 | 93.73 265 | 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 | 80.88 318 | 99.93 98 | 99.59 52 | 98.17 175 | 97.29 300 |
|
| ab-mvs | | | 94.69 236 | 93.42 263 | 98.51 128 | 98.07 211 | 96.26 162 | 96.49 420 | 98.68 79 | 90.31 319 | 94.54 256 | 97.00 309 | 76.30 365 | 99.71 154 | 95.98 209 | 93.38 292 | 99.56 154 |
|
| XVG-OURS-SEG-HR | | | 94.79 231 | 94.70 226 | 95.08 292 | 98.05 212 | 89.19 368 | 99.08 297 | 97.54 288 | 93.66 185 | 94.87 254 | 99.58 122 | 78.78 341 | 99.79 139 | 97.31 174 | 93.40 291 | 96.25 309 |
|
| 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 | | | 94.82 228 | 94.74 225 | 95.06 293 | 98.00 214 | 89.19 368 | 99.08 297 | 97.55 286 | 94.10 162 | 94.71 255 | 99.62 117 | 80.51 324 | 99.74 150 | 96.04 208 | 93.06 296 | 96.25 309 |
|
| mvsmamba | | | 96.94 142 | 96.73 138 | 97.55 199 | 97.99 215 | 94.37 245 | 99.62 215 | 97.70 266 | 93.13 205 | 98.42 144 | 97.92 282 | 88.02 221 | 98.75 233 | 98.78 100 | 99.01 147 | 99.52 165 |
|
| dp | | | 95.05 222 | 94.43 229 | 96.91 231 | 97.99 215 | 92.73 290 | 96.29 425 | 97.98 237 | 89.70 330 | 95.93 232 | 94.67 399 | 93.83 107 | 98.45 261 | 86.91 369 | 96.53 226 | 99.54 159 |
|
| tpmrst | | | 96.27 182 | 95.98 170 | 97.13 223 | 97.96 217 | 93.15 278 | 96.34 423 | 98.17 214 | 92.07 258 | 98.71 128 | 95.12 383 | 93.91 102 | 98.73 235 | 94.91 231 | 96.62 224 | 99.50 171 |
|
| TR-MVS | | | 94.54 241 | 93.56 258 | 97.49 205 | 97.96 217 | 94.34 246 | 98.71 348 | 97.51 293 | 90.30 320 | 94.51 258 | 98.69 229 | 75.56 371 | 98.77 229 | 92.82 280 | 95.99 239 | 99.35 195 |
|
| Vis-MVSNet (Re-imp) | | | 96.32 177 | 95.98 170 | 97.35 218 | 97.93 219 | 94.82 229 | 99.47 249 | 98.15 222 | 91.83 267 | 95.09 252 | 99.11 175 | 91.37 168 | 97.47 324 | 93.47 269 | 97.43 195 | 99.74 114 |
|
| MDTV_nov1_ep13 | | | | 95.69 186 | | 97.90 220 | 94.15 251 | 95.98 431 | 98.44 143 | 93.12 206 | 97.98 163 | 95.74 348 | 95.10 57 | 98.58 251 | 90.02 327 | 96.92 220 | |
|
| Fast-Effi-MVS+ | | | 95.02 224 | 94.19 236 | 97.52 202 | 97.88 221 | 94.55 237 | 99.97 38 | 97.08 356 | 88.85 347 | 94.47 259 | 97.96 281 | 84.59 279 | 98.41 265 | 89.84 330 | 97.10 212 | 99.59 145 |
|
| ADS-MVSNet2 | | | 93.80 268 | 93.88 248 | 93.55 354 | 97.87 222 | 85.94 403 | 94.24 437 | 96.84 384 | 90.07 323 | 96.43 217 | 94.48 404 | 90.29 192 | 95.37 415 | 87.44 356 | 97.23 205 | 99.36 191 |
|
| ADS-MVSNet | | | 94.79 231 | 94.02 243 | 97.11 225 | 97.87 222 | 93.79 260 | 94.24 437 | 98.16 219 | 90.07 323 | 96.43 217 | 94.48 404 | 90.29 192 | 98.19 291 | 87.44 356 | 97.23 205 | 99.36 191 |
|
| Effi-MVS+ | | | 96.30 179 | 95.69 186 | 98.16 149 | 97.85 224 | 96.26 162 | 97.41 400 | 97.21 332 | 90.37 316 | 98.65 131 | 98.58 244 | 86.61 247 | 98.70 241 | 97.11 180 | 97.37 199 | 99.52 165 |
|
| PatchmatchNet |  | | 95.94 191 | 95.45 193 | 97.39 213 | 97.83 225 | 94.41 241 | 96.05 429 | 98.40 172 | 92.86 216 | 97.09 194 | 95.28 378 | 94.21 94 | 98.07 299 | 89.26 336 | 98.11 180 | 99.70 120 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| cascas | | | 94.64 239 | 93.61 253 | 97.74 185 | 97.82 226 | 96.26 162 | 99.96 48 | 97.78 259 | 85.76 391 | 94.00 269 | 97.54 291 | 76.95 356 | 99.21 192 | 97.23 177 | 95.43 262 | 97.76 289 |
|
| 1112_ss | | | 96.01 189 | 95.20 205 | 98.42 136 | 97.80 227 | 96.41 155 | 99.65 208 | 96.66 395 | 92.71 226 | 92.88 283 | 99.40 141 | 92.16 156 | 99.30 187 | 91.92 294 | 93.66 287 | 99.55 155 |
|
| Test_1112_low_res | | | 95.72 200 | 94.83 219 | 98.42 136 | 97.79 228 | 96.41 155 | 99.65 208 | 96.65 396 | 92.70 227 | 92.86 284 | 96.13 339 | 92.15 157 | 99.30 187 | 91.88 295 | 93.64 288 | 99.55 155 |
|
| Effi-MVS+-dtu | | | 94.53 243 | 95.30 201 | 92.22 379 | 97.77 229 | 82.54 426 | 99.59 224 | 97.06 360 | 94.92 122 | 95.29 249 | 95.37 371 | 85.81 257 | 97.89 309 | 94.80 234 | 97.07 213 | 96.23 311 |
|
| tpm cat1 | | | 93.51 277 | 92.52 292 | 96.47 246 | 97.77 229 | 91.47 329 | 96.13 427 | 98.06 229 | 80.98 428 | 92.91 282 | 93.78 413 | 89.66 197 | 98.87 219 | 87.03 365 | 96.39 231 | 99.09 230 |
|
| FA-MVS(test-final) | | | 95.86 194 | 95.09 210 | 98.15 152 | 97.74 231 | 95.62 193 | 96.31 424 | 98.17 214 | 91.42 283 | 96.26 222 | 96.13 339 | 90.56 186 | 99.47 182 | 92.18 286 | 97.07 213 | 99.35 195 |
|
| xiu_mvs_v1_base_debu | | | 97.43 113 | 97.06 119 | 98.55 119 | 97.74 231 | 98.14 69 | 99.31 273 | 97.86 251 | 96.43 80 | 99.62 59 | 99.69 99 | 85.56 264 | 99.68 159 | 99.05 77 | 98.31 170 | 97.83 285 |
|
| xiu_mvs_v1_base | | | 97.43 113 | 97.06 119 | 98.55 119 | 97.74 231 | 98.14 69 | 99.31 273 | 97.86 251 | 96.43 80 | 99.62 59 | 99.69 99 | 85.56 264 | 99.68 159 | 99.05 77 | 98.31 170 | 97.83 285 |
|
| xiu_mvs_v1_base_debi | | | 97.43 113 | 97.06 119 | 98.55 119 | 97.74 231 | 98.14 69 | 99.31 273 | 97.86 251 | 96.43 80 | 99.62 59 | 99.69 99 | 85.56 264 | 99.68 159 | 99.05 77 | 98.31 170 | 97.83 285 |
|
| EPP-MVSNet | | | 96.69 158 | 96.60 144 | 96.96 230 | 97.74 231 | 93.05 281 | 99.37 265 | 98.56 108 | 88.75 349 | 95.83 236 | 99.01 184 | 96.01 36 | 98.56 253 | 96.92 190 | 97.20 207 | 99.25 215 |
|
| gg-mvs-nofinetune | | | 93.51 277 | 91.86 304 | 98.47 130 | 97.72 236 | 97.96 84 | 92.62 447 | 98.51 126 | 74.70 446 | 97.33 187 | 69.59 463 | 98.91 4 | 97.79 312 | 97.77 164 | 99.56 105 | 99.67 125 |
|
| IB-MVS | | 92.85 6 | 94.99 225 | 93.94 246 | 98.16 149 | 97.72 236 | 95.69 190 | 99.99 5 | 98.81 64 | 94.28 156 | 92.70 285 | 96.90 311 | 95.08 58 | 99.17 198 | 96.07 207 | 73.88 429 | 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 | 91.83 267 | 97.45 182 | 99.04 181 | 97.50 9 | 99.10 203 | 94.75 236 | 96.37 232 | 99.16 222 |
|
| VortexMVS | | | 94.11 257 | 93.50 260 | 95.94 264 | 97.70 239 | 96.61 147 | 99.35 268 | 97.18 335 | 93.52 190 | 89.57 329 | 95.74 348 | 87.55 228 | 96.97 357 | 95.76 215 | 85.13 354 | 94.23 342 |
|
| Syy-MVS | | | 90.00 357 | 90.63 323 | 88.11 421 | 97.68 240 | 74.66 449 | 99.71 193 | 98.35 185 | 90.79 305 | 92.10 291 | 98.67 230 | 79.10 339 | 93.09 441 | 63.35 456 | 95.95 243 | 96.59 307 |
|
| myMVS_eth3d | | | 94.46 248 | 94.76 224 | 93.55 354 | 97.68 240 | 90.97 333 | 99.71 193 | 98.35 185 | 90.79 305 | 92.10 291 | 98.67 230 | 92.46 150 | 93.09 441 | 87.13 362 | 95.95 243 | 96.59 307 |
|
| test_fmvs1_n | | | 94.25 256 | 94.36 231 | 93.92 341 | 97.68 240 | 83.70 416 | 99.90 108 | 96.57 399 | 97.40 39 | 99.67 50 | 98.88 205 | 61.82 435 | 99.92 104 | 98.23 135 | 99.13 141 | 98.14 278 |
|
| fmvsm_s_conf0.5_n_6 | | | 98.27 60 | 97.96 72 | 99.23 53 | 97.66 243 | 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 | 95.68 188 | 97.94 166 | 97.65 244 | 94.92 226 | 99.27 281 | 97.10 352 | 92.79 222 | 97.43 183 | 97.99 279 | 81.85 304 | 99.37 186 | 98.46 121 | 98.57 161 | 99.53 163 |
|
| diffmvs |  | | 97.00 139 | 96.64 142 | 98.09 156 | 97.64 245 | 96.17 171 | 99.81 155 | 97.19 333 | 94.67 134 | 98.95 111 | 99.28 153 | 86.43 248 | 98.76 231 | 98.37 126 | 97.42 197 | 99.33 198 |
| 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 | 97.63 246 | 94.70 233 | 99.77 166 | 97.33 313 | 93.41 194 | 97.34 186 | 99.17 170 | 86.72 242 | 98.83 222 | 97.40 172 | 97.32 202 | 99.46 176 |
|
| viewdifsd2359ckpt13 | | | 96.19 184 | 95.77 183 | 97.45 206 | 97.62 247 | 94.40 243 | 99.70 198 | 97.23 331 | 92.76 224 | 96.63 208 | 99.05 180 | 84.96 273 | 98.64 248 | 96.65 197 | 97.35 200 | 99.31 204 |
|
| Vis-MVSNet |  | | 95.72 200 | 95.15 208 | 97.45 206 | 97.62 247 | 94.28 247 | 99.28 279 | 98.24 205 | 94.27 158 | 96.84 203 | 98.94 200 | 79.39 334 | 98.76 231 | 93.25 271 | 98.49 165 | 99.30 207 |
| 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 | 97.60 249 | 96.70 140 | 99.92 94 | 98.54 118 | 91.11 292 | 97.07 196 | 98.97 191 | 97.47 12 | 99.03 206 | 93.73 265 | 96.09 237 | 98.92 246 |
|
| GDP-MVS | | | 97.88 82 | 97.59 96 | 98.75 101 | 97.59 250 | 97.81 91 | 99.95 67 | 97.37 308 | 94.44 144 | 99.08 105 | 99.58 122 | 97.13 23 | 99.08 204 | 94.99 226 | 98.17 175 | 99.37 189 |
|
| miper_ehance_all_eth | | | 93.16 285 | 92.60 286 | 94.82 303 | 97.57 251 | 93.56 268 | 99.50 243 | 97.07 359 | 88.75 349 | 88.85 346 | 95.52 360 | 90.97 177 | 96.74 371 | 90.77 314 | 84.45 359 | 94.17 347 |
|
| guyue | | | 97.15 130 | 96.82 133 | 98.15 152 | 97.56 252 | 96.25 166 | 99.71 193 | 97.84 254 | 95.75 101 | 98.13 160 | 98.65 233 | 87.58 227 | 98.82 223 | 98.29 131 | 97.91 187 | 99.36 191 |
|
| viewmanbaseed2359cas | | | 96.45 170 | 96.07 164 | 97.59 197 | 97.55 253 | 94.59 235 | 99.70 198 | 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 | | | 93.92 262 | 94.23 235 | 92.99 368 | 97.54 254 | 90.23 352 | 99.99 5 | 99.16 33 | 90.57 310 | 91.33 299 | 98.63 237 | 92.99 129 | 92.52 445 | 82.46 399 | 95.39 263 | 96.22 312 |
|
| SSM_0404 | | | 95.75 199 | 95.16 207 | 97.50 204 | 97.53 255 | 95.39 204 | 99.11 293 | 97.25 326 | 90.81 301 | 95.27 250 | 98.83 219 | 84.74 275 | 98.67 245 | 95.24 221 | 97.69 189 | 98.45 267 |
|
| LCM-MVSNet-Re | | | 92.31 306 | 92.60 286 | 91.43 388 | 97.53 255 | 79.27 443 | 99.02 311 | 91.83 458 | 92.07 258 | 80.31 422 | 94.38 407 | 83.50 290 | 95.48 412 | 97.22 178 | 97.58 193 | 99.54 159 |
|
| GBi-Net | | | 90.88 334 | 89.82 340 | 94.08 333 | 97.53 255 | 91.97 306 | 98.43 367 | 96.95 373 | 87.05 374 | 89.68 322 | 94.72 395 | 71.34 396 | 96.11 398 | 87.01 366 | 85.65 347 | 94.17 347 |
|
| test1 | | | 90.88 334 | 89.82 340 | 94.08 333 | 97.53 255 | 91.97 306 | 98.43 367 | 96.95 373 | 87.05 374 | 89.68 322 | 94.72 395 | 71.34 396 | 96.11 398 | 87.01 366 | 85.65 347 | 94.17 347 |
|
| FMVSNet2 | | | 91.02 331 | 89.56 345 | 95.41 283 | 97.53 255 | 95.74 185 | 98.98 314 | 97.41 303 | 87.05 374 | 88.43 356 | 95.00 389 | 71.34 396 | 96.24 394 | 85.12 381 | 85.21 352 | 94.25 340 |
|
| tttt0517 | | | 96.85 146 | 96.49 148 | 97.92 167 | 97.48 260 | 95.89 179 | 99.85 138 | 98.54 118 | 90.72 309 | 96.63 208 | 98.93 203 | 97.47 12 | 99.02 207 | 93.03 278 | 95.76 249 | 98.85 250 |
|
| BP-MVS1 | | | 98.33 56 | 98.18 53 | 98.81 96 | 97.44 261 | 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 | 99.36 191 |
|
| casdiffmvs_mvg |  | | 96.43 171 | 95.94 176 | 97.89 171 | 97.44 261 | 95.47 197 | 99.86 135 | 97.29 321 | 93.35 195 | 96.03 229 | 99.19 168 | 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 | 97.41 263 | 95.64 192 | 99.99 5 | 97.06 360 | 94.59 135 | 99.63 56 | 99.32 148 | 89.20 208 | 98.14 293 | 98.76 102 | 99.23 137 | 99.62 138 |
|
| viewdifsd2359ckpt07 | | | 95.83 197 | 95.42 195 | 97.07 226 | 97.40 264 | 93.04 282 | 99.60 222 | 97.24 329 | 92.39 246 | 96.09 228 | 99.14 174 | 83.07 295 | 98.93 215 | 97.02 183 | 96.87 221 | 99.23 218 |
|
| c3_l | | | 92.53 301 | 91.87 303 | 94.52 315 | 97.40 264 | 92.99 284 | 99.40 257 | 96.93 378 | 87.86 364 | 88.69 349 | 95.44 365 | 89.95 195 | 96.44 384 | 90.45 320 | 80.69 393 | 94.14 356 |
|
| viewmambaseed2359dif | | | 95.92 193 | 95.55 192 | 97.04 227 | 97.38 266 | 93.41 273 | 99.78 162 | 96.97 371 | 91.14 291 | 96.58 211 | 99.27 156 | 84.85 274 | 98.75 233 | 96.87 192 | 97.12 211 | 98.97 241 |
|
| fmvsm_s_conf0.1_n | | | 97.30 121 | 97.21 115 | 97.60 196 | 97.38 266 | 94.40 243 | 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 | 98.46 266 |
|
| CDS-MVSNet | | | 96.34 176 | 96.07 164 | 97.13 223 | 97.37 268 | 94.96 224 | 99.53 238 | 97.91 246 | 91.55 275 | 95.37 248 | 98.32 264 | 95.05 60 | 97.13 343 | 93.80 261 | 95.75 250 | 99.30 207 |
| 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 | 97.36 269 | 96.48 152 | 99.96 48 | 98.29 198 | 91.93 263 | 95.77 237 | 98.07 275 | 95.54 46 | 98.29 282 | 90.55 318 | 98.89 150 | 99.70 120 |
|
| miper_lstm_enhance | | | 91.81 314 | 91.39 313 | 93.06 367 | 97.34 270 | 89.18 370 | 99.38 263 | 96.79 389 | 86.70 381 | 87.47 370 | 95.22 380 | 90.00 194 | 95.86 407 | 88.26 347 | 81.37 382 | 94.15 353 |
|
| baseline | | | 96.43 171 | 95.98 170 | 97.76 183 | 97.34 270 | 95.17 220 | 99.51 241 | 97.17 337 | 93.92 174 | 96.90 201 | 99.28 153 | 85.37 268 | 98.64 248 | 97.50 170 | 96.86 223 | 99.46 176 |
|
| cl____ | | | 92.31 306 | 91.58 307 | 94.52 315 | 97.33 272 | 92.77 286 | 99.57 229 | 96.78 390 | 86.97 378 | 87.56 368 | 95.51 361 | 89.43 201 | 96.62 376 | 88.60 341 | 82.44 374 | 94.16 352 |
|
| SD_0403 | | | 92.63 300 | 93.38 267 | 90.40 402 | 97.32 273 | 77.91 445 | 97.75 396 | 98.03 233 | 91.89 264 | 90.83 305 | 98.29 268 | 82.00 301 | 93.79 435 | 88.51 345 | 95.75 250 | 99.52 165 |
|
| DIV-MVS_self_test | | | 92.32 305 | 91.60 306 | 94.47 319 | 97.31 274 | 92.74 288 | 99.58 226 | 96.75 391 | 86.99 377 | 87.64 366 | 95.54 358 | 89.55 200 | 96.50 381 | 88.58 342 | 82.44 374 | 94.17 347 |
|
| casdiffmvs |  | | 96.42 173 | 95.97 173 | 97.77 181 | 97.30 275 | 94.98 223 | 99.84 143 | 97.09 355 | 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 | | | 94.36 253 | 93.48 261 | 96.99 229 | 97.29 276 | 93.54 269 | 99.96 48 | 96.72 393 | 88.35 358 | 93.43 273 | 98.94 200 | 82.05 300 | 98.05 300 | 88.12 351 | 96.48 229 | 99.37 189 |
|
| eth_miper_zixun_eth | | | 92.41 304 | 91.93 301 | 93.84 345 | 97.28 277 | 90.68 342 | 98.83 337 | 96.97 371 | 88.57 354 | 89.19 341 | 95.73 351 | 89.24 207 | 96.69 374 | 89.97 329 | 81.55 380 | 94.15 353 |
|
| MVSFormer | | | 96.94 142 | 96.60 144 | 97.95 163 | 97.28 277 | 97.70 96 | 99.55 235 | 97.27 323 | 91.17 288 | 99.43 81 | 99.54 128 | 90.92 178 | 96.89 362 | 94.67 239 | 99.62 95 | 99.25 215 |
|
| lupinMVS | | | 97.85 86 | 97.60 94 | 98.62 111 | 97.28 277 | 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 | 97.20 280 | 95.46 198 | 99.69 201 | 97.15 340 | 94.46 140 | 98.78 120 | 99.21 166 | 85.64 261 | 98.77 229 | 98.27 132 | 97.31 203 | 99.13 226 |
|
| mamba_0408 | | | 94.98 226 | 94.09 239 | 97.64 190 | 97.14 281 | 95.31 209 | 93.48 444 | 97.08 356 | 90.48 312 | 94.40 260 | 98.62 238 | 84.49 280 | 98.67 245 | 93.99 252 | 97.18 208 | 98.93 243 |
|
| SSM_04072 | | | 94.77 233 | 94.09 239 | 96.82 235 | 97.14 281 | 95.31 209 | 93.48 444 | 97.08 356 | 90.48 312 | 94.40 260 | 98.62 238 | 84.49 280 | 96.21 395 | 93.99 252 | 97.18 208 | 98.93 243 |
|
| SSM_0407 | | | 95.62 207 | 94.95 216 | 97.61 195 | 97.14 281 | 95.31 209 | 99.00 312 | 97.25 326 | 90.81 301 | 94.40 260 | 98.83 219 | 84.74 275 | 98.58 251 | 95.24 221 | 97.18 208 | 98.93 243 |
|
| SCA | | | 94.69 236 | 93.81 250 | 97.33 219 | 97.10 284 | 94.44 238 | 98.86 334 | 98.32 192 | 93.30 198 | 96.17 227 | 95.59 356 | 76.48 363 | 97.95 306 | 91.06 306 | 97.43 195 | 99.59 145 |
|
| viewmacassd2359aftdt | | | 95.93 192 | 95.45 193 | 97.36 216 | 97.09 285 | 94.12 253 | 99.57 229 | 97.26 325 | 93.05 210 | 96.50 214 | 99.17 170 | 82.76 296 | 98.68 243 | 96.61 198 | 97.04 215 | 99.28 211 |
|
| KinetiMVS | | | 96.10 185 | 95.29 202 | 98.53 125 | 97.08 286 | 97.12 123 | 99.56 232 | 98.12 225 | 94.78 127 | 98.44 142 | 98.94 200 | 80.30 328 | 99.39 185 | 91.56 299 | 98.79 156 | 99.06 234 |
|
| TAMVS | | | 95.85 195 | 95.58 190 | 96.65 243 | 97.07 287 | 93.50 270 | 99.17 289 | 97.82 256 | 91.39 285 | 95.02 253 | 98.01 276 | 92.20 155 | 97.30 333 | 93.75 264 | 95.83 247 | 99.14 225 |
|
| Fast-Effi-MVS+-dtu | | | 93.72 272 | 93.86 249 | 93.29 359 | 97.06 288 | 86.16 400 | 99.80 159 | 96.83 385 | 92.66 230 | 92.58 286 | 97.83 287 | 81.39 310 | 97.67 317 | 89.75 331 | 96.87 221 | 96.05 314 |
|
| CostFormer | | | 96.10 185 | 95.88 180 | 96.78 237 | 97.03 289 | 92.55 296 | 97.08 409 | 97.83 255 | 90.04 325 | 98.72 127 | 94.89 393 | 95.01 62 | 98.29 282 | 96.54 200 | 95.77 248 | 99.50 171 |
|
| test_fmvsmvis_n_1920 | | | 97.67 105 | 97.59 96 | 97.91 169 | 97.02 290 | 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 | 98.42 269 |
|
| test-LLR | | | 96.47 168 | 96.04 166 | 97.78 179 | 97.02 290 | 95.44 199 | 99.96 48 | 98.21 209 | 94.07 164 | 95.55 243 | 96.38 328 | 93.90 103 | 98.27 286 | 90.42 321 | 98.83 154 | 99.64 131 |
|
| test-mter | | | 96.39 174 | 95.93 177 | 97.78 179 | 97.02 290 | 95.44 199 | 99.96 48 | 98.21 209 | 91.81 269 | 95.55 243 | 96.38 328 | 95.17 55 | 98.27 286 | 90.42 321 | 98.83 154 | 99.64 131 |
|
| icg_test_0407_2 | | | 95.04 223 | 94.78 223 | 95.84 269 | 96.97 293 | 91.64 321 | 98.63 356 | 97.12 345 | 92.33 249 | 95.60 241 | 98.88 205 | 85.65 259 | 96.56 379 | 92.12 287 | 95.70 253 | 99.32 200 |
|
| IMVS_0407 | | | 95.21 218 | 94.80 222 | 96.46 248 | 96.97 293 | 91.64 321 | 98.81 339 | 97.12 345 | 92.33 249 | 95.60 241 | 98.88 205 | 85.65 259 | 98.42 263 | 92.12 287 | 95.70 253 | 99.32 200 |
|
| IMVS_0404 | | | 93.83 264 | 93.17 274 | 95.80 271 | 96.97 293 | 91.64 321 | 97.78 395 | 97.12 345 | 92.33 249 | 90.87 304 | 98.88 205 | 76.78 358 | 96.43 385 | 92.12 287 | 95.70 253 | 99.32 200 |
|
| IMVS_0403 | | | 95.25 216 | 94.81 221 | 96.58 245 | 96.97 293 | 91.64 321 | 98.97 319 | 97.12 345 | 92.33 249 | 95.43 246 | 98.88 205 | 85.78 258 | 98.79 226 | 92.12 287 | 95.70 253 | 99.32 200 |
|
| gm-plane-assit | | | | | | 96.97 293 | 93.76 262 | | | 91.47 279 | | 98.96 193 | | 98.79 226 | 94.92 229 | | |
|
| WB-MVSnew | | | 92.90 291 | 92.77 283 | 93.26 361 | 96.95 298 | 93.63 266 | 99.71 193 | 98.16 219 | 91.49 276 | 94.28 265 | 98.14 272 | 81.33 312 | 96.48 382 | 79.47 416 | 95.46 260 | 89.68 442 |
|
| QAPM | | | 95.40 212 | 94.17 237 | 99.10 74 | 96.92 299 | 97.71 94 | 99.40 257 | 98.68 79 | 89.31 333 | 88.94 345 | 98.89 204 | 82.48 298 | 99.96 71 | 93.12 277 | 99.83 77 | 99.62 138 |
|
| KD-MVS_2432*1600 | | | 88.00 379 | 86.10 383 | 93.70 350 | 96.91 300 | 94.04 254 | 97.17 406 | 97.12 345 | 84.93 401 | 81.96 412 | 92.41 426 | 92.48 148 | 94.51 428 | 79.23 417 | 52.68 462 | 92.56 412 |
|
| miper_refine_blended | | | 88.00 379 | 86.10 383 | 93.70 350 | 96.91 300 | 94.04 254 | 97.17 406 | 97.12 345 | 84.93 401 | 81.96 412 | 92.41 426 | 92.48 148 | 94.51 428 | 79.23 417 | 52.68 462 | 92.56 412 |
|
| tpm2 | | | 95.47 210 | 95.18 206 | 96.35 254 | 96.91 300 | 91.70 319 | 96.96 412 | 97.93 242 | 88.04 362 | 98.44 142 | 95.40 367 | 93.32 118 | 97.97 303 | 94.00 251 | 95.61 258 | 99.38 187 |
|
| FMVSNet5 | | | 88.32 375 | 87.47 377 | 90.88 391 | 96.90 303 | 88.39 384 | 97.28 403 | 95.68 420 | 82.60 421 | 84.67 400 | 92.40 428 | 79.83 331 | 91.16 450 | 76.39 432 | 81.51 381 | 93.09 403 |
|
| 3Dnovator+ | | 91.53 11 | 96.31 178 | 95.24 203 | 99.52 28 | 96.88 304 | 98.64 54 | 99.72 190 | 98.24 205 | 95.27 115 | 88.42 358 | 98.98 189 | 82.76 296 | 99.94 88 | 97.10 181 | 99.83 77 | 99.96 70 |
|
| Patchmatch-test | | | 92.65 299 | 91.50 310 | 96.10 260 | 96.85 305 | 90.49 347 | 91.50 452 | 97.19 333 | 82.76 420 | 90.23 310 | 95.59 356 | 95.02 61 | 98.00 302 | 77.41 427 | 96.98 219 | 99.82 102 |
|
| MVS | | | 96.60 162 | 95.56 191 | 99.72 13 | 96.85 305 | 99.22 20 | 98.31 373 | 98.94 44 | 91.57 274 | 90.90 303 | 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 | 95.34 199 | 99.08 77 | 96.82 307 | 97.47 108 | 99.45 254 | 98.81 64 | 95.52 109 | 89.39 332 | 99.00 186 | 81.97 302 | 99.95 80 | 97.27 175 | 99.83 77 | 99.84 99 |
|
| EI-MVSNet | | | 93.73 271 | 93.40 266 | 94.74 304 | 96.80 308 | 92.69 291 | 99.06 302 | 97.67 269 | 88.96 342 | 91.39 297 | 99.02 182 | 88.75 215 | 97.30 333 | 91.07 305 | 87.85 331 | 94.22 343 |
|
| CVMVSNet | | | 94.68 238 | 94.94 217 | 93.89 344 | 96.80 308 | 86.92 397 | 99.06 302 | 98.98 41 | 94.45 141 | 94.23 267 | 99.02 182 | 85.60 262 | 95.31 417 | 90.91 311 | 95.39 263 | 99.43 183 |
|
| IterMVS-LS | | | 92.69 297 | 92.11 297 | 94.43 323 | 96.80 308 | 92.74 288 | 99.45 254 | 96.89 381 | 88.98 340 | 89.65 325 | 95.38 370 | 88.77 214 | 96.34 389 | 90.98 309 | 82.04 377 | 94.22 343 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| AstraMVS | | | 96.57 165 | 96.46 151 | 96.91 231 | 96.79 311 | 92.50 297 | 99.90 108 | 97.38 305 | 96.02 95 | 97.79 174 | 99.32 148 | 86.36 250 | 98.99 208 | 98.26 133 | 96.33 233 | 99.23 218 |
|
| IterMVS | | | 90.91 333 | 90.17 335 | 93.12 364 | 96.78 312 | 90.42 350 | 98.89 328 | 97.05 363 | 89.03 337 | 86.49 383 | 95.42 366 | 76.59 361 | 95.02 419 | 87.22 361 | 84.09 362 | 93.93 374 |
| 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 | 96.74 313 | 98.52 58 | 98.31 373 | 98.86 56 | 95.82 98 | 89.91 316 | 98.98 189 | 87.49 230 | 99.96 71 | 97.80 159 | 99.73 87 | 99.96 70 |
|
| IterMVS-SCA-FT | | | 90.85 336 | 90.16 336 | 92.93 369 | 96.72 314 | 89.96 359 | 98.89 328 | 96.99 367 | 88.95 343 | 86.63 380 | 95.67 352 | 76.48 363 | 95.00 420 | 87.04 364 | 84.04 365 | 93.84 381 |
|
| MVS-HIRNet | | | 86.22 386 | 83.19 399 | 95.31 287 | 96.71 315 | 90.29 351 | 92.12 449 | 97.33 313 | 62.85 457 | 86.82 377 | 70.37 462 | 69.37 404 | 97.49 323 | 75.12 435 | 97.99 185 | 98.15 276 |
|
| viewdifsd2359ckpt11 | | | 94.09 259 | 93.63 252 | 95.46 280 | 96.68 316 | 88.92 373 | 99.62 215 | 97.12 345 | 93.07 208 | 95.73 238 | 99.22 163 | 77.05 351 | 98.88 218 | 96.52 201 | 87.69 336 | 98.58 264 |
|
| viewmsd2359difaftdt | | | 94.09 259 | 93.64 251 | 95.46 280 | 96.68 316 | 88.92 373 | 99.62 215 | 97.13 344 | 93.07 208 | 95.73 238 | 99.22 163 | 77.05 351 | 98.89 217 | 96.52 201 | 87.70 335 | 98.58 264 |
|
| VDDNet | | | 93.12 286 | 91.91 302 | 96.76 238 | 96.67 318 | 92.65 294 | 98.69 351 | 98.21 209 | 82.81 419 | 97.75 176 | 99.28 153 | 61.57 436 | 99.48 180 | 98.09 143 | 94.09 282 | 98.15 276 |
|
| dmvs_re | | | 93.20 283 | 93.15 275 | 93.34 357 | 96.54 319 | 83.81 415 | 98.71 348 | 98.51 126 | 91.39 285 | 92.37 289 | 98.56 246 | 78.66 343 | 97.83 311 | 93.89 255 | 89.74 303 | 98.38 271 |
|
| Elysia | | | 94.50 245 | 93.38 267 | 97.85 173 | 96.49 320 | 96.70 140 | 98.98 314 | 97.78 259 | 90.81 301 | 96.19 225 | 98.55 248 | 73.63 387 | 98.98 209 | 89.41 332 | 98.56 162 | 97.88 283 |
|
| StellarMVS | | | 94.50 245 | 93.38 267 | 97.85 173 | 96.49 320 | 96.70 140 | 98.98 314 | 97.78 259 | 90.81 301 | 96.19 225 | 98.55 248 | 73.63 387 | 98.98 209 | 89.41 332 | 98.56 162 | 97.88 283 |
|
| MIMVSNet | | | 90.30 349 | 88.67 363 | 95.17 291 | 96.45 322 | 91.64 321 | 92.39 448 | 97.15 340 | 85.99 388 | 90.50 308 | 93.19 421 | 66.95 415 | 94.86 424 | 82.01 403 | 93.43 290 | 99.01 239 |
|
| CR-MVSNet | | | 93.45 280 | 92.62 285 | 95.94 264 | 96.29 323 | 92.66 292 | 92.01 450 | 96.23 407 | 92.62 232 | 96.94 199 | 93.31 419 | 91.04 175 | 96.03 403 | 79.23 417 | 95.96 241 | 99.13 226 |
|
| RPMNet | | | 89.76 361 | 87.28 378 | 97.19 222 | 96.29 323 | 92.66 292 | 92.01 450 | 98.31 194 | 70.19 453 | 96.94 199 | 85.87 455 | 87.25 235 | 99.78 141 | 62.69 457 | 95.96 241 | 99.13 226 |
|
| tt0805 | | | 91.28 326 | 90.18 334 | 94.60 310 | 96.26 325 | 87.55 390 | 98.39 371 | 98.72 73 | 89.00 339 | 89.22 338 | 98.47 256 | 62.98 431 | 98.96 213 | 90.57 317 | 88.00 330 | 97.28 301 |
|
| Patchmtry | | | 89.70 362 | 88.49 366 | 93.33 358 | 96.24 326 | 89.94 362 | 91.37 453 | 96.23 407 | 78.22 436 | 87.69 365 | 93.31 419 | 91.04 175 | 96.03 403 | 80.18 415 | 82.10 376 | 94.02 364 |
|
| test_vis1_rt | | | 86.87 384 | 86.05 386 | 89.34 410 | 96.12 327 | 78.07 444 | 99.87 124 | 83.54 470 | 92.03 261 | 78.21 433 | 89.51 440 | 45.80 456 | 99.91 105 | 96.25 205 | 93.11 295 | 90.03 439 |
|
| JIA-IIPM | | | 91.76 320 | 90.70 321 | 94.94 297 | 96.11 328 | 87.51 391 | 93.16 446 | 98.13 224 | 75.79 442 | 97.58 178 | 77.68 460 | 92.84 134 | 97.97 303 | 88.47 346 | 96.54 225 | 99.33 198 |
|
| OpenMVS |  | 90.15 15 | 94.77 233 | 93.59 256 | 98.33 140 | 96.07 329 | 97.48 107 | 99.56 232 | 98.57 102 | 90.46 314 | 86.51 382 | 98.95 198 | 78.57 344 | 99.94 88 | 93.86 256 | 99.74 86 | 97.57 296 |
|
| PAPM | | | 98.60 34 | 98.42 35 | 99.14 68 | 96.05 330 | 98.96 26 | 99.90 108 | 99.35 24 | 96.68 70 | 98.35 149 | 99.66 110 | 96.45 33 | 98.51 256 | 99.45 61 | 99.89 70 | 99.96 70 |
|
| CLD-MVS | | | 94.06 261 | 93.90 247 | 94.55 314 | 96.02 331 | 90.69 341 | 99.98 20 | 97.72 265 | 96.62 74 | 91.05 302 | 98.85 217 | 77.21 349 | 98.47 257 | 98.11 141 | 89.51 309 | 94.48 321 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| PatchT | | | 90.38 346 | 88.75 362 | 95.25 289 | 95.99 332 | 90.16 354 | 91.22 454 | 97.54 288 | 76.80 438 | 97.26 190 | 86.01 454 | 91.88 162 | 96.07 402 | 66.16 452 | 95.91 245 | 99.51 169 |
|
| ACMH+ | | 89.98 16 | 90.35 347 | 89.54 346 | 92.78 373 | 95.99 332 | 86.12 401 | 98.81 339 | 97.18 335 | 89.38 332 | 83.14 408 | 97.76 288 | 68.42 409 | 98.43 262 | 89.11 337 | 86.05 345 | 93.78 384 |
|
| DeepMVS_CX |  | | | | 82.92 432 | 95.98 334 | 58.66 463 | | 96.01 412 | 92.72 225 | 78.34 432 | 95.51 361 | 58.29 442 | 98.08 297 | 82.57 398 | 85.29 350 | 92.03 420 |
|
| ACMP | | 92.05 9 | 92.74 295 | 92.42 294 | 93.73 346 | 95.91 335 | 88.72 377 | 99.81 155 | 97.53 290 | 94.13 160 | 87.00 376 | 98.23 270 | 74.07 384 | 98.47 257 | 96.22 206 | 88.86 316 | 93.99 369 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| test_vis1_n | | | 93.61 275 | 93.03 277 | 95.35 284 | 95.86 336 | 86.94 396 | 99.87 124 | 96.36 405 | 96.85 61 | 99.54 70 | 98.79 221 | 52.41 450 | 99.83 134 | 98.64 110 | 98.97 148 | 99.29 209 |
|
| HQP-NCC | | | | | | 95.78 337 | | 99.87 124 | | 96.82 63 | 93.37 274 | | | | | | |
|
| ACMP_Plane | | | | | | 95.78 337 | | 99.87 124 | | 96.82 63 | 93.37 274 | | | | | | |
|
| HQP-MVS | | | 94.61 240 | 94.50 228 | 94.92 298 | 95.78 337 | 91.85 311 | 99.87 124 | 97.89 247 | 96.82 63 | 93.37 274 | 98.65 233 | 80.65 322 | 98.39 269 | 97.92 153 | 89.60 304 | 94.53 317 |
|
| NP-MVS | | | | | | 95.77 340 | 91.79 313 | | | | | 98.65 233 | | | | | |
|
| test_fmvsmconf0.1_n | | | 97.74 99 | 97.44 103 | 98.64 110 | 95.76 341 | 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 | | | | | | 95.76 341 | 91.72 318 | | | | | | 80.47 326 | | | | |
|
| ACMM | | 91.95 10 | 92.88 292 | 92.52 292 | 93.98 340 | 95.75 343 | 89.08 372 | 99.77 166 | 97.52 292 | 93.00 211 | 89.95 315 | 97.99 279 | 76.17 367 | 98.46 260 | 93.63 268 | 88.87 315 | 94.39 329 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| GA-MVS | | | 93.83 264 | 92.84 279 | 96.80 236 | 95.73 344 | 93.57 267 | 99.88 121 | 97.24 329 | 92.57 237 | 92.92 281 | 96.66 320 | 78.73 342 | 97.67 317 | 87.75 354 | 94.06 283 | 99.17 221 |
|
| plane_prior1 | | | | | | 95.73 344 | | | | | | | | | | | |
|
| jason | | | 97.24 125 | 96.86 130 | 98.38 139 | 95.73 344 | 97.32 112 | 99.97 38 | 97.40 304 | 95.34 113 | 98.60 136 | 99.54 128 | 87.70 224 | 98.56 253 | 97.94 152 | 99.47 119 | 99.25 215 |
| jason: jason. |
| mmtdpeth | | | 88.52 373 | 87.75 375 | 90.85 393 | 95.71 347 | 83.47 421 | 98.94 322 | 94.85 435 | 88.78 348 | 97.19 192 | 89.58 439 | 63.29 429 | 98.97 211 | 98.54 115 | 62.86 456 | 90.10 438 |
|
| HQP_MVS | | | 94.49 247 | 94.36 231 | 94.87 299 | 95.71 347 | 91.74 315 | 99.84 143 | 97.87 249 | 96.38 83 | 93.01 279 | 98.59 241 | 80.47 326 | 98.37 275 | 97.79 162 | 89.55 307 | 94.52 319 |
|
| plane_prior7 | | | | | | 95.71 347 | 91.59 327 | | | | | | | | | | |
|
| ITE_SJBPF | | | | | 92.38 376 | 95.69 350 | 85.14 407 | | 95.71 419 | 92.81 219 | 89.33 335 | 98.11 273 | 70.23 402 | 98.42 263 | 85.91 376 | 88.16 328 | 93.59 392 |
|
| fmvsm_s_conf0.1_n_a | | | 97.09 134 | 96.90 127 | 97.63 193 | 95.65 351 | 94.21 250 | 99.83 150 | 98.50 132 | 96.27 88 | 99.65 52 | 99.64 113 | 84.72 277 | 99.93 98 | 99.04 80 | 98.84 153 | 98.74 257 |
|
| ACMH | | 89.72 17 | 90.64 340 | 89.63 343 | 93.66 352 | 95.64 352 | 88.64 380 | 98.55 359 | 97.45 297 | 89.03 337 | 81.62 415 | 97.61 289 | 69.75 403 | 98.41 265 | 89.37 334 | 87.62 337 | 93.92 375 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| baseline2 | | | 96.71 157 | 96.49 148 | 97.37 214 | 95.63 353 | 95.96 177 | 99.74 179 | 98.88 54 | 92.94 213 | 91.61 295 | 98.97 191 | 97.72 6 | 98.62 250 | 94.83 233 | 98.08 183 | 97.53 298 |
|
| FMVSNet1 | | | 88.50 374 | 86.64 381 | 94.08 333 | 95.62 354 | 91.97 306 | 98.43 367 | 96.95 373 | 83.00 417 | 86.08 390 | 94.72 395 | 59.09 441 | 96.11 398 | 81.82 405 | 84.07 363 | 94.17 347 |
|
| LuminaMVS | | | 96.63 161 | 96.21 161 | 97.87 172 | 95.58 355 | 96.82 136 | 99.12 291 | 97.67 269 | 94.47 139 | 97.88 169 | 98.31 266 | 87.50 229 | 98.71 238 | 98.07 145 | 97.29 204 | 98.10 279 |
|
| LPG-MVS_test | | | 92.96 289 | 92.71 284 | 93.71 348 | 95.43 356 | 88.67 378 | 99.75 176 | 97.62 277 | 92.81 219 | 90.05 311 | 98.49 252 | 75.24 374 | 98.40 267 | 95.84 212 | 89.12 311 | 94.07 361 |
|
| LGP-MVS_train | | | | | 93.71 348 | 95.43 356 | 88.67 378 | | 97.62 277 | 92.81 219 | 90.05 311 | 98.49 252 | 75.24 374 | 98.40 267 | 95.84 212 | 89.12 311 | 94.07 361 |
|
| tpm | | | 93.70 273 | 93.41 265 | 94.58 312 | 95.36 358 | 87.41 392 | 97.01 410 | 96.90 380 | 90.85 299 | 96.72 207 | 94.14 410 | 90.40 189 | 96.84 366 | 90.75 315 | 88.54 323 | 99.51 169 |
|
| D2MVS | | | 92.76 294 | 92.59 290 | 93.27 360 | 95.13 359 | 89.54 366 | 99.69 201 | 99.38 22 | 92.26 254 | 87.59 367 | 94.61 401 | 85.05 271 | 97.79 312 | 91.59 298 | 88.01 329 | 92.47 415 |
|
| VPA-MVSNet | | | 92.70 296 | 91.55 309 | 96.16 258 | 95.09 360 | 96.20 168 | 98.88 330 | 99.00 39 | 91.02 296 | 91.82 294 | 95.29 377 | 76.05 369 | 97.96 305 | 95.62 217 | 81.19 383 | 94.30 336 |
|
| LTVRE_ROB | | 88.28 18 | 90.29 350 | 89.05 357 | 94.02 336 | 95.08 361 | 90.15 355 | 97.19 405 | 97.43 299 | 84.91 403 | 83.99 404 | 97.06 306 | 74.00 385 | 98.28 284 | 84.08 387 | 87.71 333 | 93.62 391 |
| 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 | | | 87.87 381 | 86.51 382 | 91.94 382 | 95.05 362 | 85.57 405 | 97.65 397 | 94.08 445 | 84.40 407 | 81.82 414 | 96.85 315 | 62.14 434 | 98.33 278 | 80.25 414 | 86.37 344 | 91.91 422 |
|
| test0.0.03 1 | | | 93.86 263 | 93.61 253 | 94.64 308 | 95.02 363 | 92.18 304 | 99.93 91 | 98.58 100 | 94.07 164 | 87.96 362 | 98.50 251 | 93.90 103 | 94.96 421 | 81.33 406 | 93.17 293 | 96.78 304 |
|
| UniMVSNet (Re) | | | 93.07 288 | 92.13 296 | 95.88 266 | 94.84 364 | 96.24 167 | 99.88 121 | 98.98 41 | 92.49 242 | 89.25 336 | 95.40 367 | 87.09 237 | 97.14 342 | 93.13 276 | 78.16 407 | 94.26 338 |
|
| USDC | | | 90.00 357 | 88.96 358 | 93.10 366 | 94.81 365 | 88.16 386 | 98.71 348 | 95.54 424 | 93.66 185 | 83.75 406 | 97.20 300 | 65.58 420 | 98.31 280 | 83.96 390 | 87.49 339 | 92.85 409 |
|
| VPNet | | | 91.81 314 | 90.46 325 | 95.85 268 | 94.74 366 | 95.54 196 | 98.98 314 | 98.59 98 | 92.14 256 | 90.77 307 | 97.44 293 | 68.73 407 | 97.54 322 | 94.89 232 | 77.89 409 | 94.46 322 |
|
| FIs | | | 94.10 258 | 93.43 262 | 96.11 259 | 94.70 367 | 96.82 136 | 99.58 226 | 98.93 48 | 92.54 238 | 89.34 334 | 97.31 297 | 87.62 226 | 97.10 346 | 94.22 250 | 86.58 342 | 94.40 328 |
|
| UniMVSNet_ETH3D | | | 90.06 356 | 88.58 365 | 94.49 318 | 94.67 368 | 88.09 387 | 97.81 394 | 97.57 285 | 83.91 410 | 88.44 354 | 97.41 294 | 57.44 443 | 97.62 319 | 91.41 300 | 88.59 322 | 97.77 288 |
|
| UniMVSNet_NR-MVSNet | | | 92.95 290 | 92.11 297 | 95.49 276 | 94.61 369 | 95.28 213 | 99.83 150 | 99.08 36 | 91.49 276 | 89.21 339 | 96.86 314 | 87.14 236 | 96.73 372 | 93.20 272 | 77.52 412 | 94.46 322 |
|
| test_fmvs2 | | | 89.47 366 | 89.70 342 | 88.77 417 | 94.54 370 | 75.74 446 | 99.83 150 | 94.70 441 | 94.71 131 | 91.08 300 | 96.82 319 | 54.46 446 | 97.78 314 | 92.87 279 | 88.27 326 | 92.80 410 |
|
| MonoMVSNet | | | 94.82 228 | 94.43 229 | 95.98 262 | 94.54 370 | 90.73 340 | 99.03 309 | 97.06 360 | 93.16 203 | 93.15 278 | 95.47 364 | 88.29 218 | 97.57 320 | 97.85 157 | 91.33 301 | 99.62 138 |
|
| WR-MVS | | | 92.31 306 | 91.25 314 | 95.48 279 | 94.45 372 | 95.29 212 | 99.60 222 | 98.68 79 | 90.10 322 | 88.07 361 | 96.89 312 | 80.68 321 | 96.80 370 | 93.14 275 | 79.67 400 | 94.36 330 |
|
| nrg030 | | | 93.51 277 | 92.53 291 | 96.45 249 | 94.36 373 | 97.20 118 | 99.81 155 | 97.16 339 | 91.60 273 | 89.86 318 | 97.46 292 | 86.37 249 | 97.68 316 | 95.88 211 | 80.31 396 | 94.46 322 |
|
| tfpnnormal | | | 89.29 369 | 87.61 376 | 94.34 326 | 94.35 374 | 94.13 252 | 98.95 321 | 98.94 44 | 83.94 408 | 84.47 401 | 95.51 361 | 74.84 379 | 97.39 325 | 77.05 430 | 80.41 394 | 91.48 425 |
|
| FC-MVSNet-test | | | 93.81 267 | 93.15 275 | 95.80 271 | 94.30 375 | 96.20 168 | 99.42 256 | 98.89 52 | 92.33 249 | 89.03 344 | 97.27 299 | 87.39 232 | 96.83 368 | 93.20 272 | 86.48 343 | 94.36 330 |
|
| SSC-MVS3.2 | | | 89.59 364 | 88.66 364 | 92.38 376 | 94.29 376 | 86.12 401 | 99.49 245 | 97.66 272 | 90.28 321 | 88.63 351 | 95.18 381 | 64.46 425 | 96.88 364 | 85.30 380 | 82.66 371 | 94.14 356 |
|
| MS-PatchMatch | | | 90.65 339 | 90.30 330 | 91.71 387 | 94.22 377 | 85.50 406 | 98.24 377 | 97.70 266 | 88.67 351 | 86.42 385 | 96.37 330 | 67.82 412 | 98.03 301 | 83.62 392 | 99.62 95 | 91.60 423 |
|
| WR-MVS_H | | | 91.30 324 | 90.35 328 | 94.15 330 | 94.17 378 | 92.62 295 | 99.17 289 | 98.94 44 | 88.87 346 | 86.48 384 | 94.46 406 | 84.36 283 | 96.61 377 | 88.19 348 | 78.51 405 | 93.21 401 |
|
| DU-MVS | | | 92.46 303 | 91.45 312 | 95.49 276 | 94.05 379 | 95.28 213 | 99.81 155 | 98.74 72 | 92.25 255 | 89.21 339 | 96.64 322 | 81.66 307 | 96.73 372 | 93.20 272 | 77.52 412 | 94.46 322 |
|
| NR-MVSNet | | | 91.56 322 | 90.22 332 | 95.60 274 | 94.05 379 | 95.76 184 | 98.25 376 | 98.70 75 | 91.16 290 | 80.78 421 | 96.64 322 | 83.23 293 | 96.57 378 | 91.41 300 | 77.73 411 | 94.46 322 |
|
| CP-MVSNet | | | 91.23 328 | 90.22 332 | 94.26 328 | 93.96 381 | 92.39 300 | 99.09 295 | 98.57 102 | 88.95 343 | 86.42 385 | 96.57 325 | 79.19 337 | 96.37 387 | 90.29 324 | 78.95 402 | 94.02 364 |
|
| XXY-MVS | | | 91.82 313 | 90.46 325 | 95.88 266 | 93.91 382 | 95.40 203 | 98.87 333 | 97.69 268 | 88.63 353 | 87.87 363 | 97.08 304 | 74.38 383 | 97.89 309 | 91.66 297 | 84.07 363 | 94.35 333 |
|
| PS-CasMVS | | | 90.63 341 | 89.51 348 | 93.99 339 | 93.83 383 | 91.70 319 | 98.98 314 | 98.52 123 | 88.48 355 | 86.15 389 | 96.53 327 | 75.46 372 | 96.31 391 | 88.83 339 | 78.86 404 | 93.95 372 |
|
| test_0402 | | | 85.58 388 | 83.94 393 | 90.50 399 | 93.81 384 | 85.04 408 | 98.55 359 | 95.20 432 | 76.01 440 | 79.72 427 | 95.13 382 | 64.15 427 | 96.26 393 | 66.04 453 | 86.88 341 | 90.21 436 |
|
| XVG-ACMP-BASELINE | | | 91.22 329 | 90.75 320 | 92.63 375 | 93.73 385 | 85.61 404 | 98.52 363 | 97.44 298 | 92.77 223 | 89.90 317 | 96.85 315 | 66.64 417 | 98.39 269 | 92.29 284 | 88.61 320 | 93.89 377 |
|
| TranMVSNet+NR-MVSNet | | | 91.68 321 | 90.61 324 | 94.87 299 | 93.69 386 | 93.98 257 | 99.69 201 | 98.65 83 | 91.03 295 | 88.44 354 | 96.83 318 | 80.05 330 | 96.18 396 | 90.26 325 | 76.89 420 | 94.45 327 |
|
| TransMVSNet (Re) | | | 87.25 382 | 85.28 389 | 93.16 363 | 93.56 387 | 91.03 332 | 98.54 361 | 94.05 447 | 83.69 412 | 81.09 419 | 96.16 336 | 75.32 373 | 96.40 386 | 76.69 431 | 68.41 444 | 92.06 419 |
|
| v10 | | | 90.25 351 | 88.82 360 | 94.57 313 | 93.53 388 | 93.43 272 | 99.08 297 | 96.87 383 | 85.00 400 | 87.34 374 | 94.51 402 | 80.93 317 | 97.02 356 | 82.85 397 | 79.23 401 | 93.26 399 |
|
| testgi | | | 89.01 371 | 88.04 372 | 91.90 383 | 93.49 389 | 84.89 410 | 99.73 186 | 95.66 421 | 93.89 178 | 85.14 396 | 98.17 271 | 59.68 440 | 94.66 427 | 77.73 426 | 88.88 314 | 96.16 313 |
|
| v8 | | | 90.54 343 | 89.17 353 | 94.66 307 | 93.43 390 | 93.40 275 | 99.20 286 | 96.94 377 | 85.76 391 | 87.56 368 | 94.51 402 | 81.96 303 | 97.19 339 | 84.94 383 | 78.25 406 | 93.38 397 |
|
| V42 | | | 91.28 326 | 90.12 337 | 94.74 304 | 93.42 391 | 93.46 271 | 99.68 204 | 97.02 364 | 87.36 370 | 89.85 320 | 95.05 385 | 81.31 313 | 97.34 328 | 87.34 359 | 80.07 398 | 93.40 395 |
|
| pm-mvs1 | | | 89.36 368 | 87.81 374 | 94.01 337 | 93.40 392 | 91.93 309 | 98.62 357 | 96.48 403 | 86.25 386 | 83.86 405 | 96.14 338 | 73.68 386 | 97.04 352 | 86.16 373 | 75.73 425 | 93.04 405 |
|
| v1144 | | | 91.09 330 | 89.83 339 | 94.87 299 | 93.25 393 | 93.69 265 | 99.62 215 | 96.98 369 | 86.83 380 | 89.64 326 | 94.99 390 | 80.94 316 | 97.05 349 | 85.08 382 | 81.16 384 | 93.87 379 |
|
| v1192 | | | 90.62 342 | 89.25 352 | 94.72 306 | 93.13 394 | 93.07 279 | 99.50 243 | 97.02 364 | 86.33 385 | 89.56 330 | 95.01 387 | 79.22 336 | 97.09 348 | 82.34 401 | 81.16 384 | 94.01 366 |
|
| v2v482 | | | 91.30 324 | 90.07 338 | 95.01 294 | 93.13 394 | 93.79 260 | 99.77 166 | 97.02 364 | 88.05 361 | 89.25 336 | 95.37 371 | 80.73 320 | 97.15 341 | 87.28 360 | 80.04 399 | 94.09 360 |
|
| OPM-MVS | | | 93.21 282 | 92.80 281 | 94.44 321 | 93.12 396 | 90.85 339 | 99.77 166 | 97.61 280 | 96.19 91 | 91.56 296 | 98.65 233 | 75.16 378 | 98.47 257 | 93.78 263 | 89.39 310 | 93.99 369 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| v144192 | | | 90.79 337 | 89.52 347 | 94.59 311 | 93.11 397 | 92.77 286 | 99.56 232 | 96.99 367 | 86.38 384 | 89.82 321 | 94.95 392 | 80.50 325 | 97.10 346 | 83.98 389 | 80.41 394 | 93.90 376 |
|
| PEN-MVS | | | 90.19 353 | 89.06 356 | 93.57 353 | 93.06 398 | 90.90 337 | 99.06 302 | 98.47 135 | 88.11 360 | 85.91 391 | 96.30 332 | 76.67 359 | 95.94 406 | 87.07 363 | 76.91 419 | 93.89 377 |
|
| v1240 | | | 90.20 352 | 88.79 361 | 94.44 321 | 93.05 399 | 92.27 302 | 99.38 263 | 96.92 379 | 85.89 389 | 89.36 333 | 94.87 394 | 77.89 348 | 97.03 354 | 80.66 410 | 81.08 387 | 94.01 366 |
|
| v148 | | | 90.70 338 | 89.63 343 | 93.92 341 | 92.97 400 | 90.97 333 | 99.75 176 | 96.89 381 | 87.51 367 | 88.27 359 | 95.01 387 | 81.67 306 | 97.04 352 | 87.40 358 | 77.17 417 | 93.75 385 |
|
| v1921920 | | | 90.46 344 | 89.12 354 | 94.50 317 | 92.96 401 | 92.46 298 | 99.49 245 | 96.98 369 | 86.10 387 | 89.61 328 | 95.30 374 | 78.55 345 | 97.03 354 | 82.17 402 | 80.89 392 | 94.01 366 |
|
| MVStest1 | | | 85.03 394 | 82.76 403 | 91.83 384 | 92.95 402 | 89.16 371 | 98.57 358 | 94.82 436 | 71.68 451 | 68.54 454 | 95.11 384 | 83.17 294 | 95.66 410 | 74.69 436 | 65.32 451 | 90.65 432 |
|
| tt0320-xc | | | 82.94 408 | 80.35 415 | 90.72 397 | 92.90 403 | 83.54 419 | 96.85 415 | 94.73 439 | 63.12 456 | 79.85 426 | 93.77 414 | 49.43 454 | 95.46 413 | 80.98 409 | 71.54 434 | 93.16 402 |
|
| Baseline_NR-MVSNet | | | 90.33 348 | 89.51 348 | 92.81 372 | 92.84 404 | 89.95 360 | 99.77 166 | 93.94 448 | 84.69 405 | 89.04 343 | 95.66 353 | 81.66 307 | 96.52 380 | 90.99 308 | 76.98 418 | 91.97 421 |
|
| test_method | | | 80.79 414 | 79.70 417 | 84.08 429 | 92.83 405 | 67.06 455 | 99.51 241 | 95.42 426 | 54.34 461 | 81.07 420 | 93.53 416 | 44.48 457 | 92.22 447 | 78.90 421 | 77.23 416 | 92.94 407 |
|
| pmmvs4 | | | 92.10 310 | 91.07 318 | 95.18 290 | 92.82 406 | 94.96 224 | 99.48 248 | 96.83 385 | 87.45 369 | 88.66 350 | 96.56 326 | 83.78 288 | 96.83 368 | 89.29 335 | 84.77 357 | 93.75 385 |
|
| LF4IMVS | | | 89.25 370 | 88.85 359 | 90.45 401 | 92.81 407 | 81.19 436 | 98.12 384 | 94.79 437 | 91.44 280 | 86.29 387 | 97.11 302 | 65.30 423 | 98.11 295 | 88.53 344 | 85.25 351 | 92.07 418 |
|
| tt0320 | | | 83.56 407 | 81.15 410 | 90.77 395 | 92.77 408 | 83.58 418 | 96.83 416 | 95.52 425 | 63.26 455 | 81.36 417 | 92.54 424 | 53.26 448 | 95.77 408 | 80.45 411 | 74.38 428 | 92.96 406 |
|
| DTE-MVSNet | | | 89.40 367 | 88.24 370 | 92.88 370 | 92.66 409 | 89.95 360 | 99.10 294 | 98.22 208 | 87.29 371 | 85.12 397 | 96.22 334 | 76.27 366 | 95.30 418 | 83.56 393 | 75.74 424 | 93.41 394 |
|
| EU-MVSNet | | | 90.14 355 | 90.34 329 | 89.54 409 | 92.55 410 | 81.06 437 | 98.69 351 | 98.04 232 | 91.41 284 | 86.59 381 | 96.84 317 | 80.83 319 | 93.31 440 | 86.20 372 | 81.91 378 | 94.26 338 |
|
| APD_test1 | | | 81.15 412 | 80.92 412 | 81.86 433 | 92.45 411 | 59.76 462 | 96.04 430 | 93.61 451 | 73.29 449 | 77.06 436 | 96.64 322 | 44.28 458 | 96.16 397 | 72.35 440 | 82.52 372 | 89.67 443 |
|
| sc_t1 | | | 85.01 395 | 82.46 405 | 92.67 374 | 92.44 412 | 83.09 422 | 97.39 401 | 95.72 418 | 65.06 454 | 85.64 394 | 96.16 336 | 49.50 453 | 97.34 328 | 84.86 384 | 75.39 426 | 97.57 296 |
|
| our_test_3 | | | 90.39 345 | 89.48 350 | 93.12 364 | 92.40 413 | 89.57 365 | 99.33 270 | 96.35 406 | 87.84 365 | 85.30 395 | 94.99 390 | 84.14 286 | 96.09 401 | 80.38 412 | 84.56 358 | 93.71 390 |
|
| ppachtmachnet_test | | | 89.58 365 | 88.35 368 | 93.25 362 | 92.40 413 | 90.44 349 | 99.33 270 | 96.73 392 | 85.49 396 | 85.90 392 | 95.77 347 | 81.09 315 | 96.00 405 | 76.00 434 | 82.49 373 | 93.30 398 |
|
| v7n | | | 89.65 363 | 88.29 369 | 93.72 347 | 92.22 415 | 90.56 346 | 99.07 301 | 97.10 352 | 85.42 398 | 86.73 378 | 94.72 395 | 80.06 329 | 97.13 343 | 81.14 407 | 78.12 408 | 93.49 393 |
|
| dmvs_testset | | | 83.79 404 | 86.07 385 | 76.94 437 | 92.14 416 | 48.60 472 | 96.75 417 | 90.27 462 | 89.48 331 | 78.65 430 | 98.55 248 | 79.25 335 | 86.65 460 | 66.85 450 | 82.69 370 | 95.57 315 |
|
| PS-MVSNAJss | | | 93.64 274 | 93.31 271 | 94.61 309 | 92.11 417 | 92.19 303 | 99.12 291 | 97.38 305 | 92.51 241 | 88.45 353 | 96.99 310 | 91.20 170 | 97.29 336 | 94.36 244 | 87.71 333 | 94.36 330 |
|
| pmmvs5 | | | 90.17 354 | 89.09 355 | 93.40 356 | 92.10 418 | 89.77 363 | 99.74 179 | 95.58 423 | 85.88 390 | 87.24 375 | 95.74 348 | 73.41 389 | 96.48 382 | 88.54 343 | 83.56 367 | 93.95 372 |
|
| N_pmnet | | | 80.06 417 | 80.78 413 | 77.89 436 | 91.94 419 | 45.28 474 | 98.80 342 | 56.82 476 | 78.10 437 | 80.08 424 | 93.33 417 | 77.03 353 | 95.76 409 | 68.14 448 | 82.81 369 | 92.64 411 |
|
| test_djsdf | | | 92.83 293 | 92.29 295 | 94.47 319 | 91.90 420 | 92.46 298 | 99.55 235 | 97.27 323 | 91.17 288 | 89.96 314 | 96.07 342 | 81.10 314 | 96.89 362 | 94.67 239 | 88.91 313 | 94.05 363 |
|
| SixPastTwentyTwo | | | 88.73 372 | 88.01 373 | 90.88 391 | 91.85 421 | 82.24 428 | 98.22 381 | 95.18 433 | 88.97 341 | 82.26 411 | 96.89 312 | 71.75 394 | 96.67 375 | 84.00 388 | 82.98 368 | 93.72 389 |
|
| K. test v3 | | | 88.05 378 | 87.24 379 | 90.47 400 | 91.82 422 | 82.23 429 | 98.96 320 | 97.42 301 | 89.05 336 | 76.93 438 | 95.60 355 | 68.49 408 | 95.42 414 | 85.87 377 | 81.01 390 | 93.75 385 |
|
| OurMVSNet-221017-0 | | | 89.81 360 | 89.48 350 | 90.83 394 | 91.64 423 | 81.21 435 | 98.17 383 | 95.38 428 | 91.48 278 | 85.65 393 | 97.31 297 | 72.66 390 | 97.29 336 | 88.15 349 | 84.83 356 | 93.97 371 |
|
| mvs_tets | | | 91.81 314 | 91.08 317 | 94.00 338 | 91.63 424 | 90.58 345 | 98.67 353 | 97.43 299 | 92.43 243 | 87.37 373 | 97.05 307 | 71.76 393 | 97.32 331 | 94.75 236 | 88.68 319 | 94.11 359 |
|
| Gipuma |  | | 66.95 430 | 65.00 430 | 72.79 442 | 91.52 425 | 67.96 454 | 66.16 465 | 95.15 434 | 47.89 463 | 58.54 460 | 67.99 465 | 29.74 462 | 87.54 459 | 50.20 464 | 77.83 410 | 62.87 465 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| test_fmvsmconf0.01_n | | | 96.39 174 | 95.74 184 | 98.32 141 | 91.47 426 | 95.56 195 | 99.84 143 | 97.30 318 | 97.74 29 | 97.89 168 | 99.35 147 | 79.62 332 | 99.85 124 | 99.25 70 | 99.24 136 | 99.55 155 |
|
| jajsoiax | | | 91.92 312 | 91.18 315 | 94.15 330 | 91.35 427 | 90.95 336 | 99.00 312 | 97.42 301 | 92.61 233 | 87.38 372 | 97.08 304 | 72.46 391 | 97.36 326 | 94.53 242 | 88.77 317 | 94.13 358 |
|
| MDA-MVSNet-bldmvs | | | 84.09 402 | 81.52 409 | 91.81 385 | 91.32 428 | 88.00 389 | 98.67 353 | 95.92 414 | 80.22 431 | 55.60 463 | 93.32 418 | 68.29 410 | 93.60 438 | 73.76 437 | 76.61 421 | 93.82 383 |
|
| MVP-Stereo | | | 90.93 332 | 90.45 327 | 92.37 378 | 91.25 429 | 88.76 375 | 98.05 388 | 96.17 409 | 87.27 372 | 84.04 402 | 95.30 374 | 78.46 346 | 97.27 338 | 83.78 391 | 99.70 89 | 91.09 426 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| MDA-MVSNet_test_wron | | | 85.51 390 | 83.32 398 | 92.10 380 | 90.96 430 | 88.58 381 | 99.20 286 | 96.52 401 | 79.70 433 | 57.12 462 | 92.69 423 | 79.11 338 | 93.86 434 | 77.10 429 | 77.46 414 | 93.86 380 |
|
| YYNet1 | | | 85.50 391 | 83.33 397 | 92.00 381 | 90.89 431 | 88.38 385 | 99.22 285 | 96.55 400 | 79.60 434 | 57.26 461 | 92.72 422 | 79.09 340 | 93.78 436 | 77.25 428 | 77.37 415 | 93.84 381 |
|
| anonymousdsp | | | 91.79 319 | 90.92 319 | 94.41 324 | 90.76 432 | 92.93 285 | 98.93 324 | 97.17 337 | 89.08 335 | 87.46 371 | 95.30 374 | 78.43 347 | 96.92 360 | 92.38 283 | 88.73 318 | 93.39 396 |
|
| lessismore_v0 | | | | | 90.53 398 | 90.58 433 | 80.90 438 | | 95.80 415 | | 77.01 437 | 95.84 345 | 66.15 419 | 96.95 358 | 83.03 396 | 75.05 427 | 93.74 388 |
|
| EG-PatchMatch MVS | | | 85.35 392 | 83.81 395 | 89.99 407 | 90.39 434 | 81.89 431 | 98.21 382 | 96.09 411 | 81.78 424 | 74.73 444 | 93.72 415 | 51.56 452 | 97.12 345 | 79.16 420 | 88.61 320 | 90.96 429 |
|
| EGC-MVSNET | | | 69.38 423 | 63.76 433 | 86.26 426 | 90.32 435 | 81.66 434 | 96.24 426 | 93.85 449 | 0.99 473 | 3.22 474 | 92.33 429 | 52.44 449 | 92.92 443 | 59.53 460 | 84.90 355 | 84.21 454 |
|
| CMPMVS |  | 61.59 21 | 84.75 398 | 85.14 390 | 83.57 430 | 90.32 435 | 62.54 458 | 96.98 411 | 97.59 284 | 74.33 447 | 69.95 451 | 96.66 320 | 64.17 426 | 98.32 279 | 87.88 353 | 88.41 325 | 89.84 441 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| new_pmnet | | | 84.49 401 | 82.92 401 | 89.21 411 | 90.03 437 | 82.60 425 | 96.89 414 | 95.62 422 | 80.59 429 | 75.77 443 | 89.17 441 | 65.04 424 | 94.79 425 | 72.12 441 | 81.02 389 | 90.23 435 |
|
| pmmvs6 | | | 85.69 387 | 83.84 394 | 91.26 390 | 90.00 438 | 84.41 413 | 97.82 393 | 96.15 410 | 75.86 441 | 81.29 418 | 95.39 369 | 61.21 437 | 96.87 365 | 83.52 394 | 73.29 430 | 92.50 414 |
|
| ttmdpeth | | | 88.23 377 | 87.06 380 | 91.75 386 | 89.91 439 | 87.35 393 | 98.92 327 | 95.73 417 | 87.92 363 | 84.02 403 | 96.31 331 | 68.23 411 | 96.84 366 | 86.33 371 | 76.12 422 | 91.06 427 |
|
| DSMNet-mixed | | | 88.28 376 | 88.24 370 | 88.42 419 | 89.64 440 | 75.38 448 | 98.06 387 | 89.86 463 | 85.59 395 | 88.20 360 | 92.14 430 | 76.15 368 | 91.95 448 | 78.46 423 | 96.05 238 | 97.92 282 |
|
| UnsupCasMVSNet_eth | | | 85.52 389 | 83.99 391 | 90.10 405 | 89.36 441 | 83.51 420 | 96.65 418 | 97.99 235 | 89.14 334 | 75.89 442 | 93.83 412 | 63.25 430 | 93.92 432 | 81.92 404 | 67.90 447 | 92.88 408 |
|
| Anonymous20231206 | | | 86.32 385 | 85.42 388 | 89.02 413 | 89.11 442 | 80.53 441 | 99.05 306 | 95.28 429 | 85.43 397 | 82.82 409 | 93.92 411 | 74.40 382 | 93.44 439 | 66.99 449 | 81.83 379 | 93.08 404 |
|
| Anonymous20240521 | | | 85.15 393 | 83.81 395 | 89.16 412 | 88.32 443 | 82.69 424 | 98.80 342 | 95.74 416 | 79.72 432 | 81.53 416 | 90.99 433 | 65.38 422 | 94.16 430 | 72.69 439 | 81.11 386 | 90.63 433 |
|
| OpenMVS_ROB |  | 79.82 20 | 83.77 405 | 81.68 408 | 90.03 406 | 88.30 444 | 82.82 423 | 98.46 364 | 95.22 431 | 73.92 448 | 76.00 441 | 91.29 432 | 55.00 445 | 96.94 359 | 68.40 447 | 88.51 324 | 90.34 434 |
|
| test20.03 | | | 84.72 399 | 83.99 391 | 86.91 424 | 88.19 445 | 80.62 440 | 98.88 330 | 95.94 413 | 88.36 357 | 78.87 428 | 94.62 400 | 68.75 406 | 89.11 455 | 66.52 451 | 75.82 423 | 91.00 428 |
|
| KD-MVS_self_test | | | 83.59 406 | 82.06 406 | 88.20 420 | 86.93 446 | 80.70 439 | 97.21 404 | 96.38 404 | 82.87 418 | 82.49 410 | 88.97 442 | 67.63 413 | 92.32 446 | 73.75 438 | 62.30 458 | 91.58 424 |
|
| MIMVSNet1 | | | 82.58 409 | 80.51 414 | 88.78 415 | 86.68 447 | 84.20 414 | 96.65 418 | 95.41 427 | 78.75 435 | 78.59 431 | 92.44 425 | 51.88 451 | 89.76 454 | 65.26 454 | 78.95 402 | 92.38 417 |
|
| CL-MVSNet_self_test | | | 84.50 400 | 83.15 400 | 88.53 418 | 86.00 448 | 81.79 432 | 98.82 338 | 97.35 309 | 85.12 399 | 83.62 407 | 90.91 435 | 76.66 360 | 91.40 449 | 69.53 445 | 60.36 459 | 92.40 416 |
|
| UnsupCasMVSNet_bld | | | 79.97 419 | 77.03 424 | 88.78 415 | 85.62 449 | 81.98 430 | 93.66 442 | 97.35 309 | 75.51 444 | 70.79 450 | 83.05 457 | 48.70 455 | 94.91 423 | 78.31 424 | 60.29 460 | 89.46 446 |
|
| mvs5depth | | | 84.87 396 | 82.90 402 | 90.77 395 | 85.59 450 | 84.84 411 | 91.10 455 | 93.29 453 | 83.14 415 | 85.07 398 | 94.33 408 | 62.17 433 | 97.32 331 | 78.83 422 | 72.59 433 | 90.14 437 |
|
| Patchmatch-RL test | | | 86.90 383 | 85.98 387 | 89.67 408 | 84.45 451 | 75.59 447 | 89.71 458 | 92.43 455 | 86.89 379 | 77.83 435 | 90.94 434 | 94.22 92 | 93.63 437 | 87.75 354 | 69.61 438 | 99.79 107 |
|
| pmmvs-eth3d | | | 84.03 403 | 81.97 407 | 90.20 404 | 84.15 452 | 87.09 395 | 98.10 386 | 94.73 439 | 83.05 416 | 74.10 447 | 87.77 448 | 65.56 421 | 94.01 431 | 81.08 408 | 69.24 440 | 89.49 445 |
|
| test_fmvs3 | | | 79.99 418 | 80.17 416 | 79.45 435 | 84.02 453 | 62.83 456 | 99.05 306 | 93.49 452 | 88.29 359 | 80.06 425 | 86.65 452 | 28.09 464 | 88.00 456 | 88.63 340 | 73.27 431 | 87.54 452 |
|
| PM-MVS | | | 80.47 415 | 78.88 419 | 85.26 427 | 83.79 454 | 72.22 450 | 95.89 433 | 91.08 460 | 85.71 394 | 76.56 440 | 88.30 444 | 36.64 460 | 93.90 433 | 82.39 400 | 69.57 439 | 89.66 444 |
|
| new-patchmatchnet | | | 81.19 411 | 79.34 418 | 86.76 425 | 82.86 455 | 80.36 442 | 97.92 390 | 95.27 430 | 82.09 423 | 72.02 448 | 86.87 451 | 62.81 432 | 90.74 452 | 71.10 442 | 63.08 455 | 89.19 448 |
|
| FE-MVSNET | | | 81.05 413 | 78.81 420 | 87.79 422 | 81.98 456 | 83.70 416 | 98.23 379 | 91.78 459 | 81.27 426 | 74.29 446 | 87.44 449 | 60.92 439 | 90.67 453 | 64.92 455 | 68.43 443 | 89.01 449 |
|
| mvsany_test3 | | | 82.12 410 | 81.14 411 | 85.06 428 | 81.87 457 | 70.41 452 | 97.09 408 | 92.14 456 | 91.27 287 | 77.84 434 | 88.73 443 | 39.31 459 | 95.49 411 | 90.75 315 | 71.24 435 | 89.29 447 |
|
| WB-MVS | | | 76.28 421 | 77.28 423 | 73.29 441 | 81.18 458 | 54.68 466 | 97.87 392 | 94.19 444 | 81.30 425 | 69.43 452 | 90.70 436 | 77.02 354 | 82.06 464 | 35.71 469 | 68.11 446 | 83.13 455 |
|
| test_f | | | 78.40 420 | 77.59 422 | 80.81 434 | 80.82 459 | 62.48 459 | 96.96 412 | 93.08 454 | 83.44 413 | 74.57 445 | 84.57 456 | 27.95 465 | 92.63 444 | 84.15 386 | 72.79 432 | 87.32 453 |
|
| SSC-MVS | | | 75.42 422 | 76.40 425 | 72.49 445 | 80.68 460 | 53.62 467 | 97.42 399 | 94.06 446 | 80.42 430 | 68.75 453 | 90.14 438 | 76.54 362 | 81.66 465 | 33.25 470 | 66.34 450 | 82.19 456 |
|
| pmmvs3 | | | 80.27 416 | 77.77 421 | 87.76 423 | 80.32 461 | 82.43 427 | 98.23 379 | 91.97 457 | 72.74 450 | 78.75 429 | 87.97 447 | 57.30 444 | 90.99 451 | 70.31 443 | 62.37 457 | 89.87 440 |
|
| testf1 | | | 68.38 426 | 66.92 427 | 72.78 443 | 78.80 462 | 50.36 469 | 90.95 456 | 87.35 468 | 55.47 459 | 58.95 458 | 88.14 445 | 20.64 469 | 87.60 457 | 57.28 461 | 64.69 452 | 80.39 458 |
|
| APD_test2 | | | 68.38 426 | 66.92 427 | 72.78 443 | 78.80 462 | 50.36 469 | 90.95 456 | 87.35 468 | 55.47 459 | 58.95 458 | 88.14 445 | 20.64 469 | 87.60 457 | 57.28 461 | 64.69 452 | 80.39 458 |
|
| ambc | | | | | 83.23 431 | 77.17 464 | 62.61 457 | 87.38 460 | 94.55 443 | | 76.72 439 | 86.65 452 | 30.16 461 | 96.36 388 | 84.85 385 | 69.86 437 | 90.73 431 |
|
| test_vis3_rt | | | 68.82 424 | 66.69 429 | 75.21 440 | 76.24 465 | 60.41 461 | 96.44 421 | 68.71 475 | 75.13 445 | 50.54 466 | 69.52 464 | 16.42 474 | 96.32 390 | 80.27 413 | 66.92 449 | 68.89 462 |
|
| TDRefinement | | | 84.76 397 | 82.56 404 | 91.38 389 | 74.58 466 | 84.80 412 | 97.36 402 | 94.56 442 | 84.73 404 | 80.21 423 | 96.12 341 | 63.56 428 | 98.39 269 | 87.92 352 | 63.97 454 | 90.95 430 |
|
| E-PMN | | | 52.30 434 | 52.18 436 | 52.67 451 | 71.51 467 | 45.40 473 | 93.62 443 | 76.60 473 | 36.01 467 | 43.50 468 | 64.13 467 | 27.11 466 | 67.31 470 | 31.06 471 | 26.06 466 | 45.30 469 |
|
| EMVS | | | 51.44 436 | 51.22 438 | 52.11 452 | 70.71 468 | 44.97 475 | 94.04 439 | 75.66 474 | 35.34 469 | 42.40 469 | 61.56 470 | 28.93 463 | 65.87 471 | 27.64 472 | 24.73 467 | 45.49 468 |
|
| PMMVS2 | | | 67.15 429 | 64.15 432 | 76.14 439 | 70.56 469 | 62.07 460 | 93.89 440 | 87.52 467 | 58.09 458 | 60.02 457 | 78.32 459 | 22.38 468 | 84.54 462 | 59.56 459 | 47.03 464 | 81.80 457 |
|
| FPMVS | | | 68.72 425 | 68.72 426 | 68.71 447 | 65.95 470 | 44.27 476 | 95.97 432 | 94.74 438 | 51.13 462 | 53.26 464 | 90.50 437 | 25.11 467 | 83.00 463 | 60.80 458 | 80.97 391 | 78.87 460 |
|
| wuyk23d | | | 20.37 440 | 20.84 443 | 18.99 455 | 65.34 471 | 27.73 478 | 50.43 466 | 7.67 479 | 9.50 472 | 8.01 473 | 6.34 473 | 6.13 477 | 26.24 472 | 23.40 473 | 10.69 471 | 2.99 470 |
|
| LCM-MVSNet | | | 67.77 428 | 64.73 431 | 76.87 438 | 62.95 472 | 56.25 465 | 89.37 459 | 93.74 450 | 44.53 464 | 61.99 456 | 80.74 458 | 20.42 471 | 86.53 461 | 69.37 446 | 59.50 461 | 87.84 450 |
|
| MVE |  | 53.74 22 | 51.54 435 | 47.86 439 | 62.60 449 | 59.56 473 | 50.93 468 | 79.41 463 | 77.69 472 | 35.69 468 | 36.27 470 | 61.76 469 | 5.79 478 | 69.63 468 | 37.97 468 | 36.61 465 | 67.24 463 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| ANet_high | | | 56.10 432 | 52.24 435 | 67.66 448 | 49.27 474 | 56.82 464 | 83.94 461 | 82.02 471 | 70.47 452 | 33.28 471 | 64.54 466 | 17.23 473 | 69.16 469 | 45.59 466 | 23.85 468 | 77.02 461 |
|
| tmp_tt | | | 65.23 431 | 62.94 434 | 72.13 446 | 44.90 475 | 50.03 471 | 81.05 462 | 89.42 466 | 38.45 465 | 48.51 467 | 99.90 18 | 54.09 447 | 78.70 467 | 91.84 296 | 18.26 469 | 87.64 451 |
|
| PMVS |  | 49.05 23 | 53.75 433 | 51.34 437 | 60.97 450 | 40.80 476 | 34.68 477 | 74.82 464 | 89.62 465 | 37.55 466 | 28.67 472 | 72.12 461 | 7.09 476 | 81.63 466 | 43.17 467 | 68.21 445 | 66.59 464 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| test123 | | | 37.68 438 | 39.14 441 | 33.31 453 | 19.94 477 | 24.83 479 | 98.36 372 | 9.75 478 | 15.53 471 | 51.31 465 | 87.14 450 | 19.62 472 | 17.74 473 | 47.10 465 | 3.47 472 | 57.36 466 |
|
| testmvs | | | 40.60 437 | 44.45 440 | 29.05 454 | 19.49 478 | 14.11 480 | 99.68 204 | 18.47 477 | 20.74 470 | 64.59 455 | 98.48 255 | 10.95 475 | 17.09 474 | 56.66 463 | 11.01 470 | 55.94 467 |
|
| mmdepth | | | 0.00 443 | 0.00 446 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 0.00 475 | 0.00 479 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| monomultidepth | | | 0.00 443 | 0.00 446 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 0.00 475 | 0.00 479 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| test_blank | | | 0.00 443 | 0.00 446 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 0.02 474 | 0.00 479 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| eth-test2 | | | | | | 0.00 479 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 479 | | | | | | | | | | | |
|
| uanet_test | | | 0.00 443 | 0.00 446 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 0.00 475 | 0.00 479 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| DCPMVS | | | 0.00 443 | 0.00 446 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 0.00 475 | 0.00 479 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| cdsmvs_eth3d_5k | | | 23.43 439 | 31.24 442 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 98.09 226 | 0.00 474 | 0.00 475 | 99.67 108 | 83.37 291 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| pcd_1.5k_mvsjas | | | 7.60 442 | 10.13 445 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 0.00 475 | 91.20 170 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| sosnet-low-res | | | 0.00 443 | 0.00 446 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 0.00 475 | 0.00 479 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| sosnet | | | 0.00 443 | 0.00 446 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 0.00 475 | 0.00 479 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| uncertanet | | | 0.00 443 | 0.00 446 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 0.00 475 | 0.00 479 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| Regformer | | | 0.00 443 | 0.00 446 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 0.00 475 | 0.00 479 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| ab-mvs-re | | | 8.28 441 | 11.04 444 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 99.40 141 | 0.00 479 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| uanet | | | 0.00 443 | 0.00 446 | 0.00 456 | 0.00 479 | 0.00 481 | 0.00 467 | 0.00 480 | 0.00 474 | 0.00 475 | 0.00 475 | 0.00 479 | 0.00 475 | 0.00 474 | 0.00 473 | 0.00 471 |
|
| WAC-MVS | | | | | | | 90.97 333 | | | | | | | | 86.10 375 | | |
|
| 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 | | | | | | | | 95.78 434 | | | | 59.23 471 | 93.20 125 | 97.74 315 | 91.06 306 | | |
|
| test_post | | | | | | | | | | | | 63.35 468 | 94.43 79 | 98.13 294 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 91.70 431 | 95.12 56 | 97.95 306 | | | |
|
| MTMP | | | | | | | | 99.87 124 | 96.49 402 | | | | | | | | |
|
| 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 | | | | | | | | 99.46 253 | | 94.21 159 | 99.85 17 | | | 99.95 80 | 96.96 188 | | |
|
| 新几何2 | | | | | | | | 99.40 257 | | | | | | | | | |
|
| 无先验 | | | | | | | | 99.49 245 | 98.71 74 | 93.46 191 | | | | 100.00 1 | 94.36 244 | | 99.99 23 |
|
| 原ACMM2 | | | | | | | | 99.90 108 | | | | | | | | | |
|
| testdata2 | | | | | | | | | | | | | | 99.99 36 | 90.54 319 | | |
|
| segment_acmp | | | | | | | | | | | | | 96.68 29 | | | | |
|
| testdata1 | | | | | | | | 99.28 279 | | 96.35 87 | | | | | | | |
|
| plane_prior5 | | | | | | | | | 97.87 249 | | | | | 98.37 275 | 97.79 162 | 89.55 307 | 94.52 319 |
|
| plane_prior4 | | | | | | | | | | | | 98.59 241 | | | | | |
|
| plane_prior3 | | | | | | | 91.64 321 | | | 96.63 72 | 93.01 279 | | | | | | |
|
| plane_prior2 | | | | | | | | 99.84 143 | | 96.38 83 | | | | | | | |
|
| plane_prior | | | | | | | 91.74 315 | 99.86 135 | | 96.76 67 | | | | | | 89.59 306 | |
|
| n2 | | | | | | | | | 0.00 480 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 480 | | | | | | | | |
|
| door-mid | | | | | | | | | 89.69 464 | | | | | | | | |
|
| test11 | | | | | | | | | 98.44 143 | | | | | | | | |
|
| door | | | | | | | | | 90.31 461 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 91.85 311 | | | | | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 97.92 153 | | |
|
| HQP4-MVS | | | | | | | | | | | 93.37 274 | | | 98.39 269 | | | 94.53 317 |
|
| HQP3-MVS | | | | | | | | | 97.89 247 | | | | | | | 89.60 304 | |
|
| HQP2-MVS | | | | | | | | | | | | | 80.65 322 | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 96.26 162 | 96.11 428 | | 91.89 264 | 98.06 161 | | 94.40 81 | | 94.30 247 | | 99.67 125 |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 87.04 340 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 88.23 327 | |
|
| Test By Simon | | | | | | | | | | | | | 92.82 136 | | | | |
|