| AdaColmap |  | | 97.23 130 | 96.80 139 | 98.51 132 | 99.99 1 | 95.60 200 | 99.09 308 | 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 | 95.77 189 | 99.96 53 | 98.35 189 | 89.90 339 | 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 | 92.06 271 | 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 | 96.62 152 | 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 | | | 93.83 274 | 92.06 309 | 99.15 70 | 99.94 16 | 97.50 110 | 99.94 90 | 98.42 167 | 96.22 92 | 99.41 84 | 41.37 485 | 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 | 96.13 178 | 99.82 160 | 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 | 99.64 223 | 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 | 92.34 259 | 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 | 99.75 185 | 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 | 96.13 178 | 99.18 301 | 99.45 18 | 94.84 131 | 96.41 230 | 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 | 99.24 296 | 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 | 97.27 231 | 99.89 49 | 91.92 322 | 99.90 114 | 99.07 37 | 88.67 363 | 95.26 262 | 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 | 95.39 210 | 99.61 230 | 97.78 265 | 96.52 76 | 98.61 138 | 99.31 156 | 92.73 141 | 99.67 167 | 96.77 204 | 99.48 121 | 99.06 243 |
|
| 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 | 90.78 318 | 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 | 99.39 273 | 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 | | | 95.84 205 | 95.11 219 | 98.02 166 | 99.85 60 | 95.10 228 | 98.74 358 | 98.50 136 | 87.22 385 | 93.66 283 | 99.86 33 | 87.45 235 | 99.95 84 | 90.94 321 | 99.81 87 | 99.02 248 |
|
| HPM-MVS |  | | 97.96 80 | 97.72 90 | 98.68 109 | 99.84 62 | 96.39 164 | 99.90 114 | 98.17 218 | 92.61 243 | 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 | 96.59 156 | 99.40 269 | 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 | 94.77 239 | 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 | 96.60 154 | 99.82 160 | 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 | 96.27 167 | 99.36 279 | 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 | 96.37 165 | 99.76 181 | 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 | 96.37 165 | 99.76 181 | 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 | 96.42 160 | 99.88 127 | 98.16 223 | 91.75 282 | 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 | 97.41 221 | 99.76 72 | 93.36 289 | 99.65 219 | 97.95 245 | 96.03 97 | 97.41 190 | 99.70 100 | 89.61 202 | 99.51 177 | 96.73 206 | 98.25 179 | 99.38 195 |
|
| 新几何1 | | | | | 99.42 42 | 99.75 75 | 98.27 70 | | 98.63 96 | 92.69 238 | 99.55 69 | 99.82 53 | 94.40 84 | 100.00 1 | 91.21 313 | 99.94 59 | 99.99 24 |
|
| MP-MVS-pluss | | | 98.07 78 | 97.64 96 | 99.38 48 | 99.74 76 | 98.41 68 | 99.74 188 | 98.18 217 | 93.35 201 | 96.45 226 | 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 | 99.77 175 | 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 | 95.11 234 | 99.95 54 | 99.92 92 |
|
| TSAR-MVS + GP. | | | 98.60 37 | 98.51 34 | 98.86 98 | 99.73 79 | 96.63 151 | 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 | 99.73 195 | 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 | 96.87 245 | 99.71 82 | 91.74 327 | 99.85 144 | 97.95 245 | 93.11 215 | 95.72 251 | 99.16 180 | 92.35 155 | 99.94 93 | 95.32 230 | 99.35 136 | 98.92 256 |
|
| reproduce-ours | | | 98.78 27 | 98.67 24 | 99.09 79 | 99.70 84 | 97.30 118 | 99.74 188 | 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 | 99.74 188 | 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 | 95.59 287 | 99.67 87 | 86.91 411 | 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 | 93.92 353 | 99.63 89 | 81.76 446 | 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 | 96.80 145 | 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 | 96.72 251 | 99.59 91 | 96.99 135 | 99.95 72 | 99.10 34 | 94.06 171 | 98.27 157 | 95.80 357 | 89.00 214 | 99.95 84 | 99.12 78 | 87.53 349 | 93.24 412 |
|
| 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 | 95.40 205 | 97.95 168 | 99.59 91 | 95.22 223 | 99.52 251 | 99.07 37 | 93.96 176 | 96.49 224 | 98.35 272 | 82.28 310 | 99.82 141 | 90.15 337 | 99.22 143 | 98.81 263 |
|
| dcpmvs_2 | | | 97.42 121 | 98.09 63 | 95.42 294 | 99.58 95 | 87.24 407 | 99.23 297 | 96.95 385 | 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 | 99.34 281 | 98.55 118 | 91.86 277 | 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 | 95.41 208 | 99.47 261 | 98.87 58 | 91.68 283 | 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 | 95.81 187 | 99.95 72 | 99.65 12 | 94.73 135 | 99.04 113 | 99.21 173 | 84.48 291 | 99.95 84 | 94.92 240 | 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 | 88.48 367 | 99.06 112 | 99.66 115 | 90.30 194 | 99.64 172 | 96.32 215 | 99.97 42 | 99.96 74 |
|
| cl22 | | | 93.77 279 | 93.25 283 | 95.33 298 | 99.49 101 | 94.43 249 | 99.61 230 | 98.09 230 | 90.38 327 | 89.16 354 | 95.61 365 | 90.56 189 | 97.34 339 | 91.93 304 | 84.45 371 | 94.21 357 |
|
| testdata | | | | | 98.42 141 | 99.47 102 | 95.33 214 | | 98.56 112 | 93.78 185 | 99.79 35 | 99.85 37 | 93.64 114 | 99.94 93 | 94.97 238 | 99.94 59 | 100.00 1 |
|
| MAR-MVS | | | 97.43 117 | 97.19 120 | 98.15 157 | 99.47 102 | 94.79 238 | 99.05 319 | 98.76 73 | 92.65 241 | 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 | | | 94.54 251 | 93.42 273 | 97.91 174 | 99.46 104 | 94.04 265 | 98.93 337 | 97.48 302 | 81.15 440 | 90.04 325 | 99.55 131 | 87.02 243 | 99.95 84 | 88.97 349 | 98.11 185 | 99.73 119 |
|
| MVS_111021_LR | | | 98.42 52 | 98.38 41 | 98.53 129 | 99.39 105 | 95.79 188 | 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 | 98.46 377 | 99.42 21 | 97.03 57 | 99.02 114 | 99.09 183 | 99.35 2 | 98.21 301 | 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 | 97.65 301 |
|
| 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 | 93.81 271 | 99.94 59 | 99.98 56 |
|
| TAPA-MVS | | 92.12 8 | 94.42 259 | 93.60 265 | 96.90 244 | 99.33 109 | 91.78 326 | 99.78 170 | 98.00 239 | 89.89 340 | 94.52 268 | 99.47 137 | 91.97 164 | 99.18 202 | 69.90 457 | 99.52 114 | 99.73 119 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| reproduce_monomvs | | | 95.38 223 | 95.07 221 | 96.32 266 | 99.32 111 | 96.60 154 | 99.76 181 | 98.85 62 | 96.65 72 | 87.83 376 | 96.05 354 | 99.52 1 | 98.11 306 | 96.58 210 | 81.07 400 | 94.25 351 |
|
| fmvsm_s_conf0.5_n_9 | | | 98.15 73 | 98.02 68 | 98.55 123 | 99.28 112 | 95.84 186 | 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 | 95.20 224 | 99.98 21 | 97.15 352 | 95.53 113 | 99.62 60 | 99.79 62 | 92.08 162 | 98.38 284 | 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 | 95.18 225 | 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 | 98.59 273 |
|
| 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 | 99.64 223 | 99.27 27 | 91.43 292 | 97.88 174 | 98.99 198 | 95.84 45 | 99.84 137 | 98.82 101 | 95.32 276 | 99.79 111 |
|
| DCV-MVSNet | | | 97.83 92 | 97.37 111 | 99.21 59 | 99.18 118 | 97.98 85 | 99.64 223 | 99.27 27 | 91.43 292 | 97.88 174 | 98.99 198 | 95.84 45 | 99.84 137 | 98.82 101 | 95.32 276 | 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 | 95.90 184 | 99.66 218 | 98.06 233 | 96.37 87 | 94.37 274 | 99.49 136 | 83.29 303 | 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 | 97.43 219 | 99.10 124 | 94.42 250 | 99.99 5 | 97.10 364 | 95.07 122 | 99.68 50 | 99.75 80 | 92.95 134 | 98.34 288 | 98.38 128 | 99.14 145 | 99.54 163 |
|
| Anonymous202405211 | | | 93.10 297 | 91.99 310 | 96.40 262 | 99.10 124 | 89.65 376 | 98.88 343 | 97.93 247 | 83.71 424 | 94.00 280 | 98.75 234 | 68.79 416 | 99.88 123 | 95.08 235 | 91.71 309 | 99.68 127 |
|
| fmvsm_s_conf0.5_n | | | 97.80 97 | 97.85 85 | 97.67 193 | 99.06 127 | 94.41 251 | 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 | 98.62 272 |
|
| HyFIR lowres test | | | 96.66 165 | 96.43 156 | 97.36 226 | 99.05 128 | 93.91 270 | 99.70 209 | 99.80 3 | 90.54 323 | 96.26 233 | 98.08 285 | 92.15 160 | 98.23 300 | 96.84 202 | 95.46 271 | 99.93 87 |
|
| LFMVS | | | 94.75 245 | 93.56 268 | 98.30 147 | 99.03 129 | 95.70 194 | 98.74 358 | 97.98 242 | 87.81 378 | 98.47 146 | 99.39 148 | 67.43 425 | 99.53 174 | 98.01 152 | 95.20 279 | 99.67 129 |
|
| fmvsm_s_conf0.5_n_4 | | | 97.75 102 | 97.86 84 | 97.42 220 | 99.01 130 | 94.69 241 | 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 | 97.64 302 |
|
| 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 | 81.83 316 | 99.94 93 | 99.78 35 | 98.79 161 | 97.51 310 |
|
| AllTest | | | 92.48 313 | 91.64 316 | 95.00 307 | 99.01 130 | 88.43 394 | 98.94 335 | 96.82 399 | 86.50 394 | 88.71 359 | 98.47 267 | 74.73 391 | 99.88 123 | 85.39 390 | 96.18 246 | 96.71 316 |
|
| TestCases | | | | | 95.00 307 | 99.01 130 | 88.43 394 | | 96.82 399 | 86.50 394 | 88.71 359 | 98.47 267 | 74.73 391 | 99.88 123 | 85.39 390 | 96.18 246 | 96.71 316 |
|
| COLMAP_ROB |  | 90.47 14 | 92.18 320 | 91.49 322 | 94.25 341 | 99.00 134 | 88.04 400 | 98.42 383 | 96.70 406 | 82.30 435 | 88.43 368 | 99.01 194 | 76.97 366 | 99.85 129 | 86.11 386 | 96.50 238 | 94.86 327 |
| 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 | 84.15 294 | 99.97 63 | 99.76 40 | 99.50 119 | 98.39 280 |
|
| test_fmvs1 | | | 95.35 224 | 95.68 196 | 94.36 337 | 98.99 135 | 84.98 422 | 99.96 53 | 96.65 408 | 97.60 34 | 99.73 45 | 98.96 204 | 71.58 406 | 99.93 103 | 98.31 134 | 99.37 134 | 98.17 285 |
|
| HY-MVS | | 92.50 7 | 97.79 99 | 97.17 122 | 99.63 18 | 98.98 137 | 99.32 9 | 97.49 412 | 99.52 14 | 95.69 108 | 98.32 155 | 97.41 305 | 93.32 121 | 99.77 149 | 98.08 149 | 95.75 261 | 99.81 108 |
|
| VNet | | | 97.21 131 | 96.57 150 | 99.13 76 | 98.97 138 | 97.82 94 | 99.03 322 | 99.21 32 | 94.31 158 | 99.18 102 | 98.88 216 | 86.26 256 | 99.89 117 | 98.93 92 | 94.32 289 | 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 | 96.26 233 | 98.88 216 | 89.87 199 | 99.51 177 | 94.26 259 | 94.91 281 | 99.31 212 |
|
| tfpn200view9 | | | 96.79 153 | 95.99 173 | 99.19 61 | 98.94 140 | 98.82 38 | 99.78 170 | 99.71 7 | 92.86 225 | 96.02 241 | 98.87 223 | 89.33 206 | 99.50 179 | 93.84 268 | 94.57 285 | 99.27 221 |
|
| thres400 | | | 96.78 155 | 95.99 173 | 99.16 68 | 98.94 140 | 98.82 38 | 99.78 170 | 99.71 7 | 92.86 225 | 96.02 241 | 98.87 223 | 89.33 206 | 99.50 179 | 93.84 268 | 94.57 285 | 99.16 231 |
|
| sasdasda | | | 97.09 138 | 96.32 160 | 99.39 45 | 98.93 142 | 98.95 28 | 99.72 199 | 97.35 315 | 94.45 146 | 97.88 174 | 99.42 141 | 86.71 247 | 99.52 175 | 98.48 123 | 93.97 295 | 99.72 121 |
|
| Anonymous20231211 | | | 89.86 370 | 88.44 378 | 94.13 344 | 98.93 142 | 90.68 354 | 98.54 374 | 98.26 206 | 76.28 452 | 86.73 390 | 95.54 369 | 70.60 412 | 97.56 332 | 90.82 324 | 80.27 409 | 94.15 365 |
|
| canonicalmvs | | | 97.09 138 | 96.32 160 | 99.39 45 | 98.93 142 | 98.95 28 | 99.72 199 | 97.35 315 | 94.45 146 | 97.88 174 | 99.42 141 | 86.71 247 | 99.52 175 | 98.48 123 | 93.97 295 | 99.72 121 |
|
| SDMVSNet | | | 94.80 240 | 93.96 255 | 97.33 229 | 98.92 145 | 95.42 207 | 99.59 235 | 98.99 40 | 92.41 255 | 92.55 298 | 97.85 296 | 75.81 381 | 98.93 220 | 97.90 160 | 91.62 310 | 97.64 302 |
|
| sd_testset | | | 93.55 286 | 92.83 290 | 95.74 285 | 98.92 145 | 90.89 350 | 98.24 391 | 98.85 62 | 92.41 255 | 92.55 298 | 97.85 296 | 71.07 411 | 98.68 253 | 93.93 265 | 91.62 310 | 97.64 302 |
|
| EPNet_dtu | | | 95.71 212 | 95.39 206 | 96.66 253 | 98.92 145 | 93.41 285 | 99.57 240 | 98.90 50 | 96.19 94 | 97.52 184 | 98.56 257 | 92.65 143 | 97.36 337 | 77.89 438 | 98.33 174 | 99.20 229 |
| 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 | 95.58 270 | 99.78 114 |
|
| CHOSEN 1792x2688 | | | 96.81 152 | 96.53 151 | 97.64 196 | 98.91 149 | 93.07 291 | 99.65 219 | 99.80 3 | 95.64 109 | 95.39 258 | 98.86 225 | 84.35 293 | 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 | 99.74 188 | 99.71 7 | 92.59 245 | 95.84 245 | 98.86 225 | 89.25 208 | 99.50 179 | 93.84 268 | 94.57 285 | 99.27 221 |
|
| thres600view7 | | | 96.69 163 | 95.87 188 | 99.14 72 | 98.90 150 | 98.78 45 | 99.74 188 | 99.71 7 | 92.59 245 | 95.84 245 | 98.86 225 | 89.25 208 | 99.50 179 | 93.44 281 | 94.50 288 | 99.16 231 |
|
| MSDG | | | 94.37 261 | 93.36 280 | 97.40 222 | 98.88 152 | 93.95 269 | 99.37 277 | 97.38 311 | 85.75 405 | 90.80 317 | 99.17 177 | 84.11 296 | 99.88 123 | 86.35 382 | 98.43 172 | 98.36 282 |
|
| MGCFI-Net | | | 97.00 143 | 96.22 165 | 99.34 50 | 98.86 153 | 98.80 40 | 99.67 217 | 97.30 327 | 94.31 158 | 97.77 180 | 99.41 145 | 86.36 254 | 99.50 179 | 98.38 128 | 93.90 297 | 99.72 121 |
|
| h-mvs33 | | | 94.92 237 | 94.36 241 | 96.59 255 | 98.85 154 | 91.29 342 | 98.93 337 | 98.94 44 | 95.90 99 | 98.77 127 | 98.42 270 | 90.89 184 | 99.77 149 | 97.80 164 | 70.76 448 | 98.72 269 |
|
| Anonymous20240529 | | | 92.10 321 | 90.65 333 | 96.47 257 | 98.82 155 | 90.61 356 | 98.72 360 | 98.67 86 | 75.54 456 | 93.90 282 | 98.58 255 | 66.23 429 | 99.90 112 | 94.70 249 | 90.67 313 | 98.90 259 |
|
| PVSNet_Blended_VisFu | | | 97.27 127 | 96.81 138 | 98.66 112 | 98.81 156 | 96.67 150 | 99.92 100 | 98.64 90 | 94.51 143 | 96.38 231 | 98.49 263 | 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 | 99.54 249 | 98.17 218 | 97.34 42 | 99.85 18 | 99.85 37 | 91.20 173 | 99.89 117 | 99.41 68 | 99.67 95 | 98.69 270 |
|
| CANet_DTU | | | 96.76 156 | 96.15 168 | 98.60 117 | 98.78 158 | 97.53 107 | 99.84 149 | 97.63 280 | 97.25 50 | 99.20 99 | 99.64 118 | 81.36 322 | 99.98 50 | 92.77 292 | 98.89 155 | 98.28 284 |
|
| mvsany_test1 | | | 97.82 95 | 97.90 80 | 97.55 207 | 98.77 159 | 93.04 294 | 99.80 166 | 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 | 94.26 291 | 99.67 129 |
|
| SymmetryMVS | | | 97.64 110 | 97.46 104 | 98.17 153 | 98.74 161 | 95.39 210 | 99.61 230 | 99.26 29 | 96.52 76 | 98.61 138 | 99.31 156 | 92.73 141 | 99.67 167 | 96.77 204 | 95.63 268 | 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 | 99.52 251 | 98.08 232 | 97.05 56 | 99.86 15 | 99.86 33 | 90.65 186 | 99.71 159 | 99.39 70 | 98.63 165 | 98.69 270 |
|
| miper_enhance_ethall | | | 94.36 263 | 93.98 254 | 95.49 288 | 98.68 164 | 95.24 221 | 99.73 195 | 97.29 332 | 93.28 205 | 89.86 330 | 95.97 355 | 94.37 88 | 97.05 360 | 92.20 296 | 84.45 371 | 94.19 358 |
|
| 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 | 91.10 304 | 98.17 163 | 98.59 252 | 93.86 108 | 98.19 302 | 95.64 227 | 95.24 278 | 99.28 219 |
|
| test2506 | | | 97.53 114 | 97.19 120 | 98.58 121 | 98.66 167 | 96.90 139 | 98.81 352 | 99.77 5 | 94.93 125 | 97.95 169 | 98.96 204 | 92.51 150 | 99.20 200 | 94.93 239 | 98.15 182 | 99.64 135 |
|
| ECVR-MVS |  | | 95.66 215 | 95.05 222 | 97.51 212 | 98.66 167 | 93.71 274 | 98.85 349 | 98.45 142 | 94.93 125 | 96.86 210 | 98.96 204 | 75.22 387 | 99.20 200 | 95.34 229 | 98.15 182 | 99.64 135 |
|
| mamv4 | | | 95.24 227 | 96.90 131 | 90.25 415 | 98.65 169 | 72.11 464 | 98.28 388 | 97.64 279 | 89.99 338 | 95.93 243 | 98.25 280 | 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 | 99.47 261 | 97.79 262 | 94.56 141 | 99.74 43 | 98.35 272 | 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 | 94.26 258 | 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 | 99.08 241 |
|
| MVSMamba_PlusPlus | | | 97.83 92 | 97.45 106 | 98.99 89 | 98.60 172 | 98.15 71 | 99.58 237 | 97.74 270 | 90.34 330 | 99.26 98 | 98.32 275 | 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 | 92.53 250 | 98.84 121 | 98.84 229 | 93.36 118 | 98.30 292 | 95.84 223 | 94.30 290 | 99.05 245 |
|
| test1111 | | | 95.57 218 | 94.98 225 | 97.37 224 | 98.56 173 | 93.37 288 | 98.86 347 | 98.45 142 | 94.95 124 | 96.63 216 | 98.95 209 | 75.21 388 | 99.11 206 | 95.02 236 | 98.14 184 | 99.64 135 |
|
| MVSTER | | | 95.53 219 | 95.22 214 | 96.45 260 | 98.56 173 | 97.72 98 | 99.91 108 | 97.67 275 | 92.38 258 | 91.39 308 | 97.14 312 | 97.24 20 | 97.30 344 | 94.80 245 | 87.85 342 | 94.34 346 |
|
| 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 | 98.73 236 | 95.50 52 | 99.69 163 | 98.53 121 | 94.63 283 | 98.99 250 |
|
| VDD-MVS | | | 93.77 279 | 92.94 288 | 96.27 267 | 98.55 176 | 90.22 365 | 98.77 357 | 97.79 262 | 90.85 310 | 96.82 212 | 99.42 141 | 61.18 449 | 99.77 149 | 98.95 90 | 94.13 292 | 98.82 262 |
|
| tpmvs | | | 94.28 265 | 93.57 267 | 96.40 262 | 98.55 176 | 91.50 340 | 95.70 449 | 98.55 118 | 87.47 380 | 92.15 301 | 94.26 421 | 91.42 169 | 98.95 219 | 88.15 361 | 95.85 257 | 98.76 265 |
|
| UGNet | | | 95.33 225 | 94.57 237 | 97.62 200 | 98.55 176 | 94.85 233 | 98.67 366 | 99.32 26 | 95.75 106 | 96.80 213 | 96.27 344 | 72.18 403 | 99.96 75 | 94.58 252 | 99.05 151 | 98.04 290 |
| 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 | 95.18 229 | 94.10 248 | 98.43 139 | 98.55 176 | 95.99 182 | 97.91 405 | 97.31 326 | 90.35 329 | 89.48 343 | 99.22 170 | 85.19 276 | 99.89 117 | 90.40 334 | 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 | | | 95.95 199 | 96.49 152 | 94.34 338 | 98.51 181 | 89.99 370 | 99.39 273 | 98.57 106 | 93.14 212 | 97.33 193 | 98.31 277 | 93.44 116 | 94.68 438 | 93.69 278 | 95.98 251 | 98.34 283 |
|
| UWE-MVS | | | 96.79 153 | 96.72 143 | 97.00 239 | 98.51 181 | 93.70 275 | 99.71 202 | 98.60 100 | 92.96 220 | 97.09 200 | 98.34 274 | 96.67 33 | 98.85 226 | 92.11 302 | 96.50 238 | 98.44 278 |
|
| 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 | 98.75 234 | 95.20 57 | 99.48 185 | 98.93 92 | 96.40 241 | 99.29 217 |
|
| test_vis1_n_1920 | | | 95.44 221 | 95.31 210 | 95.82 282 | 98.50 183 | 88.74 388 | 99.98 21 | 97.30 327 | 97.84 28 | 99.85 18 | 99.19 175 | 66.82 427 | 99.97 63 | 98.82 101 | 99.46 126 | 98.76 265 |
|
| BH-w/o | | | 95.71 212 | 95.38 208 | 96.68 252 | 98.49 185 | 92.28 313 | 99.84 149 | 97.50 300 | 92.12 268 | 92.06 304 | 98.79 232 | 84.69 287 | 98.67 255 | 95.29 231 | 99.66 96 | 99.09 239 |
|
| baseline1 | | | 95.78 208 | 94.86 228 | 98.54 127 | 98.47 186 | 98.07 79 | 99.06 315 | 97.99 240 | 92.68 239 | 94.13 279 | 98.62 249 | 93.28 124 | 98.69 252 | 93.79 273 | 85.76 358 | 98.84 261 |
|
| fmvsm_s_conf0.5_n_7 | | | 97.70 108 | 97.74 89 | 97.59 205 | 98.44 187 | 95.16 227 | 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 | 97.66 300 |
|
| EPMVS | | | 96.53 172 | 96.01 172 | 98.09 161 | 98.43 188 | 96.12 180 | 96.36 436 | 99.43 20 | 93.53 193 | 97.64 182 | 95.04 397 | 94.41 83 | 98.38 284 | 91.13 315 | 98.11 185 | 99.75 117 |
|
| kuosan | | | 93.17 294 | 92.60 296 | 94.86 314 | 98.40 189 | 89.54 378 | 98.44 379 | 98.53 125 | 84.46 419 | 88.49 364 | 97.92 293 | 90.57 188 | 97.05 360 | 83.10 407 | 93.49 300 | 97.99 291 |
|
| WBMVS | | | 94.52 254 | 94.03 252 | 95.98 273 | 98.38 190 | 96.68 149 | 99.92 100 | 97.63 280 | 90.75 319 | 89.64 338 | 95.25 390 | 96.77 27 | 96.90 372 | 94.35 257 | 83.57 378 | 94.35 344 |
|
| UBG | | | 97.84 91 | 97.69 93 | 98.29 148 | 98.38 190 | 96.59 156 | 99.90 114 | 98.53 125 | 93.91 180 | 98.52 142 | 98.42 270 | 96.77 27 | 99.17 203 | 98.54 119 | 96.20 245 | 99.11 238 |
|
| sss | | | 97.57 113 | 97.03 127 | 99.18 62 | 98.37 192 | 98.04 82 | 99.73 195 | 99.38 22 | 93.46 197 | 98.76 130 | 99.06 188 | 91.21 172 | 99.89 117 | 96.33 214 | 97.01 227 | 99.62 142 |
|
| testing11 | | | 97.48 116 | 97.27 116 | 98.10 160 | 98.36 193 | 96.02 181 | 99.92 100 | 98.45 142 | 93.45 199 | 98.15 164 | 98.70 239 | 95.48 53 | 99.22 196 | 97.85 162 | 95.05 280 | 99.07 242 |
|
| BH-untuned | | | 95.18 229 | 94.83 229 | 96.22 268 | 98.36 193 | 91.22 343 | 99.80 166 | 97.32 325 | 90.91 308 | 91.08 311 | 98.67 241 | 83.51 299 | 98.54 266 | 94.23 260 | 99.61 104 | 98.92 256 |
|
| testing91 | | | 97.16 133 | 96.90 131 | 97.97 167 | 98.35 195 | 95.67 197 | 99.91 108 | 98.42 167 | 92.91 223 | 97.33 193 | 98.72 237 | 94.81 71 | 99.21 197 | 96.98 194 | 94.63 283 | 99.03 247 |
|
| testing99 | | | 97.17 132 | 96.91 130 | 97.95 168 | 98.35 195 | 95.70 194 | 99.91 108 | 98.43 155 | 92.94 221 | 97.36 191 | 98.72 237 | 94.83 70 | 99.21 197 | 97.00 192 | 94.64 282 | 98.95 252 |
|
| ET-MVSNet_ETH3D | | | 94.37 261 | 93.28 282 | 97.64 196 | 98.30 197 | 97.99 84 | 99.99 5 | 97.61 286 | 94.35 155 | 71.57 462 | 99.45 140 | 96.23 38 | 95.34 428 | 96.91 200 | 85.14 365 | 99.59 149 |
|
| AUN-MVS | | | 93.28 291 | 92.60 296 | 95.34 297 | 98.29 198 | 90.09 368 | 99.31 285 | 98.56 112 | 91.80 281 | 96.35 232 | 98.00 288 | 89.38 205 | 98.28 295 | 92.46 293 | 69.22 454 | 97.64 302 |
|
| FMVSNet3 | | | 92.69 308 | 91.58 318 | 95.99 272 | 98.29 198 | 97.42 115 | 99.26 295 | 97.62 283 | 89.80 341 | 89.68 334 | 95.32 384 | 81.62 320 | 96.27 404 | 87.01 378 | 85.65 359 | 94.29 348 |
|
| PMMVS | | | 96.76 156 | 96.76 140 | 96.76 249 | 98.28 200 | 92.10 317 | 99.91 108 | 97.98 242 | 94.12 166 | 99.53 72 | 99.39 148 | 86.93 245 | 98.73 245 | 96.95 197 | 97.73 193 | 99.45 186 |
|
| hse-mvs2 | | | 94.38 260 | 94.08 251 | 95.31 299 | 98.27 201 | 90.02 369 | 99.29 291 | 98.56 112 | 95.90 99 | 98.77 127 | 98.00 288 | 90.89 184 | 98.26 299 | 97.80 164 | 69.20 455 | 97.64 302 |
|
| PVSNet_0 | | 88.03 19 | 91.80 328 | 90.27 342 | 96.38 264 | 98.27 201 | 90.46 360 | 99.94 90 | 99.61 13 | 93.99 174 | 86.26 400 | 97.39 307 | 71.13 410 | 99.89 117 | 98.77 105 | 67.05 461 | 98.79 264 |
|
| UA-Net | | | 96.54 171 | 95.96 179 | 98.27 149 | 98.23 203 | 95.71 193 | 98.00 403 | 98.45 142 | 93.72 189 | 98.41 150 | 99.27 162 | 88.71 219 | 99.66 170 | 91.19 314 | 97.69 194 | 99.44 189 |
|
| test_cas_vis1_n_1920 | | | 96.59 168 | 96.23 163 | 97.65 195 | 98.22 204 | 94.23 259 | 99.99 5 | 97.25 337 | 97.77 29 | 99.58 68 | 99.08 184 | 77.10 361 | 99.97 63 | 97.64 172 | 99.45 127 | 98.74 267 |
|
| FE-MVS | | | 95.70 214 | 95.01 224 | 97.79 182 | 98.21 205 | 94.57 243 | 95.03 450 | 98.69 81 | 88.90 357 | 97.50 186 | 96.19 346 | 92.60 146 | 99.49 184 | 89.99 339 | 97.94 191 | 99.31 212 |
|
| GG-mvs-BLEND | | | | | 98.54 127 | 98.21 205 | 98.01 83 | 93.87 455 | 98.52 127 | | 97.92 170 | 97.92 293 | 99.02 3 | 97.94 319 | 98.17 142 | 99.58 109 | 99.67 129 |
|
| mvs_anonymous | | | 95.65 216 | 95.03 223 | 97.53 209 | 98.19 207 | 95.74 191 | 99.33 282 | 97.49 301 | 90.87 309 | 90.47 320 | 97.10 314 | 88.23 222 | 97.16 351 | 95.92 221 | 97.66 197 | 99.68 127 |
|
| MVS_Test | | | 96.46 174 | 95.74 192 | 98.61 116 | 98.18 208 | 97.23 122 | 99.31 285 | 97.15 352 | 91.07 305 | 98.84 121 | 97.05 318 | 88.17 223 | 98.97 216 | 94.39 254 | 97.50 199 | 99.61 146 |
|
| BH-RMVSNet | | | 95.18 229 | 94.31 244 | 97.80 180 | 98.17 209 | 95.23 222 | 99.76 181 | 97.53 296 | 92.52 251 | 94.27 277 | 99.25 168 | 76.84 368 | 98.80 235 | 90.89 323 | 99.54 111 | 99.35 203 |
|
| dongtai | | | 91.55 334 | 91.13 327 | 92.82 383 | 98.16 210 | 86.35 412 | 99.47 261 | 98.51 130 | 83.24 427 | 85.07 410 | 97.56 301 | 90.33 193 | 94.94 434 | 76.09 446 | 91.73 308 | 97.18 313 |
|
| RPSCF | | | 91.80 328 | 92.79 292 | 88.83 427 | 98.15 211 | 69.87 466 | 98.11 399 | 96.60 410 | 83.93 422 | 94.33 275 | 99.27 162 | 79.60 344 | 99.46 188 | 91.99 303 | 93.16 305 | 97.18 313 |
|
| ETV-MVS | | | 97.92 84 | 97.80 88 | 98.25 150 | 98.14 212 | 96.48 158 | 99.98 21 | 97.63 280 | 95.61 110 | 99.29 95 | 99.46 139 | 92.55 148 | 98.82 230 | 99.02 88 | 98.54 169 | 99.46 181 |
|
| IS-MVSNet | | | 96.29 187 | 95.90 186 | 97.45 215 | 98.13 213 | 94.80 237 | 99.08 310 | 97.61 286 | 92.02 273 | 95.54 256 | 98.96 204 | 90.64 187 | 98.08 308 | 93.73 276 | 97.41 203 | 99.47 179 |
|
| test_fmvsmconf_n | | | 98.43 51 | 98.32 47 | 98.78 102 | 98.12 214 | 96.41 161 | 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 | 97.76 269 | 98.05 20 | 99.65 53 | 99.58 127 | 80.88 329 | 99.93 103 | 99.59 56 | 98.17 180 | 97.29 311 |
|
| ab-mvs | | | 94.69 246 | 93.42 273 | 98.51 132 | 98.07 216 | 96.26 168 | 96.49 434 | 98.68 83 | 90.31 331 | 94.54 267 | 97.00 320 | 76.30 376 | 99.71 159 | 95.98 220 | 93.38 303 | 99.56 158 |
|
| XVG-OURS-SEG-HR | | | 94.79 241 | 94.70 236 | 95.08 304 | 98.05 217 | 89.19 380 | 99.08 310 | 97.54 294 | 93.66 190 | 94.87 265 | 99.58 127 | 78.78 352 | 99.79 144 | 97.31 180 | 93.40 302 | 96.25 320 |
|
| EIA-MVS | | | 97.53 114 | 97.46 104 | 97.76 188 | 98.04 218 | 94.84 234 | 99.98 21 | 97.61 286 | 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 | | | 94.82 238 | 94.74 235 | 95.06 305 | 98.00 219 | 89.19 380 | 99.08 310 | 97.55 292 | 94.10 167 | 94.71 266 | 99.62 122 | 80.51 335 | 99.74 155 | 96.04 219 | 93.06 307 | 96.25 320 |
|
| mvsmamba | | | 96.94 146 | 96.73 142 | 97.55 207 | 97.99 220 | 94.37 255 | 99.62 226 | 97.70 272 | 93.13 213 | 98.42 149 | 97.92 293 | 88.02 224 | 98.75 243 | 98.78 104 | 99.01 152 | 99.52 169 |
|
| dp | | | 95.05 232 | 94.43 239 | 96.91 242 | 97.99 220 | 92.73 302 | 96.29 439 | 97.98 242 | 89.70 342 | 95.93 243 | 94.67 411 | 93.83 110 | 98.45 272 | 86.91 381 | 96.53 237 | 99.54 163 |
|
| tpmrst | | | 96.27 189 | 95.98 175 | 97.13 234 | 97.96 222 | 93.15 290 | 96.34 437 | 98.17 218 | 92.07 269 | 98.71 133 | 95.12 394 | 93.91 105 | 98.73 245 | 94.91 242 | 96.62 235 | 99.50 175 |
|
| TR-MVS | | | 94.54 251 | 93.56 268 | 97.49 214 | 97.96 222 | 94.34 256 | 98.71 361 | 97.51 299 | 90.30 332 | 94.51 269 | 98.69 240 | 75.56 382 | 98.77 239 | 92.82 291 | 95.99 250 | 99.35 203 |
|
| Vis-MVSNet (Re-imp) | | | 96.32 184 | 95.98 175 | 97.35 228 | 97.93 224 | 94.82 236 | 99.47 261 | 98.15 226 | 91.83 278 | 95.09 263 | 99.11 182 | 91.37 171 | 97.47 335 | 93.47 280 | 97.43 200 | 99.74 118 |
|
| MDTV_nov1_ep13 | | | | 95.69 194 | | 97.90 225 | 94.15 262 | 95.98 445 | 98.44 147 | 93.12 214 | 97.98 168 | 95.74 359 | 95.10 60 | 98.58 262 | 90.02 338 | 96.92 229 | |
|
| Fast-Effi-MVS+ | | | 95.02 234 | 94.19 246 | 97.52 211 | 97.88 226 | 94.55 244 | 99.97 39 | 97.08 368 | 88.85 359 | 94.47 270 | 97.96 292 | 84.59 288 | 98.41 276 | 89.84 341 | 97.10 220 | 99.59 149 |
|
| ADS-MVSNet2 | | | 93.80 278 | 93.88 258 | 93.55 366 | 97.87 227 | 85.94 416 | 94.24 451 | 96.84 396 | 90.07 335 | 96.43 228 | 94.48 416 | 90.29 195 | 95.37 427 | 87.44 368 | 97.23 211 | 99.36 199 |
|
| ADS-MVSNet | | | 94.79 241 | 94.02 253 | 97.11 236 | 97.87 227 | 93.79 271 | 94.24 451 | 98.16 223 | 90.07 335 | 96.43 228 | 94.48 416 | 90.29 195 | 98.19 302 | 87.44 368 | 97.23 211 | 99.36 199 |
|
| Effi-MVS+ | | | 96.30 186 | 95.69 194 | 98.16 154 | 97.85 229 | 96.26 168 | 97.41 414 | 97.21 344 | 90.37 328 | 98.65 136 | 98.58 255 | 86.61 251 | 98.70 251 | 97.11 188 | 97.37 205 | 99.52 169 |
|
| PatchmatchNet |  | | 95.94 200 | 95.45 202 | 97.39 223 | 97.83 230 | 94.41 251 | 96.05 443 | 98.40 176 | 92.86 225 | 97.09 200 | 95.28 389 | 94.21 97 | 98.07 310 | 89.26 347 | 98.11 185 | 99.70 124 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| cascas | | | 94.64 249 | 93.61 263 | 97.74 190 | 97.82 231 | 96.26 168 | 99.96 53 | 97.78 265 | 85.76 403 | 94.00 280 | 97.54 302 | 76.95 367 | 99.21 197 | 97.23 185 | 95.43 273 | 97.76 299 |
|
| 1112_ss | | | 96.01 197 | 95.20 215 | 98.42 141 | 97.80 232 | 96.41 161 | 99.65 219 | 96.66 407 | 92.71 236 | 92.88 294 | 99.40 146 | 92.16 159 | 99.30 192 | 91.92 305 | 93.66 298 | 99.55 159 |
|
| E3new | | | 96.75 158 | 96.43 156 | 97.71 191 | 97.79 233 | 94.83 235 | 99.80 166 | 97.33 319 | 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 | | | 95.72 210 | 94.83 229 | 98.42 141 | 97.79 233 | 96.41 161 | 99.65 219 | 96.65 408 | 92.70 237 | 92.86 295 | 96.13 350 | 92.15 160 | 99.30 192 | 91.88 306 | 93.64 299 | 99.55 159 |
|
| Effi-MVS+-dtu | | | 94.53 253 | 95.30 211 | 92.22 391 | 97.77 235 | 82.54 439 | 99.59 235 | 97.06 372 | 94.92 127 | 95.29 260 | 95.37 382 | 85.81 262 | 97.89 320 | 94.80 245 | 97.07 221 | 96.23 322 |
|
| tpm cat1 | | | 93.51 287 | 92.52 302 | 96.47 257 | 97.77 235 | 91.47 341 | 96.13 441 | 98.06 233 | 80.98 441 | 92.91 293 | 93.78 425 | 89.66 200 | 98.87 224 | 87.03 377 | 96.39 242 | 99.09 239 |
|
| FA-MVS(test-final) | | | 95.86 203 | 95.09 220 | 98.15 157 | 97.74 237 | 95.62 199 | 96.31 438 | 98.17 218 | 91.42 294 | 96.26 233 | 96.13 350 | 90.56 189 | 99.47 187 | 92.18 297 | 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 | 99.31 285 | 97.86 256 | 96.43 81 | 99.62 60 | 99.69 104 | 85.56 269 | 99.68 164 | 99.05 81 | 98.31 175 | 97.83 295 |
|
| xiu_mvs_v1_base | | | 97.43 117 | 97.06 123 | 98.55 123 | 97.74 237 | 98.14 73 | 99.31 285 | 97.86 256 | 96.43 81 | 99.62 60 | 99.69 104 | 85.56 269 | 99.68 164 | 99.05 81 | 98.31 175 | 97.83 295 |
|
| xiu_mvs_v1_base_debi | | | 97.43 117 | 97.06 123 | 98.55 123 | 97.74 237 | 98.14 73 | 99.31 285 | 97.86 256 | 96.43 81 | 99.62 60 | 99.69 104 | 85.56 269 | 99.68 164 | 99.05 81 | 98.31 175 | 97.83 295 |
|
| EPP-MVSNet | | | 96.69 163 | 96.60 148 | 96.96 241 | 97.74 237 | 93.05 293 | 99.37 277 | 98.56 112 | 88.75 361 | 95.83 247 | 99.01 194 | 96.01 39 | 98.56 264 | 96.92 198 | 97.20 213 | 99.25 224 |
|
| gg-mvs-nofinetune | | | 93.51 287 | 91.86 314 | 98.47 134 | 97.72 242 | 97.96 88 | 92.62 461 | 98.51 130 | 74.70 459 | 97.33 193 | 69.59 476 | 98.91 4 | 97.79 323 | 97.77 169 | 99.56 110 | 99.67 129 |
|
| IB-MVS | | 92.85 6 | 94.99 235 | 93.94 256 | 98.16 154 | 97.72 242 | 95.69 196 | 99.99 5 | 98.81 67 | 94.28 161 | 92.70 296 | 96.90 322 | 95.08 61 | 99.17 203 | 96.07 218 | 73.88 441 | 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 | 91.83 278 | 97.45 188 | 99.04 190 | 97.50 9 | 99.10 208 | 94.75 247 | 96.37 243 | 99.16 231 |
|
| VortexMVS | | | 94.11 267 | 93.50 270 | 95.94 275 | 97.70 245 | 96.61 153 | 99.35 280 | 97.18 347 | 93.52 195 | 89.57 341 | 95.74 359 | 87.55 232 | 96.97 368 | 95.76 226 | 85.13 366 | 94.23 353 |
|
| viewdifsd2359ckpt09 | | | 96.21 191 | 95.77 190 | 97.53 209 | 97.69 246 | 94.50 247 | 99.78 170 | 97.23 342 | 92.88 224 | 96.58 219 | 99.26 166 | 84.85 281 | 98.66 258 | 96.61 208 | 97.02 226 | 99.43 190 |
|
| Syy-MVS | | | 90.00 368 | 90.63 334 | 88.11 434 | 97.68 247 | 74.66 462 | 99.71 202 | 98.35 189 | 90.79 316 | 92.10 302 | 98.67 241 | 79.10 350 | 93.09 454 | 63.35 469 | 95.95 254 | 96.59 318 |
|
| myMVS_eth3d | | | 94.46 258 | 94.76 234 | 93.55 366 | 97.68 247 | 90.97 345 | 99.71 202 | 98.35 189 | 90.79 316 | 92.10 302 | 98.67 241 | 92.46 153 | 93.09 454 | 87.13 374 | 95.95 254 | 96.59 318 |
|
| test_fmvs1_n | | | 94.25 266 | 94.36 241 | 93.92 353 | 97.68 247 | 83.70 429 | 99.90 114 | 96.57 411 | 97.40 40 | 99.67 51 | 98.88 216 | 61.82 446 | 99.92 109 | 98.23 140 | 99.13 146 | 98.14 288 |
|
| 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 | 94.92 232 | 99.27 294 | 97.10 364 | 92.79 231 | 97.43 189 | 97.99 290 | 81.85 315 | 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 | 96.17 177 | 99.81 162 | 97.19 345 | 94.67 139 | 98.95 116 | 99.28 159 | 86.43 252 | 98.76 241 | 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 | 94.70 240 | 99.77 175 | 97.33 319 | 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 | 94.40 253 | 99.70 209 | 97.23 342 | 92.76 233 | 96.63 216 | 99.05 189 | 84.96 280 | 98.64 259 | 96.65 207 | 97.35 206 | 99.31 212 |
|
| Vis-MVSNet |  | | 95.72 210 | 95.15 218 | 97.45 215 | 97.62 254 | 94.28 257 | 99.28 292 | 98.24 209 | 94.27 163 | 96.84 211 | 98.94 211 | 79.39 345 | 98.76 241 | 93.25 282 | 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 | 96.70 146 | 99.92 100 | 98.54 122 | 91.11 303 | 97.07 202 | 98.97 202 | 97.47 12 | 99.03 211 | 93.73 276 | 96.09 248 | 98.92 256 |
|
| GDP-MVS | | | 97.88 86 | 97.59 100 | 98.75 105 | 97.59 257 | 97.81 95 | 99.95 72 | 97.37 314 | 94.44 149 | 99.08 107 | 99.58 127 | 97.13 25 | 99.08 209 | 94.99 237 | 98.17 180 | 99.37 197 |
|
| miper_ehance_all_eth | | | 93.16 295 | 92.60 296 | 94.82 315 | 97.57 258 | 93.56 280 | 99.50 255 | 97.07 371 | 88.75 361 | 88.85 358 | 95.52 371 | 90.97 180 | 96.74 382 | 90.77 325 | 84.45 371 | 94.17 359 |
|
| guyue | | | 97.15 134 | 96.82 137 | 98.15 157 | 97.56 259 | 96.25 172 | 99.71 202 | 97.84 259 | 95.75 106 | 98.13 165 | 98.65 244 | 87.58 231 | 98.82 230 | 98.29 136 | 97.91 192 | 99.36 199 |
|
| viewmanbaseed2359cas | | | 96.45 175 | 96.07 169 | 97.59 205 | 97.55 260 | 94.59 242 | 99.70 209 | 97.33 319 | 93.62 192 | 97.00 206 | 99.32 153 | 85.57 268 | 98.71 248 | 97.26 184 | 97.33 207 | 99.47 179 |
|
| testing3 | | | 93.92 272 | 94.23 245 | 92.99 380 | 97.54 261 | 90.23 364 | 99.99 5 | 99.16 33 | 90.57 322 | 91.33 310 | 98.63 248 | 92.99 132 | 92.52 458 | 82.46 411 | 95.39 274 | 96.22 323 |
|
| SSM_0404 | | | 95.75 209 | 95.16 217 | 97.50 213 | 97.53 262 | 95.39 210 | 99.11 306 | 97.25 337 | 90.81 312 | 95.27 261 | 98.83 230 | 84.74 284 | 98.67 255 | 95.24 232 | 97.69 194 | 98.45 277 |
|
| LCM-MVSNet-Re | | | 92.31 317 | 92.60 296 | 91.43 400 | 97.53 262 | 79.27 456 | 99.02 324 | 91.83 471 | 92.07 269 | 80.31 434 | 94.38 419 | 83.50 300 | 95.48 424 | 97.22 186 | 97.58 198 | 99.54 163 |
|
| GBi-Net | | | 90.88 345 | 89.82 351 | 94.08 345 | 97.53 262 | 91.97 318 | 98.43 380 | 96.95 385 | 87.05 386 | 89.68 334 | 94.72 407 | 71.34 407 | 96.11 410 | 87.01 378 | 85.65 359 | 94.17 359 |
|
| test1 | | | 90.88 345 | 89.82 351 | 94.08 345 | 97.53 262 | 91.97 318 | 98.43 380 | 96.95 385 | 87.05 386 | 89.68 334 | 94.72 407 | 71.34 407 | 96.11 410 | 87.01 378 | 85.65 359 | 94.17 359 |
|
| FMVSNet2 | | | 91.02 342 | 89.56 356 | 95.41 295 | 97.53 262 | 95.74 191 | 98.98 327 | 97.41 309 | 87.05 386 | 88.43 368 | 95.00 401 | 71.34 407 | 96.24 406 | 85.12 393 | 85.21 364 | 94.25 351 |
|
| tttt0517 | | | 96.85 150 | 96.49 152 | 97.92 172 | 97.48 267 | 95.89 185 | 99.85 144 | 98.54 122 | 90.72 320 | 96.63 216 | 98.93 214 | 97.47 12 | 99.02 212 | 93.03 289 | 95.76 260 | 98.85 260 |
|
| 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 | 95.47 203 | 99.86 141 | 97.29 332 | 93.35 201 | 96.03 240 | 99.19 175 | 85.39 273 | 98.72 247 | 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 | 94.52 245 | 99.71 202 | 97.33 319 | 93.20 207 | 97.02 203 | 99.07 186 | 85.37 274 | 98.82 230 | 97.27 181 | 97.14 217 | 99.46 181 |
|
| EC-MVSNet | | | 97.38 124 | 97.24 117 | 97.80 180 | 97.41 270 | 95.64 198 | 99.99 5 | 97.06 372 | 94.59 140 | 99.63 57 | 99.32 153 | 89.20 211 | 98.14 304 | 98.76 106 | 99.23 142 | 99.62 142 |
|
| viewdifsd2359ckpt07 | | | 95.83 206 | 95.42 204 | 97.07 237 | 97.40 272 | 93.04 294 | 99.60 233 | 97.24 340 | 92.39 257 | 96.09 239 | 99.14 181 | 83.07 306 | 98.93 220 | 97.02 191 | 96.87 230 | 99.23 227 |
|
| c3_l | | | 92.53 312 | 91.87 313 | 94.52 327 | 97.40 272 | 92.99 296 | 99.40 269 | 96.93 390 | 87.86 376 | 88.69 361 | 95.44 376 | 89.95 198 | 96.44 396 | 90.45 331 | 80.69 405 | 94.14 368 |
|
| viewmambaseed2359dif | | | 95.92 202 | 95.55 200 | 97.04 238 | 97.38 274 | 93.41 285 | 99.78 170 | 96.97 383 | 91.14 302 | 96.58 219 | 99.27 162 | 84.85 281 | 98.75 243 | 96.87 201 | 97.12 219 | 98.97 251 |
|
| fmvsm_s_conf0.1_n | | | 97.30 125 | 97.21 119 | 97.60 202 | 97.38 274 | 94.40 253 | 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 | 98.46 276 |
|
| E3 | | | 96.36 181 | 95.95 181 | 97.60 202 | 97.37 276 | 94.52 245 | 99.71 202 | 97.33 319 | 93.18 209 | 97.02 203 | 99.07 186 | 85.45 272 | 98.82 230 | 97.27 181 | 97.14 217 | 99.46 181 |
|
| CDS-MVSNet | | | 96.34 183 | 96.07 169 | 97.13 234 | 97.37 276 | 94.96 230 | 99.53 250 | 97.91 251 | 91.55 286 | 95.37 259 | 98.32 275 | 95.05 63 | 97.13 354 | 93.80 272 | 95.75 261 | 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 | 96.48 158 | 99.96 53 | 98.29 202 | 91.93 274 | 95.77 248 | 98.07 286 | 95.54 49 | 98.29 293 | 90.55 329 | 98.89 155 | 99.70 124 |
|
| miper_lstm_enhance | | | 91.81 325 | 91.39 324 | 93.06 379 | 97.34 279 | 89.18 382 | 99.38 275 | 96.79 401 | 86.70 393 | 87.47 382 | 95.22 391 | 90.00 197 | 95.86 419 | 88.26 358 | 81.37 394 | 94.15 365 |
|
| baseline | | | 96.43 176 | 95.98 175 | 97.76 188 | 97.34 279 | 95.17 226 | 99.51 253 | 97.17 349 | 93.92 179 | 96.90 209 | 99.28 159 | 85.37 274 | 98.64 259 | 97.50 176 | 96.86 232 | 99.46 181 |
|
| cl____ | | | 92.31 317 | 91.58 318 | 94.52 327 | 97.33 281 | 92.77 298 | 99.57 240 | 96.78 402 | 86.97 390 | 87.56 380 | 95.51 372 | 89.43 204 | 96.62 388 | 88.60 352 | 82.44 386 | 94.16 364 |
|
| SD_0403 | | | 92.63 311 | 93.38 277 | 90.40 414 | 97.32 282 | 77.91 458 | 97.75 410 | 98.03 238 | 91.89 275 | 90.83 316 | 98.29 279 | 82.00 312 | 93.79 447 | 88.51 356 | 95.75 261 | 99.52 169 |
|
| DIV-MVS_self_test | | | 92.32 316 | 91.60 317 | 94.47 331 | 97.31 283 | 92.74 300 | 99.58 237 | 96.75 403 | 86.99 389 | 87.64 378 | 95.54 369 | 89.55 203 | 96.50 393 | 88.58 353 | 82.44 386 | 94.17 359 |
|
| casdiffmvs |  | | 96.42 178 | 95.97 178 | 97.77 186 | 97.30 284 | 94.98 229 | 99.84 149 | 97.09 367 | 93.75 188 | 96.58 219 | 99.26 166 | 85.07 277 | 98.78 238 | 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 | | | 94.36 263 | 93.48 271 | 96.99 240 | 97.29 285 | 93.54 281 | 99.96 53 | 96.72 405 | 88.35 370 | 93.43 284 | 98.94 211 | 82.05 311 | 98.05 311 | 88.12 363 | 96.48 240 | 99.37 197 |
|
| eth_miper_zixun_eth | | | 92.41 315 | 91.93 311 | 93.84 357 | 97.28 286 | 90.68 354 | 98.83 350 | 96.97 383 | 88.57 366 | 89.19 353 | 95.73 362 | 89.24 210 | 96.69 386 | 89.97 340 | 81.55 392 | 94.15 365 |
|
| MVSFormer | | | 96.94 146 | 96.60 148 | 97.95 168 | 97.28 286 | 97.70 101 | 99.55 247 | 97.27 334 | 91.17 299 | 99.43 82 | 99.54 133 | 90.92 181 | 96.89 373 | 94.67 250 | 99.62 100 | 99.25 224 |
|
| lupinMVS | | | 97.85 90 | 97.60 98 | 98.62 115 | 97.28 286 | 97.70 101 | 99.99 5 | 97.55 292 | 95.50 115 | 99.43 82 | 99.67 113 | 90.92 181 | 98.71 248 | 98.40 127 | 99.62 100 | 99.45 186 |
|
| diffmvs_AUTHOR | | | 96.75 158 | 96.41 158 | 97.79 182 | 97.20 289 | 95.46 204 | 99.69 212 | 97.15 352 | 94.46 145 | 98.78 125 | 99.21 173 | 85.64 266 | 98.77 239 | 98.27 137 | 97.31 209 | 99.13 235 |
|
| mamba_0408 | | | 94.98 236 | 94.09 249 | 97.64 196 | 97.14 290 | 95.31 215 | 93.48 458 | 97.08 368 | 90.48 324 | 94.40 271 | 98.62 249 | 84.49 289 | 98.67 255 | 93.99 263 | 97.18 214 | 98.93 253 |
|
| SSM_04072 | | | 94.77 243 | 94.09 249 | 96.82 246 | 97.14 290 | 95.31 215 | 93.48 458 | 97.08 368 | 90.48 324 | 94.40 271 | 98.62 249 | 84.49 289 | 96.21 407 | 93.99 263 | 97.18 214 | 98.93 253 |
|
| SSM_0407 | | | 95.62 217 | 94.95 226 | 97.61 201 | 97.14 290 | 95.31 215 | 99.00 325 | 97.25 337 | 90.81 312 | 94.40 271 | 98.83 230 | 84.74 284 | 98.58 262 | 95.24 232 | 97.18 214 | 98.93 253 |
|
| SCA | | | 94.69 246 | 93.81 260 | 97.33 229 | 97.10 293 | 94.44 248 | 98.86 347 | 98.32 196 | 93.30 204 | 96.17 238 | 95.59 367 | 76.48 374 | 97.95 317 | 91.06 317 | 97.43 200 | 99.59 149 |
|
| viewmacassd2359aftdt | | | 95.93 201 | 95.45 202 | 97.36 226 | 97.09 294 | 94.12 264 | 99.57 240 | 97.26 336 | 93.05 218 | 96.50 223 | 99.17 177 | 82.76 307 | 98.68 253 | 96.61 208 | 97.04 223 | 99.28 219 |
|
| KinetiMVS | | | 96.10 193 | 95.29 212 | 98.53 129 | 97.08 295 | 97.12 128 | 99.56 244 | 98.12 229 | 94.78 132 | 98.44 147 | 98.94 211 | 80.30 339 | 99.39 190 | 91.56 310 | 98.79 161 | 99.06 243 |
|
| TAMVS | | | 95.85 204 | 95.58 198 | 96.65 254 | 97.07 296 | 93.50 282 | 99.17 302 | 97.82 261 | 91.39 296 | 95.02 264 | 98.01 287 | 92.20 158 | 97.30 344 | 93.75 275 | 95.83 258 | 99.14 234 |
|
| Fast-Effi-MVS+-dtu | | | 93.72 282 | 93.86 259 | 93.29 371 | 97.06 297 | 86.16 413 | 99.80 166 | 96.83 397 | 92.66 240 | 92.58 297 | 97.83 298 | 81.39 321 | 97.67 328 | 89.75 342 | 96.87 230 | 96.05 325 |
|
| E4 | | | 96.01 197 | 95.53 201 | 97.44 218 | 97.05 298 | 94.23 259 | 99.57 240 | 97.30 327 | 92.72 234 | 96.47 225 | 99.03 191 | 83.98 297 | 98.83 227 | 96.92 198 | 96.77 233 | 99.27 221 |
|
| CostFormer | | | 96.10 193 | 95.88 187 | 96.78 248 | 97.03 299 | 92.55 308 | 97.08 423 | 97.83 260 | 90.04 337 | 98.72 132 | 94.89 405 | 95.01 65 | 98.29 293 | 96.54 211 | 95.77 259 | 99.50 175 |
|
| test_fmvsmvis_n_1920 | | | 97.67 109 | 97.59 100 | 97.91 174 | 97.02 300 | 95.34 213 | 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 | 98.42 279 |
|
| test-LLR | | | 96.47 173 | 96.04 171 | 97.78 184 | 97.02 300 | 95.44 205 | 99.96 53 | 98.21 213 | 94.07 169 | 95.55 254 | 96.38 339 | 93.90 106 | 98.27 297 | 90.42 332 | 98.83 159 | 99.64 135 |
|
| test-mter | | | 96.39 179 | 95.93 184 | 97.78 184 | 97.02 300 | 95.44 205 | 99.96 53 | 98.21 213 | 91.81 280 | 95.55 254 | 96.38 339 | 95.17 58 | 98.27 297 | 90.42 332 | 98.83 159 | 99.64 135 |
|
| E6 | | | 95.83 206 | 95.39 206 | 97.14 233 | 97.00 303 | 93.58 278 | 99.31 285 | 97.30 327 | 92.57 247 | 96.45 226 | 99.01 194 | 83.44 301 | 98.81 234 | 96.80 203 | 96.66 234 | 99.04 246 |
|
| icg_test_0407_2 | | | 95.04 233 | 94.78 233 | 95.84 281 | 96.97 304 | 91.64 333 | 98.63 369 | 97.12 357 | 92.33 260 | 95.60 252 | 98.88 216 | 85.65 264 | 96.56 391 | 92.12 298 | 95.70 264 | 99.32 208 |
|
| IMVS_0407 | | | 95.21 228 | 94.80 232 | 96.46 259 | 96.97 304 | 91.64 333 | 98.81 352 | 97.12 357 | 92.33 260 | 95.60 252 | 98.88 216 | 85.65 264 | 98.42 274 | 92.12 298 | 95.70 264 | 99.32 208 |
|
| IMVS_0404 | | | 93.83 274 | 93.17 284 | 95.80 283 | 96.97 304 | 91.64 333 | 97.78 409 | 97.12 357 | 92.33 260 | 90.87 315 | 98.88 216 | 76.78 369 | 96.43 397 | 92.12 298 | 95.70 264 | 99.32 208 |
|
| IMVS_0403 | | | 95.25 226 | 94.81 231 | 96.58 256 | 96.97 304 | 91.64 333 | 98.97 332 | 97.12 357 | 92.33 260 | 95.43 257 | 98.88 216 | 85.78 263 | 98.79 236 | 92.12 298 | 95.70 264 | 99.32 208 |
|
| gm-plane-assit | | | | | | 96.97 304 | 93.76 273 | | | 91.47 290 | | 98.96 204 | | 98.79 236 | 94.92 240 | | |
|
| WB-MVSnew | | | 92.90 301 | 92.77 293 | 93.26 373 | 96.95 309 | 93.63 277 | 99.71 202 | 98.16 223 | 91.49 287 | 94.28 276 | 98.14 283 | 81.33 323 | 96.48 394 | 79.47 428 | 95.46 271 | 89.68 455 |
|
| QAPM | | | 95.40 222 | 94.17 247 | 99.10 78 | 96.92 310 | 97.71 99 | 99.40 269 | 98.68 83 | 89.31 345 | 88.94 357 | 98.89 215 | 82.48 309 | 99.96 75 | 93.12 288 | 99.83 81 | 99.62 142 |
|
| KD-MVS_2432*1600 | | | 88.00 390 | 86.10 394 | 93.70 362 | 96.91 311 | 94.04 265 | 97.17 420 | 97.12 357 | 84.93 414 | 81.96 424 | 92.41 438 | 92.48 151 | 94.51 440 | 79.23 429 | 52.68 475 | 92.56 424 |
|
| miper_refine_blended | | | 88.00 390 | 86.10 394 | 93.70 362 | 96.91 311 | 94.04 265 | 97.17 420 | 97.12 357 | 84.93 414 | 81.96 424 | 92.41 438 | 92.48 151 | 94.51 440 | 79.23 429 | 52.68 475 | 92.56 424 |
|
| tpm2 | | | 95.47 220 | 95.18 216 | 96.35 265 | 96.91 311 | 91.70 331 | 96.96 426 | 97.93 247 | 88.04 374 | 98.44 147 | 95.40 378 | 93.32 121 | 97.97 314 | 94.00 262 | 95.61 269 | 99.38 195 |
|
| FMVSNet5 | | | 88.32 386 | 87.47 388 | 90.88 403 | 96.90 314 | 88.39 396 | 97.28 417 | 95.68 433 | 82.60 434 | 84.67 412 | 92.40 440 | 79.83 342 | 91.16 463 | 76.39 445 | 81.51 393 | 93.09 415 |
|
| 3Dnovator+ | | 91.53 11 | 96.31 185 | 95.24 213 | 99.52 32 | 96.88 315 | 98.64 58 | 99.72 199 | 98.24 209 | 95.27 120 | 88.42 370 | 98.98 200 | 82.76 307 | 99.94 93 | 97.10 189 | 99.83 81 | 99.96 74 |
|
| Patchmatch-test | | | 92.65 310 | 91.50 321 | 96.10 271 | 96.85 316 | 90.49 359 | 91.50 466 | 97.19 345 | 82.76 433 | 90.23 321 | 95.59 367 | 95.02 64 | 98.00 313 | 77.41 440 | 96.98 228 | 99.82 106 |
|
| MVS | | | 96.60 167 | 95.56 199 | 99.72 14 | 96.85 316 | 99.22 21 | 98.31 386 | 98.94 44 | 91.57 285 | 90.90 314 | 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 | 95.34 209 | 99.08 81 | 96.82 318 | 97.47 113 | 99.45 266 | 98.81 67 | 95.52 114 | 89.39 344 | 99.00 197 | 81.97 313 | 99.95 84 | 97.27 181 | 99.83 81 | 99.84 103 |
|
| EI-MVSNet | | | 93.73 281 | 93.40 276 | 94.74 316 | 96.80 319 | 92.69 303 | 99.06 315 | 97.67 275 | 88.96 354 | 91.39 308 | 99.02 192 | 88.75 218 | 97.30 344 | 91.07 316 | 87.85 342 | 94.22 355 |
|
| CVMVSNet | | | 94.68 248 | 94.94 227 | 93.89 356 | 96.80 319 | 86.92 410 | 99.06 315 | 98.98 41 | 94.45 146 | 94.23 278 | 99.02 192 | 85.60 267 | 95.31 429 | 90.91 322 | 95.39 274 | 99.43 190 |
|
| IterMVS-LS | | | 92.69 308 | 92.11 307 | 94.43 335 | 96.80 319 | 92.74 300 | 99.45 266 | 96.89 393 | 88.98 352 | 89.65 337 | 95.38 381 | 88.77 217 | 96.34 401 | 90.98 320 | 82.04 389 | 94.22 355 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| AstraMVS | | | 96.57 170 | 96.46 155 | 96.91 242 | 96.79 322 | 92.50 309 | 99.90 114 | 97.38 311 | 96.02 98 | 97.79 179 | 99.32 153 | 86.36 254 | 98.99 213 | 98.26 138 | 96.33 244 | 99.23 227 |
|
| IterMVS | | | 90.91 344 | 90.17 346 | 93.12 376 | 96.78 323 | 90.42 362 | 98.89 341 | 97.05 375 | 89.03 349 | 86.49 395 | 95.42 377 | 76.59 372 | 95.02 431 | 87.22 373 | 84.09 374 | 93.93 386 |
| 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 | 96.74 324 | 98.52 62 | 98.31 386 | 98.86 59 | 95.82 103 | 89.91 328 | 98.98 200 | 87.49 234 | 99.96 75 | 97.80 164 | 99.73 91 | 99.96 74 |
|
| IterMVS-SCA-FT | | | 90.85 347 | 90.16 347 | 92.93 381 | 96.72 325 | 89.96 371 | 98.89 341 | 96.99 379 | 88.95 355 | 86.63 392 | 95.67 363 | 76.48 374 | 95.00 432 | 87.04 376 | 84.04 377 | 93.84 393 |
|
| MVS-HIRNet | | | 86.22 397 | 83.19 410 | 95.31 299 | 96.71 326 | 90.29 363 | 92.12 463 | 97.33 319 | 62.85 470 | 86.82 389 | 70.37 475 | 69.37 415 | 97.49 334 | 75.12 448 | 97.99 190 | 98.15 286 |
|
| viewdifsd2359ckpt11 | | | 94.09 269 | 93.63 262 | 95.46 292 | 96.68 327 | 88.92 385 | 99.62 226 | 97.12 357 | 93.07 216 | 95.73 249 | 99.22 170 | 77.05 362 | 98.88 223 | 96.52 212 | 87.69 347 | 98.58 274 |
|
| viewmsd2359difaftdt | | | 94.09 269 | 93.64 261 | 95.46 292 | 96.68 327 | 88.92 385 | 99.62 226 | 97.13 356 | 93.07 216 | 95.73 249 | 99.22 170 | 77.05 362 | 98.89 222 | 96.52 212 | 87.70 346 | 98.58 274 |
|
| VDDNet | | | 93.12 296 | 91.91 312 | 96.76 249 | 96.67 329 | 92.65 306 | 98.69 364 | 98.21 213 | 82.81 432 | 97.75 181 | 99.28 159 | 61.57 447 | 99.48 185 | 98.09 148 | 94.09 293 | 98.15 286 |
|
| dmvs_re | | | 93.20 293 | 93.15 285 | 93.34 369 | 96.54 330 | 83.81 428 | 98.71 361 | 98.51 130 | 91.39 296 | 92.37 300 | 98.56 257 | 78.66 354 | 97.83 322 | 93.89 266 | 89.74 314 | 98.38 281 |
|
| Elysia | | | 94.50 255 | 93.38 277 | 97.85 178 | 96.49 331 | 96.70 146 | 98.98 327 | 97.78 265 | 90.81 312 | 96.19 236 | 98.55 259 | 73.63 398 | 98.98 214 | 89.41 343 | 98.56 167 | 97.88 293 |
|
| StellarMVS | | | 94.50 255 | 93.38 277 | 97.85 178 | 96.49 331 | 96.70 146 | 98.98 327 | 97.78 265 | 90.81 312 | 96.19 236 | 98.55 259 | 73.63 398 | 98.98 214 | 89.41 343 | 98.56 167 | 97.88 293 |
|
| MIMVSNet | | | 90.30 360 | 88.67 374 | 95.17 303 | 96.45 333 | 91.64 333 | 92.39 462 | 97.15 352 | 85.99 400 | 90.50 319 | 93.19 433 | 66.95 426 | 94.86 436 | 82.01 415 | 93.43 301 | 99.01 249 |
|
| CR-MVSNet | | | 93.45 290 | 92.62 295 | 95.94 275 | 96.29 334 | 92.66 304 | 92.01 464 | 96.23 419 | 92.62 242 | 96.94 207 | 93.31 431 | 91.04 178 | 96.03 415 | 79.23 429 | 95.96 252 | 99.13 235 |
|
| RPMNet | | | 89.76 372 | 87.28 389 | 97.19 232 | 96.29 334 | 92.66 304 | 92.01 464 | 98.31 198 | 70.19 466 | 96.94 207 | 85.87 468 | 87.25 239 | 99.78 146 | 62.69 470 | 95.96 252 | 99.13 235 |
|
| tt0805 | | | 91.28 337 | 90.18 345 | 94.60 322 | 96.26 336 | 87.55 403 | 98.39 384 | 98.72 77 | 89.00 351 | 89.22 350 | 98.47 267 | 62.98 442 | 98.96 218 | 90.57 328 | 88.00 341 | 97.28 312 |
|
| Patchmtry | | | 89.70 373 | 88.49 377 | 93.33 370 | 96.24 337 | 89.94 374 | 91.37 467 | 96.23 419 | 78.22 449 | 87.69 377 | 93.31 431 | 91.04 178 | 96.03 415 | 80.18 427 | 82.10 388 | 94.02 376 |
|
| test_vis1_rt | | | 86.87 395 | 86.05 397 | 89.34 423 | 96.12 338 | 78.07 457 | 99.87 130 | 83.54 483 | 92.03 272 | 78.21 445 | 89.51 452 | 45.80 468 | 99.91 110 | 96.25 216 | 93.11 306 | 90.03 451 |
|
| JIA-IIPM | | | 91.76 331 | 90.70 332 | 94.94 309 | 96.11 339 | 87.51 404 | 93.16 460 | 98.13 228 | 75.79 455 | 97.58 183 | 77.68 473 | 92.84 137 | 97.97 314 | 88.47 357 | 96.54 236 | 99.33 206 |
|
| OpenMVS |  | 90.15 15 | 94.77 243 | 93.59 266 | 98.33 145 | 96.07 340 | 97.48 112 | 99.56 244 | 98.57 106 | 90.46 326 | 86.51 394 | 98.95 209 | 78.57 355 | 99.94 93 | 93.86 267 | 99.74 90 | 97.57 307 |
|
| PAPM | | | 98.60 37 | 98.42 38 | 99.14 72 | 96.05 341 | 98.96 27 | 99.90 114 | 99.35 24 | 96.68 71 | 98.35 154 | 99.66 115 | 96.45 35 | 98.51 267 | 99.45 65 | 99.89 74 | 99.96 74 |
|
| CLD-MVS | | | 94.06 271 | 93.90 257 | 94.55 326 | 96.02 342 | 90.69 353 | 99.98 21 | 97.72 271 | 96.62 75 | 91.05 313 | 98.85 228 | 77.21 360 | 98.47 268 | 98.11 146 | 89.51 320 | 94.48 332 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| PatchT | | | 90.38 357 | 88.75 373 | 95.25 301 | 95.99 343 | 90.16 366 | 91.22 468 | 97.54 294 | 76.80 451 | 97.26 196 | 86.01 467 | 91.88 165 | 96.07 414 | 66.16 465 | 95.91 256 | 99.51 173 |
|
| ACMH+ | | 89.98 16 | 90.35 358 | 89.54 357 | 92.78 385 | 95.99 343 | 86.12 414 | 98.81 352 | 97.18 347 | 89.38 344 | 83.14 420 | 97.76 299 | 68.42 420 | 98.43 273 | 89.11 348 | 86.05 357 | 93.78 396 |
|
| DeepMVS_CX |  | | | | 82.92 445 | 95.98 345 | 58.66 476 | | 96.01 425 | 92.72 234 | 78.34 444 | 95.51 372 | 58.29 454 | 98.08 308 | 82.57 410 | 85.29 362 | 92.03 432 |
|
| ACMP | | 92.05 9 | 92.74 306 | 92.42 304 | 93.73 358 | 95.91 346 | 88.72 389 | 99.81 162 | 97.53 296 | 94.13 165 | 87.00 388 | 98.23 281 | 74.07 395 | 98.47 268 | 96.22 217 | 88.86 327 | 93.99 381 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| test_vis1_n | | | 93.61 285 | 93.03 287 | 95.35 296 | 95.86 347 | 86.94 409 | 99.87 130 | 96.36 417 | 96.85 62 | 99.54 71 | 98.79 232 | 52.41 462 | 99.83 139 | 98.64 114 | 98.97 153 | 99.29 217 |
|
| HQP-NCC | | | | | | 95.78 348 | | 99.87 130 | | 96.82 64 | 93.37 285 | | | | | | |
|
| ACMP_Plane | | | | | | 95.78 348 | | 99.87 130 | | 96.82 64 | 93.37 285 | | | | | | |
|
| HQP-MVS | | | 94.61 250 | 94.50 238 | 94.92 310 | 95.78 348 | 91.85 323 | 99.87 130 | 97.89 252 | 96.82 64 | 93.37 285 | 98.65 244 | 80.65 333 | 98.39 280 | 97.92 158 | 89.60 315 | 94.53 328 |
|
| NP-MVS | | | | | | 95.77 351 | 91.79 325 | | | | | 98.65 244 | | | | | |
|
| test_fmvsmconf0.1_n | | | 97.74 103 | 97.44 107 | 98.64 114 | 95.76 352 | 96.20 174 | 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 | | | | | | 95.76 352 | 91.72 330 | | | | | | 80.47 337 | | | | |
|
| ACMM | | 91.95 10 | 92.88 302 | 92.52 302 | 93.98 352 | 95.75 354 | 89.08 384 | 99.77 175 | 97.52 298 | 93.00 219 | 89.95 327 | 97.99 290 | 76.17 378 | 98.46 271 | 93.63 279 | 88.87 326 | 94.39 340 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| GA-MVS | | | 93.83 274 | 92.84 289 | 96.80 247 | 95.73 355 | 93.57 279 | 99.88 127 | 97.24 340 | 92.57 247 | 92.92 292 | 96.66 331 | 78.73 353 | 97.67 328 | 87.75 366 | 94.06 294 | 99.17 230 |
|
| plane_prior1 | | | | | | 95.73 355 | | | | | | | | | | | |
|
| jason | | | 97.24 129 | 96.86 134 | 98.38 144 | 95.73 355 | 97.32 117 | 99.97 39 | 97.40 310 | 95.34 118 | 98.60 141 | 99.54 133 | 87.70 228 | 98.56 264 | 97.94 157 | 99.47 124 | 99.25 224 |
| jason: jason. |
| mmtdpeth | | | 88.52 384 | 87.75 386 | 90.85 405 | 95.71 358 | 83.47 434 | 98.94 335 | 94.85 448 | 88.78 360 | 97.19 198 | 89.58 451 | 63.29 440 | 98.97 216 | 98.54 119 | 62.86 469 | 90.10 450 |
|
| HQP_MVS | | | 94.49 257 | 94.36 241 | 94.87 311 | 95.71 358 | 91.74 327 | 99.84 149 | 97.87 254 | 96.38 84 | 93.01 290 | 98.59 252 | 80.47 337 | 98.37 286 | 97.79 167 | 89.55 318 | 94.52 330 |
|
| plane_prior7 | | | | | | 95.71 358 | 91.59 339 | | | | | | | | | | |
|
| ITE_SJBPF | | | | | 92.38 388 | 95.69 361 | 85.14 420 | | 95.71 432 | 92.81 228 | 89.33 347 | 98.11 284 | 70.23 413 | 98.42 274 | 85.91 388 | 88.16 339 | 93.59 404 |
|
| fmvsm_s_conf0.1_n_a | | | 97.09 138 | 96.90 131 | 97.63 199 | 95.65 362 | 94.21 261 | 99.83 156 | 98.50 136 | 96.27 91 | 99.65 53 | 99.64 118 | 84.72 286 | 99.93 103 | 99.04 84 | 98.84 158 | 98.74 267 |
|
| ACMH | | 89.72 17 | 90.64 351 | 89.63 354 | 93.66 364 | 95.64 363 | 88.64 392 | 98.55 372 | 97.45 303 | 89.03 349 | 81.62 427 | 97.61 300 | 69.75 414 | 98.41 276 | 89.37 345 | 87.62 348 | 93.92 387 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| baseline2 | | | 96.71 162 | 96.49 152 | 97.37 224 | 95.63 364 | 95.96 183 | 99.74 188 | 98.88 54 | 92.94 221 | 91.61 306 | 98.97 202 | 97.72 6 | 98.62 261 | 94.83 244 | 98.08 188 | 97.53 309 |
|
| FMVSNet1 | | | 88.50 385 | 86.64 392 | 94.08 345 | 95.62 365 | 91.97 318 | 98.43 380 | 96.95 385 | 83.00 430 | 86.08 402 | 94.72 407 | 59.09 453 | 96.11 410 | 81.82 417 | 84.07 375 | 94.17 359 |
|
| LuminaMVS | | | 96.63 166 | 96.21 166 | 97.87 177 | 95.58 366 | 96.82 141 | 99.12 304 | 97.67 275 | 94.47 144 | 97.88 174 | 98.31 277 | 87.50 233 | 98.71 248 | 98.07 150 | 97.29 210 | 98.10 289 |
|
| LPG-MVS_test | | | 92.96 299 | 92.71 294 | 93.71 360 | 95.43 367 | 88.67 390 | 99.75 185 | 97.62 283 | 92.81 228 | 90.05 323 | 98.49 263 | 75.24 385 | 98.40 278 | 95.84 223 | 89.12 322 | 94.07 373 |
|
| LGP-MVS_train | | | | | 93.71 360 | 95.43 367 | 88.67 390 | | 97.62 283 | 92.81 228 | 90.05 323 | 98.49 263 | 75.24 385 | 98.40 278 | 95.84 223 | 89.12 322 | 94.07 373 |
|
| tpm | | | 93.70 283 | 93.41 275 | 94.58 324 | 95.36 369 | 87.41 405 | 97.01 424 | 96.90 392 | 90.85 310 | 96.72 215 | 94.14 422 | 90.40 192 | 96.84 377 | 90.75 326 | 88.54 334 | 99.51 173 |
|
| D2MVS | | | 92.76 305 | 92.59 300 | 93.27 372 | 95.13 370 | 89.54 378 | 99.69 212 | 99.38 22 | 92.26 265 | 87.59 379 | 94.61 413 | 85.05 278 | 97.79 323 | 91.59 309 | 88.01 340 | 92.47 427 |
|
| VPA-MVSNet | | | 92.70 307 | 91.55 320 | 96.16 269 | 95.09 371 | 96.20 174 | 98.88 343 | 99.00 39 | 91.02 307 | 91.82 305 | 95.29 388 | 76.05 380 | 97.96 316 | 95.62 228 | 81.19 395 | 94.30 347 |
|
| LTVRE_ROB | | 88.28 18 | 90.29 361 | 89.05 368 | 94.02 348 | 95.08 372 | 90.15 367 | 97.19 419 | 97.43 305 | 84.91 416 | 83.99 416 | 97.06 317 | 74.00 396 | 98.28 295 | 84.08 399 | 87.71 344 | 93.62 403 |
| 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 | | | 87.87 392 | 86.51 393 | 91.94 394 | 95.05 373 | 85.57 418 | 97.65 411 | 94.08 458 | 84.40 420 | 81.82 426 | 96.85 326 | 62.14 445 | 98.33 289 | 80.25 426 | 86.37 355 | 91.91 434 |
|
| test0.0.03 1 | | | 93.86 273 | 93.61 263 | 94.64 320 | 95.02 374 | 92.18 316 | 99.93 97 | 98.58 104 | 94.07 169 | 87.96 374 | 98.50 262 | 93.90 106 | 94.96 433 | 81.33 418 | 93.17 304 | 96.78 315 |
|
| UniMVSNet (Re) | | | 93.07 298 | 92.13 306 | 95.88 278 | 94.84 375 | 96.24 173 | 99.88 127 | 98.98 41 | 92.49 253 | 89.25 348 | 95.40 378 | 87.09 241 | 97.14 353 | 93.13 287 | 78.16 419 | 94.26 349 |
|
| USDC | | | 90.00 368 | 88.96 369 | 93.10 378 | 94.81 376 | 88.16 398 | 98.71 361 | 95.54 437 | 93.66 190 | 83.75 418 | 97.20 311 | 65.58 431 | 98.31 291 | 83.96 402 | 87.49 350 | 92.85 421 |
|
| VPNet | | | 91.81 325 | 90.46 336 | 95.85 280 | 94.74 377 | 95.54 202 | 98.98 327 | 98.59 102 | 92.14 267 | 90.77 318 | 97.44 304 | 68.73 418 | 97.54 333 | 94.89 243 | 77.89 421 | 94.46 333 |
|
| FIs | | | 94.10 268 | 93.43 272 | 96.11 270 | 94.70 378 | 96.82 141 | 99.58 237 | 98.93 48 | 92.54 249 | 89.34 346 | 97.31 308 | 87.62 230 | 97.10 357 | 94.22 261 | 86.58 353 | 94.40 339 |
|
| UniMVSNet_ETH3D | | | 90.06 367 | 88.58 376 | 94.49 330 | 94.67 379 | 88.09 399 | 97.81 408 | 97.57 291 | 83.91 423 | 88.44 366 | 97.41 305 | 57.44 455 | 97.62 330 | 91.41 311 | 88.59 333 | 97.77 298 |
|
| UniMVSNet_NR-MVSNet | | | 92.95 300 | 92.11 307 | 95.49 288 | 94.61 380 | 95.28 219 | 99.83 156 | 99.08 36 | 91.49 287 | 89.21 351 | 96.86 325 | 87.14 240 | 96.73 383 | 93.20 283 | 77.52 424 | 94.46 333 |
|
| test_fmvs2 | | | 89.47 377 | 89.70 353 | 88.77 430 | 94.54 381 | 75.74 459 | 99.83 156 | 94.70 454 | 94.71 136 | 91.08 311 | 96.82 330 | 54.46 458 | 97.78 325 | 92.87 290 | 88.27 337 | 92.80 422 |
|
| MonoMVSNet | | | 94.82 238 | 94.43 239 | 95.98 273 | 94.54 381 | 90.73 352 | 99.03 322 | 97.06 372 | 93.16 211 | 93.15 289 | 95.47 375 | 88.29 221 | 97.57 331 | 97.85 162 | 91.33 312 | 99.62 142 |
|
| WR-MVS | | | 92.31 317 | 91.25 325 | 95.48 291 | 94.45 383 | 95.29 218 | 99.60 233 | 98.68 83 | 90.10 334 | 88.07 373 | 96.89 323 | 80.68 332 | 96.80 381 | 93.14 286 | 79.67 412 | 94.36 341 |
|
| nrg030 | | | 93.51 287 | 92.53 301 | 96.45 260 | 94.36 384 | 97.20 123 | 99.81 162 | 97.16 351 | 91.60 284 | 89.86 330 | 97.46 303 | 86.37 253 | 97.68 327 | 95.88 222 | 80.31 408 | 94.46 333 |
|
| tfpnnormal | | | 89.29 380 | 87.61 387 | 94.34 338 | 94.35 385 | 94.13 263 | 98.95 334 | 98.94 44 | 83.94 421 | 84.47 413 | 95.51 372 | 74.84 390 | 97.39 336 | 77.05 443 | 80.41 406 | 91.48 437 |
|
| FC-MVSNet-test | | | 93.81 277 | 93.15 285 | 95.80 283 | 94.30 386 | 96.20 174 | 99.42 268 | 98.89 52 | 92.33 260 | 89.03 356 | 97.27 310 | 87.39 236 | 96.83 379 | 93.20 283 | 86.48 354 | 94.36 341 |
|
| SSC-MVS3.2 | | | 89.59 375 | 88.66 375 | 92.38 388 | 94.29 387 | 86.12 414 | 99.49 257 | 97.66 278 | 90.28 333 | 88.63 363 | 95.18 392 | 64.46 436 | 96.88 375 | 85.30 392 | 82.66 383 | 94.14 368 |
|
| MS-PatchMatch | | | 90.65 350 | 90.30 341 | 91.71 399 | 94.22 388 | 85.50 419 | 98.24 391 | 97.70 272 | 88.67 363 | 86.42 397 | 96.37 341 | 67.82 423 | 98.03 312 | 83.62 404 | 99.62 100 | 91.60 435 |
|
| WR-MVS_H | | | 91.30 335 | 90.35 339 | 94.15 342 | 94.17 389 | 92.62 307 | 99.17 302 | 98.94 44 | 88.87 358 | 86.48 396 | 94.46 418 | 84.36 292 | 96.61 389 | 88.19 360 | 78.51 417 | 93.21 413 |
|
| DU-MVS | | | 92.46 314 | 91.45 323 | 95.49 288 | 94.05 390 | 95.28 219 | 99.81 162 | 98.74 76 | 92.25 266 | 89.21 351 | 96.64 333 | 81.66 318 | 96.73 383 | 93.20 283 | 77.52 424 | 94.46 333 |
|
| NR-MVSNet | | | 91.56 333 | 90.22 343 | 95.60 286 | 94.05 390 | 95.76 190 | 98.25 390 | 98.70 79 | 91.16 301 | 80.78 433 | 96.64 333 | 83.23 304 | 96.57 390 | 91.41 311 | 77.73 423 | 94.46 333 |
|
| CP-MVSNet | | | 91.23 339 | 90.22 343 | 94.26 340 | 93.96 392 | 92.39 312 | 99.09 308 | 98.57 106 | 88.95 355 | 86.42 397 | 96.57 336 | 79.19 348 | 96.37 399 | 90.29 335 | 78.95 414 | 94.02 376 |
|
| XXY-MVS | | | 91.82 324 | 90.46 336 | 95.88 278 | 93.91 393 | 95.40 209 | 98.87 346 | 97.69 274 | 88.63 365 | 87.87 375 | 97.08 315 | 74.38 394 | 97.89 320 | 91.66 308 | 84.07 375 | 94.35 344 |
|
| PS-CasMVS | | | 90.63 352 | 89.51 359 | 93.99 351 | 93.83 394 | 91.70 331 | 98.98 327 | 98.52 127 | 88.48 367 | 86.15 401 | 96.53 338 | 75.46 383 | 96.31 403 | 88.83 350 | 78.86 416 | 93.95 384 |
|
| test_0402 | | | 85.58 399 | 83.94 404 | 90.50 411 | 93.81 395 | 85.04 421 | 98.55 372 | 95.20 445 | 76.01 453 | 79.72 439 | 95.13 393 | 64.15 438 | 96.26 405 | 66.04 466 | 86.88 352 | 90.21 448 |
|
| XVG-ACMP-BASELINE | | | 91.22 340 | 90.75 331 | 92.63 387 | 93.73 396 | 85.61 417 | 98.52 376 | 97.44 304 | 92.77 232 | 89.90 329 | 96.85 326 | 66.64 428 | 98.39 280 | 92.29 295 | 88.61 331 | 93.89 389 |
|
| TranMVSNet+NR-MVSNet | | | 91.68 332 | 90.61 335 | 94.87 311 | 93.69 397 | 93.98 268 | 99.69 212 | 98.65 87 | 91.03 306 | 88.44 366 | 96.83 329 | 80.05 341 | 96.18 408 | 90.26 336 | 76.89 432 | 94.45 338 |
|
| TransMVSNet (Re) | | | 87.25 393 | 85.28 400 | 93.16 375 | 93.56 398 | 91.03 344 | 98.54 374 | 94.05 460 | 83.69 425 | 81.09 431 | 96.16 347 | 75.32 384 | 96.40 398 | 76.69 444 | 68.41 457 | 92.06 431 |
|
| v10 | | | 90.25 362 | 88.82 371 | 94.57 325 | 93.53 399 | 93.43 284 | 99.08 310 | 96.87 395 | 85.00 413 | 87.34 386 | 94.51 414 | 80.93 328 | 97.02 367 | 82.85 409 | 79.23 413 | 93.26 411 |
|
| testgi | | | 89.01 382 | 88.04 383 | 91.90 395 | 93.49 400 | 84.89 423 | 99.73 195 | 95.66 434 | 93.89 183 | 85.14 408 | 98.17 282 | 59.68 451 | 94.66 439 | 77.73 439 | 88.88 325 | 96.16 324 |
|
| v8 | | | 90.54 354 | 89.17 364 | 94.66 319 | 93.43 401 | 93.40 287 | 99.20 299 | 96.94 389 | 85.76 403 | 87.56 380 | 94.51 414 | 81.96 314 | 97.19 350 | 84.94 395 | 78.25 418 | 93.38 409 |
|
| V42 | | | 91.28 337 | 90.12 348 | 94.74 316 | 93.42 402 | 93.46 283 | 99.68 215 | 97.02 376 | 87.36 382 | 89.85 332 | 95.05 396 | 81.31 324 | 97.34 339 | 87.34 371 | 80.07 410 | 93.40 407 |
|
| pm-mvs1 | | | 89.36 379 | 87.81 385 | 94.01 349 | 93.40 403 | 91.93 321 | 98.62 370 | 96.48 415 | 86.25 398 | 83.86 417 | 96.14 349 | 73.68 397 | 97.04 363 | 86.16 385 | 75.73 437 | 93.04 417 |
|
| v1144 | | | 91.09 341 | 89.83 350 | 94.87 311 | 93.25 404 | 93.69 276 | 99.62 226 | 96.98 381 | 86.83 392 | 89.64 338 | 94.99 402 | 80.94 327 | 97.05 360 | 85.08 394 | 81.16 396 | 93.87 391 |
|
| v1192 | | | 90.62 353 | 89.25 363 | 94.72 318 | 93.13 405 | 93.07 291 | 99.50 255 | 97.02 376 | 86.33 397 | 89.56 342 | 95.01 399 | 79.22 347 | 97.09 359 | 82.34 413 | 81.16 396 | 94.01 378 |
|
| v2v482 | | | 91.30 335 | 90.07 349 | 95.01 306 | 93.13 405 | 93.79 271 | 99.77 175 | 97.02 376 | 88.05 373 | 89.25 348 | 95.37 382 | 80.73 331 | 97.15 352 | 87.28 372 | 80.04 411 | 94.09 372 |
|
| OPM-MVS | | | 93.21 292 | 92.80 291 | 94.44 333 | 93.12 407 | 90.85 351 | 99.77 175 | 97.61 286 | 96.19 94 | 91.56 307 | 98.65 244 | 75.16 389 | 98.47 268 | 93.78 274 | 89.39 321 | 93.99 381 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| v144192 | | | 90.79 348 | 89.52 358 | 94.59 323 | 93.11 408 | 92.77 298 | 99.56 244 | 96.99 379 | 86.38 396 | 89.82 333 | 94.95 404 | 80.50 336 | 97.10 357 | 83.98 401 | 80.41 406 | 93.90 388 |
|
| PEN-MVS | | | 90.19 364 | 89.06 367 | 93.57 365 | 93.06 409 | 90.90 349 | 99.06 315 | 98.47 139 | 88.11 372 | 85.91 403 | 96.30 343 | 76.67 370 | 95.94 418 | 87.07 375 | 76.91 431 | 93.89 389 |
|
| v1240 | | | 90.20 363 | 88.79 372 | 94.44 333 | 93.05 410 | 92.27 314 | 99.38 275 | 96.92 391 | 85.89 401 | 89.36 345 | 94.87 406 | 77.89 359 | 97.03 365 | 80.66 422 | 81.08 399 | 94.01 378 |
|
| FE-MVSNET3 | | | 92.78 304 | 91.73 315 | 95.92 277 | 93.03 411 | 96.82 141 | 99.83 156 | 97.79 262 | 90.58 321 | 90.09 322 | 95.04 397 | 84.75 283 | 96.72 385 | 88.20 359 | 86.23 356 | 94.23 353 |
|
| v148 | | | 90.70 349 | 89.63 354 | 93.92 353 | 92.97 412 | 90.97 345 | 99.75 185 | 96.89 393 | 87.51 379 | 88.27 371 | 95.01 399 | 81.67 317 | 97.04 363 | 87.40 370 | 77.17 429 | 93.75 397 |
|
| v1921920 | | | 90.46 355 | 89.12 365 | 94.50 329 | 92.96 413 | 92.46 310 | 99.49 257 | 96.98 381 | 86.10 399 | 89.61 340 | 95.30 385 | 78.55 356 | 97.03 365 | 82.17 414 | 80.89 404 | 94.01 378 |
|
| MVStest1 | | | 85.03 405 | 82.76 414 | 91.83 396 | 92.95 414 | 89.16 383 | 98.57 371 | 94.82 449 | 71.68 464 | 68.54 467 | 95.11 395 | 83.17 305 | 95.66 422 | 74.69 449 | 65.32 464 | 90.65 444 |
|
| tt0320-xc | | | 82.94 420 | 80.35 427 | 90.72 409 | 92.90 415 | 83.54 432 | 96.85 429 | 94.73 452 | 63.12 469 | 79.85 438 | 93.77 426 | 49.43 466 | 95.46 425 | 80.98 421 | 71.54 446 | 93.16 414 |
|
| Baseline_NR-MVSNet | | | 90.33 359 | 89.51 359 | 92.81 384 | 92.84 416 | 89.95 372 | 99.77 175 | 93.94 461 | 84.69 418 | 89.04 355 | 95.66 364 | 81.66 318 | 96.52 392 | 90.99 319 | 76.98 430 | 91.97 433 |
|
| test_method | | | 80.79 426 | 79.70 429 | 84.08 442 | 92.83 417 | 67.06 468 | 99.51 253 | 95.42 439 | 54.34 474 | 81.07 432 | 93.53 428 | 44.48 469 | 92.22 460 | 78.90 434 | 77.23 428 | 92.94 419 |
|
| pmmvs4 | | | 92.10 321 | 91.07 329 | 95.18 302 | 92.82 418 | 94.96 230 | 99.48 260 | 96.83 397 | 87.45 381 | 88.66 362 | 96.56 337 | 83.78 298 | 96.83 379 | 89.29 346 | 84.77 369 | 93.75 397 |
|
| LF4IMVS | | | 89.25 381 | 88.85 370 | 90.45 413 | 92.81 419 | 81.19 449 | 98.12 398 | 94.79 450 | 91.44 291 | 86.29 399 | 97.11 313 | 65.30 434 | 98.11 306 | 88.53 355 | 85.25 363 | 92.07 430 |
|
| tt0320 | | | 83.56 419 | 81.15 422 | 90.77 407 | 92.77 420 | 83.58 431 | 96.83 430 | 95.52 438 | 63.26 468 | 81.36 429 | 92.54 436 | 53.26 460 | 95.77 420 | 80.45 423 | 74.38 440 | 92.96 418 |
|
| DTE-MVSNet | | | 89.40 378 | 88.24 381 | 92.88 382 | 92.66 421 | 89.95 372 | 99.10 307 | 98.22 212 | 87.29 383 | 85.12 409 | 96.22 345 | 76.27 377 | 95.30 430 | 83.56 405 | 75.74 436 | 93.41 406 |
|
| EU-MVSNet | | | 90.14 366 | 90.34 340 | 89.54 422 | 92.55 422 | 81.06 450 | 98.69 364 | 98.04 236 | 91.41 295 | 86.59 393 | 96.84 328 | 80.83 330 | 93.31 452 | 86.20 384 | 81.91 390 | 94.26 349 |
|
| APD_test1 | | | 81.15 424 | 80.92 424 | 81.86 446 | 92.45 423 | 59.76 475 | 96.04 444 | 93.61 464 | 73.29 462 | 77.06 448 | 96.64 333 | 44.28 470 | 96.16 409 | 72.35 453 | 82.52 384 | 89.67 456 |
|
| sc_t1 | | | 85.01 406 | 82.46 416 | 92.67 386 | 92.44 424 | 83.09 435 | 97.39 415 | 95.72 431 | 65.06 467 | 85.64 406 | 96.16 347 | 49.50 465 | 97.34 339 | 84.86 396 | 75.39 438 | 97.57 307 |
|
| our_test_3 | | | 90.39 356 | 89.48 361 | 93.12 376 | 92.40 425 | 89.57 377 | 99.33 282 | 96.35 418 | 87.84 377 | 85.30 407 | 94.99 402 | 84.14 295 | 96.09 413 | 80.38 424 | 84.56 370 | 93.71 402 |
|
| ppachtmachnet_test | | | 89.58 376 | 88.35 379 | 93.25 374 | 92.40 425 | 90.44 361 | 99.33 282 | 96.73 404 | 85.49 408 | 85.90 404 | 95.77 358 | 81.09 326 | 96.00 417 | 76.00 447 | 82.49 385 | 93.30 410 |
|
| v7n | | | 89.65 374 | 88.29 380 | 93.72 359 | 92.22 427 | 90.56 358 | 99.07 314 | 97.10 364 | 85.42 410 | 86.73 390 | 94.72 407 | 80.06 340 | 97.13 354 | 81.14 419 | 78.12 420 | 93.49 405 |
|
| dmvs_testset | | | 83.79 415 | 86.07 396 | 76.94 450 | 92.14 428 | 48.60 485 | 96.75 431 | 90.27 475 | 89.48 343 | 78.65 442 | 98.55 259 | 79.25 346 | 86.65 473 | 66.85 463 | 82.69 382 | 95.57 326 |
|
| PS-MVSNAJss | | | 93.64 284 | 93.31 281 | 94.61 321 | 92.11 429 | 92.19 315 | 99.12 304 | 97.38 311 | 92.51 252 | 88.45 365 | 96.99 321 | 91.20 173 | 97.29 347 | 94.36 255 | 87.71 344 | 94.36 341 |
|
| pmmvs5 | | | 90.17 365 | 89.09 366 | 93.40 368 | 92.10 430 | 89.77 375 | 99.74 188 | 95.58 436 | 85.88 402 | 87.24 387 | 95.74 359 | 73.41 400 | 96.48 394 | 88.54 354 | 83.56 379 | 93.95 384 |
|
| N_pmnet | | | 80.06 429 | 80.78 425 | 77.89 449 | 91.94 431 | 45.28 487 | 98.80 355 | 56.82 489 | 78.10 450 | 80.08 436 | 93.33 429 | 77.03 364 | 95.76 421 | 68.14 461 | 82.81 381 | 92.64 423 |
|
| test_djsdf | | | 92.83 303 | 92.29 305 | 94.47 331 | 91.90 432 | 92.46 310 | 99.55 247 | 97.27 334 | 91.17 299 | 89.96 326 | 96.07 353 | 81.10 325 | 96.89 373 | 94.67 250 | 88.91 324 | 94.05 375 |
|
| SixPastTwentyTwo | | | 88.73 383 | 88.01 384 | 90.88 403 | 91.85 433 | 82.24 441 | 98.22 395 | 95.18 446 | 88.97 353 | 82.26 423 | 96.89 323 | 71.75 405 | 96.67 387 | 84.00 400 | 82.98 380 | 93.72 401 |
|
| K. test v3 | | | 88.05 389 | 87.24 390 | 90.47 412 | 91.82 434 | 82.23 442 | 98.96 333 | 97.42 307 | 89.05 348 | 76.93 450 | 95.60 366 | 68.49 419 | 95.42 426 | 85.87 389 | 81.01 402 | 93.75 397 |
|
| OurMVSNet-221017-0 | | | 89.81 371 | 89.48 361 | 90.83 406 | 91.64 435 | 81.21 448 | 98.17 397 | 95.38 441 | 91.48 289 | 85.65 405 | 97.31 308 | 72.66 401 | 97.29 347 | 88.15 361 | 84.83 368 | 93.97 383 |
|
| mvs_tets | | | 91.81 325 | 91.08 328 | 94.00 350 | 91.63 436 | 90.58 357 | 98.67 366 | 97.43 305 | 92.43 254 | 87.37 385 | 97.05 318 | 71.76 404 | 97.32 342 | 94.75 247 | 88.68 330 | 94.11 371 |
|
| Gipuma |  | | 66.95 442 | 65.00 442 | 72.79 455 | 91.52 437 | 67.96 467 | 66.16 479 | 95.15 447 | 47.89 476 | 58.54 473 | 67.99 478 | 29.74 474 | 87.54 472 | 50.20 477 | 77.83 422 | 62.87 478 |
| 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 | 91.47 438 | 95.56 201 | 99.84 149 | 97.30 327 | 97.74 30 | 97.89 173 | 99.35 152 | 79.62 343 | 99.85 129 | 99.25 74 | 99.24 141 | 99.55 159 |
|
| jajsoiax | | | 91.92 323 | 91.18 326 | 94.15 342 | 91.35 439 | 90.95 348 | 99.00 325 | 97.42 307 | 92.61 243 | 87.38 384 | 97.08 315 | 72.46 402 | 97.36 337 | 94.53 253 | 88.77 328 | 94.13 370 |
|
| MDA-MVSNet-bldmvs | | | 84.09 413 | 81.52 420 | 91.81 397 | 91.32 440 | 88.00 401 | 98.67 366 | 95.92 427 | 80.22 444 | 55.60 476 | 93.32 430 | 68.29 421 | 93.60 450 | 73.76 450 | 76.61 433 | 93.82 395 |
|
| MVP-Stereo | | | 90.93 343 | 90.45 338 | 92.37 390 | 91.25 441 | 88.76 387 | 98.05 402 | 96.17 421 | 87.27 384 | 84.04 414 | 95.30 385 | 78.46 357 | 97.27 349 | 83.78 403 | 99.70 93 | 91.09 438 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| MDA-MVSNet_test_wron | | | 85.51 401 | 83.32 409 | 92.10 392 | 90.96 442 | 88.58 393 | 99.20 299 | 96.52 413 | 79.70 446 | 57.12 475 | 92.69 435 | 79.11 349 | 93.86 446 | 77.10 442 | 77.46 426 | 93.86 392 |
|
| YYNet1 | | | 85.50 402 | 83.33 408 | 92.00 393 | 90.89 443 | 88.38 397 | 99.22 298 | 96.55 412 | 79.60 447 | 57.26 474 | 92.72 434 | 79.09 351 | 93.78 448 | 77.25 441 | 77.37 427 | 93.84 393 |
|
| anonymousdsp | | | 91.79 330 | 90.92 330 | 94.41 336 | 90.76 444 | 92.93 297 | 98.93 337 | 97.17 349 | 89.08 347 | 87.46 383 | 95.30 385 | 78.43 358 | 96.92 371 | 92.38 294 | 88.73 329 | 93.39 408 |
|
| lessismore_v0 | | | | | 90.53 410 | 90.58 445 | 80.90 451 | | 95.80 428 | | 77.01 449 | 95.84 356 | 66.15 430 | 96.95 369 | 83.03 408 | 75.05 439 | 93.74 400 |
|
| EG-PatchMatch MVS | | | 85.35 403 | 83.81 406 | 89.99 420 | 90.39 446 | 81.89 444 | 98.21 396 | 96.09 423 | 81.78 437 | 74.73 456 | 93.72 427 | 51.56 464 | 97.12 356 | 79.16 432 | 88.61 331 | 90.96 441 |
|
| EGC-MVSNET | | | 69.38 435 | 63.76 445 | 86.26 439 | 90.32 447 | 81.66 447 | 96.24 440 | 93.85 462 | 0.99 486 | 3.22 487 | 92.33 441 | 52.44 461 | 92.92 456 | 59.53 473 | 84.90 367 | 84.21 467 |
|
| CMPMVS |  | 61.59 21 | 84.75 409 | 85.14 401 | 83.57 443 | 90.32 447 | 62.54 471 | 96.98 425 | 97.59 290 | 74.33 460 | 69.95 464 | 96.66 331 | 64.17 437 | 98.32 290 | 87.88 365 | 88.41 336 | 89.84 453 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| new_pmnet | | | 84.49 412 | 82.92 412 | 89.21 424 | 90.03 449 | 82.60 438 | 96.89 428 | 95.62 435 | 80.59 442 | 75.77 455 | 89.17 453 | 65.04 435 | 94.79 437 | 72.12 454 | 81.02 401 | 90.23 447 |
|
| pmmvs6 | | | 85.69 398 | 83.84 405 | 91.26 402 | 90.00 450 | 84.41 426 | 97.82 407 | 96.15 422 | 75.86 454 | 81.29 430 | 95.39 380 | 61.21 448 | 96.87 376 | 83.52 406 | 73.29 442 | 92.50 426 |
|
| ttmdpeth | | | 88.23 388 | 87.06 391 | 91.75 398 | 89.91 451 | 87.35 406 | 98.92 340 | 95.73 430 | 87.92 375 | 84.02 415 | 96.31 342 | 68.23 422 | 96.84 377 | 86.33 383 | 76.12 434 | 91.06 439 |
|
| DSMNet-mixed | | | 88.28 387 | 88.24 381 | 88.42 432 | 89.64 452 | 75.38 461 | 98.06 401 | 89.86 476 | 85.59 407 | 88.20 372 | 92.14 442 | 76.15 379 | 91.95 461 | 78.46 436 | 96.05 249 | 97.92 292 |
|
| UnsupCasMVSNet_eth | | | 85.52 400 | 83.99 402 | 90.10 418 | 89.36 453 | 83.51 433 | 96.65 432 | 97.99 240 | 89.14 346 | 75.89 454 | 93.83 424 | 63.25 441 | 93.92 444 | 81.92 416 | 67.90 460 | 92.88 420 |
|
| Anonymous20231206 | | | 86.32 396 | 85.42 399 | 89.02 426 | 89.11 454 | 80.53 454 | 99.05 319 | 95.28 442 | 85.43 409 | 82.82 421 | 93.92 423 | 74.40 393 | 93.44 451 | 66.99 462 | 81.83 391 | 93.08 416 |
|
| Anonymous20240521 | | | 85.15 404 | 83.81 406 | 89.16 425 | 88.32 455 | 82.69 437 | 98.80 355 | 95.74 429 | 79.72 445 | 81.53 428 | 90.99 445 | 65.38 433 | 94.16 442 | 72.69 452 | 81.11 398 | 90.63 445 |
|
| OpenMVS_ROB |  | 79.82 20 | 83.77 416 | 81.68 419 | 90.03 419 | 88.30 456 | 82.82 436 | 98.46 377 | 95.22 444 | 73.92 461 | 76.00 453 | 91.29 444 | 55.00 457 | 96.94 370 | 68.40 460 | 88.51 335 | 90.34 446 |
|
| test20.03 | | | 84.72 410 | 83.99 402 | 86.91 437 | 88.19 457 | 80.62 453 | 98.88 343 | 95.94 426 | 88.36 369 | 78.87 440 | 94.62 412 | 68.75 417 | 89.11 468 | 66.52 464 | 75.82 435 | 91.00 440 |
|
| KD-MVS_self_test | | | 83.59 417 | 82.06 417 | 88.20 433 | 86.93 458 | 80.70 452 | 97.21 418 | 96.38 416 | 82.87 431 | 82.49 422 | 88.97 454 | 67.63 424 | 92.32 459 | 73.75 451 | 62.30 471 | 91.58 436 |
|
| MIMVSNet1 | | | 82.58 421 | 80.51 426 | 88.78 428 | 86.68 459 | 84.20 427 | 96.65 432 | 95.41 440 | 78.75 448 | 78.59 443 | 92.44 437 | 51.88 463 | 89.76 467 | 65.26 467 | 78.95 414 | 92.38 429 |
|
| CL-MVSNet_self_test | | | 84.50 411 | 83.15 411 | 88.53 431 | 86.00 460 | 81.79 445 | 98.82 351 | 97.35 315 | 85.12 412 | 83.62 419 | 90.91 447 | 76.66 371 | 91.40 462 | 69.53 458 | 60.36 472 | 92.40 428 |
|
| UnsupCasMVSNet_bld | | | 79.97 431 | 77.03 436 | 88.78 428 | 85.62 461 | 81.98 443 | 93.66 456 | 97.35 315 | 75.51 457 | 70.79 463 | 83.05 470 | 48.70 467 | 94.91 435 | 78.31 437 | 60.29 473 | 89.46 459 |
|
| mvs5depth | | | 84.87 407 | 82.90 413 | 90.77 407 | 85.59 462 | 84.84 424 | 91.10 469 | 93.29 466 | 83.14 428 | 85.07 410 | 94.33 420 | 62.17 444 | 97.32 342 | 78.83 435 | 72.59 445 | 90.14 449 |
|
| Patchmatch-RL test | | | 86.90 394 | 85.98 398 | 89.67 421 | 84.45 463 | 75.59 460 | 89.71 472 | 92.43 468 | 86.89 391 | 77.83 447 | 90.94 446 | 94.22 95 | 93.63 449 | 87.75 366 | 69.61 451 | 99.79 111 |
|
| pmmvs-eth3d | | | 84.03 414 | 81.97 418 | 90.20 416 | 84.15 464 | 87.09 408 | 98.10 400 | 94.73 452 | 83.05 429 | 74.10 460 | 87.77 460 | 65.56 432 | 94.01 443 | 81.08 420 | 69.24 453 | 89.49 458 |
|
| test_fmvs3 | | | 79.99 430 | 80.17 428 | 79.45 448 | 84.02 465 | 62.83 469 | 99.05 319 | 93.49 465 | 88.29 371 | 80.06 437 | 86.65 465 | 28.09 476 | 88.00 469 | 88.63 351 | 73.27 443 | 87.54 465 |
|
| PM-MVS | | | 80.47 427 | 78.88 431 | 85.26 440 | 83.79 466 | 72.22 463 | 95.89 447 | 91.08 473 | 85.71 406 | 76.56 452 | 88.30 456 | 36.64 472 | 93.90 445 | 82.39 412 | 69.57 452 | 89.66 457 |
|
| new-patchmatchnet | | | 81.19 423 | 79.34 430 | 86.76 438 | 82.86 467 | 80.36 455 | 97.92 404 | 95.27 443 | 82.09 436 | 72.02 461 | 86.87 464 | 62.81 443 | 90.74 465 | 71.10 455 | 63.08 468 | 89.19 461 |
|
| FE-MVSNET2 | | | 83.57 418 | 81.36 421 | 90.20 416 | 82.83 468 | 87.59 402 | 98.28 388 | 96.04 424 | 85.33 411 | 74.13 459 | 87.45 461 | 59.16 452 | 93.26 453 | 79.12 433 | 69.91 449 | 89.77 454 |
|
| FE-MVSNET | | | 81.05 425 | 78.81 432 | 87.79 435 | 81.98 469 | 83.70 429 | 98.23 393 | 91.78 472 | 81.27 439 | 74.29 458 | 87.44 462 | 60.92 450 | 90.67 466 | 64.92 468 | 68.43 456 | 89.01 462 |
|
| mvsany_test3 | | | 82.12 422 | 81.14 423 | 85.06 441 | 81.87 470 | 70.41 465 | 97.09 422 | 92.14 469 | 91.27 298 | 77.84 446 | 88.73 455 | 39.31 471 | 95.49 423 | 90.75 326 | 71.24 447 | 89.29 460 |
|
| WB-MVS | | | 76.28 433 | 77.28 435 | 73.29 454 | 81.18 471 | 54.68 479 | 97.87 406 | 94.19 457 | 81.30 438 | 69.43 465 | 90.70 448 | 77.02 365 | 82.06 477 | 35.71 482 | 68.11 459 | 83.13 468 |
|
| test_f | | | 78.40 432 | 77.59 434 | 80.81 447 | 80.82 472 | 62.48 472 | 96.96 426 | 93.08 467 | 83.44 426 | 74.57 457 | 84.57 469 | 27.95 477 | 92.63 457 | 84.15 398 | 72.79 444 | 87.32 466 |
|
| SSC-MVS | | | 75.42 434 | 76.40 437 | 72.49 458 | 80.68 473 | 53.62 480 | 97.42 413 | 94.06 459 | 80.42 443 | 68.75 466 | 90.14 450 | 76.54 373 | 81.66 478 | 33.25 483 | 66.34 463 | 82.19 469 |
|
| pmmvs3 | | | 80.27 428 | 77.77 433 | 87.76 436 | 80.32 474 | 82.43 440 | 98.23 393 | 91.97 470 | 72.74 463 | 78.75 441 | 87.97 459 | 57.30 456 | 90.99 464 | 70.31 456 | 62.37 470 | 89.87 452 |
|
| testf1 | | | 68.38 438 | 66.92 439 | 72.78 456 | 78.80 475 | 50.36 482 | 90.95 470 | 87.35 481 | 55.47 472 | 58.95 471 | 88.14 457 | 20.64 481 | 87.60 470 | 57.28 474 | 64.69 465 | 80.39 471 |
|
| APD_test2 | | | 68.38 438 | 66.92 439 | 72.78 456 | 78.80 475 | 50.36 482 | 90.95 470 | 87.35 481 | 55.47 472 | 58.95 471 | 88.14 457 | 20.64 481 | 87.60 470 | 57.28 474 | 64.69 465 | 80.39 471 |
|
| ambc | | | | | 83.23 444 | 77.17 477 | 62.61 470 | 87.38 474 | 94.55 456 | | 76.72 451 | 86.65 465 | 30.16 473 | 96.36 400 | 84.85 397 | 69.86 450 | 90.73 443 |
|
| test_vis3_rt | | | 68.82 436 | 66.69 441 | 75.21 453 | 76.24 478 | 60.41 474 | 96.44 435 | 68.71 488 | 75.13 458 | 50.54 479 | 69.52 477 | 16.42 486 | 96.32 402 | 80.27 425 | 66.92 462 | 68.89 475 |
|
| TDRefinement | | | 84.76 408 | 82.56 415 | 91.38 401 | 74.58 479 | 84.80 425 | 97.36 416 | 94.56 455 | 84.73 417 | 80.21 435 | 96.12 352 | 63.56 439 | 98.39 280 | 87.92 364 | 63.97 467 | 90.95 442 |
|
| E-PMN | | | 52.30 446 | 52.18 448 | 52.67 464 | 71.51 480 | 45.40 486 | 93.62 457 | 76.60 486 | 36.01 480 | 43.50 481 | 64.13 480 | 27.11 478 | 67.31 483 | 31.06 484 | 26.06 479 | 45.30 482 |
|
| EMVS | | | 51.44 448 | 51.22 450 | 52.11 465 | 70.71 481 | 44.97 488 | 94.04 453 | 75.66 487 | 35.34 482 | 42.40 482 | 61.56 483 | 28.93 475 | 65.87 484 | 27.64 485 | 24.73 480 | 45.49 481 |
|
| PMMVS2 | | | 67.15 441 | 64.15 444 | 76.14 452 | 70.56 482 | 62.07 473 | 93.89 454 | 87.52 480 | 58.09 471 | 60.02 470 | 78.32 472 | 22.38 480 | 84.54 475 | 59.56 472 | 47.03 477 | 81.80 470 |
|
| FPMVS | | | 68.72 437 | 68.72 438 | 68.71 460 | 65.95 483 | 44.27 489 | 95.97 446 | 94.74 451 | 51.13 475 | 53.26 477 | 90.50 449 | 25.11 479 | 83.00 476 | 60.80 471 | 80.97 403 | 78.87 473 |
|
| wuyk23d | | | 20.37 452 | 20.84 455 | 18.99 468 | 65.34 484 | 27.73 491 | 50.43 480 | 7.67 492 | 9.50 485 | 8.01 486 | 6.34 486 | 6.13 489 | 26.24 485 | 23.40 486 | 10.69 484 | 2.99 483 |
|
| LCM-MVSNet | | | 67.77 440 | 64.73 443 | 76.87 451 | 62.95 485 | 56.25 478 | 89.37 473 | 93.74 463 | 44.53 477 | 61.99 469 | 80.74 471 | 20.42 483 | 86.53 474 | 69.37 459 | 59.50 474 | 87.84 463 |
|
| MVE |  | 53.74 22 | 51.54 447 | 47.86 451 | 62.60 462 | 59.56 486 | 50.93 481 | 79.41 477 | 77.69 485 | 35.69 481 | 36.27 483 | 61.76 482 | 5.79 490 | 69.63 481 | 37.97 481 | 36.61 478 | 67.24 476 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| ANet_high | | | 56.10 444 | 52.24 447 | 67.66 461 | 49.27 487 | 56.82 477 | 83.94 475 | 82.02 484 | 70.47 465 | 33.28 484 | 64.54 479 | 17.23 485 | 69.16 482 | 45.59 479 | 23.85 481 | 77.02 474 |
|
| tmp_tt | | | 65.23 443 | 62.94 446 | 72.13 459 | 44.90 488 | 50.03 484 | 81.05 476 | 89.42 479 | 38.45 478 | 48.51 480 | 99.90 22 | 54.09 459 | 78.70 480 | 91.84 307 | 18.26 482 | 87.64 464 |
|
| PMVS |  | 49.05 23 | 53.75 445 | 51.34 449 | 60.97 463 | 40.80 489 | 34.68 490 | 74.82 478 | 89.62 478 | 37.55 479 | 28.67 485 | 72.12 474 | 7.09 488 | 81.63 479 | 43.17 480 | 68.21 458 | 66.59 477 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| test123 | | | 37.68 450 | 39.14 453 | 33.31 466 | 19.94 490 | 24.83 492 | 98.36 385 | 9.75 491 | 15.53 484 | 51.31 478 | 87.14 463 | 19.62 484 | 17.74 486 | 47.10 478 | 3.47 485 | 57.36 479 |
|
| testmvs | | | 40.60 449 | 44.45 452 | 29.05 467 | 19.49 491 | 14.11 493 | 99.68 215 | 18.47 490 | 20.74 483 | 64.59 468 | 98.48 266 | 10.95 487 | 17.09 487 | 56.66 476 | 11.01 483 | 55.94 480 |
|
| mmdepth | | | 0.00 455 | 0.00 458 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 0.00 488 | 0.00 491 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| monomultidepth | | | 0.00 455 | 0.00 458 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 0.00 488 | 0.00 491 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| test_blank | | | 0.00 455 | 0.00 458 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 0.02 487 | 0.00 491 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| eth-test2 | | | | | | 0.00 492 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 492 | | | | | | | | | | | |
|
| uanet_test | | | 0.00 455 | 0.00 458 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 0.00 488 | 0.00 491 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| DCPMVS | | | 0.00 455 | 0.00 458 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 0.00 488 | 0.00 491 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| cdsmvs_eth3d_5k | | | 23.43 451 | 31.24 454 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 98.09 230 | 0.00 487 | 0.00 488 | 99.67 113 | 83.37 302 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| pcd_1.5k_mvsjas | | | 7.60 454 | 10.13 457 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 0.00 488 | 91.20 173 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| sosnet-low-res | | | 0.00 455 | 0.00 458 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 0.00 488 | 0.00 491 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| sosnet | | | 0.00 455 | 0.00 458 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 0.00 488 | 0.00 491 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| uncertanet | | | 0.00 455 | 0.00 458 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 0.00 488 | 0.00 491 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| Regformer | | | 0.00 455 | 0.00 458 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 0.00 488 | 0.00 491 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| ab-mvs-re | | | 8.28 453 | 11.04 456 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 99.40 146 | 0.00 491 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| uanet | | | 0.00 455 | 0.00 458 | 0.00 469 | 0.00 492 | 0.00 494 | 0.00 481 | 0.00 493 | 0.00 487 | 0.00 488 | 0.00 488 | 0.00 491 | 0.00 488 | 0.00 487 | 0.00 486 | 0.00 484 |
|
| TestfortrainingZip | | | | | | | | 99.97 39 | | | | | | | | | |
|
| WAC-MVS | | | | | | | 90.97 345 | | | | | | | | 86.10 387 | | |
|
| 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 | | | | | | | | 95.78 448 | | | | 59.23 484 | 93.20 128 | 97.74 326 | 91.06 317 | | |
|
| test_post | | | | | | | | | | | | 63.35 481 | 94.43 82 | 98.13 305 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 91.70 443 | 95.12 59 | 97.95 317 | | | |
|
| MTMP | | | | | | | | 99.87 130 | 96.49 414 | | | | | | | | |
|
| 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 | | | | | | | | 99.46 265 | | 94.21 164 | 99.85 18 | | | 99.95 84 | 96.96 196 | | |
|
| 新几何2 | | | | | | | | 99.40 269 | | | | | | | | | |
|
| 无先验 | | | | | | | | 99.49 257 | 98.71 78 | 93.46 197 | | | | 100.00 1 | 94.36 255 | | 99.99 24 |
|
| 原ACMM2 | | | | | | | | 99.90 114 | | | | | | | | | |
|
| testdata2 | | | | | | | | | | | | | | 99.99 39 | 90.54 330 | | |
|
| segment_acmp | | | | | | | | | | | | | 96.68 31 | | | | |
|
| testdata1 | | | | | | | | 99.28 292 | | 96.35 90 | | | | | | | |
|
| plane_prior5 | | | | | | | | | 97.87 254 | | | | | 98.37 286 | 97.79 167 | 89.55 318 | 94.52 330 |
|
| plane_prior4 | | | | | | | | | | | | 98.59 252 | | | | | |
|
| plane_prior3 | | | | | | | 91.64 333 | | | 96.63 73 | 93.01 290 | | | | | | |
|
| plane_prior2 | | | | | | | | 99.84 149 | | 96.38 84 | | | | | | | |
|
| plane_prior | | | | | | | 91.74 327 | 99.86 141 | | 96.76 68 | | | | | | 89.59 317 | |
|
| n2 | | | | | | | | | 0.00 493 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 493 | | | | | | | | |
|
| door-mid | | | | | | | | | 89.69 477 | | | | | | | | |
|
| test11 | | | | | | | | | 98.44 147 | | | | | | | | |
|
| door | | | | | | | | | 90.31 474 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 91.85 323 | | | | | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 97.92 158 | | |
|
| HQP4-MVS | | | | | | | | | | | 93.37 285 | | | 98.39 280 | | | 94.53 328 |
|
| HQP3-MVS | | | | | | | | | 97.89 252 | | | | | | | 89.60 315 | |
|
| HQP2-MVS | | | | | | | | | | | | | 80.65 333 | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 96.26 168 | 96.11 442 | | 91.89 275 | 98.06 166 | | 94.40 84 | | 94.30 258 | | 99.67 129 |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 87.04 351 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 88.23 338 | |
|
| Test By Simon | | | | | | | | | | | | | 92.82 139 | | | | |
|