| AdaColmap |  | | 97.23 130 | 96.80 139 | 98.51 132 | 99.99 1 | 95.60 199 | 99.09 305 | 98.84 65 | 93.32 203 | 96.74 214 | 99.72 94 | 86.04 259 | 100.00 1 | 98.01 152 | 99.43 129 | 99.94 86 |
|
| CNVR-MVS | | | 99.40 1 | 99.26 1 | 99.84 6 | 99.98 2 | 99.51 6 | 99.98 21 | 98.69 81 | 98.20 9 | 99.93 2 | 99.98 2 | 96.82 26 | 100.00 1 | 99.75 41 | 100.00 1 | 99.99 24 |
|
| MCST-MVS | | | 99.32 3 | 99.14 4 | 99.86 5 | 99.97 3 | 99.59 5 | 99.97 39 | 98.64 90 | 98.47 3 | 99.13 104 | 99.92 17 | 96.38 36 | 100.00 1 | 99.74 43 | 100.00 1 | 100.00 1 |
|
| mPP-MVS | | | 98.39 56 | 98.20 54 | 98.97 92 | 99.97 3 | 96.92 138 | 99.95 72 | 98.38 183 | 95.04 123 | 98.61 138 | 99.80 58 | 93.39 117 | 100.00 1 | 98.64 114 | 100.00 1 | 99.98 56 |
|
| CPTT-MVS | | | 97.64 110 | 97.32 114 | 98.58 121 | 99.97 3 | 95.77 188 | 99.96 53 | 98.35 189 | 89.90 336 | 98.36 153 | 99.79 62 | 91.18 176 | 99.99 39 | 98.37 130 | 99.99 21 | 99.99 24 |
|
| DP-MVS Recon | | | 98.41 53 | 98.02 68 | 99.56 29 | 99.97 3 | 98.70 52 | 99.92 100 | 98.44 147 | 92.06 269 | 98.40 152 | 99.84 48 | 95.68 47 | 100.00 1 | 98.19 141 | 99.71 92 | 99.97 66 |
|
| PAPR | | | 98.52 43 | 98.16 58 | 99.58 28 | 99.97 3 | 98.77 46 | 99.95 72 | 98.43 155 | 95.35 117 | 98.03 167 | 99.75 80 | 94.03 102 | 99.98 50 | 98.11 146 | 99.83 81 | 99.99 24 |
|
| MED-MVS test | | | | | 99.60 23 | 99.96 8 | 98.79 41 | 99.97 39 | 98.88 54 | 96.36 88 | 99.07 109 | 99.93 11 | | 100.00 1 | 99.98 9 | 99.96 46 | 99.99 24 |
|
| MED-MVS | | | 99.15 8 | 99.00 12 | 99.60 23 | 99.96 8 | 98.79 41 | 99.97 39 | 98.88 54 | 95.89 101 | 99.07 109 | 99.93 11 | 97.36 17 | 100.00 1 | 99.98 9 | 99.96 46 | 99.99 24 |
|
| TestfortrainingZip a | | | 99.09 10 | 98.87 19 | 99.76 10 | 99.96 8 | 99.27 18 | 99.97 39 | 98.88 54 | 96.36 88 | 99.07 109 | 99.93 11 | 97.36 17 | 100.00 1 | 98.32 133 | 99.96 46 | 100.00 1 |
|
| HFP-MVS | | | 98.56 39 | 98.37 43 | 99.14 72 | 99.96 8 | 97.43 114 | 99.95 72 | 98.61 98 | 94.77 133 | 99.31 92 | 99.85 37 | 94.22 95 | 100.00 1 | 98.70 109 | 99.98 32 | 99.98 56 |
|
| region2R | | | 98.54 41 | 98.37 43 | 99.05 82 | 99.96 8 | 97.18 124 | 99.96 53 | 98.55 118 | 94.87 130 | 99.45 79 | 99.85 37 | 94.07 101 | 100.00 1 | 98.67 111 | 100.00 1 | 99.98 56 |
|
| ACMMPR | | | 98.50 44 | 98.32 47 | 99.05 82 | 99.96 8 | 97.18 124 | 99.95 72 | 98.60 100 | 94.77 133 | 99.31 92 | 99.84 48 | 93.73 111 | 100.00 1 | 98.70 109 | 99.98 32 | 99.98 56 |
|
| NCCC | | | 99.37 2 | 99.25 2 | 99.71 16 | 99.96 8 | 99.15 23 | 99.97 39 | 98.62 97 | 98.02 22 | 99.90 6 | 99.95 3 | 97.33 19 | 100.00 1 | 99.54 58 | 100.00 1 | 100.00 1 |
|
| CP-MVS | | | 98.45 48 | 98.32 47 | 98.87 97 | 99.96 8 | 96.62 151 | 99.97 39 | 98.39 179 | 94.43 150 | 98.90 119 | 99.87 31 | 94.30 92 | 100.00 1 | 99.04 84 | 99.99 21 | 99.99 24 |
|
| test_one_0601 | | | | | | 99.94 16 | 99.30 12 | | 98.41 172 | 96.63 73 | 99.75 40 | 99.93 11 | 97.49 10 | | | | |
|
| test_0728_SECOND | | | | | 99.82 7 | 99.94 16 | 99.47 7 | 99.95 72 | 98.43 155 | | | | | 100.00 1 | 99.99 5 | 100.00 1 | 100.00 1 |
|
| XVS | | | 98.70 32 | 98.55 31 | 99.15 70 | 99.94 16 | 97.50 110 | 99.94 90 | 98.42 167 | 96.22 92 | 99.41 84 | 99.78 66 | 94.34 89 | 99.96 75 | 98.92 94 | 99.95 54 | 99.99 24 |
|
| X-MVStestdata | | | 93.83 272 | 92.06 307 | 99.15 70 | 99.94 16 | 97.50 110 | 99.94 90 | 98.42 167 | 96.22 92 | 99.41 84 | 41.37 483 | 94.34 89 | 99.96 75 | 98.92 94 | 99.95 54 | 99.99 24 |
|
| test_prior | | | | | 99.43 40 | 99.94 16 | 98.49 65 | | 98.65 87 | | | | | 99.80 142 | | | 99.99 24 |
|
| MSLP-MVS++ | | | 99.13 9 | 99.01 11 | 99.49 36 | 99.94 16 | 98.46 66 | 99.98 21 | 98.86 59 | 97.10 53 | 99.80 26 | 99.94 4 | 95.92 43 | 100.00 1 | 99.51 59 | 100.00 1 | 100.00 1 |
|
| APDe-MVS |  | | 99.06 14 | 98.91 15 | 99.51 33 | 99.94 16 | 98.76 49 | 99.91 108 | 98.39 179 | 97.20 51 | 99.46 78 | 99.85 37 | 95.53 51 | 99.79 144 | 99.86 27 | 100.00 1 | 99.99 24 |
| Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition |
| MP-MVS |  | | 98.23 71 | 97.97 72 | 99.03 84 | 99.94 16 | 97.17 127 | 99.95 72 | 98.39 179 | 94.70 137 | 98.26 159 | 99.81 57 | 91.84 167 | 100.00 1 | 98.85 100 | 99.97 42 | 99.93 87 |
| Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
| CDPH-MVS | | | 98.65 35 | 98.36 45 | 99.49 36 | 99.94 16 | 98.73 50 | 99.87 130 | 98.33 194 | 93.97 175 | 99.76 39 | 99.87 31 | 94.99 67 | 99.75 153 | 98.55 118 | 100.00 1 | 99.98 56 |
|
| PAPM_NR | | | 98.12 75 | 97.93 78 | 98.70 108 | 99.94 16 | 96.13 177 | 99.82 159 | 98.43 155 | 94.56 141 | 97.52 184 | 99.70 100 | 94.40 84 | 99.98 50 | 97.00 192 | 99.98 32 | 99.99 24 |
|
| MG-MVS | | | 98.91 22 | 98.65 27 | 99.68 17 | 99.94 16 | 99.07 25 | 99.64 222 | 99.44 19 | 97.33 44 | 99.00 115 | 99.72 94 | 94.03 102 | 99.98 50 | 98.73 108 | 100.00 1 | 100.00 1 |
|
| ME-MVS | | | 99.07 12 | 98.89 17 | 99.59 26 | 99.93 27 | 98.79 41 | 99.95 72 | 98.80 71 | 95.89 101 | 99.28 96 | 99.93 11 | 96.28 37 | 99.98 50 | 99.98 9 | 99.96 46 | 99.99 24 |
|
| SED-MVS | | | 99.28 5 | 99.11 7 | 99.77 8 | 99.93 27 | 99.30 12 | 99.96 53 | 98.43 155 | 97.27 47 | 99.80 26 | 99.94 4 | 96.71 29 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
| IU-MVS | | | | | | 99.93 27 | 99.31 10 | | 98.41 172 | 97.71 31 | 99.84 21 | | | | 100.00 1 | 100.00 1 | 100.00 1 |
|
| test_241102_ONE | | | | | | 99.93 27 | 99.30 12 | | 98.43 155 | 97.26 49 | 99.80 26 | 99.88 28 | 96.71 29 | 100.00 1 | | | |
|
| DVP-MVS |  | | 99.30 4 | 99.16 3 | 99.73 13 | 99.93 27 | 99.29 15 | 99.95 72 | 98.32 196 | 97.28 45 | 99.83 22 | 99.91 18 | 97.22 21 | 100.00 1 | 99.99 5 | 100.00 1 | 99.89 96 |
| 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 27 | 99.29 15 | 99.96 53 | 98.42 167 | 97.28 45 | 99.86 15 | 99.94 4 | 97.22 21 | | | | |
|
| MSP-MVS | | | 99.09 10 | 99.12 5 | 98.98 91 | 99.93 27 | 97.24 121 | 99.95 72 | 98.42 167 | 97.50 38 | 99.52 74 | 99.88 28 | 97.43 16 | 99.71 159 | 99.50 61 | 99.98 32 | 100.00 1 |
| Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025 |
| agg_prior | | | | | | 99.93 27 | 98.77 46 | | 98.43 155 | | 99.63 57 | | | 99.85 129 | | | |
|
| FOURS1 | | | | | | 99.92 35 | 97.66 104 | 99.95 72 | 98.36 187 | 95.58 111 | 99.52 74 | | | | | | |
|
| ZD-MVS | | | | | | 99.92 35 | 98.57 60 | | 98.52 127 | 92.34 257 | 99.31 92 | 99.83 50 | 95.06 62 | 99.80 142 | 99.70 49 | 99.97 42 | |
|
| GST-MVS | | | 98.27 63 | 97.97 72 | 99.17 65 | 99.92 35 | 97.57 106 | 99.93 97 | 98.39 179 | 94.04 173 | 98.80 124 | 99.74 87 | 92.98 133 | 100.00 1 | 98.16 143 | 99.76 89 | 99.93 87 |
|
| TEST9 | | | | | | 99.92 35 | 98.92 30 | 99.96 53 | 98.43 155 | 93.90 181 | 99.71 47 | 99.86 33 | 95.88 44 | 99.85 129 | | | |
|
| train_agg | | | 98.88 23 | 98.65 27 | 99.59 26 | 99.92 35 | 98.92 30 | 99.96 53 | 98.43 155 | 94.35 155 | 99.71 47 | 99.86 33 | 95.94 41 | 99.85 129 | 99.69 50 | 99.98 32 | 99.99 24 |
|
| test_8 | | | | | | 99.92 35 | 98.88 33 | 99.96 53 | 98.43 155 | 94.35 155 | 99.69 49 | 99.85 37 | 95.94 41 | 99.85 129 | | | |
|
| PGM-MVS | | | 98.34 58 | 98.13 60 | 98.99 89 | 99.92 35 | 97.00 134 | 99.75 184 | 99.50 17 | 93.90 181 | 99.37 89 | 99.76 72 | 93.24 126 | 100.00 1 | 97.75 171 | 99.96 46 | 99.98 56 |
|
| ACMMP |  | | 97.74 103 | 97.44 107 | 98.66 112 | 99.92 35 | 96.13 177 | 99.18 298 | 99.45 18 | 94.84 131 | 96.41 228 | 99.71 97 | 91.40 170 | 99.99 39 | 97.99 154 | 98.03 189 | 99.87 99 |
| 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 43 | 99.31 10 | 99.95 72 | 98.43 155 | 96.48 78 | 99.80 26 | 99.93 11 | 97.44 14 | 100.00 1 | 99.92 16 | 99.98 32 | 100.00 1 |
|
| MSC_two_6792asdad | | | | | 99.93 2 | 99.91 43 | 99.80 2 | | 98.41 172 | | | | | 100.00 1 | 99.96 12 | 100.00 1 | 100.00 1 |
|
| No_MVS | | | | | 99.93 2 | 99.91 43 | 99.80 2 | | 98.41 172 | | | | | 100.00 1 | 99.96 12 | 100.00 1 | 100.00 1 |
|
| HPM-MVS++ |  | | 99.07 12 | 98.88 18 | 99.63 18 | 99.90 46 | 99.02 26 | 99.95 72 | 98.56 112 | 97.56 37 | 99.44 80 | 99.85 37 | 95.38 55 | 100.00 1 | 99.31 71 | 99.99 21 | 99.87 99 |
|
| APD-MVS |  | | 98.62 36 | 98.35 46 | 99.41 43 | 99.90 46 | 98.51 63 | 99.87 130 | 98.36 187 | 94.08 168 | 99.74 43 | 99.73 91 | 94.08 100 | 99.74 155 | 99.42 67 | 99.99 21 | 99.99 24 |
| Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
| DeepC-MVS_fast | | 96.59 1 | 98.81 26 | 98.54 32 | 99.62 21 | 99.90 46 | 98.85 36 | 99.24 293 | 98.47 139 | 98.14 16 | 99.08 107 | 99.91 18 | 93.09 130 | 100.00 1 | 99.04 84 | 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 49 | 99.80 2 | 99.96 53 | | | | 99.80 58 | 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 12 | 99.89 49 | 99.24 20 | 99.87 130 | 98.44 147 | 97.48 39 | 99.64 56 | 99.94 4 | 96.68 31 | 99.99 39 | 99.99 5 | 100.00 1 | 99.99 24 |
| Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
| test_part2 | | | | | | 99.89 49 | 99.25 19 | | | | 99.49 77 | | | | | | |
|
| CSCG | | | 97.10 136 | 97.04 126 | 97.27 230 | 99.89 49 | 91.92 319 | 99.90 114 | 99.07 37 | 88.67 360 | 95.26 260 | 99.82 53 | 93.17 129 | 99.98 50 | 98.15 144 | 99.47 124 | 99.90 95 |
|
| ZNCC-MVS | | | 98.31 60 | 98.03 67 | 99.17 65 | 99.88 53 | 97.59 105 | 99.94 90 | 98.44 147 | 94.31 158 | 98.50 145 | 99.82 53 | 93.06 131 | 99.99 39 | 98.30 135 | 99.99 21 | 99.93 87 |
|
| SR-MVS | | | 98.46 47 | 98.30 50 | 98.93 95 | 99.88 53 | 97.04 133 | 99.84 149 | 98.35 189 | 94.92 127 | 99.32 91 | 99.80 58 | 93.35 119 | 99.78 146 | 99.30 72 | 99.95 54 | 99.96 74 |
|
| 9.14 | | | | 98.38 41 | | 99.87 55 | | 99.91 108 | 98.33 194 | 93.22 206 | 99.78 37 | 99.89 26 | 94.57 80 | 99.85 129 | 99.84 29 | 99.97 42 | |
|
| SMA-MVS |  | | 98.76 29 | 98.48 35 | 99.62 21 | 99.87 55 | 98.87 34 | 99.86 141 | 98.38 183 | 93.19 208 | 99.77 38 | 99.94 4 | 95.54 49 | 100.00 1 | 99.74 43 | 99.99 21 | 100.00 1 |
| Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology |
| NormalMVS | | | 97.90 85 | 97.85 85 | 98.04 165 | 99.86 57 | 95.39 209 | 99.61 229 | 97.78 264 | 96.52 76 | 98.61 138 | 99.31 156 | 92.73 141 | 99.67 167 | 96.77 202 | 99.48 121 | 99.06 242 |
|
| lecture | | | 98.67 33 | 98.46 36 | 99.28 52 | 99.86 57 | 97.88 91 | 99.97 39 | 99.25 30 | 96.07 96 | 99.79 35 | 99.70 100 | 92.53 149 | 99.98 50 | 99.51 59 | 99.48 121 | 99.97 66 |
|
| PHI-MVS | | | 98.41 53 | 98.21 53 | 99.03 84 | 99.86 57 | 97.10 131 | 99.98 21 | 98.80 71 | 90.78 316 | 99.62 60 | 99.78 66 | 95.30 56 | 100.00 1 | 99.80 32 | 99.93 65 | 99.99 24 |
|
| MTAPA | | | 98.29 62 | 97.96 75 | 99.30 51 | 99.85 60 | 97.93 89 | 99.39 271 | 98.28 203 | 95.76 105 | 97.18 199 | 99.88 28 | 92.74 140 | 100.00 1 | 98.67 111 | 99.88 77 | 99.99 24 |
|
| LS3D | | | 95.84 204 | 95.11 217 | 98.02 166 | 99.85 60 | 95.10 227 | 98.74 355 | 98.50 136 | 87.22 382 | 93.66 281 | 99.86 33 | 87.45 235 | 99.95 84 | 90.94 319 | 99.81 87 | 99.02 246 |
|
| HPM-MVS |  | | 97.96 80 | 97.72 90 | 98.68 109 | 99.84 62 | 96.39 163 | 99.90 114 | 98.17 218 | 92.61 242 | 98.62 137 | 99.57 130 | 91.87 166 | 99.67 167 | 98.87 99 | 99.99 21 | 99.99 24 |
| Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
| EI-MVSNet-Vis-set | | | 98.27 63 | 98.11 62 | 98.75 105 | 99.83 63 | 96.59 155 | 99.40 267 | 98.51 130 | 95.29 119 | 98.51 144 | 99.76 72 | 93.60 115 | 99.71 159 | 98.53 121 | 99.52 114 | 99.95 82 |
|
| save fliter | | | | | | 99.82 64 | 98.79 41 | 99.96 53 | 98.40 176 | 97.66 33 | | | | | | | |
|
| PLC |  | 95.54 3 | 97.93 83 | 97.89 82 | 98.05 164 | 99.82 64 | 94.77 238 | 99.92 100 | 98.46 141 | 93.93 178 | 97.20 197 | 99.27 162 | 95.44 54 | 99.97 63 | 97.41 177 | 99.51 117 | 99.41 193 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| APD-MVS_3200maxsize | | | 98.25 68 | 98.08 64 | 98.78 102 | 99.81 66 | 96.60 153 | 99.82 159 | 98.30 201 | 93.95 177 | 99.37 89 | 99.77 70 | 92.84 137 | 99.76 152 | 98.95 90 | 99.92 68 | 99.97 66 |
|
| EI-MVSNet-UG-set | | | 98.14 74 | 97.99 70 | 98.60 117 | 99.80 67 | 96.27 166 | 99.36 277 | 98.50 136 | 95.21 121 | 98.30 156 | 99.75 80 | 93.29 123 | 99.73 158 | 98.37 130 | 99.30 138 | 99.81 108 |
|
| SR-MVS-dyc-post | | | 98.31 60 | 98.17 57 | 98.71 107 | 99.79 68 | 96.37 164 | 99.76 180 | 98.31 198 | 94.43 150 | 99.40 86 | 99.75 80 | 93.28 124 | 99.78 146 | 98.90 97 | 99.92 68 | 99.97 66 |
|
| RE-MVS-def | | | | 98.13 60 | | 99.79 68 | 96.37 164 | 99.76 180 | 98.31 198 | 94.43 150 | 99.40 86 | 99.75 80 | 92.95 134 | | 98.90 97 | 99.92 68 | 99.97 66 |
|
| HPM-MVS_fast | | | 97.80 97 | 97.50 103 | 98.68 109 | 99.79 68 | 96.42 159 | 99.88 127 | 98.16 223 | 91.75 280 | 98.94 117 | 99.54 133 | 91.82 168 | 99.65 171 | 97.62 174 | 99.99 21 | 99.99 24 |
|
| SF-MVS | | | 98.67 33 | 98.40 39 | 99.50 34 | 99.77 71 | 98.67 53 | 99.90 114 | 98.21 213 | 93.53 193 | 99.81 24 | 99.89 26 | 94.70 76 | 99.86 128 | 99.84 29 | 99.93 65 | 99.96 74 |
|
| MGCNet | | | 99.06 14 | 98.84 20 | 99.72 14 | 99.76 72 | 99.21 22 | 99.99 5 | 99.34 25 | 98.70 2 | 99.44 80 | 99.75 80 | 93.24 126 | 99.99 39 | 99.94 14 | 99.41 131 | 99.95 82 |
|
| 旧先验1 | | | | | | 99.76 72 | 97.52 108 | | 98.64 90 | | | 99.85 37 | 95.63 48 | | | 99.94 59 | 99.99 24 |
|
| OMC-MVS | | | 97.28 126 | 97.23 118 | 97.41 220 | 99.76 72 | 93.36 286 | 99.65 218 | 97.95 245 | 96.03 97 | 97.41 190 | 99.70 100 | 89.61 202 | 99.51 177 | 96.73 204 | 98.25 179 | 99.38 195 |
|
| 新几何1 | | | | | 99.42 42 | 99.75 75 | 98.27 70 | | 98.63 96 | 92.69 237 | 99.55 69 | 99.82 53 | 94.40 84 | 100.00 1 | 91.21 311 | 99.94 59 | 99.99 24 |
|
| MP-MVS-pluss | | | 98.07 78 | 97.64 96 | 99.38 48 | 99.74 76 | 98.41 68 | 99.74 187 | 98.18 217 | 93.35 201 | 96.45 225 | 99.85 37 | 92.64 144 | 99.97 63 | 98.91 96 | 99.89 74 | 99.77 115 |
| MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
| TSAR-MVS + MP. | | | 98.93 20 | 98.77 22 | 99.41 43 | 99.74 76 | 98.67 53 | 99.77 174 | 98.38 183 | 96.73 69 | 99.88 12 | 99.74 87 | 94.89 69 | 99.59 173 | 99.80 32 | 99.98 32 | 99.97 66 |
| 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 40 | 99.74 76 | 98.56 61 | | 98.40 176 | | 99.65 53 | | 94.76 72 | 99.75 153 | | 99.98 32 | 99.99 24 |
|
| 原ACMM1 | | | | | 98.96 93 | 99.73 79 | 96.99 135 | | 98.51 130 | 94.06 171 | 99.62 60 | 99.85 37 | 94.97 68 | 99.96 75 | 95.11 232 | 99.95 54 | 99.92 92 |
|
| TSAR-MVS + GP. | | | 98.60 37 | 98.51 34 | 98.86 98 | 99.73 79 | 96.63 150 | 99.97 39 | 97.92 250 | 98.07 19 | 98.76 130 | 99.55 131 | 95.00 66 | 99.94 93 | 99.91 19 | 97.68 196 | 99.99 24 |
|
| CANet | | | 98.27 63 | 97.82 87 | 99.63 18 | 99.72 81 | 99.10 24 | 99.98 21 | 98.51 130 | 97.00 59 | 98.52 142 | 99.71 97 | 87.80 226 | 99.95 84 | 99.75 41 | 99.38 133 | 99.83 104 |
|
| reproduce_model | | | 98.75 30 | 98.66 26 | 99.03 84 | 99.71 82 | 97.10 131 | 99.73 194 | 98.23 211 | 97.02 58 | 99.18 102 | 99.90 22 | 94.54 81 | 99.99 39 | 99.77 37 | 99.90 73 | 99.99 24 |
|
| F-COLMAP | | | 96.93 148 | 96.95 129 | 96.87 243 | 99.71 82 | 91.74 324 | 99.85 144 | 97.95 245 | 93.11 215 | 95.72 249 | 99.16 180 | 92.35 155 | 99.94 93 | 95.32 228 | 99.35 136 | 98.92 254 |
|
| reproduce-ours | | | 98.78 27 | 98.67 24 | 99.09 79 | 99.70 84 | 97.30 118 | 99.74 187 | 98.25 207 | 97.10 53 | 99.10 105 | 99.90 22 | 94.59 77 | 99.99 39 | 99.77 37 | 99.91 71 | 99.99 24 |
|
| our_new_method | | | 98.78 27 | 98.67 24 | 99.09 79 | 99.70 84 | 97.30 118 | 99.74 187 | 98.25 207 | 97.10 53 | 99.10 105 | 99.90 22 | 94.59 77 | 99.99 39 | 99.77 37 | 99.91 71 | 99.99 24 |
|
| SD-MVS | | | 98.92 21 | 98.70 23 | 99.56 29 | 99.70 84 | 98.73 50 | 99.94 90 | 98.34 193 | 96.38 84 | 99.81 24 | 99.76 72 | 94.59 77 | 99.98 50 | 99.84 29 | 99.96 46 | 99.97 66 |
| Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024 |
| patch_mono-2 | | | 98.24 69 | 99.12 5 | 95.59 284 | 99.67 87 | 86.91 408 | 99.95 72 | 98.89 52 | 97.60 34 | 99.90 6 | 99.76 72 | 96.54 34 | 99.98 50 | 99.94 14 | 99.82 85 | 99.88 97 |
|
| ACMMP_NAP | | | 98.49 45 | 98.14 59 | 99.54 31 | 99.66 88 | 98.62 59 | 99.85 144 | 98.37 186 | 94.68 138 | 99.53 72 | 99.83 50 | 92.87 136 | 100.00 1 | 98.66 113 | 99.84 80 | 99.99 24 |
|
| DeepPCF-MVS | | 95.94 2 | 97.71 107 | 98.98 13 | 93.92 350 | 99.63 89 | 81.76 444 | 99.96 53 | 98.56 112 | 99.47 1 | 99.19 101 | 99.99 1 | 94.16 99 | 100.00 1 | 99.92 16 | 99.93 65 | 100.00 1 |
|
| EPNet | | | 98.49 45 | 98.40 39 | 98.77 104 | 99.62 90 | 96.80 144 | 99.90 114 | 99.51 16 | 97.60 34 | 99.20 99 | 99.36 151 | 93.71 112 | 99.91 110 | 97.99 154 | 98.71 164 | 99.61 146 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| MM | | | 98.83 24 | 98.53 33 | 99.76 10 | 99.59 91 | 99.33 8 | 99.99 5 | 99.76 6 | 98.39 4 | 99.39 88 | 99.80 58 | 90.49 191 | 99.96 75 | 99.89 21 | 99.43 129 | 99.98 56 |
|
| PVSNet_BlendedMVS | | | 96.05 195 | 95.82 189 | 96.72 249 | 99.59 91 | 96.99 135 | 99.95 72 | 99.10 34 | 94.06 171 | 98.27 157 | 95.80 355 | 89.00 214 | 99.95 84 | 99.12 78 | 87.53 347 | 93.24 409 |
|
| PVSNet_Blended | | | 97.94 82 | 97.64 96 | 98.83 99 | 99.59 91 | 96.99 135 | 100.00 1 | 99.10 34 | 95.38 116 | 98.27 157 | 99.08 184 | 89.00 214 | 99.95 84 | 99.12 78 | 99.25 140 | 99.57 157 |
|
| PatchMatch-RL | | | 96.04 196 | 95.40 204 | 97.95 168 | 99.59 91 | 95.22 222 | 99.52 249 | 99.07 37 | 93.96 176 | 96.49 224 | 98.35 270 | 82.28 307 | 99.82 141 | 90.15 335 | 99.22 143 | 98.81 261 |
|
| dcpmvs_2 | | | 97.42 121 | 98.09 63 | 95.42 291 | 99.58 95 | 87.24 404 | 99.23 294 | 96.95 382 | 94.28 161 | 98.93 118 | 99.73 91 | 94.39 87 | 99.16 205 | 99.89 21 | 99.82 85 | 99.86 101 |
|
| test222 | | | | | | 99.55 96 | 97.41 116 | 99.34 279 | 98.55 118 | 91.86 275 | 99.27 97 | 99.83 50 | 93.84 109 | | | 99.95 54 | 99.99 24 |
|
| CNLPA | | | 97.76 101 | 97.38 110 | 98.92 96 | 99.53 97 | 96.84 140 | 99.87 130 | 98.14 227 | 93.78 185 | 96.55 222 | 99.69 104 | 92.28 157 | 99.98 50 | 97.13 187 | 99.44 128 | 99.93 87 |
|
| API-MVS | | | 97.86 88 | 97.66 94 | 98.47 134 | 99.52 98 | 95.41 207 | 99.47 259 | 98.87 58 | 91.68 281 | 98.84 121 | 99.85 37 | 92.34 156 | 99.99 39 | 98.44 126 | 99.96 46 | 100.00 1 |
|
| PVSNet | | 91.05 13 | 97.13 135 | 96.69 145 | 98.45 137 | 99.52 98 | 95.81 186 | 99.95 72 | 99.65 12 | 94.73 135 | 99.04 113 | 99.21 173 | 84.48 290 | 99.95 84 | 94.92 238 | 98.74 163 | 99.58 155 |
|
| 114514_t | | | 97.41 122 | 96.83 136 | 99.14 72 | 99.51 100 | 97.83 93 | 99.89 124 | 98.27 205 | 88.48 364 | 99.06 112 | 99.66 115 | 90.30 194 | 99.64 172 | 96.32 213 | 99.97 42 | 99.96 74 |
|
| cl22 | | | 93.77 277 | 93.25 281 | 95.33 295 | 99.49 101 | 94.43 248 | 99.61 229 | 98.09 230 | 90.38 324 | 89.16 351 | 95.61 363 | 90.56 189 | 97.34 337 | 91.93 302 | 84.45 368 | 94.21 354 |
|
| testdata | | | | | 98.42 141 | 99.47 102 | 95.33 213 | | 98.56 112 | 93.78 185 | 99.79 35 | 99.85 37 | 93.64 114 | 99.94 93 | 94.97 236 | 99.94 59 | 100.00 1 |
|
| MAR-MVS | | | 97.43 117 | 97.19 120 | 98.15 157 | 99.47 102 | 94.79 237 | 99.05 316 | 98.76 73 | 92.65 240 | 98.66 135 | 99.82 53 | 88.52 220 | 99.98 50 | 98.12 145 | 99.63 99 | 99.67 129 |
| 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 | | | 94.54 249 | 93.42 271 | 97.91 174 | 99.46 104 | 94.04 263 | 98.93 334 | 97.48 301 | 81.15 437 | 90.04 322 | 99.55 131 | 87.02 243 | 99.95 84 | 88.97 347 | 98.11 185 | 99.73 119 |
|
| MVS_111021_LR | | | 98.42 52 | 98.38 41 | 98.53 129 | 99.39 105 | 95.79 187 | 99.87 130 | 99.86 2 | 96.70 70 | 98.78 125 | 99.79 62 | 92.03 163 | 99.90 112 | 99.17 77 | 99.86 79 | 99.88 97 |
|
| CHOSEN 280x420 | | | 99.01 17 | 99.03 10 | 98.95 94 | 99.38 106 | 98.87 34 | 98.46 374 | 99.42 21 | 97.03 57 | 99.02 114 | 99.09 183 | 99.35 2 | 98.21 299 | 99.73 45 | 99.78 88 | 99.77 115 |
|
| MVS_111021_HR | | | 98.72 31 | 98.62 29 | 99.01 88 | 99.36 107 | 97.18 124 | 99.93 97 | 99.90 1 | 96.81 67 | 98.67 134 | 99.77 70 | 93.92 104 | 99.89 117 | 99.27 73 | 99.94 59 | 99.96 74 |
|
| fmvsm_s_conf0.5_n_11 | | | 98.03 79 | 97.89 82 | 98.46 136 | 99.35 108 | 97.76 97 | 99.99 5 | 98.04 236 | 98.20 9 | 99.90 6 | 99.78 66 | 86.21 257 | 99.95 84 | 99.89 21 | 99.68 94 | 97.65 299 |
|
| DPM-MVS | | | 98.83 24 | 98.46 36 | 99.97 1 | 99.33 109 | 99.92 1 | 99.96 53 | 98.44 147 | 97.96 23 | 99.55 69 | 99.94 4 | 97.18 23 | 100.00 1 | 93.81 269 | 99.94 59 | 99.98 56 |
|
| TAPA-MVS | | 92.12 8 | 94.42 257 | 93.60 263 | 96.90 242 | 99.33 109 | 91.78 323 | 99.78 169 | 98.00 239 | 89.89 337 | 94.52 266 | 99.47 137 | 91.97 164 | 99.18 202 | 69.90 455 | 99.52 114 | 99.73 119 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| reproduce_monomvs | | | 95.38 221 | 95.07 219 | 96.32 264 | 99.32 111 | 96.60 153 | 99.76 180 | 98.85 62 | 96.65 72 | 87.83 373 | 96.05 352 | 99.52 1 | 98.11 304 | 96.58 208 | 81.07 397 | 94.25 349 |
|
| fmvsm_s_conf0.5_n_9 | | | 98.15 73 | 98.02 68 | 98.55 123 | 99.28 112 | 95.84 185 | 99.99 5 | 98.57 106 | 98.17 13 | 99.93 2 | 99.74 87 | 87.04 242 | 99.97 63 | 99.86 27 | 99.59 108 | 99.83 104 |
|
| SPE-MVS-test | | | 97.88 86 | 97.94 77 | 97.70 192 | 99.28 112 | 95.20 223 | 99.98 21 | 97.15 349 | 95.53 113 | 99.62 60 | 99.79 62 | 92.08 162 | 98.38 282 | 98.75 107 | 99.28 139 | 99.52 169 |
|
| test_fmvsm_n_1920 | | | 98.44 49 | 98.61 30 | 97.92 172 | 99.27 114 | 95.18 224 | 100.00 1 | 98.90 50 | 98.05 20 | 99.80 26 | 99.73 91 | 92.64 144 | 99.99 39 | 99.58 57 | 99.51 117 | 98.59 271 |
|
| fmvsm_s_conf0.5_n_10 | | | 98.24 69 | 97.90 80 | 99.26 54 | 99.24 115 | 97.88 91 | 99.99 5 | 98.76 73 | 98.20 9 | 99.92 4 | 99.74 87 | 85.97 261 | 99.94 93 | 99.72 46 | 99.53 113 | 99.96 74 |
|
| fmvsm_l_conf0.5_n_a | | | 99.00 18 | 98.91 15 | 99.28 52 | 99.21 116 | 97.91 90 | 99.98 21 | 98.85 62 | 98.25 5 | 99.92 4 | 99.75 80 | 94.72 74 | 99.97 63 | 99.87 25 | 99.64 97 | 99.95 82 |
|
| fmvsm_s_conf0.5_n_8 | | | 98.38 57 | 98.05 66 | 99.35 49 | 99.20 117 | 98.12 76 | 99.98 21 | 98.81 67 | 98.22 7 | 99.80 26 | 99.71 97 | 87.37 237 | 99.97 63 | 99.91 19 | 99.48 121 | 99.97 66 |
|
| test_yl | | | 97.83 92 | 97.37 111 | 99.21 59 | 99.18 118 | 97.98 85 | 99.64 222 | 99.27 27 | 91.43 290 | 97.88 174 | 98.99 196 | 95.84 45 | 99.84 137 | 98.82 101 | 95.32 274 | 99.79 111 |
|
| DCV-MVSNet | | | 97.83 92 | 97.37 111 | 99.21 59 | 99.18 118 | 97.98 85 | 99.64 222 | 99.27 27 | 91.43 290 | 97.88 174 | 98.99 196 | 95.84 45 | 99.84 137 | 98.82 101 | 95.32 274 | 99.79 111 |
|
| fmvsm_l_conf0.5_n | | | 98.94 19 | 98.84 20 | 99.25 55 | 99.17 120 | 97.81 95 | 99.98 21 | 98.86 59 | 98.25 5 | 99.90 6 | 99.76 72 | 94.21 97 | 99.97 63 | 99.87 25 | 99.52 114 | 99.98 56 |
|
| DeepC-MVS | | 94.51 4 | 96.92 149 | 96.40 159 | 98.45 137 | 99.16 121 | 95.90 183 | 99.66 217 | 98.06 233 | 96.37 87 | 94.37 272 | 99.49 136 | 83.29 300 | 99.90 112 | 97.63 173 | 99.61 104 | 99.55 159 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| DELS-MVS | | | 98.54 41 | 98.22 52 | 99.50 34 | 99.15 122 | 98.65 57 | 100.00 1 | 98.58 104 | 97.70 32 | 98.21 162 | 99.24 169 | 92.58 147 | 99.94 93 | 98.63 116 | 99.94 59 | 99.92 92 |
| Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023 |
| fmvsm_l_conf0.5_n_3 | | | 98.41 53 | 98.08 64 | 99.39 45 | 99.12 123 | 98.29 69 | 99.98 21 | 98.64 90 | 98.14 16 | 99.86 15 | 99.76 72 | 87.99 225 | 99.97 63 | 99.72 46 | 99.54 111 | 99.91 94 |
|
| fmvsm_l_conf0.5_n_9 | | | 98.55 40 | 98.23 51 | 99.49 36 | 99.10 124 | 98.50 64 | 99.99 5 | 98.70 79 | 98.14 16 | 99.94 1 | 99.68 111 | 89.02 213 | 99.98 50 | 99.89 21 | 99.61 104 | 99.99 24 |
|
| CS-MVS | | | 97.79 99 | 97.91 79 | 97.43 218 | 99.10 124 | 94.42 249 | 99.99 5 | 97.10 361 | 95.07 122 | 99.68 50 | 99.75 80 | 92.95 134 | 98.34 286 | 98.38 128 | 99.14 145 | 99.54 163 |
|
| Anonymous202405211 | | | 93.10 295 | 91.99 308 | 96.40 260 | 99.10 124 | 89.65 373 | 98.88 340 | 97.93 247 | 83.71 421 | 94.00 278 | 98.75 232 | 68.79 413 | 99.88 123 | 95.08 233 | 91.71 307 | 99.68 127 |
|
| fmvsm_s_conf0.5_n | | | 97.80 97 | 97.85 85 | 97.67 193 | 99.06 127 | 94.41 250 | 99.98 21 | 98.97 43 | 97.34 42 | 99.63 57 | 99.69 104 | 87.27 238 | 99.97 63 | 99.62 55 | 99.06 150 | 98.62 270 |
|
| HyFIR lowres test | | | 96.66 165 | 96.43 156 | 97.36 225 | 99.05 128 | 93.91 268 | 99.70 208 | 99.80 3 | 90.54 320 | 96.26 231 | 98.08 283 | 92.15 160 | 98.23 298 | 96.84 201 | 95.46 269 | 99.93 87 |
|
| LFMVS | | | 94.75 243 | 93.56 266 | 98.30 147 | 99.03 129 | 95.70 193 | 98.74 355 | 97.98 242 | 87.81 375 | 98.47 146 | 99.39 148 | 67.43 422 | 99.53 174 | 98.01 152 | 95.20 277 | 99.67 129 |
|
| fmvsm_s_conf0.5_n_4 | | | 97.75 102 | 97.86 84 | 97.42 219 | 99.01 130 | 94.69 240 | 99.97 39 | 98.76 73 | 97.91 25 | 99.87 13 | 99.76 72 | 86.70 249 | 99.93 103 | 99.67 52 | 99.12 148 | 97.64 300 |
|
| fmvsm_s_conf0.5_n_2 | | | 97.59 112 | 97.28 115 | 98.53 129 | 99.01 130 | 98.15 71 | 99.98 21 | 98.59 102 | 98.17 13 | 99.75 40 | 99.63 121 | 81.83 313 | 99.94 93 | 99.78 35 | 98.79 161 | 97.51 308 |
|
| AllTest | | | 92.48 310 | 91.64 313 | 95.00 304 | 99.01 130 | 88.43 391 | 98.94 332 | 96.82 396 | 86.50 391 | 88.71 356 | 98.47 265 | 74.73 388 | 99.88 123 | 85.39 387 | 96.18 244 | 96.71 314 |
|
| TestCases | | | | | 95.00 304 | 99.01 130 | 88.43 391 | | 96.82 396 | 86.50 391 | 88.71 356 | 98.47 265 | 74.73 388 | 99.88 123 | 85.39 387 | 96.18 244 | 96.71 314 |
|
| COLMAP_ROB |  | 90.47 14 | 92.18 317 | 91.49 319 | 94.25 338 | 99.00 134 | 88.04 397 | 98.42 380 | 96.70 403 | 82.30 432 | 88.43 365 | 99.01 193 | 76.97 363 | 99.85 129 | 86.11 383 | 96.50 236 | 94.86 325 |
| Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
| fmvsm_s_conf0.5_n_3 | | | 97.95 81 | 97.66 94 | 98.81 100 | 98.99 135 | 98.07 79 | 99.98 21 | 98.81 67 | 98.18 12 | 99.89 10 | 99.70 100 | 84.15 293 | 99.97 63 | 99.76 40 | 99.50 119 | 98.39 278 |
|
| test_fmvs1 | | | 95.35 222 | 95.68 196 | 94.36 334 | 98.99 135 | 84.98 419 | 99.96 53 | 96.65 405 | 97.60 34 | 99.73 45 | 98.96 202 | 71.58 403 | 99.93 103 | 98.31 134 | 99.37 134 | 98.17 283 |
|
| HY-MVS | | 92.50 7 | 97.79 99 | 97.17 122 | 99.63 18 | 98.98 137 | 99.32 9 | 97.49 409 | 99.52 14 | 95.69 108 | 98.32 155 | 97.41 303 | 93.32 121 | 99.77 149 | 98.08 149 | 95.75 259 | 99.81 108 |
|
| VNet | | | 97.21 131 | 96.57 150 | 99.13 76 | 98.97 138 | 97.82 94 | 99.03 319 | 99.21 32 | 94.31 158 | 99.18 102 | 98.88 214 | 86.26 256 | 99.89 117 | 98.93 92 | 94.32 287 | 99.69 126 |
|
| thres200 | | | 96.96 145 | 96.21 166 | 99.22 58 | 98.97 138 | 98.84 37 | 99.85 144 | 99.71 7 | 93.17 210 | 96.26 231 | 98.88 214 | 89.87 199 | 99.51 177 | 94.26 257 | 94.91 279 | 99.31 212 |
|
| tfpn200view9 | | | 96.79 153 | 95.99 173 | 99.19 61 | 98.94 140 | 98.82 38 | 99.78 169 | 99.71 7 | 92.86 225 | 96.02 239 | 98.87 221 | 89.33 206 | 99.50 179 | 93.84 266 | 94.57 283 | 99.27 221 |
|
| thres400 | | | 96.78 155 | 95.99 173 | 99.16 68 | 98.94 140 | 98.82 38 | 99.78 169 | 99.71 7 | 92.86 225 | 96.02 239 | 98.87 221 | 89.33 206 | 99.50 179 | 93.84 266 | 94.57 283 | 99.16 230 |
|
| sasdasda | | | 97.09 138 | 96.32 160 | 99.39 45 | 98.93 142 | 98.95 28 | 99.72 198 | 97.35 314 | 94.45 146 | 97.88 174 | 99.42 141 | 86.71 247 | 99.52 175 | 98.48 123 | 93.97 293 | 99.72 121 |
|
| Anonymous20231211 | | | 89.86 367 | 88.44 375 | 94.13 341 | 98.93 142 | 90.68 351 | 98.54 371 | 98.26 206 | 76.28 450 | 86.73 387 | 95.54 367 | 70.60 409 | 97.56 330 | 90.82 322 | 80.27 406 | 94.15 362 |
|
| canonicalmvs | | | 97.09 138 | 96.32 160 | 99.39 45 | 98.93 142 | 98.95 28 | 99.72 198 | 97.35 314 | 94.45 146 | 97.88 174 | 99.42 141 | 86.71 247 | 99.52 175 | 98.48 123 | 93.97 293 | 99.72 121 |
|
| SDMVSNet | | | 94.80 238 | 93.96 253 | 97.33 228 | 98.92 145 | 95.42 206 | 99.59 234 | 98.99 40 | 92.41 253 | 92.55 296 | 97.85 294 | 75.81 378 | 98.93 220 | 97.90 160 | 91.62 308 | 97.64 300 |
|
| sd_testset | | | 93.55 284 | 92.83 288 | 95.74 282 | 98.92 145 | 90.89 347 | 98.24 388 | 98.85 62 | 92.41 253 | 92.55 296 | 97.85 294 | 71.07 408 | 98.68 251 | 93.93 263 | 91.62 308 | 97.64 300 |
|
| EPNet_dtu | | | 95.71 210 | 95.39 205 | 96.66 251 | 98.92 145 | 93.41 282 | 99.57 239 | 98.90 50 | 96.19 94 | 97.52 184 | 98.56 255 | 92.65 143 | 97.36 335 | 77.89 435 | 98.33 174 | 99.20 228 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| WTY-MVS | | | 98.10 76 | 97.60 98 | 99.60 23 | 98.92 145 | 99.28 17 | 99.89 124 | 99.52 14 | 95.58 111 | 98.24 161 | 99.39 148 | 93.33 120 | 99.74 155 | 97.98 156 | 95.58 268 | 99.78 114 |
|
| CHOSEN 1792x2688 | | | 96.81 152 | 96.53 151 | 97.64 196 | 98.91 149 | 93.07 288 | 99.65 218 | 99.80 3 | 95.64 109 | 95.39 256 | 98.86 223 | 84.35 292 | 99.90 112 | 96.98 194 | 99.16 144 | 99.95 82 |
|
| thres100view900 | | | 96.74 160 | 95.92 185 | 99.18 62 | 98.90 150 | 98.77 46 | 99.74 187 | 99.71 7 | 92.59 244 | 95.84 243 | 98.86 223 | 89.25 208 | 99.50 179 | 93.84 266 | 94.57 283 | 99.27 221 |
|
| thres600view7 | | | 96.69 163 | 95.87 188 | 99.14 72 | 98.90 150 | 98.78 45 | 99.74 187 | 99.71 7 | 92.59 244 | 95.84 243 | 98.86 223 | 89.25 208 | 99.50 179 | 93.44 279 | 94.50 286 | 99.16 230 |
|
| MSDG | | | 94.37 259 | 93.36 278 | 97.40 221 | 98.88 152 | 93.95 267 | 99.37 275 | 97.38 310 | 85.75 402 | 90.80 315 | 99.17 177 | 84.11 295 | 99.88 123 | 86.35 379 | 98.43 172 | 98.36 280 |
|
| MGCFI-Net | | | 97.00 143 | 96.22 165 | 99.34 50 | 98.86 153 | 98.80 40 | 99.67 216 | 97.30 326 | 94.31 158 | 97.77 180 | 99.41 145 | 86.36 254 | 99.50 179 | 98.38 128 | 93.90 295 | 99.72 121 |
|
| h-mvs33 | | | 94.92 235 | 94.36 239 | 96.59 253 | 98.85 154 | 91.29 339 | 98.93 334 | 98.94 44 | 95.90 99 | 98.77 127 | 98.42 268 | 90.89 184 | 99.77 149 | 97.80 164 | 70.76 445 | 98.72 267 |
|
| Anonymous20240529 | | | 92.10 318 | 90.65 330 | 96.47 255 | 98.82 155 | 90.61 353 | 98.72 357 | 98.67 86 | 75.54 454 | 93.90 280 | 98.58 253 | 66.23 426 | 99.90 112 | 94.70 247 | 90.67 311 | 98.90 257 |
|
| PVSNet_Blended_VisFu | | | 97.27 127 | 96.81 138 | 98.66 112 | 98.81 156 | 96.67 149 | 99.92 100 | 98.64 90 | 94.51 143 | 96.38 229 | 98.49 261 | 89.05 212 | 99.88 123 | 97.10 189 | 98.34 173 | 99.43 190 |
|
| PS-MVSNAJ | | | 98.44 49 | 98.20 54 | 99.16 68 | 98.80 157 | 98.92 30 | 99.54 247 | 98.17 218 | 97.34 42 | 99.85 18 | 99.85 37 | 91.20 173 | 99.89 117 | 99.41 68 | 99.67 95 | 98.69 268 |
|
| CANet_DTU | | | 96.76 156 | 96.15 168 | 98.60 117 | 98.78 158 | 97.53 107 | 99.84 149 | 97.63 279 | 97.25 50 | 99.20 99 | 99.64 118 | 81.36 319 | 99.98 50 | 92.77 290 | 98.89 155 | 98.28 282 |
|
| mvsany_test1 | | | 97.82 95 | 97.90 80 | 97.55 207 | 98.77 159 | 93.04 291 | 99.80 165 | 97.93 247 | 96.95 61 | 99.61 67 | 99.68 111 | 90.92 181 | 99.83 139 | 99.18 76 | 98.29 178 | 99.80 110 |
|
| alignmvs | | | 97.81 96 | 97.33 113 | 99.25 55 | 98.77 159 | 98.66 55 | 99.99 5 | 98.44 147 | 94.40 154 | 98.41 150 | 99.47 137 | 93.65 113 | 99.42 189 | 98.57 117 | 94.26 289 | 99.67 129 |
|
| SymmetryMVS | | | 97.64 110 | 97.46 104 | 98.17 153 | 98.74 161 | 95.39 209 | 99.61 229 | 99.26 29 | 96.52 76 | 98.61 138 | 99.31 156 | 92.73 141 | 99.67 167 | 96.77 202 | 95.63 266 | 99.45 186 |
|
| SteuartSystems-ACMMP | | | 99.02 16 | 98.97 14 | 99.18 62 | 98.72 162 | 97.71 99 | 99.98 21 | 98.44 147 | 96.85 62 | 99.80 26 | 99.91 18 | 97.57 8 | 99.85 129 | 99.44 66 | 99.99 21 | 99.99 24 |
| Skip Steuart: Steuart Systems R&D Blog. |
| xiu_mvs_v2_base | | | 98.23 71 | 97.97 72 | 99.02 87 | 98.69 163 | 98.66 55 | 99.52 249 | 98.08 232 | 97.05 56 | 99.86 15 | 99.86 33 | 90.65 186 | 99.71 159 | 99.39 70 | 98.63 165 | 98.69 268 |
|
| miper_enhance_ethall | | | 94.36 261 | 93.98 252 | 95.49 285 | 98.68 164 | 95.24 220 | 99.73 194 | 97.29 329 | 93.28 205 | 89.86 327 | 95.97 353 | 94.37 88 | 97.05 358 | 92.20 294 | 84.45 368 | 94.19 355 |
|
| fmvsm_s_conf0.5_n_5 | | | 98.08 77 | 97.71 92 | 99.17 65 | 98.67 165 | 97.69 103 | 99.99 5 | 98.57 106 | 97.40 40 | 99.89 10 | 99.69 104 | 85.99 260 | 99.96 75 | 99.80 32 | 99.40 132 | 99.85 102 |
|
| ETVMVS | | | 97.03 142 | 96.64 146 | 98.20 152 | 98.67 165 | 97.12 128 | 99.89 124 | 98.57 106 | 91.10 302 | 98.17 163 | 98.59 250 | 93.86 108 | 98.19 300 | 95.64 225 | 95.24 276 | 99.28 219 |
|
| test2506 | | | 97.53 114 | 97.19 120 | 98.58 121 | 98.66 167 | 96.90 139 | 98.81 349 | 99.77 5 | 94.93 125 | 97.95 169 | 98.96 202 | 92.51 150 | 99.20 200 | 94.93 237 | 98.15 182 | 99.64 135 |
|
| ECVR-MVS |  | | 95.66 213 | 95.05 220 | 97.51 212 | 98.66 167 | 93.71 272 | 98.85 346 | 98.45 142 | 94.93 125 | 96.86 210 | 98.96 202 | 75.22 384 | 99.20 200 | 95.34 227 | 98.15 182 | 99.64 135 |
|
| mamv4 | | | 95.24 225 | 96.90 131 | 90.25 412 | 98.65 169 | 72.11 462 | 98.28 385 | 97.64 278 | 89.99 335 | 95.93 241 | 98.25 278 | 94.74 73 | 99.11 206 | 99.01 89 | 99.64 97 | 99.53 167 |
|
| balanced_conf03 | | | 98.27 63 | 97.99 70 | 99.11 77 | 98.64 170 | 98.43 67 | 99.47 259 | 97.79 262 | 94.56 141 | 99.74 43 | 98.35 270 | 94.33 91 | 99.25 194 | 99.12 78 | 99.96 46 | 99.64 135 |
|
| fmvsm_s_conf0.5_n_a | | | 97.73 105 | 97.72 90 | 97.77 186 | 98.63 171 | 94.26 257 | 99.96 53 | 98.92 49 | 97.18 52 | 99.75 40 | 99.69 104 | 87.00 244 | 99.97 63 | 99.46 64 | 98.89 155 | 99.08 240 |
|
| MVSMamba_PlusPlus | | | 97.83 92 | 97.45 106 | 98.99 89 | 98.60 172 | 98.15 71 | 99.58 236 | 97.74 269 | 90.34 327 | 99.26 98 | 98.32 273 | 94.29 93 | 99.23 195 | 99.03 87 | 99.89 74 | 99.58 155 |
|
| testing222 | | | 97.08 141 | 96.75 141 | 98.06 163 | 98.56 173 | 96.82 141 | 99.85 144 | 98.61 98 | 92.53 248 | 98.84 121 | 98.84 227 | 93.36 118 | 98.30 290 | 95.84 221 | 94.30 288 | 99.05 244 |
|
| test1111 | | | 95.57 216 | 94.98 223 | 97.37 223 | 98.56 173 | 93.37 285 | 98.86 344 | 98.45 142 | 94.95 124 | 96.63 216 | 98.95 207 | 75.21 385 | 99.11 206 | 95.02 234 | 98.14 184 | 99.64 135 |
|
| MVSTER | | | 95.53 217 | 95.22 212 | 96.45 258 | 98.56 173 | 97.72 98 | 99.91 108 | 97.67 274 | 92.38 256 | 91.39 306 | 97.14 310 | 97.24 20 | 97.30 342 | 94.80 243 | 87.85 340 | 94.34 344 |
|
| testing3-2 | | | 97.72 106 | 97.43 109 | 98.60 117 | 98.55 176 | 97.11 130 | 100.00 1 | 99.23 31 | 93.78 185 | 97.90 171 | 98.73 234 | 95.50 52 | 99.69 163 | 98.53 121 | 94.63 281 | 98.99 248 |
|
| VDD-MVS | | | 93.77 277 | 92.94 286 | 96.27 265 | 98.55 176 | 90.22 362 | 98.77 354 | 97.79 262 | 90.85 308 | 96.82 212 | 99.42 141 | 61.18 446 | 99.77 149 | 98.95 90 | 94.13 290 | 98.82 260 |
|
| tpmvs | | | 94.28 263 | 93.57 265 | 96.40 260 | 98.55 176 | 91.50 337 | 95.70 447 | 98.55 118 | 87.47 377 | 92.15 299 | 94.26 418 | 91.42 169 | 98.95 219 | 88.15 358 | 95.85 255 | 98.76 263 |
|
| UGNet | | | 95.33 223 | 94.57 235 | 97.62 200 | 98.55 176 | 94.85 232 | 98.67 363 | 99.32 26 | 95.75 106 | 96.80 213 | 96.27 342 | 72.18 400 | 99.96 75 | 94.58 250 | 99.05 151 | 98.04 288 |
| 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 | 95.18 227 | 94.10 246 | 98.43 139 | 98.55 176 | 95.99 181 | 97.91 402 | 97.31 325 | 90.35 326 | 89.48 340 | 99.22 170 | 85.19 276 | 99.89 117 | 90.40 332 | 98.47 171 | 99.41 193 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| UWE-MVS-28 | | | 95.95 198 | 96.49 152 | 94.34 335 | 98.51 181 | 89.99 367 | 99.39 271 | 98.57 106 | 93.14 212 | 97.33 193 | 98.31 275 | 93.44 116 | 94.68 435 | 93.69 276 | 95.98 249 | 98.34 281 |
|
| UWE-MVS | | | 96.79 153 | 96.72 143 | 97.00 237 | 98.51 181 | 93.70 273 | 99.71 201 | 98.60 100 | 92.96 220 | 97.09 200 | 98.34 272 | 96.67 33 | 98.85 226 | 92.11 300 | 96.50 236 | 98.44 276 |
|
| myMVS_eth3d28 | | | 97.86 88 | 97.59 100 | 98.68 109 | 98.50 183 | 97.26 120 | 99.92 100 | 98.55 118 | 93.79 184 | 98.26 159 | 98.75 232 | 95.20 57 | 99.48 185 | 98.93 92 | 96.40 239 | 99.29 217 |
|
| test_vis1_n_1920 | | | 95.44 219 | 95.31 208 | 95.82 279 | 98.50 183 | 88.74 385 | 99.98 21 | 97.30 326 | 97.84 28 | 99.85 18 | 99.19 175 | 66.82 424 | 99.97 63 | 98.82 101 | 99.46 126 | 98.76 263 |
|
| BH-w/o | | | 95.71 210 | 95.38 206 | 96.68 250 | 98.49 185 | 92.28 310 | 99.84 149 | 97.50 299 | 92.12 266 | 92.06 302 | 98.79 230 | 84.69 286 | 98.67 253 | 95.29 229 | 99.66 96 | 99.09 238 |
|
| baseline1 | | | 95.78 206 | 94.86 226 | 98.54 127 | 98.47 186 | 98.07 79 | 99.06 312 | 97.99 240 | 92.68 238 | 94.13 277 | 98.62 247 | 93.28 124 | 98.69 250 | 93.79 271 | 85.76 355 | 98.84 259 |
|
| fmvsm_s_conf0.5_n_7 | | | 97.70 108 | 97.74 89 | 97.59 205 | 98.44 187 | 95.16 226 | 99.97 39 | 98.65 87 | 97.95 24 | 99.62 60 | 99.78 66 | 86.09 258 | 99.94 93 | 99.69 50 | 99.50 119 | 97.66 298 |
|
| EPMVS | | | 96.53 172 | 96.01 172 | 98.09 161 | 98.43 188 | 96.12 179 | 96.36 434 | 99.43 20 | 93.53 193 | 97.64 182 | 95.04 395 | 94.41 83 | 98.38 282 | 91.13 313 | 98.11 185 | 99.75 117 |
|
| kuosan | | | 93.17 292 | 92.60 294 | 94.86 311 | 98.40 189 | 89.54 375 | 98.44 376 | 98.53 125 | 84.46 416 | 88.49 361 | 97.92 291 | 90.57 188 | 97.05 358 | 83.10 404 | 93.49 298 | 97.99 289 |
|
| WBMVS | | | 94.52 252 | 94.03 250 | 95.98 271 | 98.38 190 | 96.68 148 | 99.92 100 | 97.63 279 | 90.75 317 | 89.64 335 | 95.25 388 | 96.77 27 | 96.90 370 | 94.35 255 | 83.57 375 | 94.35 342 |
|
| UBG | | | 97.84 91 | 97.69 93 | 98.29 148 | 98.38 190 | 96.59 155 | 99.90 114 | 98.53 125 | 93.91 180 | 98.52 142 | 98.42 268 | 96.77 27 | 99.17 203 | 98.54 119 | 96.20 243 | 99.11 237 |
|
| sss | | | 97.57 113 | 97.03 127 | 99.18 62 | 98.37 192 | 98.04 82 | 99.73 194 | 99.38 22 | 93.46 197 | 98.76 130 | 99.06 188 | 91.21 172 | 99.89 117 | 96.33 212 | 97.01 227 | 99.62 142 |
|
| testing11 | | | 97.48 116 | 97.27 116 | 98.10 160 | 98.36 193 | 96.02 180 | 99.92 100 | 98.45 142 | 93.45 199 | 98.15 164 | 98.70 237 | 95.48 53 | 99.22 196 | 97.85 162 | 95.05 278 | 99.07 241 |
|
| BH-untuned | | | 95.18 227 | 94.83 227 | 96.22 266 | 98.36 193 | 91.22 340 | 99.80 165 | 97.32 324 | 90.91 306 | 91.08 309 | 98.67 239 | 83.51 297 | 98.54 264 | 94.23 258 | 99.61 104 | 98.92 254 |
|
| testing91 | | | 97.16 133 | 96.90 131 | 97.97 167 | 98.35 195 | 95.67 196 | 99.91 108 | 98.42 167 | 92.91 223 | 97.33 193 | 98.72 235 | 94.81 71 | 99.21 197 | 96.98 194 | 94.63 281 | 99.03 245 |
|
| testing99 | | | 97.17 132 | 96.91 130 | 97.95 168 | 98.35 195 | 95.70 193 | 99.91 108 | 98.43 155 | 92.94 221 | 97.36 191 | 98.72 235 | 94.83 70 | 99.21 197 | 97.00 192 | 94.64 280 | 98.95 250 |
|
| ET-MVSNet_ETH3D | | | 94.37 259 | 93.28 280 | 97.64 196 | 98.30 197 | 97.99 84 | 99.99 5 | 97.61 285 | 94.35 155 | 71.57 460 | 99.45 140 | 96.23 38 | 95.34 425 | 96.91 199 | 85.14 362 | 99.59 149 |
|
| AUN-MVS | | | 93.28 289 | 92.60 294 | 95.34 294 | 98.29 198 | 90.09 365 | 99.31 283 | 98.56 112 | 91.80 279 | 96.35 230 | 98.00 286 | 89.38 205 | 98.28 293 | 92.46 291 | 69.22 451 | 97.64 300 |
|
| FMVSNet3 | | | 92.69 305 | 91.58 315 | 95.99 270 | 98.29 198 | 97.42 115 | 99.26 292 | 97.62 282 | 89.80 338 | 89.68 331 | 95.32 382 | 81.62 317 | 96.27 401 | 87.01 375 | 85.65 356 | 94.29 346 |
|
| PMMVS | | | 96.76 156 | 96.76 140 | 96.76 247 | 98.28 200 | 92.10 314 | 99.91 108 | 97.98 242 | 94.12 166 | 99.53 72 | 99.39 148 | 86.93 245 | 98.73 243 | 96.95 197 | 97.73 193 | 99.45 186 |
|
| hse-mvs2 | | | 94.38 258 | 94.08 249 | 95.31 296 | 98.27 201 | 90.02 366 | 99.29 288 | 98.56 112 | 95.90 99 | 98.77 127 | 98.00 286 | 90.89 184 | 98.26 297 | 97.80 164 | 69.20 452 | 97.64 300 |
|
| PVSNet_0 | | 88.03 19 | 91.80 325 | 90.27 339 | 96.38 262 | 98.27 201 | 90.46 357 | 99.94 90 | 99.61 13 | 93.99 174 | 86.26 397 | 97.39 305 | 71.13 407 | 99.89 117 | 98.77 105 | 67.05 459 | 98.79 262 |
|
| UA-Net | | | 96.54 171 | 95.96 179 | 98.27 149 | 98.23 203 | 95.71 192 | 98.00 400 | 98.45 142 | 93.72 189 | 98.41 150 | 99.27 162 | 88.71 219 | 99.66 170 | 91.19 312 | 97.69 194 | 99.44 189 |
|
| test_cas_vis1_n_1920 | | | 96.59 168 | 96.23 163 | 97.65 195 | 98.22 204 | 94.23 258 | 99.99 5 | 97.25 334 | 97.77 29 | 99.58 68 | 99.08 184 | 77.10 358 | 99.97 63 | 97.64 172 | 99.45 127 | 98.74 265 |
|
| FE-MVS | | | 95.70 212 | 95.01 222 | 97.79 182 | 98.21 205 | 94.57 242 | 95.03 448 | 98.69 81 | 88.90 354 | 97.50 186 | 96.19 344 | 92.60 146 | 99.49 184 | 89.99 337 | 97.94 191 | 99.31 212 |
|
| GG-mvs-BLEND | | | | | 98.54 127 | 98.21 205 | 98.01 83 | 93.87 453 | 98.52 127 | | 97.92 170 | 97.92 291 | 99.02 3 | 97.94 317 | 98.17 142 | 99.58 109 | 99.67 129 |
|
| mvs_anonymous | | | 95.65 214 | 95.03 221 | 97.53 209 | 98.19 207 | 95.74 190 | 99.33 280 | 97.49 300 | 90.87 307 | 90.47 318 | 97.10 312 | 88.23 222 | 97.16 349 | 95.92 219 | 97.66 197 | 99.68 127 |
|
| MVS_Test | | | 96.46 174 | 95.74 192 | 98.61 116 | 98.18 208 | 97.23 122 | 99.31 283 | 97.15 349 | 91.07 303 | 98.84 121 | 97.05 316 | 88.17 223 | 98.97 216 | 94.39 252 | 97.50 199 | 99.61 146 |
|
| BH-RMVSNet | | | 95.18 227 | 94.31 242 | 97.80 180 | 98.17 209 | 95.23 221 | 99.76 180 | 97.53 295 | 92.52 249 | 94.27 275 | 99.25 168 | 76.84 365 | 98.80 233 | 90.89 321 | 99.54 111 | 99.35 203 |
|
| dongtai | | | 91.55 331 | 91.13 324 | 92.82 380 | 98.16 210 | 86.35 409 | 99.47 259 | 98.51 130 | 83.24 424 | 85.07 407 | 97.56 299 | 90.33 193 | 94.94 431 | 76.09 444 | 91.73 306 | 97.18 311 |
|
| RPSCF | | | 91.80 325 | 92.79 290 | 88.83 424 | 98.15 211 | 69.87 464 | 98.11 396 | 96.60 407 | 83.93 419 | 94.33 273 | 99.27 162 | 79.60 341 | 99.46 188 | 91.99 301 | 93.16 303 | 97.18 311 |
|
| ETV-MVS | | | 97.92 84 | 97.80 88 | 98.25 150 | 98.14 212 | 96.48 157 | 99.98 21 | 97.63 279 | 95.61 110 | 99.29 95 | 99.46 139 | 92.55 148 | 98.82 229 | 99.02 88 | 98.54 169 | 99.46 181 |
|
| IS-MVSNet | | | 96.29 187 | 95.90 186 | 97.45 215 | 98.13 213 | 94.80 236 | 99.08 307 | 97.61 285 | 92.02 271 | 95.54 254 | 98.96 202 | 90.64 187 | 98.08 306 | 93.73 274 | 97.41 203 | 99.47 179 |
|
| test_fmvsmconf_n | | | 98.43 51 | 98.32 47 | 98.78 102 | 98.12 214 | 96.41 160 | 99.99 5 | 98.83 66 | 98.22 7 | 99.67 51 | 99.64 118 | 91.11 177 | 99.94 93 | 99.67 52 | 99.62 100 | 99.98 56 |
|
| fmvsm_s_conf0.1_n_2 | | | 97.25 128 | 96.85 135 | 98.43 139 | 98.08 215 | 98.08 78 | 99.92 100 | 97.76 268 | 98.05 20 | 99.65 53 | 99.58 127 | 80.88 326 | 99.93 103 | 99.59 56 | 98.17 180 | 97.29 309 |
|
| ab-mvs | | | 94.69 244 | 93.42 271 | 98.51 132 | 98.07 216 | 96.26 167 | 96.49 432 | 98.68 83 | 90.31 328 | 94.54 265 | 97.00 318 | 76.30 373 | 99.71 159 | 95.98 218 | 93.38 301 | 99.56 158 |
|
| XVG-OURS-SEG-HR | | | 94.79 239 | 94.70 234 | 95.08 301 | 98.05 217 | 89.19 377 | 99.08 307 | 97.54 293 | 93.66 190 | 94.87 263 | 99.58 127 | 78.78 349 | 99.79 144 | 97.31 180 | 93.40 300 | 96.25 318 |
|
| EIA-MVS | | | 97.53 114 | 97.46 104 | 97.76 188 | 98.04 218 | 94.84 233 | 99.98 21 | 97.61 285 | 94.41 153 | 97.90 171 | 99.59 124 | 92.40 154 | 98.87 224 | 98.04 151 | 99.13 146 | 99.59 149 |
|
| XVG-OURS | | | 94.82 236 | 94.74 233 | 95.06 302 | 98.00 219 | 89.19 377 | 99.08 307 | 97.55 291 | 94.10 167 | 94.71 264 | 99.62 122 | 80.51 332 | 99.74 155 | 96.04 217 | 93.06 305 | 96.25 318 |
|
| mvsmamba | | | 96.94 146 | 96.73 142 | 97.55 207 | 97.99 220 | 94.37 254 | 99.62 225 | 97.70 271 | 93.13 213 | 98.42 149 | 97.92 291 | 88.02 224 | 98.75 241 | 98.78 104 | 99.01 152 | 99.52 169 |
|
| dp | | | 95.05 230 | 94.43 237 | 96.91 240 | 97.99 220 | 92.73 299 | 96.29 437 | 97.98 242 | 89.70 339 | 95.93 241 | 94.67 408 | 93.83 110 | 98.45 270 | 86.91 378 | 96.53 235 | 99.54 163 |
|
| tpmrst | | | 96.27 189 | 95.98 175 | 97.13 232 | 97.96 222 | 93.15 287 | 96.34 435 | 98.17 218 | 92.07 267 | 98.71 133 | 95.12 392 | 93.91 105 | 98.73 243 | 94.91 240 | 96.62 233 | 99.50 175 |
|
| TR-MVS | | | 94.54 249 | 93.56 266 | 97.49 214 | 97.96 222 | 94.34 255 | 98.71 358 | 97.51 298 | 90.30 329 | 94.51 267 | 98.69 238 | 75.56 379 | 98.77 237 | 92.82 289 | 95.99 248 | 99.35 203 |
|
| Vis-MVSNet (Re-imp) | | | 96.32 184 | 95.98 175 | 97.35 227 | 97.93 224 | 94.82 235 | 99.47 259 | 98.15 226 | 91.83 276 | 95.09 261 | 99.11 182 | 91.37 171 | 97.47 333 | 93.47 278 | 97.43 200 | 99.74 118 |
|
| MDTV_nov1_ep13 | | | | 95.69 194 | | 97.90 225 | 94.15 260 | 95.98 443 | 98.44 147 | 93.12 214 | 97.98 168 | 95.74 357 | 95.10 60 | 98.58 260 | 90.02 336 | 96.92 229 | |
|
| Fast-Effi-MVS+ | | | 95.02 232 | 94.19 244 | 97.52 211 | 97.88 226 | 94.55 243 | 99.97 39 | 97.08 365 | 88.85 356 | 94.47 268 | 97.96 290 | 84.59 287 | 98.41 274 | 89.84 339 | 97.10 220 | 99.59 149 |
|
| ADS-MVSNet2 | | | 93.80 276 | 93.88 256 | 93.55 363 | 97.87 227 | 85.94 413 | 94.24 449 | 96.84 393 | 90.07 332 | 96.43 226 | 94.48 413 | 90.29 195 | 95.37 424 | 87.44 365 | 97.23 211 | 99.36 199 |
|
| ADS-MVSNet | | | 94.79 239 | 94.02 251 | 97.11 234 | 97.87 227 | 93.79 269 | 94.24 449 | 98.16 223 | 90.07 332 | 96.43 226 | 94.48 413 | 90.29 195 | 98.19 300 | 87.44 365 | 97.23 211 | 99.36 199 |
|
| Effi-MVS+ | | | 96.30 186 | 95.69 194 | 98.16 154 | 97.85 229 | 96.26 167 | 97.41 411 | 97.21 341 | 90.37 325 | 98.65 136 | 98.58 253 | 86.61 251 | 98.70 249 | 97.11 188 | 97.37 205 | 99.52 169 |
|
| PatchmatchNet |  | | 95.94 199 | 95.45 201 | 97.39 222 | 97.83 230 | 94.41 250 | 96.05 441 | 98.40 176 | 92.86 225 | 97.09 200 | 95.28 387 | 94.21 97 | 98.07 308 | 89.26 345 | 98.11 185 | 99.70 124 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| cascas | | | 94.64 247 | 93.61 261 | 97.74 190 | 97.82 231 | 96.26 167 | 99.96 53 | 97.78 264 | 85.76 400 | 94.00 278 | 97.54 300 | 76.95 364 | 99.21 197 | 97.23 185 | 95.43 271 | 97.76 297 |
|
| 1112_ss | | | 96.01 197 | 95.20 213 | 98.42 141 | 97.80 232 | 96.41 160 | 99.65 218 | 96.66 404 | 92.71 235 | 92.88 292 | 99.40 146 | 92.16 159 | 99.30 192 | 91.92 303 | 93.66 296 | 99.55 159 |
|
| E3new | | | 96.75 158 | 96.43 156 | 97.71 191 | 97.79 233 | 94.83 234 | 99.80 165 | 97.33 318 | 93.52 195 | 97.49 187 | 99.31 156 | 87.73 227 | 98.83 227 | 97.52 175 | 97.40 204 | 99.48 178 |
|
| Test_1112_low_res | | | 95.72 208 | 94.83 227 | 98.42 141 | 97.79 233 | 96.41 160 | 99.65 218 | 96.65 405 | 92.70 236 | 92.86 293 | 96.13 348 | 92.15 160 | 99.30 192 | 91.88 304 | 93.64 297 | 99.55 159 |
|
| Effi-MVS+-dtu | | | 94.53 251 | 95.30 209 | 92.22 388 | 97.77 235 | 82.54 437 | 99.59 234 | 97.06 369 | 94.92 127 | 95.29 258 | 95.37 380 | 85.81 262 | 97.89 318 | 94.80 243 | 97.07 221 | 96.23 320 |
|
| tpm cat1 | | | 93.51 285 | 92.52 300 | 96.47 255 | 97.77 235 | 91.47 338 | 96.13 439 | 98.06 233 | 80.98 438 | 92.91 291 | 93.78 422 | 89.66 200 | 98.87 224 | 87.03 374 | 96.39 240 | 99.09 238 |
|
| FA-MVS(test-final) | | | 95.86 202 | 95.09 218 | 98.15 157 | 97.74 237 | 95.62 198 | 96.31 436 | 98.17 218 | 91.42 292 | 96.26 231 | 96.13 348 | 90.56 189 | 99.47 187 | 92.18 295 | 97.07 221 | 99.35 203 |
|
| xiu_mvs_v1_base_debu | | | 97.43 117 | 97.06 123 | 98.55 123 | 97.74 237 | 98.14 73 | 99.31 283 | 97.86 256 | 96.43 81 | 99.62 60 | 99.69 104 | 85.56 269 | 99.68 164 | 99.05 81 | 98.31 175 | 97.83 293 |
|
| xiu_mvs_v1_base | | | 97.43 117 | 97.06 123 | 98.55 123 | 97.74 237 | 98.14 73 | 99.31 283 | 97.86 256 | 96.43 81 | 99.62 60 | 99.69 104 | 85.56 269 | 99.68 164 | 99.05 81 | 98.31 175 | 97.83 293 |
|
| xiu_mvs_v1_base_debi | | | 97.43 117 | 97.06 123 | 98.55 123 | 97.74 237 | 98.14 73 | 99.31 283 | 97.86 256 | 96.43 81 | 99.62 60 | 99.69 104 | 85.56 269 | 99.68 164 | 99.05 81 | 98.31 175 | 97.83 293 |
|
| EPP-MVSNet | | | 96.69 163 | 96.60 148 | 96.96 239 | 97.74 237 | 93.05 290 | 99.37 275 | 98.56 112 | 88.75 358 | 95.83 245 | 99.01 193 | 96.01 39 | 98.56 262 | 96.92 198 | 97.20 213 | 99.25 223 |
|
| gg-mvs-nofinetune | | | 93.51 285 | 91.86 312 | 98.47 134 | 97.72 242 | 97.96 88 | 92.62 459 | 98.51 130 | 74.70 457 | 97.33 193 | 69.59 474 | 98.91 4 | 97.79 321 | 97.77 169 | 99.56 110 | 99.67 129 |
|
| IB-MVS | | 92.85 6 | 94.99 233 | 93.94 254 | 98.16 154 | 97.72 242 | 95.69 195 | 99.99 5 | 98.81 67 | 94.28 161 | 92.70 294 | 96.90 320 | 95.08 61 | 99.17 203 | 96.07 216 | 73.88 438 | 99.60 148 |
| Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
| thisisatest0515 | | | 97.41 122 | 97.02 128 | 98.59 120 | 97.71 244 | 97.52 108 | 99.97 39 | 98.54 122 | 91.83 276 | 97.45 188 | 99.04 190 | 97.50 9 | 99.10 208 | 94.75 245 | 96.37 241 | 99.16 230 |
|
| VortexMVS | | | 94.11 265 | 93.50 268 | 95.94 273 | 97.70 245 | 96.61 152 | 99.35 278 | 97.18 344 | 93.52 195 | 89.57 338 | 95.74 357 | 87.55 232 | 96.97 366 | 95.76 224 | 85.13 363 | 94.23 351 |
|
| viewdifsd2359ckpt09 | | | 96.21 191 | 95.77 190 | 97.53 209 | 97.69 246 | 94.50 246 | 99.78 169 | 97.23 339 | 92.88 224 | 96.58 219 | 99.26 166 | 84.85 281 | 98.66 256 | 96.61 206 | 97.02 226 | 99.43 190 |
|
| Syy-MVS | | | 90.00 365 | 90.63 331 | 88.11 432 | 97.68 247 | 74.66 460 | 99.71 201 | 98.35 189 | 90.79 314 | 92.10 300 | 98.67 239 | 79.10 347 | 93.09 451 | 63.35 467 | 95.95 252 | 96.59 316 |
|
| myMVS_eth3d | | | 94.46 256 | 94.76 232 | 93.55 363 | 97.68 247 | 90.97 342 | 99.71 201 | 98.35 189 | 90.79 314 | 92.10 300 | 98.67 239 | 92.46 153 | 93.09 451 | 87.13 371 | 95.95 252 | 96.59 316 |
|
| test_fmvs1_n | | | 94.25 264 | 94.36 239 | 93.92 350 | 97.68 247 | 83.70 426 | 99.90 114 | 96.57 408 | 97.40 40 | 99.67 51 | 98.88 214 | 61.82 443 | 99.92 109 | 98.23 140 | 99.13 146 | 98.14 286 |
|
| fmvsm_s_conf0.5_n_6 | | | 98.27 63 | 97.96 75 | 99.23 57 | 97.66 250 | 98.11 77 | 99.98 21 | 98.64 90 | 97.85 27 | 99.87 13 | 99.72 94 | 88.86 216 | 99.93 103 | 99.64 54 | 99.36 135 | 99.63 141 |
|
| RRT-MVS | | | 96.24 190 | 95.68 196 | 97.94 171 | 97.65 251 | 94.92 231 | 99.27 291 | 97.10 361 | 92.79 231 | 97.43 189 | 97.99 288 | 81.85 312 | 99.37 191 | 98.46 125 | 98.57 166 | 99.53 167 |
|
| diffmvs |  | | 97.00 143 | 96.64 146 | 98.09 161 | 97.64 252 | 96.17 176 | 99.81 161 | 97.19 342 | 94.67 139 | 98.95 116 | 99.28 159 | 86.43 252 | 98.76 239 | 98.37 130 | 97.42 202 | 99.33 206 |
| 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 | | | 96.59 168 | 96.23 163 | 97.66 194 | 97.63 253 | 94.70 239 | 99.77 174 | 97.33 318 | 93.41 200 | 97.34 192 | 99.17 177 | 86.72 246 | 98.83 227 | 97.40 178 | 97.32 208 | 99.46 181 |
|
| viewdifsd2359ckpt13 | | | 96.19 192 | 95.77 190 | 97.45 215 | 97.62 254 | 94.40 252 | 99.70 208 | 97.23 339 | 92.76 233 | 96.63 216 | 99.05 189 | 84.96 280 | 98.64 257 | 96.65 205 | 97.35 206 | 99.31 212 |
|
| Vis-MVSNet |  | | 95.72 208 | 95.15 216 | 97.45 215 | 97.62 254 | 94.28 256 | 99.28 289 | 98.24 209 | 94.27 163 | 96.84 211 | 98.94 209 | 79.39 342 | 98.76 239 | 93.25 280 | 98.49 170 | 99.30 215 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| thisisatest0530 | | | 97.10 136 | 96.72 143 | 98.22 151 | 97.60 256 | 96.70 145 | 99.92 100 | 98.54 122 | 91.11 301 | 97.07 202 | 98.97 200 | 97.47 12 | 99.03 211 | 93.73 274 | 96.09 246 | 98.92 254 |
|
| GDP-MVS | | | 97.88 86 | 97.59 100 | 98.75 105 | 97.59 257 | 97.81 95 | 99.95 72 | 97.37 313 | 94.44 149 | 99.08 107 | 99.58 127 | 97.13 25 | 99.08 209 | 94.99 235 | 98.17 180 | 99.37 197 |
|
| miper_ehance_all_eth | | | 93.16 293 | 92.60 294 | 94.82 312 | 97.57 258 | 93.56 277 | 99.50 253 | 97.07 368 | 88.75 358 | 88.85 355 | 95.52 369 | 90.97 180 | 96.74 380 | 90.77 323 | 84.45 368 | 94.17 356 |
|
| guyue | | | 97.15 134 | 96.82 137 | 98.15 157 | 97.56 259 | 96.25 171 | 99.71 201 | 97.84 259 | 95.75 106 | 98.13 165 | 98.65 242 | 87.58 231 | 98.82 229 | 98.29 136 | 97.91 192 | 99.36 199 |
|
| viewmanbaseed2359cas | | | 96.45 175 | 96.07 169 | 97.59 205 | 97.55 260 | 94.59 241 | 99.70 208 | 97.33 318 | 93.62 192 | 97.00 206 | 99.32 153 | 85.57 268 | 98.71 246 | 97.26 184 | 97.33 207 | 99.47 179 |
|
| testing3 | | | 93.92 270 | 94.23 243 | 92.99 377 | 97.54 261 | 90.23 361 | 99.99 5 | 99.16 33 | 90.57 319 | 91.33 308 | 98.63 246 | 92.99 132 | 92.52 456 | 82.46 408 | 95.39 272 | 96.22 321 |
|
| SSM_0404 | | | 95.75 207 | 95.16 215 | 97.50 213 | 97.53 262 | 95.39 209 | 99.11 303 | 97.25 334 | 90.81 310 | 95.27 259 | 98.83 228 | 84.74 283 | 98.67 253 | 95.24 230 | 97.69 194 | 98.45 275 |
|
| LCM-MVSNet-Re | | | 92.31 314 | 92.60 294 | 91.43 397 | 97.53 262 | 79.27 454 | 99.02 321 | 91.83 469 | 92.07 267 | 80.31 431 | 94.38 416 | 83.50 298 | 95.48 421 | 97.22 186 | 97.58 198 | 99.54 163 |
|
| GBi-Net | | | 90.88 342 | 89.82 348 | 94.08 342 | 97.53 262 | 91.97 315 | 98.43 377 | 96.95 382 | 87.05 383 | 89.68 331 | 94.72 404 | 71.34 404 | 96.11 407 | 87.01 375 | 85.65 356 | 94.17 356 |
|
| test1 | | | 90.88 342 | 89.82 348 | 94.08 342 | 97.53 262 | 91.97 315 | 98.43 377 | 96.95 382 | 87.05 383 | 89.68 331 | 94.72 404 | 71.34 404 | 96.11 407 | 87.01 375 | 85.65 356 | 94.17 356 |
|
| FMVSNet2 | | | 91.02 339 | 89.56 353 | 95.41 292 | 97.53 262 | 95.74 190 | 98.98 324 | 97.41 308 | 87.05 383 | 88.43 365 | 95.00 398 | 71.34 404 | 96.24 403 | 85.12 390 | 85.21 361 | 94.25 349 |
|
| tttt0517 | | | 96.85 150 | 96.49 152 | 97.92 172 | 97.48 267 | 95.89 184 | 99.85 144 | 98.54 122 | 90.72 318 | 96.63 216 | 98.93 212 | 97.47 12 | 99.02 212 | 93.03 287 | 95.76 258 | 98.85 258 |
|
| BP-MVS1 | | | 98.33 59 | 98.18 56 | 98.81 100 | 97.44 268 | 97.98 85 | 99.96 53 | 98.17 218 | 94.88 129 | 98.77 127 | 99.59 124 | 97.59 7 | 99.08 209 | 98.24 139 | 98.93 154 | 99.36 199 |
|
| casdiffmvs_mvg |  | | 96.43 176 | 95.94 183 | 97.89 176 | 97.44 268 | 95.47 202 | 99.86 141 | 97.29 329 | 93.35 201 | 96.03 238 | 99.19 175 | 85.39 273 | 98.72 245 | 97.89 161 | 97.04 223 | 99.49 177 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| E2 | | | 96.36 181 | 95.95 181 | 97.60 202 | 97.41 270 | 94.52 244 | 99.71 201 | 97.33 318 | 93.20 207 | 97.02 203 | 99.07 186 | 85.37 274 | 98.82 229 | 97.27 181 | 97.14 217 | 99.46 181 |
|
| EC-MVSNet | | | 97.38 124 | 97.24 117 | 97.80 180 | 97.41 270 | 95.64 197 | 99.99 5 | 97.06 369 | 94.59 140 | 99.63 57 | 99.32 153 | 89.20 211 | 98.14 302 | 98.76 106 | 99.23 142 | 99.62 142 |
|
| viewdifsd2359ckpt07 | | | 95.83 205 | 95.42 203 | 97.07 235 | 97.40 272 | 93.04 291 | 99.60 232 | 97.24 337 | 92.39 255 | 96.09 237 | 99.14 181 | 83.07 303 | 98.93 220 | 97.02 191 | 96.87 230 | 99.23 226 |
|
| c3_l | | | 92.53 309 | 91.87 311 | 94.52 324 | 97.40 272 | 92.99 293 | 99.40 267 | 96.93 387 | 87.86 373 | 88.69 358 | 95.44 374 | 89.95 198 | 96.44 393 | 90.45 329 | 80.69 402 | 94.14 365 |
|
| viewmambaseed2359dif | | | 95.92 201 | 95.55 200 | 97.04 236 | 97.38 274 | 93.41 282 | 99.78 169 | 96.97 380 | 91.14 300 | 96.58 219 | 99.27 162 | 84.85 281 | 98.75 241 | 96.87 200 | 97.12 219 | 98.97 249 |
|
| fmvsm_s_conf0.1_n | | | 97.30 125 | 97.21 119 | 97.60 202 | 97.38 274 | 94.40 252 | 99.90 114 | 98.64 90 | 96.47 80 | 99.51 76 | 99.65 117 | 84.99 279 | 99.93 103 | 99.22 75 | 99.09 149 | 98.46 274 |
|
| E3 | | | 96.36 181 | 95.95 181 | 97.60 202 | 97.37 276 | 94.52 244 | 99.71 201 | 97.33 318 | 93.18 209 | 97.02 203 | 99.07 186 | 85.45 272 | 98.82 229 | 97.27 181 | 97.14 217 | 99.46 181 |
|
| CDS-MVSNet | | | 96.34 183 | 96.07 169 | 97.13 232 | 97.37 276 | 94.96 229 | 99.53 248 | 97.91 251 | 91.55 284 | 95.37 257 | 98.32 273 | 95.05 63 | 97.13 352 | 93.80 270 | 95.75 259 | 99.30 215 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| TESTMET0.1,1 | | | 96.74 160 | 96.26 162 | 98.16 154 | 97.36 278 | 96.48 157 | 99.96 53 | 98.29 202 | 91.93 272 | 95.77 246 | 98.07 284 | 95.54 49 | 98.29 291 | 90.55 327 | 98.89 155 | 99.70 124 |
|
| miper_lstm_enhance | | | 91.81 322 | 91.39 321 | 93.06 376 | 97.34 279 | 89.18 379 | 99.38 273 | 96.79 398 | 86.70 390 | 87.47 379 | 95.22 389 | 90.00 197 | 95.86 416 | 88.26 356 | 81.37 391 | 94.15 362 |
|
| baseline | | | 96.43 176 | 95.98 175 | 97.76 188 | 97.34 279 | 95.17 225 | 99.51 251 | 97.17 346 | 93.92 179 | 96.90 209 | 99.28 159 | 85.37 274 | 98.64 257 | 97.50 176 | 96.86 232 | 99.46 181 |
|
| cl____ | | | 92.31 314 | 91.58 315 | 94.52 324 | 97.33 281 | 92.77 295 | 99.57 239 | 96.78 399 | 86.97 387 | 87.56 377 | 95.51 370 | 89.43 204 | 96.62 385 | 88.60 350 | 82.44 383 | 94.16 361 |
|
| SD_0403 | | | 92.63 308 | 93.38 275 | 90.40 411 | 97.32 282 | 77.91 456 | 97.75 407 | 98.03 238 | 91.89 273 | 90.83 314 | 98.29 277 | 82.00 309 | 93.79 444 | 88.51 354 | 95.75 259 | 99.52 169 |
|
| DIV-MVS_self_test | | | 92.32 313 | 91.60 314 | 94.47 328 | 97.31 283 | 92.74 297 | 99.58 236 | 96.75 400 | 86.99 386 | 87.64 375 | 95.54 367 | 89.55 203 | 96.50 390 | 88.58 351 | 82.44 383 | 94.17 356 |
|
| casdiffmvs |  | | 96.42 178 | 95.97 178 | 97.77 186 | 97.30 284 | 94.98 228 | 99.84 149 | 97.09 364 | 93.75 188 | 96.58 219 | 99.26 166 | 85.07 277 | 98.78 236 | 97.77 169 | 97.04 223 | 99.54 163 |
| 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 | | | 94.36 261 | 93.48 269 | 96.99 238 | 97.29 285 | 93.54 278 | 99.96 53 | 96.72 402 | 88.35 367 | 93.43 282 | 98.94 209 | 82.05 308 | 98.05 309 | 88.12 360 | 96.48 238 | 99.37 197 |
|
| eth_miper_zixun_eth | | | 92.41 312 | 91.93 309 | 93.84 354 | 97.28 286 | 90.68 351 | 98.83 347 | 96.97 380 | 88.57 363 | 89.19 350 | 95.73 360 | 89.24 210 | 96.69 383 | 89.97 338 | 81.55 389 | 94.15 362 |
|
| MVSFormer | | | 96.94 146 | 96.60 148 | 97.95 168 | 97.28 286 | 97.70 101 | 99.55 245 | 97.27 331 | 91.17 297 | 99.43 82 | 99.54 133 | 90.92 181 | 96.89 371 | 94.67 248 | 99.62 100 | 99.25 223 |
|
| lupinMVS | | | 97.85 90 | 97.60 98 | 98.62 115 | 97.28 286 | 97.70 101 | 99.99 5 | 97.55 291 | 95.50 115 | 99.43 82 | 99.67 113 | 90.92 181 | 98.71 246 | 98.40 127 | 99.62 100 | 99.45 186 |
|
| diffmvs_AUTHOR | | | 96.75 158 | 96.41 158 | 97.79 182 | 97.20 289 | 95.46 203 | 99.69 211 | 97.15 349 | 94.46 145 | 98.78 125 | 99.21 173 | 85.64 266 | 98.77 237 | 98.27 137 | 97.31 209 | 99.13 234 |
|
| mamba_0408 | | | 94.98 234 | 94.09 247 | 97.64 196 | 97.14 290 | 95.31 214 | 93.48 456 | 97.08 365 | 90.48 321 | 94.40 269 | 98.62 247 | 84.49 288 | 98.67 253 | 93.99 261 | 97.18 214 | 98.93 251 |
|
| SSM_04072 | | | 94.77 241 | 94.09 247 | 96.82 244 | 97.14 290 | 95.31 214 | 93.48 456 | 97.08 365 | 90.48 321 | 94.40 269 | 98.62 247 | 84.49 288 | 96.21 404 | 93.99 261 | 97.18 214 | 98.93 251 |
|
| SSM_0407 | | | 95.62 215 | 94.95 224 | 97.61 201 | 97.14 290 | 95.31 214 | 99.00 322 | 97.25 334 | 90.81 310 | 94.40 269 | 98.83 228 | 84.74 283 | 98.58 260 | 95.24 230 | 97.18 214 | 98.93 251 |
|
| SCA | | | 94.69 244 | 93.81 258 | 97.33 228 | 97.10 293 | 94.44 247 | 98.86 344 | 98.32 196 | 93.30 204 | 96.17 236 | 95.59 365 | 76.48 371 | 97.95 315 | 91.06 315 | 97.43 200 | 99.59 149 |
|
| viewmacassd2359aftdt | | | 95.93 200 | 95.45 201 | 97.36 225 | 97.09 294 | 94.12 262 | 99.57 239 | 97.26 333 | 93.05 218 | 96.50 223 | 99.17 177 | 82.76 304 | 98.68 251 | 96.61 206 | 97.04 223 | 99.28 219 |
|
| KinetiMVS | | | 96.10 193 | 95.29 210 | 98.53 129 | 97.08 295 | 97.12 128 | 99.56 242 | 98.12 229 | 94.78 132 | 98.44 147 | 98.94 209 | 80.30 336 | 99.39 190 | 91.56 308 | 98.79 161 | 99.06 242 |
|
| TAMVS | | | 95.85 203 | 95.58 198 | 96.65 252 | 97.07 296 | 93.50 279 | 99.17 299 | 97.82 261 | 91.39 294 | 95.02 262 | 98.01 285 | 92.20 158 | 97.30 342 | 93.75 273 | 95.83 256 | 99.14 233 |
|
| Fast-Effi-MVS+-dtu | | | 93.72 280 | 93.86 257 | 93.29 368 | 97.06 297 | 86.16 410 | 99.80 165 | 96.83 394 | 92.66 239 | 92.58 295 | 97.83 296 | 81.39 318 | 97.67 326 | 89.75 340 | 96.87 230 | 96.05 323 |
|
| CostFormer | | | 96.10 193 | 95.88 187 | 96.78 246 | 97.03 298 | 92.55 305 | 97.08 421 | 97.83 260 | 90.04 334 | 98.72 132 | 94.89 402 | 95.01 65 | 98.29 291 | 96.54 209 | 95.77 257 | 99.50 175 |
|
| test_fmvsmvis_n_1920 | | | 97.67 109 | 97.59 100 | 97.91 174 | 97.02 299 | 95.34 212 | 99.95 72 | 98.45 142 | 97.87 26 | 97.02 203 | 99.59 124 | 89.64 201 | 99.98 50 | 99.41 68 | 99.34 137 | 98.42 277 |
|
| test-LLR | | | 96.47 173 | 96.04 171 | 97.78 184 | 97.02 299 | 95.44 204 | 99.96 53 | 98.21 213 | 94.07 169 | 95.55 252 | 96.38 337 | 93.90 106 | 98.27 295 | 90.42 330 | 98.83 159 | 99.64 135 |
|
| test-mter | | | 96.39 179 | 95.93 184 | 97.78 184 | 97.02 299 | 95.44 204 | 99.96 53 | 98.21 213 | 91.81 278 | 95.55 252 | 96.38 337 | 95.17 58 | 98.27 295 | 90.42 330 | 98.83 159 | 99.64 135 |
|
| icg_test_0407_2 | | | 95.04 231 | 94.78 231 | 95.84 278 | 96.97 302 | 91.64 330 | 98.63 366 | 97.12 354 | 92.33 258 | 95.60 250 | 98.88 214 | 85.65 264 | 96.56 388 | 92.12 296 | 95.70 262 | 99.32 208 |
|
| IMVS_0407 | | | 95.21 226 | 94.80 230 | 96.46 257 | 96.97 302 | 91.64 330 | 98.81 349 | 97.12 354 | 92.33 258 | 95.60 250 | 98.88 214 | 85.65 264 | 98.42 272 | 92.12 296 | 95.70 262 | 99.32 208 |
|
| IMVS_0404 | | | 93.83 272 | 93.17 282 | 95.80 280 | 96.97 302 | 91.64 330 | 97.78 406 | 97.12 354 | 92.33 258 | 90.87 313 | 98.88 214 | 76.78 366 | 96.43 394 | 92.12 296 | 95.70 262 | 99.32 208 |
|
| IMVS_0403 | | | 95.25 224 | 94.81 229 | 96.58 254 | 96.97 302 | 91.64 330 | 98.97 329 | 97.12 354 | 92.33 258 | 95.43 255 | 98.88 214 | 85.78 263 | 98.79 234 | 92.12 296 | 95.70 262 | 99.32 208 |
|
| gm-plane-assit | | | | | | 96.97 302 | 93.76 271 | | | 91.47 288 | | 98.96 202 | | 98.79 234 | 94.92 238 | | |
|
| WB-MVSnew | | | 92.90 299 | 92.77 291 | 93.26 370 | 96.95 307 | 93.63 275 | 99.71 201 | 98.16 223 | 91.49 285 | 94.28 274 | 98.14 281 | 81.33 320 | 96.48 391 | 79.47 425 | 95.46 269 | 89.68 452 |
|
| QAPM | | | 95.40 220 | 94.17 245 | 99.10 78 | 96.92 308 | 97.71 99 | 99.40 267 | 98.68 83 | 89.31 342 | 88.94 354 | 98.89 213 | 82.48 306 | 99.96 75 | 93.12 286 | 99.83 81 | 99.62 142 |
|
| KD-MVS_2432*1600 | | | 88.00 387 | 86.10 391 | 93.70 359 | 96.91 309 | 94.04 263 | 97.17 418 | 97.12 354 | 84.93 411 | 81.96 421 | 92.41 435 | 92.48 151 | 94.51 437 | 79.23 426 | 52.68 473 | 92.56 421 |
|
| miper_refine_blended | | | 88.00 387 | 86.10 391 | 93.70 359 | 96.91 309 | 94.04 263 | 97.17 418 | 97.12 354 | 84.93 411 | 81.96 421 | 92.41 435 | 92.48 151 | 94.51 437 | 79.23 426 | 52.68 473 | 92.56 421 |
|
| tpm2 | | | 95.47 218 | 95.18 214 | 96.35 263 | 96.91 309 | 91.70 328 | 96.96 424 | 97.93 247 | 88.04 371 | 98.44 147 | 95.40 376 | 93.32 121 | 97.97 312 | 94.00 260 | 95.61 267 | 99.38 195 |
|
| FMVSNet5 | | | 88.32 383 | 87.47 385 | 90.88 400 | 96.90 312 | 88.39 393 | 97.28 414 | 95.68 431 | 82.60 431 | 84.67 409 | 92.40 437 | 79.83 339 | 91.16 461 | 76.39 443 | 81.51 390 | 93.09 412 |
|
| 3Dnovator+ | | 91.53 11 | 96.31 185 | 95.24 211 | 99.52 32 | 96.88 313 | 98.64 58 | 99.72 198 | 98.24 209 | 95.27 120 | 88.42 367 | 98.98 198 | 82.76 304 | 99.94 93 | 97.10 189 | 99.83 81 | 99.96 74 |
|
| Patchmatch-test | | | 92.65 307 | 91.50 318 | 96.10 269 | 96.85 314 | 90.49 356 | 91.50 464 | 97.19 342 | 82.76 430 | 90.23 319 | 95.59 365 | 95.02 64 | 98.00 311 | 77.41 437 | 96.98 228 | 99.82 106 |
|
| MVS | | | 96.60 167 | 95.56 199 | 99.72 14 | 96.85 314 | 99.22 21 | 98.31 383 | 98.94 44 | 91.57 283 | 90.90 312 | 99.61 123 | 86.66 250 | 99.96 75 | 97.36 179 | 99.88 77 | 99.99 24 |
|
| 3Dnovator | | 91.47 12 | 96.28 188 | 95.34 207 | 99.08 81 | 96.82 316 | 97.47 113 | 99.45 264 | 98.81 67 | 95.52 114 | 89.39 341 | 99.00 195 | 81.97 310 | 99.95 84 | 97.27 181 | 99.83 81 | 99.84 103 |
|
| EI-MVSNet | | | 93.73 279 | 93.40 274 | 94.74 313 | 96.80 317 | 92.69 300 | 99.06 312 | 97.67 274 | 88.96 351 | 91.39 306 | 99.02 191 | 88.75 218 | 97.30 342 | 91.07 314 | 87.85 340 | 94.22 352 |
|
| CVMVSNet | | | 94.68 246 | 94.94 225 | 93.89 353 | 96.80 317 | 86.92 407 | 99.06 312 | 98.98 41 | 94.45 146 | 94.23 276 | 99.02 191 | 85.60 267 | 95.31 426 | 90.91 320 | 95.39 272 | 99.43 190 |
|
| IterMVS-LS | | | 92.69 305 | 92.11 305 | 94.43 332 | 96.80 317 | 92.74 297 | 99.45 264 | 96.89 390 | 88.98 349 | 89.65 334 | 95.38 379 | 88.77 217 | 96.34 398 | 90.98 318 | 82.04 386 | 94.22 352 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| AstraMVS | | | 96.57 170 | 96.46 155 | 96.91 240 | 96.79 320 | 92.50 306 | 99.90 114 | 97.38 310 | 96.02 98 | 97.79 179 | 99.32 153 | 86.36 254 | 98.99 213 | 98.26 138 | 96.33 242 | 99.23 226 |
|
| IterMVS | | | 90.91 341 | 90.17 343 | 93.12 373 | 96.78 321 | 90.42 359 | 98.89 338 | 97.05 372 | 89.03 346 | 86.49 392 | 95.42 375 | 76.59 369 | 95.02 428 | 87.22 370 | 84.09 371 | 93.93 383 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| 1314 | | | 96.84 151 | 95.96 179 | 99.48 39 | 96.74 322 | 98.52 62 | 98.31 383 | 98.86 59 | 95.82 103 | 89.91 325 | 98.98 198 | 87.49 234 | 99.96 75 | 97.80 164 | 99.73 91 | 99.96 74 |
|
| IterMVS-SCA-FT | | | 90.85 344 | 90.16 344 | 92.93 378 | 96.72 323 | 89.96 368 | 98.89 338 | 96.99 376 | 88.95 352 | 86.63 389 | 95.67 361 | 76.48 371 | 95.00 429 | 87.04 373 | 84.04 374 | 93.84 390 |
|
| MVS-HIRNet | | | 86.22 394 | 83.19 407 | 95.31 296 | 96.71 324 | 90.29 360 | 92.12 461 | 97.33 318 | 62.85 468 | 86.82 386 | 70.37 473 | 69.37 412 | 97.49 332 | 75.12 446 | 97.99 190 | 98.15 284 |
|
| viewdifsd2359ckpt11 | | | 94.09 267 | 93.63 260 | 95.46 289 | 96.68 325 | 88.92 382 | 99.62 225 | 97.12 354 | 93.07 216 | 95.73 247 | 99.22 170 | 77.05 359 | 98.88 223 | 96.52 210 | 87.69 345 | 98.58 272 |
|
| viewmsd2359difaftdt | | | 94.09 267 | 93.64 259 | 95.46 289 | 96.68 325 | 88.92 382 | 99.62 225 | 97.13 353 | 93.07 216 | 95.73 247 | 99.22 170 | 77.05 359 | 98.89 222 | 96.52 210 | 87.70 344 | 98.58 272 |
|
| VDDNet | | | 93.12 294 | 91.91 310 | 96.76 247 | 96.67 327 | 92.65 303 | 98.69 361 | 98.21 213 | 82.81 429 | 97.75 181 | 99.28 159 | 61.57 444 | 99.48 185 | 98.09 148 | 94.09 291 | 98.15 284 |
|
| dmvs_re | | | 93.20 291 | 93.15 283 | 93.34 366 | 96.54 328 | 83.81 425 | 98.71 358 | 98.51 130 | 91.39 294 | 92.37 298 | 98.56 255 | 78.66 351 | 97.83 320 | 93.89 264 | 89.74 312 | 98.38 279 |
|
| Elysia | | | 94.50 253 | 93.38 275 | 97.85 178 | 96.49 329 | 96.70 145 | 98.98 324 | 97.78 264 | 90.81 310 | 96.19 234 | 98.55 257 | 73.63 395 | 98.98 214 | 89.41 341 | 98.56 167 | 97.88 291 |
|
| StellarMVS | | | 94.50 253 | 93.38 275 | 97.85 178 | 96.49 329 | 96.70 145 | 98.98 324 | 97.78 264 | 90.81 310 | 96.19 234 | 98.55 257 | 73.63 395 | 98.98 214 | 89.41 341 | 98.56 167 | 97.88 291 |
|
| MIMVSNet | | | 90.30 357 | 88.67 371 | 95.17 300 | 96.45 331 | 91.64 330 | 92.39 460 | 97.15 349 | 85.99 397 | 90.50 317 | 93.19 430 | 66.95 423 | 94.86 433 | 82.01 412 | 93.43 299 | 99.01 247 |
|
| CR-MVSNet | | | 93.45 288 | 92.62 293 | 95.94 273 | 96.29 332 | 92.66 301 | 92.01 462 | 96.23 416 | 92.62 241 | 96.94 207 | 93.31 428 | 91.04 178 | 96.03 412 | 79.23 426 | 95.96 250 | 99.13 234 |
|
| RPMNet | | | 89.76 369 | 87.28 386 | 97.19 231 | 96.29 332 | 92.66 301 | 92.01 462 | 98.31 198 | 70.19 464 | 96.94 207 | 85.87 466 | 87.25 239 | 99.78 146 | 62.69 468 | 95.96 250 | 99.13 234 |
|
| tt0805 | | | 91.28 334 | 90.18 342 | 94.60 319 | 96.26 334 | 87.55 400 | 98.39 381 | 98.72 77 | 89.00 348 | 89.22 347 | 98.47 265 | 62.98 439 | 98.96 218 | 90.57 326 | 88.00 339 | 97.28 310 |
|
| Patchmtry | | | 89.70 370 | 88.49 374 | 93.33 367 | 96.24 335 | 89.94 371 | 91.37 465 | 96.23 416 | 78.22 447 | 87.69 374 | 93.31 428 | 91.04 178 | 96.03 412 | 80.18 424 | 82.10 385 | 94.02 373 |
|
| test_vis1_rt | | | 86.87 392 | 86.05 394 | 89.34 420 | 96.12 336 | 78.07 455 | 99.87 130 | 83.54 481 | 92.03 270 | 78.21 442 | 89.51 449 | 45.80 465 | 99.91 110 | 96.25 214 | 93.11 304 | 90.03 448 |
|
| JIA-IIPM | | | 91.76 328 | 90.70 329 | 94.94 306 | 96.11 337 | 87.51 401 | 93.16 458 | 98.13 228 | 75.79 453 | 97.58 183 | 77.68 471 | 92.84 137 | 97.97 312 | 88.47 355 | 96.54 234 | 99.33 206 |
|
| OpenMVS |  | 90.15 15 | 94.77 241 | 93.59 264 | 98.33 145 | 96.07 338 | 97.48 112 | 99.56 242 | 98.57 106 | 90.46 323 | 86.51 391 | 98.95 207 | 78.57 352 | 99.94 93 | 93.86 265 | 99.74 90 | 97.57 305 |
|
| PAPM | | | 98.60 37 | 98.42 38 | 99.14 72 | 96.05 339 | 98.96 27 | 99.90 114 | 99.35 24 | 96.68 71 | 98.35 154 | 99.66 115 | 96.45 35 | 98.51 265 | 99.45 65 | 99.89 74 | 99.96 74 |
|
| CLD-MVS | | | 94.06 269 | 93.90 255 | 94.55 323 | 96.02 340 | 90.69 350 | 99.98 21 | 97.72 270 | 96.62 75 | 91.05 311 | 98.85 226 | 77.21 357 | 98.47 266 | 98.11 146 | 89.51 318 | 94.48 330 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| PatchT | | | 90.38 354 | 88.75 370 | 95.25 298 | 95.99 341 | 90.16 363 | 91.22 466 | 97.54 293 | 76.80 449 | 97.26 196 | 86.01 465 | 91.88 165 | 96.07 411 | 66.16 463 | 95.91 254 | 99.51 173 |
|
| ACMH+ | | 89.98 16 | 90.35 355 | 89.54 354 | 92.78 382 | 95.99 341 | 86.12 411 | 98.81 349 | 97.18 344 | 89.38 341 | 83.14 417 | 97.76 297 | 68.42 417 | 98.43 271 | 89.11 346 | 86.05 354 | 93.78 393 |
|
| DeepMVS_CX |  | | | | 82.92 443 | 95.98 343 | 58.66 474 | | 96.01 422 | 92.72 234 | 78.34 441 | 95.51 370 | 58.29 451 | 98.08 306 | 82.57 407 | 85.29 359 | 92.03 429 |
|
| ACMP | | 92.05 9 | 92.74 303 | 92.42 302 | 93.73 355 | 95.91 344 | 88.72 386 | 99.81 161 | 97.53 295 | 94.13 165 | 87.00 385 | 98.23 279 | 74.07 392 | 98.47 266 | 96.22 215 | 88.86 325 | 93.99 378 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| test_vis1_n | | | 93.61 283 | 93.03 285 | 95.35 293 | 95.86 345 | 86.94 406 | 99.87 130 | 96.36 414 | 96.85 62 | 99.54 71 | 98.79 230 | 52.41 459 | 99.83 139 | 98.64 114 | 98.97 153 | 99.29 217 |
|
| HQP-NCC | | | | | | 95.78 346 | | 99.87 130 | | 96.82 64 | 93.37 283 | | | | | | |
|
| ACMP_Plane | | | | | | 95.78 346 | | 99.87 130 | | 96.82 64 | 93.37 283 | | | | | | |
|
| HQP-MVS | | | 94.61 248 | 94.50 236 | 94.92 307 | 95.78 346 | 91.85 320 | 99.87 130 | 97.89 252 | 96.82 64 | 93.37 283 | 98.65 242 | 80.65 330 | 98.39 278 | 97.92 158 | 89.60 313 | 94.53 326 |
|
| NP-MVS | | | | | | 95.77 349 | 91.79 322 | | | | | 98.65 242 | | | | | |
|
| test_fmvsmconf0.1_n | | | 97.74 103 | 97.44 107 | 98.64 114 | 95.76 350 | 96.20 173 | 99.94 90 | 98.05 235 | 98.17 13 | 98.89 120 | 99.42 141 | 87.65 229 | 99.90 112 | 99.50 61 | 99.60 107 | 99.82 106 |
|
| plane_prior6 | | | | | | 95.76 350 | 91.72 327 | | | | | | 80.47 334 | | | | |
|
| ACMM | | 91.95 10 | 92.88 300 | 92.52 300 | 93.98 349 | 95.75 352 | 89.08 381 | 99.77 174 | 97.52 297 | 93.00 219 | 89.95 324 | 97.99 288 | 76.17 375 | 98.46 269 | 93.63 277 | 88.87 324 | 94.39 338 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| GA-MVS | | | 93.83 272 | 92.84 287 | 96.80 245 | 95.73 353 | 93.57 276 | 99.88 127 | 97.24 337 | 92.57 246 | 92.92 290 | 96.66 329 | 78.73 350 | 97.67 326 | 87.75 363 | 94.06 292 | 99.17 229 |
|
| plane_prior1 | | | | | | 95.73 353 | | | | | | | | | | | |
|
| jason | | | 97.24 129 | 96.86 134 | 98.38 144 | 95.73 353 | 97.32 117 | 99.97 39 | 97.40 309 | 95.34 118 | 98.60 141 | 99.54 133 | 87.70 228 | 98.56 262 | 97.94 157 | 99.47 124 | 99.25 223 |
| jason: jason. |
| mmtdpeth | | | 88.52 381 | 87.75 383 | 90.85 402 | 95.71 356 | 83.47 431 | 98.94 332 | 94.85 446 | 88.78 357 | 97.19 198 | 89.58 448 | 63.29 437 | 98.97 216 | 98.54 119 | 62.86 467 | 90.10 447 |
|
| HQP_MVS | | | 94.49 255 | 94.36 239 | 94.87 308 | 95.71 356 | 91.74 324 | 99.84 149 | 97.87 254 | 96.38 84 | 93.01 288 | 98.59 250 | 80.47 334 | 98.37 284 | 97.79 167 | 89.55 316 | 94.52 328 |
|
| plane_prior7 | | | | | | 95.71 356 | 91.59 336 | | | | | | | | | | |
|
| ITE_SJBPF | | | | | 92.38 385 | 95.69 359 | 85.14 417 | | 95.71 430 | 92.81 228 | 89.33 344 | 98.11 282 | 70.23 410 | 98.42 272 | 85.91 385 | 88.16 337 | 93.59 401 |
|
| fmvsm_s_conf0.1_n_a | | | 97.09 138 | 96.90 131 | 97.63 199 | 95.65 360 | 94.21 259 | 99.83 156 | 98.50 136 | 96.27 91 | 99.65 53 | 99.64 118 | 84.72 285 | 99.93 103 | 99.04 84 | 98.84 158 | 98.74 265 |
|
| ACMH | | 89.72 17 | 90.64 348 | 89.63 351 | 93.66 361 | 95.64 361 | 88.64 389 | 98.55 369 | 97.45 302 | 89.03 346 | 81.62 424 | 97.61 298 | 69.75 411 | 98.41 274 | 89.37 343 | 87.62 346 | 93.92 384 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| baseline2 | | | 96.71 162 | 96.49 152 | 97.37 223 | 95.63 362 | 95.96 182 | 99.74 187 | 98.88 54 | 92.94 221 | 91.61 304 | 98.97 200 | 97.72 6 | 98.62 259 | 94.83 242 | 98.08 188 | 97.53 307 |
|
| FMVSNet1 | | | 88.50 382 | 86.64 389 | 94.08 342 | 95.62 363 | 91.97 315 | 98.43 377 | 96.95 382 | 83.00 427 | 86.08 399 | 94.72 404 | 59.09 450 | 96.11 407 | 81.82 414 | 84.07 372 | 94.17 356 |
|
| LuminaMVS | | | 96.63 166 | 96.21 166 | 97.87 177 | 95.58 364 | 96.82 141 | 99.12 301 | 97.67 274 | 94.47 144 | 97.88 174 | 98.31 275 | 87.50 233 | 98.71 246 | 98.07 150 | 97.29 210 | 98.10 287 |
|
| LPG-MVS_test | | | 92.96 297 | 92.71 292 | 93.71 357 | 95.43 365 | 88.67 387 | 99.75 184 | 97.62 282 | 92.81 228 | 90.05 320 | 98.49 261 | 75.24 382 | 98.40 276 | 95.84 221 | 89.12 320 | 94.07 370 |
|
| LGP-MVS_train | | | | | 93.71 357 | 95.43 365 | 88.67 387 | | 97.62 282 | 92.81 228 | 90.05 320 | 98.49 261 | 75.24 382 | 98.40 276 | 95.84 221 | 89.12 320 | 94.07 370 |
|
| tpm | | | 93.70 281 | 93.41 273 | 94.58 321 | 95.36 367 | 87.41 402 | 97.01 422 | 96.90 389 | 90.85 308 | 96.72 215 | 94.14 419 | 90.40 192 | 96.84 375 | 90.75 324 | 88.54 332 | 99.51 173 |
|
| D2MVS | | | 92.76 302 | 92.59 298 | 93.27 369 | 95.13 368 | 89.54 375 | 99.69 211 | 99.38 22 | 92.26 263 | 87.59 376 | 94.61 410 | 85.05 278 | 97.79 321 | 91.59 307 | 88.01 338 | 92.47 424 |
|
| VPA-MVSNet | | | 92.70 304 | 91.55 317 | 96.16 267 | 95.09 369 | 96.20 173 | 98.88 340 | 99.00 39 | 91.02 305 | 91.82 303 | 95.29 386 | 76.05 377 | 97.96 314 | 95.62 226 | 81.19 392 | 94.30 345 |
|
| LTVRE_ROB | | 88.28 18 | 90.29 358 | 89.05 365 | 94.02 345 | 95.08 370 | 90.15 364 | 97.19 417 | 97.43 304 | 84.91 413 | 83.99 413 | 97.06 315 | 74.00 393 | 98.28 293 | 84.08 396 | 87.71 342 | 93.62 400 |
| 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 | | | 87.87 389 | 86.51 390 | 91.94 391 | 95.05 371 | 85.57 415 | 97.65 408 | 94.08 456 | 84.40 417 | 81.82 423 | 96.85 324 | 62.14 442 | 98.33 287 | 80.25 423 | 86.37 353 | 91.91 431 |
|
| test0.0.03 1 | | | 93.86 271 | 93.61 261 | 94.64 317 | 95.02 372 | 92.18 313 | 99.93 97 | 98.58 104 | 94.07 169 | 87.96 371 | 98.50 260 | 93.90 106 | 94.96 430 | 81.33 415 | 93.17 302 | 96.78 313 |
|
| UniMVSNet (Re) | | | 93.07 296 | 92.13 304 | 95.88 275 | 94.84 373 | 96.24 172 | 99.88 127 | 98.98 41 | 92.49 251 | 89.25 345 | 95.40 376 | 87.09 241 | 97.14 351 | 93.13 285 | 78.16 416 | 94.26 347 |
|
| USDC | | | 90.00 365 | 88.96 366 | 93.10 375 | 94.81 374 | 88.16 395 | 98.71 358 | 95.54 435 | 93.66 190 | 83.75 415 | 97.20 309 | 65.58 428 | 98.31 289 | 83.96 399 | 87.49 348 | 92.85 418 |
|
| VPNet | | | 91.81 322 | 90.46 333 | 95.85 277 | 94.74 375 | 95.54 201 | 98.98 324 | 98.59 102 | 92.14 265 | 90.77 316 | 97.44 302 | 68.73 415 | 97.54 331 | 94.89 241 | 77.89 418 | 94.46 331 |
|
| FIs | | | 94.10 266 | 93.43 270 | 96.11 268 | 94.70 376 | 96.82 141 | 99.58 236 | 98.93 48 | 92.54 247 | 89.34 343 | 97.31 306 | 87.62 230 | 97.10 355 | 94.22 259 | 86.58 351 | 94.40 337 |
|
| UniMVSNet_ETH3D | | | 90.06 364 | 88.58 373 | 94.49 327 | 94.67 377 | 88.09 396 | 97.81 405 | 97.57 290 | 83.91 420 | 88.44 363 | 97.41 303 | 57.44 452 | 97.62 328 | 91.41 309 | 88.59 331 | 97.77 296 |
|
| UniMVSNet_NR-MVSNet | | | 92.95 298 | 92.11 305 | 95.49 285 | 94.61 378 | 95.28 218 | 99.83 156 | 99.08 36 | 91.49 285 | 89.21 348 | 96.86 323 | 87.14 240 | 96.73 381 | 93.20 281 | 77.52 421 | 94.46 331 |
|
| test_fmvs2 | | | 89.47 374 | 89.70 350 | 88.77 427 | 94.54 379 | 75.74 457 | 99.83 156 | 94.70 452 | 94.71 136 | 91.08 309 | 96.82 328 | 54.46 455 | 97.78 323 | 92.87 288 | 88.27 335 | 92.80 419 |
|
| MonoMVSNet | | | 94.82 236 | 94.43 237 | 95.98 271 | 94.54 379 | 90.73 349 | 99.03 319 | 97.06 369 | 93.16 211 | 93.15 287 | 95.47 373 | 88.29 221 | 97.57 329 | 97.85 162 | 91.33 310 | 99.62 142 |
|
| WR-MVS | | | 92.31 314 | 91.25 322 | 95.48 288 | 94.45 381 | 95.29 217 | 99.60 232 | 98.68 83 | 90.10 331 | 88.07 370 | 96.89 321 | 80.68 329 | 96.80 379 | 93.14 284 | 79.67 409 | 94.36 339 |
|
| nrg030 | | | 93.51 285 | 92.53 299 | 96.45 258 | 94.36 382 | 97.20 123 | 99.81 161 | 97.16 348 | 91.60 282 | 89.86 327 | 97.46 301 | 86.37 253 | 97.68 325 | 95.88 220 | 80.31 405 | 94.46 331 |
|
| tfpnnormal | | | 89.29 377 | 87.61 384 | 94.34 335 | 94.35 383 | 94.13 261 | 98.95 331 | 98.94 44 | 83.94 418 | 84.47 410 | 95.51 370 | 74.84 387 | 97.39 334 | 77.05 440 | 80.41 403 | 91.48 434 |
|
| FC-MVSNet-test | | | 93.81 275 | 93.15 283 | 95.80 280 | 94.30 384 | 96.20 173 | 99.42 266 | 98.89 52 | 92.33 258 | 89.03 353 | 97.27 308 | 87.39 236 | 96.83 377 | 93.20 281 | 86.48 352 | 94.36 339 |
|
| SSC-MVS3.2 | | | 89.59 372 | 88.66 372 | 92.38 385 | 94.29 385 | 86.12 411 | 99.49 255 | 97.66 277 | 90.28 330 | 88.63 360 | 95.18 390 | 64.46 433 | 96.88 373 | 85.30 389 | 82.66 380 | 94.14 365 |
|
| MS-PatchMatch | | | 90.65 347 | 90.30 338 | 91.71 396 | 94.22 386 | 85.50 416 | 98.24 388 | 97.70 271 | 88.67 360 | 86.42 394 | 96.37 339 | 67.82 420 | 98.03 310 | 83.62 401 | 99.62 100 | 91.60 432 |
|
| WR-MVS_H | | | 91.30 332 | 90.35 336 | 94.15 339 | 94.17 387 | 92.62 304 | 99.17 299 | 98.94 44 | 88.87 355 | 86.48 393 | 94.46 415 | 84.36 291 | 96.61 386 | 88.19 357 | 78.51 414 | 93.21 410 |
|
| DU-MVS | | | 92.46 311 | 91.45 320 | 95.49 285 | 94.05 388 | 95.28 218 | 99.81 161 | 98.74 76 | 92.25 264 | 89.21 348 | 96.64 331 | 81.66 315 | 96.73 381 | 93.20 281 | 77.52 421 | 94.46 331 |
|
| NR-MVSNet | | | 91.56 330 | 90.22 340 | 95.60 283 | 94.05 388 | 95.76 189 | 98.25 387 | 98.70 79 | 91.16 299 | 80.78 430 | 96.64 331 | 83.23 301 | 96.57 387 | 91.41 309 | 77.73 420 | 94.46 331 |
|
| CP-MVSNet | | | 91.23 336 | 90.22 340 | 94.26 337 | 93.96 390 | 92.39 309 | 99.09 305 | 98.57 106 | 88.95 352 | 86.42 394 | 96.57 334 | 79.19 345 | 96.37 396 | 90.29 333 | 78.95 411 | 94.02 373 |
|
| XXY-MVS | | | 91.82 321 | 90.46 333 | 95.88 275 | 93.91 391 | 95.40 208 | 98.87 343 | 97.69 273 | 88.63 362 | 87.87 372 | 97.08 313 | 74.38 391 | 97.89 318 | 91.66 306 | 84.07 372 | 94.35 342 |
|
| PS-CasMVS | | | 90.63 349 | 89.51 356 | 93.99 348 | 93.83 392 | 91.70 328 | 98.98 324 | 98.52 127 | 88.48 364 | 86.15 398 | 96.53 336 | 75.46 380 | 96.31 400 | 88.83 348 | 78.86 413 | 93.95 381 |
|
| test_0402 | | | 85.58 396 | 83.94 401 | 90.50 408 | 93.81 393 | 85.04 418 | 98.55 369 | 95.20 443 | 76.01 451 | 79.72 436 | 95.13 391 | 64.15 435 | 96.26 402 | 66.04 464 | 86.88 350 | 90.21 445 |
|
| XVG-ACMP-BASELINE | | | 91.22 337 | 90.75 328 | 92.63 384 | 93.73 394 | 85.61 414 | 98.52 373 | 97.44 303 | 92.77 232 | 89.90 326 | 96.85 324 | 66.64 425 | 98.39 278 | 92.29 293 | 88.61 329 | 93.89 386 |
|
| TranMVSNet+NR-MVSNet | | | 91.68 329 | 90.61 332 | 94.87 308 | 93.69 395 | 93.98 266 | 99.69 211 | 98.65 87 | 91.03 304 | 88.44 363 | 96.83 327 | 80.05 338 | 96.18 405 | 90.26 334 | 76.89 429 | 94.45 336 |
|
| TransMVSNet (Re) | | | 87.25 390 | 85.28 397 | 93.16 372 | 93.56 396 | 91.03 341 | 98.54 371 | 94.05 458 | 83.69 422 | 81.09 428 | 96.16 345 | 75.32 381 | 96.40 395 | 76.69 441 | 68.41 455 | 92.06 428 |
|
| v10 | | | 90.25 359 | 88.82 368 | 94.57 322 | 93.53 397 | 93.43 281 | 99.08 307 | 96.87 392 | 85.00 410 | 87.34 383 | 94.51 411 | 80.93 325 | 97.02 365 | 82.85 406 | 79.23 410 | 93.26 408 |
|
| testgi | | | 89.01 379 | 88.04 380 | 91.90 392 | 93.49 398 | 84.89 420 | 99.73 194 | 95.66 432 | 93.89 183 | 85.14 405 | 98.17 280 | 59.68 448 | 94.66 436 | 77.73 436 | 88.88 323 | 96.16 322 |
|
| v8 | | | 90.54 351 | 89.17 361 | 94.66 316 | 93.43 399 | 93.40 284 | 99.20 296 | 96.94 386 | 85.76 400 | 87.56 377 | 94.51 411 | 81.96 311 | 97.19 348 | 84.94 392 | 78.25 415 | 93.38 406 |
|
| V42 | | | 91.28 334 | 90.12 345 | 94.74 313 | 93.42 400 | 93.46 280 | 99.68 214 | 97.02 373 | 87.36 379 | 89.85 329 | 95.05 394 | 81.31 321 | 97.34 337 | 87.34 368 | 80.07 407 | 93.40 404 |
|
| pm-mvs1 | | | 89.36 376 | 87.81 382 | 94.01 346 | 93.40 401 | 91.93 318 | 98.62 367 | 96.48 412 | 86.25 395 | 83.86 414 | 96.14 347 | 73.68 394 | 97.04 361 | 86.16 382 | 75.73 434 | 93.04 414 |
|
| v1144 | | | 91.09 338 | 89.83 347 | 94.87 308 | 93.25 402 | 93.69 274 | 99.62 225 | 96.98 378 | 86.83 389 | 89.64 335 | 94.99 399 | 80.94 324 | 97.05 358 | 85.08 391 | 81.16 393 | 93.87 388 |
|
| v1192 | | | 90.62 350 | 89.25 360 | 94.72 315 | 93.13 403 | 93.07 288 | 99.50 253 | 97.02 373 | 86.33 394 | 89.56 339 | 95.01 396 | 79.22 344 | 97.09 357 | 82.34 410 | 81.16 393 | 94.01 375 |
|
| v2v482 | | | 91.30 332 | 90.07 346 | 95.01 303 | 93.13 403 | 93.79 269 | 99.77 174 | 97.02 373 | 88.05 370 | 89.25 345 | 95.37 380 | 80.73 328 | 97.15 350 | 87.28 369 | 80.04 408 | 94.09 369 |
|
| OPM-MVS | | | 93.21 290 | 92.80 289 | 94.44 330 | 93.12 405 | 90.85 348 | 99.77 174 | 97.61 285 | 96.19 94 | 91.56 305 | 98.65 242 | 75.16 386 | 98.47 266 | 93.78 272 | 89.39 319 | 93.99 378 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| v144192 | | | 90.79 345 | 89.52 355 | 94.59 320 | 93.11 406 | 92.77 295 | 99.56 242 | 96.99 376 | 86.38 393 | 89.82 330 | 94.95 401 | 80.50 333 | 97.10 355 | 83.98 398 | 80.41 403 | 93.90 385 |
|
| PEN-MVS | | | 90.19 361 | 89.06 364 | 93.57 362 | 93.06 407 | 90.90 346 | 99.06 312 | 98.47 139 | 88.11 369 | 85.91 400 | 96.30 341 | 76.67 367 | 95.94 415 | 87.07 372 | 76.91 428 | 93.89 386 |
|
| v1240 | | | 90.20 360 | 88.79 369 | 94.44 330 | 93.05 408 | 92.27 311 | 99.38 273 | 96.92 388 | 85.89 398 | 89.36 342 | 94.87 403 | 77.89 356 | 97.03 363 | 80.66 419 | 81.08 396 | 94.01 375 |
|
| v148 | | | 90.70 346 | 89.63 351 | 93.92 350 | 92.97 409 | 90.97 342 | 99.75 184 | 96.89 390 | 87.51 376 | 88.27 368 | 95.01 396 | 81.67 314 | 97.04 361 | 87.40 367 | 77.17 426 | 93.75 394 |
|
| v1921920 | | | 90.46 352 | 89.12 362 | 94.50 326 | 92.96 410 | 92.46 307 | 99.49 255 | 96.98 378 | 86.10 396 | 89.61 337 | 95.30 383 | 78.55 353 | 97.03 363 | 82.17 411 | 80.89 401 | 94.01 375 |
|
| MVStest1 | | | 85.03 402 | 82.76 411 | 91.83 393 | 92.95 411 | 89.16 380 | 98.57 368 | 94.82 447 | 71.68 462 | 68.54 465 | 95.11 393 | 83.17 302 | 95.66 419 | 74.69 447 | 65.32 462 | 90.65 441 |
|
| tt0320-xc | | | 82.94 417 | 80.35 424 | 90.72 406 | 92.90 412 | 83.54 429 | 96.85 427 | 94.73 450 | 63.12 467 | 79.85 435 | 93.77 423 | 49.43 463 | 95.46 422 | 80.98 418 | 71.54 443 | 93.16 411 |
|
| Baseline_NR-MVSNet | | | 90.33 356 | 89.51 356 | 92.81 381 | 92.84 413 | 89.95 369 | 99.77 174 | 93.94 459 | 84.69 415 | 89.04 352 | 95.66 362 | 81.66 315 | 96.52 389 | 90.99 317 | 76.98 427 | 91.97 430 |
|
| test_method | | | 80.79 423 | 79.70 426 | 84.08 440 | 92.83 414 | 67.06 466 | 99.51 251 | 95.42 437 | 54.34 472 | 81.07 429 | 93.53 425 | 44.48 467 | 92.22 458 | 78.90 431 | 77.23 425 | 92.94 416 |
|
| pmmvs4 | | | 92.10 318 | 91.07 326 | 95.18 299 | 92.82 415 | 94.96 229 | 99.48 258 | 96.83 394 | 87.45 378 | 88.66 359 | 96.56 335 | 83.78 296 | 96.83 377 | 89.29 344 | 84.77 366 | 93.75 394 |
|
| LF4IMVS | | | 89.25 378 | 88.85 367 | 90.45 410 | 92.81 416 | 81.19 447 | 98.12 395 | 94.79 448 | 91.44 289 | 86.29 396 | 97.11 311 | 65.30 431 | 98.11 304 | 88.53 353 | 85.25 360 | 92.07 427 |
|
| tt0320 | | | 83.56 416 | 81.15 419 | 90.77 404 | 92.77 417 | 83.58 428 | 96.83 428 | 95.52 436 | 63.26 466 | 81.36 426 | 92.54 433 | 53.26 457 | 95.77 417 | 80.45 420 | 74.38 437 | 92.96 415 |
|
| DTE-MVSNet | | | 89.40 375 | 88.24 378 | 92.88 379 | 92.66 418 | 89.95 369 | 99.10 304 | 98.22 212 | 87.29 380 | 85.12 406 | 96.22 343 | 76.27 374 | 95.30 427 | 83.56 402 | 75.74 433 | 93.41 403 |
|
| EU-MVSNet | | | 90.14 363 | 90.34 337 | 89.54 419 | 92.55 419 | 81.06 448 | 98.69 361 | 98.04 236 | 91.41 293 | 86.59 390 | 96.84 326 | 80.83 327 | 93.31 449 | 86.20 381 | 81.91 387 | 94.26 347 |
|
| APD_test1 | | | 81.15 421 | 80.92 421 | 81.86 444 | 92.45 420 | 59.76 473 | 96.04 442 | 93.61 462 | 73.29 460 | 77.06 445 | 96.64 331 | 44.28 468 | 96.16 406 | 72.35 451 | 82.52 381 | 89.67 454 |
|
| sc_t1 | | | 85.01 403 | 82.46 413 | 92.67 383 | 92.44 421 | 83.09 433 | 97.39 412 | 95.72 429 | 65.06 465 | 85.64 403 | 96.16 345 | 49.50 462 | 97.34 337 | 84.86 393 | 75.39 435 | 97.57 305 |
|
| our_test_3 | | | 90.39 353 | 89.48 358 | 93.12 373 | 92.40 422 | 89.57 374 | 99.33 280 | 96.35 415 | 87.84 374 | 85.30 404 | 94.99 399 | 84.14 294 | 96.09 410 | 80.38 421 | 84.56 367 | 93.71 399 |
|
| ppachtmachnet_test | | | 89.58 373 | 88.35 376 | 93.25 371 | 92.40 422 | 90.44 358 | 99.33 280 | 96.73 401 | 85.49 405 | 85.90 401 | 95.77 356 | 81.09 323 | 96.00 414 | 76.00 445 | 82.49 382 | 93.30 407 |
|
| v7n | | | 89.65 371 | 88.29 377 | 93.72 356 | 92.22 424 | 90.56 355 | 99.07 311 | 97.10 361 | 85.42 407 | 86.73 387 | 94.72 404 | 80.06 337 | 97.13 352 | 81.14 416 | 78.12 417 | 93.49 402 |
|
| dmvs_testset | | | 83.79 412 | 86.07 393 | 76.94 448 | 92.14 425 | 48.60 483 | 96.75 429 | 90.27 473 | 89.48 340 | 78.65 439 | 98.55 257 | 79.25 343 | 86.65 471 | 66.85 461 | 82.69 379 | 95.57 324 |
|
| PS-MVSNAJss | | | 93.64 282 | 93.31 279 | 94.61 318 | 92.11 426 | 92.19 312 | 99.12 301 | 97.38 310 | 92.51 250 | 88.45 362 | 96.99 319 | 91.20 173 | 97.29 345 | 94.36 253 | 87.71 342 | 94.36 339 |
|
| pmmvs5 | | | 90.17 362 | 89.09 363 | 93.40 365 | 92.10 427 | 89.77 372 | 99.74 187 | 95.58 434 | 85.88 399 | 87.24 384 | 95.74 357 | 73.41 397 | 96.48 391 | 88.54 352 | 83.56 376 | 93.95 381 |
|
| N_pmnet | | | 80.06 427 | 80.78 422 | 77.89 447 | 91.94 428 | 45.28 485 | 98.80 352 | 56.82 487 | 78.10 448 | 80.08 433 | 93.33 426 | 77.03 361 | 95.76 418 | 68.14 459 | 82.81 378 | 92.64 420 |
|
| test_djsdf | | | 92.83 301 | 92.29 303 | 94.47 328 | 91.90 429 | 92.46 307 | 99.55 245 | 97.27 331 | 91.17 297 | 89.96 323 | 96.07 351 | 81.10 322 | 96.89 371 | 94.67 248 | 88.91 322 | 94.05 372 |
|
| SixPastTwentyTwo | | | 88.73 380 | 88.01 381 | 90.88 400 | 91.85 430 | 82.24 439 | 98.22 392 | 95.18 444 | 88.97 350 | 82.26 420 | 96.89 321 | 71.75 402 | 96.67 384 | 84.00 397 | 82.98 377 | 93.72 398 |
|
| K. test v3 | | | 88.05 386 | 87.24 387 | 90.47 409 | 91.82 431 | 82.23 440 | 98.96 330 | 97.42 306 | 89.05 345 | 76.93 447 | 95.60 364 | 68.49 416 | 95.42 423 | 85.87 386 | 81.01 399 | 93.75 394 |
|
| OurMVSNet-221017-0 | | | 89.81 368 | 89.48 358 | 90.83 403 | 91.64 432 | 81.21 446 | 98.17 394 | 95.38 439 | 91.48 287 | 85.65 402 | 97.31 306 | 72.66 398 | 97.29 345 | 88.15 358 | 84.83 365 | 93.97 380 |
|
| mvs_tets | | | 91.81 322 | 91.08 325 | 94.00 347 | 91.63 433 | 90.58 354 | 98.67 363 | 97.43 304 | 92.43 252 | 87.37 382 | 97.05 316 | 71.76 401 | 97.32 340 | 94.75 245 | 88.68 328 | 94.11 368 |
|
| Gipuma |  | | 66.95 440 | 65.00 440 | 72.79 453 | 91.52 434 | 67.96 465 | 66.16 477 | 95.15 445 | 47.89 474 | 58.54 471 | 67.99 476 | 29.74 472 | 87.54 470 | 50.20 475 | 77.83 419 | 62.87 476 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| test_fmvsmconf0.01_n | | | 96.39 179 | 95.74 192 | 98.32 146 | 91.47 435 | 95.56 200 | 99.84 149 | 97.30 326 | 97.74 30 | 97.89 173 | 99.35 152 | 79.62 340 | 99.85 129 | 99.25 74 | 99.24 141 | 99.55 159 |
|
| jajsoiax | | | 91.92 320 | 91.18 323 | 94.15 339 | 91.35 436 | 90.95 345 | 99.00 322 | 97.42 306 | 92.61 242 | 87.38 381 | 97.08 313 | 72.46 399 | 97.36 335 | 94.53 251 | 88.77 326 | 94.13 367 |
|
| MDA-MVSNet-bldmvs | | | 84.09 410 | 81.52 417 | 91.81 394 | 91.32 437 | 88.00 398 | 98.67 363 | 95.92 424 | 80.22 441 | 55.60 474 | 93.32 427 | 68.29 418 | 93.60 447 | 73.76 448 | 76.61 430 | 93.82 392 |
|
| MVP-Stereo | | | 90.93 340 | 90.45 335 | 92.37 387 | 91.25 438 | 88.76 384 | 98.05 399 | 96.17 418 | 87.27 381 | 84.04 411 | 95.30 383 | 78.46 354 | 97.27 347 | 83.78 400 | 99.70 93 | 91.09 435 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| MDA-MVSNet_test_wron | | | 85.51 398 | 83.32 406 | 92.10 389 | 90.96 439 | 88.58 390 | 99.20 296 | 96.52 410 | 79.70 443 | 57.12 473 | 92.69 432 | 79.11 346 | 93.86 443 | 77.10 439 | 77.46 423 | 93.86 389 |
|
| YYNet1 | | | 85.50 399 | 83.33 405 | 92.00 390 | 90.89 440 | 88.38 394 | 99.22 295 | 96.55 409 | 79.60 444 | 57.26 472 | 92.72 431 | 79.09 348 | 93.78 445 | 77.25 438 | 77.37 424 | 93.84 390 |
|
| anonymousdsp | | | 91.79 327 | 90.92 327 | 94.41 333 | 90.76 441 | 92.93 294 | 98.93 334 | 97.17 346 | 89.08 344 | 87.46 380 | 95.30 383 | 78.43 355 | 96.92 369 | 92.38 292 | 88.73 327 | 93.39 405 |
|
| lessismore_v0 | | | | | 90.53 407 | 90.58 442 | 80.90 449 | | 95.80 426 | | 77.01 446 | 95.84 354 | 66.15 427 | 96.95 367 | 83.03 405 | 75.05 436 | 93.74 397 |
|
| EG-PatchMatch MVS | | | 85.35 400 | 83.81 403 | 89.99 417 | 90.39 443 | 81.89 442 | 98.21 393 | 96.09 420 | 81.78 434 | 74.73 453 | 93.72 424 | 51.56 461 | 97.12 354 | 79.16 429 | 88.61 329 | 90.96 438 |
|
| EGC-MVSNET | | | 69.38 433 | 63.76 443 | 86.26 437 | 90.32 444 | 81.66 445 | 96.24 438 | 93.85 460 | 0.99 484 | 3.22 485 | 92.33 438 | 52.44 458 | 92.92 454 | 59.53 471 | 84.90 364 | 84.21 465 |
|
| CMPMVS |  | 61.59 21 | 84.75 406 | 85.14 398 | 83.57 441 | 90.32 444 | 62.54 469 | 96.98 423 | 97.59 289 | 74.33 458 | 69.95 462 | 96.66 329 | 64.17 434 | 98.32 288 | 87.88 362 | 88.41 334 | 89.84 450 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| new_pmnet | | | 84.49 409 | 82.92 409 | 89.21 421 | 90.03 446 | 82.60 436 | 96.89 426 | 95.62 433 | 80.59 439 | 75.77 452 | 89.17 450 | 65.04 432 | 94.79 434 | 72.12 452 | 81.02 398 | 90.23 444 |
|
| pmmvs6 | | | 85.69 395 | 83.84 402 | 91.26 399 | 90.00 447 | 84.41 423 | 97.82 404 | 96.15 419 | 75.86 452 | 81.29 427 | 95.39 378 | 61.21 445 | 96.87 374 | 83.52 403 | 73.29 439 | 92.50 423 |
|
| ttmdpeth | | | 88.23 385 | 87.06 388 | 91.75 395 | 89.91 448 | 87.35 403 | 98.92 337 | 95.73 428 | 87.92 372 | 84.02 412 | 96.31 340 | 68.23 419 | 96.84 375 | 86.33 380 | 76.12 431 | 91.06 436 |
|
| DSMNet-mixed | | | 88.28 384 | 88.24 378 | 88.42 430 | 89.64 449 | 75.38 459 | 98.06 398 | 89.86 474 | 85.59 404 | 88.20 369 | 92.14 439 | 76.15 376 | 91.95 459 | 78.46 433 | 96.05 247 | 97.92 290 |
|
| UnsupCasMVSNet_eth | | | 85.52 397 | 83.99 399 | 90.10 415 | 89.36 450 | 83.51 430 | 96.65 430 | 97.99 240 | 89.14 343 | 75.89 451 | 93.83 421 | 63.25 438 | 93.92 441 | 81.92 413 | 67.90 458 | 92.88 417 |
|
| Anonymous20231206 | | | 86.32 393 | 85.42 396 | 89.02 423 | 89.11 451 | 80.53 452 | 99.05 316 | 95.28 440 | 85.43 406 | 82.82 418 | 93.92 420 | 74.40 390 | 93.44 448 | 66.99 460 | 81.83 388 | 93.08 413 |
|
| Anonymous20240521 | | | 85.15 401 | 83.81 403 | 89.16 422 | 88.32 452 | 82.69 435 | 98.80 352 | 95.74 427 | 79.72 442 | 81.53 425 | 90.99 442 | 65.38 430 | 94.16 439 | 72.69 450 | 81.11 395 | 90.63 442 |
|
| OpenMVS_ROB |  | 79.82 20 | 83.77 413 | 81.68 416 | 90.03 416 | 88.30 453 | 82.82 434 | 98.46 374 | 95.22 442 | 73.92 459 | 76.00 450 | 91.29 441 | 55.00 454 | 96.94 368 | 68.40 458 | 88.51 333 | 90.34 443 |
|
| test20.03 | | | 84.72 407 | 83.99 399 | 86.91 435 | 88.19 454 | 80.62 451 | 98.88 340 | 95.94 423 | 88.36 366 | 78.87 437 | 94.62 409 | 68.75 414 | 89.11 466 | 66.52 462 | 75.82 432 | 91.00 437 |
|
| KD-MVS_self_test | | | 83.59 414 | 82.06 414 | 88.20 431 | 86.93 455 | 80.70 450 | 97.21 416 | 96.38 413 | 82.87 428 | 82.49 419 | 88.97 451 | 67.63 421 | 92.32 457 | 73.75 449 | 62.30 469 | 91.58 433 |
|
| MIMVSNet1 | | | 82.58 418 | 80.51 423 | 88.78 425 | 86.68 456 | 84.20 424 | 96.65 430 | 95.41 438 | 78.75 446 | 78.59 440 | 92.44 434 | 51.88 460 | 89.76 465 | 65.26 465 | 78.95 411 | 92.38 426 |
|
| CL-MVSNet_self_test | | | 84.50 408 | 83.15 408 | 88.53 429 | 86.00 457 | 81.79 443 | 98.82 348 | 97.35 314 | 85.12 409 | 83.62 416 | 90.91 444 | 76.66 368 | 91.40 460 | 69.53 456 | 60.36 470 | 92.40 425 |
|
| UnsupCasMVSNet_bld | | | 79.97 429 | 77.03 434 | 88.78 425 | 85.62 458 | 81.98 441 | 93.66 454 | 97.35 314 | 75.51 455 | 70.79 461 | 83.05 468 | 48.70 464 | 94.91 432 | 78.31 434 | 60.29 471 | 89.46 457 |
|
| mvs5depth | | | 84.87 404 | 82.90 410 | 90.77 404 | 85.59 459 | 84.84 421 | 91.10 467 | 93.29 464 | 83.14 425 | 85.07 407 | 94.33 417 | 62.17 441 | 97.32 340 | 78.83 432 | 72.59 442 | 90.14 446 |
|
| Patchmatch-RL test | | | 86.90 391 | 85.98 395 | 89.67 418 | 84.45 460 | 75.59 458 | 89.71 470 | 92.43 466 | 86.89 388 | 77.83 444 | 90.94 443 | 94.22 95 | 93.63 446 | 87.75 363 | 69.61 448 | 99.79 111 |
|
| pmmvs-eth3d | | | 84.03 411 | 81.97 415 | 90.20 413 | 84.15 461 | 87.09 405 | 98.10 397 | 94.73 450 | 83.05 426 | 74.10 457 | 87.77 457 | 65.56 429 | 94.01 440 | 81.08 417 | 69.24 450 | 89.49 456 |
|
| test_fmvs3 | | | 79.99 428 | 80.17 425 | 79.45 446 | 84.02 462 | 62.83 467 | 99.05 316 | 93.49 463 | 88.29 368 | 80.06 434 | 86.65 463 | 28.09 474 | 88.00 467 | 88.63 349 | 73.27 440 | 87.54 463 |
|
| PM-MVS | | | 80.47 425 | 78.88 428 | 85.26 438 | 83.79 463 | 72.22 461 | 95.89 445 | 91.08 471 | 85.71 403 | 76.56 449 | 88.30 453 | 36.64 470 | 93.90 442 | 82.39 409 | 69.57 449 | 89.66 455 |
|
| new-patchmatchnet | | | 81.19 420 | 79.34 427 | 86.76 436 | 82.86 464 | 80.36 453 | 97.92 401 | 95.27 441 | 82.09 433 | 72.02 458 | 86.87 462 | 62.81 440 | 90.74 463 | 71.10 453 | 63.08 466 | 89.19 459 |
|
| FE-MVSNET2 | | | 83.57 415 | 81.36 418 | 90.20 413 | 82.83 465 | 87.59 399 | 98.28 385 | 96.04 421 | 85.33 408 | 74.13 456 | 87.45 458 | 59.16 449 | 93.26 450 | 79.12 430 | 69.91 446 | 89.77 451 |
|
| FE-MVSNET | | | 81.05 422 | 78.81 429 | 87.79 433 | 81.98 466 | 83.70 426 | 98.23 390 | 91.78 470 | 81.27 436 | 74.29 455 | 87.44 459 | 60.92 447 | 90.67 464 | 64.92 466 | 68.43 454 | 89.01 460 |
|
| mvsany_test3 | | | 82.12 419 | 81.14 420 | 85.06 439 | 81.87 467 | 70.41 463 | 97.09 420 | 92.14 467 | 91.27 296 | 77.84 443 | 88.73 452 | 39.31 469 | 95.49 420 | 90.75 324 | 71.24 444 | 89.29 458 |
|
| WB-MVS | | | 76.28 431 | 77.28 433 | 73.29 452 | 81.18 468 | 54.68 477 | 97.87 403 | 94.19 455 | 81.30 435 | 69.43 463 | 90.70 445 | 77.02 362 | 82.06 475 | 35.71 480 | 68.11 457 | 83.13 466 |
|
| test_f | | | 78.40 430 | 77.59 432 | 80.81 445 | 80.82 469 | 62.48 470 | 96.96 424 | 93.08 465 | 83.44 423 | 74.57 454 | 84.57 467 | 27.95 475 | 92.63 455 | 84.15 395 | 72.79 441 | 87.32 464 |
|
| SSC-MVS | | | 75.42 432 | 76.40 435 | 72.49 456 | 80.68 470 | 53.62 478 | 97.42 410 | 94.06 457 | 80.42 440 | 68.75 464 | 90.14 447 | 76.54 370 | 81.66 476 | 33.25 481 | 66.34 461 | 82.19 467 |
|
| FE-MVSNET1 | | | 80.74 424 | 78.10 430 | 88.66 428 | 80.60 471 | 83.26 432 | 97.26 415 | 95.88 425 | 78.83 445 | 71.95 459 | 87.05 461 | 45.50 466 | 93.05 453 | 76.67 442 | 69.12 453 | 89.68 452 |
|
| pmmvs3 | | | 80.27 426 | 77.77 431 | 87.76 434 | 80.32 472 | 82.43 438 | 98.23 390 | 91.97 468 | 72.74 461 | 78.75 438 | 87.97 456 | 57.30 453 | 90.99 462 | 70.31 454 | 62.37 468 | 89.87 449 |
|
| testf1 | | | 68.38 436 | 66.92 437 | 72.78 454 | 78.80 473 | 50.36 480 | 90.95 468 | 87.35 479 | 55.47 470 | 58.95 469 | 88.14 454 | 20.64 479 | 87.60 468 | 57.28 472 | 64.69 463 | 80.39 469 |
|
| APD_test2 | | | 68.38 436 | 66.92 437 | 72.78 454 | 78.80 473 | 50.36 480 | 90.95 468 | 87.35 479 | 55.47 470 | 58.95 469 | 88.14 454 | 20.64 479 | 87.60 468 | 57.28 472 | 64.69 463 | 80.39 469 |
|
| ambc | | | | | 83.23 442 | 77.17 475 | 62.61 468 | 87.38 472 | 94.55 454 | | 76.72 448 | 86.65 463 | 30.16 471 | 96.36 397 | 84.85 394 | 69.86 447 | 90.73 440 |
|
| test_vis3_rt | | | 68.82 434 | 66.69 439 | 75.21 451 | 76.24 476 | 60.41 472 | 96.44 433 | 68.71 486 | 75.13 456 | 50.54 477 | 69.52 475 | 16.42 484 | 96.32 399 | 80.27 422 | 66.92 460 | 68.89 473 |
|
| TDRefinement | | | 84.76 405 | 82.56 412 | 91.38 398 | 74.58 477 | 84.80 422 | 97.36 413 | 94.56 453 | 84.73 414 | 80.21 432 | 96.12 350 | 63.56 436 | 98.39 278 | 87.92 361 | 63.97 465 | 90.95 439 |
|
| E-PMN | | | 52.30 444 | 52.18 446 | 52.67 462 | 71.51 478 | 45.40 484 | 93.62 455 | 76.60 484 | 36.01 478 | 43.50 479 | 64.13 478 | 27.11 476 | 67.31 481 | 31.06 482 | 26.06 477 | 45.30 480 |
|
| EMVS | | | 51.44 446 | 51.22 448 | 52.11 463 | 70.71 479 | 44.97 486 | 94.04 451 | 75.66 485 | 35.34 480 | 42.40 480 | 61.56 481 | 28.93 473 | 65.87 482 | 27.64 483 | 24.73 478 | 45.49 479 |
|
| PMMVS2 | | | 67.15 439 | 64.15 442 | 76.14 450 | 70.56 480 | 62.07 471 | 93.89 452 | 87.52 478 | 58.09 469 | 60.02 468 | 78.32 470 | 22.38 478 | 84.54 473 | 59.56 470 | 47.03 475 | 81.80 468 |
|
| FPMVS | | | 68.72 435 | 68.72 436 | 68.71 458 | 65.95 481 | 44.27 487 | 95.97 444 | 94.74 449 | 51.13 473 | 53.26 475 | 90.50 446 | 25.11 477 | 83.00 474 | 60.80 469 | 80.97 400 | 78.87 471 |
|
| wuyk23d | | | 20.37 450 | 20.84 453 | 18.99 466 | 65.34 482 | 27.73 489 | 50.43 478 | 7.67 490 | 9.50 483 | 8.01 484 | 6.34 484 | 6.13 487 | 26.24 483 | 23.40 484 | 10.69 482 | 2.99 481 |
|
| LCM-MVSNet | | | 67.77 438 | 64.73 441 | 76.87 449 | 62.95 483 | 56.25 476 | 89.37 471 | 93.74 461 | 44.53 475 | 61.99 467 | 80.74 469 | 20.42 481 | 86.53 472 | 69.37 457 | 59.50 472 | 87.84 461 |
|
| MVE |  | 53.74 22 | 51.54 445 | 47.86 449 | 62.60 460 | 59.56 484 | 50.93 479 | 79.41 475 | 77.69 483 | 35.69 479 | 36.27 481 | 61.76 480 | 5.79 488 | 69.63 479 | 37.97 479 | 36.61 476 | 67.24 474 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| ANet_high | | | 56.10 442 | 52.24 445 | 67.66 459 | 49.27 485 | 56.82 475 | 83.94 473 | 82.02 482 | 70.47 463 | 33.28 482 | 64.54 477 | 17.23 483 | 69.16 480 | 45.59 477 | 23.85 479 | 77.02 472 |
|
| tmp_tt | | | 65.23 441 | 62.94 444 | 72.13 457 | 44.90 486 | 50.03 482 | 81.05 474 | 89.42 477 | 38.45 476 | 48.51 478 | 99.90 22 | 54.09 456 | 78.70 478 | 91.84 305 | 18.26 480 | 87.64 462 |
|
| PMVS |  | 49.05 23 | 53.75 443 | 51.34 447 | 60.97 461 | 40.80 487 | 34.68 488 | 74.82 476 | 89.62 476 | 37.55 477 | 28.67 483 | 72.12 472 | 7.09 486 | 81.63 477 | 43.17 478 | 68.21 456 | 66.59 475 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| test123 | | | 37.68 448 | 39.14 451 | 33.31 464 | 19.94 488 | 24.83 490 | 98.36 382 | 9.75 489 | 15.53 482 | 51.31 476 | 87.14 460 | 19.62 482 | 17.74 484 | 47.10 476 | 3.47 483 | 57.36 477 |
|
| testmvs | | | 40.60 447 | 44.45 450 | 29.05 465 | 19.49 489 | 14.11 491 | 99.68 214 | 18.47 488 | 20.74 481 | 64.59 466 | 98.48 264 | 10.95 485 | 17.09 485 | 56.66 474 | 11.01 481 | 55.94 478 |
|
| mmdepth | | | 0.00 453 | 0.00 456 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 0.00 486 | 0.00 489 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| monomultidepth | | | 0.00 453 | 0.00 456 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 0.00 486 | 0.00 489 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| test_blank | | | 0.00 453 | 0.00 456 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 0.02 485 | 0.00 489 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| eth-test2 | | | | | | 0.00 490 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 490 | | | | | | | | | | | |
|
| uanet_test | | | 0.00 453 | 0.00 456 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 0.00 486 | 0.00 489 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| DCPMVS | | | 0.00 453 | 0.00 456 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 0.00 486 | 0.00 489 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| cdsmvs_eth3d_5k | | | 23.43 449 | 31.24 452 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 98.09 230 | 0.00 485 | 0.00 486 | 99.67 113 | 83.37 299 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| pcd_1.5k_mvsjas | | | 7.60 452 | 10.13 455 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 0.00 486 | 91.20 173 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| sosnet-low-res | | | 0.00 453 | 0.00 456 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 0.00 486 | 0.00 489 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| sosnet | | | 0.00 453 | 0.00 456 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 0.00 486 | 0.00 489 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| uncertanet | | | 0.00 453 | 0.00 456 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 0.00 486 | 0.00 489 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| Regformer | | | 0.00 453 | 0.00 456 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 0.00 486 | 0.00 489 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| ab-mvs-re | | | 8.28 451 | 11.04 454 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 99.40 146 | 0.00 489 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| uanet | | | 0.00 453 | 0.00 456 | 0.00 467 | 0.00 490 | 0.00 492 | 0.00 479 | 0.00 491 | 0.00 485 | 0.00 486 | 0.00 486 | 0.00 489 | 0.00 486 | 0.00 485 | 0.00 484 | 0.00 482 |
|
| TestfortrainingZip | | | | | | | | 99.97 39 | | | | | | | | | |
|
| WAC-MVS | | | | | | | 90.97 342 | | | | | | | | 86.10 384 | | |
|
| PC_three_1452 | | | | | | | | | | 96.96 60 | 99.80 26 | 99.79 62 | 97.49 10 | 100.00 1 | 99.99 5 | 99.98 32 | 100.00 1 |
|
| test_241102_TWO | | | | | | | | | 98.43 155 | 97.27 47 | 99.80 26 | 99.94 4 | 97.18 23 | 100.00 1 | 100.00 1 | 100.00 1 | 100.00 1 |
|
| test_0728_THIRD | | | | | | | | | | 96.48 78 | 99.83 22 | 99.91 18 | 97.87 5 | 100.00 1 | 99.92 16 | 100.00 1 | 100.00 1 |
|
| GSMVS | | | | | | | | | | | | | | | | | 99.59 149 |
|
| sam_mvs1 | | | | | | | | | | | | | 94.72 74 | | | | 99.59 149 |
|
| sam_mvs | | | | | | | | | | | | | 94.25 94 | | | | |
|
| MTGPA |  | | | | | | | | 98.28 203 | | | | | | | | |
|
| test_post1 | | | | | | | | 95.78 446 | | | | 59.23 482 | 93.20 128 | 97.74 324 | 91.06 315 | | |
|
| test_post | | | | | | | | | | | | 63.35 479 | 94.43 82 | 98.13 303 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 91.70 440 | 95.12 59 | 97.95 315 | | | |
|
| MTMP | | | | | | | | 99.87 130 | 96.49 411 | | | | | | | | |
|
| test9_res | | | | | | | | | | | | | | | 99.71 48 | 99.99 21 | 100.00 1 |
|
| agg_prior2 | | | | | | | | | | | | | | | 99.48 63 | 100.00 1 | 100.00 1 |
|
| test_prior4 | | | | | | | 98.05 81 | 99.94 90 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 99.95 72 | | 95.78 104 | 99.73 45 | 99.76 72 | 96.00 40 | | 99.78 35 | 100.00 1 | |
|
| 旧先验2 | | | | | | | | 99.46 263 | | 94.21 164 | 99.85 18 | | | 99.95 84 | 96.96 196 | | |
|
| 新几何2 | | | | | | | | 99.40 267 | | | | | | | | | |
|
| 无先验 | | | | | | | | 99.49 255 | 98.71 78 | 93.46 197 | | | | 100.00 1 | 94.36 253 | | 99.99 24 |
|
| 原ACMM2 | | | | | | | | 99.90 114 | | | | | | | | | |
|
| testdata2 | | | | | | | | | | | | | | 99.99 39 | 90.54 328 | | |
|
| segment_acmp | | | | | | | | | | | | | 96.68 31 | | | | |
|
| testdata1 | | | | | | | | 99.28 289 | | 96.35 90 | | | | | | | |
|
| plane_prior5 | | | | | | | | | 97.87 254 | | | | | 98.37 284 | 97.79 167 | 89.55 316 | 94.52 328 |
|
| plane_prior4 | | | | | | | | | | | | 98.59 250 | | | | | |
|
| plane_prior3 | | | | | | | 91.64 330 | | | 96.63 73 | 93.01 288 | | | | | | |
|
| plane_prior2 | | | | | | | | 99.84 149 | | 96.38 84 | | | | | | | |
|
| plane_prior | | | | | | | 91.74 324 | 99.86 141 | | 96.76 68 | | | | | | 89.59 315 | |
|
| n2 | | | | | | | | | 0.00 491 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 491 | | | | | | | | |
|
| door-mid | | | | | | | | | 89.69 475 | | | | | | | | |
|
| test11 | | | | | | | | | 98.44 147 | | | | | | | | |
|
| door | | | | | | | | | 90.31 472 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 91.85 320 | | | | | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 97.92 158 | | |
|
| HQP4-MVS | | | | | | | | | | | 93.37 283 | | | 98.39 278 | | | 94.53 326 |
|
| HQP3-MVS | | | | | | | | | 97.89 252 | | | | | | | 89.60 313 | |
|
| HQP2-MVS | | | | | | | | | | | | | 80.65 330 | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 96.26 167 | 96.11 440 | | 91.89 273 | 98.06 166 | | 94.40 84 | | 94.30 256 | | 99.67 129 |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 87.04 349 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 88.23 336 | |
|
| Test By Simon | | | | | | | | | | | | | 92.82 139 | | | | |
|