| LCM-MVSNet | | | 99.86 1 | 99.86 1 | 99.87 1 | 99.99 1 | 99.77 1 | 99.77 1 | 99.80 3 | 99.97 1 | 99.97 1 | 99.95 1 | 99.74 1 | 99.98 1 | 99.56 1 | 100.00 1 | 99.85 6 |
|
| LTVRE_ROB | | 96.88 1 | 99.18 2 | 99.34 2 | 98.72 40 | 99.71 10 | 96.99 47 | 99.69 2 | 99.57 20 | 99.02 21 | 99.62 15 | 99.36 26 | 98.53 11 | 99.52 225 | 98.58 42 | 99.95 5 | 99.66 36 |
| 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 |
| tt0320-xc | | | 99.10 4 | 99.31 3 | 98.49 57 | 99.57 20 | 96.09 79 | 98.91 11 | 99.55 24 | 99.67 3 | 99.78 3 | 99.69 4 | 98.63 10 | 99.77 69 | 98.02 58 | 99.93 11 | 99.60 46 |
|
| tt0320 | | | 99.07 6 | 99.29 4 | 98.43 62 | 99.55 24 | 95.92 87 | 98.97 10 | 99.53 26 | 99.67 3 | 99.79 2 | 99.71 3 | 98.33 14 | 99.78 58 | 98.11 52 | 99.92 15 | 99.57 58 |
|
| sc_t1 | | | 99.09 5 | 99.28 5 | 98.53 54 | 99.72 8 | 96.21 73 | 98.87 12 | 99.19 60 | 99.71 2 | 99.76 4 | 99.65 8 | 98.64 9 | 99.79 53 | 98.07 56 | 99.90 25 | 99.58 50 |
|
| UniMVSNet_ETH3D | | | 99.12 3 | 99.28 5 | 98.65 45 | 99.77 5 | 96.34 69 | 99.18 6 | 99.20 58 | 99.67 3 | 99.73 6 | 99.65 8 | 99.15 3 | 99.86 27 | 97.22 95 | 99.92 15 | 99.77 15 |
|
| pmmvs6 | | | 99.07 6 | 99.24 7 | 98.56 51 | 99.81 2 | 96.38 65 | 98.87 12 | 99.30 41 | 99.01 22 | 99.63 14 | 99.66 6 | 99.27 2 | 99.68 150 | 97.75 73 | 99.89 26 | 99.62 44 |
|
| v7n | | | 98.73 14 | 98.99 8 | 97.95 110 | 99.64 14 | 94.20 169 | 98.67 18 | 99.14 76 | 99.08 16 | 99.42 28 | 99.23 38 | 96.53 122 | 99.91 13 | 99.27 10 | 99.93 11 | 99.73 26 |
|
| mvs_tets | | | 98.90 8 | 98.94 9 | 98.75 34 | 99.69 11 | 96.48 63 | 98.54 26 | 99.22 55 | 96.23 153 | 99.71 7 | 99.48 15 | 98.77 7 | 99.93 3 | 98.89 30 | 99.95 5 | 99.84 8 |
|
| ANet_high | | | 98.31 39 | 98.94 9 | 96.41 255 | 99.33 60 | 89.64 317 | 97.92 74 | 99.56 22 | 99.27 10 | 99.66 12 | 99.50 14 | 97.67 36 | 99.83 35 | 97.55 82 | 99.98 2 | 99.77 15 |
|
| DTE-MVSNet | | | 98.79 11 | 98.86 11 | 98.59 49 | 99.55 24 | 96.12 77 | 98.48 33 | 99.10 87 | 99.36 7 | 99.29 38 | 99.06 61 | 97.27 58 | 99.93 3 | 97.71 75 | 99.91 19 | 99.70 31 |
|
| TDRefinement | | | 98.90 8 | 98.86 11 | 99.02 9 | 99.54 28 | 98.06 8 | 99.34 5 | 99.44 32 | 98.85 27 | 99.00 62 | 99.20 40 | 97.42 52 | 99.59 200 | 97.21 96 | 99.76 70 | 99.40 134 |
|
| PS-CasMVS | | | 98.73 14 | 98.85 13 | 98.39 66 | 99.55 24 | 95.47 111 | 98.49 31 | 99.13 78 | 99.22 12 | 99.22 43 | 98.96 74 | 97.35 54 | 99.92 5 | 97.79 70 | 99.93 11 | 99.79 13 |
|
| PEN-MVS | | | 98.75 13 | 98.85 13 | 98.44 61 | 99.58 19 | 95.67 98 | 98.45 34 | 99.15 73 | 99.33 8 | 99.30 37 | 99.00 68 | 97.27 58 | 99.92 5 | 97.64 79 | 99.92 15 | 99.75 24 |
|
| jajsoiax | | | 98.77 12 | 98.79 15 | 98.74 37 | 99.66 13 | 96.48 63 | 98.45 34 | 99.12 79 | 95.83 194 | 99.67 10 | 99.37 24 | 98.25 17 | 99.92 5 | 98.77 33 | 99.94 8 | 99.82 9 |
|
| Anonymous20231211 | | | 98.55 24 | 98.76 16 | 97.94 111 | 98.79 164 | 94.37 161 | 98.84 14 | 99.15 73 | 99.37 6 | 99.67 10 | 99.43 20 | 95.61 174 | 99.72 110 | 98.12 51 | 99.86 35 | 99.73 26 |
|
| UA-Net | | | 98.88 10 | 98.76 16 | 99.22 2 | 99.11 105 | 97.89 16 | 99.47 3 | 99.32 39 | 99.08 16 | 97.87 210 | 99.67 5 | 96.47 127 | 99.92 5 | 97.88 64 | 99.98 2 | 99.85 6 |
|
| ACMH | | 93.61 9 | 98.44 32 | 98.76 16 | 97.51 143 | 99.43 43 | 93.54 194 | 98.23 50 | 99.05 107 | 97.40 92 | 99.37 32 | 99.08 60 | 98.79 6 | 99.47 245 | 97.74 74 | 99.71 91 | 99.50 87 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| test_fmvsmconf0.01_n | | | 98.57 21 | 98.74 19 | 98.06 100 | 99.39 50 | 94.63 148 | 96.70 172 | 99.82 1 | 95.44 216 | 99.64 13 | 99.52 12 | 98.96 4 | 99.74 94 | 99.38 7 | 99.86 35 | 99.81 10 |
|
| test_djsdf | | | 98.73 14 | 98.74 19 | 98.69 42 | 99.63 15 | 96.30 71 | 98.67 18 | 99.02 120 | 96.50 137 | 99.32 36 | 99.44 19 | 97.43 51 | 99.92 5 | 98.73 36 | 99.95 5 | 99.86 5 |
|
| pm-mvs1 | | | 98.47 31 | 98.67 21 | 97.86 115 | 99.52 31 | 94.58 151 | 98.28 46 | 99.00 132 | 97.57 78 | 99.27 39 | 99.22 39 | 98.32 15 | 99.50 230 | 97.09 103 | 99.75 80 | 99.50 87 |
|
| TransMVSNet (Re) | | | 98.38 35 | 98.67 21 | 97.51 143 | 99.51 32 | 93.39 203 | 98.20 55 | 98.87 166 | 98.23 53 | 99.48 21 | 99.27 34 | 98.47 13 | 99.55 216 | 96.52 126 | 99.53 164 | 99.60 46 |
|
| anonymousdsp | | | 98.72 17 | 98.63 23 | 98.99 13 | 99.62 16 | 97.29 40 | 98.65 22 | 99.19 60 | 95.62 204 | 99.35 35 | 99.37 24 | 97.38 53 | 99.90 17 | 98.59 41 | 99.91 19 | 99.77 15 |
|
| PS-MVSNAJss | | | 98.53 27 | 98.63 23 | 98.21 86 | 99.68 12 | 94.82 141 | 98.10 60 | 99.21 56 | 96.91 116 | 99.75 5 | 99.45 18 | 95.82 161 | 99.92 5 | 98.80 32 | 99.96 4 | 99.89 4 |
|
| nrg030 | | | 98.54 25 | 98.62 25 | 98.32 72 | 99.22 78 | 95.66 99 | 97.90 76 | 99.08 96 | 98.31 47 | 99.02 59 | 98.74 100 | 97.68 35 | 99.61 195 | 97.77 72 | 99.85 46 | 99.70 31 |
|
| WR-MVS_H | | | 98.65 18 | 98.62 25 | 98.75 34 | 99.51 32 | 96.61 59 | 98.55 25 | 99.17 65 | 99.05 19 | 99.17 46 | 98.79 91 | 95.47 180 | 99.89 20 | 97.95 62 | 99.91 19 | 99.75 24 |
|
| OurMVSNet-221017-0 | | | 98.61 19 | 98.61 27 | 98.63 47 | 99.77 5 | 96.35 68 | 99.17 7 | 99.05 107 | 98.05 60 | 99.61 16 | 99.52 12 | 93.72 246 | 99.88 22 | 98.72 38 | 99.88 28 | 99.65 39 |
|
| lecture | | | 98.59 20 | 98.60 28 | 98.55 52 | 99.48 37 | 96.38 65 | 98.08 62 | 99.09 92 | 98.46 41 | 98.68 102 | 98.73 101 | 97.88 27 | 99.80 50 | 97.43 87 | 99.59 136 | 99.48 101 |
|
| mvs5depth | | | 98.06 58 | 98.58 29 | 96.51 239 | 98.97 132 | 89.65 316 | 99.43 4 | 99.81 2 | 99.30 9 | 98.36 138 | 99.86 2 | 93.15 259 | 99.88 22 | 98.50 44 | 99.84 49 | 99.99 1 |
|
| test_fmvsmconf0.1_n | | | 98.41 34 | 98.54 30 | 98.03 105 | 99.16 93 | 94.61 149 | 96.18 212 | 99.73 5 | 95.05 235 | 99.60 17 | 99.34 29 | 98.68 8 | 99.72 110 | 99.21 12 | 99.85 46 | 99.76 21 |
|
| mmtdpeth | | | 98.33 36 | 98.53 31 | 97.71 125 | 99.07 111 | 93.44 199 | 98.80 15 | 99.78 4 | 99.10 15 | 96.61 301 | 99.63 10 | 95.42 183 | 99.73 100 | 98.53 43 | 99.86 35 | 99.95 2 |
|
| test_fmvsmvis_n_1920 | | | 98.08 55 | 98.47 32 | 96.93 200 | 99.03 121 | 93.29 205 | 96.32 199 | 99.65 12 | 95.59 206 | 99.71 7 | 99.01 67 | 97.66 38 | 99.60 198 | 99.44 5 | 99.83 54 | 97.90 390 |
|
| fmvsm_l_conf0.5_n_3 | | | 98.29 41 | 98.46 33 | 97.79 119 | 98.90 147 | 94.05 174 | 96.06 224 | 99.63 16 | 96.07 171 | 99.37 32 | 98.93 78 | 98.29 16 | 99.68 150 | 99.11 22 | 99.79 64 | 99.65 39 |
|
| VPA-MVSNet | | | 98.27 42 | 98.46 33 | 97.70 127 | 99.06 113 | 93.80 183 | 97.76 86 | 99.00 132 | 98.40 44 | 99.07 56 | 98.98 71 | 96.89 96 | 99.75 84 | 97.19 99 | 99.79 64 | 99.55 70 |
|
| CP-MVSNet | | | 98.42 33 | 98.46 33 | 98.30 75 | 99.46 40 | 95.22 130 | 98.27 48 | 98.84 177 | 99.05 19 | 99.01 60 | 98.65 119 | 95.37 185 | 99.90 17 | 97.57 81 | 99.91 19 | 99.77 15 |
|
| testf1 | | | 98.57 21 | 98.45 36 | 98.93 21 | 99.79 3 | 98.78 2 | 97.69 96 | 99.42 34 | 97.69 74 | 98.92 71 | 98.77 95 | 97.80 30 | 99.25 343 | 96.27 143 | 99.69 97 | 98.76 292 |
|
| APD_test2 | | | 98.57 21 | 98.45 36 | 98.93 21 | 99.79 3 | 98.78 2 | 97.69 96 | 99.42 34 | 97.69 74 | 98.92 71 | 98.77 95 | 97.80 30 | 99.25 343 | 96.27 143 | 99.69 97 | 98.76 292 |
|
| MIMVSNet1 | | | 98.51 28 | 98.45 36 | 98.67 43 | 99.72 8 | 96.71 53 | 98.76 16 | 98.89 157 | 98.49 40 | 99.38 31 | 99.14 52 | 95.44 182 | 99.84 33 | 96.47 128 | 99.80 62 | 99.47 105 |
|
| test_fmvsmconf_n | | | 98.30 40 | 98.41 39 | 97.99 108 | 98.94 136 | 94.60 150 | 96.00 232 | 99.64 15 | 94.99 240 | 99.43 27 | 99.18 45 | 98.51 12 | 99.71 126 | 99.13 20 | 99.84 49 | 99.67 34 |
|
| fmvsm_l_conf0.5_n_9 | | | 97.92 79 | 98.37 40 | 96.57 233 | 98.94 136 | 90.54 288 | 95.39 285 | 99.58 18 | 96.82 119 | 99.56 18 | 98.77 95 | 97.23 65 | 99.61 195 | 99.17 17 | 99.86 35 | 99.57 58 |
|
| Elysia | | | 98.19 46 | 98.37 40 | 97.66 131 | 99.28 64 | 93.52 195 | 97.35 123 | 98.90 153 | 98.63 32 | 99.45 24 | 98.32 165 | 94.31 228 | 99.91 13 | 99.19 14 | 99.88 28 | 99.54 72 |
|
| StellarMVS | | | 98.19 46 | 98.37 40 | 97.66 131 | 99.28 64 | 93.52 195 | 97.35 123 | 98.90 153 | 98.63 32 | 99.45 24 | 98.32 165 | 94.31 228 | 99.91 13 | 99.19 14 | 99.88 28 | 99.54 72 |
|
| fmvsm_s_conf0.5_n_3 | | | 97.88 88 | 98.37 40 | 96.41 255 | 98.73 174 | 89.82 311 | 95.94 242 | 99.49 29 | 96.81 120 | 99.09 53 | 99.03 65 | 97.09 71 | 99.65 171 | 99.37 8 | 99.76 70 | 99.76 21 |
|
| FC-MVSNet-test | | | 98.16 48 | 98.37 40 | 97.56 138 | 99.49 36 | 93.10 210 | 98.35 39 | 99.21 56 | 98.43 42 | 98.89 74 | 98.83 90 | 94.30 230 | 99.81 43 | 97.87 65 | 99.91 19 | 99.77 15 |
|
| fmvsm_s_conf0.5_n_11 | | | 97.90 85 | 98.34 45 | 96.60 228 | 98.75 172 | 90.50 292 | 96.28 201 | 99.56 22 | 97.05 106 | 99.15 48 | 99.11 54 | 96.31 137 | 99.69 143 | 98.97 29 | 99.84 49 | 99.62 44 |
|
| Vis-MVSNet |  | | 98.27 42 | 98.34 45 | 98.07 98 | 99.33 60 | 95.21 132 | 98.04 64 | 99.46 30 | 97.32 98 | 97.82 214 | 99.11 54 | 96.75 107 | 99.86 27 | 97.84 67 | 99.36 229 | 99.15 201 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| reproduce_model | | | 98.54 25 | 98.33 47 | 99.15 3 | 99.06 113 | 98.04 11 | 97.04 142 | 99.09 92 | 98.42 43 | 99.03 57 | 98.71 109 | 96.93 89 | 99.83 35 | 97.09 103 | 99.63 113 | 99.56 66 |
|
| fmvsm_s_conf0.5_n_9 | | | 97.98 64 | 98.32 48 | 96.96 197 | 98.92 142 | 91.45 263 | 95.87 247 | 99.53 26 | 97.44 85 | 99.56 18 | 99.05 62 | 95.34 186 | 99.67 160 | 99.52 2 | 99.70 95 | 99.77 15 |
|
| ACMH+ | | 93.58 10 | 98.23 45 | 98.31 49 | 97.98 109 | 99.39 50 | 95.22 130 | 97.55 108 | 99.20 58 | 98.21 54 | 99.25 41 | 98.51 138 | 98.21 18 | 99.40 282 | 94.79 253 | 99.72 88 | 99.32 158 |
|
| Gipuma |  | | 98.07 57 | 98.31 49 | 97.36 163 | 99.76 7 | 96.28 72 | 98.51 30 | 99.10 87 | 98.76 29 | 96.79 284 | 99.34 29 | 96.61 116 | 98.82 404 | 96.38 135 | 99.50 182 | 96.98 433 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| TranMVSNet+NR-MVSNet | | | 98.33 36 | 98.30 51 | 98.43 62 | 99.07 111 | 95.87 89 | 96.73 170 | 99.05 107 | 98.67 30 | 98.84 82 | 98.45 145 | 97.58 44 | 99.88 22 | 96.45 131 | 99.86 35 | 99.54 72 |
|
| test_fmvsm_n_1920 | | | 98.08 55 | 98.29 52 | 97.43 156 | 98.88 149 | 93.95 178 | 96.17 216 | 99.57 20 | 95.66 201 | 99.52 20 | 98.71 109 | 97.04 78 | 99.64 177 | 99.21 12 | 99.87 33 | 98.69 302 |
|
| reproduce-ours | | | 98.48 29 | 98.27 53 | 99.12 4 | 98.99 128 | 98.02 12 | 96.81 158 | 99.02 120 | 98.29 50 | 98.97 66 | 98.61 122 | 97.27 58 | 99.82 38 | 96.86 114 | 99.61 126 | 99.51 84 |
|
| our_new_method | | | 98.48 29 | 98.27 53 | 99.12 4 | 98.99 128 | 98.02 12 | 96.81 158 | 99.02 120 | 98.29 50 | 98.97 66 | 98.61 122 | 97.27 58 | 99.82 38 | 96.86 114 | 99.61 126 | 99.51 84 |
|
| SDMVSNet | | | 97.97 65 | 98.26 55 | 97.11 182 | 99.41 46 | 92.21 236 | 96.92 149 | 98.60 236 | 98.58 36 | 98.78 87 | 99.39 21 | 97.80 30 | 99.62 187 | 94.98 246 | 99.86 35 | 99.52 80 |
|
| fmvsm_s_conf0.1_n_2 | | | 97.68 113 | 98.18 56 | 96.20 273 | 99.06 113 | 89.08 335 | 95.51 275 | 99.72 6 | 96.06 172 | 99.48 21 | 99.24 36 | 95.18 194 | 99.60 198 | 99.45 4 | 99.88 28 | 99.94 3 |
|
| HPM-MVS_fast | | | 98.32 38 | 98.13 57 | 98.88 26 | 99.54 28 | 97.48 33 | 98.35 39 | 99.03 116 | 95.88 189 | 97.88 207 | 98.22 190 | 98.15 20 | 99.74 94 | 96.50 127 | 99.62 116 | 99.42 127 |
|
| fmvsm_s_conf0.5_n_8 | | | 97.66 116 | 98.12 58 | 96.27 267 | 98.79 164 | 89.43 323 | 95.76 255 | 99.42 34 | 97.49 83 | 99.16 47 | 99.04 63 | 94.56 220 | 99.69 143 | 99.18 16 | 99.73 83 | 99.70 31 |
|
| sd_testset | | | 97.97 65 | 98.12 58 | 97.51 143 | 99.41 46 | 93.44 199 | 97.96 68 | 98.25 279 | 98.58 36 | 98.78 87 | 99.39 21 | 98.21 18 | 99.56 211 | 92.65 329 | 99.86 35 | 99.52 80 |
|
| fmvsm_s_conf0.5_n_10 | | | 97.74 105 | 98.11 60 | 96.62 225 | 98.72 177 | 90.95 278 | 95.99 235 | 99.50 28 | 96.22 154 | 99.20 44 | 98.93 78 | 95.13 198 | 99.77 69 | 99.49 3 | 99.76 70 | 99.15 201 |
|
| casdiffmvs_mvg |  | | 97.83 94 | 98.11 60 | 97.00 196 | 98.57 209 | 92.10 244 | 95.97 238 | 99.18 62 | 97.67 77 | 99.00 62 | 98.48 143 | 97.64 39 | 99.50 230 | 96.96 110 | 99.54 160 | 99.40 134 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| COLMAP_ROB |  | 94.48 6 | 98.25 44 | 98.11 60 | 98.64 46 | 99.21 85 | 97.35 38 | 97.96 68 | 99.16 67 | 98.34 46 | 98.78 87 | 98.52 136 | 97.32 55 | 99.45 260 | 94.08 283 | 99.67 104 | 99.13 209 |
| Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
| FMVSNet1 | | | 97.95 71 | 98.08 63 | 97.56 138 | 99.14 103 | 93.67 188 | 98.23 50 | 98.66 228 | 97.41 91 | 99.00 62 | 99.19 41 | 95.47 180 | 99.73 100 | 95.83 170 | 99.76 70 | 99.30 163 |
|
| fmvsm_s_conf0.5_n_2 | | | 97.59 126 | 98.07 64 | 96.17 277 | 98.78 168 | 89.10 334 | 95.33 293 | 99.55 24 | 95.96 181 | 99.41 30 | 99.10 56 | 95.18 194 | 99.59 200 | 99.43 6 | 99.86 35 | 99.81 10 |
|
| KD-MVS_self_test | | | 97.86 92 | 98.07 64 | 97.25 173 | 99.22 78 | 92.81 217 | 97.55 108 | 98.94 148 | 97.10 105 | 98.85 80 | 98.88 87 | 95.03 201 | 99.67 160 | 97.39 90 | 99.65 109 | 99.26 176 |
|
| FIs | | | 97.93 78 | 98.07 64 | 97.48 151 | 99.38 52 | 92.95 214 | 98.03 66 | 99.11 82 | 98.04 61 | 98.62 105 | 98.66 115 | 93.75 245 | 99.78 58 | 97.23 94 | 99.84 49 | 99.73 26 |
|
| v8 | | | 97.60 123 | 98.06 67 | 96.23 270 | 98.71 181 | 89.44 322 | 97.43 119 | 98.82 192 | 97.29 100 | 98.74 94 | 99.10 56 | 93.86 240 | 99.68 150 | 98.61 40 | 99.94 8 | 99.56 66 |
|
| Anonymous20240529 | | | 97.96 67 | 98.04 68 | 97.71 125 | 98.69 186 | 94.28 167 | 97.86 78 | 98.31 276 | 98.79 28 | 99.23 42 | 98.86 89 | 95.76 167 | 99.61 195 | 95.49 190 | 99.36 229 | 99.23 185 |
|
| APDe-MVS |  | | 98.14 49 | 98.03 69 | 98.47 60 | 98.72 177 | 96.04 81 | 98.07 63 | 99.10 87 | 95.96 181 | 98.59 110 | 98.69 112 | 96.94 87 | 99.81 43 | 96.64 117 | 99.58 141 | 99.57 58 |
| Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition |
| KinetiMVS | | | 97.82 97 | 98.02 70 | 97.24 175 | 99.24 72 | 92.32 231 | 96.92 149 | 98.38 265 | 98.56 39 | 99.03 57 | 98.33 162 | 93.22 257 | 99.83 35 | 98.74 35 | 99.71 91 | 99.57 58 |
|
| fmvsm_s_conf0.1_n | | | 97.73 106 | 98.02 70 | 96.85 208 | 99.09 108 | 91.43 265 | 96.37 195 | 99.11 82 | 94.19 278 | 99.01 60 | 99.25 35 | 96.30 139 | 99.38 295 | 99.00 26 | 99.88 28 | 99.73 26 |
|
| fmvsm_s_conf0.1_n_a | | | 97.80 100 | 98.01 72 | 97.18 177 | 99.17 92 | 92.51 225 | 96.57 176 | 99.15 73 | 93.68 298 | 98.89 74 | 99.30 32 | 96.42 132 | 99.37 301 | 99.03 25 | 99.83 54 | 99.66 36 |
|
| CS-MVS | | | 98.09 54 | 98.01 72 | 98.32 72 | 98.45 232 | 96.69 55 | 98.52 29 | 99.69 8 | 98.07 59 | 96.07 335 | 97.19 307 | 96.88 98 | 99.86 27 | 97.50 84 | 99.73 83 | 98.41 333 |
|
| dcpmvs_2 | | | 97.12 171 | 97.99 74 | 94.51 379 | 99.11 105 | 84.00 442 | 97.75 87 | 99.65 12 | 97.38 94 | 99.14 49 | 98.42 149 | 95.16 196 | 99.96 2 | 95.52 189 | 99.78 68 | 99.58 50 |
|
| MVSMamba_PlusPlus | | | 97.43 146 | 97.98 75 | 95.78 299 | 98.88 149 | 89.70 313 | 98.03 66 | 98.85 173 | 99.18 13 | 96.84 283 | 99.12 53 | 93.04 263 | 99.91 13 | 98.38 47 | 99.55 154 | 97.73 404 |
|
| E6new | | | 97.59 126 | 97.97 76 | 96.45 244 | 99.01 123 | 90.45 294 | 96.50 181 | 99.23 51 | 96.20 155 | 98.27 152 | 98.72 102 | 97.49 46 | 99.47 245 | 96.64 117 | 99.62 116 | 99.42 127 |
|
| E6 | | | 97.59 126 | 97.97 76 | 96.45 244 | 99.01 123 | 90.45 294 | 96.50 181 | 99.23 51 | 96.20 155 | 98.27 152 | 98.72 102 | 97.49 46 | 99.47 245 | 96.64 117 | 99.62 116 | 99.42 127 |
|
| FE-MVSNET2 | | | 97.69 110 | 97.97 76 | 96.85 208 | 99.19 89 | 91.46 262 | 97.04 142 | 99.11 82 | 95.85 192 | 98.73 96 | 99.02 66 | 96.66 110 | 99.68 150 | 96.31 140 | 99.86 35 | 99.40 134 |
|
| tfpnnormal | | | 97.72 108 | 97.97 76 | 96.94 199 | 99.26 68 | 92.23 235 | 97.83 81 | 98.45 252 | 98.25 52 | 99.13 50 | 98.66 115 | 96.65 113 | 99.69 143 | 93.92 294 | 99.62 116 | 98.91 262 |
|
| v10 | | | 97.55 132 | 97.97 76 | 96.31 265 | 98.60 203 | 89.64 317 | 97.44 117 | 99.02 120 | 96.60 128 | 98.72 97 | 99.16 49 | 93.48 252 | 99.72 110 | 98.76 34 | 99.92 15 | 99.58 50 |
|
| test_0402 | | | 97.84 93 | 97.97 76 | 97.47 152 | 99.19 89 | 94.07 172 | 96.71 171 | 98.73 210 | 98.66 31 | 98.56 113 | 98.41 151 | 96.84 102 | 99.69 143 | 94.82 251 | 99.81 58 | 98.64 306 |
|
| E5new | | | 97.59 126 | 97.96 82 | 96.45 244 | 99.01 123 | 90.45 294 | 96.50 181 | 99.23 51 | 96.19 159 | 98.27 152 | 98.72 102 | 97.49 46 | 99.47 245 | 96.64 117 | 99.62 116 | 99.42 127 |
|
| E5 | | | 97.59 126 | 97.96 82 | 96.45 244 | 99.01 123 | 90.45 294 | 96.50 181 | 99.23 51 | 96.19 159 | 98.27 152 | 98.72 102 | 97.49 46 | 99.47 245 | 96.64 117 | 99.62 116 | 99.42 127 |
|
| EC-MVSNet | | | 97.90 85 | 97.94 84 | 97.79 119 | 98.66 189 | 95.14 133 | 98.31 43 | 99.66 11 | 97.57 78 | 95.95 339 | 97.01 326 | 96.99 82 | 99.82 38 | 97.66 78 | 99.64 111 | 98.39 336 |
|
| DVP-MVS++ | | | 97.96 67 | 97.90 85 | 98.12 96 | 97.75 331 | 95.40 112 | 99.03 8 | 98.89 157 | 96.62 126 | 98.62 105 | 98.30 173 | 96.97 85 | 99.75 84 | 95.70 173 | 99.25 259 | 99.21 189 |
|
| SED-MVS | | | 97.94 75 | 97.90 85 | 98.07 98 | 99.22 78 | 95.35 117 | 96.79 162 | 98.83 184 | 96.11 166 | 99.08 54 | 98.24 185 | 97.87 28 | 99.72 110 | 95.44 199 | 99.51 178 | 99.14 207 |
|
| APD-MVS_3200maxsize | | | 98.13 52 | 97.90 85 | 98.79 32 | 98.79 164 | 97.31 39 | 97.55 108 | 98.92 151 | 97.72 71 | 98.25 160 | 98.13 201 | 97.10 69 | 99.75 84 | 95.44 199 | 99.24 262 | 99.32 158 |
|
| fmvsm_s_conf0.5_n | | | 97.62 121 | 97.89 88 | 96.80 214 | 98.79 164 | 91.44 264 | 96.14 218 | 99.06 101 | 94.19 278 | 98.82 84 | 98.98 71 | 96.22 144 | 99.38 295 | 98.98 28 | 99.86 35 | 99.58 50 |
|
| DP-MVS | | | 97.87 90 | 97.89 88 | 97.81 118 | 98.62 201 | 94.82 141 | 97.13 137 | 98.79 198 | 98.98 23 | 98.74 94 | 98.49 139 | 95.80 166 | 99.49 236 | 95.04 234 | 99.44 201 | 99.11 220 |
|
| casdiffseed414692147 | | | 97.67 115 | 97.88 90 | 97.03 193 | 98.82 157 | 92.32 231 | 96.55 178 | 99.17 65 | 96.99 107 | 98.01 190 | 98.67 114 | 97.64 39 | 99.38 295 | 95.45 198 | 99.66 107 | 99.40 134 |
|
| RE-MVS-def | | | | 97.88 90 | | 98.81 158 | 98.05 9 | 97.55 108 | 98.86 169 | 97.77 66 | 98.20 164 | 98.07 212 | 96.94 87 | | 95.49 190 | 99.20 264 | 99.26 176 |
|
| MED-MVS | | | 97.95 71 | 97.87 92 | 98.17 87 | 99.36 54 | 95.35 117 | 97.75 87 | 99.30 41 | 96.16 164 | 98.88 76 | 97.54 274 | 96.99 82 | 99.73 100 | 95.36 207 | 99.53 164 | 99.44 121 |
|
| TestfortrainingZip a | | | 97.99 63 | 97.86 93 | 98.38 67 | 99.36 54 | 95.77 93 | 97.75 87 | 99.30 41 | 94.02 286 | 98.88 76 | 97.54 274 | 96.99 82 | 99.73 100 | 97.40 88 | 99.53 164 | 99.65 39 |
|
| NR-MVSNet | | | 97.96 67 | 97.86 93 | 98.26 78 | 98.73 174 | 95.54 104 | 98.14 58 | 98.73 210 | 97.79 65 | 99.42 28 | 97.83 244 | 94.40 226 | 99.78 58 | 95.91 164 | 99.76 70 | 99.46 107 |
|
| SR-MVS-dyc-post | | | 98.14 49 | 97.84 95 | 99.02 9 | 98.81 158 | 98.05 9 | 97.55 108 | 98.86 169 | 97.77 66 | 98.20 164 | 98.07 212 | 96.60 118 | 99.76 76 | 95.49 190 | 99.20 264 | 99.26 176 |
|
| SPE-MVS-test | | | 97.91 83 | 97.84 95 | 98.14 94 | 98.52 216 | 96.03 84 | 98.38 38 | 99.67 9 | 98.11 57 | 95.50 363 | 96.92 333 | 96.81 104 | 99.87 25 | 96.87 113 | 99.76 70 | 98.51 325 |
|
| MTAPA | | | 98.14 49 | 97.84 95 | 99.06 6 | 99.44 42 | 97.90 15 | 97.25 128 | 98.73 210 | 97.69 74 | 97.90 205 | 97.96 229 | 95.81 165 | 99.82 38 | 96.13 149 | 99.61 126 | 99.45 111 |
|
| fmvsm_s_conf0.5_n_5 | | | 97.63 120 | 97.83 98 | 97.04 191 | 98.77 170 | 92.33 229 | 95.63 270 | 99.58 18 | 93.53 302 | 99.10 52 | 98.66 115 | 96.44 130 | 99.65 171 | 99.12 21 | 99.68 101 | 99.12 215 |
|
| fmvsm_s_conf0.5_n_a | | | 97.65 117 | 97.83 98 | 97.13 181 | 98.80 161 | 92.51 225 | 96.25 207 | 99.06 101 | 93.67 299 | 98.64 103 | 99.00 68 | 96.23 143 | 99.36 305 | 98.99 27 | 99.80 62 | 99.53 77 |
|
| HPM-MVS |  | | 98.11 53 | 97.83 98 | 98.92 24 | 99.42 45 | 97.46 34 | 98.57 23 | 99.05 107 | 95.43 218 | 97.41 239 | 97.50 282 | 97.98 23 | 99.79 53 | 95.58 187 | 99.57 144 | 99.50 87 |
| Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
| fmvsm_l_conf0.5_n | | | 97.68 113 | 97.81 101 | 97.27 170 | 98.92 142 | 92.71 222 | 95.89 246 | 99.41 37 | 93.36 309 | 99.00 62 | 98.44 147 | 96.46 129 | 99.65 171 | 99.09 23 | 99.76 70 | 99.45 111 |
|
| casdiffmvs |  | | 97.50 137 | 97.81 101 | 96.56 235 | 98.51 218 | 91.04 272 | 95.83 250 | 99.09 92 | 97.23 101 | 98.33 145 | 98.30 173 | 97.03 79 | 99.37 301 | 96.58 125 | 99.38 224 | 99.28 171 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| fmvsm_s_conf0.5_n_6 | | | 97.45 142 | 97.79 103 | 96.44 248 | 98.58 207 | 90.31 300 | 95.77 254 | 99.33 38 | 94.52 261 | 98.85 80 | 98.44 147 | 95.68 170 | 99.62 187 | 99.15 19 | 99.81 58 | 99.38 143 |
|
| Baseline_NR-MVSNet | | | 97.72 108 | 97.79 103 | 97.50 147 | 99.56 22 | 93.29 205 | 95.44 279 | 98.86 169 | 98.20 55 | 98.37 135 | 99.24 36 | 94.69 211 | 99.55 216 | 95.98 159 | 99.79 64 | 99.65 39 |
|
| EG-PatchMatch MVS | | | 97.69 110 | 97.79 103 | 97.40 160 | 99.06 113 | 93.52 195 | 95.96 240 | 98.97 142 | 94.55 260 | 98.82 84 | 98.76 99 | 97.31 56 | 99.29 331 | 97.20 98 | 99.44 201 | 99.38 143 |
|
| ACMM | | 93.33 11 | 98.05 59 | 97.79 103 | 98.85 27 | 99.15 96 | 97.55 29 | 96.68 173 | 98.83 184 | 95.21 225 | 98.36 138 | 98.13 201 | 98.13 22 | 99.62 187 | 96.04 153 | 99.54 160 | 99.39 141 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| baseline | | | 97.44 144 | 97.78 107 | 96.43 250 | 98.52 216 | 90.75 283 | 96.84 155 | 99.03 116 | 96.51 136 | 97.86 211 | 98.02 222 | 96.67 109 | 99.36 305 | 97.09 103 | 99.47 192 | 99.19 193 |
|
| fmvsm_s_conf0.5_n_4 | | | 97.43 146 | 97.77 108 | 96.39 259 | 98.48 227 | 89.89 309 | 95.65 265 | 99.26 48 | 94.73 250 | 98.72 97 | 98.58 128 | 95.58 176 | 99.57 209 | 99.28 9 | 99.67 104 | 99.73 26 |
|
| fmvsm_l_conf0.5_n_a | | | 97.60 123 | 97.76 109 | 97.11 182 | 98.92 142 | 92.28 233 | 95.83 250 | 99.32 39 | 93.22 315 | 98.91 73 | 98.49 139 | 96.31 137 | 99.64 177 | 99.07 24 | 99.76 70 | 99.40 134 |
|
| SteuartSystems-ACMMP | | | 98.02 61 | 97.76 109 | 98.79 32 | 99.43 43 | 97.21 44 | 97.15 134 | 98.90 153 | 96.58 132 | 98.08 180 | 97.87 240 | 97.02 80 | 99.76 76 | 95.25 215 | 99.59 136 | 99.40 134 |
| Skip Steuart: Steuart Systems R&D Blog. |
| SSM_0404 | | | 97.47 140 | 97.75 111 | 96.64 224 | 98.81 158 | 91.26 268 | 96.57 176 | 99.16 67 | 96.95 112 | 98.44 128 | 98.09 208 | 97.05 76 | 99.72 110 | 95.21 218 | 99.44 201 | 98.95 251 |
|
| ACMMP |  | | 98.05 59 | 97.75 111 | 98.93 21 | 99.23 75 | 97.60 25 | 98.09 61 | 98.96 143 | 95.75 199 | 97.91 204 | 98.06 217 | 96.89 96 | 99.76 76 | 95.32 212 | 99.57 144 | 99.43 125 |
| 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 |
| GeoE | | | 97.75 104 | 97.70 113 | 97.89 113 | 98.88 149 | 94.53 153 | 97.10 138 | 98.98 139 | 95.75 199 | 97.62 221 | 97.59 270 | 97.61 43 | 99.77 69 | 96.34 138 | 99.44 201 | 99.36 151 |
|
| SD-MVS | | | 97.37 153 | 97.70 113 | 96.35 260 | 98.14 275 | 95.13 134 | 96.54 180 | 98.92 151 | 95.94 184 | 99.19 45 | 98.08 210 | 97.74 33 | 95.06 489 | 95.24 216 | 99.54 160 | 98.87 272 |
| 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 |
| XXY-MVS | | | 97.54 133 | 97.70 113 | 97.07 188 | 99.46 40 | 92.21 236 | 97.22 131 | 99.00 132 | 94.93 244 | 98.58 111 | 98.92 81 | 97.31 56 | 99.41 280 | 94.44 267 | 99.43 211 | 99.59 49 |
|
| DeepC-MVS | | 95.41 4 | 97.82 97 | 97.70 113 | 98.16 90 | 98.78 168 | 95.72 94 | 96.23 210 | 99.02 120 | 93.92 291 | 98.62 105 | 98.99 70 | 97.69 34 | 99.62 187 | 96.18 147 | 99.87 33 | 99.15 201 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| APD_test1 | | | 97.95 71 | 97.68 117 | 98.75 34 | 99.60 17 | 98.60 5 | 97.21 132 | 99.08 96 | 96.57 135 | 98.07 182 | 98.38 155 | 96.22 144 | 99.14 361 | 94.71 260 | 99.31 249 | 98.52 324 |
|
| SSM_0407 | | | 97.39 150 | 97.67 118 | 96.54 238 | 98.51 218 | 90.96 275 | 96.40 189 | 99.16 67 | 96.95 112 | 98.27 152 | 98.09 208 | 97.05 76 | 99.67 160 | 95.21 218 | 99.40 219 | 98.98 245 |
|
| LPG-MVS_test | | | 97.94 75 | 97.67 118 | 98.74 37 | 99.15 96 | 97.02 45 | 97.09 139 | 99.02 120 | 95.15 229 | 98.34 142 | 98.23 187 | 97.91 25 | 99.70 135 | 94.41 269 | 99.73 83 | 99.50 87 |
|
| SR-MVS | | | 98.00 62 | 97.66 120 | 99.01 11 | 98.77 170 | 97.93 14 | 97.38 121 | 98.83 184 | 97.32 98 | 98.06 183 | 97.85 241 | 96.65 113 | 99.77 69 | 95.00 239 | 99.11 280 | 99.32 158 |
|
| DVP-MVS |  | | 97.78 102 | 97.65 121 | 98.16 90 | 99.24 72 | 95.51 106 | 96.74 166 | 98.23 282 | 95.92 186 | 98.40 132 | 98.28 178 | 97.06 74 | 99.71 126 | 95.48 194 | 99.52 173 | 99.26 176 |
| 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 |
| UniMVSNet_NR-MVSNet | | | 97.83 94 | 97.65 121 | 98.37 68 | 98.72 177 | 95.78 91 | 95.66 263 | 99.02 120 | 98.11 57 | 98.31 148 | 97.69 263 | 94.65 215 | 99.85 30 | 97.02 108 | 99.71 91 | 99.48 101 |
|
| UniMVSNet (Re) | | | 97.83 94 | 97.65 121 | 98.35 71 | 98.80 161 | 95.86 90 | 95.92 244 | 99.04 115 | 97.51 82 | 98.22 163 | 97.81 249 | 94.68 213 | 99.78 58 | 97.14 101 | 99.75 80 | 99.41 133 |
|
| HFP-MVS | | | 97.94 75 | 97.64 124 | 98.83 28 | 99.15 96 | 97.50 32 | 97.59 105 | 98.84 177 | 96.05 173 | 97.49 230 | 97.54 274 | 97.07 73 | 99.70 135 | 95.61 184 | 99.46 195 | 99.30 163 |
|
| 3Dnovator | | 96.53 2 | 97.61 122 | 97.64 124 | 97.50 147 | 97.74 334 | 93.65 192 | 98.49 31 | 98.88 164 | 96.86 118 | 97.11 257 | 98.55 133 | 95.82 161 | 99.73 100 | 95.94 161 | 99.42 214 | 99.13 209 |
|
| ACMMP_NAP | | | 97.89 87 | 97.63 126 | 98.67 43 | 99.35 58 | 96.84 50 | 96.36 196 | 98.79 198 | 95.07 233 | 97.88 207 | 98.35 159 | 97.24 64 | 99.72 110 | 96.05 152 | 99.58 141 | 99.45 111 |
|
| XVS | | | 97.96 67 | 97.63 126 | 98.94 18 | 99.15 96 | 97.66 22 | 97.77 84 | 98.83 184 | 97.42 87 | 96.32 318 | 97.64 266 | 96.49 125 | 99.72 110 | 95.66 178 | 99.37 225 | 99.45 111 |
|
| viewdifsd2359ckpt11 | | | 97.13 168 | 97.62 128 | 95.67 309 | 98.64 190 | 88.36 355 | 94.84 332 | 98.95 145 | 96.24 151 | 98.70 99 | 98.61 122 | 96.66 110 | 99.29 331 | 96.46 129 | 99.45 198 | 99.36 151 |
|
| viewmsd2359difaftdt | | | 97.13 168 | 97.62 128 | 95.67 309 | 98.64 190 | 88.36 355 | 94.84 332 | 98.95 145 | 96.24 151 | 98.70 99 | 98.61 122 | 96.66 110 | 99.29 331 | 96.46 129 | 99.45 198 | 99.36 151 |
|
| ZNCC-MVS | | | 97.92 79 | 97.62 128 | 98.83 28 | 99.32 62 | 97.24 42 | 97.45 116 | 98.84 177 | 95.76 197 | 96.93 276 | 97.43 286 | 97.26 62 | 99.79 53 | 96.06 150 | 99.53 164 | 99.45 111 |
|
| ACMMPR | | | 97.95 71 | 97.62 128 | 98.94 18 | 99.20 87 | 97.56 28 | 97.59 105 | 98.83 184 | 96.05 173 | 97.46 236 | 97.63 267 | 96.77 106 | 99.76 76 | 95.61 184 | 99.46 195 | 99.49 95 |
|
| DU-MVS | | | 97.79 101 | 97.60 132 | 98.36 70 | 98.73 174 | 95.78 91 | 95.65 265 | 98.87 166 | 97.57 78 | 98.31 148 | 97.83 244 | 94.69 211 | 99.85 30 | 97.02 108 | 99.71 91 | 99.46 107 |
|
| region2R | | | 97.92 79 | 97.59 133 | 98.92 24 | 99.22 78 | 97.55 29 | 97.60 103 | 98.84 177 | 96.00 178 | 97.22 247 | 97.62 268 | 96.87 100 | 99.76 76 | 95.48 194 | 99.43 211 | 99.46 107 |
|
| 3Dnovator+ | | 96.13 3 | 97.73 106 | 97.59 133 | 98.15 93 | 98.11 279 | 95.60 100 | 98.04 64 | 98.70 219 | 98.13 56 | 96.93 276 | 98.45 145 | 95.30 189 | 99.62 187 | 95.64 180 | 98.96 298 | 99.24 183 |
|
| SixPastTwentyTwo | | | 97.49 138 | 97.57 135 | 97.26 172 | 99.56 22 | 92.33 229 | 98.28 46 | 96.97 369 | 98.30 49 | 99.45 24 | 99.35 28 | 88.43 347 | 99.89 20 | 98.01 59 | 99.76 70 | 99.54 72 |
|
| test_fmvs3 | | | 97.38 151 | 97.56 136 | 96.84 211 | 98.63 199 | 92.81 217 | 97.60 103 | 99.61 17 | 90.87 382 | 98.76 92 | 99.66 6 | 94.03 236 | 97.90 465 | 99.24 11 | 99.68 101 | 99.81 10 |
|
| tt0805 | | | 97.44 144 | 97.56 136 | 97.11 182 | 99.55 24 | 96.36 67 | 98.66 21 | 95.66 398 | 98.31 47 | 97.09 263 | 95.45 404 | 97.17 67 | 98.50 439 | 98.67 39 | 97.45 409 | 96.48 454 |
|
| CP-MVS | | | 97.92 79 | 97.56 136 | 98.99 13 | 98.99 128 | 97.82 18 | 97.93 73 | 98.96 143 | 96.11 166 | 96.89 279 | 97.45 284 | 96.85 101 | 99.78 58 | 95.19 220 | 99.63 113 | 99.38 143 |
|
| E4 | | | 97.28 159 | 97.55 139 | 96.46 243 | 98.86 153 | 90.53 290 | 95.28 301 | 99.18 62 | 95.82 195 | 98.01 190 | 98.59 127 | 96.78 105 | 99.46 252 | 95.86 169 | 99.56 147 | 99.38 143 |
|
| viewdifsd2359ckpt07 | | | 97.10 173 | 97.55 139 | 95.76 300 | 98.64 190 | 88.58 348 | 94.54 345 | 99.11 82 | 96.96 111 | 98.54 114 | 98.18 196 | 96.91 93 | 99.44 263 | 95.58 187 | 99.49 185 | 99.26 176 |
|
| mPP-MVS | | | 97.91 83 | 97.53 141 | 99.04 7 | 99.22 78 | 97.87 17 | 97.74 93 | 98.78 202 | 96.04 175 | 97.10 258 | 97.73 260 | 96.53 122 | 99.78 58 | 95.16 225 | 99.50 182 | 99.46 107 |
|
| viewmacassd2359aftdt | | | 97.25 161 | 97.52 142 | 96.43 250 | 98.83 155 | 90.49 293 | 95.45 278 | 99.18 62 | 95.44 216 | 97.98 197 | 98.47 144 | 96.90 95 | 99.37 301 | 95.93 162 | 99.55 154 | 99.43 125 |
|
| PGM-MVS | | | 97.88 88 | 97.52 142 | 98.96 16 | 99.20 87 | 97.62 24 | 97.09 139 | 99.06 101 | 95.45 214 | 97.55 225 | 97.94 232 | 97.11 68 | 99.78 58 | 94.77 256 | 99.46 195 | 99.48 101 |
|
| Anonymous20240521 | | | 97.07 174 | 97.51 144 | 95.76 300 | 99.35 58 | 88.18 364 | 97.78 83 | 98.40 262 | 97.11 104 | 98.34 142 | 99.04 63 | 89.58 332 | 99.79 53 | 98.09 54 | 99.93 11 | 99.30 163 |
|
| RPSCF | | | 97.87 90 | 97.51 144 | 98.95 17 | 99.15 96 | 98.43 6 | 97.56 107 | 99.06 101 | 96.19 159 | 98.48 122 | 98.70 111 | 94.72 209 | 99.24 347 | 94.37 272 | 99.33 244 | 99.17 197 |
|
| fmvsm_s_conf0.5_n_7 | | | 97.13 168 | 97.50 146 | 96.04 284 | 98.43 234 | 89.03 338 | 94.92 326 | 99.00 132 | 94.51 262 | 98.42 129 | 98.96 74 | 94.97 205 | 99.54 219 | 98.42 46 | 99.85 46 | 99.56 66 |
|
| LS3D | | | 97.77 103 | 97.50 146 | 98.57 50 | 96.24 411 | 97.58 27 | 98.45 34 | 98.85 173 | 98.58 36 | 97.51 228 | 97.94 232 | 95.74 168 | 99.63 182 | 95.19 220 | 98.97 295 | 98.51 325 |
|
| GST-MVS | | | 97.82 97 | 97.49 148 | 98.81 30 | 99.23 75 | 97.25 41 | 97.16 133 | 98.79 198 | 95.96 181 | 97.53 226 | 97.40 288 | 96.93 89 | 99.77 69 | 95.04 234 | 99.35 234 | 99.42 127 |
|
| VPNet | | | 97.26 160 | 97.49 148 | 96.59 230 | 99.47 39 | 90.58 285 | 96.27 203 | 98.53 245 | 97.77 66 | 98.46 125 | 98.41 151 | 94.59 217 | 99.68 150 | 94.61 262 | 99.29 252 | 99.52 80 |
|
| EI-MVSNet-UG-set | | | 97.32 157 | 97.40 150 | 97.09 186 | 97.34 375 | 92.01 248 | 95.33 293 | 97.65 334 | 97.74 69 | 98.30 150 | 98.14 199 | 95.04 200 | 99.69 143 | 97.55 82 | 99.52 173 | 99.58 50 |
|
| SF-MVS | | | 97.60 123 | 97.39 151 | 98.22 83 | 98.93 140 | 95.69 96 | 97.05 141 | 99.10 87 | 95.32 222 | 97.83 213 | 97.88 237 | 96.44 130 | 99.72 110 | 94.59 266 | 99.39 223 | 99.25 182 |
|
| EI-MVSNet-Vis-set | | | 97.32 157 | 97.39 151 | 97.11 182 | 97.36 372 | 92.08 245 | 95.34 292 | 97.65 334 | 97.74 69 | 98.29 151 | 98.11 206 | 95.05 199 | 99.68 150 | 97.50 84 | 99.50 182 | 99.56 66 |
|
| mamba_0408 | | | 97.17 166 | 97.38 153 | 96.55 237 | 98.51 218 | 90.96 275 | 95.19 306 | 99.06 101 | 96.60 128 | 98.27 152 | 97.78 251 | 96.58 119 | 99.72 110 | 95.04 234 | 99.40 219 | 98.98 245 |
|
| SSM_04072 | | | 97.14 167 | 97.38 153 | 96.42 252 | 98.51 218 | 90.96 275 | 95.19 306 | 99.06 101 | 96.60 128 | 98.27 152 | 97.78 251 | 96.58 119 | 99.31 323 | 95.04 234 | 99.40 219 | 98.98 245 |
|
| MP-MVS-pluss | | | 97.69 110 | 97.36 155 | 98.70 41 | 99.50 35 | 96.84 50 | 95.38 287 | 98.99 136 | 92.45 344 | 98.11 175 | 98.31 167 | 97.25 63 | 99.77 69 | 96.60 123 | 99.62 116 | 99.48 101 |
| MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
| DPE-MVS |  | | 97.64 118 | 97.35 156 | 98.50 56 | 98.85 154 | 96.18 74 | 95.21 305 | 98.99 136 | 95.84 193 | 98.78 87 | 98.08 210 | 96.84 102 | 99.81 43 | 93.98 291 | 99.57 144 | 99.52 80 |
| Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
| LCM-MVSNet-Re | | | 97.33 156 | 97.33 157 | 97.32 166 | 98.13 278 | 93.79 184 | 96.99 146 | 99.65 12 | 96.74 123 | 99.47 23 | 98.93 78 | 96.91 93 | 99.84 33 | 90.11 390 | 99.06 290 | 98.32 345 |
|
| ME-MVS | | | 97.53 136 | 97.32 158 | 98.16 90 | 98.70 183 | 95.35 117 | 96.04 227 | 98.60 236 | 96.16 164 | 97.99 192 | 97.54 274 | 95.94 153 | 99.70 135 | 95.36 207 | 99.53 164 | 99.44 121 |
|
| CSCG | | | 97.40 149 | 97.30 159 | 97.69 129 | 98.95 133 | 94.83 140 | 97.28 127 | 98.99 136 | 96.35 147 | 98.13 174 | 95.95 388 | 95.99 152 | 99.66 168 | 94.36 274 | 99.73 83 | 98.59 314 |
|
| balanced_conf03 | | | 96.88 190 | 97.29 160 | 95.63 312 | 97.66 344 | 89.47 321 | 97.95 70 | 98.89 157 | 95.94 184 | 97.77 217 | 98.55 133 | 92.23 289 | 99.68 150 | 97.05 107 | 99.61 126 | 97.73 404 |
|
| IterMVS-LS | | | 96.92 186 | 97.29 160 | 95.79 298 | 98.51 218 | 88.13 367 | 95.10 312 | 98.66 228 | 96.99 107 | 98.46 125 | 98.68 113 | 92.55 280 | 99.74 94 | 96.91 111 | 99.79 64 | 99.50 87 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| XVG-ACMP-BASELINE | | | 97.58 131 | 97.28 162 | 98.49 57 | 99.16 93 | 96.90 49 | 96.39 191 | 98.98 139 | 95.05 235 | 98.06 183 | 98.02 222 | 95.86 157 | 99.56 211 | 94.37 272 | 99.64 111 | 99.00 238 |
|
| usedtu_dtu_shiyan2 | | | 97.54 133 | 97.26 163 | 98.37 68 | 99.54 28 | 96.04 81 | 97.94 71 | 98.06 309 | 97.36 96 | 98.62 105 | 98.20 192 | 95.52 177 | 99.73 100 | 90.90 366 | 99.18 269 | 99.33 156 |
|
| OPM-MVS | | | 97.54 133 | 97.25 164 | 98.41 64 | 99.11 105 | 96.61 59 | 95.24 303 | 98.46 251 | 94.58 259 | 98.10 177 | 98.07 212 | 97.09 71 | 99.39 291 | 95.16 225 | 99.44 201 | 99.21 189 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| VDD-MVS | | | 97.37 153 | 97.25 164 | 97.74 123 | 98.69 186 | 94.50 156 | 97.04 142 | 95.61 402 | 98.59 35 | 98.51 117 | 98.72 102 | 92.54 282 | 99.58 203 | 96.02 155 | 99.49 185 | 99.12 215 |
|
| MGCFI-Net | | | 97.20 164 | 97.23 166 | 97.08 187 | 97.68 339 | 93.71 187 | 97.79 82 | 99.09 92 | 97.40 92 | 96.59 302 | 93.96 429 | 97.67 36 | 99.35 309 | 96.43 133 | 98.50 355 | 98.17 366 |
|
| TSAR-MVS + MP. | | | 97.42 148 | 97.23 166 | 98.00 107 | 99.38 52 | 95.00 137 | 97.63 102 | 98.20 286 | 93.00 328 | 98.16 170 | 98.06 217 | 95.89 156 | 99.72 110 | 95.67 177 | 99.10 283 | 99.28 171 |
| Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
| sasdasda | | | 97.23 162 | 97.21 168 | 97.30 167 | 97.65 346 | 94.39 158 | 97.84 79 | 99.05 107 | 97.42 87 | 96.68 293 | 93.85 431 | 97.63 41 | 99.33 314 | 96.29 141 | 98.47 356 | 98.18 364 |
|
| canonicalmvs | | | 97.23 162 | 97.21 168 | 97.30 167 | 97.65 346 | 94.39 158 | 97.84 79 | 99.05 107 | 97.42 87 | 96.68 293 | 93.85 431 | 97.63 41 | 99.33 314 | 96.29 141 | 98.47 356 | 98.18 364 |
|
| E2 | | | 96.97 182 | 97.19 170 | 96.33 261 | 98.64 190 | 90.34 298 | 95.07 316 | 99.12 79 | 95.00 238 | 97.66 219 | 98.31 167 | 96.19 146 | 99.43 266 | 95.35 210 | 99.35 234 | 99.23 185 |
|
| E3 | | | 96.97 182 | 97.19 170 | 96.33 261 | 98.64 190 | 90.34 298 | 95.07 316 | 99.12 79 | 95.00 238 | 97.66 219 | 98.31 167 | 96.19 146 | 99.43 266 | 95.35 210 | 99.35 234 | 99.23 185 |
|
| MP-MVS |  | | 97.64 118 | 97.18 172 | 99.00 12 | 99.32 62 | 97.77 20 | 97.49 114 | 98.73 210 | 96.27 148 | 95.59 359 | 97.75 256 | 96.30 139 | 99.78 58 | 93.70 306 | 99.48 190 | 99.45 111 |
| Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
| V42 | | | 97.04 175 | 97.16 173 | 96.68 223 | 98.59 205 | 91.05 271 | 96.33 198 | 98.36 268 | 94.60 256 | 97.99 192 | 98.30 173 | 93.32 254 | 99.62 187 | 97.40 88 | 99.53 164 | 99.38 143 |
|
| SMA-MVS |  | | 97.48 139 | 97.11 174 | 98.60 48 | 98.83 155 | 96.67 56 | 96.74 166 | 98.73 210 | 91.61 360 | 98.48 122 | 98.36 157 | 96.53 122 | 99.68 150 | 95.17 223 | 99.54 160 | 99.45 111 |
| 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 |
| PM-MVS | | | 97.36 155 | 97.10 175 | 98.14 94 | 98.91 145 | 96.77 52 | 96.20 211 | 98.63 234 | 93.82 292 | 98.54 114 | 98.33 162 | 93.98 237 | 99.05 377 | 95.99 158 | 99.45 198 | 98.61 313 |
|
| ACMP | | 92.54 13 | 97.47 140 | 97.10 175 | 98.55 52 | 99.04 120 | 96.70 54 | 96.24 209 | 98.89 157 | 93.71 295 | 97.97 198 | 97.75 256 | 97.44 50 | 99.63 182 | 93.22 320 | 99.70 95 | 99.32 158 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| v1144 | | | 96.84 193 | 97.08 177 | 96.13 281 | 98.42 236 | 89.28 326 | 95.41 283 | 98.67 225 | 94.21 276 | 97.97 198 | 98.31 167 | 93.06 262 | 99.65 171 | 98.06 57 | 99.62 116 | 99.45 111 |
|
| XVG-OURS-SEG-HR | | | 97.38 151 | 97.07 178 | 98.30 75 | 99.01 123 | 97.41 37 | 94.66 341 | 99.02 120 | 95.20 226 | 98.15 172 | 97.52 280 | 98.83 5 | 98.43 444 | 94.87 249 | 96.41 438 | 99.07 227 |
|
| v1192 | | | 96.83 196 | 97.06 179 | 96.15 280 | 98.28 250 | 89.29 325 | 95.36 288 | 98.77 203 | 93.73 294 | 98.11 175 | 98.34 161 | 93.02 267 | 99.67 160 | 98.35 48 | 99.58 141 | 99.50 87 |
|
| v2v482 | | | 96.78 200 | 97.06 179 | 95.95 291 | 98.57 209 | 88.77 345 | 95.36 288 | 98.26 278 | 95.18 228 | 97.85 212 | 98.23 187 | 92.58 277 | 99.63 182 | 97.80 69 | 99.69 97 | 99.45 111 |
|
| SSC-MVS | | | 95.92 254 | 97.03 181 | 92.58 437 | 99.28 64 | 78.39 475 | 96.68 173 | 95.12 414 | 98.90 25 | 99.11 51 | 98.66 115 | 91.36 306 | 99.68 150 | 95.00 239 | 99.16 272 | 99.67 34 |
|
| v1240 | | | 96.74 203 | 97.02 182 | 95.91 294 | 98.18 266 | 88.52 349 | 95.39 285 | 98.88 164 | 93.15 324 | 98.46 125 | 98.40 154 | 92.80 270 | 99.71 126 | 98.45 45 | 99.49 185 | 99.49 95 |
|
| test_vis3_rt | | | 97.04 175 | 96.98 183 | 97.23 176 | 98.44 233 | 95.88 88 | 96.82 157 | 99.67 9 | 90.30 391 | 99.27 39 | 99.33 31 | 94.04 235 | 96.03 486 | 97.14 101 | 97.83 386 | 99.78 14 |
|
| v148 | | | 96.58 217 | 96.97 184 | 95.42 328 | 98.63 199 | 87.57 380 | 95.09 313 | 97.90 316 | 95.91 188 | 98.24 161 | 97.96 229 | 93.42 253 | 99.39 291 | 96.04 153 | 99.52 173 | 99.29 170 |
|
| PMVS |  | 89.60 17 | 96.71 209 | 96.97 184 | 95.95 291 | 99.51 32 | 97.81 19 | 97.42 120 | 97.49 344 | 97.93 62 | 95.95 339 | 98.58 128 | 96.88 98 | 96.91 478 | 89.59 399 | 99.36 229 | 93.12 487 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| v1921920 | | | 96.72 207 | 96.96 186 | 95.99 286 | 98.21 260 | 88.79 344 | 95.42 281 | 98.79 198 | 93.22 315 | 98.19 168 | 98.26 183 | 92.68 273 | 99.70 135 | 98.34 49 | 99.55 154 | 99.49 95 |
|
| viewmanbaseed2359cas | | | 96.77 201 | 96.94 187 | 96.27 267 | 98.41 238 | 90.24 301 | 95.11 311 | 99.03 116 | 94.28 275 | 97.45 237 | 97.85 241 | 95.92 155 | 99.32 322 | 95.18 222 | 99.19 268 | 99.24 183 |
|
| patch_mono-2 | | | 96.59 214 | 96.93 188 | 95.55 322 | 98.88 149 | 87.12 390 | 94.47 347 | 99.30 41 | 94.12 281 | 96.65 299 | 98.41 151 | 94.98 204 | 99.87 25 | 95.81 172 | 99.78 68 | 99.66 36 |
|
| EI-MVSNet | | | 96.63 213 | 96.93 188 | 95.74 302 | 97.26 380 | 88.13 367 | 95.29 299 | 97.65 334 | 96.99 107 | 97.94 202 | 98.19 193 | 92.55 280 | 99.58 203 | 96.91 111 | 99.56 147 | 99.50 87 |
|
| MSP-MVS | | | 97.45 142 | 96.92 190 | 99.03 8 | 99.26 68 | 97.70 21 | 97.66 99 | 98.89 157 | 95.65 202 | 98.51 117 | 96.46 361 | 92.15 291 | 99.81 43 | 95.14 228 | 98.58 349 | 99.58 50 |
| 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 |
| AllTest | | | 97.20 164 | 96.92 190 | 98.06 100 | 99.08 109 | 96.16 75 | 97.14 136 | 99.16 67 | 94.35 272 | 97.78 215 | 98.07 212 | 95.84 158 | 99.12 365 | 91.41 352 | 99.42 214 | 98.91 262 |
|
| v144192 | | | 96.69 210 | 96.90 192 | 96.03 285 | 98.25 256 | 88.92 339 | 95.49 276 | 98.77 203 | 93.05 326 | 98.09 178 | 98.29 177 | 92.51 285 | 99.70 135 | 98.11 52 | 99.56 147 | 99.47 105 |
|
| viewcassd2359sk11 | | | 96.73 205 | 96.89 193 | 96.24 269 | 98.46 231 | 90.20 302 | 94.94 325 | 99.07 100 | 94.43 269 | 97.33 241 | 98.05 220 | 95.69 169 | 99.40 282 | 94.98 246 | 99.11 280 | 99.12 215 |
|
| IMVS_0407 | | | 96.35 232 | 96.88 194 | 94.74 366 | 97.83 310 | 86.11 406 | 96.25 207 | 98.82 192 | 94.48 263 | 97.57 223 | 97.14 310 | 96.08 149 | 99.33 314 | 95.00 239 | 98.78 322 | 98.78 281 |
|
| VDDNet | | | 96.98 181 | 96.84 195 | 97.41 159 | 99.40 49 | 93.26 207 | 97.94 71 | 95.31 410 | 99.26 11 | 98.39 134 | 99.18 45 | 87.85 357 | 99.62 187 | 95.13 230 | 99.09 284 | 99.35 155 |
|
| VNet | | | 96.84 193 | 96.83 196 | 96.88 206 | 98.06 281 | 92.02 247 | 96.35 197 | 97.57 343 | 97.70 73 | 97.88 207 | 97.80 250 | 92.40 287 | 99.54 219 | 94.73 258 | 98.96 298 | 99.08 225 |
|
| diffmvs_AUTHOR | | | 96.50 220 | 96.81 197 | 95.57 316 | 98.03 282 | 88.26 359 | 93.73 381 | 99.14 76 | 94.92 245 | 97.24 246 | 97.84 243 | 94.62 216 | 99.33 314 | 96.44 132 | 99.37 225 | 99.13 209 |
|
| WR-MVS | | | 96.90 188 | 96.81 197 | 97.16 178 | 98.56 211 | 92.20 239 | 94.33 350 | 98.12 301 | 97.34 97 | 98.20 164 | 97.33 299 | 92.81 269 | 99.75 84 | 94.79 253 | 99.81 58 | 99.54 72 |
|
| GBi-Net | | | 96.99 178 | 96.80 199 | 97.56 138 | 97.96 292 | 93.67 188 | 98.23 50 | 98.66 228 | 95.59 206 | 97.99 192 | 99.19 41 | 89.51 336 | 99.73 100 | 94.60 263 | 99.44 201 | 99.30 163 |
|
| test1 | | | 96.99 178 | 96.80 199 | 97.56 138 | 97.96 292 | 93.67 188 | 98.23 50 | 98.66 228 | 95.59 206 | 97.99 192 | 99.19 41 | 89.51 336 | 99.73 100 | 94.60 263 | 99.44 201 | 99.30 163 |
|
| MVS_Test | | | 96.27 236 | 96.79 201 | 94.73 367 | 96.94 394 | 86.63 398 | 96.18 212 | 98.33 272 | 94.94 242 | 96.07 335 | 98.28 178 | 95.25 191 | 99.26 340 | 97.21 96 | 97.90 383 | 98.30 350 |
|
| IMVS_0403 | | | 96.27 236 | 96.77 202 | 94.76 364 | 97.83 310 | 86.11 406 | 96.00 232 | 98.82 192 | 94.48 263 | 97.49 230 | 97.14 310 | 95.38 184 | 99.40 282 | 95.00 239 | 98.78 322 | 98.78 281 |
|
| XVG-OURS | | | 97.12 171 | 96.74 203 | 98.26 78 | 98.99 128 | 97.45 35 | 93.82 377 | 99.05 107 | 95.19 227 | 98.32 146 | 97.70 262 | 95.22 192 | 98.41 445 | 94.27 276 | 98.13 373 | 98.93 258 |
|
| MSLP-MVS++ | | | 96.42 229 | 96.71 204 | 95.57 316 | 97.82 314 | 90.56 287 | 95.71 257 | 98.84 177 | 94.72 251 | 96.71 292 | 97.39 292 | 94.91 207 | 98.10 462 | 95.28 213 | 99.02 292 | 98.05 379 |
|
| 9.14 | | | | 96.69 205 | | 98.53 215 | | 96.02 230 | 98.98 139 | 93.23 314 | 97.18 252 | 97.46 283 | 96.47 127 | 99.62 187 | 92.99 324 | 99.32 246 | |
|
| IS-MVSNet | | | 96.93 185 | 96.68 206 | 97.70 127 | 99.25 71 | 94.00 176 | 98.57 23 | 96.74 378 | 98.36 45 | 98.14 173 | 97.98 228 | 88.23 350 | 99.71 126 | 93.10 323 | 99.72 88 | 99.38 143 |
|
| FMVSNet2 | | | 96.72 207 | 96.67 207 | 96.87 207 | 97.96 292 | 91.88 251 | 97.15 134 | 98.06 309 | 95.59 206 | 98.50 119 | 98.62 121 | 89.51 336 | 99.65 171 | 94.99 245 | 99.60 133 | 99.07 227 |
|
| FE-MVSNET | | | 96.59 214 | 96.65 208 | 96.41 255 | 98.94 136 | 90.51 291 | 96.07 222 | 99.05 107 | 92.94 334 | 98.03 187 | 98.00 226 | 93.08 261 | 99.42 270 | 94.04 287 | 99.74 82 | 99.30 163 |
|
| MM | | | 96.87 191 | 96.62 209 | 97.62 135 | 97.72 336 | 93.30 204 | 96.39 191 | 92.61 447 | 97.90 64 | 96.76 289 | 98.64 120 | 90.46 319 | 99.81 43 | 99.16 18 | 99.94 8 | 99.76 21 |
|
| WB-MVS | | | 95.50 276 | 96.62 209 | 92.11 448 | 99.21 85 | 77.26 485 | 96.12 219 | 95.40 408 | 98.62 34 | 98.84 82 | 98.26 183 | 91.08 309 | 99.50 230 | 93.37 313 | 98.70 337 | 99.58 50 |
|
| E3new | | | 96.50 220 | 96.61 211 | 96.17 277 | 98.28 250 | 90.09 303 | 94.85 331 | 99.02 120 | 93.95 290 | 97.01 268 | 97.74 259 | 95.19 193 | 99.39 291 | 94.70 261 | 98.77 328 | 99.04 233 |
|
| test20.03 | | | 96.58 217 | 96.61 211 | 96.48 242 | 98.49 225 | 91.72 255 | 95.68 261 | 97.69 329 | 96.81 120 | 98.27 152 | 97.92 235 | 94.18 233 | 98.71 417 | 90.78 371 | 99.66 107 | 99.00 238 |
|
| balanced_ft_v1 | | | 96.29 234 | 96.60 213 | 95.38 333 | 96.77 398 | 88.73 347 | 98.44 37 | 98.44 255 | 94.97 241 | 95.91 341 | 98.77 95 | 91.03 310 | 99.75 84 | 96.16 148 | 98.91 306 | 97.65 409 |
|
| ab-mvs | | | 96.59 214 | 96.59 214 | 96.60 228 | 98.64 190 | 92.21 236 | 98.35 39 | 97.67 330 | 94.45 268 | 96.99 270 | 98.79 91 | 94.96 206 | 99.49 236 | 90.39 387 | 99.07 287 | 98.08 370 |
|
| LuminaMVS | | | 96.76 202 | 96.58 215 | 97.30 167 | 98.94 136 | 92.96 213 | 96.17 216 | 96.15 386 | 95.54 210 | 98.96 68 | 98.18 196 | 87.73 358 | 99.80 50 | 97.98 60 | 99.61 126 | 99.15 201 |
|
| new-patchmatchnet | | | 95.67 269 | 96.58 215 | 92.94 427 | 97.48 362 | 80.21 470 | 92.96 403 | 98.19 291 | 94.83 246 | 98.82 84 | 98.79 91 | 93.31 255 | 99.51 229 | 95.83 170 | 99.04 291 | 99.12 215 |
|
| EPP-MVSNet | | | 96.84 193 | 96.58 215 | 97.65 133 | 99.18 91 | 93.78 185 | 98.68 17 | 96.34 384 | 97.91 63 | 97.30 242 | 98.06 217 | 88.46 346 | 99.85 30 | 93.85 297 | 99.40 219 | 99.32 158 |
|
| VortexMVS | | | 96.04 248 | 96.56 218 | 94.49 381 | 97.60 353 | 84.36 437 | 96.05 225 | 98.67 225 | 94.74 248 | 98.95 69 | 98.78 94 | 87.13 365 | 99.50 230 | 97.37 92 | 99.76 70 | 99.60 46 |
|
| SSC-MVS3.2 | | | 95.75 264 | 96.56 218 | 93.34 409 | 98.69 186 | 80.75 467 | 91.60 442 | 97.43 348 | 97.37 95 | 96.99 270 | 97.02 323 | 93.69 247 | 99.71 126 | 96.32 139 | 99.89 26 | 99.55 70 |
|
| UGNet | | | 96.81 198 | 96.56 218 | 97.58 137 | 96.64 401 | 93.84 182 | 97.75 87 | 97.12 357 | 96.47 141 | 93.62 419 | 98.88 87 | 93.22 257 | 99.53 222 | 95.61 184 | 99.69 97 | 99.36 151 |
| 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 |
| CNVR-MVS | | | 96.92 186 | 96.55 221 | 98.03 105 | 98.00 290 | 95.54 104 | 94.87 329 | 98.17 292 | 94.60 256 | 96.38 315 | 97.05 321 | 95.67 172 | 99.36 305 | 95.12 231 | 99.08 285 | 99.19 193 |
|
| MVS_111021_LR | | | 96.82 197 | 96.55 221 | 97.62 135 | 98.27 253 | 95.34 122 | 93.81 379 | 98.33 272 | 94.59 258 | 96.56 305 | 96.63 352 | 96.61 116 | 98.73 414 | 94.80 252 | 99.34 239 | 98.78 281 |
|
| MVS_111021_HR | | | 96.73 205 | 96.54 223 | 97.27 170 | 98.35 242 | 93.66 191 | 93.42 392 | 98.36 268 | 94.74 248 | 96.58 303 | 96.76 345 | 96.54 121 | 98.99 385 | 94.87 249 | 99.27 255 | 99.15 201 |
|
| APD-MVS |  | | 97.00 177 | 96.53 224 | 98.41 64 | 98.55 212 | 96.31 70 | 96.32 199 | 98.77 203 | 92.96 333 | 97.44 238 | 97.58 272 | 95.84 158 | 99.74 94 | 91.96 339 | 99.35 234 | 99.19 193 |
| Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
| PHI-MVS | | | 96.96 184 | 96.53 224 | 98.25 81 | 97.48 362 | 96.50 62 | 96.76 164 | 98.85 173 | 93.52 303 | 96.19 330 | 96.85 336 | 95.94 153 | 99.42 270 | 93.79 301 | 99.43 211 | 98.83 275 |
|
| DeepC-MVS_fast | | 94.34 7 | 96.74 203 | 96.51 226 | 97.44 155 | 97.69 338 | 94.15 170 | 96.02 230 | 98.43 256 | 93.17 323 | 97.30 242 | 97.38 294 | 95.48 179 | 99.28 335 | 93.74 303 | 99.34 239 | 98.88 270 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| testgi | | | 96.07 246 | 96.50 227 | 94.80 361 | 99.26 68 | 87.69 379 | 95.96 240 | 98.58 241 | 95.08 232 | 98.02 189 | 96.25 373 | 97.92 24 | 97.60 471 | 88.68 413 | 98.74 331 | 99.11 220 |
|
| AstraMVS | | | 96.41 230 | 96.48 228 | 96.20 273 | 98.91 145 | 89.69 314 | 96.28 201 | 93.29 437 | 96.11 166 | 98.70 99 | 98.36 157 | 89.41 339 | 99.66 168 | 97.60 80 | 99.63 113 | 99.26 176 |
|
| test_fmvs2 | | | 96.38 231 | 96.45 229 | 96.16 279 | 97.85 301 | 91.30 266 | 96.81 158 | 99.45 31 | 89.24 404 | 98.49 120 | 99.38 23 | 88.68 344 | 97.62 470 | 98.83 31 | 99.32 246 | 99.57 58 |
|
| DeepPCF-MVS | | 94.58 5 | 96.90 188 | 96.43 230 | 98.31 74 | 97.48 362 | 97.23 43 | 92.56 415 | 98.60 236 | 92.84 336 | 98.54 114 | 97.40 288 | 96.64 115 | 98.78 408 | 94.40 271 | 99.41 218 | 98.93 258 |
|
| viewdifsd2359ckpt13 | | | 96.47 224 | 96.42 231 | 96.61 227 | 98.35 242 | 91.50 260 | 95.31 296 | 98.84 177 | 93.21 317 | 96.73 290 | 97.58 272 | 95.28 190 | 99.26 340 | 94.02 289 | 98.45 358 | 99.07 227 |
|
| test_vis1_n_1920 | | | 95.77 262 | 96.41 232 | 93.85 398 | 98.55 212 | 84.86 429 | 95.91 245 | 99.71 7 | 92.72 339 | 97.67 218 | 98.90 85 | 87.44 361 | 98.73 414 | 97.96 61 | 98.85 315 | 97.96 386 |
|
| icg_test_0407_2 | | | 95.88 256 | 96.39 233 | 94.36 385 | 97.83 310 | 86.11 406 | 91.82 439 | 98.82 192 | 94.48 263 | 97.57 223 | 97.14 310 | 96.08 149 | 98.20 460 | 95.00 239 | 98.78 322 | 98.78 281 |
|
| NormalMVS | | | 96.87 191 | 96.39 233 | 98.30 75 | 99.48 37 | 95.57 101 | 96.87 153 | 98.90 153 | 96.94 114 | 96.85 281 | 97.88 237 | 85.36 382 | 99.76 76 | 95.63 181 | 99.59 136 | 99.57 58 |
|
| HPM-MVS++ |  | | 96.99 178 | 96.38 235 | 98.81 30 | 98.64 190 | 97.59 26 | 95.97 238 | 98.20 286 | 95.51 211 | 95.06 374 | 96.53 357 | 94.10 234 | 99.70 135 | 94.29 275 | 99.15 273 | 99.13 209 |
|
| MVSFormer | | | 96.14 244 | 96.36 236 | 95.49 325 | 97.68 339 | 87.81 376 | 98.67 18 | 99.02 120 | 96.50 137 | 94.48 392 | 96.15 377 | 86.90 366 | 99.92 5 | 98.73 36 | 99.13 276 | 98.74 294 |
|
| TinyColmap | | | 96.00 252 | 96.34 237 | 94.96 352 | 97.90 299 | 87.91 372 | 94.13 364 | 98.49 249 | 94.41 270 | 98.16 170 | 97.76 253 | 96.29 141 | 98.68 423 | 90.52 383 | 99.42 214 | 98.30 350 |
|
| HQP_MVS | | | 96.66 212 | 96.33 238 | 97.68 130 | 98.70 183 | 94.29 164 | 96.50 181 | 98.75 207 | 96.36 145 | 96.16 332 | 96.77 343 | 91.91 301 | 99.46 252 | 92.59 331 | 99.20 264 | 99.28 171 |
|
| guyue | | | 96.21 240 | 96.29 239 | 95.98 288 | 98.80 161 | 89.14 332 | 96.40 189 | 94.34 425 | 95.99 180 | 98.58 111 | 98.13 201 | 87.42 362 | 99.64 177 | 97.39 90 | 99.55 154 | 99.16 200 |
|
| K. test v3 | | | 96.44 226 | 96.28 240 | 96.95 198 | 99.41 46 | 91.53 258 | 97.65 100 | 90.31 473 | 98.89 26 | 98.93 70 | 99.36 26 | 84.57 390 | 99.92 5 | 97.81 68 | 99.56 147 | 99.39 141 |
|
| RRT-MVS | | | 95.78 261 | 96.25 241 | 94.35 387 | 96.68 400 | 84.47 435 | 97.72 95 | 99.11 82 | 97.23 101 | 97.27 244 | 98.72 102 | 86.39 372 | 99.79 53 | 95.49 190 | 97.67 397 | 98.80 278 |
|
| diffmvs |  | | 96.04 248 | 96.23 242 | 95.46 327 | 97.35 373 | 88.03 370 | 93.42 392 | 99.08 96 | 94.09 284 | 96.66 297 | 96.93 331 | 93.85 241 | 99.29 331 | 96.01 157 | 98.67 339 | 99.06 230 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| DELS-MVS | | | 96.17 243 | 96.23 242 | 95.99 286 | 97.55 357 | 90.04 306 | 92.38 424 | 98.52 246 | 94.13 280 | 96.55 307 | 97.06 320 | 94.99 203 | 99.58 203 | 95.62 183 | 99.28 253 | 98.37 338 |
| 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 |
| IterMVS-SCA-FT | | | 95.86 258 | 96.19 244 | 94.85 358 | 97.68 339 | 85.53 414 | 92.42 421 | 97.63 341 | 96.99 107 | 98.36 138 | 98.54 135 | 87.94 352 | 99.75 84 | 97.07 106 | 99.08 285 | 99.27 175 |
|
| pmmvs-eth3d | | | 96.49 222 | 96.18 245 | 97.42 158 | 98.25 256 | 94.29 164 | 94.77 337 | 98.07 308 | 89.81 398 | 97.97 198 | 98.33 162 | 93.11 260 | 99.08 374 | 95.46 197 | 99.84 49 | 98.89 266 |
|
| Fast-Effi-MVS+-dtu | | | 96.44 226 | 96.12 246 | 97.39 161 | 97.18 384 | 94.39 158 | 95.46 277 | 98.73 210 | 96.03 177 | 94.72 385 | 94.92 414 | 96.28 142 | 99.69 143 | 93.81 300 | 97.98 378 | 98.09 369 |
|
| TSAR-MVS + GP. | | | 96.47 224 | 96.12 246 | 97.49 150 | 97.74 334 | 95.23 127 | 94.15 361 | 96.90 371 | 93.26 313 | 98.04 186 | 96.70 348 | 94.41 224 | 98.89 396 | 94.77 256 | 99.14 274 | 98.37 338 |
|
| Effi-MVS+-dtu | | | 96.81 198 | 96.09 248 | 98.99 13 | 96.90 396 | 98.69 4 | 96.42 188 | 98.09 303 | 95.86 191 | 95.15 372 | 95.54 401 | 94.26 231 | 99.81 43 | 94.06 284 | 98.51 354 | 98.47 330 |
|
| CPTT-MVS | | | 96.69 210 | 96.08 249 | 98.49 57 | 98.89 148 | 96.64 58 | 97.25 128 | 98.77 203 | 92.89 335 | 96.01 338 | 97.13 314 | 92.23 289 | 99.67 160 | 92.24 336 | 99.34 239 | 99.17 197 |
|
| mvs_anonymous | | | 95.36 285 | 96.07 250 | 93.21 416 | 96.29 410 | 81.56 460 | 94.60 343 | 97.66 332 | 93.30 312 | 96.95 275 | 98.91 84 | 93.03 266 | 99.38 295 | 96.60 123 | 97.30 414 | 98.69 302 |
|
| viewdifsd2359ckpt09 | | | 96.23 239 | 96.04 251 | 96.82 212 | 98.29 247 | 92.06 246 | 95.25 302 | 99.03 116 | 91.51 366 | 96.19 330 | 97.01 326 | 94.41 224 | 99.40 282 | 93.76 302 | 98.90 307 | 99.00 238 |
|
| IMVS_0404 | | | 95.66 271 | 96.03 252 | 94.55 376 | 97.83 310 | 86.11 406 | 93.24 398 | 98.82 192 | 94.48 263 | 95.51 362 | 97.14 310 | 93.49 251 | 98.78 408 | 95.00 239 | 98.78 322 | 98.78 281 |
|
| Effi-MVS+ | | | 96.19 242 | 96.01 253 | 96.71 220 | 97.43 368 | 92.19 240 | 96.12 219 | 99.10 87 | 95.45 214 | 93.33 431 | 94.71 417 | 97.23 65 | 99.56 211 | 93.21 321 | 97.54 403 | 98.37 338 |
|
| OMC-MVS | | | 96.48 223 | 96.00 254 | 97.91 112 | 98.30 246 | 96.01 85 | 94.86 330 | 98.60 236 | 91.88 354 | 97.18 252 | 97.21 306 | 96.11 148 | 99.04 379 | 90.49 386 | 99.34 239 | 98.69 302 |
|
| NCCC | | | 96.52 219 | 95.99 255 | 98.10 97 | 97.81 315 | 95.68 97 | 95.00 323 | 98.20 286 | 95.39 219 | 95.40 367 | 96.36 368 | 93.81 242 | 99.45 260 | 93.55 311 | 98.42 361 | 99.17 197 |
|
| Anonymous202405211 | | | 96.34 233 | 95.98 256 | 97.43 156 | 98.25 256 | 93.85 181 | 96.74 166 | 94.41 423 | 97.72 71 | 98.37 135 | 98.03 221 | 87.15 364 | 99.53 222 | 94.06 284 | 99.07 287 | 98.92 261 |
|
| xiu_mvs_v1_base_debu | | | 95.62 272 | 95.96 257 | 94.60 372 | 98.01 286 | 88.42 352 | 93.99 369 | 98.21 283 | 92.98 329 | 95.91 341 | 94.53 420 | 96.39 133 | 99.72 110 | 95.43 202 | 98.19 370 | 95.64 466 |
|
| xiu_mvs_v1_base | | | 95.62 272 | 95.96 257 | 94.60 372 | 98.01 286 | 88.42 352 | 93.99 369 | 98.21 283 | 92.98 329 | 95.91 341 | 94.53 420 | 96.39 133 | 99.72 110 | 95.43 202 | 98.19 370 | 95.64 466 |
|
| xiu_mvs_v1_base_debi | | | 95.62 272 | 95.96 257 | 94.60 372 | 98.01 286 | 88.42 352 | 93.99 369 | 98.21 283 | 92.98 329 | 95.91 341 | 94.53 420 | 96.39 133 | 99.72 110 | 95.43 202 | 98.19 370 | 95.64 466 |
|
| mvsany_test3 | | | 96.21 240 | 95.93 260 | 97.05 189 | 97.40 370 | 94.33 163 | 95.76 255 | 94.20 426 | 89.10 405 | 99.36 34 | 99.60 11 | 93.97 238 | 97.85 466 | 95.40 206 | 98.63 344 | 98.99 242 |
|
| ETV-MVS | | | 96.13 245 | 95.90 261 | 96.82 212 | 97.76 329 | 93.89 179 | 95.40 284 | 98.95 145 | 95.87 190 | 95.58 360 | 91.00 467 | 96.36 136 | 99.72 110 | 93.36 314 | 98.83 318 | 96.85 440 |
|
| test_vis1_n | | | 95.67 269 | 95.89 262 | 95.03 347 | 98.18 266 | 89.89 309 | 96.94 148 | 99.28 46 | 88.25 420 | 98.20 164 | 98.92 81 | 86.69 369 | 97.19 473 | 97.70 77 | 98.82 319 | 98.00 384 |
|
| test_f | | | 95.82 260 | 95.88 263 | 95.66 311 | 97.61 351 | 93.21 209 | 95.61 271 | 98.17 292 | 86.98 433 | 98.42 129 | 99.47 16 | 90.46 319 | 94.74 491 | 97.71 75 | 98.45 358 | 99.03 234 |
|
| viewmambaseed2359dif | | | 95.68 268 | 95.85 264 | 95.17 340 | 97.51 359 | 87.41 384 | 93.61 387 | 98.58 241 | 91.06 378 | 96.68 293 | 97.66 265 | 94.71 210 | 99.11 368 | 93.93 293 | 98.94 301 | 98.99 242 |
|
| SymmetryMVS | | | 96.43 228 | 95.85 264 | 98.17 87 | 98.58 207 | 95.57 101 | 96.87 153 | 95.29 411 | 96.94 114 | 96.85 281 | 97.88 237 | 85.36 382 | 99.76 76 | 95.63 181 | 99.27 255 | 99.19 193 |
|
| IterMVS | | | 95.42 283 | 95.83 266 | 94.20 393 | 97.52 358 | 83.78 445 | 92.41 422 | 97.47 346 | 95.49 213 | 98.06 183 | 98.49 139 | 87.94 352 | 99.58 203 | 96.02 155 | 99.02 292 | 99.23 185 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| MCST-MVS | | | 96.24 238 | 95.80 267 | 97.56 138 | 98.75 172 | 94.13 171 | 94.66 341 | 98.17 292 | 90.17 394 | 96.21 328 | 96.10 382 | 95.14 197 | 99.43 266 | 94.13 282 | 98.85 315 | 99.13 209 |
|
| PVSNet_Blended_VisFu | | | 95.95 253 | 95.80 267 | 96.42 252 | 99.28 64 | 90.62 284 | 95.31 296 | 99.08 96 | 88.40 417 | 96.97 274 | 98.17 198 | 92.11 293 | 99.78 58 | 93.64 307 | 99.21 263 | 98.86 273 |
|
| EIA-MVS | | | 96.04 248 | 95.77 269 | 96.85 208 | 97.80 319 | 92.98 212 | 96.12 219 | 99.16 67 | 94.65 254 | 93.77 413 | 91.69 461 | 95.68 170 | 99.67 160 | 94.18 279 | 98.85 315 | 97.91 389 |
|
| UnsupCasMVSNet_eth | | | 95.91 255 | 95.73 270 | 96.44 248 | 98.48 227 | 91.52 259 | 95.31 296 | 98.45 252 | 95.76 197 | 97.48 233 | 97.54 274 | 89.53 335 | 98.69 420 | 94.43 268 | 94.61 469 | 99.13 209 |
|
| test_cas_vis1_n_1920 | | | 95.34 287 | 95.67 271 | 94.35 387 | 98.21 260 | 86.83 396 | 95.61 271 | 99.26 48 | 90.45 389 | 98.17 169 | 98.96 74 | 84.43 391 | 98.31 453 | 96.74 116 | 99.17 271 | 97.90 390 |
|
| MDA-MVSNet-bldmvs | | | 95.69 266 | 95.67 271 | 95.74 302 | 98.48 227 | 88.76 346 | 92.84 405 | 97.25 350 | 96.00 178 | 97.59 222 | 97.95 231 | 91.38 305 | 99.46 252 | 93.16 322 | 96.35 441 | 98.99 242 |
|
| CANet | | | 95.86 258 | 95.65 273 | 96.49 241 | 96.41 408 | 90.82 280 | 94.36 349 | 98.41 260 | 94.94 242 | 92.62 448 | 96.73 346 | 92.68 273 | 99.71 126 | 95.12 231 | 99.60 133 | 98.94 254 |
|
| h-mvs33 | | | 96.29 234 | 95.63 274 | 98.26 78 | 98.50 224 | 96.11 78 | 96.90 151 | 97.09 361 | 96.58 132 | 97.21 249 | 98.19 193 | 84.14 392 | 99.78 58 | 95.89 165 | 96.17 446 | 98.89 266 |
|
| LF4IMVS | | | 96.07 246 | 95.63 274 | 97.36 163 | 98.19 263 | 95.55 103 | 95.44 279 | 98.82 192 | 92.29 347 | 95.70 356 | 96.55 355 | 92.63 276 | 98.69 420 | 91.75 350 | 99.33 244 | 97.85 394 |
|
| QAPM | | | 95.88 256 | 95.57 276 | 96.80 214 | 97.90 299 | 91.84 253 | 98.18 57 | 98.73 210 | 88.41 416 | 96.42 313 | 98.13 201 | 94.73 208 | 99.75 84 | 88.72 411 | 98.94 301 | 98.81 277 |
|
| alignmvs | | | 96.01 251 | 95.52 277 | 97.50 147 | 97.77 328 | 94.71 143 | 96.07 222 | 96.84 372 | 97.48 84 | 96.78 288 | 94.28 426 | 85.50 381 | 99.40 282 | 96.22 145 | 98.73 334 | 98.40 334 |
|
| c3_l | | | 95.20 294 | 95.32 278 | 94.83 360 | 96.19 415 | 86.43 401 | 91.83 438 | 98.35 271 | 93.47 306 | 97.36 240 | 97.26 303 | 88.69 343 | 99.28 335 | 95.41 205 | 99.36 229 | 98.78 281 |
|
| test_fmvs1_n | | | 95.21 293 | 95.28 279 | 94.99 350 | 98.15 273 | 89.13 333 | 96.81 158 | 99.43 33 | 86.97 434 | 97.21 249 | 98.92 81 | 83.00 402 | 97.13 474 | 98.09 54 | 98.94 301 | 98.72 297 |
|
| MVP-Stereo | | | 95.69 266 | 95.28 279 | 96.92 201 | 98.15 273 | 93.03 211 | 95.64 269 | 98.20 286 | 90.39 390 | 96.63 300 | 97.73 260 | 91.63 303 | 99.10 372 | 91.84 344 | 97.31 413 | 98.63 308 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| wuyk23d | | | 93.25 374 | 95.20 281 | 87.40 477 | 96.07 423 | 95.38 114 | 97.04 142 | 94.97 416 | 95.33 221 | 99.70 9 | 98.11 206 | 98.14 21 | 91.94 495 | 77.76 483 | 99.68 101 | 74.89 495 |
|
| OpenMVS |  | 94.22 8 | 95.48 279 | 95.20 281 | 96.32 264 | 97.16 385 | 91.96 249 | 97.74 93 | 98.84 177 | 87.26 428 | 94.36 394 | 98.01 224 | 93.95 239 | 99.67 160 | 90.70 378 | 98.75 330 | 97.35 425 |
|
| MGCNet | | | 95.71 265 | 95.18 283 | 97.33 165 | 94.85 462 | 92.82 215 | 95.36 288 | 90.89 465 | 95.51 211 | 95.61 358 | 97.82 247 | 88.39 348 | 99.78 58 | 98.23 50 | 99.91 19 | 99.40 134 |
|
| D2MVS | | | 95.18 295 | 95.17 284 | 95.21 337 | 97.76 329 | 87.76 378 | 94.15 361 | 97.94 313 | 89.77 399 | 96.99 270 | 97.68 264 | 87.45 360 | 99.14 361 | 95.03 238 | 99.81 58 | 98.74 294 |
|
| DP-MVS Recon | | | 95.55 275 | 95.13 285 | 96.80 214 | 98.51 218 | 93.99 177 | 94.60 343 | 98.69 220 | 90.20 393 | 95.78 352 | 96.21 375 | 92.73 272 | 98.98 387 | 90.58 382 | 98.86 314 | 97.42 422 |
|
| MSDG | | | 95.33 288 | 95.13 285 | 95.94 293 | 97.40 370 | 91.85 252 | 91.02 460 | 98.37 267 | 95.30 223 | 96.31 321 | 95.99 384 | 94.51 222 | 98.38 448 | 89.59 399 | 97.65 400 | 97.60 414 |
|
| hse-mvs2 | | | 95.77 262 | 95.09 287 | 97.79 119 | 97.84 307 | 95.51 106 | 95.66 263 | 95.43 407 | 96.58 132 | 97.21 249 | 96.16 376 | 84.14 392 | 99.54 219 | 95.89 165 | 96.92 418 | 98.32 345 |
|
| Fast-Effi-MVS+ | | | 95.49 277 | 95.07 288 | 96.75 218 | 97.67 343 | 92.82 215 | 94.22 357 | 98.60 236 | 91.61 360 | 93.42 429 | 92.90 442 | 96.73 108 | 99.70 135 | 92.60 330 | 97.89 384 | 97.74 403 |
|
| CLD-MVS | | | 95.47 280 | 95.07 288 | 96.69 222 | 98.27 253 | 92.53 224 | 91.36 447 | 98.67 225 | 91.22 376 | 95.78 352 | 94.12 427 | 95.65 173 | 98.98 387 | 90.81 369 | 99.72 88 | 98.57 315 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| Anonymous20231206 | | | 95.27 291 | 95.06 290 | 95.88 295 | 98.72 177 | 89.37 324 | 95.70 258 | 97.85 319 | 88.00 423 | 96.98 273 | 97.62 268 | 91.95 298 | 99.34 312 | 89.21 404 | 99.53 164 | 98.94 254 |
|
| API-MVS | | | 95.09 300 | 95.01 291 | 95.31 334 | 96.61 402 | 94.02 175 | 96.83 156 | 97.18 354 | 95.60 205 | 95.79 350 | 94.33 425 | 94.54 221 | 98.37 450 | 85.70 445 | 98.52 351 | 93.52 484 |
|
| FMVSNet3 | | | 95.26 292 | 94.94 292 | 96.22 272 | 96.53 404 | 90.06 304 | 95.99 235 | 97.66 332 | 94.11 282 | 97.99 192 | 97.91 236 | 80.22 422 | 99.63 182 | 94.60 263 | 99.44 201 | 98.96 249 |
|
| TAMVS | | | 95.49 277 | 94.94 292 | 97.16 178 | 98.31 245 | 93.41 202 | 95.07 316 | 96.82 374 | 91.09 377 | 97.51 228 | 97.82 247 | 89.96 328 | 99.42 270 | 88.42 416 | 99.44 201 | 98.64 306 |
|
| eth_miper_zixun_eth | | | 94.89 308 | 94.93 294 | 94.75 365 | 95.99 424 | 86.12 405 | 91.35 448 | 98.49 249 | 93.40 307 | 97.12 256 | 97.25 304 | 86.87 368 | 99.35 309 | 95.08 233 | 98.82 319 | 98.78 281 |
|
| PVSNet_BlendedMVS | | | 95.02 304 | 94.93 294 | 95.27 335 | 97.79 324 | 87.40 385 | 94.14 363 | 98.68 222 | 88.94 409 | 94.51 390 | 98.01 224 | 93.04 263 | 99.30 327 | 89.77 397 | 99.49 185 | 99.11 220 |
|
| MS-PatchMatch | | | 94.83 310 | 94.91 296 | 94.57 375 | 96.81 397 | 87.10 391 | 94.23 356 | 97.34 349 | 88.74 412 | 97.14 254 | 97.11 317 | 91.94 299 | 98.23 457 | 92.99 324 | 97.92 381 | 98.37 338 |
|
| GDP-MVS | | | 95.39 284 | 94.89 297 | 96.90 204 | 98.26 255 | 91.91 250 | 96.48 187 | 99.28 46 | 95.06 234 | 96.54 308 | 97.12 316 | 74.83 448 | 99.82 38 | 97.19 99 | 99.27 255 | 98.96 249 |
|
| FA-MVS(test-final) | | | 94.91 306 | 94.89 297 | 94.99 350 | 97.51 359 | 88.11 369 | 98.27 48 | 95.20 413 | 92.40 346 | 96.68 293 | 98.60 126 | 83.44 398 | 99.28 335 | 93.34 315 | 98.53 350 | 97.59 415 |
|
| LFMVS | | | 95.32 289 | 94.88 299 | 96.62 225 | 98.03 282 | 91.47 261 | 97.65 100 | 90.72 468 | 99.11 14 | 97.89 206 | 98.31 167 | 79.20 424 | 99.48 239 | 93.91 295 | 99.12 279 | 98.93 258 |
|
| BP-MVS1 | | | 95.36 285 | 94.86 300 | 96.89 205 | 98.35 242 | 91.72 255 | 96.76 164 | 95.21 412 | 96.48 140 | 96.23 326 | 97.19 307 | 75.97 444 | 99.80 50 | 97.91 63 | 99.60 133 | 99.15 201 |
|
| Vis-MVSNet (Re-imp) | | | 95.11 298 | 94.85 301 | 95.87 296 | 99.12 104 | 89.17 327 | 97.54 113 | 94.92 418 | 96.50 137 | 96.58 303 | 97.27 302 | 83.64 397 | 99.48 239 | 88.42 416 | 99.67 104 | 98.97 248 |
|
| ppachtmachnet_test | | | 94.49 332 | 94.84 302 | 93.46 408 | 96.16 417 | 82.10 455 | 90.59 466 | 97.48 345 | 90.53 388 | 97.01 268 | 97.59 270 | 91.01 311 | 99.36 305 | 93.97 292 | 99.18 269 | 98.94 254 |
|
| YYNet1 | | | 94.73 313 | 94.84 302 | 94.41 384 | 97.47 366 | 85.09 425 | 90.29 469 | 95.85 396 | 92.52 341 | 97.53 226 | 97.76 253 | 91.97 297 | 99.18 354 | 93.31 317 | 96.86 421 | 98.95 251 |
|
| MDA-MVSNet_test_wron | | | 94.73 313 | 94.83 304 | 94.42 383 | 97.48 362 | 85.15 423 | 90.28 470 | 95.87 395 | 92.52 341 | 97.48 233 | 97.76 253 | 91.92 300 | 99.17 358 | 93.32 316 | 96.80 426 | 98.94 254 |
|
| test1111 | | | 94.53 330 | 94.81 305 | 93.72 402 | 99.06 113 | 81.94 458 | 98.31 43 | 83.87 494 | 96.37 144 | 98.49 120 | 99.17 48 | 81.49 409 | 99.73 100 | 96.64 117 | 99.86 35 | 99.49 95 |
|
| miper_lstm_enhance | | | 94.81 312 | 94.80 306 | 94.85 358 | 96.16 417 | 86.45 400 | 91.14 457 | 98.20 286 | 93.49 305 | 97.03 266 | 97.37 296 | 84.97 387 | 99.26 340 | 95.28 213 | 99.56 147 | 98.83 275 |
|
| CL-MVSNet_self_test | | | 95.04 301 | 94.79 307 | 95.82 297 | 97.51 359 | 89.79 312 | 91.14 457 | 96.82 374 | 93.05 326 | 96.72 291 | 96.40 366 | 90.82 314 | 99.16 359 | 91.95 340 | 98.66 341 | 98.50 328 |
|
| BH-untuned | | | 94.69 318 | 94.75 308 | 94.52 378 | 97.95 295 | 87.53 381 | 94.07 366 | 97.01 367 | 93.99 288 | 97.10 258 | 95.65 397 | 92.65 275 | 98.95 392 | 87.60 426 | 96.74 428 | 97.09 430 |
|
| miper_ehance_all_eth | | | 94.69 318 | 94.70 309 | 94.64 368 | 95.77 437 | 86.22 404 | 91.32 451 | 98.24 281 | 91.67 357 | 97.05 265 | 96.65 351 | 88.39 348 | 99.22 351 | 94.88 248 | 98.34 364 | 98.49 329 |
|
| train_agg | | | 95.46 281 | 94.66 310 | 97.88 114 | 97.84 307 | 95.23 127 | 93.62 385 | 98.39 263 | 87.04 431 | 93.78 411 | 95.99 384 | 94.58 218 | 99.52 225 | 91.76 349 | 98.90 307 | 98.89 266 |
|
| CDPH-MVS | | | 95.45 282 | 94.65 311 | 97.84 117 | 98.28 250 | 94.96 138 | 93.73 381 | 98.33 272 | 85.03 454 | 95.44 364 | 96.60 353 | 95.31 188 | 99.44 263 | 90.01 392 | 99.13 276 | 99.11 220 |
|
| cl____ | | | 94.73 313 | 94.64 312 | 95.01 348 | 95.85 431 | 87.00 392 | 91.33 449 | 98.08 304 | 93.34 310 | 97.10 258 | 97.33 299 | 84.01 396 | 99.30 327 | 95.14 228 | 99.56 147 | 98.71 301 |
|
| DIV-MVS_self_test | | | 94.73 313 | 94.64 312 | 95.01 348 | 95.86 430 | 87.00 392 | 91.33 449 | 98.08 304 | 93.34 310 | 97.10 258 | 97.34 298 | 84.02 395 | 99.31 323 | 95.15 227 | 99.55 154 | 98.72 297 |
|
| xiu_mvs_v2_base | | | 94.22 338 | 94.63 314 | 92.99 425 | 97.32 378 | 84.84 430 | 92.12 431 | 97.84 321 | 91.96 352 | 94.17 399 | 93.43 433 | 96.07 151 | 99.71 126 | 91.27 355 | 97.48 406 | 94.42 478 |
|
| AdaColmap |  | | 95.11 298 | 94.62 315 | 96.58 231 | 97.33 377 | 94.45 157 | 94.92 326 | 98.08 304 | 93.15 324 | 93.98 409 | 95.53 402 | 94.34 227 | 99.10 372 | 85.69 446 | 98.61 346 | 96.20 459 |
|
| test_fmvs1 | | | 94.51 331 | 94.60 316 | 94.26 392 | 95.91 426 | 87.92 371 | 95.35 291 | 99.02 120 | 86.56 438 | 96.79 284 | 98.52 136 | 82.64 404 | 97.00 477 | 97.87 65 | 98.71 335 | 97.88 392 |
|
| RPMNet | | | 94.68 320 | 94.60 316 | 94.90 355 | 95.44 447 | 88.15 365 | 96.18 212 | 98.86 169 | 97.43 86 | 94.10 402 | 98.49 139 | 79.40 423 | 99.76 76 | 95.69 175 | 95.81 453 | 96.81 444 |
|
| Patchmtry | | | 95.03 303 | 94.59 318 | 96.33 261 | 94.83 464 | 90.82 280 | 96.38 194 | 97.20 352 | 96.59 131 | 97.49 230 | 98.57 130 | 77.67 431 | 99.38 295 | 92.95 326 | 99.62 116 | 98.80 278 |
|
| our_test_3 | | | 94.20 342 | 94.58 319 | 93.07 420 | 96.16 417 | 81.20 464 | 90.42 468 | 96.84 372 | 90.72 384 | 97.14 254 | 97.13 314 | 90.47 318 | 99.11 368 | 94.04 287 | 98.25 368 | 98.91 262 |
|
| HQP-MVS | | | 95.17 297 | 94.58 319 | 96.92 201 | 97.85 301 | 92.47 227 | 94.26 351 | 98.43 256 | 93.18 320 | 92.86 439 | 95.08 408 | 90.33 322 | 99.23 349 | 90.51 384 | 98.74 331 | 99.05 232 |
|
| USDC | | | 94.56 328 | 94.57 321 | 94.55 376 | 97.78 327 | 86.43 401 | 92.75 408 | 98.65 233 | 85.96 442 | 96.91 278 | 97.93 234 | 90.82 314 | 98.74 413 | 90.71 377 | 99.59 136 | 98.47 330 |
|
| Patchmatch-RL test | | | 94.66 321 | 94.49 322 | 95.19 338 | 98.54 214 | 88.91 340 | 92.57 414 | 98.74 209 | 91.46 371 | 98.32 146 | 97.75 256 | 77.31 436 | 98.81 406 | 96.06 150 | 99.61 126 | 97.85 394 |
|
| ECVR-MVS |  | | 94.37 336 | 94.48 323 | 94.05 397 | 98.95 133 | 83.10 448 | 98.31 43 | 82.48 496 | 96.20 155 | 98.23 162 | 99.16 49 | 81.18 412 | 99.66 168 | 95.95 160 | 99.83 54 | 99.38 143 |
|
| PS-MVSNAJ | | | 94.10 344 | 94.47 324 | 93.00 424 | 97.35 373 | 84.88 427 | 91.86 437 | 97.84 321 | 91.96 352 | 94.17 399 | 92.50 452 | 95.82 161 | 99.71 126 | 91.27 355 | 97.48 406 | 94.40 479 |
|
| EU-MVSNet | | | 94.25 337 | 94.47 324 | 93.60 405 | 98.14 275 | 82.60 453 | 97.24 130 | 92.72 444 | 85.08 452 | 98.48 122 | 98.94 77 | 82.59 405 | 98.76 412 | 97.47 86 | 99.53 164 | 99.44 121 |
|
| CNLPA | | | 95.04 301 | 94.47 324 | 96.75 218 | 97.81 315 | 95.25 126 | 94.12 365 | 97.89 317 | 94.41 270 | 94.57 388 | 95.69 395 | 90.30 325 | 98.35 451 | 86.72 438 | 98.76 329 | 96.64 448 |
|
| BH-RMVSNet | | | 94.56 328 | 94.44 327 | 94.91 353 | 97.57 354 | 87.44 383 | 93.78 380 | 96.26 385 | 93.69 297 | 96.41 314 | 96.50 360 | 92.10 294 | 99.00 383 | 85.96 443 | 97.71 393 | 98.31 347 |
|
| mvsmamba | | | 94.91 306 | 94.41 328 | 96.40 258 | 97.65 346 | 91.30 266 | 97.92 74 | 95.32 409 | 91.50 367 | 95.54 361 | 98.38 155 | 83.06 401 | 99.68 150 | 92.46 334 | 97.84 385 | 98.23 358 |
|
| F-COLMAP | | | 95.30 290 | 94.38 329 | 98.05 104 | 98.64 190 | 96.04 81 | 95.61 271 | 98.66 228 | 89.00 408 | 93.22 432 | 96.40 366 | 92.90 268 | 99.35 309 | 87.45 431 | 97.53 404 | 98.77 290 |
|
| pmmvs5 | | | 94.63 323 | 94.34 330 | 95.50 324 | 97.63 350 | 88.34 357 | 94.02 367 | 97.13 356 | 87.15 430 | 95.22 371 | 97.15 309 | 87.50 359 | 99.27 338 | 93.99 290 | 99.26 258 | 98.88 270 |
|
| usedtu_dtu_shiyan1 | | | 94.61 324 | 94.29 331 | 95.57 316 | 97.93 296 | 88.45 350 | 91.30 452 | 97.64 338 | 91.61 360 | 95.85 348 | 95.79 392 | 86.65 370 | 99.48 239 | 92.92 327 | 98.97 295 | 98.78 281 |
|
| FE-MVSNET3 | | | 94.61 324 | 94.29 331 | 95.57 316 | 97.93 296 | 88.45 350 | 91.30 452 | 97.64 338 | 91.61 360 | 95.85 348 | 95.79 392 | 86.65 370 | 99.48 239 | 92.92 327 | 98.97 295 | 98.78 281 |
|
| UnsupCasMVSNet_bld | | | 94.72 317 | 94.26 333 | 96.08 283 | 98.62 201 | 90.54 288 | 93.38 394 | 98.05 311 | 90.30 391 | 97.02 267 | 96.80 342 | 89.54 333 | 99.16 359 | 88.44 415 | 96.18 445 | 98.56 316 |
|
| N_pmnet | | | 95.18 295 | 94.23 334 | 98.06 100 | 97.85 301 | 96.55 61 | 92.49 416 | 91.63 456 | 89.34 402 | 98.09 178 | 97.41 287 | 90.33 322 | 99.06 376 | 91.58 351 | 99.31 249 | 98.56 316 |
|
| TAPA-MVS | | 93.32 12 | 94.93 305 | 94.23 334 | 97.04 191 | 98.18 266 | 94.51 154 | 95.22 304 | 98.73 210 | 81.22 476 | 96.25 325 | 95.95 388 | 93.80 243 | 98.98 387 | 89.89 395 | 98.87 312 | 97.62 412 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| CANet_DTU | | | 94.65 322 | 94.21 336 | 95.96 289 | 95.90 427 | 89.68 315 | 93.92 374 | 97.83 323 | 93.19 319 | 90.12 470 | 95.64 398 | 88.52 345 | 99.57 209 | 93.27 319 | 99.47 192 | 98.62 309 |
|
| pmmvs4 | | | 94.82 311 | 94.19 337 | 96.70 221 | 97.42 369 | 92.75 221 | 92.09 433 | 96.76 376 | 86.80 436 | 95.73 355 | 97.22 305 | 89.28 340 | 98.89 396 | 93.28 318 | 99.14 274 | 98.46 332 |
|
| PAPM_NR | | | 94.61 324 | 94.17 338 | 95.96 289 | 98.36 241 | 91.23 269 | 95.93 243 | 97.95 312 | 92.98 329 | 93.42 429 | 94.43 424 | 90.53 317 | 98.38 448 | 87.60 426 | 96.29 443 | 98.27 354 |
|
| ttmdpeth | | | 94.05 347 | 94.15 339 | 93.75 401 | 95.81 434 | 85.32 418 | 96.00 232 | 94.93 417 | 92.07 348 | 94.19 398 | 99.09 58 | 85.73 378 | 96.41 485 | 90.98 362 | 98.52 351 | 99.53 77 |
|
| CDS-MVSNet | | | 94.88 309 | 94.12 340 | 97.14 180 | 97.64 349 | 93.57 193 | 93.96 373 | 97.06 363 | 90.05 395 | 96.30 322 | 96.55 355 | 86.10 374 | 99.47 245 | 90.10 391 | 99.31 249 | 98.40 334 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| PMMVS2 | | | 93.66 360 | 94.07 341 | 92.45 441 | 97.57 354 | 80.67 468 | 86.46 485 | 96.00 390 | 93.99 288 | 97.10 258 | 97.38 294 | 89.90 329 | 97.82 467 | 88.76 410 | 99.47 192 | 98.86 273 |
|
| jason | | | 94.39 335 | 94.04 342 | 95.41 330 | 98.29 247 | 87.85 375 | 92.74 410 | 96.75 377 | 85.38 451 | 95.29 369 | 96.15 377 | 88.21 351 | 99.65 171 | 94.24 277 | 99.34 239 | 98.74 294 |
| jason: jason. |
| test_yl | | | 94.40 333 | 94.00 343 | 95.59 314 | 96.95 392 | 89.52 319 | 94.75 338 | 95.55 404 | 96.18 162 | 96.79 284 | 96.14 379 | 81.09 413 | 99.18 354 | 90.75 373 | 97.77 387 | 98.07 372 |
|
| DCV-MVSNet | | | 94.40 333 | 94.00 343 | 95.59 314 | 96.95 392 | 89.52 319 | 94.75 338 | 95.55 404 | 96.18 162 | 96.79 284 | 96.14 379 | 81.09 413 | 99.18 354 | 90.75 373 | 97.77 387 | 98.07 372 |
|
| MG-MVS | | | 94.08 346 | 94.00 343 | 94.32 389 | 97.09 388 | 85.89 411 | 93.19 401 | 95.96 392 | 92.52 341 | 94.93 380 | 97.51 281 | 89.54 333 | 98.77 410 | 87.52 430 | 97.71 393 | 98.31 347 |
|
| MonoMVSNet | | | 93.30 372 | 93.96 346 | 91.33 456 | 94.14 476 | 81.33 463 | 97.68 98 | 96.69 380 | 95.38 220 | 96.32 318 | 98.42 149 | 84.12 394 | 96.76 482 | 90.78 371 | 92.12 479 | 95.89 461 |
|
| MVSTER | | | 94.21 340 | 93.93 347 | 95.05 346 | 95.83 432 | 86.46 399 | 95.18 308 | 97.65 334 | 92.41 345 | 97.94 202 | 98.00 226 | 72.39 460 | 99.58 203 | 96.36 136 | 99.56 147 | 99.12 215 |
|
| PatchMatch-RL | | | 94.61 324 | 93.81 348 | 97.02 195 | 98.19 263 | 95.72 94 | 93.66 383 | 97.23 351 | 88.17 421 | 94.94 379 | 95.62 399 | 91.43 304 | 98.57 432 | 87.36 432 | 97.68 396 | 96.76 446 |
|
| sss | | | 94.22 338 | 93.72 349 | 95.74 302 | 97.71 337 | 89.95 308 | 93.84 376 | 96.98 368 | 88.38 418 | 93.75 414 | 95.74 394 | 87.94 352 | 98.89 396 | 91.02 361 | 98.10 374 | 98.37 338 |
|
| test_vis1_rt | | | 94.03 349 | 93.65 350 | 95.17 340 | 95.76 438 | 93.42 201 | 93.97 372 | 98.33 272 | 84.68 458 | 93.17 433 | 95.89 390 | 92.53 284 | 94.79 490 | 93.50 312 | 94.97 465 | 97.31 427 |
|
| PVSNet_Blended | | | 93.96 350 | 93.65 350 | 94.91 353 | 97.79 324 | 87.40 385 | 91.43 446 | 98.68 222 | 84.50 461 | 94.51 390 | 94.48 423 | 93.04 263 | 99.30 327 | 89.77 397 | 98.61 346 | 98.02 382 |
|
| PatchT | | | 93.75 354 | 93.57 352 | 94.29 391 | 95.05 457 | 87.32 387 | 96.05 225 | 92.98 440 | 97.54 81 | 94.25 395 | 98.72 102 | 75.79 445 | 99.24 347 | 95.92 163 | 95.81 453 | 96.32 456 |
|
| SCA | | | 93.38 368 | 93.52 353 | 92.96 426 | 96.24 411 | 81.40 462 | 93.24 398 | 94.00 427 | 91.58 365 | 94.57 388 | 96.97 328 | 87.94 352 | 99.42 270 | 89.47 401 | 97.66 399 | 98.06 376 |
|
| SD_0403 | | | 93.73 356 | 93.43 354 | 94.64 368 | 97.85 301 | 86.35 403 | 97.47 115 | 97.94 313 | 93.50 304 | 93.71 415 | 96.73 346 | 93.77 244 | 98.84 402 | 73.48 489 | 96.39 439 | 98.72 297 |
|
| 1112_ss | | | 94.12 343 | 93.42 355 | 96.23 270 | 98.59 205 | 90.85 279 | 94.24 355 | 98.85 173 | 85.49 447 | 92.97 437 | 94.94 412 | 86.01 375 | 99.64 177 | 91.78 348 | 97.92 381 | 98.20 362 |
|
| CHOSEN 1792x2688 | | | 94.10 344 | 93.41 356 | 96.18 276 | 99.16 93 | 90.04 306 | 92.15 429 | 98.68 222 | 79.90 481 | 96.22 327 | 97.83 244 | 87.92 356 | 99.42 270 | 89.18 405 | 99.65 109 | 99.08 225 |
|
| lupinMVS | | | 93.77 353 | 93.28 357 | 95.24 336 | 97.68 339 | 87.81 376 | 92.12 431 | 96.05 388 | 84.52 460 | 94.48 392 | 95.06 410 | 86.90 366 | 99.63 182 | 93.62 310 | 99.13 276 | 98.27 354 |
|
| Patchmatch-test | | | 93.60 362 | 93.25 358 | 94.63 370 | 96.14 421 | 87.47 382 | 96.04 227 | 94.50 422 | 93.57 300 | 96.47 311 | 96.97 328 | 76.50 439 | 98.61 429 | 90.67 380 | 98.41 362 | 97.81 398 |
|
| 114514_t | | | 93.96 350 | 93.22 359 | 96.19 275 | 99.06 113 | 90.97 274 | 95.99 235 | 98.94 148 | 73.88 494 | 93.43 428 | 96.93 331 | 92.38 288 | 99.37 301 | 89.09 406 | 99.28 253 | 98.25 357 |
|
| usedtu_blend_shiyan5 | | | 93.74 355 | 93.08 360 | 95.71 307 | 94.99 458 | 89.17 327 | 97.38 121 | 98.93 150 | 96.40 142 | 94.75 382 | 87.24 486 | 80.36 418 | 99.40 282 | 91.84 344 | 95.85 449 | 98.55 318 |
|
| OpenMVS_ROB |  | 91.80 14 | 93.64 361 | 93.05 361 | 95.42 328 | 97.31 379 | 91.21 270 | 95.08 315 | 96.68 381 | 81.56 473 | 96.88 280 | 96.41 364 | 90.44 321 | 99.25 343 | 85.39 451 | 97.67 397 | 95.80 464 |
|
| mvsany_test1 | | | 93.47 365 | 93.03 362 | 94.79 362 | 94.05 478 | 92.12 241 | 90.82 464 | 90.01 477 | 85.02 455 | 97.26 245 | 98.28 178 | 93.57 249 | 97.03 475 | 92.51 333 | 95.75 459 | 95.23 472 |
|
| MAR-MVS | | | 94.21 340 | 93.03 362 | 97.76 122 | 96.94 394 | 97.44 36 | 96.97 147 | 97.15 355 | 87.89 425 | 92.00 453 | 92.73 448 | 92.14 292 | 99.12 365 | 83.92 460 | 97.51 405 | 96.73 447 |
| 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 |
| WTY-MVS | | | 93.55 363 | 93.00 364 | 95.19 338 | 97.81 315 | 87.86 373 | 93.89 375 | 96.00 390 | 89.02 407 | 94.07 404 | 95.44 405 | 86.27 373 | 99.33 314 | 87.69 424 | 96.82 424 | 98.39 336 |
|
| PLC |  | 91.02 16 | 94.05 347 | 92.90 365 | 97.51 143 | 98.00 290 | 95.12 135 | 94.25 354 | 98.25 279 | 86.17 440 | 91.48 458 | 95.25 406 | 91.01 311 | 99.19 353 | 85.02 455 | 96.69 431 | 98.22 360 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| Test_1112_low_res | | | 93.53 364 | 92.86 366 | 95.54 323 | 98.60 203 | 88.86 342 | 92.75 408 | 98.69 220 | 82.66 468 | 92.65 445 | 96.92 333 | 84.75 388 | 99.56 211 | 90.94 364 | 97.76 389 | 98.19 363 |
|
| MIMVSNet | | | 93.42 366 | 92.86 366 | 95.10 344 | 98.17 269 | 88.19 361 | 98.13 59 | 93.69 429 | 92.07 348 | 95.04 377 | 98.21 191 | 80.95 415 | 99.03 382 | 81.42 471 | 98.06 376 | 98.07 372 |
|
| cl22 | | | 93.25 374 | 92.84 368 | 94.46 382 | 94.30 471 | 86.00 410 | 91.09 459 | 96.64 382 | 90.74 383 | 95.79 350 | 96.31 370 | 78.24 428 | 98.77 410 | 94.15 281 | 98.34 364 | 98.62 309 |
|
| CVMVSNet | | | 92.33 391 | 92.79 369 | 90.95 458 | 97.26 380 | 75.84 489 | 95.29 299 | 92.33 450 | 81.86 471 | 96.27 323 | 98.19 193 | 81.44 410 | 98.46 443 | 94.23 278 | 98.29 367 | 98.55 318 |
|
| CR-MVSNet | | | 93.29 373 | 92.79 369 | 94.78 363 | 95.44 447 | 88.15 365 | 96.18 212 | 97.20 352 | 84.94 457 | 94.10 402 | 98.57 130 | 77.67 431 | 99.39 291 | 95.17 223 | 95.81 453 | 96.81 444 |
|
| miper_enhance_ethall | | | 93.14 376 | 92.78 371 | 94.20 393 | 93.65 481 | 85.29 420 | 89.97 472 | 97.85 319 | 85.05 453 | 96.15 334 | 94.56 419 | 85.74 377 | 99.14 361 | 93.74 303 | 98.34 364 | 98.17 366 |
|
| DPM-MVS | | | 93.68 359 | 92.77 372 | 96.42 252 | 97.91 298 | 92.54 223 | 91.17 456 | 97.47 346 | 84.99 456 | 93.08 435 | 94.74 416 | 89.90 329 | 99.00 383 | 87.54 428 | 98.09 375 | 97.72 406 |
|
| AUN-MVS | | | 93.95 352 | 92.69 373 | 97.74 123 | 97.80 319 | 95.38 114 | 95.57 274 | 95.46 406 | 91.26 375 | 92.64 446 | 96.10 382 | 74.67 449 | 99.55 216 | 93.72 305 | 96.97 417 | 98.30 350 |
|
| HyFIR lowres test | | | 93.72 357 | 92.65 374 | 96.91 203 | 98.93 140 | 91.81 254 | 91.23 455 | 98.52 246 | 82.69 467 | 96.46 312 | 96.52 359 | 80.38 417 | 99.90 17 | 90.36 388 | 98.79 321 | 99.03 234 |
|
| baseline1 | | | 93.14 376 | 92.64 375 | 94.62 371 | 97.34 375 | 87.20 389 | 96.67 175 | 93.02 439 | 94.71 252 | 96.51 309 | 95.83 391 | 81.64 408 | 98.60 431 | 90.00 393 | 88.06 487 | 98.07 372 |
|
| EPNet | | | 93.72 357 | 92.62 376 | 97.03 193 | 87.61 502 | 92.25 234 | 96.27 203 | 91.28 461 | 96.74 123 | 87.65 484 | 97.39 292 | 85.00 386 | 99.64 177 | 92.14 337 | 99.48 190 | 99.20 192 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| tttt0517 | | | 93.31 371 | 92.56 377 | 95.57 316 | 98.71 181 | 87.86 373 | 97.44 117 | 87.17 488 | 95.79 196 | 97.47 235 | 96.84 337 | 64.12 474 | 99.81 43 | 96.20 146 | 99.32 246 | 99.02 237 |
|
| blended_shiyan8 | | | 93.34 369 | 92.55 378 | 95.73 305 | 95.69 441 | 89.08 335 | 92.36 425 | 97.11 358 | 91.47 369 | 95.42 366 | 88.94 480 | 82.26 406 | 99.48 239 | 93.84 298 | 95.81 453 | 98.62 309 |
|
| blended_shiyan6 | | | 93.34 369 | 92.54 379 | 95.73 305 | 95.68 442 | 89.08 335 | 92.35 426 | 97.10 359 | 91.47 369 | 95.37 368 | 88.96 479 | 82.26 406 | 99.48 239 | 93.83 299 | 95.85 449 | 98.62 309 |
|
| FMVSNet5 | | | 93.39 367 | 92.35 380 | 96.50 240 | 95.83 432 | 90.81 282 | 97.31 125 | 98.27 277 | 92.74 338 | 96.27 323 | 98.28 178 | 62.23 476 | 99.67 160 | 90.86 367 | 99.36 229 | 99.03 234 |
|
| 1314 | | | 92.38 389 | 92.30 381 | 92.64 436 | 95.42 449 | 85.15 423 | 95.86 248 | 96.97 369 | 85.40 450 | 90.62 461 | 93.06 440 | 91.12 308 | 97.80 468 | 86.74 437 | 95.49 462 | 94.97 474 |
|
| reproduce_monomvs | | | 92.05 398 | 92.26 382 | 91.43 454 | 95.42 449 | 75.72 490 | 95.68 261 | 97.05 364 | 94.47 267 | 97.95 201 | 98.35 159 | 55.58 490 | 99.05 377 | 96.36 136 | 99.44 201 | 99.51 84 |
|
| FE-MVS | | | 92.95 378 | 92.22 383 | 95.11 342 | 97.21 383 | 88.33 358 | 98.54 26 | 93.66 432 | 89.91 397 | 96.21 328 | 98.14 199 | 70.33 467 | 99.50 230 | 87.79 422 | 98.24 369 | 97.51 418 |
|
| TR-MVS | | | 92.54 387 | 92.20 384 | 93.57 406 | 96.49 405 | 86.66 397 | 93.51 390 | 94.73 419 | 89.96 396 | 94.95 378 | 93.87 430 | 90.24 327 | 98.61 429 | 81.18 473 | 94.88 466 | 95.45 470 |
|
| GA-MVS | | | 92.83 381 | 92.15 385 | 94.87 357 | 96.97 391 | 87.27 388 | 90.03 471 | 96.12 387 | 91.83 355 | 94.05 405 | 94.57 418 | 76.01 443 | 98.97 391 | 92.46 334 | 97.34 412 | 98.36 343 |
|
| BH-w/o | | | 92.14 394 | 91.94 386 | 92.73 433 | 97.13 387 | 85.30 419 | 92.46 418 | 95.64 399 | 89.33 403 | 94.21 397 | 92.74 447 | 89.60 331 | 98.24 456 | 81.68 470 | 94.66 468 | 94.66 476 |
|
| PatchmatchNet |  | | 91.98 400 | 91.87 387 | 92.30 444 | 94.60 467 | 79.71 471 | 95.12 309 | 93.59 434 | 89.52 401 | 93.61 420 | 97.02 323 | 77.94 429 | 99.18 354 | 90.84 368 | 94.57 471 | 98.01 383 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| DSMNet-mixed | | | 92.19 393 | 91.83 388 | 93.25 413 | 96.18 416 | 83.68 446 | 96.27 203 | 93.68 431 | 76.97 491 | 92.54 449 | 99.18 45 | 89.20 342 | 98.55 435 | 83.88 461 | 98.60 348 | 97.51 418 |
|
| HY-MVS | | 91.43 15 | 92.58 386 | 91.81 389 | 94.90 355 | 96.49 405 | 88.87 341 | 97.31 125 | 94.62 420 | 85.92 443 | 90.50 464 | 96.84 337 | 85.05 385 | 99.40 282 | 83.77 463 | 95.78 457 | 96.43 455 |
|
| Syy-MVS | | | 92.09 396 | 91.80 390 | 92.93 428 | 95.19 454 | 82.65 451 | 92.46 418 | 91.35 459 | 90.67 386 | 91.76 456 | 87.61 483 | 85.64 380 | 98.50 439 | 94.73 258 | 96.84 422 | 97.65 409 |
|
| gbinet_0.2-2-1-0.02 | | | 92.86 379 | 91.78 391 | 96.13 281 | 94.34 469 | 90.06 304 | 91.90 436 | 96.63 383 | 91.73 356 | 94.24 396 | 86.22 491 | 80.26 421 | 99.56 211 | 93.87 296 | 96.80 426 | 98.77 290 |
|
| thisisatest0530 | | | 92.71 383 | 91.76 392 | 95.56 321 | 98.42 236 | 88.23 360 | 96.03 229 | 87.35 487 | 94.04 285 | 96.56 305 | 95.47 403 | 64.03 475 | 99.77 69 | 94.78 255 | 99.11 280 | 98.68 305 |
|
| wanda-best-256-512 | | | 92.66 384 | 91.75 393 | 95.40 331 | 94.99 458 | 88.19 361 | 90.89 461 | 97.05 364 | 91.02 380 | 94.75 382 | 87.24 486 | 80.36 418 | 99.46 252 | 93.63 308 | 95.85 449 | 98.55 318 |
|
| FE-blended-shiyan7 | | | 92.66 384 | 91.75 393 | 95.40 331 | 94.99 458 | 88.19 361 | 90.89 461 | 97.05 364 | 91.02 380 | 94.75 382 | 87.24 486 | 80.36 418 | 99.46 252 | 93.63 308 | 95.85 449 | 98.55 318 |
|
| new_pmnet | | | 92.34 390 | 91.69 395 | 94.32 389 | 96.23 413 | 89.16 330 | 92.27 427 | 92.88 441 | 84.39 463 | 95.29 369 | 96.35 369 | 85.66 379 | 96.74 483 | 84.53 458 | 97.56 402 | 97.05 431 |
|
| MVStest1 | | | 91.89 401 | 91.45 396 | 93.21 416 | 89.01 497 | 84.87 428 | 95.82 252 | 95.05 415 | 91.50 367 | 98.75 93 | 99.19 41 | 57.56 481 | 95.11 488 | 97.78 71 | 98.37 363 | 99.64 43 |
|
| thres600view7 | | | 92.03 399 | 91.43 397 | 93.82 399 | 98.19 263 | 84.61 433 | 96.27 203 | 90.39 470 | 96.81 120 | 96.37 316 | 93.11 435 | 73.44 458 | 99.49 236 | 80.32 475 | 97.95 380 | 97.36 423 |
|
| CMPMVS |  | 73.10 23 | 92.74 382 | 91.39 398 | 96.77 217 | 93.57 483 | 94.67 146 | 94.21 358 | 97.67 330 | 80.36 480 | 93.61 420 | 96.60 353 | 82.85 403 | 97.35 472 | 84.86 456 | 98.78 322 | 98.29 353 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| cascas | | | 91.89 401 | 91.35 399 | 93.51 407 | 94.27 472 | 85.60 413 | 88.86 481 | 98.61 235 | 79.32 483 | 92.16 452 | 91.44 463 | 89.22 341 | 98.12 461 | 90.80 370 | 97.47 408 | 96.82 443 |
|
| WB-MVSnew | | | 91.50 407 | 91.29 400 | 92.14 447 | 94.85 462 | 80.32 469 | 93.29 397 | 88.77 480 | 88.57 415 | 94.03 406 | 92.21 454 | 92.56 278 | 98.28 455 | 80.21 476 | 97.08 416 | 97.81 398 |
|
| MDTV_nov1_ep13 | | | | 91.28 401 | | 94.31 470 | 73.51 496 | 94.80 334 | 93.16 438 | 86.75 437 | 93.45 427 | 97.40 288 | 76.37 440 | 98.55 435 | 88.85 409 | 96.43 437 | |
|
| dmvs_re | | | 92.08 397 | 91.27 402 | 94.51 379 | 97.16 385 | 92.79 220 | 95.65 265 | 92.64 446 | 94.11 282 | 92.74 442 | 90.98 468 | 83.41 399 | 94.44 493 | 80.72 474 | 94.07 472 | 96.29 457 |
|
| PAPR | | | 92.22 392 | 91.27 402 | 95.07 345 | 95.73 440 | 88.81 343 | 91.97 434 | 97.87 318 | 85.80 445 | 90.91 460 | 92.73 448 | 91.16 307 | 98.33 452 | 79.48 477 | 95.76 458 | 98.08 370 |
|
| thres100view900 | | | 91.76 404 | 91.26 404 | 93.26 412 | 98.21 260 | 84.50 434 | 96.39 191 | 90.39 470 | 96.87 117 | 96.33 317 | 93.08 439 | 73.44 458 | 99.42 270 | 78.85 480 | 97.74 390 | 95.85 462 |
|
| PMMVS | | | 92.39 388 | 91.08 405 | 96.30 266 | 93.12 485 | 92.81 217 | 90.58 467 | 95.96 392 | 79.17 484 | 91.85 455 | 92.27 453 | 90.29 326 | 98.66 425 | 89.85 396 | 96.68 432 | 97.43 421 |
|
| tfpn200view9 | | | 91.55 406 | 91.00 406 | 93.21 416 | 98.02 284 | 84.35 438 | 95.70 258 | 90.79 466 | 96.26 149 | 95.90 345 | 92.13 456 | 73.62 455 | 99.42 270 | 78.85 480 | 97.74 390 | 95.85 462 |
|
| thres400 | | | 91.68 405 | 91.00 406 | 93.71 403 | 98.02 284 | 84.35 438 | 95.70 258 | 90.79 466 | 96.26 149 | 95.90 345 | 92.13 456 | 73.62 455 | 99.42 270 | 78.85 480 | 97.74 390 | 97.36 423 |
|
| PVSNet | | 86.72 19 | 91.10 412 | 90.97 408 | 91.49 453 | 97.56 356 | 78.04 478 | 87.17 483 | 94.60 421 | 84.65 459 | 92.34 450 | 92.20 455 | 87.37 363 | 98.47 442 | 85.17 454 | 97.69 395 | 97.96 386 |
|
| tpmvs | | | 90.79 416 | 90.87 409 | 90.57 461 | 92.75 489 | 76.30 487 | 95.79 253 | 93.64 433 | 91.04 379 | 91.91 454 | 96.26 372 | 77.19 437 | 98.86 401 | 89.38 403 | 89.85 484 | 96.56 451 |
|
| tpm | | | 91.08 413 | 90.85 410 | 91.75 451 | 95.33 451 | 78.09 477 | 95.03 322 | 91.27 462 | 88.75 411 | 93.53 424 | 97.40 288 | 71.24 462 | 99.30 327 | 91.25 357 | 93.87 473 | 97.87 393 |
|
| X-MVStestdata | | | 92.86 379 | 90.83 411 | 98.94 18 | 99.15 96 | 97.66 22 | 97.77 84 | 98.83 184 | 97.42 87 | 96.32 318 | 36.50 499 | 96.49 125 | 99.72 110 | 95.66 178 | 99.37 225 | 99.45 111 |
|
| EPNet_dtu | | | 91.39 409 | 90.75 412 | 93.31 411 | 90.48 495 | 82.61 452 | 94.80 334 | 92.88 441 | 93.39 308 | 81.74 493 | 94.90 415 | 81.36 411 | 99.11 368 | 88.28 418 | 98.87 312 | 98.21 361 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| WBMVS | | | 91.11 411 | 90.72 413 | 92.26 445 | 95.99 424 | 77.98 480 | 91.47 445 | 95.90 394 | 91.63 358 | 95.90 345 | 96.45 362 | 59.60 478 | 99.46 252 | 89.97 394 | 99.59 136 | 99.33 156 |
|
| JIA-IIPM | | | 91.79 403 | 90.69 414 | 95.11 342 | 93.80 480 | 90.98 273 | 94.16 360 | 91.78 455 | 96.38 143 | 90.30 467 | 99.30 32 | 72.02 461 | 98.90 395 | 88.28 418 | 90.17 483 | 95.45 470 |
|
| PCF-MVS | | 89.43 18 | 92.12 395 | 90.64 415 | 96.57 233 | 97.80 319 | 93.48 198 | 89.88 476 | 98.45 252 | 74.46 493 | 96.04 337 | 95.68 396 | 90.71 316 | 99.31 323 | 73.73 488 | 99.01 294 | 96.91 437 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| tpmrst | | | 90.31 418 | 90.61 416 | 89.41 467 | 94.06 477 | 72.37 498 | 95.06 319 | 93.69 429 | 88.01 422 | 92.32 451 | 96.86 335 | 77.45 433 | 98.82 404 | 91.04 360 | 87.01 488 | 97.04 432 |
|
| ADS-MVSNet2 | | | 91.47 408 | 90.51 417 | 94.36 385 | 95.51 445 | 85.63 412 | 95.05 320 | 95.70 397 | 83.46 465 | 92.69 443 | 96.84 337 | 79.15 425 | 99.41 280 | 85.66 447 | 90.52 481 | 98.04 380 |
|
| thres200 | | | 91.00 414 | 90.42 418 | 92.77 432 | 97.47 366 | 83.98 443 | 94.01 368 | 91.18 463 | 95.12 231 | 95.44 364 | 91.21 465 | 73.93 451 | 99.31 323 | 77.76 483 | 97.63 401 | 95.01 473 |
|
| testing3-2 | | | 90.09 420 | 90.38 419 | 89.24 468 | 98.07 280 | 69.88 501 | 95.12 309 | 90.71 469 | 96.65 125 | 93.60 422 | 94.03 428 | 55.81 489 | 99.33 314 | 90.69 379 | 98.71 335 | 98.51 325 |
|
| ADS-MVSNet | | | 90.95 415 | 90.26 420 | 93.04 421 | 95.51 445 | 82.37 454 | 95.05 320 | 93.41 435 | 83.46 465 | 92.69 443 | 96.84 337 | 79.15 425 | 98.70 418 | 85.66 447 | 90.52 481 | 98.04 380 |
|
| MVS-HIRNet | | | 88.40 441 | 90.20 421 | 82.99 478 | 97.01 390 | 60.04 503 | 93.11 402 | 85.61 492 | 84.45 462 | 88.72 480 | 99.09 58 | 84.72 389 | 98.23 457 | 82.52 467 | 96.59 435 | 90.69 493 |
|
| test-LLR | | | 89.97 424 | 89.90 422 | 90.16 462 | 94.24 473 | 74.98 491 | 89.89 473 | 89.06 478 | 92.02 350 | 89.97 471 | 90.77 469 | 73.92 452 | 98.57 432 | 91.88 342 | 97.36 410 | 96.92 435 |
|
| E-PMN | | | 89.52 431 | 89.78 423 | 88.73 470 | 93.14 484 | 77.61 481 | 83.26 493 | 92.02 452 | 94.82 247 | 93.71 415 | 93.11 435 | 75.31 446 | 96.81 479 | 85.81 444 | 96.81 425 | 91.77 490 |
|
| ET-MVSNet_ETH3D | | | 91.12 410 | 89.67 424 | 95.47 326 | 96.41 408 | 89.15 331 | 91.54 444 | 90.23 474 | 89.07 406 | 86.78 488 | 92.84 445 | 69.39 469 | 99.44 263 | 94.16 280 | 96.61 434 | 97.82 396 |
|
| CostFormer | | | 89.75 427 | 89.25 425 | 91.26 457 | 94.69 466 | 78.00 479 | 95.32 295 | 91.98 453 | 81.50 474 | 90.55 463 | 96.96 330 | 71.06 464 | 98.89 396 | 88.59 414 | 92.63 477 | 96.87 438 |
|
| EMVS | | | 89.06 434 | 89.22 426 | 88.61 471 | 93.00 486 | 77.34 483 | 82.91 494 | 90.92 464 | 94.64 255 | 92.63 447 | 91.81 459 | 76.30 441 | 97.02 476 | 83.83 462 | 96.90 420 | 91.48 491 |
|
| test0.0.03 1 | | | 90.11 419 | 89.21 427 | 92.83 430 | 93.89 479 | 86.87 395 | 91.74 440 | 88.74 481 | 92.02 350 | 94.71 386 | 91.14 466 | 73.92 452 | 94.48 492 | 83.75 464 | 92.94 475 | 97.16 429 |
|
| MVS | | | 90.02 421 | 89.20 428 | 92.47 440 | 94.71 465 | 86.90 394 | 95.86 248 | 96.74 378 | 64.72 496 | 90.62 461 | 92.77 446 | 92.54 282 | 98.39 447 | 79.30 478 | 95.56 461 | 92.12 488 |
|
| CHOSEN 280x420 | | | 89.98 423 | 89.19 429 | 92.37 442 | 95.60 444 | 81.13 465 | 86.22 486 | 97.09 361 | 81.44 475 | 87.44 485 | 93.15 434 | 73.99 450 | 99.47 245 | 88.69 412 | 99.07 287 | 96.52 452 |
|
| thisisatest0515 | | | 90.43 417 | 89.18 430 | 94.17 395 | 97.07 389 | 85.44 415 | 89.75 477 | 87.58 486 | 88.28 419 | 93.69 418 | 91.72 460 | 65.27 473 | 99.58 203 | 90.59 381 | 98.67 339 | 97.50 420 |
|
| test2506 | | | 89.86 426 | 89.16 431 | 91.97 449 | 98.95 133 | 76.83 486 | 98.54 26 | 61.07 504 | 96.20 155 | 97.07 264 | 99.16 49 | 55.19 493 | 99.69 143 | 96.43 133 | 99.83 54 | 99.38 143 |
|
| pmmvs3 | | | 90.00 422 | 88.90 432 | 93.32 410 | 94.20 475 | 85.34 417 | 91.25 454 | 92.56 448 | 78.59 485 | 93.82 410 | 95.17 407 | 67.36 472 | 98.69 420 | 89.08 407 | 98.03 377 | 95.92 460 |
|
| FPMVS | | | 89.92 425 | 88.63 433 | 93.82 399 | 98.37 240 | 96.94 48 | 91.58 443 | 93.34 436 | 88.00 423 | 90.32 466 | 97.10 318 | 70.87 465 | 91.13 496 | 71.91 492 | 96.16 447 | 93.39 486 |
|
| testing91 | | | 89.67 429 | 88.55 434 | 93.04 421 | 95.90 427 | 81.80 459 | 92.71 412 | 93.71 428 | 93.71 295 | 90.18 468 | 90.15 473 | 57.11 482 | 99.22 351 | 87.17 435 | 96.32 442 | 98.12 368 |
|
| EPMVS | | | 89.26 432 | 88.55 434 | 91.39 455 | 92.36 490 | 79.11 474 | 95.65 265 | 79.86 497 | 88.60 414 | 93.12 434 | 96.53 357 | 70.73 466 | 98.10 462 | 90.75 373 | 89.32 485 | 96.98 433 |
|
| baseline2 | | | 89.65 430 | 88.44 436 | 93.25 413 | 95.62 443 | 82.71 450 | 93.82 377 | 85.94 491 | 88.89 410 | 87.35 486 | 92.54 450 | 71.23 463 | 99.33 314 | 86.01 441 | 94.60 470 | 97.72 406 |
|
| testing3 | | | 89.72 428 | 88.26 437 | 94.10 396 | 97.66 344 | 84.30 440 | 94.80 334 | 88.25 482 | 94.66 253 | 95.07 373 | 92.51 451 | 41.15 503 | 99.43 266 | 91.81 347 | 98.44 360 | 98.55 318 |
|
| dp | | | 88.08 445 | 88.05 438 | 88.16 475 | 92.85 487 | 68.81 502 | 94.17 359 | 92.88 441 | 85.47 448 | 91.38 459 | 96.14 379 | 68.87 470 | 98.81 406 | 86.88 436 | 83.80 491 | 96.87 438 |
|
| testing99 | | | 89.21 433 | 88.04 439 | 92.70 434 | 95.78 436 | 81.00 466 | 92.65 413 | 92.03 451 | 93.20 318 | 89.90 473 | 90.08 475 | 55.25 491 | 99.14 361 | 87.54 428 | 95.95 448 | 97.97 385 |
|
| KD-MVS_2432*1600 | | | 88.93 435 | 87.74 440 | 92.49 438 | 88.04 500 | 81.99 456 | 89.63 478 | 95.62 400 | 91.35 373 | 95.06 374 | 93.11 435 | 56.58 484 | 98.63 427 | 85.19 452 | 95.07 463 | 96.85 440 |
|
| miper_refine_blended | | | 88.93 435 | 87.74 440 | 92.49 438 | 88.04 500 | 81.99 456 | 89.63 478 | 95.62 400 | 91.35 373 | 95.06 374 | 93.11 435 | 56.58 484 | 98.63 427 | 85.19 452 | 95.07 463 | 96.85 440 |
|
| myMVS_eth3d28 | | | 88.32 442 | 87.73 442 | 90.11 465 | 96.42 407 | 74.96 494 | 92.21 428 | 92.37 449 | 93.56 301 | 90.14 469 | 89.61 476 | 56.13 487 | 98.05 464 | 81.84 468 | 97.26 415 | 97.33 426 |
|
| tpm2 | | | 88.47 440 | 87.69 443 | 90.79 459 | 94.98 461 | 77.34 483 | 95.09 313 | 91.83 454 | 77.51 490 | 89.40 476 | 96.41 364 | 67.83 471 | 98.73 414 | 83.58 465 | 92.60 478 | 96.29 457 |
|
| testing11 | | | 88.93 435 | 87.63 444 | 92.80 431 | 95.87 429 | 81.49 461 | 92.48 417 | 91.54 457 | 91.62 359 | 88.27 482 | 90.24 471 | 55.12 494 | 99.11 368 | 87.30 433 | 96.28 444 | 97.81 398 |
|
| tpm cat1 | | | 88.01 446 | 87.33 445 | 90.05 466 | 94.48 468 | 76.28 488 | 94.47 347 | 94.35 424 | 73.84 495 | 89.26 477 | 95.61 400 | 73.64 454 | 98.30 454 | 84.13 459 | 86.20 489 | 95.57 469 |
|
| UBG | | | 88.29 443 | 87.17 446 | 91.63 452 | 96.08 422 | 78.21 476 | 91.61 441 | 91.50 458 | 89.67 400 | 89.71 474 | 88.97 478 | 59.01 479 | 98.91 393 | 81.28 472 | 96.72 430 | 97.77 401 |
|
| test-mter | | | 87.92 447 | 87.17 446 | 90.16 462 | 94.24 473 | 74.98 491 | 89.89 473 | 89.06 478 | 86.44 439 | 89.97 471 | 90.77 469 | 54.96 495 | 98.57 432 | 91.88 342 | 97.36 410 | 96.92 435 |
|
| dmvs_testset | | | 87.30 452 | 86.99 448 | 88.24 473 | 96.71 399 | 77.48 482 | 94.68 340 | 86.81 490 | 92.64 340 | 89.61 475 | 87.01 489 | 85.91 376 | 93.12 494 | 61.04 496 | 88.49 486 | 94.13 481 |
|
| gg-mvs-nofinetune | | | 88.28 444 | 86.96 449 | 92.23 446 | 92.84 488 | 84.44 436 | 98.19 56 | 74.60 500 | 99.08 16 | 87.01 487 | 99.47 16 | 56.93 483 | 98.23 457 | 78.91 479 | 95.61 460 | 94.01 482 |
|
| IB-MVS | | 85.98 20 | 88.63 439 | 86.95 450 | 93.68 404 | 95.12 456 | 84.82 431 | 90.85 463 | 90.17 475 | 87.55 427 | 88.48 481 | 91.34 464 | 58.01 480 | 99.59 200 | 87.24 434 | 93.80 474 | 96.63 450 |
| 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 | | | 87.57 450 | 86.72 451 | 90.13 464 | 95.21 453 | 73.56 495 | 91.94 435 | 83.78 495 | 88.73 413 | 93.00 436 | 92.87 444 | 55.22 492 | 99.25 343 | 81.74 469 | 97.96 379 | 97.59 415 |
|
| TESTMET0.1,1 | | | 87.20 453 | 86.57 452 | 89.07 469 | 93.62 482 | 72.84 497 | 89.89 473 | 87.01 489 | 85.46 449 | 89.12 478 | 90.20 472 | 56.00 488 | 97.72 469 | 90.91 365 | 96.92 418 | 96.64 448 |
|
| blend_shiyan4 | | | 88.73 438 | 86.43 453 | 95.61 313 | 95.31 452 | 89.17 327 | 92.13 430 | 97.10 359 | 91.59 364 | 94.15 401 | 87.38 485 | 52.97 498 | 99.40 282 | 91.84 344 | 75.42 496 | 98.27 354 |
|
| MVE |  | 73.61 22 | 86.48 455 | 85.92 454 | 88.18 474 | 96.23 413 | 85.28 421 | 81.78 495 | 75.79 499 | 86.01 441 | 82.53 492 | 91.88 458 | 92.74 271 | 87.47 498 | 71.42 493 | 94.86 467 | 91.78 489 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| PAPM | | | 87.64 448 | 85.84 455 | 93.04 421 | 96.54 403 | 84.99 426 | 88.42 482 | 95.57 403 | 79.52 482 | 83.82 490 | 93.05 441 | 80.57 416 | 98.41 445 | 62.29 495 | 92.79 476 | 95.71 465 |
|
| ETVMVS | | | 87.62 449 | 85.75 456 | 93.22 415 | 96.15 420 | 83.26 447 | 92.94 404 | 90.37 472 | 91.39 372 | 90.37 465 | 88.45 481 | 51.93 499 | 98.64 426 | 73.76 487 | 96.38 440 | 97.75 402 |
|
| myMVS_eth3d | | | 87.16 454 | 85.61 457 | 91.82 450 | 95.19 454 | 79.32 472 | 92.46 418 | 91.35 459 | 90.67 386 | 91.76 456 | 87.61 483 | 41.96 502 | 98.50 439 | 82.66 466 | 96.84 422 | 97.65 409 |
|
| testing222 | | | 87.35 451 | 85.50 458 | 92.93 428 | 95.79 435 | 82.83 449 | 92.40 423 | 90.10 476 | 92.80 337 | 88.87 479 | 89.02 477 | 48.34 501 | 98.70 418 | 75.40 486 | 96.74 428 | 97.27 428 |
|
| PVSNet_0 | | 81.89 21 | 84.49 456 | 83.21 459 | 88.34 472 | 95.76 438 | 74.97 493 | 83.49 492 | 92.70 445 | 78.47 486 | 87.94 483 | 86.90 490 | 83.38 400 | 96.63 484 | 73.44 490 | 66.86 498 | 93.40 485 |
|
| UWE-MVS-28 | | | 83.78 457 | 82.36 460 | 88.03 476 | 90.72 494 | 71.58 499 | 93.64 384 | 77.87 498 | 87.62 426 | 85.91 489 | 92.89 443 | 59.94 477 | 95.99 487 | 56.06 498 | 96.56 436 | 96.52 452 |
|
| 0.4-1-1-0.1 | | | 83.64 458 | 80.50 461 | 93.08 419 | 90.32 496 | 85.42 416 | 86.48 484 | 87.71 485 | 83.60 464 | 80.38 496 | 75.45 495 | 53.19 497 | 98.91 393 | 86.46 439 | 80.88 493 | 94.93 475 |
|
| 0.4-1-1-0.2 | | | 82.53 460 | 79.25 462 | 92.37 442 | 88.10 499 | 83.96 444 | 83.72 491 | 88.15 483 | 82.14 470 | 78.97 497 | 72.49 497 | 53.22 496 | 98.84 402 | 85.99 442 | 80.50 494 | 94.30 480 |
|
| 0.3-1-1-0.015 | | | 82.33 461 | 78.89 463 | 92.66 435 | 88.57 498 | 84.69 432 | 84.76 489 | 88.02 484 | 82.48 469 | 77.55 498 | 72.96 496 | 49.60 500 | 98.87 400 | 86.05 440 | 80.02 495 | 94.43 477 |
|
| EGC-MVSNET | | | 83.08 459 | 77.93 464 | 98.53 54 | 99.57 20 | 97.55 29 | 98.33 42 | 98.57 243 | 4.71 501 | 10.38 502 | 98.90 85 | 95.60 175 | 99.50 230 | 95.69 175 | 99.61 126 | 98.55 318 |
|
| test_method | | | 66.88 462 | 66.13 465 | 69.11 480 | 62.68 505 | 25.73 508 | 49.76 496 | 96.04 389 | 14.32 500 | 64.27 500 | 91.69 461 | 73.45 457 | 88.05 497 | 76.06 485 | 66.94 497 | 93.54 483 |
|
| dongtai | | | 63.43 463 | 63.37 466 | 63.60 481 | 83.91 503 | 53.17 505 | 85.14 487 | 43.40 507 | 77.91 489 | 80.96 494 | 79.17 494 | 36.36 504 | 77.10 499 | 37.88 499 | 45.63 499 | 60.54 496 |
|
| tmp_tt | | | 57.23 464 | 62.50 467 | 41.44 483 | 34.77 506 | 49.21 507 | 83.93 490 | 60.22 505 | 15.31 499 | 71.11 499 | 79.37 493 | 70.09 468 | 44.86 502 | 64.76 494 | 82.93 492 | 30.25 498 |
|
| kuosan | | | 54.81 465 | 54.94 468 | 54.42 482 | 74.43 504 | 50.03 506 | 84.98 488 | 44.27 506 | 61.80 497 | 62.49 501 | 70.43 498 | 35.16 505 | 58.04 501 | 19.30 500 | 41.61 500 | 55.19 497 |
|
| cdsmvs_eth3d_5k | | | 24.22 466 | 32.30 469 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 98.10 302 | 0.00 504 | 0.00 505 | 95.06 410 | 97.54 45 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| test123 | | | 12.59 467 | 15.49 470 | 3.87 484 | 6.07 507 | 2.55 509 | 90.75 465 | 2.59 509 | 2.52 502 | 5.20 504 | 13.02 501 | 4.96 506 | 1.85 504 | 5.20 501 | 9.09 501 | 7.23 499 |
|
| testmvs | | | 12.33 468 | 15.23 471 | 3.64 485 | 5.77 508 | 2.23 510 | 88.99 480 | 3.62 508 | 2.30 503 | 5.29 503 | 13.09 500 | 4.52 507 | 1.95 503 | 5.16 502 | 8.32 502 | 6.75 500 |
|
| pcd_1.5k_mvsjas | | | 7.98 469 | 10.65 472 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 95.82 161 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| ab-mvs-re | | | 7.91 470 | 10.55 473 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 94.94 412 | 0.00 508 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| mmdepth | | | 0.00 471 | 0.00 474 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 0.00 508 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| monomultidepth | | | 0.00 471 | 0.00 474 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 0.00 508 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| test_blank | | | 0.00 471 | 0.00 474 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 0.00 508 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| uanet_test | | | 0.00 471 | 0.00 474 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 0.00 508 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| DCPMVS | | | 0.00 471 | 0.00 474 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 0.00 508 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| sosnet-low-res | | | 0.00 471 | 0.00 474 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 0.00 508 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| sosnet | | | 0.00 471 | 0.00 474 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 0.00 508 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| uncertanet | | | 0.00 471 | 0.00 474 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 0.00 508 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| Regformer | | | 0.00 471 | 0.00 474 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 0.00 508 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| uanet | | | 0.00 471 | 0.00 474 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 0.00 508 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| MED-MVS test | | | | | 98.17 87 | 99.36 54 | 95.35 117 | 97.75 87 | 99.30 41 | 94.02 286 | 98.88 76 | 97.54 274 | | 99.73 100 | 95.36 207 | 99.53 164 | 99.44 121 |
|
| TestfortrainingZip | | | | | 97.39 161 | 97.24 382 | 94.58 151 | 97.75 87 | 97.64 338 | 96.08 170 | 96.48 310 | 96.31 370 | 92.56 278 | 99.27 338 | | 96.62 433 | 98.31 347 |
|
| WAC-MVS | | | | | | | 79.32 472 | | | | | | | | 85.41 450 | | |
|
| FOURS1 | | | | | | 99.59 18 | 98.20 7 | 99.03 8 | 99.25 50 | 98.96 24 | 98.87 79 | | | | | | |
|
| MSC_two_6792asdad | | | | | 98.22 83 | 97.75 331 | 95.34 122 | | 98.16 296 | | | | | 99.75 84 | 95.87 167 | 99.51 178 | 99.57 58 |
|
| PC_three_1452 | | | | | | | | | | 87.24 429 | 98.37 135 | 97.44 285 | 97.00 81 | 96.78 481 | 92.01 338 | 99.25 259 | 99.21 189 |
|
| No_MVS | | | | | 98.22 83 | 97.75 331 | 95.34 122 | | 98.16 296 | | | | | 99.75 84 | 95.87 167 | 99.51 178 | 99.57 58 |
|
| test_one_0601 | | | | | | 99.05 119 | 95.50 109 | | 98.87 166 | 97.21 103 | 98.03 187 | 98.30 173 | 96.93 89 | | | | |
|
| eth-test2 | | | | | | 0.00 509 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 509 | | | | | | | | | | | |
|
| ZD-MVS | | | | | | 98.43 234 | 95.94 86 | | 98.56 244 | 90.72 384 | 96.66 297 | 97.07 319 | 95.02 202 | 99.74 94 | 91.08 359 | 98.93 304 | |
|
| IU-MVS | | | | | | 99.22 78 | 95.40 112 | | 98.14 299 | 85.77 446 | 98.36 138 | | | | 95.23 217 | 99.51 178 | 99.49 95 |
|
| OPU-MVS | | | | | 97.64 134 | 98.01 286 | 95.27 125 | 96.79 162 | | | | 97.35 297 | 96.97 85 | 98.51 438 | 91.21 358 | 99.25 259 | 99.14 207 |
|
| test_241102_TWO | | | | | | | | | 98.83 184 | 96.11 166 | 98.62 105 | 98.24 185 | 96.92 92 | 99.72 110 | 95.44 199 | 99.49 185 | 99.49 95 |
|
| test_241102_ONE | | | | | | 99.22 78 | 95.35 117 | | 98.83 184 | 96.04 175 | 99.08 54 | 98.13 201 | 97.87 28 | 99.33 314 | | | |
|
| save fliter | | | | | | 98.48 227 | 94.71 143 | 94.53 346 | 98.41 260 | 95.02 237 | | | | | | | |
|
| test_0728_THIRD | | | | | | | | | | 96.62 126 | 98.40 132 | 98.28 178 | 97.10 69 | 99.71 126 | 95.70 173 | 99.62 116 | 99.58 50 |
|
| test_0728_SECOND | | | | | 98.25 81 | 99.23 75 | 95.49 110 | 96.74 166 | 98.89 157 | | | | | 99.75 84 | 95.48 194 | 99.52 173 | 99.53 77 |
|
| test0726 | | | | | | 99.24 72 | 95.51 106 | 96.89 152 | 98.89 157 | 95.92 186 | 98.64 103 | 98.31 167 | 97.06 74 | | | | |
|
| GSMVS | | | | | | | | | | | | | | | | | 98.06 376 |
|
| test_part2 | | | | | | 99.03 121 | 96.07 80 | | | | 98.08 180 | | | | | | |
|
| sam_mvs1 | | | | | | | | | | | | | 77.80 430 | | | | 98.06 376 |
|
| sam_mvs | | | | | | | | | | | | | 77.38 434 | | | | |
|
| ambc | | | | | 96.56 235 | 98.23 259 | 91.68 257 | 97.88 77 | 98.13 300 | | 98.42 129 | 98.56 132 | 94.22 232 | 99.04 379 | 94.05 286 | 99.35 234 | 98.95 251 |
|
| MTGPA |  | | | | | | | | 98.73 210 | | | | | | | | |
|
| test_post1 | | | | | | | | 94.98 324 | | | | 10.37 503 | 76.21 442 | 99.04 379 | 89.47 401 | | |
|
| test_post | | | | | | | | | | | | 10.87 502 | 76.83 438 | 99.07 375 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 96.84 337 | 77.36 435 | 99.42 270 | | | |
|
| GG-mvs-BLEND | | | | | 90.60 460 | 91.00 492 | 84.21 441 | 98.23 50 | 72.63 503 | | 82.76 491 | 84.11 492 | 56.14 486 | 96.79 480 | 72.20 491 | 92.09 480 | 90.78 492 |
|
| MTMP | | | | | | | | 96.55 178 | 74.60 500 | | | | | | | | |
|
| gm-plane-assit | | | | | | 91.79 491 | 71.40 500 | | | 81.67 472 | | 90.11 474 | | 98.99 385 | 84.86 456 | | |
|
| test9_res | | | | | | | | | | | | | | | 91.29 354 | 98.89 311 | 99.00 238 |
|
| TEST9 | | | | | | 97.84 307 | 95.23 127 | 93.62 385 | 98.39 263 | 86.81 435 | 93.78 411 | 95.99 384 | 94.68 213 | 99.52 225 | | | |
|
| test_8 | | | | | | 97.81 315 | 95.07 136 | 93.54 389 | 98.38 265 | 87.04 431 | 93.71 415 | 95.96 387 | 94.58 218 | 99.52 225 | | | |
|
| agg_prior2 | | | | | | | | | | | | | | | 90.34 389 | 98.90 307 | 99.10 224 |
|
| agg_prior | | | | | | 97.80 319 | 94.96 138 | | 98.36 268 | | 93.49 425 | | | 99.53 222 | | | |
|
| TestCases | | | | | 98.06 100 | 99.08 109 | 96.16 75 | | 99.16 67 | 94.35 272 | 97.78 215 | 98.07 212 | 95.84 158 | 99.12 365 | 91.41 352 | 99.42 214 | 98.91 262 |
|
| test_prior4 | | | | | | | 95.38 114 | 93.61 387 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 93.33 396 | | 94.21 276 | 94.02 407 | 96.25 373 | 93.64 248 | | 91.90 341 | 98.96 298 | |
|
| test_prior | | | | | 97.46 153 | 97.79 324 | 94.26 168 | | 98.42 259 | | | | | 99.34 312 | | | 98.79 280 |
|
| 旧先验2 | | | | | | | | 93.35 395 | | 77.95 488 | 95.77 354 | | | 98.67 424 | 90.74 376 | | |
|
| 新几何2 | | | | | | | | 93.43 391 | | | | | | | | | |
|
| 新几何1 | | | | | 97.25 173 | 98.29 247 | 94.70 145 | | 97.73 327 | 77.98 487 | 94.83 381 | 96.67 350 | 92.08 295 | 99.45 260 | 88.17 420 | 98.65 343 | 97.61 413 |
|
| 旧先验1 | | | | | | 97.80 319 | 93.87 180 | | 97.75 326 | | | 97.04 322 | 93.57 249 | | | 98.68 338 | 98.72 297 |
|
| 无先验 | | | | | | | | 93.20 400 | 97.91 315 | 80.78 477 | | | | 99.40 282 | 87.71 423 | | 97.94 388 |
|
| 原ACMM2 | | | | | | | | 92.82 406 | | | | | | | | | |
|
| 原ACMM1 | | | | | 96.58 231 | 98.16 271 | 92.12 241 | | 98.15 298 | 85.90 444 | 93.49 425 | 96.43 363 | 92.47 286 | 99.38 295 | 87.66 425 | 98.62 345 | 98.23 358 |
|
| test222 | | | | | | 98.17 269 | 93.24 208 | 92.74 410 | 97.61 342 | 75.17 492 | 94.65 387 | 96.69 349 | 90.96 313 | | | 98.66 341 | 97.66 408 |
|
| testdata2 | | | | | | | | | | | | | | 99.46 252 | 87.84 421 | | |
|
| segment_acmp | | | | | | | | | | | | | 95.34 186 | | | | |
|
| testdata | | | | | 95.70 308 | 98.16 271 | 90.58 285 | | 97.72 328 | 80.38 479 | 95.62 357 | 97.02 323 | 92.06 296 | 98.98 387 | 89.06 408 | 98.52 351 | 97.54 417 |
|
| testdata1 | | | | | | | | 92.77 407 | | 93.78 293 | | | | | | | |
|
| test12 | | | | | 97.46 153 | 97.61 351 | 94.07 172 | | 97.78 325 | | 93.57 423 | | 93.31 255 | 99.42 270 | | 98.78 322 | 98.89 266 |
|
| plane_prior7 | | | | | | 98.70 183 | 94.67 146 | | | | | | | | | | |
|
| plane_prior6 | | | | | | 98.38 239 | 94.37 161 | | | | | | 91.91 301 | | | | |
|
| plane_prior5 | | | | | | | | | 98.75 207 | | | | | 99.46 252 | 92.59 331 | 99.20 264 | 99.28 171 |
|
| plane_prior4 | | | | | | | | | | | | 96.77 343 | | | | | |
|
| plane_prior3 | | | | | | | 94.51 154 | | | 95.29 224 | 96.16 332 | | | | | | |
|
| plane_prior2 | | | | | | | | 96.50 181 | | 96.36 145 | | | | | | | |
|
| plane_prior1 | | | | | | 98.49 225 | | | | | | | | | | | |
|
| plane_prior | | | | | | | 94.29 164 | 95.42 281 | | 94.31 274 | | | | | | 98.93 304 | |
|
| n2 | | | | | | | | | 0.00 510 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 510 | | | | | | | | |
|
| door-mid | | | | | | | | | 98.17 292 | | | | | | | | |
|
| lessismore_v0 | | | | | 97.05 189 | 99.36 54 | 92.12 241 | | 84.07 493 | | 98.77 91 | 98.98 71 | 85.36 382 | 99.74 94 | 97.34 93 | 99.37 225 | 99.30 163 |
|
| LGP-MVS_train | | | | | 98.74 37 | 99.15 96 | 97.02 45 | | 99.02 120 | 95.15 229 | 98.34 142 | 98.23 187 | 97.91 25 | 99.70 135 | 94.41 269 | 99.73 83 | 99.50 87 |
|
| test11 | | | | | | | | | 98.08 304 | | | | | | | | |
|
| door | | | | | | | | | 97.81 324 | | | | | | | | |
|
| HQP5-MVS | | | | | | | 92.47 227 | | | | | | | | | | |
|
| HQP-NCC | | | | | | 97.85 301 | | 94.26 351 | | 93.18 320 | 92.86 439 | | | | | | |
|
| ACMP_Plane | | | | | | 97.85 301 | | 94.26 351 | | 93.18 320 | 92.86 439 | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 90.51 384 | | |
|
| HQP4-MVS | | | | | | | | | | | 92.87 438 | | | 99.23 349 | | | 99.06 230 |
|
| HQP3-MVS | | | | | | | | | 98.43 256 | | | | | | | 98.74 331 | |
|
| HQP2-MVS | | | | | | | | | | | | | 90.33 322 | | | | |
|
| NP-MVS | | | | | | 98.14 275 | 93.72 186 | | | | | 95.08 408 | | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 57.28 504 | 94.89 328 | | 80.59 478 | 94.02 407 | | 78.66 427 | | 85.50 449 | | 97.82 396 |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 99.52 173 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 99.55 154 | |
|
| Test By Simon | | | | | | | | | | | | | 94.51 222 | | | | |
|
| ITE_SJBPF | | | | | 97.85 116 | 98.64 190 | 96.66 57 | | 98.51 248 | 95.63 203 | 97.22 247 | 97.30 301 | 95.52 177 | 98.55 435 | 90.97 363 | 98.90 307 | 98.34 344 |
|
| DeepMVS_CX |  | | | | 77.17 479 | 90.94 493 | 85.28 421 | | 74.08 502 | 52.51 498 | 80.87 495 | 88.03 482 | 75.25 447 | 70.63 500 | 59.23 497 | 84.94 490 | 75.62 494 |
|