| LCM-MVSNet | | | 99.93 1 | 99.92 1 | 99.94 1 | 99.99 1 | 99.97 1 | 99.90 1 | 99.89 13 | 99.98 1 | 99.99 1 | 99.96 1 | 99.77 2 | 100.00 1 | 99.81 16 | 100.00 1 | 99.85 30 |
|
| Gipuma |  | | 99.03 81 | 99.16 63 | 98.64 219 | 99.94 2 | 98.51 112 | 99.32 26 | 99.75 42 | 99.58 39 | 98.60 269 | 99.62 40 | 98.22 105 | 99.51 399 | 97.70 190 | 99.73 181 | 97.89 432 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| OurMVSNet-221017-0 | | | 99.37 29 | 99.31 42 | 99.53 39 | 99.91 3 | 98.98 72 | 99.63 7 | 99.58 89 | 99.44 53 | 99.78 40 | 99.76 15 | 96.39 250 | 99.92 65 | 99.44 55 | 99.92 69 | 99.68 71 |
|
| pmmvs6 | | | 99.67 3 | 99.70 3 | 99.60 16 | 99.90 4 | 99.27 28 | 99.53 9 | 99.76 39 | 99.64 27 | 99.84 30 | 99.83 4 | 99.50 9 | 99.87 134 | 99.36 58 | 99.92 69 | 99.64 84 |
|
| PS-MVSNAJss | | | 99.46 17 | 99.49 16 | 99.35 80 | 99.90 4 | 98.15 139 | 99.20 48 | 99.65 69 | 99.48 45 | 99.92 8 | 99.71 22 | 98.07 120 | 99.96 14 | 99.53 48 | 100.00 1 | 99.93 11 |
|
| testf1 | | | 99.25 41 | 99.16 63 | 99.51 49 | 99.89 6 | 99.63 4 | 98.71 104 | 99.69 54 | 98.90 133 | 99.43 106 | 99.35 105 | 98.86 34 | 99.67 322 | 97.81 177 | 99.81 130 | 99.24 279 |
|
| APD_test2 | | | 99.25 41 | 99.16 63 | 99.51 49 | 99.89 6 | 99.63 4 | 98.71 104 | 99.69 54 | 98.90 133 | 99.43 106 | 99.35 105 | 98.86 34 | 99.67 322 | 97.81 177 | 99.81 130 | 99.24 279 |
|
| ANet_high | | | 99.57 10 | 99.67 6 | 99.28 96 | 99.89 6 | 98.09 146 | 99.14 57 | 99.93 5 | 99.82 8 | 99.93 6 | 99.81 8 | 99.17 20 | 99.94 42 | 99.31 62 | 100.00 1 | 99.82 36 |
|
| anonymousdsp | | | 99.51 14 | 99.47 21 | 99.62 10 | 99.88 9 | 99.08 70 | 99.34 23 | 99.69 54 | 98.93 129 | 99.65 64 | 99.72 21 | 98.93 32 | 99.95 26 | 99.11 78 | 100.00 1 | 99.82 36 |
|
| v7n | | | 99.53 12 | 99.57 13 | 99.41 70 | 99.88 9 | 98.54 110 | 99.45 14 | 99.61 78 | 99.66 24 | 99.68 58 | 99.66 32 | 98.44 78 | 99.95 26 | 99.73 28 | 99.96 28 | 99.75 60 |
|
| mvs_tets | | | 99.63 6 | 99.67 6 | 99.49 55 | 99.88 9 | 98.61 102 | 99.34 23 | 99.71 47 | 99.27 74 | 99.90 14 | 99.74 18 | 99.68 4 | 99.97 7 | 99.55 43 | 99.99 5 | 99.88 20 |
|
| test_fmvsmconf0.01_n | | | 99.57 10 | 99.63 10 | 99.36 74 | 99.87 12 | 98.13 142 | 98.08 187 | 99.95 1 | 99.45 51 | 99.98 2 | 99.75 16 | 99.80 1 | 99.97 7 | 99.82 12 | 99.99 5 | 99.99 2 |
|
| jajsoiax | | | 99.58 9 | 99.61 11 | 99.48 57 | 99.87 12 | 98.61 102 | 99.28 40 | 99.66 65 | 99.09 108 | 99.89 18 | 99.68 25 | 99.53 7 | 99.97 7 | 99.50 51 | 99.99 5 | 99.87 22 |
|
| test_djsdf | | | 99.52 13 | 99.51 15 | 99.53 39 | 99.86 14 | 98.74 92 | 99.39 20 | 99.56 105 | 99.11 98 | 99.70 52 | 99.73 20 | 99.00 27 | 99.97 7 | 99.26 66 | 99.98 12 | 99.89 16 |
|
| MIMVSNet1 | | | 99.38 28 | 99.32 40 | 99.55 29 | 99.86 14 | 99.19 43 | 99.41 17 | 99.59 87 | 99.59 37 | 99.71 50 | 99.57 49 | 97.12 205 | 99.90 81 | 99.21 71 | 99.87 98 | 99.54 142 |
|
| LTVRE_ROB | | 98.40 1 | 99.67 3 | 99.71 2 | 99.56 27 | 99.85 16 | 99.11 65 | 99.90 1 | 99.78 36 | 99.63 29 | 99.78 40 | 99.67 30 | 99.48 10 | 99.81 222 | 99.30 63 | 99.97 21 | 99.77 50 |
| 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 |
| UniMVSNet_ETH3D | | | 99.69 2 | 99.69 4 | 99.69 3 | 99.84 17 | 99.34 20 | 99.69 5 | 99.58 89 | 99.90 3 | 99.86 24 | 99.78 13 | 99.58 6 | 99.95 26 | 99.00 88 | 99.95 38 | 99.78 47 |
|
| SixPastTwentyTwo | | | 98.75 131 | 98.62 146 | 99.16 118 | 99.83 18 | 97.96 166 | 99.28 40 | 98.20 379 | 99.37 61 | 99.70 52 | 99.65 36 | 92.65 356 | 99.93 54 | 99.04 85 | 99.84 112 | 99.60 100 |
|
| sc_t1 | | | 99.62 7 | 99.66 8 | 99.53 39 | 99.82 19 | 99.09 69 | 99.50 11 | 99.63 73 | 99.88 4 | 99.86 24 | 99.80 11 | 99.03 24 | 99.89 97 | 99.48 53 | 99.93 56 | 99.60 100 |
|
| Baseline_NR-MVSNet | | | 98.98 89 | 98.86 108 | 99.36 74 | 99.82 19 | 98.55 107 | 97.47 295 | 99.57 96 | 99.37 61 | 99.21 160 | 99.61 43 | 96.76 232 | 99.83 192 | 98.06 154 | 99.83 119 | 99.71 63 |
|
| pm-mvs1 | | | 99.44 19 | 99.48 18 | 99.33 89 | 99.80 21 | 98.63 99 | 99.29 36 | 99.63 73 | 99.30 71 | 99.65 64 | 99.60 45 | 99.16 22 | 99.82 205 | 99.07 81 | 99.83 119 | 99.56 129 |
|
| TransMVSNet (Re) | | | 99.44 19 | 99.47 21 | 99.36 74 | 99.80 21 | 98.58 105 | 99.27 42 | 99.57 96 | 99.39 59 | 99.75 45 | 99.62 40 | 99.17 20 | 99.83 192 | 99.06 83 | 99.62 240 | 99.66 78 |
|
| K. test v3 | | | 98.00 250 | 97.66 275 | 99.03 145 | 99.79 23 | 97.56 202 | 99.19 52 | 92.47 465 | 99.62 33 | 99.52 88 | 99.66 32 | 89.61 388 | 99.96 14 | 99.25 68 | 99.81 130 | 99.56 129 |
|
| test_fmvsmconf0.1_n | | | 99.49 15 | 99.54 14 | 99.34 83 | 99.78 24 | 98.11 143 | 97.77 244 | 99.90 11 | 99.33 66 | 99.97 3 | 99.66 32 | 99.71 3 | 99.96 14 | 99.79 19 | 99.99 5 | 99.96 8 |
|
| APD_test1 | | | 98.83 115 | 98.66 139 | 99.34 83 | 99.78 24 | 99.47 9 | 98.42 149 | 99.45 154 | 98.28 187 | 98.98 197 | 99.19 150 | 97.76 152 | 99.58 373 | 96.57 288 | 99.55 267 | 98.97 334 |
|
| test_vis3_rt | | | 99.14 63 | 99.17 61 | 99.07 135 | 99.78 24 | 98.38 119 | 98.92 82 | 99.94 2 | 97.80 233 | 99.91 12 | 99.67 30 | 97.15 204 | 98.91 458 | 99.76 23 | 99.56 263 | 99.92 12 |
|
| EGC-MVSNET | | | 85.24 444 | 80.54 447 | 99.34 83 | 99.77 27 | 99.20 40 | 99.08 61 | 99.29 234 | 12.08 483 | 20.84 484 | 99.42 90 | 97.55 171 | 99.85 156 | 97.08 236 | 99.72 189 | 98.96 336 |
|
| Anonymous20240521 | | | 98.69 144 | 98.87 104 | 98.16 296 | 99.77 27 | 95.11 338 | 99.08 61 | 99.44 162 | 99.34 65 | 99.33 130 | 99.55 57 | 94.10 331 | 99.94 42 | 99.25 68 | 99.96 28 | 99.42 208 |
|
| FC-MVSNet-test | | | 99.27 38 | 99.25 53 | 99.34 83 | 99.77 27 | 98.37 121 | 99.30 35 | 99.57 96 | 99.61 35 | 99.40 115 | 99.50 69 | 97.12 205 | 99.85 156 | 99.02 87 | 99.94 50 | 99.80 42 |
|
| test_vis1_n | | | 98.31 214 | 98.50 166 | 97.73 331 | 99.76 30 | 94.17 366 | 98.68 107 | 99.91 9 | 96.31 349 | 99.79 39 | 99.57 49 | 92.85 352 | 99.42 419 | 99.79 19 | 99.84 112 | 99.60 100 |
|
| test_fmvs3 | | | 99.12 70 | 99.41 26 | 98.25 284 | 99.76 30 | 95.07 339 | 99.05 67 | 99.94 2 | 97.78 236 | 99.82 34 | 99.84 3 | 98.56 68 | 99.71 297 | 99.96 1 | 99.96 28 | 99.97 4 |
|
| XXY-MVS | | | 99.14 63 | 99.15 68 | 99.10 128 | 99.76 30 | 97.74 191 | 98.85 92 | 99.62 75 | 98.48 170 | 99.37 120 | 99.49 75 | 98.75 46 | 99.86 143 | 98.20 144 | 99.80 141 | 99.71 63 |
|
| TDRefinement | | | 99.42 24 | 99.38 29 | 99.55 29 | 99.76 30 | 99.33 21 | 99.68 6 | 99.71 47 | 99.38 60 | 99.53 83 | 99.61 43 | 98.64 56 | 99.80 231 | 98.24 139 | 99.84 112 | 99.52 154 |
|
| fmvsm_s_conf0.1_n_a | | | 99.17 53 | 99.30 45 | 98.80 184 | 99.75 34 | 96.59 270 | 97.97 217 | 99.86 16 | 98.22 190 | 99.88 21 | 99.71 22 | 98.59 62 | 99.84 174 | 99.73 28 | 99.98 12 | 99.98 3 |
|
| tt0805 | | | 98.69 144 | 98.62 146 | 98.90 171 | 99.75 34 | 99.30 23 | 99.15 56 | 96.97 416 | 98.86 138 | 98.87 230 | 97.62 394 | 98.63 58 | 98.96 455 | 99.41 57 | 98.29 407 | 98.45 398 |
|
| test_vis1_n_1920 | | | 98.40 197 | 98.92 96 | 96.81 393 | 99.74 36 | 90.76 444 | 98.15 175 | 99.91 9 | 98.33 178 | 99.89 18 | 99.55 57 | 95.07 302 | 99.88 115 | 99.76 23 | 99.93 56 | 99.79 44 |
|
| FOURS1 | | | | | | 99.73 37 | 99.67 3 | 99.43 15 | 99.54 114 | 99.43 55 | 99.26 148 | | | | | | |
|
| PEN-MVS | | | 99.41 25 | 99.34 36 | 99.62 10 | 99.73 37 | 99.14 58 | 99.29 36 | 99.54 114 | 99.62 33 | 99.56 74 | 99.42 90 | 98.16 114 | 99.96 14 | 98.78 103 | 99.93 56 | 99.77 50 |
|
| lessismore_v0 | | | | | 98.97 157 | 99.73 37 | 97.53 204 | | 86.71 480 | | 99.37 120 | 99.52 68 | 89.93 384 | 99.92 65 | 98.99 89 | 99.72 189 | 99.44 199 |
|
| SteuartSystems-ACMMP | | | 98.79 124 | 98.54 159 | 99.54 32 | 99.73 37 | 99.16 49 | 98.23 165 | 99.31 218 | 97.92 224 | 98.90 219 | 98.90 237 | 98.00 126 | 99.88 115 | 96.15 320 | 99.72 189 | 99.58 115 |
| Skip Steuart: Steuart Systems R&D Blog. |
| PVSNet_Blended_VisFu | | | 98.17 235 | 98.15 227 | 98.22 290 | 99.73 37 | 95.15 335 | 97.36 309 | 99.68 60 | 94.45 406 | 98.99 196 | 99.27 125 | 96.87 221 | 99.94 42 | 97.13 233 | 99.91 78 | 99.57 123 |
|
| Vis-MVSNet |  | | 99.34 30 | 99.36 33 | 99.27 99 | 99.73 37 | 98.26 128 | 99.17 53 | 99.78 36 | 99.11 98 | 99.27 144 | 99.48 76 | 98.82 37 | 99.95 26 | 98.94 92 | 99.93 56 | 99.59 107 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| tt0320-xc | | | 99.64 5 | 99.68 5 | 99.50 54 | 99.72 43 | 98.98 72 | 99.51 10 | 99.85 18 | 99.86 6 | 99.88 21 | 99.82 5 | 99.02 26 | 99.90 81 | 99.54 44 | 99.95 38 | 99.61 98 |
|
| SSC-MVS | | | 98.71 135 | 98.74 119 | 98.62 225 | 99.72 43 | 96.08 295 | 98.74 97 | 98.64 359 | 99.74 13 | 99.67 60 | 99.24 138 | 94.57 317 | 99.95 26 | 99.11 78 | 99.24 331 | 99.82 36 |
|
| test_f | | | 98.67 153 | 98.87 104 | 98.05 306 | 99.72 43 | 95.59 310 | 98.51 133 | 99.81 31 | 96.30 351 | 99.78 40 | 99.82 5 | 96.14 261 | 98.63 465 | 99.82 12 | 99.93 56 | 99.95 9 |
|
| ACMH | | 96.65 7 | 99.25 41 | 99.24 54 | 99.26 101 | 99.72 43 | 98.38 119 | 99.07 64 | 99.55 109 | 98.30 182 | 99.65 64 | 99.45 85 | 99.22 17 | 99.76 267 | 98.44 129 | 99.77 158 | 99.64 84 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| tt0320 | | | 99.61 8 | 99.65 9 | 99.48 57 | 99.71 47 | 98.94 79 | 99.54 8 | 99.83 25 | 99.87 5 | 99.89 18 | 99.82 5 | 98.75 46 | 99.90 81 | 99.54 44 | 99.95 38 | 99.59 107 |
|
| fmvsm_s_conf0.1_n | | | 99.16 57 | 99.33 38 | 98.64 219 | 99.71 47 | 96.10 290 | 97.87 230 | 99.85 18 | 98.56 166 | 99.90 14 | 99.68 25 | 98.69 52 | 99.85 156 | 99.72 30 | 99.98 12 | 99.97 4 |
|
| PS-CasMVS | | | 99.40 26 | 99.33 38 | 99.62 10 | 99.71 47 | 99.10 66 | 99.29 36 | 99.53 118 | 99.53 42 | 99.46 101 | 99.41 94 | 98.23 102 | 99.95 26 | 98.89 97 | 99.95 38 | 99.81 40 |
|
| DTE-MVSNet | | | 99.43 23 | 99.35 34 | 99.66 7 | 99.71 47 | 99.30 23 | 99.31 30 | 99.51 124 | 99.64 27 | 99.56 74 | 99.46 81 | 98.23 102 | 99.97 7 | 98.78 103 | 99.93 56 | 99.72 62 |
|
| WR-MVS_H | | | 99.33 31 | 99.22 55 | 99.65 8 | 99.71 47 | 99.24 31 | 99.32 26 | 99.55 109 | 99.46 50 | 99.50 94 | 99.34 109 | 97.30 193 | 99.93 54 | 98.90 95 | 99.93 56 | 99.77 50 |
|
| HPM-MVS_fast | | | 99.01 83 | 98.82 112 | 99.57 22 | 99.71 47 | 99.35 17 | 99.00 72 | 99.50 127 | 97.33 282 | 98.94 214 | 98.86 247 | 98.75 46 | 99.82 205 | 97.53 202 | 99.71 198 | 99.56 129 |
|
| ACMH+ | | 96.62 9 | 99.08 77 | 99.00 88 | 99.33 89 | 99.71 47 | 98.83 87 | 98.60 119 | 99.58 89 | 99.11 98 | 99.53 83 | 99.18 154 | 98.81 38 | 99.67 322 | 96.71 274 | 99.77 158 | 99.50 162 |
|
| PMVS |  | 91.26 20 | 97.86 264 | 97.94 251 | 97.65 338 | 99.71 47 | 97.94 168 | 98.52 128 | 98.68 355 | 98.99 121 | 97.52 363 | 99.35 105 | 97.41 186 | 98.18 471 | 91.59 434 | 99.67 219 | 96.82 460 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| FE-MVSNET2 | | | 99.15 58 | 99.22 55 | 98.94 161 | 99.70 55 | 97.49 205 | 98.62 116 | 99.67 64 | 98.85 141 | 99.34 127 | 99.54 63 | 98.47 72 | 99.81 222 | 98.93 93 | 99.91 78 | 99.51 158 |
|
| KinetiMVS | | | 99.03 81 | 99.02 84 | 99.03 145 | 99.70 55 | 97.48 208 | 98.43 146 | 99.29 234 | 99.70 16 | 99.60 71 | 99.07 183 | 96.13 262 | 99.94 42 | 99.42 56 | 99.87 98 | 99.68 71 |
|
| FIs | | | 99.14 63 | 99.09 76 | 99.29 95 | 99.70 55 | 98.28 127 | 99.13 58 | 99.52 123 | 99.48 45 | 99.24 154 | 99.41 94 | 96.79 229 | 99.82 205 | 98.69 113 | 99.88 94 | 99.76 56 |
|
| VPNet | | | 98.87 105 | 98.83 111 | 99.01 149 | 99.70 55 | 97.62 200 | 98.43 146 | 99.35 199 | 99.47 48 | 99.28 142 | 99.05 191 | 96.72 235 | 99.82 205 | 98.09 151 | 99.36 310 | 99.59 107 |
|
| fmvsm_s_conf0.1_n_2 | | | 99.20 51 | 99.38 29 | 98.65 217 | 99.69 59 | 96.08 295 | 97.49 290 | 99.90 11 | 99.53 42 | 99.88 21 | 99.64 37 | 98.51 71 | 99.90 81 | 99.83 10 | 99.98 12 | 99.97 4 |
|
| test_cas_vis1_n_1920 | | | 98.33 211 | 98.68 134 | 97.27 369 | 99.69 59 | 92.29 418 | 98.03 198 | 99.85 18 | 97.62 246 | 99.96 4 | 99.62 40 | 93.98 332 | 99.74 281 | 99.52 50 | 99.86 105 | 99.79 44 |
|
| MP-MVS-pluss | | | 98.57 170 | 98.23 215 | 99.60 16 | 99.69 59 | 99.35 17 | 97.16 331 | 99.38 185 | 94.87 396 | 98.97 201 | 98.99 213 | 98.01 125 | 99.88 115 | 97.29 220 | 99.70 205 | 99.58 115 |
| MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
| SDMVSNet | | | 99.23 46 | 99.32 40 | 98.96 158 | 99.68 62 | 97.35 216 | 98.84 94 | 99.48 137 | 99.69 18 | 99.63 67 | 99.68 25 | 99.03 24 | 99.96 14 | 97.97 165 | 99.92 69 | 99.57 123 |
|
| sd_testset | | | 99.28 37 | 99.31 42 | 99.19 112 | 99.68 62 | 98.06 155 | 99.41 17 | 99.30 226 | 99.69 18 | 99.63 67 | 99.68 25 | 99.25 16 | 99.96 14 | 97.25 223 | 99.92 69 | 99.57 123 |
|
| test_fmvs1_n | | | 98.09 241 | 98.28 206 | 97.52 355 | 99.68 62 | 93.47 397 | 98.63 114 | 99.93 5 | 95.41 384 | 99.68 58 | 99.64 37 | 91.88 367 | 99.48 406 | 99.82 12 | 99.87 98 | 99.62 90 |
|
| CHOSEN 1792x2688 | | | 97.49 293 | 97.14 308 | 98.54 248 | 99.68 62 | 96.09 293 | 96.50 367 | 99.62 75 | 91.58 444 | 98.84 233 | 98.97 220 | 92.36 358 | 99.88 115 | 96.76 267 | 99.95 38 | 99.67 76 |
|
| tfpnnormal | | | 98.90 100 | 98.90 98 | 98.91 168 | 99.67 66 | 97.82 183 | 99.00 72 | 99.44 162 | 99.45 51 | 99.51 93 | 99.24 138 | 98.20 109 | 99.86 143 | 95.92 329 | 99.69 208 | 99.04 321 |
|
| MTAPA | | | 98.88 104 | 98.64 142 | 99.61 14 | 99.67 66 | 99.36 16 | 98.43 146 | 99.20 258 | 98.83 143 | 98.89 222 | 98.90 237 | 96.98 215 | 99.92 65 | 97.16 228 | 99.70 205 | 99.56 129 |
|
| test_fmvsmvis_n_1920 | | | 99.26 40 | 99.49 16 | 98.54 248 | 99.66 68 | 96.97 249 | 98.00 205 | 99.85 18 | 99.24 76 | 99.92 8 | 99.50 69 | 99.39 12 | 99.95 26 | 99.89 3 | 99.98 12 | 98.71 375 |
|
| mvs5depth | | | 99.30 34 | 99.59 12 | 98.44 262 | 99.65 69 | 95.35 327 | 99.82 3 | 99.94 2 | 99.83 7 | 99.42 110 | 99.94 2 | 98.13 117 | 99.96 14 | 99.63 36 | 99.96 28 | 100.00 1 |
|
| fmvsm_l_conf0.5_n_a | | | 99.19 52 | 99.27 48 | 98.94 161 | 99.65 69 | 97.05 244 | 97.80 239 | 99.76 39 | 98.70 148 | 99.78 40 | 99.11 173 | 98.79 42 | 99.95 26 | 99.85 6 | 99.96 28 | 99.83 33 |
|
| WB-MVS | | | 98.52 184 | 98.55 157 | 98.43 263 | 99.65 69 | 95.59 310 | 98.52 128 | 98.77 344 | 99.65 26 | 99.52 88 | 99.00 211 | 94.34 323 | 99.93 54 | 98.65 115 | 98.83 379 | 99.76 56 |
|
| CP-MVSNet | | | 99.21 48 | 99.09 76 | 99.56 27 | 99.65 69 | 98.96 78 | 99.13 58 | 99.34 205 | 99.42 56 | 99.33 130 | 99.26 131 | 97.01 213 | 99.94 42 | 98.74 108 | 99.93 56 | 99.79 44 |
|
| HPM-MVS |  | | 98.79 124 | 98.53 161 | 99.59 20 | 99.65 69 | 99.29 25 | 99.16 54 | 99.43 168 | 96.74 329 | 98.61 267 | 98.38 338 | 98.62 59 | 99.87 134 | 96.47 300 | 99.67 219 | 99.59 107 |
| Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
| RPSCF | | | 98.62 162 | 98.36 192 | 99.42 68 | 99.65 69 | 99.42 11 | 98.55 124 | 99.57 96 | 97.72 240 | 98.90 219 | 99.26 131 | 96.12 264 | 99.52 394 | 95.72 340 | 99.71 198 | 99.32 255 |
|
| NormalMVS | | | 98.26 221 | 97.97 248 | 99.15 121 | 99.64 75 | 97.83 178 | 98.28 159 | 99.43 168 | 99.24 76 | 98.80 241 | 98.85 250 | 89.76 386 | 99.94 42 | 98.04 156 | 99.67 219 | 99.68 71 |
|
| lecture | | | 99.25 41 | 99.12 71 | 99.62 10 | 99.64 75 | 99.40 12 | 98.89 87 | 99.51 124 | 99.19 88 | 99.37 120 | 99.25 136 | 98.36 83 | 99.88 115 | 98.23 141 | 99.67 219 | 99.59 107 |
|
| fmvsm_l_conf0.5_n | | | 99.21 48 | 99.28 47 | 99.02 148 | 99.64 75 | 97.28 223 | 97.82 235 | 99.76 39 | 98.73 145 | 99.82 34 | 99.09 181 | 98.81 38 | 99.95 26 | 99.86 4 | 99.96 28 | 99.83 33 |
|
| test_fmvsmconf_n | | | 99.44 19 | 99.48 18 | 99.31 94 | 99.64 75 | 98.10 145 | 97.68 258 | 99.84 22 | 99.29 72 | 99.92 8 | 99.57 49 | 99.60 5 | 99.96 14 | 99.74 27 | 99.98 12 | 99.89 16 |
|
| TSAR-MVS + MP. | | | 98.63 159 | 98.49 171 | 99.06 141 | 99.64 75 | 97.90 172 | 98.51 133 | 98.94 309 | 96.96 313 | 99.24 154 | 98.89 243 | 97.83 144 | 99.81 222 | 96.88 257 | 99.49 289 | 99.48 180 |
| Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
| PM-MVS | | | 98.82 118 | 98.72 123 | 99.12 124 | 99.64 75 | 98.54 110 | 97.98 213 | 99.68 60 | 97.62 246 | 99.34 127 | 99.18 154 | 97.54 173 | 99.77 261 | 97.79 179 | 99.74 178 | 99.04 321 |
|
| Elysia | | | 99.15 58 | 99.14 69 | 99.18 113 | 99.63 81 | 97.92 169 | 98.50 135 | 99.43 168 | 99.67 21 | 99.70 52 | 99.13 169 | 96.66 238 | 99.98 4 | 99.54 44 | 99.96 28 | 99.64 84 |
|
| StellarMVS | | | 99.15 58 | 99.14 69 | 99.18 113 | 99.63 81 | 97.92 169 | 98.50 135 | 99.43 168 | 99.67 21 | 99.70 52 | 99.13 169 | 96.66 238 | 99.98 4 | 99.54 44 | 99.96 28 | 99.64 84 |
|
| KD-MVS_self_test | | | 99.25 41 | 99.18 60 | 99.44 66 | 99.63 81 | 99.06 71 | 98.69 106 | 99.54 114 | 99.31 69 | 99.62 70 | 99.53 65 | 97.36 190 | 99.86 143 | 99.24 70 | 99.71 198 | 99.39 221 |
|
| EU-MVSNet | | | 97.66 281 | 98.50 166 | 95.13 435 | 99.63 81 | 85.84 466 | 98.35 155 | 98.21 378 | 98.23 189 | 99.54 79 | 99.46 81 | 95.02 303 | 99.68 318 | 98.24 139 | 99.87 98 | 99.87 22 |
|
| HyFIR lowres test | | | 97.19 320 | 96.60 344 | 98.96 158 | 99.62 85 | 97.28 223 | 95.17 432 | 99.50 127 | 94.21 411 | 99.01 191 | 98.32 346 | 86.61 406 | 99.99 2 | 97.10 235 | 99.84 112 | 99.60 100 |
|
| fmvsm_l_conf0.5_n_9 | | | 99.32 33 | 99.43 24 | 98.98 155 | 99.59 86 | 97.18 235 | 97.44 299 | 99.83 25 | 99.56 40 | 99.91 12 | 99.34 109 | 99.36 13 | 99.93 54 | 99.83 10 | 99.98 12 | 99.85 30 |
|
| fmvsm_l_conf0.5_n_3 | | | 99.45 18 | 99.48 18 | 99.34 83 | 99.59 86 | 98.21 136 | 97.82 235 | 99.84 22 | 99.41 58 | 99.92 8 | 99.41 94 | 99.51 8 | 99.95 26 | 99.84 9 | 99.97 21 | 99.87 22 |
|
| MED-MVS test | | | | | 99.45 64 | 99.58 88 | 98.93 80 | 98.68 107 | 99.60 80 | 96.46 342 | 99.53 83 | 98.77 270 | | 99.83 192 | 96.67 277 | 99.64 230 | 99.58 115 |
|
| MED-MVS | | | 98.90 100 | 98.72 123 | 99.45 64 | 99.58 88 | 98.93 80 | 98.68 107 | 99.60 80 | 98.14 208 | 99.53 83 | 98.77 270 | 97.87 141 | 99.83 192 | 96.67 277 | 99.64 230 | 99.58 115 |
|
| TestfortrainingZip a | | | 98.95 93 | 98.72 123 | 99.64 9 | 99.58 88 | 99.32 22 | 98.68 107 | 99.60 80 | 96.46 342 | 99.53 83 | 98.77 270 | 97.87 141 | 99.83 192 | 98.39 132 | 99.64 230 | 99.77 50 |
|
| FE-MVSNET | | | 98.59 167 | 98.50 166 | 98.87 172 | 99.58 88 | 97.30 221 | 98.08 187 | 99.74 43 | 96.94 315 | 98.97 201 | 99.10 176 | 96.94 217 | 99.74 281 | 97.33 218 | 99.86 105 | 99.55 136 |
|
| mmtdpeth | | | 99.30 34 | 99.42 25 | 98.92 167 | 99.58 88 | 96.89 257 | 99.48 13 | 99.92 7 | 99.92 2 | 98.26 305 | 99.80 11 | 98.33 89 | 99.91 74 | 99.56 41 | 99.95 38 | 99.97 4 |
|
| ACMMP_NAP | | | 98.75 131 | 98.48 172 | 99.57 22 | 99.58 88 | 99.29 25 | 97.82 235 | 99.25 247 | 96.94 315 | 98.78 243 | 99.12 172 | 98.02 124 | 99.84 174 | 97.13 233 | 99.67 219 | 99.59 107 |
|
| nrg030 | | | 99.40 26 | 99.35 34 | 99.54 32 | 99.58 88 | 99.13 61 | 98.98 75 | 99.48 137 | 99.68 20 | 99.46 101 | 99.26 131 | 98.62 59 | 99.73 288 | 99.17 75 | 99.92 69 | 99.76 56 |
|
| VDDNet | | | 98.21 228 | 97.95 249 | 99.01 149 | 99.58 88 | 97.74 191 | 99.01 70 | 97.29 407 | 99.67 21 | 98.97 201 | 99.50 69 | 90.45 381 | 99.80 231 | 97.88 172 | 99.20 339 | 99.48 180 |
|
| COLMAP_ROB |  | 96.50 10 | 98.99 86 | 98.85 110 | 99.41 70 | 99.58 88 | 99.10 66 | 98.74 97 | 99.56 105 | 99.09 108 | 99.33 130 | 99.19 150 | 98.40 80 | 99.72 296 | 95.98 327 | 99.76 173 | 99.42 208 |
| Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
| test_fmvsm_n_1920 | | | 99.33 31 | 99.45 23 | 98.99 151 | 99.57 97 | 97.73 193 | 97.93 219 | 99.83 25 | 99.22 79 | 99.93 6 | 99.30 119 | 99.42 11 | 99.96 14 | 99.85 6 | 99.99 5 | 99.29 265 |
|
| ZNCC-MVS | | | 98.68 150 | 98.40 184 | 99.54 32 | 99.57 97 | 99.21 34 | 98.46 143 | 99.29 234 | 97.28 288 | 98.11 317 | 98.39 336 | 98.00 126 | 99.87 134 | 96.86 260 | 99.64 230 | 99.55 136 |
|
| MSP-MVS | | | 98.40 197 | 98.00 243 | 99.61 14 | 99.57 97 | 99.25 30 | 98.57 122 | 99.35 199 | 97.55 257 | 99.31 138 | 97.71 387 | 94.61 316 | 99.88 115 | 96.14 321 | 99.19 342 | 99.70 68 |
| 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 |
| testgi | | | 98.32 212 | 98.39 187 | 98.13 297 | 99.57 97 | 95.54 313 | 97.78 241 | 99.49 135 | 97.37 279 | 99.19 162 | 97.65 391 | 98.96 29 | 99.49 403 | 96.50 299 | 98.99 367 | 99.34 246 |
|
| MP-MVS |  | | 98.46 190 | 98.09 232 | 99.54 32 | 99.57 97 | 99.22 33 | 98.50 135 | 99.19 262 | 97.61 249 | 97.58 357 | 98.66 298 | 97.40 187 | 99.88 115 | 94.72 366 | 99.60 247 | 99.54 142 |
| Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
| LPG-MVS_test | | | 98.71 135 | 98.46 176 | 99.47 61 | 99.57 97 | 98.97 74 | 98.23 165 | 99.48 137 | 96.60 334 | 99.10 173 | 99.06 184 | 98.71 50 | 99.83 192 | 95.58 347 | 99.78 152 | 99.62 90 |
|
| LGP-MVS_train | | | | | 99.47 61 | 99.57 97 | 98.97 74 | | 99.48 137 | 96.60 334 | 99.10 173 | 99.06 184 | 98.71 50 | 99.83 192 | 95.58 347 | 99.78 152 | 99.62 90 |
|
| IS-MVSNet | | | 98.19 231 | 97.90 257 | 99.08 133 | 99.57 97 | 97.97 163 | 99.31 30 | 98.32 374 | 99.01 120 | 98.98 197 | 99.03 195 | 91.59 369 | 99.79 244 | 95.49 349 | 99.80 141 | 99.48 180 |
|
| viewdifsd2359ckpt11 | | | 98.84 112 | 99.04 81 | 98.24 286 | 99.56 105 | 95.51 315 | 97.38 304 | 99.70 52 | 99.16 93 | 99.57 72 | 99.40 97 | 98.26 98 | 99.71 297 | 98.55 124 | 99.82 124 | 99.50 162 |
|
| viewmsd2359difaftdt | | | 98.84 112 | 99.04 81 | 98.24 286 | 99.56 105 | 95.51 315 | 97.38 304 | 99.70 52 | 99.16 93 | 99.57 72 | 99.40 97 | 98.26 98 | 99.71 297 | 98.55 124 | 99.82 124 | 99.50 162 |
|
| dcpmvs_2 | | | 98.78 126 | 99.11 72 | 97.78 321 | 99.56 105 | 93.67 392 | 99.06 65 | 99.86 16 | 99.50 44 | 99.66 61 | 99.26 131 | 97.21 201 | 99.99 2 | 98.00 161 | 99.91 78 | 99.68 71 |
|
| test_0402 | | | 98.76 130 | 98.71 128 | 98.93 164 | 99.56 105 | 98.14 141 | 98.45 145 | 99.34 205 | 99.28 73 | 98.95 207 | 98.91 234 | 98.34 88 | 99.79 244 | 95.63 344 | 99.91 78 | 98.86 353 |
|
| EPP-MVSNet | | | 98.30 215 | 98.04 239 | 99.07 135 | 99.56 105 | 97.83 178 | 99.29 36 | 98.07 385 | 99.03 118 | 98.59 271 | 99.13 169 | 92.16 362 | 99.90 81 | 96.87 258 | 99.68 213 | 99.49 169 |
|
| ACMMP |  | | 98.75 131 | 98.50 166 | 99.52 45 | 99.56 105 | 99.16 49 | 98.87 88 | 99.37 189 | 97.16 303 | 98.82 237 | 99.01 207 | 97.71 155 | 99.87 134 | 96.29 312 | 99.69 208 | 99.54 142 |
| 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 |
| fmvsm_s_conf0.5_n_a | | | 99.10 72 | 99.20 59 | 98.78 191 | 99.55 111 | 96.59 270 | 97.79 240 | 99.82 30 | 98.21 192 | 99.81 37 | 99.53 65 | 98.46 76 | 99.84 174 | 99.70 33 | 99.97 21 | 99.90 15 |
|
| fmvsm_s_conf0.5_n | | | 99.09 73 | 99.26 51 | 98.61 229 | 99.55 111 | 96.09 293 | 97.74 251 | 99.81 31 | 98.55 167 | 99.85 27 | 99.55 57 | 98.60 61 | 99.84 174 | 99.69 35 | 99.98 12 | 99.89 16 |
|
| FMVSNet1 | | | 99.17 53 | 99.17 61 | 99.17 115 | 99.55 111 | 98.24 130 | 99.20 48 | 99.44 162 | 99.21 81 | 99.43 106 | 99.55 57 | 97.82 147 | 99.86 143 | 98.42 131 | 99.89 92 | 99.41 211 |
|
| Vis-MVSNet (Re-imp) | | | 97.46 295 | 97.16 305 | 98.34 275 | 99.55 111 | 96.10 290 | 98.94 80 | 98.44 368 | 98.32 180 | 98.16 311 | 98.62 307 | 88.76 393 | 99.73 288 | 93.88 392 | 99.79 147 | 99.18 299 |
|
| ACMM | | 96.08 12 | 98.91 98 | 98.73 121 | 99.48 57 | 99.55 111 | 99.14 58 | 98.07 191 | 99.37 189 | 97.62 246 | 99.04 187 | 98.96 223 | 98.84 36 | 99.79 244 | 97.43 212 | 99.65 228 | 99.49 169 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| test_fmvs2 | | | 98.70 140 | 98.97 92 | 97.89 314 | 99.54 116 | 94.05 369 | 98.55 124 | 99.92 7 | 96.78 327 | 99.72 48 | 99.78 13 | 96.60 242 | 99.67 322 | 99.91 2 | 99.90 86 | 99.94 10 |
|
| mPP-MVS | | | 98.64 157 | 98.34 195 | 99.54 32 | 99.54 116 | 99.17 45 | 98.63 114 | 99.24 252 | 97.47 265 | 98.09 319 | 98.68 293 | 97.62 164 | 99.89 97 | 96.22 315 | 99.62 240 | 99.57 123 |
|
| XVG-ACMP-BASELINE | | | 98.56 171 | 98.34 195 | 99.22 109 | 99.54 116 | 98.59 104 | 97.71 254 | 99.46 150 | 97.25 291 | 98.98 197 | 98.99 213 | 97.54 173 | 99.84 174 | 95.88 330 | 99.74 178 | 99.23 281 |
|
| viewmacassd2359aftdt | | | 98.86 109 | 98.87 104 | 98.83 177 | 99.53 119 | 97.32 220 | 97.70 256 | 99.64 71 | 98.22 190 | 99.25 152 | 99.27 125 | 98.40 80 | 99.61 359 | 97.98 164 | 99.87 98 | 99.55 136 |
|
| region2R | | | 98.69 144 | 98.40 184 | 99.54 32 | 99.53 119 | 99.17 45 | 98.52 128 | 99.31 218 | 97.46 270 | 98.44 290 | 98.51 321 | 97.83 144 | 99.88 115 | 96.46 301 | 99.58 256 | 99.58 115 |
|
| PGM-MVS | | | 98.66 154 | 98.37 191 | 99.55 29 | 99.53 119 | 99.18 44 | 98.23 165 | 99.49 135 | 97.01 312 | 98.69 254 | 98.88 244 | 98.00 126 | 99.89 97 | 95.87 333 | 99.59 251 | 99.58 115 |
|
| E4 | | | 98.87 105 | 98.88 101 | 98.81 181 | 99.52 122 | 97.23 226 | 97.62 269 | 99.61 78 | 98.58 161 | 99.18 166 | 99.33 112 | 98.29 92 | 99.69 308 | 97.99 163 | 99.83 119 | 99.52 154 |
|
| Patchmatch-RL test | | | 97.26 313 | 97.02 314 | 97.99 310 | 99.52 122 | 95.53 314 | 96.13 392 | 99.71 47 | 97.47 265 | 99.27 144 | 99.16 160 | 84.30 427 | 99.62 352 | 97.89 169 | 99.77 158 | 98.81 361 |
|
| ACMMPR | | | 98.70 140 | 98.42 182 | 99.54 32 | 99.52 122 | 99.14 58 | 98.52 128 | 99.31 218 | 97.47 265 | 98.56 277 | 98.54 316 | 97.75 153 | 99.88 115 | 96.57 288 | 99.59 251 | 99.58 115 |
|
| fmvsm_s_conf0.5_n_9 | | | 99.17 53 | 99.38 29 | 98.53 250 | 99.51 125 | 95.82 305 | 97.62 269 | 99.78 36 | 99.72 15 | 99.90 14 | 99.48 76 | 98.66 54 | 99.89 97 | 99.85 6 | 99.93 56 | 99.89 16 |
|
| AstraMVS | | | 98.16 237 | 98.07 237 | 98.41 265 | 99.51 125 | 95.86 302 | 98.00 205 | 95.14 448 | 98.97 124 | 99.43 106 | 99.24 138 | 93.25 340 | 99.84 174 | 99.21 71 | 99.87 98 | 99.54 142 |
|
| fmvsm_s_conf0.5_n_8 | | | 99.13 67 | 99.26 51 | 98.74 204 | 99.51 125 | 96.44 282 | 97.65 264 | 99.65 69 | 99.66 24 | 99.78 40 | 99.48 76 | 97.92 134 | 99.93 54 | 99.72 30 | 99.95 38 | 99.87 22 |
|
| GST-MVS | | | 98.61 163 | 98.30 203 | 99.52 45 | 99.51 125 | 99.20 40 | 98.26 163 | 99.25 247 | 97.44 273 | 98.67 257 | 98.39 336 | 97.68 156 | 99.85 156 | 96.00 325 | 99.51 279 | 99.52 154 |
|
| Anonymous20231206 | | | 98.21 228 | 98.21 216 | 98.20 291 | 99.51 125 | 95.43 324 | 98.13 177 | 99.32 213 | 96.16 355 | 98.93 215 | 98.82 260 | 96.00 269 | 99.83 192 | 97.32 219 | 99.73 181 | 99.36 239 |
|
| ACMP | | 95.32 15 | 98.41 194 | 98.09 232 | 99.36 74 | 99.51 125 | 98.79 90 | 97.68 258 | 99.38 185 | 95.76 371 | 98.81 239 | 98.82 260 | 98.36 83 | 99.82 205 | 94.75 363 | 99.77 158 | 99.48 180 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| LuminaMVS | | | 98.39 203 | 98.20 217 | 98.98 155 | 99.50 131 | 97.49 205 | 97.78 241 | 97.69 394 | 98.75 144 | 99.49 95 | 99.25 136 | 92.30 360 | 99.94 42 | 99.14 76 | 99.88 94 | 99.50 162 |
|
| DVP-MVS |  | | 98.77 129 | 98.52 162 | 99.52 45 | 99.50 131 | 99.21 34 | 98.02 201 | 98.84 333 | 97.97 218 | 99.08 175 | 99.02 196 | 97.61 166 | 99.88 115 | 96.99 244 | 99.63 237 | 99.48 180 |
| 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 |
| test_0728_SECOND | | | | | 99.60 16 | 99.50 131 | 99.23 32 | 98.02 201 | 99.32 213 | | | | | 99.88 115 | 96.99 244 | 99.63 237 | 99.68 71 |
|
| test0726 | | | | | | 99.50 131 | 99.21 34 | 98.17 173 | 99.35 199 | 97.97 218 | 99.26 148 | 99.06 184 | 97.61 166 | | | | |
|
| AllTest | | | 98.44 192 | 98.20 217 | 99.16 118 | 99.50 131 | 98.55 107 | 98.25 164 | 99.58 89 | 96.80 325 | 98.88 226 | 99.06 184 | 97.65 159 | 99.57 375 | 94.45 373 | 99.61 245 | 99.37 232 |
|
| TestCases | | | | | 99.16 118 | 99.50 131 | 98.55 107 | | 99.58 89 | 96.80 325 | 98.88 226 | 99.06 184 | 97.65 159 | 99.57 375 | 94.45 373 | 99.61 245 | 99.37 232 |
|
| XVG-OURS | | | 98.53 180 | 98.34 195 | 99.11 126 | 99.50 131 | 98.82 89 | 95.97 398 | 99.50 127 | 97.30 286 | 99.05 185 | 98.98 218 | 99.35 14 | 99.32 433 | 95.72 340 | 99.68 213 | 99.18 299 |
|
| EG-PatchMatch MVS | | | 98.99 86 | 99.01 86 | 98.94 161 | 99.50 131 | 97.47 209 | 98.04 196 | 99.59 87 | 98.15 207 | 99.40 115 | 99.36 104 | 98.58 67 | 99.76 267 | 98.78 103 | 99.68 213 | 99.59 107 |
|
| fmvsm_s_conf0.5_n_2 | | | 99.14 63 | 99.31 42 | 98.63 223 | 99.49 139 | 96.08 295 | 97.38 304 | 99.81 31 | 99.48 45 | 99.84 30 | 99.57 49 | 98.46 76 | 99.89 97 | 99.82 12 | 99.97 21 | 99.91 13 |
|
| SED-MVS | | | 98.91 98 | 98.72 123 | 99.49 55 | 99.49 139 | 99.17 45 | 98.10 184 | 99.31 218 | 98.03 214 | 99.66 61 | 99.02 196 | 98.36 83 | 99.88 115 | 96.91 250 | 99.62 240 | 99.41 211 |
|
| IU-MVS | | | | | | 99.49 139 | 99.15 53 | | 98.87 324 | 92.97 429 | 99.41 112 | | | | 96.76 267 | 99.62 240 | 99.66 78 |
|
| test_241102_ONE | | | | | | 99.49 139 | 99.17 45 | | 99.31 218 | 97.98 217 | 99.66 61 | 98.90 237 | 98.36 83 | 99.48 406 | | | |
|
| UA-Net | | | 99.47 16 | 99.40 27 | 99.70 2 | 99.49 139 | 99.29 25 | 99.80 4 | 99.72 45 | 99.82 8 | 99.04 187 | 99.81 8 | 98.05 123 | 99.96 14 | 98.85 99 | 99.99 5 | 99.86 28 |
|
| HFP-MVS | | | 98.71 135 | 98.44 179 | 99.51 49 | 99.49 139 | 99.16 49 | 98.52 128 | 99.31 218 | 97.47 265 | 98.58 273 | 98.50 325 | 97.97 130 | 99.85 156 | 96.57 288 | 99.59 251 | 99.53 151 |
|
| VPA-MVSNet | | | 99.30 34 | 99.30 45 | 99.28 96 | 99.49 139 | 98.36 124 | 99.00 72 | 99.45 154 | 99.63 29 | 99.52 88 | 99.44 86 | 98.25 100 | 99.88 115 | 99.09 80 | 99.84 112 | 99.62 90 |
|
| XVG-OURS-SEG-HR | | | 98.49 187 | 98.28 206 | 99.14 122 | 99.49 139 | 98.83 87 | 96.54 363 | 99.48 137 | 97.32 284 | 99.11 170 | 98.61 309 | 99.33 15 | 99.30 436 | 96.23 314 | 98.38 403 | 99.28 268 |
|
| fmvsm_s_conf0.5_n_11 | | | 99.21 48 | 99.34 36 | 98.80 184 | 99.48 147 | 96.56 275 | 97.97 217 | 99.69 54 | 99.63 29 | 99.84 30 | 99.54 63 | 98.21 107 | 99.94 42 | 99.76 23 | 99.95 38 | 99.88 20 |
|
| 114514_t | | | 96.50 353 | 95.77 362 | 98.69 212 | 99.48 147 | 97.43 213 | 97.84 234 | 99.55 109 | 81.42 476 | 96.51 416 | 98.58 313 | 95.53 289 | 99.67 322 | 93.41 405 | 99.58 256 | 98.98 331 |
|
| IterMVS-LS | | | 98.55 175 | 98.70 131 | 98.09 299 | 99.48 147 | 94.73 349 | 97.22 325 | 99.39 183 | 98.97 124 | 99.38 118 | 99.31 118 | 96.00 269 | 99.93 54 | 98.58 118 | 99.97 21 | 99.60 100 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| fmvsm_s_conf0.5_n_10 | | | 99.15 58 | 99.27 48 | 98.78 191 | 99.47 150 | 96.56 275 | 97.75 250 | 99.71 47 | 99.60 36 | 99.74 47 | 99.44 86 | 97.96 131 | 99.95 26 | 99.86 4 | 99.94 50 | 99.82 36 |
|
| fmvsm_s_conf0.5_n_5 | | | 99.07 79 | 99.10 74 | 98.99 151 | 99.47 150 | 97.22 229 | 97.40 301 | 99.83 25 | 97.61 249 | 99.85 27 | 99.30 119 | 98.80 40 | 99.95 26 | 99.71 32 | 99.90 86 | 99.78 47 |
|
| v8 | | | 99.01 83 | 99.16 63 | 98.57 236 | 99.47 150 | 96.31 287 | 98.90 83 | 99.47 146 | 99.03 118 | 99.52 88 | 99.57 49 | 96.93 218 | 99.81 222 | 99.60 37 | 99.98 12 | 99.60 100 |
|
| SSC-MVS3.2 | | | 98.53 180 | 98.79 115 | 97.74 328 | 99.46 153 | 93.62 395 | 96.45 369 | 99.34 205 | 99.33 66 | 98.93 215 | 98.70 289 | 97.90 135 | 99.90 81 | 99.12 77 | 99.92 69 | 99.69 70 |
|
| fmvsm_s_conf0.5_n_3 | | | 99.22 47 | 99.37 32 | 98.78 191 | 99.46 153 | 96.58 273 | 97.65 264 | 99.72 45 | 99.47 48 | 99.86 24 | 99.50 69 | 98.94 30 | 99.89 97 | 99.75 26 | 99.97 21 | 99.86 28 |
|
| XVS | | | 98.72 134 | 98.45 177 | 99.53 39 | 99.46 153 | 99.21 34 | 98.65 112 | 99.34 205 | 98.62 155 | 97.54 361 | 98.63 305 | 97.50 179 | 99.83 192 | 96.79 263 | 99.53 273 | 99.56 129 |
|
| X-MVStestdata | | | 94.32 402 | 92.59 421 | 99.53 39 | 99.46 153 | 99.21 34 | 98.65 112 | 99.34 205 | 98.62 155 | 97.54 361 | 45.85 481 | 97.50 179 | 99.83 192 | 96.79 263 | 99.53 273 | 99.56 129 |
|
| test20.03 | | | 98.78 126 | 98.77 118 | 98.78 191 | 99.46 153 | 97.20 232 | 97.78 241 | 99.24 252 | 99.04 117 | 99.41 112 | 98.90 237 | 97.65 159 | 99.76 267 | 97.70 190 | 99.79 147 | 99.39 221 |
|
| guyue | | | 98.01 249 | 97.93 253 | 98.26 282 | 99.45 158 | 95.48 319 | 98.08 187 | 96.24 431 | 98.89 135 | 99.34 127 | 99.14 167 | 91.32 373 | 99.82 205 | 99.07 81 | 99.83 119 | 99.48 180 |
|
| CSCG | | | 98.68 150 | 98.50 166 | 99.20 110 | 99.45 158 | 98.63 99 | 98.56 123 | 99.57 96 | 97.87 228 | 98.85 231 | 98.04 367 | 97.66 158 | 99.84 174 | 96.72 272 | 99.81 130 | 99.13 310 |
|
| GeoE | | | 99.05 80 | 98.99 90 | 99.25 104 | 99.44 160 | 98.35 125 | 98.73 101 | 99.56 105 | 98.42 173 | 98.91 218 | 98.81 263 | 98.94 30 | 99.91 74 | 98.35 134 | 99.73 181 | 99.49 169 |
|
| v148 | | | 98.45 191 | 98.60 151 | 98.00 309 | 99.44 160 | 94.98 341 | 97.44 299 | 99.06 288 | 98.30 182 | 99.32 136 | 98.97 220 | 96.65 240 | 99.62 352 | 98.37 133 | 99.85 107 | 99.39 221 |
|
| v10 | | | 98.97 90 | 99.11 72 | 98.55 243 | 99.44 160 | 96.21 289 | 98.90 83 | 99.55 109 | 98.73 145 | 99.48 96 | 99.60 45 | 96.63 241 | 99.83 192 | 99.70 33 | 99.99 5 | 99.61 98 |
|
| V42 | | | 98.78 126 | 98.78 117 | 98.76 198 | 99.44 160 | 97.04 245 | 98.27 162 | 99.19 262 | 97.87 228 | 99.25 152 | 99.16 160 | 96.84 222 | 99.78 255 | 99.21 71 | 99.84 112 | 99.46 190 |
|
| MDA-MVSNet-bldmvs | | | 97.94 255 | 97.91 256 | 98.06 304 | 99.44 160 | 94.96 342 | 96.63 359 | 99.15 278 | 98.35 176 | 98.83 234 | 99.11 173 | 94.31 324 | 99.85 156 | 96.60 285 | 98.72 385 | 99.37 232 |
|
| viewdifsd2359ckpt07 | | | 98.71 135 | 98.86 108 | 98.26 282 | 99.43 165 | 95.65 309 | 97.20 326 | 99.66 65 | 99.20 83 | 99.29 140 | 99.01 207 | 98.29 92 | 99.73 288 | 97.92 168 | 99.75 177 | 99.39 221 |
|
| casdiffmvs_mvg |  | | 99.12 70 | 99.16 63 | 98.99 151 | 99.43 165 | 97.73 193 | 98.00 205 | 99.62 75 | 99.22 79 | 99.55 77 | 99.22 144 | 98.93 32 | 99.75 275 | 98.66 114 | 99.81 130 | 99.50 162 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| SSM_0404 | | | 98.90 100 | 99.01 86 | 98.57 236 | 99.42 167 | 96.59 270 | 98.13 177 | 99.66 65 | 99.09 108 | 99.30 139 | 99.02 196 | 98.79 42 | 99.89 97 | 97.87 174 | 99.80 141 | 99.23 281 |
|
| test1111 | | | 96.49 354 | 96.82 328 | 95.52 428 | 99.42 167 | 87.08 463 | 99.22 45 | 87.14 479 | 99.11 98 | 99.46 101 | 99.58 47 | 88.69 394 | 99.86 143 | 98.80 101 | 99.95 38 | 99.62 90 |
|
| v2v482 | | | 98.56 171 | 98.62 146 | 98.37 272 | 99.42 167 | 95.81 306 | 97.58 278 | 99.16 273 | 97.90 226 | 99.28 142 | 99.01 207 | 95.98 274 | 99.79 244 | 99.33 60 | 99.90 86 | 99.51 158 |
|
| OPM-MVS | | | 98.56 171 | 98.32 201 | 99.25 104 | 99.41 170 | 98.73 95 | 97.13 333 | 99.18 266 | 97.10 306 | 98.75 249 | 98.92 231 | 98.18 110 | 99.65 342 | 96.68 276 | 99.56 263 | 99.37 232 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| PMMVS2 | | | 98.07 243 | 98.08 235 | 98.04 307 | 99.41 170 | 94.59 355 | 94.59 450 | 99.40 181 | 97.50 262 | 98.82 237 | 98.83 257 | 96.83 224 | 99.84 174 | 97.50 205 | 99.81 130 | 99.71 63 |
|
| E2 | | | 98.70 140 | 98.68 134 | 98.73 206 | 99.40 172 | 97.10 242 | 97.48 291 | 99.57 96 | 98.09 211 | 99.00 192 | 99.20 147 | 97.90 135 | 99.67 322 | 97.73 188 | 99.77 158 | 99.43 203 |
|
| E3 | | | 98.69 144 | 98.68 134 | 98.73 206 | 99.40 172 | 97.10 242 | 97.48 291 | 99.57 96 | 98.09 211 | 99.00 192 | 99.20 147 | 97.90 135 | 99.67 322 | 97.73 188 | 99.77 158 | 99.43 203 |
|
| test_one_0601 | | | | | | 99.39 174 | 99.20 40 | | 99.31 218 | 98.49 169 | 98.66 259 | 99.02 196 | 97.64 162 | | | | |
|
| mvsany_test3 | | | 98.87 105 | 98.92 96 | 98.74 204 | 99.38 175 | 96.94 253 | 98.58 121 | 99.10 283 | 96.49 339 | 99.96 4 | 99.81 8 | 98.18 110 | 99.45 414 | 98.97 90 | 99.79 147 | 99.83 33 |
|
| patch_mono-2 | | | 98.51 185 | 98.63 144 | 98.17 294 | 99.38 175 | 94.78 346 | 97.36 309 | 99.69 54 | 98.16 202 | 98.49 286 | 99.29 122 | 97.06 208 | 99.97 7 | 98.29 138 | 99.91 78 | 99.76 56 |
|
| test2506 | | | 92.39 433 | 91.89 435 | 93.89 449 | 99.38 175 | 82.28 480 | 99.32 26 | 66.03 487 | 99.08 112 | 98.77 246 | 99.57 49 | 66.26 474 | 99.84 174 | 98.71 111 | 99.95 38 | 99.54 142 |
|
| ECVR-MVS |  | | 96.42 356 | 96.61 342 | 95.85 420 | 99.38 175 | 88.18 458 | 99.22 45 | 86.00 481 | 99.08 112 | 99.36 123 | 99.57 49 | 88.47 399 | 99.82 205 | 98.52 126 | 99.95 38 | 99.54 142 |
|
| casdiffmvs |  | | 98.95 93 | 99.00 88 | 98.81 181 | 99.38 175 | 97.33 218 | 97.82 235 | 99.57 96 | 99.17 92 | 99.35 125 | 99.17 158 | 98.35 87 | 99.69 308 | 98.46 128 | 99.73 181 | 99.41 211 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| baseline | | | 98.96 92 | 99.02 84 | 98.76 198 | 99.38 175 | 97.26 225 | 98.49 138 | 99.50 127 | 98.86 138 | 99.19 162 | 99.06 184 | 98.23 102 | 99.69 308 | 98.71 111 | 99.76 173 | 99.33 252 |
|
| TranMVSNet+NR-MVSNet | | | 99.17 53 | 99.07 79 | 99.46 63 | 99.37 181 | 98.87 85 | 98.39 151 | 99.42 174 | 99.42 56 | 99.36 123 | 99.06 184 | 98.38 82 | 99.95 26 | 98.34 135 | 99.90 86 | 99.57 123 |
|
| fmvsm_s_conf0.5_n_6 | | | 99.08 77 | 99.21 58 | 98.69 212 | 99.36 182 | 96.51 277 | 97.62 269 | 99.68 60 | 98.43 172 | 99.85 27 | 99.10 176 | 99.12 23 | 99.88 115 | 99.77 22 | 99.92 69 | 99.67 76 |
|
| tttt0517 | | | 95.64 381 | 94.98 391 | 97.64 341 | 99.36 182 | 93.81 387 | 98.72 102 | 90.47 473 | 98.08 213 | 98.67 257 | 98.34 343 | 73.88 460 | 99.92 65 | 97.77 181 | 99.51 279 | 99.20 291 |
|
| test_part2 | | | | | | 99.36 182 | 99.10 66 | | | | 99.05 185 | | | | | | |
|
| v1144 | | | 98.60 165 | 98.66 139 | 98.41 265 | 99.36 182 | 95.90 300 | 97.58 278 | 99.34 205 | 97.51 261 | 99.27 144 | 99.15 164 | 96.34 255 | 99.80 231 | 99.47 54 | 99.93 56 | 99.51 158 |
|
| CP-MVS | | | 98.70 140 | 98.42 182 | 99.52 45 | 99.36 182 | 99.12 63 | 98.72 102 | 99.36 193 | 97.54 259 | 98.30 299 | 98.40 335 | 97.86 143 | 99.89 97 | 96.53 297 | 99.72 189 | 99.56 129 |
|
| diffmvs_AUTHOR | | | 98.50 186 | 98.59 153 | 98.23 289 | 99.35 187 | 95.48 319 | 96.61 360 | 99.60 80 | 98.37 174 | 98.90 219 | 99.00 211 | 97.37 189 | 99.76 267 | 98.22 142 | 99.85 107 | 99.46 190 |
|
| Test_1112_low_res | | | 96.99 335 | 96.55 346 | 98.31 278 | 99.35 187 | 95.47 322 | 95.84 410 | 99.53 118 | 91.51 446 | 96.80 403 | 98.48 328 | 91.36 372 | 99.83 192 | 96.58 286 | 99.53 273 | 99.62 90 |
|
| DeepC-MVS | | 97.60 4 | 98.97 90 | 98.93 95 | 99.10 128 | 99.35 187 | 97.98 162 | 98.01 204 | 99.46 150 | 97.56 255 | 99.54 79 | 99.50 69 | 98.97 28 | 99.84 174 | 98.06 154 | 99.92 69 | 99.49 169 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| 1112_ss | | | 97.29 312 | 96.86 324 | 98.58 233 | 99.34 190 | 96.32 286 | 96.75 352 | 99.58 89 | 93.14 427 | 96.89 398 | 97.48 401 | 92.11 364 | 99.86 143 | 96.91 250 | 99.54 269 | 99.57 123 |
|
| reproduce_model | | | 99.15 58 | 98.97 92 | 99.67 4 | 99.33 191 | 99.44 10 | 98.15 175 | 99.47 146 | 99.12 97 | 99.52 88 | 99.32 117 | 98.31 90 | 99.90 81 | 97.78 180 | 99.73 181 | 99.66 78 |
|
| MVSMamba_PlusPlus | | | 98.83 115 | 98.98 91 | 98.36 273 | 99.32 192 | 96.58 273 | 98.90 83 | 99.41 178 | 99.75 11 | 98.72 252 | 99.50 69 | 96.17 260 | 99.94 42 | 99.27 65 | 99.78 152 | 98.57 391 |
|
| fmvsm_s_conf0.5_n_4 | | | 99.01 83 | 99.22 55 | 98.38 269 | 99.31 193 | 95.48 319 | 97.56 280 | 99.73 44 | 98.87 136 | 99.75 45 | 99.27 125 | 98.80 40 | 99.86 143 | 99.80 17 | 99.90 86 | 99.81 40 |
|
| SF-MVS | | | 98.53 180 | 98.27 209 | 99.32 91 | 99.31 193 | 98.75 91 | 98.19 169 | 99.41 178 | 96.77 328 | 98.83 234 | 98.90 237 | 97.80 149 | 99.82 205 | 95.68 343 | 99.52 276 | 99.38 230 |
|
| CPTT-MVS | | | 97.84 270 | 97.36 294 | 99.27 99 | 99.31 193 | 98.46 115 | 98.29 158 | 99.27 241 | 94.90 395 | 97.83 341 | 98.37 339 | 94.90 305 | 99.84 174 | 93.85 394 | 99.54 269 | 99.51 158 |
|
| UnsupCasMVSNet_eth | | | 97.89 259 | 97.60 280 | 98.75 200 | 99.31 193 | 97.17 237 | 97.62 269 | 99.35 199 | 98.72 147 | 98.76 248 | 98.68 293 | 92.57 357 | 99.74 281 | 97.76 185 | 95.60 465 | 99.34 246 |
|
| fmvsm_s_conf0.5_n_7 | | | 98.83 115 | 99.04 81 | 98.20 291 | 99.30 197 | 94.83 344 | 97.23 321 | 99.36 193 | 98.64 150 | 99.84 30 | 99.43 89 | 98.10 119 | 99.91 74 | 99.56 41 | 99.96 28 | 99.87 22 |
|
| pmmvs-eth3d | | | 98.47 189 | 98.34 195 | 98.86 174 | 99.30 197 | 97.76 189 | 97.16 331 | 99.28 238 | 95.54 377 | 99.42 110 | 99.19 150 | 97.27 196 | 99.63 349 | 97.89 169 | 99.97 21 | 99.20 291 |
|
| mamv4 | | | 99.44 19 | 99.39 28 | 99.58 21 | 99.30 197 | 99.74 2 | 99.04 68 | 99.81 31 | 99.77 10 | 99.82 34 | 99.57 49 | 97.82 147 | 99.98 4 | 99.53 48 | 99.89 92 | 99.01 325 |
|
| viewcassd2359sk11 | | | 98.55 175 | 98.51 163 | 98.67 215 | 99.29 200 | 96.99 248 | 97.39 302 | 99.54 114 | 97.73 238 | 98.81 239 | 99.08 182 | 97.55 171 | 99.66 335 | 97.52 204 | 99.67 219 | 99.36 239 |
|
| SymmetryMVS | | | 98.05 245 | 97.71 270 | 99.09 132 | 99.29 200 | 97.83 178 | 98.28 159 | 97.64 399 | 99.24 76 | 98.80 241 | 98.85 250 | 89.76 386 | 99.94 42 | 98.04 156 | 99.50 287 | 99.49 169 |
|
| Anonymous20231211 | | | 99.27 38 | 99.27 48 | 99.26 101 | 99.29 200 | 98.18 137 | 99.49 12 | 99.51 124 | 99.70 16 | 99.80 38 | 99.68 25 | 96.84 222 | 99.83 192 | 99.21 71 | 99.91 78 | 99.77 50 |
|
| viewmanbaseed2359cas | | | 98.58 169 | 98.54 159 | 98.70 210 | 99.28 203 | 97.13 241 | 97.47 295 | 99.55 109 | 97.55 257 | 98.96 206 | 98.92 231 | 97.77 151 | 99.59 366 | 97.59 198 | 99.77 158 | 99.39 221 |
|
| UnsupCasMVSNet_bld | | | 97.30 310 | 96.92 320 | 98.45 260 | 99.28 203 | 96.78 264 | 96.20 386 | 99.27 241 | 95.42 381 | 98.28 303 | 98.30 347 | 93.16 343 | 99.71 297 | 94.99 357 | 97.37 441 | 98.87 352 |
|
| EC-MVSNet | | | 99.09 73 | 99.05 80 | 99.20 110 | 99.28 203 | 98.93 80 | 99.24 44 | 99.84 22 | 99.08 112 | 98.12 316 | 98.37 339 | 98.72 49 | 99.90 81 | 99.05 84 | 99.77 158 | 98.77 369 |
|
| mamba_0408 | | | 98.80 122 | 98.88 101 | 98.55 243 | 99.27 206 | 96.50 278 | 98.00 205 | 99.60 80 | 98.93 129 | 99.22 157 | 98.84 255 | 98.59 62 | 99.89 97 | 97.74 186 | 99.72 189 | 99.27 269 |
|
| SSM_04072 | | | 98.80 122 | 98.88 101 | 98.56 241 | 99.27 206 | 96.50 278 | 98.00 205 | 99.60 80 | 98.93 129 | 99.22 157 | 98.84 255 | 98.59 62 | 99.90 81 | 97.74 186 | 99.72 189 | 99.27 269 |
|
| SSM_0407 | | | 98.86 109 | 98.96 94 | 98.55 243 | 99.27 206 | 96.50 278 | 98.04 196 | 99.66 65 | 99.09 108 | 99.22 157 | 99.02 196 | 98.79 42 | 99.87 134 | 97.87 174 | 99.72 189 | 99.27 269 |
|
| reproduce-ours | | | 99.09 73 | 98.90 98 | 99.67 4 | 99.27 206 | 99.49 6 | 98.00 205 | 99.42 174 | 99.05 115 | 99.48 96 | 99.27 125 | 98.29 92 | 99.89 97 | 97.61 195 | 99.71 198 | 99.62 90 |
|
| our_new_method | | | 99.09 73 | 98.90 98 | 99.67 4 | 99.27 206 | 99.49 6 | 98.00 205 | 99.42 174 | 99.05 115 | 99.48 96 | 99.27 125 | 98.29 92 | 99.89 97 | 97.61 195 | 99.71 198 | 99.62 90 |
|
| DPE-MVS |  | | 98.59 167 | 98.26 210 | 99.57 22 | 99.27 206 | 99.15 53 | 97.01 336 | 99.39 183 | 97.67 242 | 99.44 105 | 98.99 213 | 97.53 175 | 99.89 97 | 95.40 351 | 99.68 213 | 99.66 78 |
| Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
| IterMVS-SCA-FT | | | 97.85 269 | 98.18 222 | 96.87 389 | 99.27 206 | 91.16 438 | 95.53 420 | 99.25 247 | 99.10 105 | 99.41 112 | 99.35 105 | 93.10 345 | 99.96 14 | 98.65 115 | 99.94 50 | 99.49 169 |
|
| v1192 | | | 98.60 165 | 98.66 139 | 98.41 265 | 99.27 206 | 95.88 301 | 97.52 285 | 99.36 193 | 97.41 274 | 99.33 130 | 99.20 147 | 96.37 253 | 99.82 205 | 99.57 39 | 99.92 69 | 99.55 136 |
|
| N_pmnet | | | 97.63 283 | 97.17 304 | 98.99 151 | 99.27 206 | 97.86 175 | 95.98 397 | 93.41 462 | 95.25 386 | 99.47 100 | 98.90 237 | 95.63 286 | 99.85 156 | 96.91 250 | 99.73 181 | 99.27 269 |
|
| viewdifsd2359ckpt13 | | | 98.39 203 | 98.29 205 | 98.70 210 | 99.26 215 | 97.19 233 | 97.51 287 | 99.48 137 | 96.94 315 | 98.58 273 | 98.82 260 | 97.47 184 | 99.55 382 | 97.21 225 | 99.33 315 | 99.34 246 |
|
| FPMVS | | | 93.44 419 | 92.23 426 | 97.08 377 | 99.25 216 | 97.86 175 | 95.61 417 | 97.16 411 | 92.90 431 | 93.76 464 | 98.65 300 | 75.94 458 | 95.66 478 | 79.30 476 | 97.49 434 | 97.73 442 |
|
| ME-MVS | | | 98.61 163 | 98.33 200 | 99.44 66 | 99.24 217 | 98.93 80 | 97.45 297 | 99.06 288 | 98.14 208 | 99.06 177 | 98.77 270 | 96.97 216 | 99.82 205 | 96.67 277 | 99.64 230 | 99.58 115 |
|
| new-patchmatchnet | | | 98.35 206 | 98.74 119 | 97.18 372 | 99.24 217 | 92.23 420 | 96.42 373 | 99.48 137 | 98.30 182 | 99.69 56 | 99.53 65 | 97.44 185 | 99.82 205 | 98.84 100 | 99.77 158 | 99.49 169 |
|
| MCST-MVS | | | 98.00 250 | 97.63 278 | 99.10 128 | 99.24 217 | 98.17 138 | 96.89 345 | 98.73 352 | 95.66 372 | 97.92 332 | 97.70 389 | 97.17 203 | 99.66 335 | 96.18 319 | 99.23 334 | 99.47 188 |
|
| UniMVSNet (Re) | | | 98.87 105 | 98.71 128 | 99.35 80 | 99.24 217 | 98.73 95 | 97.73 253 | 99.38 185 | 98.93 129 | 99.12 169 | 98.73 279 | 96.77 230 | 99.86 143 | 98.63 117 | 99.80 141 | 99.46 190 |
|
| jason | | | 97.45 297 | 97.35 295 | 97.76 325 | 99.24 217 | 93.93 381 | 95.86 407 | 98.42 370 | 94.24 410 | 98.50 285 | 98.13 357 | 94.82 309 | 99.91 74 | 97.22 224 | 99.73 181 | 99.43 203 |
| jason: jason. |
| IterMVS | | | 97.73 275 | 98.11 231 | 96.57 399 | 99.24 217 | 90.28 447 | 95.52 422 | 99.21 256 | 98.86 138 | 99.33 130 | 99.33 112 | 93.11 344 | 99.94 42 | 98.49 127 | 99.94 50 | 99.48 180 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| v1240 | | | 98.55 175 | 98.62 146 | 98.32 276 | 99.22 223 | 95.58 312 | 97.51 287 | 99.45 154 | 97.16 303 | 99.45 104 | 99.24 138 | 96.12 264 | 99.85 156 | 99.60 37 | 99.88 94 | 99.55 136 |
|
| ITE_SJBPF | | | | | 98.87 172 | 99.22 223 | 98.48 114 | | 99.35 199 | 97.50 262 | 98.28 303 | 98.60 311 | 97.64 162 | 99.35 429 | 93.86 393 | 99.27 326 | 98.79 367 |
|
| h-mvs33 | | | 97.77 273 | 97.33 297 | 99.10 128 | 99.21 225 | 97.84 177 | 98.35 155 | 98.57 362 | 99.11 98 | 98.58 273 | 99.02 196 | 88.65 397 | 99.96 14 | 98.11 149 | 96.34 457 | 99.49 169 |
|
| v144192 | | | 98.54 178 | 98.57 155 | 98.45 260 | 99.21 225 | 95.98 298 | 97.63 268 | 99.36 193 | 97.15 305 | 99.32 136 | 99.18 154 | 95.84 281 | 99.84 174 | 99.50 51 | 99.91 78 | 99.54 142 |
|
| APDe-MVS |  | | 98.99 86 | 98.79 115 | 99.60 16 | 99.21 225 | 99.15 53 | 98.87 88 | 99.48 137 | 97.57 253 | 99.35 125 | 99.24 138 | 97.83 144 | 99.89 97 | 97.88 172 | 99.70 205 | 99.75 60 |
| Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition |
| DP-MVS | | | 98.93 96 | 98.81 114 | 99.28 96 | 99.21 225 | 98.45 116 | 98.46 143 | 99.33 211 | 99.63 29 | 99.48 96 | 99.15 164 | 97.23 199 | 99.75 275 | 97.17 227 | 99.66 227 | 99.63 89 |
|
| SR-MVS-dyc-post | | | 98.81 120 | 98.55 157 | 99.57 22 | 99.20 229 | 99.38 13 | 98.48 141 | 99.30 226 | 98.64 150 | 98.95 207 | 98.96 223 | 97.49 182 | 99.86 143 | 96.56 292 | 99.39 306 | 99.45 195 |
|
| RE-MVS-def | | | | 98.58 154 | | 99.20 229 | 99.38 13 | 98.48 141 | 99.30 226 | 98.64 150 | 98.95 207 | 98.96 223 | 97.75 153 | | 96.56 292 | 99.39 306 | 99.45 195 |
|
| v1921920 | | | 98.54 178 | 98.60 151 | 98.38 269 | 99.20 229 | 95.76 308 | 97.56 280 | 99.36 193 | 97.23 297 | 99.38 118 | 99.17 158 | 96.02 267 | 99.84 174 | 99.57 39 | 99.90 86 | 99.54 142 |
|
| E3new | | | 98.41 194 | 98.34 195 | 98.62 225 | 99.19 232 | 96.90 256 | 97.32 312 | 99.50 127 | 97.40 276 | 98.63 262 | 98.92 231 | 97.21 201 | 99.65 342 | 97.34 216 | 99.52 276 | 99.31 259 |
|
| thisisatest0530 | | | 95.27 388 | 94.45 399 | 97.74 328 | 99.19 232 | 94.37 359 | 97.86 231 | 90.20 474 | 97.17 302 | 98.22 306 | 97.65 391 | 73.53 461 | 99.90 81 | 96.90 255 | 99.35 312 | 98.95 337 |
|
| Anonymous20240529 | | | 98.93 96 | 98.87 104 | 99.12 124 | 99.19 232 | 98.22 135 | 99.01 70 | 98.99 306 | 99.25 75 | 99.54 79 | 99.37 100 | 97.04 209 | 99.80 231 | 97.89 169 | 99.52 276 | 99.35 244 |
|
| APD-MVS_3200maxsize | | | 98.84 112 | 98.61 150 | 99.53 39 | 99.19 232 | 99.27 28 | 98.49 138 | 99.33 211 | 98.64 150 | 99.03 190 | 98.98 218 | 97.89 139 | 99.85 156 | 96.54 296 | 99.42 303 | 99.46 190 |
|
| HQP_MVS | | | 97.99 253 | 97.67 272 | 98.93 164 | 99.19 232 | 97.65 197 | 97.77 244 | 99.27 241 | 98.20 196 | 97.79 344 | 97.98 371 | 94.90 305 | 99.70 304 | 94.42 375 | 99.51 279 | 99.45 195 |
|
| plane_prior7 | | | | | | 99.19 232 | 97.87 174 | | | | | | | | | | |
|
| ab-mvs | | | 98.41 194 | 98.36 192 | 98.59 232 | 99.19 232 | 97.23 226 | 99.32 26 | 98.81 338 | 97.66 243 | 98.62 265 | 99.40 97 | 96.82 225 | 99.80 231 | 95.88 330 | 99.51 279 | 98.75 372 |
|
| F-COLMAP | | | 97.30 310 | 96.68 337 | 99.14 122 | 99.19 232 | 98.39 118 | 97.27 320 | 99.30 226 | 92.93 430 | 96.62 409 | 98.00 369 | 95.73 284 | 99.68 318 | 92.62 421 | 98.46 402 | 99.35 244 |
|
| viewdifsd2359ckpt09 | | | 98.13 238 | 97.92 254 | 98.77 196 | 99.18 240 | 97.35 216 | 97.29 316 | 99.53 118 | 95.81 369 | 98.09 319 | 98.47 329 | 96.34 255 | 99.66 335 | 97.02 240 | 99.51 279 | 99.29 265 |
|
| SR-MVS | | | 98.71 135 | 98.43 180 | 99.57 22 | 99.18 240 | 99.35 17 | 98.36 154 | 99.29 234 | 98.29 185 | 98.88 226 | 98.85 250 | 97.53 175 | 99.87 134 | 96.14 321 | 99.31 319 | 99.48 180 |
|
| UniMVSNet_NR-MVSNet | | | 98.86 109 | 98.68 134 | 99.40 72 | 99.17 242 | 98.74 92 | 97.68 258 | 99.40 181 | 99.14 96 | 99.06 177 | 98.59 312 | 96.71 236 | 99.93 54 | 98.57 120 | 99.77 158 | 99.53 151 |
|
| LF4IMVS | | | 97.90 257 | 97.69 271 | 98.52 251 | 99.17 242 | 97.66 196 | 97.19 330 | 99.47 146 | 96.31 349 | 97.85 340 | 98.20 354 | 96.71 236 | 99.52 394 | 94.62 367 | 99.72 189 | 98.38 408 |
|
| SMA-MVS |  | | 98.40 197 | 98.03 240 | 99.51 49 | 99.16 244 | 99.21 34 | 98.05 194 | 99.22 255 | 94.16 412 | 98.98 197 | 99.10 176 | 97.52 177 | 99.79 244 | 96.45 302 | 99.64 230 | 99.53 151 |
| 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 |
| DU-MVS | | | 98.82 118 | 98.63 144 | 99.39 73 | 99.16 244 | 98.74 92 | 97.54 283 | 99.25 247 | 98.84 142 | 99.06 177 | 98.76 276 | 96.76 232 | 99.93 54 | 98.57 120 | 99.77 158 | 99.50 162 |
|
| NR-MVSNet | | | 98.95 93 | 98.82 112 | 99.36 74 | 99.16 244 | 98.72 97 | 99.22 45 | 99.20 258 | 99.10 105 | 99.72 48 | 98.76 276 | 96.38 252 | 99.86 143 | 98.00 161 | 99.82 124 | 99.50 162 |
|
| MVS_111021_LR | | | 98.30 215 | 98.12 230 | 98.83 177 | 99.16 244 | 98.03 157 | 96.09 394 | 99.30 226 | 97.58 252 | 98.10 318 | 98.24 350 | 98.25 100 | 99.34 430 | 96.69 275 | 99.65 228 | 99.12 311 |
|
| DSMNet-mixed | | | 97.42 300 | 97.60 280 | 96.87 389 | 99.15 248 | 91.46 427 | 98.54 126 | 99.12 280 | 92.87 432 | 97.58 357 | 99.63 39 | 96.21 259 | 99.90 81 | 95.74 339 | 99.54 269 | 99.27 269 |
|
| D2MVS | | | 97.84 270 | 97.84 261 | 97.83 317 | 99.14 249 | 94.74 348 | 96.94 340 | 98.88 322 | 95.84 368 | 98.89 222 | 98.96 223 | 94.40 321 | 99.69 308 | 97.55 199 | 99.95 38 | 99.05 317 |
|
| pmmvs5 | | | 97.64 282 | 97.49 286 | 98.08 302 | 99.14 249 | 95.12 337 | 96.70 355 | 99.05 292 | 93.77 419 | 98.62 265 | 98.83 257 | 93.23 341 | 99.75 275 | 98.33 137 | 99.76 173 | 99.36 239 |
|
| SPE-MVS-test | | | 99.13 67 | 99.09 76 | 99.26 101 | 99.13 251 | 98.97 74 | 99.31 30 | 99.88 14 | 99.44 53 | 98.16 311 | 98.51 321 | 98.64 56 | 99.93 54 | 98.91 94 | 99.85 107 | 98.88 351 |
|
| VDD-MVS | | | 98.56 171 | 98.39 187 | 99.07 135 | 99.13 251 | 98.07 152 | 98.59 120 | 97.01 414 | 99.59 37 | 99.11 170 | 99.27 125 | 94.82 309 | 99.79 244 | 98.34 135 | 99.63 237 | 99.34 246 |
|
| save fliter | | | | | | 99.11 253 | 97.97 163 | 96.53 365 | 99.02 300 | 98.24 188 | | | | | | | |
|
| APD-MVS |  | | 98.10 239 | 97.67 272 | 99.42 68 | 99.11 253 | 98.93 80 | 97.76 247 | 99.28 238 | 94.97 393 | 98.72 252 | 98.77 270 | 97.04 209 | 99.85 156 | 93.79 395 | 99.54 269 | 99.49 169 |
| Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
| EI-MVSNet-UG-set | | | 98.69 144 | 98.71 128 | 98.62 225 | 99.10 255 | 96.37 284 | 97.23 321 | 98.87 324 | 99.20 83 | 99.19 162 | 98.99 213 | 97.30 193 | 99.85 156 | 98.77 106 | 99.79 147 | 99.65 83 |
|
| EI-MVSNet | | | 98.40 197 | 98.51 163 | 98.04 307 | 99.10 255 | 94.73 349 | 97.20 326 | 98.87 324 | 98.97 124 | 99.06 177 | 99.02 196 | 96.00 269 | 99.80 231 | 98.58 118 | 99.82 124 | 99.60 100 |
|
| CVMVSNet | | | 96.25 362 | 97.21 303 | 93.38 456 | 99.10 255 | 80.56 484 | 97.20 326 | 98.19 381 | 96.94 315 | 99.00 192 | 99.02 196 | 89.50 390 | 99.80 231 | 96.36 308 | 99.59 251 | 99.78 47 |
|
| EI-MVSNet-Vis-set | | | 98.68 150 | 98.70 131 | 98.63 223 | 99.09 258 | 96.40 283 | 97.23 321 | 98.86 329 | 99.20 83 | 99.18 166 | 98.97 220 | 97.29 195 | 99.85 156 | 98.72 110 | 99.78 152 | 99.64 84 |
|
| HPM-MVS++ |  | | 98.10 239 | 97.64 277 | 99.48 57 | 99.09 258 | 99.13 61 | 97.52 285 | 98.75 349 | 97.46 270 | 96.90 397 | 97.83 381 | 96.01 268 | 99.84 174 | 95.82 337 | 99.35 312 | 99.46 190 |
|
| DP-MVS Recon | | | 97.33 308 | 96.92 320 | 98.57 236 | 99.09 258 | 97.99 159 | 96.79 348 | 99.35 199 | 93.18 426 | 97.71 348 | 98.07 365 | 95.00 304 | 99.31 434 | 93.97 388 | 99.13 350 | 98.42 405 |
|
| MVS_111021_HR | | | 98.25 224 | 98.08 235 | 98.75 200 | 99.09 258 | 97.46 210 | 95.97 398 | 99.27 241 | 97.60 251 | 97.99 329 | 98.25 349 | 98.15 116 | 99.38 425 | 96.87 258 | 99.57 260 | 99.42 208 |
|
| BP-MVS1 | | | 97.40 302 | 96.97 316 | 98.71 209 | 99.07 262 | 96.81 260 | 98.34 157 | 97.18 409 | 98.58 161 | 98.17 308 | 98.61 309 | 84.01 429 | 99.94 42 | 98.97 90 | 99.78 152 | 99.37 232 |
|
| 9.14 | | | | 97.78 263 | | 99.07 262 | | 97.53 284 | 99.32 213 | 95.53 378 | 98.54 281 | 98.70 289 | 97.58 168 | 99.76 267 | 94.32 380 | 99.46 292 | |
|
| PAPM_NR | | | 96.82 342 | 96.32 353 | 98.30 279 | 99.07 262 | 96.69 268 | 97.48 291 | 98.76 346 | 95.81 369 | 96.61 410 | 96.47 427 | 94.12 330 | 99.17 447 | 90.82 448 | 97.78 428 | 99.06 316 |
|
| TAMVS | | | 98.24 225 | 98.05 238 | 98.80 184 | 99.07 262 | 97.18 235 | 97.88 227 | 98.81 338 | 96.66 333 | 99.17 168 | 99.21 145 | 94.81 311 | 99.77 261 | 96.96 248 | 99.88 94 | 99.44 199 |
|
| CLD-MVS | | | 97.49 293 | 97.16 305 | 98.48 257 | 99.07 262 | 97.03 246 | 94.71 443 | 99.21 256 | 94.46 404 | 98.06 322 | 97.16 413 | 97.57 169 | 99.48 406 | 94.46 372 | 99.78 152 | 98.95 337 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| CS-MVS | | | 99.13 67 | 99.10 74 | 99.24 106 | 99.06 267 | 99.15 53 | 99.36 22 | 99.88 14 | 99.36 64 | 98.21 307 | 98.46 330 | 98.68 53 | 99.93 54 | 99.03 86 | 99.85 107 | 98.64 384 |
|
| thres100view900 | | | 94.19 405 | 93.67 410 | 95.75 423 | 99.06 267 | 91.35 431 | 98.03 198 | 94.24 457 | 98.33 178 | 97.40 373 | 94.98 457 | 79.84 445 | 99.62 352 | 83.05 469 | 98.08 419 | 96.29 464 |
|
| thres600view7 | | | 94.45 400 | 93.83 407 | 96.29 407 | 99.06 267 | 91.53 426 | 97.99 212 | 94.24 457 | 98.34 177 | 97.44 371 | 95.01 455 | 79.84 445 | 99.67 322 | 84.33 467 | 98.23 408 | 97.66 445 |
|
| plane_prior1 | | | | | | 99.05 270 | | | | | | | | | | | |
|
| YYNet1 | | | 97.60 284 | 97.67 272 | 97.39 365 | 99.04 271 | 93.04 404 | 95.27 429 | 98.38 373 | 97.25 291 | 98.92 217 | 98.95 227 | 95.48 293 | 99.73 288 | 96.99 244 | 98.74 383 | 99.41 211 |
|
| MDA-MVSNet_test_wron | | | 97.60 284 | 97.66 275 | 97.41 364 | 99.04 271 | 93.09 400 | 95.27 429 | 98.42 370 | 97.26 290 | 98.88 226 | 98.95 227 | 95.43 294 | 99.73 288 | 97.02 240 | 98.72 385 | 99.41 211 |
|
| MIMVSNet | | | 96.62 349 | 96.25 357 | 97.71 332 | 99.04 271 | 94.66 352 | 99.16 54 | 96.92 420 | 97.23 297 | 97.87 337 | 99.10 176 | 86.11 412 | 99.65 342 | 91.65 432 | 99.21 338 | 98.82 356 |
|
| FE-MVSNET3 | | | 97.37 304 | 97.13 309 | 98.11 298 | 99.03 274 | 95.40 325 | 94.47 453 | 98.99 306 | 96.87 321 | 97.97 330 | 97.81 382 | 92.12 363 | 99.75 275 | 97.49 210 | 99.43 302 | 99.16 306 |
|
| icg_test_0407_2 | | | 98.20 230 | 98.38 189 | 97.65 338 | 99.03 274 | 94.03 372 | 95.78 412 | 99.45 154 | 98.16 202 | 99.06 177 | 98.71 282 | 98.27 96 | 99.68 318 | 97.50 205 | 99.45 294 | 99.22 286 |
|
| IMVS_0407 | | | 98.39 203 | 98.64 142 | 97.66 336 | 99.03 274 | 94.03 372 | 98.10 184 | 99.45 154 | 98.16 202 | 99.06 177 | 98.71 282 | 98.27 96 | 99.71 297 | 97.50 205 | 99.45 294 | 99.22 286 |
|
| IMVS_0404 | | | 98.07 243 | 98.20 217 | 97.69 333 | 99.03 274 | 94.03 372 | 96.67 356 | 99.45 154 | 98.16 202 | 98.03 326 | 98.71 282 | 96.80 228 | 99.82 205 | 97.50 205 | 99.45 294 | 99.22 286 |
|
| IMVS_0403 | | | 98.34 207 | 98.56 156 | 97.66 336 | 99.03 274 | 94.03 372 | 97.98 213 | 99.45 154 | 98.16 202 | 98.89 222 | 98.71 282 | 97.90 135 | 99.74 281 | 97.50 205 | 99.45 294 | 99.22 286 |
|
| PatchMatch-RL | | | 97.24 316 | 96.78 331 | 98.61 229 | 99.03 274 | 97.83 178 | 96.36 376 | 99.06 288 | 93.49 424 | 97.36 377 | 97.78 383 | 95.75 283 | 99.49 403 | 93.44 404 | 98.77 382 | 98.52 393 |
|
| viewmambaseed2359dif | | | 98.19 231 | 98.26 210 | 97.99 310 | 99.02 280 | 95.03 340 | 96.59 362 | 99.53 118 | 96.21 352 | 99.00 192 | 98.99 213 | 97.62 164 | 99.61 359 | 97.62 194 | 99.72 189 | 99.33 252 |
|
| GDP-MVS | | | 97.50 290 | 97.11 310 | 98.67 215 | 99.02 280 | 96.85 258 | 98.16 174 | 99.71 47 | 98.32 180 | 98.52 284 | 98.54 316 | 83.39 433 | 99.95 26 | 98.79 102 | 99.56 263 | 99.19 296 |
|
| ZD-MVS | | | | | | 99.01 282 | 98.84 86 | | 99.07 287 | 94.10 414 | 98.05 324 | 98.12 359 | 96.36 254 | 99.86 143 | 92.70 420 | 99.19 342 | |
|
| CDPH-MVS | | | 97.26 313 | 96.66 340 | 99.07 135 | 99.00 283 | 98.15 139 | 96.03 396 | 99.01 303 | 91.21 450 | 97.79 344 | 97.85 380 | 96.89 220 | 99.69 308 | 92.75 418 | 99.38 309 | 99.39 221 |
|
| diffmvs |  | | 98.22 226 | 98.24 214 | 98.17 294 | 99.00 283 | 95.44 323 | 96.38 375 | 99.58 89 | 97.79 235 | 98.53 282 | 98.50 325 | 96.76 232 | 99.74 281 | 97.95 167 | 99.64 230 | 99.34 246 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| WR-MVS | | | 98.40 197 | 98.19 221 | 99.03 145 | 99.00 283 | 97.65 197 | 96.85 346 | 98.94 309 | 98.57 163 | 98.89 222 | 98.50 325 | 95.60 287 | 99.85 156 | 97.54 201 | 99.85 107 | 99.59 107 |
|
| plane_prior6 | | | | | | 98.99 286 | 97.70 195 | | | | | | 94.90 305 | | | | |
|
| xiu_mvs_v1_base_debu | | | 97.86 264 | 98.17 223 | 96.92 386 | 98.98 287 | 93.91 382 | 96.45 369 | 99.17 270 | 97.85 230 | 98.41 293 | 97.14 415 | 98.47 72 | 99.92 65 | 98.02 158 | 99.05 356 | 96.92 457 |
|
| xiu_mvs_v1_base | | | 97.86 264 | 98.17 223 | 96.92 386 | 98.98 287 | 93.91 382 | 96.45 369 | 99.17 270 | 97.85 230 | 98.41 293 | 97.14 415 | 98.47 72 | 99.92 65 | 98.02 158 | 99.05 356 | 96.92 457 |
|
| xiu_mvs_v1_base_debi | | | 97.86 264 | 98.17 223 | 96.92 386 | 98.98 287 | 93.91 382 | 96.45 369 | 99.17 270 | 97.85 230 | 98.41 293 | 97.14 415 | 98.47 72 | 99.92 65 | 98.02 158 | 99.05 356 | 96.92 457 |
|
| MVP-Stereo | | | 98.08 242 | 97.92 254 | 98.57 236 | 98.96 290 | 96.79 261 | 97.90 225 | 99.18 266 | 96.41 345 | 98.46 288 | 98.95 227 | 95.93 278 | 99.60 362 | 96.51 298 | 98.98 370 | 99.31 259 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| SD-MVS | | | 98.40 197 | 98.68 134 | 97.54 353 | 98.96 290 | 97.99 159 | 97.88 227 | 99.36 193 | 98.20 196 | 99.63 67 | 99.04 193 | 98.76 45 | 95.33 480 | 96.56 292 | 99.74 178 | 99.31 259 |
| 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 |
| 新几何1 | | | | | 98.91 168 | 98.94 292 | 97.76 189 | | 98.76 346 | 87.58 467 | 96.75 405 | 98.10 361 | 94.80 312 | 99.78 255 | 92.73 419 | 99.00 365 | 99.20 291 |
|
| USDC | | | 97.41 301 | 97.40 290 | 97.44 362 | 98.94 292 | 93.67 392 | 95.17 432 | 99.53 118 | 94.03 416 | 98.97 201 | 99.10 176 | 95.29 296 | 99.34 430 | 95.84 336 | 99.73 181 | 99.30 263 |
|
| tfpn200view9 | | | 94.03 409 | 93.44 412 | 95.78 422 | 98.93 294 | 91.44 429 | 97.60 275 | 94.29 455 | 97.94 222 | 97.10 383 | 94.31 464 | 79.67 447 | 99.62 352 | 83.05 469 | 98.08 419 | 96.29 464 |
|
| testdata | | | | | 98.09 299 | 98.93 294 | 95.40 325 | | 98.80 340 | 90.08 458 | 97.45 370 | 98.37 339 | 95.26 297 | 99.70 304 | 93.58 400 | 98.95 373 | 99.17 303 |
|
| thres400 | | | 94.14 407 | 93.44 412 | 96.24 410 | 98.93 294 | 91.44 429 | 97.60 275 | 94.29 455 | 97.94 222 | 97.10 383 | 94.31 464 | 79.67 447 | 99.62 352 | 83.05 469 | 98.08 419 | 97.66 445 |
|
| TAPA-MVS | | 96.21 11 | 96.63 348 | 95.95 359 | 98.65 217 | 98.93 294 | 98.09 146 | 96.93 342 | 99.28 238 | 83.58 473 | 98.13 315 | 97.78 383 | 96.13 262 | 99.40 421 | 93.52 401 | 99.29 324 | 98.45 398 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| test222 | | | | | | 98.92 298 | 96.93 254 | 95.54 419 | 98.78 343 | 85.72 470 | 96.86 400 | 98.11 360 | 94.43 319 | | | 99.10 355 | 99.23 281 |
|
| PVSNet_BlendedMVS | | | 97.55 289 | 97.53 283 | 97.60 345 | 98.92 298 | 93.77 389 | 96.64 358 | 99.43 168 | 94.49 402 | 97.62 353 | 99.18 154 | 96.82 225 | 99.67 322 | 94.73 364 | 99.93 56 | 99.36 239 |
|
| PVSNet_Blended | | | 96.88 338 | 96.68 337 | 97.47 360 | 98.92 298 | 93.77 389 | 94.71 443 | 99.43 168 | 90.98 452 | 97.62 353 | 97.36 409 | 96.82 225 | 99.67 322 | 94.73 364 | 99.56 263 | 98.98 331 |
|
| MSDG | | | 97.71 277 | 97.52 284 | 98.28 281 | 98.91 301 | 96.82 259 | 94.42 454 | 99.37 189 | 97.65 244 | 98.37 298 | 98.29 348 | 97.40 187 | 99.33 432 | 94.09 386 | 99.22 335 | 98.68 382 |
|
| Anonymous202405211 | | | 97.90 257 | 97.50 285 | 99.08 133 | 98.90 302 | 98.25 129 | 98.53 127 | 96.16 432 | 98.87 136 | 99.11 170 | 98.86 247 | 90.40 382 | 99.78 255 | 97.36 215 | 99.31 319 | 99.19 296 |
|
| 原ACMM1 | | | | | 98.35 274 | 98.90 302 | 96.25 288 | | 98.83 337 | 92.48 436 | 96.07 427 | 98.10 361 | 95.39 295 | 99.71 297 | 92.61 422 | 98.99 367 | 99.08 313 |
|
| GBi-Net | | | 98.65 155 | 98.47 174 | 99.17 115 | 98.90 302 | 98.24 130 | 99.20 48 | 99.44 162 | 98.59 158 | 98.95 207 | 99.55 57 | 94.14 327 | 99.86 143 | 97.77 181 | 99.69 208 | 99.41 211 |
|
| test1 | | | 98.65 155 | 98.47 174 | 99.17 115 | 98.90 302 | 98.24 130 | 99.20 48 | 99.44 162 | 98.59 158 | 98.95 207 | 99.55 57 | 94.14 327 | 99.86 143 | 97.77 181 | 99.69 208 | 99.41 211 |
|
| FMVSNet2 | | | 98.49 187 | 98.40 184 | 98.75 200 | 98.90 302 | 97.14 240 | 98.61 118 | 99.13 279 | 98.59 158 | 99.19 162 | 99.28 123 | 94.14 327 | 99.82 205 | 97.97 165 | 99.80 141 | 99.29 265 |
|
| OMC-MVS | | | 97.88 261 | 97.49 286 | 99.04 144 | 98.89 307 | 98.63 99 | 96.94 340 | 99.25 247 | 95.02 391 | 98.53 282 | 98.51 321 | 97.27 196 | 99.47 409 | 93.50 403 | 99.51 279 | 99.01 325 |
|
| VortexMVS | | | 97.98 254 | 98.31 202 | 97.02 380 | 98.88 308 | 91.45 428 | 98.03 198 | 99.47 146 | 98.65 149 | 99.55 77 | 99.47 79 | 91.49 371 | 99.81 222 | 99.32 61 | 99.91 78 | 99.80 42 |
|
| MVSFormer | | | 98.26 221 | 98.43 180 | 97.77 322 | 98.88 308 | 93.89 385 | 99.39 20 | 99.56 105 | 99.11 98 | 98.16 311 | 98.13 357 | 93.81 335 | 99.97 7 | 99.26 66 | 99.57 260 | 99.43 203 |
|
| lupinMVS | | | 97.06 328 | 96.86 324 | 97.65 338 | 98.88 308 | 93.89 385 | 95.48 423 | 97.97 387 | 93.53 422 | 98.16 311 | 97.58 395 | 93.81 335 | 99.91 74 | 96.77 266 | 99.57 260 | 99.17 303 |
|
| dmvs_re | | | 95.98 370 | 95.39 380 | 97.74 328 | 98.86 311 | 97.45 211 | 98.37 153 | 95.69 444 | 97.95 220 | 96.56 411 | 95.95 436 | 90.70 379 | 97.68 474 | 88.32 457 | 96.13 461 | 98.11 420 |
|
| DELS-MVS | | | 98.27 219 | 98.20 217 | 98.48 257 | 98.86 311 | 96.70 267 | 95.60 418 | 99.20 258 | 97.73 238 | 98.45 289 | 98.71 282 | 97.50 179 | 99.82 205 | 98.21 143 | 99.59 251 | 98.93 342 |
| 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 |
| TinyColmap | | | 97.89 259 | 97.98 245 | 97.60 345 | 98.86 311 | 94.35 360 | 96.21 385 | 99.44 162 | 97.45 272 | 99.06 177 | 98.88 244 | 97.99 129 | 99.28 440 | 94.38 379 | 99.58 256 | 99.18 299 |
|
| LCM-MVSNet-Re | | | 98.64 157 | 98.48 172 | 99.11 126 | 98.85 314 | 98.51 112 | 98.49 138 | 99.83 25 | 98.37 174 | 99.69 56 | 99.46 81 | 98.21 107 | 99.92 65 | 94.13 385 | 99.30 322 | 98.91 346 |
|
| pmmvs4 | | | 97.58 287 | 97.28 298 | 98.51 252 | 98.84 315 | 96.93 254 | 95.40 427 | 98.52 365 | 93.60 421 | 98.61 267 | 98.65 300 | 95.10 301 | 99.60 362 | 96.97 247 | 99.79 147 | 98.99 330 |
|
| NP-MVS | | | | | | 98.84 315 | 97.39 215 | | | | | 96.84 418 | | | | | |
|
| sss | | | 97.21 318 | 96.93 318 | 98.06 304 | 98.83 317 | 95.22 333 | 96.75 352 | 98.48 367 | 94.49 402 | 97.27 379 | 97.90 377 | 92.77 353 | 99.80 231 | 96.57 288 | 99.32 317 | 99.16 306 |
|
| PVSNet | | 93.40 17 | 95.67 379 | 95.70 365 | 95.57 427 | 98.83 317 | 88.57 454 | 92.50 471 | 97.72 392 | 92.69 434 | 96.49 419 | 96.44 428 | 93.72 338 | 99.43 417 | 93.61 398 | 99.28 325 | 98.71 375 |
|
| MVE |  | 83.40 22 | 92.50 432 | 91.92 434 | 94.25 443 | 98.83 317 | 91.64 425 | 92.71 470 | 83.52 483 | 95.92 366 | 86.46 481 | 95.46 449 | 95.20 298 | 95.40 479 | 80.51 474 | 98.64 394 | 95.73 472 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| testing3-2 | | | 93.78 413 | 93.91 405 | 93.39 455 | 98.82 320 | 81.72 482 | 97.76 247 | 95.28 446 | 98.60 157 | 96.54 412 | 96.66 422 | 65.85 477 | 99.62 352 | 96.65 281 | 98.99 367 | 98.82 356 |
|
| ambc | | | | | 98.24 286 | 98.82 320 | 95.97 299 | 98.62 116 | 99.00 305 | | 99.27 144 | 99.21 145 | 96.99 214 | 99.50 400 | 96.55 295 | 99.50 287 | 99.26 275 |
|
| 旧先验1 | | | | | | 98.82 320 | 97.45 211 | | 98.76 346 | | | 98.34 343 | 95.50 292 | | | 99.01 364 | 99.23 281 |
|
| test_vis1_rt | | | 97.75 274 | 97.72 269 | 97.83 317 | 98.81 323 | 96.35 285 | 97.30 315 | 99.69 54 | 94.61 400 | 97.87 337 | 98.05 366 | 96.26 258 | 98.32 468 | 98.74 108 | 98.18 411 | 98.82 356 |
|
| WTY-MVS | | | 96.67 346 | 96.27 356 | 97.87 315 | 98.81 323 | 94.61 354 | 96.77 350 | 97.92 389 | 94.94 394 | 97.12 382 | 97.74 386 | 91.11 375 | 99.82 205 | 93.89 391 | 98.15 415 | 99.18 299 |
|
| 3Dnovator+ | | 97.89 3 | 98.69 144 | 98.51 163 | 99.24 106 | 98.81 323 | 98.40 117 | 99.02 69 | 99.19 262 | 98.99 121 | 98.07 321 | 99.28 123 | 97.11 207 | 99.84 174 | 96.84 261 | 99.32 317 | 99.47 188 |
|
| QAPM | | | 97.31 309 | 96.81 330 | 98.82 179 | 98.80 326 | 97.49 205 | 99.06 65 | 99.19 262 | 90.22 456 | 97.69 350 | 99.16 160 | 96.91 219 | 99.90 81 | 90.89 447 | 99.41 304 | 99.07 315 |
|
| VNet | | | 98.42 193 | 98.30 203 | 98.79 188 | 98.79 327 | 97.29 222 | 98.23 165 | 98.66 356 | 99.31 69 | 98.85 231 | 98.80 264 | 94.80 312 | 99.78 255 | 98.13 148 | 99.13 350 | 99.31 259 |
|
| DPM-MVS | | | 96.32 358 | 95.59 371 | 98.51 252 | 98.76 328 | 97.21 231 | 94.54 452 | 98.26 376 | 91.94 441 | 96.37 420 | 97.25 411 | 93.06 347 | 99.43 417 | 91.42 437 | 98.74 383 | 98.89 348 |
|
| 3Dnovator | | 98.27 2 | 98.81 120 | 98.73 121 | 99.05 142 | 98.76 328 | 97.81 186 | 99.25 43 | 99.30 226 | 98.57 163 | 98.55 279 | 99.33 112 | 97.95 132 | 99.90 81 | 97.16 228 | 99.67 219 | 99.44 199 |
|
| PLC |  | 94.65 16 | 96.51 351 | 95.73 364 | 98.85 175 | 98.75 330 | 97.91 171 | 96.42 373 | 99.06 288 | 90.94 453 | 95.59 433 | 97.38 407 | 94.41 320 | 99.59 366 | 90.93 445 | 98.04 424 | 99.05 317 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| BH-untuned | | | 96.83 340 | 96.75 333 | 97.08 377 | 98.74 331 | 93.33 398 | 96.71 354 | 98.26 376 | 96.72 330 | 98.44 290 | 97.37 408 | 95.20 298 | 99.47 409 | 91.89 427 | 97.43 438 | 98.44 401 |
|
| hse-mvs2 | | | 97.46 295 | 97.07 311 | 98.64 219 | 98.73 332 | 97.33 218 | 97.45 297 | 97.64 399 | 99.11 98 | 98.58 273 | 97.98 371 | 88.65 397 | 99.79 244 | 98.11 149 | 97.39 440 | 98.81 361 |
|
| CDS-MVSNet | | | 97.69 278 | 97.35 295 | 98.69 212 | 98.73 332 | 97.02 247 | 96.92 344 | 98.75 349 | 95.89 367 | 98.59 271 | 98.67 295 | 92.08 365 | 99.74 281 | 96.72 272 | 99.81 130 | 99.32 255 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| SD_0403 | | | 96.28 360 | 95.83 361 | 97.64 341 | 98.72 334 | 94.30 361 | 98.87 88 | 98.77 344 | 97.80 233 | 96.53 413 | 98.02 368 | 97.34 191 | 99.47 409 | 76.93 478 | 99.48 290 | 99.16 306 |
|
| EIA-MVS | | | 98.00 250 | 97.74 266 | 98.80 184 | 98.72 334 | 98.09 146 | 98.05 194 | 99.60 80 | 97.39 277 | 96.63 408 | 95.55 444 | 97.68 156 | 99.80 231 | 96.73 271 | 99.27 326 | 98.52 393 |
|
| LFMVS | | | 97.20 319 | 96.72 334 | 98.64 219 | 98.72 334 | 96.95 252 | 98.93 81 | 94.14 459 | 99.74 13 | 98.78 243 | 99.01 207 | 84.45 424 | 99.73 288 | 97.44 211 | 99.27 326 | 99.25 276 |
|
| new_pmnet | | | 96.99 335 | 96.76 332 | 97.67 334 | 98.72 334 | 94.89 343 | 95.95 402 | 98.20 379 | 92.62 435 | 98.55 279 | 98.54 316 | 94.88 308 | 99.52 394 | 93.96 389 | 99.44 301 | 98.59 390 |
|
| Fast-Effi-MVS+ | | | 97.67 280 | 97.38 292 | 98.57 236 | 98.71 338 | 97.43 213 | 97.23 321 | 99.45 154 | 94.82 397 | 96.13 424 | 96.51 424 | 98.52 70 | 99.91 74 | 96.19 317 | 98.83 379 | 98.37 410 |
|
| TEST9 | | | | | | 98.71 338 | 98.08 150 | 95.96 400 | 99.03 297 | 91.40 447 | 95.85 430 | 97.53 397 | 96.52 245 | 99.76 267 | | | |
|
| train_agg | | | 97.10 325 | 96.45 350 | 99.07 135 | 98.71 338 | 98.08 150 | 95.96 400 | 99.03 297 | 91.64 442 | 95.85 430 | 97.53 397 | 96.47 247 | 99.76 267 | 93.67 397 | 99.16 345 | 99.36 239 |
|
| TSAR-MVS + GP. | | | 98.18 233 | 97.98 245 | 98.77 196 | 98.71 338 | 97.88 173 | 96.32 379 | 98.66 356 | 96.33 347 | 99.23 156 | 98.51 321 | 97.48 183 | 99.40 421 | 97.16 228 | 99.46 292 | 99.02 324 |
|
| FA-MVS(test-final) | | | 96.99 335 | 96.82 328 | 97.50 357 | 98.70 342 | 94.78 346 | 99.34 23 | 96.99 415 | 95.07 390 | 98.48 287 | 99.33 112 | 88.41 400 | 99.65 342 | 96.13 323 | 98.92 376 | 98.07 423 |
|
| AUN-MVS | | | 96.24 364 | 95.45 376 | 98.60 231 | 98.70 342 | 97.22 229 | 97.38 304 | 97.65 397 | 95.95 365 | 95.53 440 | 97.96 375 | 82.11 441 | 99.79 244 | 96.31 310 | 97.44 437 | 98.80 366 |
|
| our_test_3 | | | 97.39 303 | 97.73 268 | 96.34 405 | 98.70 342 | 89.78 450 | 94.61 449 | 98.97 308 | 96.50 338 | 99.04 187 | 98.85 250 | 95.98 274 | 99.84 174 | 97.26 222 | 99.67 219 | 99.41 211 |
|
| ppachtmachnet_test | | | 97.50 290 | 97.74 266 | 96.78 395 | 98.70 342 | 91.23 437 | 94.55 451 | 99.05 292 | 96.36 346 | 99.21 160 | 98.79 266 | 96.39 250 | 99.78 255 | 96.74 269 | 99.82 124 | 99.34 246 |
|
| PCF-MVS | | 92.86 18 | 94.36 401 | 93.00 419 | 98.42 264 | 98.70 342 | 97.56 202 | 93.16 469 | 99.11 282 | 79.59 477 | 97.55 360 | 97.43 404 | 92.19 361 | 99.73 288 | 79.85 475 | 99.45 294 | 97.97 429 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| ttmdpeth | | | 97.91 256 | 98.02 241 | 97.58 347 | 98.69 347 | 94.10 368 | 98.13 177 | 98.90 318 | 97.95 220 | 97.32 378 | 99.58 47 | 95.95 277 | 98.75 463 | 96.41 304 | 99.22 335 | 99.87 22 |
|
| ETV-MVS | | | 98.03 246 | 97.86 260 | 98.56 241 | 98.69 347 | 98.07 152 | 97.51 287 | 99.50 127 | 98.10 210 | 97.50 365 | 95.51 445 | 98.41 79 | 99.88 115 | 96.27 313 | 99.24 331 | 97.71 444 |
|
| test_prior | | | | | 98.95 160 | 98.69 347 | 97.95 167 | | 99.03 297 | | | | | 99.59 366 | | | 99.30 263 |
|
| mvsmamba | | | 97.57 288 | 97.26 299 | 98.51 252 | 98.69 347 | 96.73 266 | 98.74 97 | 97.25 408 | 97.03 311 | 97.88 336 | 99.23 143 | 90.95 376 | 99.87 134 | 96.61 284 | 99.00 365 | 98.91 346 |
|
| agg_prior | | | | | | 98.68 351 | 97.99 159 | | 99.01 303 | | 95.59 433 | | | 99.77 261 | | | |
|
| test_8 | | | | | | 98.67 352 | 98.01 158 | 95.91 406 | 99.02 300 | 91.64 442 | 95.79 432 | 97.50 400 | 96.47 247 | 99.76 267 | | | |
|
| HQP-NCC | | | | | | 98.67 352 | | 96.29 381 | | 96.05 358 | 95.55 436 | | | | | | |
|
| ACMP_Plane | | | | | | 98.67 352 | | 96.29 381 | | 96.05 358 | 95.55 436 | | | | | | |
|
| CNVR-MVS | | | 98.17 235 | 97.87 259 | 99.07 135 | 98.67 352 | 98.24 130 | 97.01 336 | 98.93 312 | 97.25 291 | 97.62 353 | 98.34 343 | 97.27 196 | 99.57 375 | 96.42 303 | 99.33 315 | 99.39 221 |
|
| HQP-MVS | | | 97.00 334 | 96.49 349 | 98.55 243 | 98.67 352 | 96.79 261 | 96.29 381 | 99.04 295 | 96.05 358 | 95.55 436 | 96.84 418 | 93.84 333 | 99.54 388 | 92.82 415 | 99.26 329 | 99.32 255 |
|
| MM | | | 98.22 226 | 97.99 244 | 98.91 168 | 98.66 357 | 96.97 249 | 97.89 226 | 94.44 453 | 99.54 41 | 98.95 207 | 99.14 167 | 93.50 339 | 99.92 65 | 99.80 17 | 99.96 28 | 99.85 30 |
|
| test_fmvs1 | | | 97.72 276 | 97.94 251 | 97.07 379 | 98.66 357 | 92.39 415 | 97.68 258 | 99.81 31 | 95.20 389 | 99.54 79 | 99.44 86 | 91.56 370 | 99.41 420 | 99.78 21 | 99.77 158 | 99.40 220 |
|
| balanced_conf03 | | | 98.63 159 | 98.72 123 | 98.38 269 | 98.66 357 | 96.68 269 | 98.90 83 | 99.42 174 | 98.99 121 | 98.97 201 | 99.19 150 | 95.81 282 | 99.85 156 | 98.77 106 | 99.77 158 | 98.60 387 |
|
| thres200 | | | 93.72 415 | 93.14 417 | 95.46 431 | 98.66 357 | 91.29 433 | 96.61 360 | 94.63 452 | 97.39 277 | 96.83 401 | 93.71 467 | 79.88 444 | 99.56 378 | 82.40 472 | 98.13 416 | 95.54 473 |
|
| wuyk23d | | | 96.06 366 | 97.62 279 | 91.38 460 | 98.65 361 | 98.57 106 | 98.85 92 | 96.95 418 | 96.86 323 | 99.90 14 | 99.16 160 | 99.18 19 | 98.40 467 | 89.23 455 | 99.77 158 | 77.18 480 |
|
| NCCC | | | 97.86 264 | 97.47 289 | 99.05 142 | 98.61 362 | 98.07 152 | 96.98 338 | 98.90 318 | 97.63 245 | 97.04 387 | 97.93 376 | 95.99 273 | 99.66 335 | 95.31 352 | 98.82 381 | 99.43 203 |
|
| DeepC-MVS_fast | | 96.85 6 | 98.30 215 | 98.15 227 | 98.75 200 | 98.61 362 | 97.23 226 | 97.76 247 | 99.09 285 | 97.31 285 | 98.75 249 | 98.66 298 | 97.56 170 | 99.64 346 | 96.10 324 | 99.55 267 | 99.39 221 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| testing3 | | | 93.51 417 | 92.09 428 | 97.75 326 | 98.60 364 | 94.40 358 | 97.32 312 | 95.26 447 | 97.56 255 | 96.79 404 | 95.50 446 | 53.57 485 | 99.77 261 | 95.26 353 | 98.97 371 | 99.08 313 |
|
| thisisatest0515 | | | 94.12 408 | 93.16 416 | 96.97 384 | 98.60 364 | 92.90 405 | 93.77 465 | 90.61 472 | 94.10 414 | 96.91 394 | 95.87 439 | 74.99 459 | 99.80 231 | 94.52 370 | 99.12 353 | 98.20 416 |
|
| GA-MVS | | | 95.86 373 | 95.32 383 | 97.49 358 | 98.60 364 | 94.15 367 | 93.83 464 | 97.93 388 | 95.49 379 | 96.68 406 | 97.42 405 | 83.21 434 | 99.30 436 | 96.22 315 | 98.55 400 | 99.01 325 |
|
| dmvs_testset | | | 92.94 427 | 92.21 427 | 95.13 435 | 98.59 367 | 90.99 440 | 97.65 264 | 92.09 468 | 96.95 314 | 94.00 460 | 93.55 468 | 92.34 359 | 96.97 477 | 72.20 479 | 92.52 475 | 97.43 452 |
|
| OPU-MVS | | | | | 98.82 179 | 98.59 367 | 98.30 126 | 98.10 184 | | | | 98.52 320 | 98.18 110 | 98.75 463 | 94.62 367 | 99.48 290 | 99.41 211 |
|
| MSLP-MVS++ | | | 98.02 247 | 98.14 229 | 97.64 341 | 98.58 369 | 95.19 334 | 97.48 291 | 99.23 254 | 97.47 265 | 97.90 334 | 98.62 307 | 97.04 209 | 98.81 461 | 97.55 199 | 99.41 304 | 98.94 341 |
|
| test12 | | | | | 98.93 164 | 98.58 369 | 97.83 178 | | 98.66 356 | | 96.53 413 | | 95.51 291 | 99.69 308 | | 99.13 350 | 99.27 269 |
|
| CL-MVSNet_self_test | | | 97.44 298 | 97.22 302 | 98.08 302 | 98.57 371 | 95.78 307 | 94.30 457 | 98.79 341 | 96.58 336 | 98.60 269 | 98.19 355 | 94.74 315 | 99.64 346 | 96.41 304 | 98.84 378 | 98.82 356 |
|
| PS-MVSNAJ | | | 97.08 327 | 97.39 291 | 96.16 416 | 98.56 372 | 92.46 413 | 95.24 431 | 98.85 332 | 97.25 291 | 97.49 366 | 95.99 435 | 98.07 120 | 99.90 81 | 96.37 306 | 98.67 393 | 96.12 469 |
|
| CNLPA | | | 97.17 322 | 96.71 335 | 98.55 243 | 98.56 372 | 98.05 156 | 96.33 378 | 98.93 312 | 96.91 319 | 97.06 386 | 97.39 406 | 94.38 322 | 99.45 414 | 91.66 431 | 99.18 344 | 98.14 419 |
|
| xiu_mvs_v2_base | | | 97.16 323 | 97.49 286 | 96.17 414 | 98.54 374 | 92.46 413 | 95.45 424 | 98.84 333 | 97.25 291 | 97.48 367 | 96.49 425 | 98.31 90 | 99.90 81 | 96.34 309 | 98.68 392 | 96.15 468 |
|
| alignmvs | | | 97.35 306 | 96.88 323 | 98.78 191 | 98.54 374 | 98.09 146 | 97.71 254 | 97.69 394 | 99.20 83 | 97.59 356 | 95.90 438 | 88.12 402 | 99.55 382 | 98.18 145 | 98.96 372 | 98.70 378 |
|
| FE-MVS | | | 95.66 380 | 94.95 393 | 97.77 322 | 98.53 376 | 95.28 330 | 99.40 19 | 96.09 435 | 93.11 428 | 97.96 331 | 99.26 131 | 79.10 451 | 99.77 261 | 92.40 424 | 98.71 387 | 98.27 414 |
|
| Effi-MVS+ | | | 98.02 247 | 97.82 262 | 98.62 225 | 98.53 376 | 97.19 233 | 97.33 311 | 99.68 60 | 97.30 286 | 96.68 406 | 97.46 403 | 98.56 68 | 99.80 231 | 96.63 282 | 98.20 410 | 98.86 353 |
|
| baseline1 | | | 95.96 371 | 95.44 377 | 97.52 355 | 98.51 378 | 93.99 379 | 98.39 151 | 96.09 435 | 98.21 192 | 98.40 297 | 97.76 385 | 86.88 404 | 99.63 349 | 95.42 350 | 89.27 478 | 98.95 337 |
|
| MVS_Test | | | 98.18 233 | 98.36 192 | 97.67 334 | 98.48 379 | 94.73 349 | 98.18 170 | 99.02 300 | 97.69 241 | 98.04 325 | 99.11 173 | 97.22 200 | 99.56 378 | 98.57 120 | 98.90 377 | 98.71 375 |
|
| MGCFI-Net | | | 98.34 207 | 98.28 206 | 98.51 252 | 98.47 380 | 97.59 201 | 98.96 77 | 99.48 137 | 99.18 91 | 97.40 373 | 95.50 446 | 98.66 54 | 99.50 400 | 98.18 145 | 98.71 387 | 98.44 401 |
|
| BH-RMVSNet | | | 96.83 340 | 96.58 345 | 97.58 347 | 98.47 380 | 94.05 369 | 96.67 356 | 97.36 403 | 96.70 332 | 97.87 337 | 97.98 371 | 95.14 300 | 99.44 416 | 90.47 450 | 98.58 399 | 99.25 276 |
|
| sasdasda | | | 98.34 207 | 98.26 210 | 98.58 233 | 98.46 382 | 97.82 183 | 98.96 77 | 99.46 150 | 99.19 88 | 97.46 368 | 95.46 449 | 98.59 62 | 99.46 412 | 98.08 152 | 98.71 387 | 98.46 395 |
|
| canonicalmvs | | | 98.34 207 | 98.26 210 | 98.58 233 | 98.46 382 | 97.82 183 | 98.96 77 | 99.46 150 | 99.19 88 | 97.46 368 | 95.46 449 | 98.59 62 | 99.46 412 | 98.08 152 | 98.71 387 | 98.46 395 |
|
| MVS-HIRNet | | | 94.32 402 | 95.62 368 | 90.42 461 | 98.46 382 | 75.36 485 | 96.29 381 | 89.13 476 | 95.25 386 | 95.38 442 | 99.75 16 | 92.88 350 | 99.19 446 | 94.07 387 | 99.39 306 | 96.72 462 |
|
| PHI-MVS | | | 98.29 218 | 97.95 249 | 99.34 83 | 98.44 385 | 99.16 49 | 98.12 181 | 99.38 185 | 96.01 362 | 98.06 322 | 98.43 333 | 97.80 149 | 99.67 322 | 95.69 342 | 99.58 256 | 99.20 291 |
|
| DVP-MVS++ | | | 98.90 100 | 98.70 131 | 99.51 49 | 98.43 386 | 99.15 53 | 99.43 15 | 99.32 213 | 98.17 199 | 99.26 148 | 99.02 196 | 98.18 110 | 99.88 115 | 97.07 237 | 99.45 294 | 99.49 169 |
|
| MSC_two_6792asdad | | | | | 99.32 91 | 98.43 386 | 98.37 121 | | 98.86 329 | | | | | 99.89 97 | 97.14 231 | 99.60 247 | 99.71 63 |
|
| No_MVS | | | | | 99.32 91 | 98.43 386 | 98.37 121 | | 98.86 329 | | | | | 99.89 97 | 97.14 231 | 99.60 247 | 99.71 63 |
|
| Fast-Effi-MVS+-dtu | | | 98.27 219 | 98.09 232 | 98.81 181 | 98.43 386 | 98.11 143 | 97.61 274 | 99.50 127 | 98.64 150 | 97.39 375 | 97.52 399 | 98.12 118 | 99.95 26 | 96.90 255 | 98.71 387 | 98.38 408 |
|
| OpenMVS_ROB |  | 95.38 14 | 95.84 375 | 95.18 388 | 97.81 319 | 98.41 390 | 97.15 239 | 97.37 308 | 98.62 360 | 83.86 472 | 98.65 260 | 98.37 339 | 94.29 325 | 99.68 318 | 88.41 456 | 98.62 397 | 96.60 463 |
|
| DeepPCF-MVS | | 96.93 5 | 98.32 212 | 98.01 242 | 99.23 108 | 98.39 391 | 98.97 74 | 95.03 436 | 99.18 266 | 96.88 320 | 99.33 130 | 98.78 268 | 98.16 114 | 99.28 440 | 96.74 269 | 99.62 240 | 99.44 199 |
|
| Patchmatch-test | | | 96.55 350 | 96.34 352 | 97.17 374 | 98.35 392 | 93.06 401 | 98.40 150 | 97.79 390 | 97.33 282 | 98.41 293 | 98.67 295 | 83.68 432 | 99.69 308 | 95.16 355 | 99.31 319 | 98.77 369 |
|
| AdaColmap |  | | 97.14 324 | 96.71 335 | 98.46 259 | 98.34 393 | 97.80 187 | 96.95 339 | 98.93 312 | 95.58 376 | 96.92 392 | 97.66 390 | 95.87 280 | 99.53 390 | 90.97 444 | 99.14 348 | 98.04 424 |
|
| OpenMVS |  | 96.65 7 | 97.09 326 | 96.68 337 | 98.32 276 | 98.32 394 | 97.16 238 | 98.86 91 | 99.37 189 | 89.48 460 | 96.29 422 | 99.15 164 | 96.56 243 | 99.90 81 | 92.90 412 | 99.20 339 | 97.89 432 |
|
| MG-MVS | | | 96.77 343 | 96.61 342 | 97.26 370 | 98.31 395 | 93.06 401 | 95.93 403 | 98.12 384 | 96.45 344 | 97.92 332 | 98.73 279 | 93.77 337 | 99.39 423 | 91.19 442 | 99.04 359 | 99.33 252 |
|
| test_yl | | | 96.69 344 | 96.29 354 | 97.90 312 | 98.28 396 | 95.24 331 | 97.29 316 | 97.36 403 | 98.21 192 | 98.17 308 | 97.86 378 | 86.27 408 | 99.55 382 | 94.87 361 | 98.32 404 | 98.89 348 |
|
| DCV-MVSNet | | | 96.69 344 | 96.29 354 | 97.90 312 | 98.28 396 | 95.24 331 | 97.29 316 | 97.36 403 | 98.21 192 | 98.17 308 | 97.86 378 | 86.27 408 | 99.55 382 | 94.87 361 | 98.32 404 | 98.89 348 |
|
| CHOSEN 280x420 | | | 95.51 385 | 95.47 374 | 95.65 426 | 98.25 398 | 88.27 457 | 93.25 468 | 98.88 322 | 93.53 422 | 94.65 451 | 97.15 414 | 86.17 410 | 99.93 54 | 97.41 213 | 99.93 56 | 98.73 374 |
|
| SCA | | | 96.41 357 | 96.66 340 | 95.67 424 | 98.24 399 | 88.35 456 | 95.85 409 | 96.88 421 | 96.11 356 | 97.67 351 | 98.67 295 | 93.10 345 | 99.85 156 | 94.16 381 | 99.22 335 | 98.81 361 |
|
| DeepMVS_CX |  | | | | 93.44 454 | 98.24 399 | 94.21 364 | | 94.34 454 | 64.28 480 | 91.34 474 | 94.87 461 | 89.45 391 | 92.77 481 | 77.54 477 | 93.14 474 | 93.35 476 |
|
| MS-PatchMatch | | | 97.68 279 | 97.75 265 | 97.45 361 | 98.23 401 | 93.78 388 | 97.29 316 | 98.84 333 | 96.10 357 | 98.64 261 | 98.65 300 | 96.04 266 | 99.36 426 | 96.84 261 | 99.14 348 | 99.20 291 |
|
| BH-w/o | | | 95.13 391 | 94.89 395 | 95.86 419 | 98.20 402 | 91.31 432 | 95.65 416 | 97.37 402 | 93.64 420 | 96.52 415 | 95.70 442 | 93.04 348 | 99.02 452 | 88.10 458 | 95.82 464 | 97.24 455 |
|
| mvs_anonymous | | | 97.83 272 | 98.16 226 | 96.87 389 | 98.18 403 | 91.89 422 | 97.31 314 | 98.90 318 | 97.37 279 | 98.83 234 | 99.46 81 | 96.28 257 | 99.79 244 | 98.90 95 | 98.16 414 | 98.95 337 |
|
| miper_lstm_enhance | | | 97.18 321 | 97.16 305 | 97.25 371 | 98.16 404 | 92.85 406 | 95.15 434 | 99.31 218 | 97.25 291 | 98.74 251 | 98.78 268 | 90.07 383 | 99.78 255 | 97.19 226 | 99.80 141 | 99.11 312 |
|
| RRT-MVS | | | 97.88 261 | 97.98 245 | 97.61 344 | 98.15 405 | 93.77 389 | 98.97 76 | 99.64 71 | 99.16 93 | 98.69 254 | 99.42 90 | 91.60 368 | 99.89 97 | 97.63 193 | 98.52 401 | 99.16 306 |
|
| ET-MVSNet_ETH3D | | | 94.30 404 | 93.21 415 | 97.58 347 | 98.14 406 | 94.47 357 | 94.78 442 | 93.24 464 | 94.72 398 | 89.56 476 | 95.87 439 | 78.57 454 | 99.81 222 | 96.91 250 | 97.11 449 | 98.46 395 |
|
| ADS-MVSNet2 | | | 95.43 386 | 94.98 391 | 96.76 396 | 98.14 406 | 91.74 423 | 97.92 222 | 97.76 391 | 90.23 454 | 96.51 416 | 98.91 234 | 85.61 415 | 99.85 156 | 92.88 413 | 96.90 450 | 98.69 379 |
|
| ADS-MVSNet | | | 95.24 389 | 94.93 394 | 96.18 413 | 98.14 406 | 90.10 449 | 97.92 222 | 97.32 406 | 90.23 454 | 96.51 416 | 98.91 234 | 85.61 415 | 99.74 281 | 92.88 413 | 96.90 450 | 98.69 379 |
|
| c3_l | | | 97.36 305 | 97.37 293 | 97.31 366 | 98.09 409 | 93.25 399 | 95.01 437 | 99.16 273 | 97.05 308 | 98.77 246 | 98.72 281 | 92.88 350 | 99.64 346 | 96.93 249 | 99.76 173 | 99.05 317 |
|
| FMVSNet3 | | | 97.50 290 | 97.24 301 | 98.29 280 | 98.08 410 | 95.83 304 | 97.86 231 | 98.91 317 | 97.89 227 | 98.95 207 | 98.95 227 | 87.06 403 | 99.81 222 | 97.77 181 | 99.69 208 | 99.23 281 |
|
| PAPM | | | 91.88 441 | 90.34 444 | 96.51 400 | 98.06 411 | 92.56 411 | 92.44 472 | 97.17 410 | 86.35 468 | 90.38 475 | 96.01 434 | 86.61 406 | 99.21 445 | 70.65 481 | 95.43 466 | 97.75 441 |
|
| Effi-MVS+-dtu | | | 98.26 221 | 97.90 257 | 99.35 80 | 98.02 412 | 99.49 6 | 98.02 201 | 99.16 273 | 98.29 185 | 97.64 352 | 97.99 370 | 96.44 249 | 99.95 26 | 96.66 280 | 98.93 375 | 98.60 387 |
|
| eth_miper_zixun_eth | | | 97.23 317 | 97.25 300 | 97.17 374 | 98.00 413 | 92.77 408 | 94.71 443 | 99.18 266 | 97.27 289 | 98.56 277 | 98.74 278 | 91.89 366 | 99.69 308 | 97.06 239 | 99.81 130 | 99.05 317 |
|
| HY-MVS | | 95.94 13 | 95.90 372 | 95.35 382 | 97.55 352 | 97.95 414 | 94.79 345 | 98.81 96 | 96.94 419 | 92.28 439 | 95.17 444 | 98.57 314 | 89.90 385 | 99.75 275 | 91.20 441 | 97.33 445 | 98.10 421 |
|
| UGNet | | | 98.53 180 | 98.45 177 | 98.79 188 | 97.94 415 | 96.96 251 | 99.08 61 | 98.54 363 | 99.10 105 | 96.82 402 | 99.47 79 | 96.55 244 | 99.84 174 | 98.56 123 | 99.94 50 | 99.55 136 |
| 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 |
| MAR-MVS | | | 96.47 355 | 95.70 365 | 98.79 188 | 97.92 416 | 99.12 63 | 98.28 159 | 98.60 361 | 92.16 440 | 95.54 439 | 96.17 432 | 94.77 314 | 99.52 394 | 89.62 453 | 98.23 408 | 97.72 443 |
| 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 |
| MVSTER | | | 96.86 339 | 96.55 346 | 97.79 320 | 97.91 417 | 94.21 364 | 97.56 280 | 98.87 324 | 97.49 264 | 99.06 177 | 99.05 191 | 80.72 442 | 99.80 231 | 98.44 129 | 99.82 124 | 99.37 232 |
|
| API-MVS | | | 97.04 330 | 96.91 322 | 97.42 363 | 97.88 418 | 98.23 134 | 98.18 170 | 98.50 366 | 97.57 253 | 97.39 375 | 96.75 420 | 96.77 230 | 99.15 449 | 90.16 451 | 99.02 363 | 94.88 474 |
|
| myMVS_eth3d28 | | | 92.92 428 | 92.31 424 | 94.77 438 | 97.84 419 | 87.59 461 | 96.19 387 | 96.11 434 | 97.08 307 | 94.27 454 | 93.49 470 | 66.07 476 | 98.78 462 | 91.78 429 | 97.93 427 | 97.92 431 |
|
| miper_ehance_all_eth | | | 97.06 328 | 97.03 313 | 97.16 376 | 97.83 420 | 93.06 401 | 94.66 446 | 99.09 285 | 95.99 363 | 98.69 254 | 98.45 331 | 92.73 355 | 99.61 359 | 96.79 263 | 99.03 360 | 98.82 356 |
|
| cl____ | | | 97.02 331 | 96.83 327 | 97.58 347 | 97.82 421 | 94.04 371 | 94.66 446 | 99.16 273 | 97.04 309 | 98.63 262 | 98.71 282 | 88.68 396 | 99.69 308 | 97.00 242 | 99.81 130 | 99.00 329 |
|
| DIV-MVS_self_test | | | 97.02 331 | 96.84 326 | 97.58 347 | 97.82 421 | 94.03 372 | 94.66 446 | 99.16 273 | 97.04 309 | 98.63 262 | 98.71 282 | 88.69 394 | 99.69 308 | 97.00 242 | 99.81 130 | 99.01 325 |
|
| CANet | | | 97.87 263 | 97.76 264 | 98.19 293 | 97.75 423 | 95.51 315 | 96.76 351 | 99.05 292 | 97.74 237 | 96.93 391 | 98.21 353 | 95.59 288 | 99.89 97 | 97.86 176 | 99.93 56 | 99.19 296 |
|
| UBG | | | 93.25 422 | 92.32 423 | 96.04 418 | 97.72 424 | 90.16 448 | 95.92 405 | 95.91 439 | 96.03 361 | 93.95 462 | 93.04 473 | 69.60 466 | 99.52 394 | 90.72 449 | 97.98 425 | 98.45 398 |
|
| mvsany_test1 | | | 97.60 284 | 97.54 282 | 97.77 322 | 97.72 424 | 95.35 327 | 95.36 428 | 97.13 412 | 94.13 413 | 99.71 50 | 99.33 112 | 97.93 133 | 99.30 436 | 97.60 197 | 98.94 374 | 98.67 383 |
|
| PVSNet_0 | | 89.98 21 | 91.15 442 | 90.30 445 | 93.70 451 | 97.72 424 | 84.34 475 | 90.24 475 | 97.42 401 | 90.20 457 | 93.79 463 | 93.09 472 | 90.90 378 | 98.89 460 | 86.57 464 | 72.76 481 | 97.87 434 |
|
| CR-MVSNet | | | 96.28 360 | 95.95 359 | 97.28 368 | 97.71 427 | 94.22 362 | 98.11 182 | 98.92 315 | 92.31 438 | 96.91 394 | 99.37 100 | 85.44 418 | 99.81 222 | 97.39 214 | 97.36 443 | 97.81 437 |
|
| RPMNet | | | 97.02 331 | 96.93 318 | 97.30 367 | 97.71 427 | 94.22 362 | 98.11 182 | 99.30 226 | 99.37 61 | 96.91 394 | 99.34 109 | 86.72 405 | 99.87 134 | 97.53 202 | 97.36 443 | 97.81 437 |
|
| ETVMVS | | | 92.60 431 | 91.08 440 | 97.18 372 | 97.70 429 | 93.65 394 | 96.54 363 | 95.70 442 | 96.51 337 | 94.68 450 | 92.39 476 | 61.80 482 | 99.50 400 | 86.97 461 | 97.41 439 | 98.40 406 |
|
| pmmvs3 | | | 95.03 393 | 94.40 400 | 96.93 385 | 97.70 429 | 92.53 412 | 95.08 435 | 97.71 393 | 88.57 464 | 97.71 348 | 98.08 364 | 79.39 449 | 99.82 205 | 96.19 317 | 99.11 354 | 98.43 403 |
|
| baseline2 | | | 93.73 414 | 92.83 420 | 96.42 403 | 97.70 429 | 91.28 434 | 96.84 347 | 89.77 475 | 93.96 418 | 92.44 470 | 95.93 437 | 79.14 450 | 99.77 261 | 92.94 411 | 96.76 454 | 98.21 415 |
|
| WBMVS | | | 95.18 390 | 94.78 396 | 96.37 404 | 97.68 432 | 89.74 451 | 95.80 411 | 98.73 352 | 97.54 259 | 98.30 299 | 98.44 332 | 70.06 464 | 99.82 205 | 96.62 283 | 99.87 98 | 99.54 142 |
|
| tpm | | | 94.67 398 | 94.34 402 | 95.66 425 | 97.68 432 | 88.42 455 | 97.88 227 | 94.90 449 | 94.46 404 | 96.03 429 | 98.56 315 | 78.66 452 | 99.79 244 | 95.88 330 | 95.01 468 | 98.78 368 |
|
| CANet_DTU | | | 97.26 313 | 97.06 312 | 97.84 316 | 97.57 434 | 94.65 353 | 96.19 387 | 98.79 341 | 97.23 297 | 95.14 445 | 98.24 350 | 93.22 342 | 99.84 174 | 97.34 216 | 99.84 112 | 99.04 321 |
|
| testing11 | | | 93.08 425 | 92.02 430 | 96.26 409 | 97.56 435 | 90.83 443 | 96.32 379 | 95.70 442 | 96.47 341 | 92.66 469 | 93.73 466 | 64.36 480 | 99.59 366 | 93.77 396 | 97.57 432 | 98.37 410 |
|
| tpm2 | | | 93.09 424 | 92.58 422 | 94.62 440 | 97.56 435 | 86.53 464 | 97.66 262 | 95.79 441 | 86.15 469 | 94.07 459 | 98.23 352 | 75.95 457 | 99.53 390 | 90.91 446 | 96.86 453 | 97.81 437 |
|
| testing91 | | | 93.32 420 | 92.27 425 | 96.47 402 | 97.54 437 | 91.25 435 | 96.17 391 | 96.76 423 | 97.18 301 | 93.65 465 | 93.50 469 | 65.11 479 | 99.63 349 | 93.04 410 | 97.45 436 | 98.53 392 |
|
| TR-MVS | | | 95.55 383 | 95.12 389 | 96.86 392 | 97.54 437 | 93.94 380 | 96.49 368 | 96.53 428 | 94.36 409 | 97.03 389 | 96.61 423 | 94.26 326 | 99.16 448 | 86.91 463 | 96.31 458 | 97.47 451 |
|
| testing99 | | | 93.04 426 | 91.98 433 | 96.23 411 | 97.53 439 | 90.70 445 | 96.35 377 | 95.94 438 | 96.87 321 | 93.41 466 | 93.43 471 | 63.84 481 | 99.59 366 | 93.24 408 | 97.19 446 | 98.40 406 |
|
| 1314 | | | 95.74 377 | 95.60 369 | 96.17 414 | 97.53 439 | 92.75 409 | 98.07 191 | 98.31 375 | 91.22 449 | 94.25 455 | 96.68 421 | 95.53 289 | 99.03 451 | 91.64 433 | 97.18 447 | 96.74 461 |
|
| CostFormer | | | 93.97 410 | 93.78 408 | 94.51 441 | 97.53 439 | 85.83 467 | 97.98 213 | 95.96 437 | 89.29 462 | 94.99 447 | 98.63 305 | 78.63 453 | 99.62 352 | 94.54 369 | 96.50 455 | 98.09 422 |
|
| FMVSNet5 | | | 96.01 368 | 95.20 387 | 98.41 265 | 97.53 439 | 96.10 290 | 98.74 97 | 99.50 127 | 97.22 300 | 98.03 326 | 99.04 193 | 69.80 465 | 99.88 115 | 97.27 221 | 99.71 198 | 99.25 276 |
|
| PMMVS | | | 96.51 351 | 95.98 358 | 98.09 299 | 97.53 439 | 95.84 303 | 94.92 439 | 98.84 333 | 91.58 444 | 96.05 428 | 95.58 443 | 95.68 285 | 99.66 335 | 95.59 346 | 98.09 418 | 98.76 371 |
|
| reproduce_monomvs | | | 95.00 395 | 95.25 384 | 94.22 444 | 97.51 444 | 83.34 476 | 97.86 231 | 98.44 368 | 98.51 168 | 99.29 140 | 99.30 119 | 67.68 470 | 99.56 378 | 98.89 97 | 99.81 130 | 99.77 50 |
|
| PAPR | | | 95.29 387 | 94.47 398 | 97.75 326 | 97.50 445 | 95.14 336 | 94.89 440 | 98.71 354 | 91.39 448 | 95.35 443 | 95.48 448 | 94.57 317 | 99.14 450 | 84.95 466 | 97.37 441 | 98.97 334 |
|
| testing222 | | | 91.96 439 | 90.37 443 | 96.72 397 | 97.47 446 | 92.59 410 | 96.11 393 | 94.76 450 | 96.83 324 | 92.90 468 | 92.87 474 | 57.92 483 | 99.55 382 | 86.93 462 | 97.52 433 | 98.00 428 |
|
| PatchT | | | 96.65 347 | 96.35 351 | 97.54 353 | 97.40 447 | 95.32 329 | 97.98 213 | 96.64 425 | 99.33 66 | 96.89 398 | 99.42 90 | 84.32 426 | 99.81 222 | 97.69 192 | 97.49 434 | 97.48 450 |
|
| tpm cat1 | | | 93.29 421 | 93.13 418 | 93.75 450 | 97.39 448 | 84.74 470 | 97.39 302 | 97.65 397 | 83.39 474 | 94.16 456 | 98.41 334 | 82.86 437 | 99.39 423 | 91.56 435 | 95.35 467 | 97.14 456 |
|
| PatchmatchNet |  | | 95.58 382 | 95.67 367 | 95.30 434 | 97.34 449 | 87.32 462 | 97.65 264 | 96.65 424 | 95.30 385 | 97.07 385 | 98.69 291 | 84.77 421 | 99.75 275 | 94.97 359 | 98.64 394 | 98.83 355 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| Patchmtry | | | 97.35 306 | 96.97 316 | 98.50 256 | 97.31 450 | 96.47 281 | 98.18 170 | 98.92 315 | 98.95 128 | 98.78 243 | 99.37 100 | 85.44 418 | 99.85 156 | 95.96 328 | 99.83 119 | 99.17 303 |
|
| LS3D | | | 98.63 159 | 98.38 189 | 99.36 74 | 97.25 451 | 99.38 13 | 99.12 60 | 99.32 213 | 99.21 81 | 98.44 290 | 98.88 244 | 97.31 192 | 99.80 231 | 96.58 286 | 99.34 314 | 98.92 343 |
|
| IB-MVS | | 91.63 19 | 92.24 437 | 90.90 441 | 96.27 408 | 97.22 452 | 91.24 436 | 94.36 456 | 93.33 463 | 92.37 437 | 92.24 472 | 94.58 463 | 66.20 475 | 99.89 97 | 93.16 409 | 94.63 470 | 97.66 445 |
| 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 |
| UWE-MVS | | | 92.38 434 | 91.76 437 | 94.21 445 | 97.16 453 | 84.65 471 | 95.42 426 | 88.45 477 | 95.96 364 | 96.17 423 | 95.84 441 | 66.36 473 | 99.71 297 | 91.87 428 | 98.64 394 | 98.28 413 |
|
| tpmrst | | | 95.07 392 | 95.46 375 | 93.91 448 | 97.11 454 | 84.36 474 | 97.62 269 | 96.96 417 | 94.98 392 | 96.35 421 | 98.80 264 | 85.46 417 | 99.59 366 | 95.60 345 | 96.23 459 | 97.79 440 |
|
| Syy-MVS | | | 96.04 367 | 95.56 373 | 97.49 358 | 97.10 455 | 94.48 356 | 96.18 389 | 96.58 426 | 95.65 373 | 94.77 448 | 92.29 477 | 91.27 374 | 99.36 426 | 98.17 147 | 98.05 422 | 98.63 385 |
|
| myMVS_eth3d | | | 91.92 440 | 90.45 442 | 96.30 406 | 97.10 455 | 90.90 441 | 96.18 389 | 96.58 426 | 95.65 373 | 94.77 448 | 92.29 477 | 53.88 484 | 99.36 426 | 89.59 454 | 98.05 422 | 98.63 385 |
|
| MDTV_nov1_ep13 | | | | 95.22 386 | | 97.06 457 | 83.20 477 | 97.74 251 | 96.16 432 | 94.37 408 | 96.99 390 | 98.83 257 | 83.95 430 | 99.53 390 | 93.90 390 | 97.95 426 | |
|
| MVS | | | 93.19 423 | 92.09 428 | 96.50 401 | 96.91 458 | 94.03 372 | 98.07 191 | 98.06 386 | 68.01 479 | 94.56 453 | 96.48 426 | 95.96 276 | 99.30 436 | 83.84 468 | 96.89 452 | 96.17 466 |
|
| E-PMN | | | 94.17 406 | 94.37 401 | 93.58 452 | 96.86 459 | 85.71 468 | 90.11 477 | 97.07 413 | 98.17 199 | 97.82 343 | 97.19 412 | 84.62 423 | 98.94 456 | 89.77 452 | 97.68 431 | 96.09 470 |
|
| JIA-IIPM | | | 95.52 384 | 95.03 390 | 97.00 381 | 96.85 460 | 94.03 372 | 96.93 342 | 95.82 440 | 99.20 83 | 94.63 452 | 99.71 22 | 83.09 435 | 99.60 362 | 94.42 375 | 94.64 469 | 97.36 454 |
|
| EMVS | | | 93.83 412 | 94.02 404 | 93.23 457 | 96.83 461 | 84.96 469 | 89.77 478 | 96.32 430 | 97.92 224 | 97.43 372 | 96.36 431 | 86.17 410 | 98.93 457 | 87.68 459 | 97.73 430 | 95.81 471 |
|
| cl22 | | | 95.79 376 | 95.39 380 | 96.98 383 | 96.77 462 | 92.79 407 | 94.40 455 | 98.53 364 | 94.59 401 | 97.89 335 | 98.17 356 | 82.82 438 | 99.24 442 | 96.37 306 | 99.03 360 | 98.92 343 |
|
| WB-MVSnew | | | 95.73 378 | 95.57 372 | 96.23 411 | 96.70 463 | 90.70 445 | 96.07 395 | 93.86 460 | 95.60 375 | 97.04 387 | 95.45 452 | 96.00 269 | 99.55 382 | 91.04 443 | 98.31 406 | 98.43 403 |
|
| dp | | | 93.47 418 | 93.59 411 | 93.13 458 | 96.64 464 | 81.62 483 | 97.66 262 | 96.42 429 | 92.80 433 | 96.11 425 | 98.64 303 | 78.55 455 | 99.59 366 | 93.31 406 | 92.18 477 | 98.16 418 |
|
| MonoMVSNet | | | 96.25 362 | 96.53 348 | 95.39 432 | 96.57 465 | 91.01 439 | 98.82 95 | 97.68 396 | 98.57 163 | 98.03 326 | 99.37 100 | 90.92 377 | 97.78 473 | 94.99 357 | 93.88 473 | 97.38 453 |
|
| test-LLR | | | 93.90 411 | 93.85 406 | 94.04 446 | 96.53 466 | 84.62 472 | 94.05 461 | 92.39 466 | 96.17 353 | 94.12 457 | 95.07 453 | 82.30 439 | 99.67 322 | 95.87 333 | 98.18 411 | 97.82 435 |
|
| test-mter | | | 92.33 436 | 91.76 437 | 94.04 446 | 96.53 466 | 84.62 472 | 94.05 461 | 92.39 466 | 94.00 417 | 94.12 457 | 95.07 453 | 65.63 478 | 99.67 322 | 95.87 333 | 98.18 411 | 97.82 435 |
|
| TESTMET0.1,1 | | | 92.19 438 | 91.77 436 | 93.46 453 | 96.48 468 | 82.80 479 | 94.05 461 | 91.52 471 | 94.45 406 | 94.00 460 | 94.88 459 | 66.65 472 | 99.56 378 | 95.78 338 | 98.11 417 | 98.02 425 |
|
| MGCNet | | | 97.44 298 | 97.01 315 | 98.72 208 | 96.42 469 | 96.74 265 | 97.20 326 | 91.97 469 | 98.46 171 | 98.30 299 | 98.79 266 | 92.74 354 | 99.91 74 | 99.30 63 | 99.94 50 | 99.52 154 |
|
| miper_enhance_ethall | | | 96.01 368 | 95.74 363 | 96.81 393 | 96.41 470 | 92.27 419 | 93.69 466 | 98.89 321 | 91.14 451 | 98.30 299 | 97.35 410 | 90.58 380 | 99.58 373 | 96.31 310 | 99.03 360 | 98.60 387 |
|
| tpmvs | | | 95.02 394 | 95.25 384 | 94.33 442 | 96.39 471 | 85.87 465 | 98.08 187 | 96.83 422 | 95.46 380 | 95.51 441 | 98.69 291 | 85.91 413 | 99.53 390 | 94.16 381 | 96.23 459 | 97.58 448 |
|
| CMPMVS |  | 75.91 23 | 96.29 359 | 95.44 377 | 98.84 176 | 96.25 472 | 98.69 98 | 97.02 335 | 99.12 280 | 88.90 463 | 97.83 341 | 98.86 247 | 89.51 389 | 98.90 459 | 91.92 426 | 99.51 279 | 98.92 343 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| test0.0.03 1 | | | 94.51 399 | 93.69 409 | 96.99 382 | 96.05 473 | 93.61 396 | 94.97 438 | 93.49 461 | 96.17 353 | 97.57 359 | 94.88 459 | 82.30 439 | 99.01 454 | 93.60 399 | 94.17 472 | 98.37 410 |
|
| EPMVS | | | 93.72 415 | 93.27 414 | 95.09 437 | 96.04 474 | 87.76 459 | 98.13 177 | 85.01 482 | 94.69 399 | 96.92 392 | 98.64 303 | 78.47 456 | 99.31 434 | 95.04 356 | 96.46 456 | 98.20 416 |
|
| cascas | | | 94.79 397 | 94.33 403 | 96.15 417 | 96.02 475 | 92.36 417 | 92.34 473 | 99.26 246 | 85.34 471 | 95.08 446 | 94.96 458 | 92.96 349 | 98.53 466 | 94.41 378 | 98.59 398 | 97.56 449 |
|
| MVStest1 | | | 95.86 373 | 95.60 369 | 96.63 398 | 95.87 476 | 91.70 424 | 97.93 219 | 98.94 309 | 98.03 214 | 99.56 74 | 99.66 32 | 71.83 462 | 98.26 469 | 99.35 59 | 99.24 331 | 99.91 13 |
|
| gg-mvs-nofinetune | | | 92.37 435 | 91.20 439 | 95.85 420 | 95.80 477 | 92.38 416 | 99.31 30 | 81.84 484 | 99.75 11 | 91.83 473 | 99.74 18 | 68.29 467 | 99.02 452 | 87.15 460 | 97.12 448 | 96.16 467 |
|
| gm-plane-assit | | | | | | 94.83 478 | 81.97 481 | | | 88.07 466 | | 94.99 456 | | 99.60 362 | 91.76 430 | | |
|
| GG-mvs-BLEND | | | | | 94.76 439 | 94.54 479 | 92.13 421 | 99.31 30 | 80.47 485 | | 88.73 479 | 91.01 479 | 67.59 471 | 98.16 472 | 82.30 473 | 94.53 471 | 93.98 475 |
|
| UWE-MVS-28 | | | 90.22 443 | 89.28 446 | 93.02 459 | 94.50 480 | 82.87 478 | 96.52 366 | 87.51 478 | 95.21 388 | 92.36 471 | 96.04 433 | 71.57 463 | 98.25 470 | 72.04 480 | 97.77 429 | 97.94 430 |
|
| EPNet_dtu | | | 94.93 396 | 94.78 396 | 95.38 433 | 93.58 481 | 87.68 460 | 96.78 349 | 95.69 444 | 97.35 281 | 89.14 478 | 98.09 363 | 88.15 401 | 99.49 403 | 94.95 360 | 99.30 322 | 98.98 331 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| dongtai | | | 76.24 447 | 75.95 450 | 77.12 464 | 92.39 482 | 67.91 488 | 90.16 476 | 59.44 489 | 82.04 475 | 89.42 477 | 94.67 462 | 49.68 486 | 81.74 482 | 48.06 482 | 77.66 480 | 81.72 478 |
|
| KD-MVS_2432*1600 | | | 92.87 429 | 91.99 431 | 95.51 429 | 91.37 483 | 89.27 452 | 94.07 459 | 98.14 382 | 95.42 381 | 97.25 380 | 96.44 428 | 67.86 468 | 99.24 442 | 91.28 439 | 96.08 462 | 98.02 425 |
|
| miper_refine_blended | | | 92.87 429 | 91.99 431 | 95.51 429 | 91.37 483 | 89.27 452 | 94.07 459 | 98.14 382 | 95.42 381 | 97.25 380 | 96.44 428 | 67.86 468 | 99.24 442 | 91.28 439 | 96.08 462 | 98.02 425 |
|
| EPNet | | | 96.14 365 | 95.44 377 | 98.25 284 | 90.76 485 | 95.50 318 | 97.92 222 | 94.65 451 | 98.97 124 | 92.98 467 | 98.85 250 | 89.12 392 | 99.87 134 | 95.99 326 | 99.68 213 | 99.39 221 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| kuosan | | | 69.30 448 | 68.95 451 | 70.34 465 | 87.68 486 | 65.00 489 | 91.11 474 | 59.90 488 | 69.02 478 | 74.46 483 | 88.89 480 | 48.58 487 | 68.03 484 | 28.61 483 | 72.33 482 | 77.99 479 |
|
| test_method | | | 79.78 445 | 79.50 448 | 80.62 462 | 80.21 487 | 45.76 490 | 70.82 479 | 98.41 372 | 31.08 482 | 80.89 482 | 97.71 387 | 84.85 420 | 97.37 475 | 91.51 436 | 80.03 479 | 98.75 372 |
|
| tmp_tt | | | 78.77 446 | 78.73 449 | 78.90 463 | 58.45 488 | 74.76 487 | 94.20 458 | 78.26 486 | 39.16 481 | 86.71 480 | 92.82 475 | 80.50 443 | 75.19 483 | 86.16 465 | 92.29 476 | 86.74 477 |
|
| testmvs | | | 17.12 450 | 20.53 453 | 6.87 467 | 12.05 489 | 4.20 492 | 93.62 467 | 6.73 490 | 4.62 485 | 10.41 485 | 24.33 482 | 8.28 489 | 3.56 486 | 9.69 485 | 15.07 483 | 12.86 482 |
|
| test123 | | | 17.04 451 | 20.11 454 | 7.82 466 | 10.25 490 | 4.91 491 | 94.80 441 | 4.47 491 | 4.93 484 | 10.00 486 | 24.28 483 | 9.69 488 | 3.64 485 | 10.14 484 | 12.43 484 | 14.92 481 |
|
| mmdepth | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| monomultidepth | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| test_blank | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| eth-test2 | | | | | | 0.00 491 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 491 | | | | | | | | | | | |
|
| uanet_test | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| DCPMVS | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| cdsmvs_eth3d_5k | | | 24.66 449 | 32.88 452 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 99.10 283 | 0.00 486 | 0.00 487 | 97.58 395 | 99.21 18 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| pcd_1.5k_mvsjas | | | 8.17 452 | 10.90 455 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 98.07 120 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| sosnet-low-res | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| sosnet | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| uncertanet | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| Regformer | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| ab-mvs-re | | | 8.12 453 | 10.83 456 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 97.48 401 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| uanet | | | 0.00 454 | 0.00 457 | 0.00 468 | 0.00 491 | 0.00 493 | 0.00 480 | 0.00 492 | 0.00 486 | 0.00 487 | 0.00 486 | 0.00 490 | 0.00 487 | 0.00 486 | 0.00 485 | 0.00 483 |
|
| TestfortrainingZip | | | | | | | | 98.68 107 | | | | | | | | | |
|
| WAC-MVS | | | | | | | 90.90 441 | | | | | | | | 91.37 438 | | |
|
| PC_three_1452 | | | | | | | | | | 93.27 425 | 99.40 115 | 98.54 316 | 98.22 105 | 97.00 476 | 95.17 354 | 99.45 294 | 99.49 169 |
|
| test_241102_TWO | | | | | | | | | 99.30 226 | 98.03 214 | 99.26 148 | 99.02 196 | 97.51 178 | 99.88 115 | 96.91 250 | 99.60 247 | 99.66 78 |
|
| test_0728_THIRD | | | | | | | | | | 98.17 199 | 99.08 175 | 99.02 196 | 97.89 139 | 99.88 115 | 97.07 237 | 99.71 198 | 99.70 68 |
|
| GSMVS | | | | | | | | | | | | | | | | | 98.81 361 |
|
| sam_mvs1 | | | | | | | | | | | | | 84.74 422 | | | | 98.81 361 |
|
| sam_mvs | | | | | | | | | | | | | 84.29 428 | | | | |
|
| MTGPA |  | | | | | | | | 99.20 258 | | | | | | | | |
|
| test_post1 | | | | | | | | 97.59 277 | | | | 20.48 485 | 83.07 436 | 99.66 335 | 94.16 381 | | |
|
| test_post | | | | | | | | | | | | 21.25 484 | 83.86 431 | 99.70 304 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 98.77 270 | 84.37 425 | 99.85 156 | | | |
|
| MTMP | | | | | | | | 97.93 219 | 91.91 470 | | | | | | | | |
|
| test9_res | | | | | | | | | | | | | | | 93.28 407 | 99.15 347 | 99.38 230 |
|
| agg_prior2 | | | | | | | | | | | | | | | 92.50 423 | 99.16 345 | 99.37 232 |
|
| test_prior4 | | | | | | | 97.97 163 | 95.86 407 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 95.74 414 | | 96.48 340 | 96.11 425 | 97.63 393 | 95.92 279 | | 94.16 381 | 99.20 339 | |
|
| 旧先验2 | | | | | | | | 95.76 413 | | 88.56 465 | 97.52 363 | | | 99.66 335 | 94.48 371 | | |
|
| 新几何2 | | | | | | | | 95.93 403 | | | | | | | | | |
|
| 无先验 | | | | | | | | 95.74 414 | 98.74 351 | 89.38 461 | | | | 99.73 288 | 92.38 425 | | 99.22 286 |
|
| 原ACMM2 | | | | | | | | 95.53 420 | | | | | | | | | |
|
| testdata2 | | | | | | | | | | | | | | 99.79 244 | 92.80 417 | | |
|
| segment_acmp | | | | | | | | | | | | | 97.02 212 | | | | |
|
| testdata1 | | | | | | | | 95.44 425 | | 96.32 348 | | | | | | | |
|
| plane_prior5 | | | | | | | | | 99.27 241 | | | | | 99.70 304 | 94.42 375 | 99.51 279 | 99.45 195 |
|
| plane_prior4 | | | | | | | | | | | | 97.98 371 | | | | | |
|
| plane_prior3 | | | | | | | 97.78 188 | | | 97.41 274 | 97.79 344 | | | | | | |
|
| plane_prior2 | | | | | | | | 97.77 244 | | 98.20 196 | | | | | | | |
|
| plane_prior | | | | | | | 97.65 197 | 97.07 334 | | 96.72 330 | | | | | | 99.36 310 | |
|
| n2 | | | | | | | | | 0.00 492 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 492 | | | | | | | | |
|
| door-mid | | | | | | | | | 99.57 96 | | | | | | | | |
|
| test11 | | | | | | | | | 98.87 324 | | | | | | | | |
|
| door | | | | | | | | | 99.41 178 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 96.79 261 | | | | | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 92.82 415 | | |
|
| HQP4-MVS | | | | | | | | | | | 95.56 435 | | | 99.54 388 | | | 99.32 255 |
|
| HQP3-MVS | | | | | | | | | 99.04 295 | | | | | | | 99.26 329 | |
|
| HQP2-MVS | | | | | | | | | | | | | 93.84 333 | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 74.92 486 | 97.69 257 | | 90.06 459 | 97.75 347 | | 85.78 414 | | 93.52 401 | | 98.69 379 |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 99.77 158 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 99.68 213 | |
|
| Test By Simon | | | | | | | | | | | | | 96.52 245 | | | | |
|