| test_fmvsm_n_1920 | | | 97.55 16 | 97.89 3 | 96.53 106 | 98.41 86 | 91.73 131 | 98.01 67 | 99.02 1 | 96.37 13 | 99.30 7 | 98.92 23 | 92.39 44 | 99.79 46 | 99.16 14 | 99.46 46 | 98.08 230 |
|
| PGM-MVS | | | 96.81 58 | 96.53 69 | 97.65 48 | 99.35 25 | 93.53 66 | 97.65 130 | 98.98 2 | 92.22 179 | 97.14 77 | 98.44 64 | 91.17 71 | 99.85 21 | 94.35 163 | 99.46 46 | 99.57 36 |
|
| MVS_111021_HR | | | 96.68 69 | 96.58 68 | 96.99 85 | 98.46 80 | 92.31 111 | 96.20 306 | 98.90 3 | 94.30 86 | 95.86 136 | 97.74 145 | 92.33 45 | 99.38 137 | 96.04 96 | 99.42 56 | 99.28 77 |
|
| test_fmvsmconf_n | | | 97.49 21 | 97.56 16 | 97.29 65 | 97.44 165 | 92.37 108 | 97.91 86 | 98.88 4 | 95.83 19 | 98.92 23 | 99.05 14 | 91.45 61 | 99.80 40 | 99.12 16 | 99.46 46 | 99.69 14 |
|
| lecture | | | 97.58 15 | 97.63 12 | 97.43 59 | 99.37 19 | 92.93 87 | 98.86 7 | 98.85 5 | 95.27 34 | 98.65 36 | 98.90 25 | 91.97 52 | 99.80 40 | 97.63 37 | 99.21 83 | 99.57 36 |
|
| ACMMP |  | | 96.27 86 | 95.93 88 | 97.28 67 | 99.24 33 | 92.62 99 | 98.25 40 | 98.81 6 | 92.99 141 | 94.56 184 | 98.39 68 | 88.96 102 | 99.85 21 | 94.57 157 | 97.63 163 | 99.36 72 |
| 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 |
| MVS_111021_LR | | | 96.24 87 | 96.19 85 | 96.39 125 | 98.23 106 | 91.35 154 | 96.24 303 | 98.79 7 | 93.99 96 | 95.80 138 | 97.65 155 | 89.92 91 | 99.24 151 | 95.87 100 | 99.20 88 | 98.58 173 |
|
| patch_mono-2 | | | 96.83 57 | 97.44 24 | 95.01 228 | 99.05 45 | 85.39 380 | 96.98 219 | 98.77 8 | 94.70 66 | 97.99 52 | 98.66 43 | 93.61 22 | 99.91 1 | 97.67 36 | 99.50 40 | 99.72 13 |
|
| fmvsm_s_conf0.5_n | | | 96.85 54 | 97.13 31 | 96.04 152 | 98.07 121 | 90.28 207 | 97.97 78 | 98.76 9 | 94.93 48 | 98.84 28 | 99.06 12 | 88.80 106 | 99.65 79 | 99.06 18 | 98.63 123 | 98.18 215 |
|
| fmvsm_l_conf0.5_n | | | 97.65 9 | 97.75 8 | 97.34 62 | 98.21 107 | 92.75 93 | 97.83 99 | 98.73 10 | 95.04 45 | 99.30 7 | 98.84 36 | 93.34 25 | 99.78 49 | 99.32 7 | 99.13 97 | 99.50 52 |
|
| fmvsm_s_conf0.5_n_a | | | 96.75 62 | 96.93 46 | 96.20 141 | 97.64 151 | 90.72 188 | 98.00 68 | 98.73 10 | 94.55 73 | 98.91 24 | 99.08 8 | 88.22 118 | 99.63 88 | 98.91 21 | 98.37 136 | 98.25 210 |
|
| fmvsm_s_conf0.5_n_10 | | | 97.29 31 | 97.40 26 | 96.97 87 | 98.24 101 | 91.96 127 | 97.89 89 | 98.72 12 | 96.77 7 | 99.46 3 | 99.06 12 | 87.78 127 | 99.84 26 | 99.40 4 | 99.27 75 | 99.12 93 |
|
| fmvsm_l_conf0.5_n_9 | | | 97.59 13 | 97.79 6 | 96.97 87 | 98.28 95 | 91.49 145 | 97.61 139 | 98.71 13 | 97.10 5 | 99.70 1 | 98.93 22 | 90.95 76 | 99.77 52 | 99.35 6 | 99.53 33 | 99.65 20 |
|
| FC-MVSNet-test | | | 93.94 184 | 93.57 176 | 95.04 226 | 95.48 318 | 91.45 150 | 98.12 56 | 98.71 13 | 93.37 123 | 90.23 298 | 96.70 224 | 87.66 129 | 97.85 352 | 91.49 227 | 90.39 338 | 95.83 327 |
|
| UniMVSNet (Re) | | | 93.31 211 | 92.55 224 | 95.61 192 | 95.39 324 | 93.34 72 | 97.39 174 | 98.71 13 | 93.14 136 | 90.10 307 | 94.83 326 | 87.71 128 | 98.03 325 | 91.67 225 | 83.99 414 | 95.46 346 |
|
| MED-MVS test | | | | | 98.00 24 | 99.56 1 | 94.50 36 | 98.69 11 | 98.70 16 | 93.45 119 | 98.73 30 | 98.53 51 | | 99.86 9 | 97.40 49 | 99.58 23 | 99.65 20 |
|
| MED-MVS | | | 97.91 4 | 97.88 4 | 98.00 24 | 99.56 1 | 94.50 36 | 98.69 11 | 98.70 16 | 94.23 87 | 98.73 30 | 98.53 51 | 95.46 7 | 99.86 9 | 97.40 49 | 99.58 23 | 99.65 20 |
|
| TestfortrainingZip a | | | 97.92 3 | 97.70 10 | 98.58 3 | 99.56 1 | 96.08 6 | 98.69 11 | 98.70 16 | 93.45 119 | 98.73 30 | 98.53 51 | 95.46 7 | 99.86 9 | 96.63 69 | 99.58 23 | 99.80 1 |
|
| fmvsm_l_conf0.5_n_a | | | 97.63 11 | 97.76 7 | 97.26 69 | 98.25 100 | 92.59 101 | 97.81 104 | 98.68 19 | 94.93 48 | 99.24 10 | 98.87 31 | 93.52 23 | 99.79 46 | 99.32 7 | 99.21 83 | 99.40 66 |
|
| FIs | | | 94.09 175 | 93.70 172 | 95.27 215 | 95.70 307 | 92.03 123 | 98.10 57 | 98.68 19 | 93.36 125 | 90.39 295 | 96.70 224 | 87.63 132 | 97.94 343 | 92.25 205 | 90.50 337 | 95.84 326 |
|
| WR-MVS_H | | | 92.00 268 | 91.35 265 | 93.95 301 | 95.09 351 | 89.47 243 | 98.04 64 | 98.68 19 | 91.46 211 | 88.34 360 | 94.68 333 | 85.86 170 | 97.56 384 | 85.77 364 | 84.24 412 | 94.82 399 |
|
| fmvsm_s_conf0.5_n_4 | | | 96.75 62 | 97.07 34 | 95.79 176 | 97.76 142 | 89.57 236 | 97.66 129 | 98.66 22 | 95.36 30 | 99.03 16 | 98.90 25 | 88.39 114 | 99.73 61 | 99.17 13 | 98.66 121 | 98.08 230 |
|
| VPA-MVSNet | | | 93.24 213 | 92.48 229 | 95.51 202 | 95.70 307 | 92.39 107 | 97.86 92 | 98.66 22 | 92.30 176 | 92.09 256 | 95.37 301 | 80.49 294 | 98.40 276 | 93.95 169 | 85.86 385 | 95.75 335 |
|
| fmvsm_l_conf0.5_n_3 | | | 97.64 10 | 97.60 13 | 97.79 35 | 98.14 114 | 93.94 57 | 97.93 84 | 98.65 24 | 96.70 8 | 99.38 5 | 99.07 11 | 89.92 91 | 99.81 35 | 99.16 14 | 99.43 53 | 99.61 30 |
|
| fmvsm_s_conf0.5_n_3 | | | 97.15 36 | 97.36 28 | 96.52 108 | 97.98 126 | 91.19 162 | 97.84 96 | 98.65 24 | 97.08 6 | 99.25 9 | 99.10 6 | 87.88 125 | 99.79 46 | 99.32 7 | 99.18 90 | 98.59 172 |
|
| fmvsm_s_conf0.5_n_8 | | | 97.32 28 | 97.48 23 | 96.85 89 | 98.28 95 | 91.07 170 | 97.76 109 | 98.62 26 | 97.53 2 | 99.20 12 | 99.12 5 | 88.24 117 | 99.81 35 | 99.41 3 | 99.17 91 | 99.67 15 |
|
| fmvsm_s_conf0.5_n_2 | | | 96.62 70 | 96.82 55 | 96.02 154 | 97.98 126 | 90.43 198 | 97.50 154 | 98.59 27 | 96.59 10 | 99.31 6 | 99.08 8 | 84.47 204 | 99.75 58 | 99.37 5 | 98.45 133 | 97.88 243 |
|
| UniMVSNet_NR-MVSNet | | | 93.37 209 | 92.67 218 | 95.47 208 | 95.34 330 | 92.83 90 | 97.17 202 | 98.58 28 | 92.98 146 | 90.13 303 | 95.80 277 | 88.37 116 | 97.85 352 | 91.71 222 | 83.93 415 | 95.73 337 |
|
| CSCG | | | 96.05 90 | 95.91 89 | 96.46 118 | 99.24 33 | 90.47 195 | 98.30 33 | 98.57 29 | 89.01 306 | 93.97 204 | 97.57 166 | 92.62 40 | 99.76 54 | 94.66 151 | 99.27 75 | 99.15 87 |
|
| fmvsm_s_conf0.5_n_9 | | | 97.33 27 | 97.57 15 | 96.62 102 | 98.43 83 | 90.32 206 | 97.80 105 | 98.53 30 | 97.24 4 | 99.62 2 | 99.14 2 | 88.65 109 | 99.80 40 | 99.54 1 | 99.15 94 | 99.74 9 |
|
| fmvsm_s_conf0.5_n_6 | | | 97.08 39 | 97.17 30 | 96.81 90 | 97.28 170 | 91.73 131 | 97.75 111 | 98.50 31 | 94.86 52 | 99.22 11 | 98.78 40 | 89.75 94 | 99.76 54 | 99.10 17 | 99.29 73 | 98.94 123 |
|
| MSLP-MVS++ | | | 96.94 48 | 97.06 35 | 96.59 103 | 98.72 64 | 91.86 129 | 97.67 126 | 98.49 32 | 94.66 69 | 97.24 73 | 98.41 67 | 92.31 47 | 98.94 196 | 96.61 71 | 99.46 46 | 98.96 116 |
|
| HyFIR lowres test | | | 93.66 196 | 92.92 206 | 95.87 165 | 98.24 101 | 89.88 222 | 94.58 390 | 98.49 32 | 85.06 404 | 93.78 208 | 95.78 281 | 82.86 241 | 98.67 249 | 91.77 220 | 95.71 236 | 99.07 101 |
|
| CHOSEN 1792x2688 | | | 94.15 170 | 93.51 182 | 96.06 150 | 98.27 97 | 89.38 248 | 95.18 372 | 98.48 34 | 85.60 394 | 93.76 209 | 97.11 198 | 83.15 231 | 99.61 91 | 91.33 230 | 98.72 119 | 99.19 83 |
|
| fmvsm_s_conf0.5_n_7 | | | 96.45 77 | 96.80 57 | 95.37 211 | 97.29 169 | 88.38 290 | 97.23 196 | 98.47 35 | 95.14 39 | 98.43 41 | 99.09 7 | 87.58 133 | 99.72 65 | 98.80 25 | 99.21 83 | 98.02 234 |
|
| fmvsm_s_conf0.5_n_5 | | | 97.00 45 | 96.97 43 | 97.09 80 | 97.58 161 | 92.56 102 | 97.68 125 | 98.47 35 | 94.02 94 | 98.90 25 | 98.89 28 | 88.94 103 | 99.78 49 | 99.18 12 | 99.03 106 | 98.93 127 |
|
| PHI-MVS | | | 96.77 60 | 96.46 76 | 97.71 46 | 98.40 87 | 94.07 53 | 98.21 48 | 98.45 37 | 89.86 276 | 97.11 79 | 98.01 104 | 92.52 42 | 99.69 73 | 96.03 97 | 99.53 33 | 99.36 72 |
|
| fmvsm_s_conf0.1_n | | | 96.58 73 | 96.77 60 | 96.01 157 | 96.67 229 | 90.25 208 | 97.91 86 | 98.38 38 | 94.48 77 | 98.84 28 | 99.14 2 | 88.06 120 | 99.62 90 | 98.82 23 | 98.60 125 | 98.15 219 |
|
| PVSNet_BlendedMVS | | | 94.06 176 | 93.92 166 | 94.47 266 | 98.27 97 | 89.46 245 | 96.73 251 | 98.36 39 | 90.17 269 | 94.36 189 | 95.24 309 | 88.02 121 | 99.58 99 | 93.44 183 | 90.72 333 | 94.36 420 |
|
| PVSNet_Blended | | | 94.87 145 | 94.56 143 | 95.81 172 | 98.27 97 | 89.46 245 | 95.47 351 | 98.36 39 | 88.84 315 | 94.36 189 | 96.09 266 | 88.02 121 | 99.58 99 | 93.44 183 | 98.18 145 | 98.40 195 |
|
| 3Dnovator | | 91.36 5 | 95.19 127 | 94.44 152 | 97.44 58 | 96.56 245 | 93.36 71 | 98.65 16 | 98.36 39 | 94.12 91 | 89.25 337 | 98.06 98 | 82.20 258 | 99.77 52 | 93.41 185 | 99.32 71 | 99.18 84 |
|
| FOURS1 | | | | | | 99.55 4 | 93.34 72 | 99.29 1 | 98.35 42 | 94.98 46 | 98.49 39 | | | | | | |
|
| DPE-MVS |  | | 97.86 6 | 97.65 11 | 98.47 6 | 99.17 38 | 95.78 9 | 97.21 199 | 98.35 42 | 95.16 38 | 98.71 35 | 98.80 38 | 95.05 12 | 99.89 3 | 96.70 68 | 99.73 1 | 99.73 12 |
| Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025 |
| ME-MVS | | | 97.54 17 | 97.39 27 | 98.00 24 | 99.21 36 | 94.50 36 | 97.75 111 | 98.34 44 | 94.23 87 | 98.15 47 | 98.53 51 | 93.32 28 | 99.84 26 | 97.40 49 | 99.58 23 | 99.65 20 |
|
| fmvsm_s_conf0.1_n_a | | | 96.40 79 | 96.47 73 | 96.16 143 | 95.48 318 | 90.69 189 | 97.91 86 | 98.33 45 | 94.07 92 | 98.93 20 | 99.14 2 | 87.44 141 | 99.61 91 | 98.63 26 | 98.32 138 | 98.18 215 |
|
| HFP-MVS | | | 97.14 37 | 96.92 47 | 97.83 31 | 99.42 10 | 94.12 51 | 98.52 20 | 98.32 46 | 93.21 128 | 97.18 74 | 98.29 84 | 92.08 49 | 99.83 31 | 95.63 113 | 99.59 19 | 99.54 45 |
|
| ACMMPR | | | 97.07 41 | 96.84 51 | 97.79 35 | 99.44 9 | 93.88 58 | 98.52 20 | 98.31 47 | 93.21 128 | 97.15 76 | 98.33 78 | 91.35 65 | 99.86 9 | 95.63 113 | 99.59 19 | 99.62 27 |
|
| test_fmvsmvis_n_1920 | | | 96.70 65 | 96.84 51 | 96.31 130 | 96.62 231 | 91.73 131 | 97.98 72 | 98.30 48 | 96.19 14 | 96.10 126 | 98.95 20 | 89.42 95 | 99.76 54 | 98.90 22 | 99.08 101 | 97.43 270 |
|
| APDe-MVS |  | | 97.82 7 | 97.73 9 | 98.08 20 | 99.15 39 | 94.82 30 | 98.81 8 | 98.30 48 | 94.76 64 | 98.30 43 | 98.90 25 | 93.77 20 | 99.68 75 | 97.93 28 | 99.69 3 | 99.75 7 |
| Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition |
| test0726 | | | | | | 99.45 6 | 95.36 15 | 98.31 32 | 98.29 50 | 94.92 50 | 98.99 18 | 98.92 23 | 95.08 10 | | | | |
|
| MSP-MVS | | | 97.59 13 | 97.54 17 | 97.73 43 | 99.40 14 | 93.77 62 | 98.53 19 | 98.29 50 | 95.55 27 | 98.56 38 | 97.81 137 | 93.90 18 | 99.65 79 | 96.62 70 | 99.21 83 | 99.77 3 |
| 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 |
| DVP-MVS++ | | | 98.06 1 | 97.99 1 | 98.28 11 | 98.67 67 | 95.39 13 | 99.29 1 | 98.28 52 | 94.78 61 | 98.93 20 | 98.87 31 | 96.04 2 | 99.86 9 | 97.45 45 | 99.58 23 | 99.59 32 |
|
| test_0728_SECOND | | | | | 98.51 5 | 99.45 6 | 95.93 7 | 98.21 48 | 98.28 52 | | | | | 99.86 9 | 97.52 41 | 99.67 6 | 99.75 7 |
|
| CP-MVS | | | 97.02 43 | 96.81 56 | 97.64 50 | 99.33 26 | 93.54 65 | 98.80 9 | 98.28 52 | 92.99 141 | 96.45 112 | 98.30 83 | 91.90 53 | 99.85 21 | 95.61 115 | 99.68 4 | 99.54 45 |
|
| test_fmvsmconf0.1_n | | | 97.09 38 | 97.06 35 | 97.19 74 | 95.67 309 | 92.21 115 | 97.95 81 | 98.27 55 | 95.78 23 | 98.40 42 | 99.00 16 | 89.99 89 | 99.78 49 | 99.06 18 | 99.41 59 | 99.59 32 |
|
| SED-MVS | | | 98.05 2 | 97.99 1 | 98.24 12 | 99.42 10 | 95.30 19 | 98.25 40 | 98.27 55 | 95.13 40 | 99.19 13 | 98.89 28 | 95.54 5 | 99.85 21 | 97.52 41 | 99.66 10 | 99.56 40 |
|
| test_241102_TWO | | | | | | | | | 98.27 55 | 95.13 40 | 98.93 20 | 98.89 28 | 94.99 13 | 99.85 21 | 97.52 41 | 99.65 13 | 99.74 9 |
|
| test_241102_ONE | | | | | | 99.42 10 | 95.30 19 | | 98.27 55 | 95.09 43 | 99.19 13 | 98.81 37 | 95.54 5 | 99.65 79 | | | |
|
| SF-MVS | | | 97.39 24 | 97.13 31 | 98.17 17 | 99.02 48 | 95.28 21 | 98.23 44 | 98.27 55 | 92.37 173 | 98.27 44 | 98.65 45 | 93.33 26 | 99.72 65 | 96.49 75 | 99.52 35 | 99.51 49 |
|
| SteuartSystems-ACMMP | | | 97.62 12 | 97.53 18 | 97.87 29 | 98.39 89 | 94.25 45 | 98.43 27 | 98.27 55 | 95.34 32 | 98.11 48 | 98.56 47 | 94.53 14 | 99.71 67 | 96.57 73 | 99.62 17 | 99.65 20 |
| Skip Steuart: Steuart Systems R&D Blog. |
| test_one_0601 | | | | | | 99.32 27 | 95.20 22 | | 98.25 61 | 95.13 40 | 98.48 40 | 98.87 31 | 95.16 9 | | | | |
|
| PVSNet_Blended_VisFu | | | 95.27 117 | 94.91 125 | 96.38 126 | 98.20 108 | 90.86 180 | 97.27 190 | 98.25 61 | 90.21 268 | 94.18 197 | 97.27 187 | 87.48 140 | 99.73 61 | 93.53 180 | 97.77 161 | 98.55 176 |
|
| region2R | | | 97.07 41 | 96.84 51 | 97.77 39 | 99.46 5 | 93.79 60 | 98.52 20 | 98.24 63 | 93.19 131 | 97.14 77 | 98.34 75 | 91.59 60 | 99.87 7 | 95.46 119 | 99.59 19 | 99.64 25 |
|
| PS-CasMVS | | | 91.55 290 | 90.84 289 | 93.69 318 | 94.96 355 | 88.28 293 | 97.84 96 | 98.24 63 | 91.46 211 | 88.04 371 | 95.80 277 | 79.67 310 | 97.48 397 | 87.02 344 | 84.54 409 | 95.31 360 |
|
| DU-MVS | | | 92.90 231 | 92.04 240 | 95.49 205 | 94.95 356 | 92.83 90 | 97.16 203 | 98.24 63 | 93.02 140 | 90.13 303 | 95.71 284 | 83.47 222 | 97.85 352 | 91.71 222 | 83.93 415 | 95.78 331 |
|
| 9.14 | | | | 96.75 61 | | 98.93 56 | | 97.73 116 | 98.23 66 | 91.28 220 | 97.88 56 | 98.44 64 | 93.00 30 | 99.65 79 | 95.76 106 | 99.47 45 | |
|
| reproduce_model | | | 97.51 20 | 97.51 20 | 97.50 55 | 98.99 52 | 93.01 83 | 97.79 107 | 98.21 67 | 95.73 24 | 97.99 52 | 99.03 15 | 92.63 39 | 99.82 33 | 97.80 30 | 99.42 56 | 99.67 15 |
|
| D2MVS | | | 91.30 307 | 90.95 283 | 92.35 373 | 94.71 371 | 85.52 374 | 96.18 308 | 98.21 67 | 88.89 313 | 86.60 400 | 93.82 382 | 79.92 306 | 97.95 341 | 89.29 281 | 90.95 330 | 93.56 436 |
|
| reproduce-ours | | | 97.53 18 | 97.51 20 | 97.60 52 | 98.97 53 | 93.31 74 | 97.71 121 | 98.20 69 | 95.80 21 | 97.88 56 | 98.98 18 | 92.91 31 | 99.81 35 | 97.68 32 | 99.43 53 | 99.67 15 |
|
| our_new_method | | | 97.53 18 | 97.51 20 | 97.60 52 | 98.97 53 | 93.31 74 | 97.71 121 | 98.20 69 | 95.80 21 | 97.88 56 | 98.98 18 | 92.91 31 | 99.81 35 | 97.68 32 | 99.43 53 | 99.67 15 |
|
| SDMVSNet | | | 94.17 168 | 93.61 175 | 95.86 168 | 98.09 117 | 91.37 152 | 97.35 178 | 98.20 69 | 93.18 133 | 91.79 264 | 97.28 185 | 79.13 318 | 98.93 197 | 94.61 154 | 92.84 296 | 97.28 278 |
|
| XVS | | | 97.18 34 | 96.96 45 | 97.81 33 | 99.38 17 | 94.03 55 | 98.59 17 | 98.20 69 | 94.85 53 | 96.59 100 | 98.29 84 | 91.70 56 | 99.80 40 | 95.66 108 | 99.40 61 | 99.62 27 |
|
| X-MVStestdata | | | 91.71 277 | 89.67 345 | 97.81 33 | 99.38 17 | 94.03 55 | 98.59 17 | 98.20 69 | 94.85 53 | 96.59 100 | 32.69 498 | 91.70 56 | 99.80 40 | 95.66 108 | 99.40 61 | 99.62 27 |
|
| ACMMP_NAP | | | 97.20 33 | 96.86 49 | 98.23 13 | 99.09 40 | 95.16 24 | 97.60 140 | 98.19 74 | 92.82 156 | 97.93 55 | 98.74 42 | 91.60 59 | 99.86 9 | 96.26 80 | 99.52 35 | 99.67 15 |
|
| CP-MVSNet | | | 91.89 273 | 91.24 272 | 93.82 310 | 95.05 352 | 88.57 281 | 97.82 101 | 98.19 74 | 91.70 200 | 88.21 366 | 95.76 282 | 81.96 263 | 97.52 395 | 87.86 310 | 84.65 403 | 95.37 356 |
|
| ZNCC-MVS | | | 96.96 46 | 96.67 64 | 97.85 30 | 99.37 19 | 94.12 51 | 98.49 24 | 98.18 76 | 92.64 163 | 96.39 114 | 98.18 91 | 91.61 58 | 99.88 4 | 95.59 118 | 99.55 30 | 99.57 36 |
|
| SMA-MVS |  | | 97.35 25 | 97.03 40 | 98.30 10 | 99.06 44 | 95.42 12 | 97.94 82 | 98.18 76 | 90.57 259 | 98.85 27 | 98.94 21 | 93.33 26 | 99.83 31 | 96.72 66 | 99.68 4 | 99.63 26 |
| 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 |
| PEN-MVS | | | 91.20 312 | 90.44 308 | 93.48 336 | 94.49 379 | 87.91 312 | 97.76 109 | 98.18 76 | 91.29 217 | 87.78 375 | 95.74 283 | 80.35 297 | 97.33 409 | 85.46 368 | 82.96 425 | 95.19 371 |
|
| DELS-MVS | | | 96.61 71 | 96.38 80 | 97.30 64 | 97.79 140 | 93.19 79 | 95.96 320 | 98.18 76 | 95.23 35 | 95.87 135 | 97.65 155 | 91.45 61 | 99.70 72 | 95.87 100 | 99.44 52 | 99.00 110 |
| 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 |
| tfpnnormal | | | 89.70 364 | 88.40 370 | 93.60 327 | 95.15 347 | 90.10 211 | 97.56 145 | 98.16 80 | 87.28 367 | 86.16 407 | 94.63 337 | 77.57 346 | 98.05 321 | 74.48 455 | 84.59 407 | 92.65 449 |
|
| VNet | | | 95.89 98 | 95.45 100 | 97.21 72 | 98.07 121 | 92.94 86 | 97.50 154 | 98.15 81 | 93.87 100 | 97.52 63 | 97.61 162 | 85.29 188 | 99.53 113 | 95.81 105 | 95.27 249 | 99.16 85 |
|
| DeepPCF-MVS | | 93.97 1 | 96.61 71 | 97.09 33 | 95.15 219 | 98.09 117 | 86.63 346 | 96.00 318 | 98.15 81 | 95.43 28 | 97.95 54 | 98.56 47 | 93.40 24 | 99.36 138 | 96.77 63 | 99.48 44 | 99.45 59 |
|
| SD-MVS | | | 97.41 23 | 97.53 18 | 97.06 83 | 98.57 78 | 94.46 39 | 97.92 85 | 98.14 83 | 94.82 57 | 99.01 17 | 98.55 49 | 94.18 16 | 97.41 404 | 96.94 58 | 99.64 14 | 99.32 74 |
| 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 |
| GST-MVS | | | 96.85 54 | 96.52 70 | 97.82 32 | 99.36 23 | 94.14 50 | 98.29 34 | 98.13 84 | 92.72 159 | 96.70 92 | 98.06 98 | 91.35 65 | 99.86 9 | 94.83 140 | 99.28 74 | 99.47 58 |
|
| UA-Net | | | 95.95 95 | 95.53 96 | 97.20 73 | 97.67 147 | 92.98 85 | 97.65 130 | 98.13 84 | 94.81 59 | 96.61 98 | 98.35 72 | 88.87 104 | 99.51 118 | 90.36 256 | 97.35 175 | 99.11 95 |
|
| QAPM | | | 93.45 207 | 92.27 234 | 96.98 86 | 96.77 222 | 92.62 99 | 98.39 29 | 98.12 86 | 84.50 412 | 88.27 364 | 97.77 141 | 82.39 255 | 99.81 35 | 85.40 369 | 98.81 114 | 98.51 181 |
|
| Vis-MVSNet |  | | 95.23 122 | 94.81 131 | 96.51 112 | 97.18 175 | 91.58 142 | 98.26 39 | 98.12 86 | 94.38 84 | 94.90 173 | 98.15 93 | 82.28 256 | 98.92 199 | 91.45 229 | 98.58 127 | 99.01 107 |
| Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
| OpenMVS |  | 89.19 12 | 92.86 234 | 91.68 255 | 96.40 123 | 95.34 330 | 92.73 95 | 98.27 37 | 98.12 86 | 84.86 407 | 85.78 416 | 97.75 142 | 78.89 328 | 99.74 59 | 87.50 333 | 98.65 122 | 96.73 296 |
|
| TranMVSNet+NR-MVSNet | | | 92.50 243 | 91.63 256 | 95.14 220 | 94.76 367 | 92.07 120 | 97.53 151 | 98.11 89 | 92.90 152 | 89.56 325 | 96.12 261 | 83.16 230 | 97.60 381 | 89.30 280 | 83.20 424 | 95.75 335 |
|
| CPTT-MVS | | | 95.57 108 | 95.19 112 | 96.70 93 | 99.27 31 | 91.48 147 | 98.33 31 | 98.11 89 | 87.79 352 | 95.17 163 | 98.03 101 | 87.09 148 | 99.61 91 | 93.51 181 | 99.42 56 | 99.02 104 |
|
| APD-MVS |  | | 96.95 47 | 96.60 66 | 98.01 22 | 99.03 47 | 94.93 29 | 97.72 119 | 98.10 91 | 91.50 209 | 98.01 51 | 98.32 80 | 92.33 45 | 99.58 99 | 94.85 137 | 99.51 38 | 99.53 48 |
| Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
| mPP-MVS | | | 96.86 52 | 96.60 66 | 97.64 50 | 99.40 14 | 93.44 67 | 98.50 23 | 98.09 92 | 93.27 127 | 95.95 133 | 98.33 78 | 91.04 73 | 99.88 4 | 95.20 122 | 99.57 29 | 99.60 31 |
|
| ZD-MVS | | | | | | 99.05 45 | 94.59 34 | | 98.08 93 | 89.22 299 | 97.03 82 | 98.10 94 | 92.52 42 | 99.65 79 | 94.58 156 | 99.31 72 | |
|
| MTGPA |  | | | | | | | | 98.08 93 | | | | | | | | |
|
| MTAPA | | | 97.08 39 | 96.78 59 | 97.97 28 | 99.37 19 | 94.42 41 | 97.24 192 | 98.08 93 | 95.07 44 | 96.11 125 | 98.59 46 | 90.88 79 | 99.90 2 | 96.18 92 | 99.50 40 | 99.58 35 |
|
| CNVR-MVS | | | 97.68 8 | 97.44 24 | 98.37 8 | 98.90 59 | 95.86 8 | 97.27 190 | 98.08 93 | 95.81 20 | 97.87 59 | 98.31 81 | 94.26 15 | 99.68 75 | 97.02 57 | 99.49 43 | 99.57 36 |
|
| DP-MVS Recon | | | 95.68 103 | 95.12 116 | 97.37 61 | 99.19 37 | 94.19 47 | 97.03 210 | 98.08 93 | 88.35 333 | 95.09 165 | 97.65 155 | 89.97 90 | 99.48 125 | 92.08 214 | 98.59 126 | 98.44 192 |
|
| SR-MVS | | | 97.01 44 | 96.86 49 | 97.47 57 | 99.09 40 | 93.27 76 | 97.98 72 | 98.07 98 | 93.75 103 | 97.45 65 | 98.48 61 | 91.43 63 | 99.59 96 | 96.22 83 | 99.27 75 | 99.54 45 |
|
| MCST-MVS | | | 97.18 34 | 96.84 51 | 98.20 16 | 99.30 29 | 95.35 17 | 97.12 206 | 98.07 98 | 93.54 113 | 96.08 127 | 97.69 150 | 93.86 19 | 99.71 67 | 96.50 74 | 99.39 63 | 99.55 43 |
|
| NR-MVSNet | | | 92.34 252 | 91.27 271 | 95.53 197 | 94.95 356 | 93.05 82 | 97.39 174 | 98.07 98 | 92.65 161 | 84.46 428 | 95.71 284 | 85.00 195 | 97.77 363 | 89.71 268 | 83.52 421 | 95.78 331 |
|
| MP-MVS-pluss | | | 96.70 65 | 96.27 83 | 97.98 27 | 99.23 35 | 94.71 31 | 96.96 221 | 98.06 101 | 90.67 249 | 95.55 149 | 98.78 40 | 91.07 72 | 99.86 9 | 96.58 72 | 99.55 30 | 99.38 70 |
| MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
| APD-MVS_3200maxsize | | | 96.81 58 | 96.71 63 | 97.12 77 | 99.01 51 | 92.31 111 | 97.98 72 | 98.06 101 | 93.11 137 | 97.44 66 | 98.55 49 | 90.93 77 | 99.55 109 | 96.06 93 | 99.25 80 | 99.51 49 |
|
| MP-MVS |  | | 96.77 60 | 96.45 77 | 97.72 44 | 99.39 16 | 93.80 59 | 98.41 28 | 98.06 101 | 93.37 123 | 95.54 151 | 98.34 75 | 90.59 83 | 99.88 4 | 94.83 140 | 99.54 32 | 99.49 54 |
| Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
| HPM-MVS_fast | | | 96.51 74 | 96.27 83 | 97.22 71 | 99.32 27 | 92.74 94 | 98.74 10 | 98.06 101 | 90.57 259 | 96.77 89 | 98.35 72 | 90.21 86 | 99.53 113 | 94.80 144 | 99.63 16 | 99.38 70 |
|
| HPM-MVS |  | | 96.69 67 | 96.45 77 | 97.40 60 | 99.36 23 | 93.11 81 | 98.87 6 | 98.06 101 | 91.17 228 | 96.40 113 | 97.99 107 | 90.99 74 | 99.58 99 | 95.61 115 | 99.61 18 | 99.49 54 |
| Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
| sss | | | 94.51 159 | 93.80 168 | 96.64 95 | 97.07 182 | 91.97 125 | 96.32 295 | 98.06 101 | 88.94 311 | 94.50 186 | 96.78 219 | 84.60 201 | 99.27 148 | 91.90 215 | 96.02 225 | 98.68 167 |
|
| DeepC-MVS | | 93.07 3 | 96.06 89 | 95.66 93 | 97.29 65 | 97.96 128 | 93.17 80 | 97.30 184 | 98.06 101 | 93.92 98 | 93.38 224 | 98.66 43 | 86.83 150 | 99.73 61 | 95.60 117 | 99.22 82 | 98.96 116 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| NCCC | | | 97.30 29 | 97.03 40 | 98.11 19 | 98.77 62 | 95.06 27 | 97.34 179 | 98.04 108 | 95.96 15 | 97.09 80 | 97.88 124 | 93.18 29 | 99.71 67 | 95.84 104 | 99.17 91 | 99.56 40 |
|
| DeepC-MVS_fast | | 93.89 2 | 96.93 49 | 96.64 65 | 97.78 37 | 98.64 73 | 94.30 42 | 97.41 169 | 98.04 108 | 94.81 59 | 96.59 100 | 98.37 70 | 91.24 68 | 99.64 87 | 95.16 124 | 99.52 35 | 99.42 65 |
| Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
| SR-MVS-dyc-post | | | 96.88 51 | 96.80 57 | 97.11 79 | 99.02 48 | 92.34 109 | 97.98 72 | 98.03 110 | 93.52 116 | 97.43 68 | 98.51 56 | 91.40 64 | 99.56 107 | 96.05 94 | 99.26 78 | 99.43 63 |
|
| RE-MVS-def | | | | 96.72 62 | | 99.02 48 | 92.34 109 | 97.98 72 | 98.03 110 | 93.52 116 | 97.43 68 | 98.51 56 | 90.71 81 | | 96.05 94 | 99.26 78 | 99.43 63 |
|
| RPMNet | | | 88.98 370 | 87.05 384 | 94.77 247 | 94.45 381 | 87.19 330 | 90.23 471 | 98.03 110 | 77.87 470 | 92.40 242 | 87.55 470 | 80.17 301 | 99.51 118 | 68.84 477 | 93.95 282 | 97.60 263 |
|
| save fliter | | | | | | 98.91 58 | 94.28 43 | 97.02 212 | 98.02 113 | 95.35 31 | | | | | | | |
|
| TEST9 | | | | | | 98.70 65 | 94.19 47 | 96.41 281 | 98.02 113 | 88.17 337 | 96.03 128 | 97.56 168 | 92.74 36 | 99.59 96 | | | |
|
| train_agg | | | 96.30 85 | 95.83 92 | 97.72 44 | 98.70 65 | 94.19 47 | 96.41 281 | 98.02 113 | 88.58 324 | 96.03 128 | 97.56 168 | 92.73 37 | 99.59 96 | 95.04 126 | 99.37 67 | 99.39 68 |
|
| test_8 | | | | | | 98.67 67 | 94.06 54 | 96.37 289 | 98.01 116 | 88.58 324 | 95.98 132 | 97.55 170 | 92.73 37 | 99.58 99 | | | |
|
| fmvsm_s_conf0.5_n_11 | | | 97.30 29 | 97.59 14 | 96.43 120 | 98.42 84 | 91.37 152 | 98.04 64 | 98.00 117 | 97.30 3 | 99.45 4 | 99.21 1 | 89.28 97 | 99.80 40 | 99.27 10 | 99.35 69 | 98.12 222 |
|
| agg_prior | | | | | | 98.67 67 | 93.79 60 | | 98.00 117 | | 95.68 145 | | | 99.57 106 | | | |
|
| test_prior | | | | | 97.23 70 | 98.67 67 | 92.99 84 | | 98.00 117 | | | | | 99.41 133 | | | 99.29 75 |
|
| WR-MVS | | | 92.34 252 | 91.53 260 | 94.77 247 | 95.13 349 | 90.83 181 | 96.40 285 | 97.98 120 | 91.88 195 | 89.29 334 | 95.54 295 | 82.50 251 | 97.80 359 | 89.79 267 | 85.27 394 | 95.69 338 |
|
| HPM-MVS++ |  | | 97.34 26 | 96.97 43 | 98.47 6 | 99.08 42 | 96.16 5 | 97.55 150 | 97.97 121 | 95.59 25 | 96.61 98 | 97.89 119 | 92.57 41 | 99.84 26 | 95.95 99 | 99.51 38 | 99.40 66 |
|
| CANet | | | 96.39 80 | 96.02 87 | 97.50 55 | 97.62 154 | 93.38 69 | 97.02 212 | 97.96 122 | 95.42 29 | 94.86 174 | 97.81 137 | 87.38 143 | 99.82 33 | 96.88 60 | 99.20 88 | 99.29 75 |
|
| 114514_t | | | 93.95 183 | 93.06 200 | 96.63 99 | 99.07 43 | 91.61 139 | 97.46 165 | 97.96 122 | 77.99 468 | 93.00 233 | 97.57 166 | 86.14 166 | 99.33 140 | 89.22 284 | 99.15 94 | 98.94 123 |
|
| IU-MVS | | | | | | 99.42 10 | 95.39 13 | | 97.94 124 | 90.40 266 | 98.94 19 | | | | 97.41 48 | 99.66 10 | 99.74 9 |
|
| MSC_two_6792asdad | | | | | 98.86 1 | 98.67 67 | 96.94 1 | | 97.93 125 | | | | | 99.86 9 | 97.68 32 | 99.67 6 | 99.77 3 |
|
| No_MVS | | | | | 98.86 1 | 98.67 67 | 96.94 1 | | 97.93 125 | | | | | 99.86 9 | 97.68 32 | 99.67 6 | 99.77 3 |
|
| fmvsm_s_conf0.1_n_2 | | | 96.33 84 | 96.44 79 | 96.00 158 | 97.30 168 | 90.37 204 | 97.53 151 | 97.92 127 | 96.52 11 | 99.14 15 | 99.08 8 | 83.21 228 | 99.74 59 | 99.22 11 | 98.06 150 | 97.88 243 |
|
| Anonymous20231211 | | | 90.63 336 | 89.42 352 | 94.27 281 | 98.24 101 | 89.19 260 | 98.05 63 | 97.89 128 | 79.95 459 | 88.25 365 | 94.96 318 | 72.56 392 | 98.13 304 | 89.70 269 | 85.14 396 | 95.49 342 |
|
| 原ACMM1 | | | | | 96.38 126 | 98.59 75 | 91.09 169 | | 97.89 128 | 87.41 363 | 95.22 162 | 97.68 151 | 90.25 85 | 99.54 111 | 87.95 309 | 99.12 99 | 98.49 184 |
|
| CDPH-MVS | | | 95.97 94 | 95.38 106 | 97.77 39 | 98.93 56 | 94.44 40 | 96.35 290 | 97.88 130 | 86.98 371 | 96.65 96 | 97.89 119 | 91.99 51 | 99.47 126 | 92.26 203 | 99.46 46 | 99.39 68 |
|
| test11 | | | | | | | | | 97.88 130 | | | | | | | | |
|
| EIA-MVS | | | 95.53 110 | 95.47 99 | 95.71 187 | 97.06 185 | 89.63 232 | 97.82 101 | 97.87 132 | 93.57 109 | 93.92 206 | 95.04 315 | 90.61 82 | 98.95 194 | 94.62 153 | 98.68 120 | 98.54 177 |
|
| CS-MVS | | | 96.86 52 | 97.06 35 | 96.26 136 | 98.16 113 | 91.16 167 | 99.09 3 | 97.87 132 | 95.30 33 | 97.06 81 | 98.03 101 | 91.72 54 | 98.71 242 | 97.10 55 | 99.17 91 | 98.90 132 |
|
| 无先验 | | | | | | | | 95.79 332 | 97.87 132 | 83.87 421 | | | | 99.65 79 | 87.68 323 | | 98.89 138 |
|
| 3Dnovator+ | | 91.43 4 | 95.40 111 | 94.48 150 | 98.16 18 | 96.90 202 | 95.34 18 | 98.48 25 | 97.87 132 | 94.65 70 | 88.53 356 | 98.02 103 | 83.69 218 | 99.71 67 | 93.18 189 | 98.96 109 | 99.44 61 |
|
| VPNet | | | 92.23 260 | 91.31 268 | 94.99 230 | 95.56 314 | 90.96 173 | 97.22 198 | 97.86 136 | 92.96 147 | 90.96 286 | 96.62 236 | 75.06 367 | 98.20 298 | 91.90 215 | 83.65 420 | 95.80 329 |
|
| TestfortrainingZip | | | | | 98.34 9 | 98.54 79 | 96.25 4 | 98.69 11 | 97.85 137 | 94.15 90 | 98.17 46 | 97.94 111 | 94.00 17 | 99.63 88 | | 97.45 171 | 99.15 87 |
|
| test_vis1_n_1920 | | | 94.17 168 | 94.58 142 | 92.91 357 | 97.42 166 | 82.02 428 | 97.83 99 | 97.85 137 | 94.68 67 | 98.10 49 | 98.49 58 | 70.15 412 | 99.32 142 | 97.91 29 | 98.82 113 | 97.40 272 |
|
| DVP-MVS |  | | 97.91 4 | 97.81 5 | 98.22 15 | 99.45 6 | 95.36 15 | 98.21 48 | 97.85 137 | 94.92 50 | 98.73 30 | 98.87 31 | 95.08 10 | 99.84 26 | 97.52 41 | 99.67 6 | 99.48 56 |
| 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 |
| TSAR-MVS + MP. | | | 97.42 22 | 97.33 29 | 97.69 47 | 99.25 32 | 94.24 46 | 98.07 61 | 97.85 137 | 93.72 104 | 98.57 37 | 98.35 72 | 93.69 21 | 99.40 134 | 97.06 56 | 99.46 46 | 99.44 61 |
| Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
| SPE-MVS-test | | | 96.89 50 | 97.04 39 | 96.45 119 | 98.29 94 | 91.66 138 | 99.03 4 | 97.85 137 | 95.84 18 | 96.90 84 | 97.97 109 | 91.24 68 | 98.75 232 | 96.92 59 | 99.33 70 | 98.94 123 |
|
| test_fmvsmconf0.01_n | | | 96.15 88 | 95.85 91 | 97.03 84 | 92.66 434 | 91.83 130 | 97.97 78 | 97.84 142 | 95.57 26 | 97.53 62 | 99.00 16 | 84.20 211 | 99.76 54 | 98.82 23 | 99.08 101 | 99.48 56 |
|
| GDP-MVS | | | 95.62 105 | 95.13 114 | 97.09 80 | 96.79 215 | 93.26 77 | 97.89 89 | 97.83 143 | 93.58 108 | 96.80 86 | 97.82 135 | 83.06 235 | 99.16 163 | 94.40 160 | 97.95 156 | 98.87 142 |
|
| balanced_conf03 | | | 96.84 56 | 96.89 48 | 96.68 94 | 97.63 153 | 92.22 114 | 98.17 54 | 97.82 144 | 94.44 79 | 98.23 45 | 97.36 180 | 90.97 75 | 99.22 153 | 97.74 31 | 99.66 10 | 98.61 170 |
|
| AdaColmap |  | | 94.34 163 | 93.68 173 | 96.31 130 | 98.59 75 | 91.68 137 | 96.59 270 | 97.81 145 | 89.87 275 | 92.15 252 | 97.06 202 | 83.62 221 | 99.54 111 | 89.34 279 | 98.07 149 | 97.70 256 |
|
| MVSMamba_PlusPlus | | | 96.51 74 | 96.48 72 | 96.59 103 | 98.07 121 | 91.97 125 | 98.14 55 | 97.79 146 | 90.43 264 | 97.34 71 | 97.52 171 | 91.29 67 | 99.19 156 | 98.12 27 | 99.64 14 | 98.60 171 |
|
| KinetiMVS | | | 95.26 118 | 94.75 136 | 96.79 91 | 96.99 195 | 92.05 121 | 97.82 101 | 97.78 147 | 94.77 63 | 96.46 110 | 97.70 148 | 80.62 291 | 99.34 139 | 92.37 202 | 98.28 140 | 98.97 113 |
|
| ETV-MVS | | | 96.02 91 | 95.89 90 | 96.40 123 | 97.16 176 | 92.44 106 | 97.47 163 | 97.77 148 | 94.55 73 | 96.48 108 | 94.51 343 | 91.23 70 | 98.92 199 | 95.65 111 | 98.19 144 | 97.82 251 |
|
| 新几何1 | | | | | 97.32 63 | 98.60 74 | 93.59 64 | | 97.75 149 | 81.58 450 | 95.75 140 | 97.85 129 | 90.04 88 | 99.67 77 | 86.50 350 | 99.13 97 | 98.69 166 |
|
| 旧先验1 | | | | | | 98.38 90 | 93.38 69 | | 97.75 149 | | | 98.09 96 | 92.30 48 | | | 99.01 107 | 99.16 85 |
|
| EC-MVSNet | | | 96.42 78 | 96.47 73 | 96.26 136 | 97.01 193 | 91.52 144 | 98.89 5 | 97.75 149 | 94.42 80 | 96.64 97 | 97.68 151 | 89.32 96 | 98.60 259 | 97.45 45 | 99.11 100 | 98.67 168 |
|
| EI-MVSNet-Vis-set | | | 96.51 74 | 96.47 73 | 96.63 99 | 98.24 101 | 91.20 161 | 96.89 229 | 97.73 152 | 94.74 65 | 96.49 107 | 98.49 58 | 90.88 79 | 99.58 99 | 96.44 76 | 98.32 138 | 99.13 90 |
|
| PAPM_NR | | | 95.01 136 | 94.59 141 | 96.26 136 | 98.89 60 | 90.68 190 | 97.24 192 | 97.73 152 | 91.80 196 | 92.93 238 | 96.62 236 | 89.13 100 | 99.14 168 | 89.21 285 | 97.78 160 | 98.97 113 |
|
| Anonymous20240529 | | | 91.98 269 | 90.73 296 | 95.73 185 | 98.14 114 | 89.40 247 | 97.99 69 | 97.72 154 | 79.63 461 | 93.54 217 | 97.41 177 | 69.94 414 | 99.56 107 | 91.04 237 | 91.11 326 | 98.22 212 |
|
| CHOSEN 280x420 | | | 93.12 219 | 92.72 217 | 94.34 274 | 96.71 228 | 87.27 326 | 90.29 470 | 97.72 154 | 86.61 378 | 91.34 275 | 95.29 303 | 84.29 210 | 98.41 275 | 93.25 187 | 98.94 110 | 97.35 275 |
|
| EI-MVSNet-UG-set | | | 96.34 83 | 96.30 82 | 96.47 116 | 98.20 108 | 90.93 177 | 96.86 232 | 97.72 154 | 94.67 68 | 96.16 124 | 98.46 62 | 90.43 84 | 99.58 99 | 96.23 82 | 97.96 155 | 98.90 132 |
|
| LS3D | | | 93.57 200 | 92.61 222 | 96.47 116 | 97.59 157 | 91.61 139 | 97.67 126 | 97.72 154 | 85.17 402 | 90.29 297 | 98.34 75 | 84.60 201 | 99.73 61 | 83.85 392 | 98.27 141 | 98.06 232 |
|
| PAPR | | | 94.18 167 | 93.42 189 | 96.48 115 | 97.64 151 | 91.42 151 | 95.55 346 | 97.71 158 | 88.99 308 | 92.34 248 | 95.82 276 | 89.19 98 | 99.11 171 | 86.14 356 | 97.38 173 | 98.90 132 |
|
| UGNet | | | 94.04 178 | 93.28 192 | 96.31 130 | 96.85 207 | 91.19 162 | 97.88 91 | 97.68 159 | 94.40 82 | 93.00 233 | 96.18 256 | 73.39 386 | 99.61 91 | 91.72 221 | 98.46 132 | 98.13 220 |
| 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 |
| testdata | | | | | 95.46 209 | 98.18 112 | 88.90 271 | | 97.66 160 | 82.73 439 | 97.03 82 | 98.07 97 | 90.06 87 | 98.85 206 | 89.67 270 | 98.98 108 | 98.64 169 |
|
| test12 | | | | | 97.65 48 | 98.46 80 | 94.26 44 | | 97.66 160 | | 95.52 152 | | 90.89 78 | 99.46 127 | | 99.25 80 | 99.22 82 |
|
| DTE-MVSNet | | | 90.56 337 | 89.75 343 | 93.01 353 | 93.95 394 | 87.25 327 | 97.64 134 | 97.65 162 | 90.74 244 | 87.12 388 | 95.68 287 | 79.97 305 | 97.00 422 | 83.33 393 | 81.66 431 | 94.78 406 |
|
| TAPA-MVS | | 90.10 7 | 92.30 255 | 91.22 274 | 95.56 194 | 98.33 92 | 89.60 234 | 96.79 243 | 97.65 162 | 81.83 447 | 91.52 270 | 97.23 190 | 87.94 123 | 98.91 201 | 71.31 470 | 98.37 136 | 98.17 218 |
| Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
| sd_testset | | | 93.10 220 | 92.45 230 | 95.05 224 | 98.09 117 | 89.21 257 | 96.89 229 | 97.64 164 | 93.18 133 | 91.79 264 | 97.28 185 | 75.35 366 | 98.65 253 | 88.99 291 | 92.84 296 | 97.28 278 |
|
| test_cas_vis1_n_1920 | | | 94.48 161 | 94.55 146 | 94.28 280 | 96.78 220 | 86.45 352 | 97.63 136 | 97.64 164 | 93.32 126 | 97.68 61 | 98.36 71 | 73.75 382 | 99.08 178 | 96.73 65 | 99.05 103 | 97.31 277 |
|
| NormalMVS | | | 96.36 82 | 96.11 86 | 97.12 77 | 99.37 19 | 92.90 88 | 97.99 69 | 97.63 166 | 95.92 16 | 96.57 103 | 97.93 112 | 85.34 186 | 99.50 121 | 94.99 129 | 99.21 83 | 98.97 113 |
|
| Elysia | | | 94.00 180 | 93.12 197 | 96.64 95 | 96.08 293 | 92.72 96 | 97.50 154 | 97.63 166 | 91.15 230 | 94.82 175 | 97.12 196 | 74.98 369 | 99.06 184 | 90.78 242 | 98.02 151 | 98.12 222 |
|
| StellarMVS | | | 94.00 180 | 93.12 197 | 96.64 95 | 96.08 293 | 92.72 96 | 97.50 154 | 97.63 166 | 91.15 230 | 94.82 175 | 97.12 196 | 74.98 369 | 99.06 184 | 90.78 242 | 98.02 151 | 98.12 222 |
|
| cdsmvs_eth3d_5k | | | 23.24 466 | 30.99 468 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 97.63 166 | 0.00 504 | 0.00 505 | 96.88 215 | 84.38 206 | 0.00 505 | 0.00 503 | 0.00 503 | 0.00 501 |
|
| DPM-MVS | | | 95.69 102 | 94.92 124 | 98.01 22 | 98.08 120 | 95.71 11 | 95.27 363 | 97.62 170 | 90.43 264 | 95.55 149 | 97.07 201 | 91.72 54 | 99.50 121 | 89.62 272 | 98.94 110 | 98.82 148 |
|
| sasdasda | | | 96.02 91 | 95.45 100 | 97.75 41 | 97.59 157 | 95.15 25 | 98.28 35 | 97.60 171 | 94.52 75 | 96.27 119 | 96.12 261 | 87.65 130 | 99.18 159 | 96.20 88 | 94.82 258 | 98.91 129 |
|
| canonicalmvs | | | 96.02 91 | 95.45 100 | 97.75 41 | 97.59 157 | 95.15 25 | 98.28 35 | 97.60 171 | 94.52 75 | 96.27 119 | 96.12 261 | 87.65 130 | 99.18 159 | 96.20 88 | 94.82 258 | 98.91 129 |
|
| test222 | | | | | | 98.24 101 | 92.21 115 | 95.33 358 | 97.60 171 | 79.22 463 | 95.25 160 | 97.84 131 | 88.80 106 | | | 99.15 94 | 98.72 163 |
|
| cascas | | | 91.20 312 | 90.08 325 | 94.58 259 | 94.97 354 | 89.16 261 | 93.65 432 | 97.59 174 | 79.90 460 | 89.40 329 | 92.92 410 | 75.36 365 | 98.36 283 | 92.14 208 | 94.75 261 | 96.23 308 |
|
| E2 | | | 95.20 124 | 95.00 121 | 95.79 176 | 96.79 215 | 89.66 229 | 96.82 238 | 97.58 175 | 92.35 174 | 95.28 158 | 97.83 133 | 86.68 152 | 98.76 226 | 94.79 147 | 96.92 194 | 98.95 120 |
|
| E3 | | | 95.20 124 | 95.00 121 | 95.79 176 | 96.77 222 | 89.66 229 | 96.82 238 | 97.58 175 | 92.35 174 | 95.28 158 | 97.83 133 | 86.69 151 | 98.76 226 | 94.79 147 | 96.92 194 | 98.95 120 |
|
| h-mvs33 | | | 94.15 170 | 93.52 181 | 96.04 152 | 97.81 139 | 90.22 209 | 97.62 138 | 97.58 175 | 95.19 36 | 96.74 90 | 97.45 173 | 83.67 219 | 99.61 91 | 95.85 102 | 79.73 438 | 98.29 208 |
|
| E5new | | | 95.04 132 | 94.88 126 | 95.52 198 | 96.62 231 | 89.02 265 | 97.29 185 | 97.57 178 | 92.54 164 | 95.04 166 | 97.89 119 | 85.65 178 | 98.77 220 | 94.92 132 | 96.44 218 | 98.78 151 |
|
| E6new | | | 95.04 132 | 94.88 126 | 95.52 198 | 96.60 236 | 89.02 265 | 97.29 185 | 97.57 178 | 92.54 164 | 95.04 166 | 97.90 117 | 85.66 176 | 98.77 220 | 94.92 132 | 96.44 218 | 98.78 151 |
|
| E6 | | | 95.04 132 | 94.88 126 | 95.52 198 | 96.60 236 | 89.02 265 | 97.29 185 | 97.57 178 | 92.54 164 | 95.04 166 | 97.90 117 | 85.66 176 | 98.77 220 | 94.92 132 | 96.44 218 | 98.78 151 |
|
| E5 | | | 95.04 132 | 94.88 126 | 95.52 198 | 96.62 231 | 89.02 265 | 97.29 185 | 97.57 178 | 92.54 164 | 95.04 166 | 97.89 119 | 85.65 178 | 98.77 220 | 94.92 132 | 96.44 218 | 98.78 151 |
|
| MGCFI-Net | | | 95.94 96 | 95.40 104 | 97.56 54 | 97.59 157 | 94.62 33 | 98.21 48 | 97.57 178 | 94.41 81 | 96.17 123 | 96.16 259 | 87.54 135 | 99.17 161 | 96.19 90 | 94.73 263 | 98.91 129 |
|
| MVSFormer | | | 95.37 112 | 95.16 113 | 95.99 159 | 96.34 269 | 91.21 159 | 98.22 46 | 97.57 178 | 91.42 213 | 96.22 121 | 97.32 181 | 86.20 164 | 97.92 346 | 94.07 166 | 99.05 103 | 98.85 144 |
|
| test_djsdf | | | 93.07 222 | 92.76 212 | 94.00 295 | 93.49 413 | 88.70 276 | 98.22 46 | 97.57 178 | 91.42 213 | 90.08 309 | 95.55 294 | 82.85 242 | 97.92 346 | 94.07 166 | 91.58 317 | 95.40 353 |
|
| OMC-MVS | | | 95.09 129 | 94.70 137 | 96.25 139 | 98.46 80 | 91.28 155 | 96.43 277 | 97.57 178 | 92.04 191 | 94.77 179 | 97.96 110 | 87.01 149 | 99.09 176 | 91.31 231 | 96.77 199 | 98.36 199 |
|
| E4 | | | 95.09 129 | 94.86 130 | 95.77 179 | 96.58 240 | 89.56 237 | 96.85 233 | 97.56 186 | 92.50 168 | 95.03 170 | 97.86 127 | 86.03 167 | 98.78 216 | 94.71 150 | 96.65 208 | 98.96 116 |
|
| viewcassd2359sk11 | | | 95.26 118 | 95.09 118 | 95.80 173 | 96.95 199 | 89.72 228 | 96.80 242 | 97.56 186 | 92.21 181 | 95.37 156 | 97.80 139 | 87.17 147 | 98.77 220 | 94.82 142 | 97.10 188 | 98.90 132 |
|
| PS-MVSNAJss | | | 93.74 193 | 93.51 182 | 94.44 268 | 93.91 396 | 89.28 255 | 97.75 111 | 97.56 186 | 92.50 168 | 89.94 311 | 96.54 239 | 88.65 109 | 98.18 301 | 93.83 175 | 90.90 331 | 95.86 323 |
|
| casdiffmvs_mvg |  | | 95.81 101 | 95.57 94 | 96.51 112 | 96.87 204 | 91.49 145 | 97.50 154 | 97.56 186 | 93.99 96 | 95.13 164 | 97.92 115 | 87.89 124 | 98.78 216 | 95.97 98 | 97.33 176 | 99.26 79 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| E3new | | | 95.28 116 | 95.11 117 | 95.80 173 | 97.03 190 | 89.76 226 | 96.78 247 | 97.54 190 | 92.06 190 | 95.40 155 | 97.75 142 | 87.49 139 | 98.76 226 | 94.85 137 | 97.10 188 | 98.88 140 |
|
| jajsoiax | | | 92.42 248 | 91.89 248 | 94.03 294 | 93.33 421 | 88.50 286 | 97.73 116 | 97.53 191 | 92.00 193 | 88.85 348 | 96.50 241 | 75.62 364 | 98.11 308 | 93.88 173 | 91.56 318 | 95.48 343 |
|
| mvs_tets | | | 92.31 254 | 91.76 251 | 93.94 303 | 93.41 418 | 88.29 292 | 97.63 136 | 97.53 191 | 92.04 191 | 88.76 351 | 96.45 243 | 74.62 374 | 98.09 313 | 93.91 171 | 91.48 319 | 95.45 348 |
|
| dcpmvs_2 | | | 96.37 81 | 97.05 38 | 94.31 278 | 98.96 55 | 84.11 401 | 97.56 145 | 97.51 193 | 93.92 98 | 97.43 68 | 98.52 55 | 92.75 35 | 99.32 142 | 97.32 54 | 99.50 40 | 99.51 49 |
|
| HQP_MVS | | | 93.78 192 | 93.43 187 | 94.82 240 | 96.21 273 | 89.99 215 | 97.74 114 | 97.51 193 | 94.85 53 | 91.34 275 | 96.64 229 | 81.32 275 | 98.60 259 | 93.02 195 | 92.23 305 | 95.86 323 |
|
| plane_prior5 | | | | | | | | | 97.51 193 | | | | | 98.60 259 | 93.02 195 | 92.23 305 | 95.86 323 |
|
| viewmanbaseed2359cas | | | 95.24 121 | 95.02 120 | 95.91 162 | 96.87 204 | 89.98 217 | 96.82 238 | 97.49 196 | 92.26 177 | 95.47 153 | 97.82 135 | 86.47 157 | 98.69 244 | 94.80 144 | 97.20 184 | 99.06 102 |
|
| reproduce_monomvs | | | 91.30 307 | 91.10 278 | 91.92 387 | 96.82 212 | 82.48 422 | 97.01 215 | 97.49 196 | 94.64 71 | 88.35 359 | 95.27 306 | 70.53 407 | 98.10 309 | 95.20 122 | 84.60 406 | 95.19 371 |
|
| viewmacassd2359aftdt | | | 95.07 131 | 94.80 132 | 95.87 165 | 96.53 250 | 89.84 223 | 96.90 228 | 97.48 198 | 92.44 170 | 95.36 157 | 97.89 119 | 85.23 189 | 98.68 246 | 94.40 160 | 97.00 192 | 99.09 97 |
|
| PS-MVSNAJ | | | 95.37 112 | 95.33 108 | 95.49 205 | 97.35 167 | 90.66 191 | 95.31 360 | 97.48 198 | 93.85 101 | 96.51 106 | 95.70 286 | 88.65 109 | 99.65 79 | 94.80 144 | 98.27 141 | 96.17 312 |
|
| API-MVS | | | 94.84 147 | 94.49 149 | 95.90 163 | 97.90 134 | 92.00 124 | 97.80 105 | 97.48 198 | 89.19 300 | 94.81 177 | 96.71 222 | 88.84 105 | 99.17 161 | 88.91 294 | 98.76 118 | 96.53 301 |
|
| MG-MVS | | | 95.61 106 | 95.38 106 | 96.31 130 | 98.42 84 | 90.53 193 | 96.04 315 | 97.48 198 | 93.47 118 | 95.67 146 | 98.10 94 | 89.17 99 | 99.25 150 | 91.27 232 | 98.77 117 | 99.13 90 |
|
| MAR-MVS | | | 94.22 166 | 93.46 184 | 96.51 112 | 98.00 125 | 92.19 118 | 97.67 126 | 97.47 202 | 88.13 341 | 93.00 233 | 95.84 274 | 84.86 199 | 99.51 118 | 87.99 308 | 98.17 146 | 97.83 250 |
| 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 |
| CLD-MVS | | | 92.98 226 | 92.53 226 | 94.32 276 | 96.12 288 | 89.20 258 | 95.28 361 | 97.47 202 | 92.66 160 | 89.90 312 | 95.62 290 | 80.58 292 | 98.40 276 | 92.73 200 | 92.40 303 | 95.38 355 |
| Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
| UniMVSNet_ETH3D | | | 91.34 305 | 90.22 321 | 94.68 251 | 94.86 363 | 87.86 313 | 97.23 196 | 97.46 204 | 87.99 342 | 89.90 312 | 96.92 213 | 66.35 442 | 98.23 295 | 90.30 257 | 90.99 329 | 97.96 237 |
|
| nrg030 | | | 94.05 177 | 93.31 191 | 96.27 135 | 95.22 341 | 94.59 34 | 98.34 30 | 97.46 204 | 92.93 148 | 91.21 284 | 96.64 229 | 87.23 146 | 98.22 296 | 94.99 129 | 85.80 386 | 95.98 322 |
|
| XVG-OURS | | | 93.72 194 | 93.35 190 | 94.80 245 | 97.07 182 | 88.61 279 | 94.79 385 | 97.46 204 | 91.97 194 | 93.99 202 | 97.86 127 | 81.74 269 | 98.88 203 | 92.64 201 | 92.67 301 | 96.92 291 |
|
| LPG-MVS_test | | | 92.94 229 | 92.56 223 | 94.10 289 | 96.16 283 | 88.26 294 | 97.65 130 | 97.46 204 | 91.29 217 | 90.12 305 | 97.16 193 | 79.05 321 | 98.73 236 | 92.25 205 | 91.89 313 | 95.31 360 |
|
| LGP-MVS_train | | | | | 94.10 289 | 96.16 283 | 88.26 294 | | 97.46 204 | 91.29 217 | 90.12 305 | 97.16 193 | 79.05 321 | 98.73 236 | 92.25 205 | 91.89 313 | 95.31 360 |
|
| MVS | | | 91.71 277 | 90.44 308 | 95.51 202 | 95.20 343 | 91.59 141 | 96.04 315 | 97.45 209 | 73.44 478 | 87.36 384 | 95.60 291 | 85.42 185 | 99.10 173 | 85.97 361 | 97.46 167 | 95.83 327 |
|
| XVG-OURS-SEG-HR | | | 93.86 189 | 93.55 177 | 94.81 242 | 97.06 185 | 88.53 285 | 95.28 361 | 97.45 209 | 91.68 201 | 94.08 201 | 97.68 151 | 82.41 254 | 98.90 202 | 93.84 174 | 92.47 302 | 96.98 286 |
|
| baseline | | | 95.58 107 | 95.42 103 | 96.08 147 | 96.78 220 | 90.41 199 | 97.16 203 | 97.45 209 | 93.69 107 | 95.65 147 | 97.85 129 | 87.29 144 | 98.68 246 | 95.66 108 | 97.25 182 | 99.13 90 |
|
| ab-mvs | | | 93.57 200 | 92.55 224 | 96.64 95 | 97.28 170 | 91.96 127 | 95.40 354 | 97.45 209 | 89.81 280 | 93.22 230 | 96.28 252 | 79.62 312 | 99.46 127 | 90.74 245 | 93.11 293 | 98.50 182 |
|
| xiu_mvs_v2_base | | | 95.32 115 | 95.29 109 | 95.40 210 | 97.22 172 | 90.50 194 | 95.44 353 | 97.44 213 | 93.70 106 | 96.46 110 | 96.18 256 | 88.59 113 | 99.53 113 | 94.79 147 | 97.81 159 | 96.17 312 |
|
| 1314 | | | 92.81 238 | 92.03 241 | 95.14 220 | 95.33 333 | 89.52 242 | 96.04 315 | 97.44 213 | 87.72 356 | 86.25 405 | 95.33 302 | 83.84 216 | 98.79 215 | 89.26 282 | 97.05 191 | 97.11 284 |
|
| casdiffmvs |  | | 95.64 104 | 95.49 97 | 96.08 147 | 96.76 226 | 90.45 196 | 97.29 185 | 97.44 213 | 94.00 95 | 95.46 154 | 97.98 108 | 87.52 138 | 98.73 236 | 95.64 112 | 97.33 176 | 99.08 99 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| viewdifsd2359ckpt07 | | | 94.76 153 | 94.68 138 | 95.01 228 | 96.76 226 | 87.41 322 | 96.38 287 | 97.43 216 | 92.65 161 | 94.52 185 | 97.75 142 | 85.55 183 | 98.81 212 | 94.36 162 | 96.69 205 | 98.82 148 |
|
| XXY-MVS | | | 92.16 262 | 91.23 273 | 94.95 236 | 94.75 368 | 90.94 176 | 97.47 163 | 97.43 216 | 89.14 301 | 88.90 344 | 96.43 244 | 79.71 309 | 98.24 294 | 89.56 273 | 87.68 367 | 95.67 339 |
|
| anonymousdsp | | | 92.16 262 | 91.55 259 | 93.97 299 | 92.58 436 | 89.55 239 | 97.51 153 | 97.42 218 | 89.42 294 | 88.40 358 | 94.84 325 | 80.66 290 | 97.88 351 | 91.87 217 | 91.28 323 | 94.48 415 |
|
| Effi-MVS+ | | | 94.93 141 | 94.45 151 | 96.36 128 | 96.61 234 | 91.47 148 | 96.41 281 | 97.41 219 | 91.02 236 | 94.50 186 | 95.92 270 | 87.53 136 | 98.78 216 | 93.89 172 | 96.81 198 | 98.84 147 |
|
| RRT-MVS | | | 94.51 159 | 94.35 155 | 94.98 232 | 96.40 263 | 86.55 349 | 97.56 145 | 97.41 219 | 93.19 131 | 94.93 172 | 97.04 203 | 79.12 319 | 99.30 146 | 96.19 90 | 97.32 178 | 99.09 97 |
|
| casdiffseed414692147 | | | 94.55 157 | 94.02 163 | 96.15 144 | 96.61 234 | 90.79 183 | 97.42 167 | 97.39 221 | 92.18 186 | 93.95 205 | 97.64 158 | 84.37 207 | 98.66 252 | 90.68 247 | 95.91 229 | 99.00 110 |
|
| HQP3-MVS | | | | | | | | | 97.39 221 | | | | | | | 92.10 310 | |
|
| HQP-MVS | | | 93.19 216 | 92.74 215 | 94.54 262 | 95.86 299 | 89.33 251 | 96.65 261 | 97.39 221 | 93.55 110 | 90.14 299 | 95.87 272 | 80.95 281 | 98.50 269 | 92.13 211 | 92.10 310 | 95.78 331 |
|
| PLC |  | 91.00 6 | 94.11 174 | 93.43 187 | 96.13 145 | 98.58 77 | 91.15 168 | 96.69 257 | 97.39 221 | 87.29 366 | 91.37 274 | 96.71 222 | 88.39 114 | 99.52 117 | 87.33 337 | 97.13 187 | 97.73 254 |
| Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
| diffmvs_AUTHOR | | | 95.33 114 | 95.27 110 | 95.50 204 | 96.37 267 | 89.08 263 | 96.08 313 | 97.38 225 | 93.09 139 | 96.53 105 | 97.74 145 | 86.45 158 | 98.68 246 | 96.32 78 | 97.48 166 | 98.75 159 |
|
| v7n | | | 90.76 329 | 89.86 336 | 93.45 338 | 93.54 410 | 87.60 320 | 97.70 124 | 97.37 226 | 88.85 314 | 87.65 377 | 94.08 373 | 81.08 280 | 98.10 309 | 84.68 378 | 83.79 419 | 94.66 412 |
|
| UnsupCasMVSNet_eth | | | 85.99 417 | 84.45 418 | 90.62 423 | 89.97 457 | 82.40 425 | 93.62 433 | 97.37 226 | 89.86 276 | 78.59 468 | 92.37 420 | 65.25 454 | 95.35 457 | 82.27 407 | 70.75 476 | 94.10 426 |
|
| viewdifsd2359ckpt13 | | | 94.87 145 | 94.52 147 | 95.90 163 | 96.88 203 | 90.19 210 | 96.92 225 | 97.36 228 | 91.26 221 | 94.65 181 | 97.46 172 | 85.79 173 | 98.64 254 | 93.64 178 | 96.76 200 | 98.88 140 |
|
| ACMM | | 89.79 8 | 92.96 227 | 92.50 228 | 94.35 272 | 96.30 271 | 88.71 275 | 97.58 141 | 97.36 228 | 91.40 215 | 90.53 292 | 96.65 228 | 79.77 308 | 98.75 232 | 91.24 233 | 91.64 315 | 95.59 341 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| xiu_mvs_v1_base_debu | | | 95.01 136 | 94.76 133 | 95.75 182 | 96.58 240 | 91.71 134 | 96.25 300 | 97.35 230 | 92.99 141 | 96.70 92 | 96.63 233 | 82.67 246 | 99.44 130 | 96.22 83 | 97.46 167 | 96.11 318 |
|
| xiu_mvs_v1_base | | | 95.01 136 | 94.76 133 | 95.75 182 | 96.58 240 | 91.71 134 | 96.25 300 | 97.35 230 | 92.99 141 | 96.70 92 | 96.63 233 | 82.67 246 | 99.44 130 | 96.22 83 | 97.46 167 | 96.11 318 |
|
| xiu_mvs_v1_base_debi | | | 95.01 136 | 94.76 133 | 95.75 182 | 96.58 240 | 91.71 134 | 96.25 300 | 97.35 230 | 92.99 141 | 96.70 92 | 96.63 233 | 82.67 246 | 99.44 130 | 96.22 83 | 97.46 167 | 96.11 318 |
|
| diffmvs |  | | 95.25 120 | 95.13 114 | 95.63 190 | 96.43 262 | 89.34 250 | 95.99 319 | 97.35 230 | 92.83 155 | 96.31 117 | 97.37 179 | 86.44 159 | 98.67 249 | 96.26 80 | 97.19 185 | 98.87 142 |
| Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025 |
| WTY-MVS | | | 94.71 155 | 94.02 163 | 96.79 91 | 97.71 145 | 92.05 121 | 96.59 270 | 97.35 230 | 90.61 255 | 94.64 182 | 96.93 210 | 86.41 160 | 99.39 135 | 91.20 234 | 94.71 264 | 98.94 123 |
|
| viewdifsd2359ckpt09 | | | 94.81 150 | 94.37 154 | 96.12 146 | 96.91 200 | 90.75 187 | 96.94 222 | 97.31 235 | 90.51 262 | 94.31 191 | 97.38 178 | 85.70 175 | 98.71 242 | 93.54 179 | 96.75 201 | 98.90 132 |
|
| balanced_ft_v1 | | | 95.56 109 | 95.40 104 | 96.07 149 | 97.16 176 | 90.36 205 | 98.23 44 | 97.31 235 | 92.89 153 | 96.36 115 | 97.11 198 | 83.28 226 | 99.26 149 | 97.40 49 | 98.80 115 | 98.58 173 |
|
| SSM_0407 | | | 94.54 158 | 94.12 162 | 95.80 173 | 96.79 215 | 90.38 201 | 96.79 243 | 97.29 237 | 91.24 222 | 93.68 210 | 97.60 163 | 85.03 193 | 98.67 249 | 92.14 208 | 96.51 211 | 98.35 201 |
|
| SSM_0404 | | | 94.73 154 | 94.31 157 | 95.98 160 | 97.05 187 | 90.90 179 | 97.01 215 | 97.29 237 | 91.24 222 | 94.17 198 | 97.60 163 | 85.03 193 | 98.76 226 | 92.14 208 | 97.30 179 | 98.29 208 |
|
| F-COLMAP | | | 93.58 198 | 92.98 204 | 95.37 211 | 98.40 87 | 88.98 269 | 97.18 201 | 97.29 237 | 87.75 355 | 90.49 293 | 97.10 200 | 85.21 190 | 99.50 121 | 86.70 347 | 96.72 204 | 97.63 258 |
|
| VortexMVS | | | 92.88 233 | 92.64 219 | 93.58 329 | 96.58 240 | 87.53 321 | 96.93 224 | 97.28 240 | 92.78 158 | 89.75 317 | 94.99 316 | 82.73 245 | 97.76 364 | 94.60 155 | 88.16 362 | 95.46 346 |
|
| XVG-ACMP-BASELINE | | | 90.93 325 | 90.21 322 | 93.09 351 | 94.31 387 | 85.89 367 | 95.33 358 | 97.26 241 | 91.06 235 | 89.38 330 | 95.44 300 | 68.61 425 | 98.60 259 | 89.46 275 | 91.05 327 | 94.79 404 |
|
| PCF-MVS | | 89.48 11 | 91.56 289 | 89.95 333 | 96.36 128 | 96.60 236 | 92.52 104 | 92.51 453 | 97.26 241 | 79.41 462 | 88.90 344 | 96.56 238 | 84.04 215 | 99.55 109 | 77.01 446 | 97.30 179 | 97.01 285 |
| Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
| ACMP | | 89.59 10 | 92.62 242 | 92.14 237 | 94.05 292 | 96.40 263 | 88.20 300 | 97.36 177 | 97.25 243 | 91.52 208 | 88.30 362 | 96.64 229 | 78.46 333 | 98.72 241 | 91.86 218 | 91.48 319 | 95.23 367 |
| Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
| icg_test_0407_2 | | | 93.58 198 | 93.46 184 | 93.94 303 | 96.19 277 | 86.16 361 | 93.73 427 | 97.24 244 | 91.54 204 | 93.50 219 | 97.04 203 | 85.64 181 | 96.91 425 | 90.68 247 | 95.59 240 | 98.76 155 |
|
| IMVS_0407 | | | 93.94 184 | 93.75 170 | 94.49 265 | 96.19 277 | 86.16 361 | 96.35 290 | 97.24 244 | 91.54 204 | 93.50 219 | 97.04 203 | 85.64 181 | 98.54 266 | 90.68 247 | 95.59 240 | 98.76 155 |
|
| IMVS_0404 | | | 92.44 246 | 91.92 246 | 94.00 295 | 96.19 277 | 86.16 361 | 93.84 424 | 97.24 244 | 91.54 204 | 88.17 368 | 97.04 203 | 76.96 351 | 97.09 416 | 90.68 247 | 95.59 240 | 98.76 155 |
|
| IMVS_0403 | | | 93.98 182 | 93.79 169 | 94.55 261 | 96.19 277 | 86.16 361 | 96.35 290 | 97.24 244 | 91.54 204 | 93.59 214 | 97.04 203 | 85.86 170 | 98.73 236 | 90.68 247 | 95.59 240 | 98.76 155 |
|
| OPM-MVS | | | 93.28 212 | 92.76 212 | 94.82 240 | 94.63 374 | 90.77 185 | 96.65 261 | 97.18 248 | 93.72 104 | 91.68 268 | 97.26 188 | 79.33 316 | 98.63 256 | 92.13 211 | 92.28 304 | 95.07 376 |
| Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS). |
| PatchMatch-RL | | | 92.90 231 | 92.02 242 | 95.56 194 | 98.19 110 | 90.80 182 | 95.27 363 | 97.18 248 | 87.96 343 | 91.86 263 | 95.68 287 | 80.44 295 | 98.99 192 | 84.01 387 | 97.54 165 | 96.89 292 |
|
| alignmvs | | | 95.87 100 | 95.23 111 | 97.78 37 | 97.56 163 | 95.19 23 | 97.86 92 | 97.17 250 | 94.39 83 | 96.47 109 | 96.40 246 | 85.89 169 | 99.20 155 | 96.21 87 | 95.11 254 | 98.95 120 |
|
| MVS_Test | | | 94.89 143 | 94.62 140 | 95.68 188 | 96.83 210 | 89.55 239 | 96.70 255 | 97.17 250 | 91.17 228 | 95.60 148 | 96.11 265 | 87.87 126 | 98.76 226 | 93.01 197 | 97.17 186 | 98.72 163 |
|
| Fast-Effi-MVS+ | | | 93.46 204 | 92.75 214 | 95.59 193 | 96.77 222 | 90.03 212 | 96.81 241 | 97.13 252 | 88.19 336 | 91.30 278 | 94.27 361 | 86.21 163 | 98.63 256 | 87.66 326 | 96.46 217 | 98.12 222 |
|
| usedtu_dtu_shiyan1 | | | 91.65 281 | 90.67 300 | 94.60 253 | 93.65 407 | 90.95 174 | 94.86 382 | 97.12 253 | 89.69 283 | 89.21 338 | 93.62 392 | 81.17 278 | 97.67 371 | 87.54 330 | 89.14 349 | 95.17 373 |
|
| FE-MVSNET3 | | | 91.65 281 | 90.67 300 | 94.60 253 | 93.65 407 | 90.95 174 | 94.86 382 | 97.12 253 | 89.69 283 | 89.21 338 | 93.62 392 | 81.17 278 | 97.67 371 | 87.54 330 | 89.14 349 | 95.17 373 |
|
| EI-MVSNet | | | 93.03 224 | 92.88 208 | 93.48 336 | 95.77 305 | 86.98 335 | 96.44 275 | 97.12 253 | 90.66 251 | 91.30 278 | 97.64 158 | 86.56 154 | 98.05 321 | 89.91 263 | 90.55 335 | 95.41 350 |
|
| MVSTER | | | 93.20 215 | 92.81 211 | 94.37 271 | 96.56 245 | 89.59 235 | 97.06 209 | 97.12 253 | 91.24 222 | 91.30 278 | 95.96 268 | 82.02 262 | 98.05 321 | 93.48 182 | 90.55 335 | 95.47 345 |
|
| viewmambaseed2359dif | | | 94.28 164 | 94.14 160 | 94.71 250 | 96.21 273 | 86.97 336 | 95.93 322 | 97.11 257 | 89.00 307 | 95.00 171 | 97.70 148 | 86.02 168 | 98.59 263 | 93.71 177 | 96.59 210 | 98.57 175 |
|
| test_yl | | | 94.78 151 | 94.23 158 | 96.43 120 | 97.74 143 | 91.22 157 | 96.85 233 | 97.10 258 | 91.23 225 | 95.71 142 | 96.93 210 | 84.30 208 | 99.31 144 | 93.10 190 | 95.12 252 | 98.75 159 |
|
| DCV-MVSNet | | | 94.78 151 | 94.23 158 | 96.43 120 | 97.74 143 | 91.22 157 | 96.85 233 | 97.10 258 | 91.23 225 | 95.71 142 | 96.93 210 | 84.30 208 | 99.31 144 | 93.10 190 | 95.12 252 | 98.75 159 |
|
| LTVRE_ROB | | 88.41 13 | 90.99 321 | 89.92 335 | 94.19 283 | 96.18 281 | 89.55 239 | 96.31 296 | 97.09 260 | 87.88 346 | 85.67 417 | 95.91 271 | 78.79 329 | 98.57 264 | 81.50 410 | 89.98 340 | 94.44 418 |
| 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 |
| viewmsd2359difaftdt | | | 93.46 204 | 93.23 194 | 94.17 284 | 96.12 288 | 85.42 376 | 96.43 277 | 97.08 261 | 92.91 149 | 94.21 194 | 98.00 105 | 80.82 287 | 98.74 234 | 94.41 159 | 89.05 351 | 98.34 205 |
|
| test_fmvs1_n | | | 92.73 240 | 92.88 208 | 92.29 377 | 96.08 293 | 81.05 436 | 97.98 72 | 97.08 261 | 90.72 246 | 96.79 88 | 98.18 91 | 63.07 459 | 98.45 273 | 97.62 39 | 98.42 135 | 97.36 273 |
|
| v10 | | | 91.04 319 | 90.23 319 | 93.49 335 | 94.12 390 | 88.16 303 | 97.32 182 | 97.08 261 | 88.26 335 | 88.29 363 | 94.22 366 | 82.17 259 | 97.97 333 | 86.45 351 | 84.12 413 | 94.33 421 |
|
| viewdifsd2359ckpt11 | | | 93.46 204 | 93.22 195 | 94.17 284 | 96.11 290 | 85.42 376 | 96.43 277 | 97.07 264 | 92.91 149 | 94.20 195 | 98.00 105 | 80.82 287 | 98.73 236 | 94.42 158 | 89.04 353 | 98.34 205 |
|
| mamba_0408 | | | 93.70 195 | 92.99 201 | 95.83 170 | 96.79 215 | 90.38 201 | 88.69 480 | 97.07 264 | 90.96 238 | 93.68 210 | 97.31 183 | 84.97 196 | 98.76 226 | 90.95 238 | 96.51 211 | 98.35 201 |
|
| SSM_04072 | | | 93.51 203 | 92.99 201 | 95.05 224 | 96.79 215 | 90.38 201 | 88.69 480 | 97.07 264 | 90.96 238 | 93.68 210 | 97.31 183 | 84.97 196 | 96.42 436 | 90.95 238 | 96.51 211 | 98.35 201 |
|
| v144192 | | | 91.06 318 | 90.28 315 | 93.39 339 | 93.66 405 | 87.23 329 | 96.83 237 | 97.07 264 | 87.43 362 | 89.69 320 | 94.28 360 | 81.48 272 | 98.00 328 | 87.18 341 | 84.92 402 | 94.93 384 |
|
| v1192 | | | 91.07 317 | 90.23 319 | 93.58 329 | 93.70 402 | 87.82 315 | 96.73 251 | 97.07 264 | 87.77 353 | 89.58 323 | 94.32 358 | 80.90 285 | 97.97 333 | 86.52 349 | 85.48 389 | 94.95 380 |
|
| v8 | | | 91.29 309 | 90.53 307 | 93.57 331 | 94.15 389 | 88.12 304 | 97.34 179 | 97.06 269 | 88.99 308 | 88.32 361 | 94.26 363 | 83.08 233 | 98.01 327 | 87.62 328 | 83.92 417 | 94.57 414 |
|
| mvs_anonymous | | | 93.82 190 | 93.74 171 | 94.06 291 | 96.44 261 | 85.41 378 | 95.81 330 | 97.05 270 | 89.85 278 | 90.09 308 | 96.36 248 | 87.44 141 | 97.75 366 | 93.97 168 | 96.69 205 | 99.02 104 |
|
| IterMVS-LS | | | 92.29 256 | 91.94 245 | 93.34 341 | 96.25 272 | 86.97 336 | 96.57 273 | 97.05 270 | 90.67 249 | 89.50 328 | 94.80 328 | 86.59 153 | 97.64 376 | 89.91 263 | 86.11 384 | 95.40 353 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| v1921920 | | | 90.85 327 | 90.03 330 | 93.29 343 | 93.55 409 | 86.96 338 | 96.74 250 | 97.04 272 | 87.36 364 | 89.52 327 | 94.34 355 | 80.23 300 | 97.97 333 | 86.27 352 | 85.21 395 | 94.94 382 |
|
| CDS-MVSNet | | | 94.14 173 | 93.54 178 | 95.93 161 | 96.18 281 | 91.46 149 | 96.33 294 | 97.04 272 | 88.97 310 | 93.56 215 | 96.51 240 | 87.55 134 | 97.89 350 | 89.80 266 | 95.95 227 | 98.44 192 |
| Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
| SSC-MVS3.2 | | | 89.74 363 | 89.26 356 | 91.19 412 | 95.16 344 | 80.29 447 | 94.53 392 | 97.03 274 | 91.79 197 | 88.86 347 | 94.10 370 | 69.94 414 | 97.82 356 | 85.29 370 | 86.66 380 | 95.45 348 |
|
| v1144 | | | 91.37 302 | 90.60 303 | 93.68 321 | 93.89 397 | 88.23 296 | 96.84 236 | 97.03 274 | 88.37 332 | 89.69 320 | 94.39 350 | 82.04 261 | 97.98 330 | 87.80 313 | 85.37 391 | 94.84 393 |
|
| v1240 | | | 90.70 333 | 89.85 337 | 93.23 345 | 93.51 412 | 86.80 339 | 96.61 267 | 97.02 276 | 87.16 369 | 89.58 323 | 94.31 359 | 79.55 313 | 97.98 330 | 85.52 367 | 85.44 390 | 94.90 387 |
|
| EPP-MVSNet | | | 95.22 123 | 95.04 119 | 95.76 180 | 97.49 164 | 89.56 237 | 98.67 15 | 97.00 277 | 90.69 247 | 94.24 193 | 97.62 161 | 89.79 93 | 98.81 212 | 93.39 186 | 96.49 215 | 98.92 128 |
|
| V42 | | | 91.58 288 | 90.87 285 | 93.73 314 | 94.05 393 | 88.50 286 | 97.32 182 | 96.97 278 | 88.80 320 | 89.71 318 | 94.33 356 | 82.54 250 | 98.05 321 | 89.01 290 | 85.07 398 | 94.64 413 |
|
| test_fmvs1 | | | 93.21 214 | 93.53 179 | 92.25 380 | 96.55 247 | 81.20 435 | 97.40 173 | 96.96 279 | 90.68 248 | 96.80 86 | 98.04 100 | 69.25 420 | 98.40 276 | 97.58 40 | 98.50 128 | 97.16 283 |
|
| FMVSNet2 | | | 91.31 306 | 90.08 325 | 94.99 230 | 96.51 254 | 92.21 115 | 97.41 169 | 96.95 280 | 88.82 317 | 88.62 353 | 94.75 330 | 73.87 378 | 97.42 403 | 85.20 373 | 88.55 359 | 95.35 357 |
|
| ACMH | | 87.59 16 | 90.53 338 | 89.42 352 | 93.87 308 | 96.21 273 | 87.92 310 | 97.24 192 | 96.94 281 | 88.45 330 | 83.91 439 | 96.27 253 | 71.92 395 | 98.62 258 | 84.43 381 | 89.43 346 | 95.05 378 |
| Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
| GBi-Net | | | 91.35 303 | 90.27 316 | 94.59 255 | 96.51 254 | 91.18 164 | 97.50 154 | 96.93 282 | 88.82 317 | 89.35 331 | 94.51 343 | 73.87 378 | 97.29 411 | 86.12 357 | 88.82 354 | 95.31 360 |
|
| test1 | | | 91.35 303 | 90.27 316 | 94.59 255 | 96.51 254 | 91.18 164 | 97.50 154 | 96.93 282 | 88.82 317 | 89.35 331 | 94.51 343 | 73.87 378 | 97.29 411 | 86.12 357 | 88.82 354 | 95.31 360 |
|
| FMVSNet3 | | | 91.78 275 | 90.69 299 | 95.03 227 | 96.53 250 | 92.27 113 | 97.02 212 | 96.93 282 | 89.79 281 | 89.35 331 | 94.65 336 | 77.01 349 | 97.47 398 | 86.12 357 | 88.82 354 | 95.35 357 |
|
| FMVSNet1 | | | 89.88 358 | 88.31 371 | 94.59 255 | 95.41 323 | 91.18 164 | 97.50 154 | 96.93 282 | 86.62 377 | 87.41 382 | 94.51 343 | 65.94 447 | 97.29 411 | 83.04 396 | 87.43 370 | 95.31 360 |
|
| GeoE | | | 93.89 187 | 93.28 192 | 95.72 186 | 96.96 198 | 89.75 227 | 98.24 43 | 96.92 286 | 89.47 291 | 92.12 254 | 97.21 191 | 84.42 205 | 98.39 281 | 87.71 318 | 96.50 214 | 99.01 107 |
|
| SymmetryMVS | | | 95.94 96 | 95.54 95 | 97.15 75 | 97.85 136 | 92.90 88 | 97.99 69 | 96.91 287 | 95.92 16 | 96.57 103 | 97.93 112 | 85.34 186 | 99.50 121 | 94.99 129 | 96.39 222 | 99.05 103 |
|
| miper_enhance_ethall | | | 91.54 292 | 91.01 281 | 93.15 349 | 95.35 329 | 87.07 334 | 93.97 416 | 96.90 288 | 86.79 375 | 89.17 340 | 93.43 404 | 86.55 155 | 97.64 376 | 89.97 262 | 86.93 375 | 94.74 409 |
|
| eth_miper_zixun_eth | | | 91.02 320 | 90.59 304 | 92.34 375 | 95.33 333 | 84.35 397 | 94.10 413 | 96.90 288 | 88.56 326 | 88.84 349 | 94.33 356 | 84.08 213 | 97.60 381 | 88.77 298 | 84.37 411 | 95.06 377 |
|
| TAMVS | | | 94.01 179 | 93.46 184 | 95.64 189 | 96.16 283 | 90.45 196 | 96.71 254 | 96.89 290 | 89.27 298 | 93.46 222 | 96.92 213 | 87.29 144 | 97.94 343 | 88.70 300 | 95.74 234 | 98.53 178 |
|
| miper_ehance_all_eth | | | 91.59 286 | 91.13 277 | 92.97 355 | 95.55 315 | 86.57 347 | 94.47 397 | 96.88 291 | 87.77 353 | 88.88 346 | 94.01 375 | 86.22 162 | 97.54 391 | 89.49 274 | 86.93 375 | 94.79 404 |
|
| v2v482 | | | 91.59 286 | 90.85 288 | 93.80 311 | 93.87 398 | 88.17 302 | 96.94 222 | 96.88 291 | 89.54 288 | 89.53 326 | 94.90 322 | 81.70 270 | 98.02 326 | 89.25 283 | 85.04 400 | 95.20 368 |
|
| CNLPA | | | 94.28 164 | 93.53 179 | 96.52 108 | 98.38 90 | 92.55 103 | 96.59 270 | 96.88 291 | 90.13 272 | 91.91 260 | 97.24 189 | 85.21 190 | 99.09 176 | 87.64 327 | 97.83 158 | 97.92 240 |
|
| PAPM | | | 91.52 293 | 90.30 314 | 95.20 217 | 95.30 336 | 89.83 224 | 93.38 438 | 96.85 294 | 86.26 385 | 88.59 354 | 95.80 277 | 84.88 198 | 98.15 303 | 75.67 451 | 95.93 228 | 97.63 258 |
|
| c3_l | | | 91.38 300 | 90.89 284 | 92.88 359 | 95.58 313 | 86.30 355 | 94.68 387 | 96.84 295 | 88.17 337 | 88.83 350 | 94.23 364 | 85.65 178 | 97.47 398 | 89.36 278 | 84.63 404 | 94.89 388 |
|
| pm-mvs1 | | | 90.72 332 | 89.65 347 | 93.96 300 | 94.29 388 | 89.63 232 | 97.79 107 | 96.82 296 | 89.07 303 | 86.12 410 | 95.48 299 | 78.61 331 | 97.78 361 | 86.97 345 | 81.67 430 | 94.46 416 |
|
| test_vis1_n | | | 92.37 251 | 92.26 235 | 92.72 365 | 94.75 368 | 82.64 418 | 98.02 66 | 96.80 297 | 91.18 227 | 97.77 60 | 97.93 112 | 58.02 470 | 98.29 291 | 97.63 37 | 98.21 143 | 97.23 281 |
|
| CMPMVS |  | 62.92 21 | 85.62 422 | 84.92 411 | 87.74 450 | 89.14 462 | 73.12 480 | 94.17 411 | 96.80 297 | 73.98 475 | 73.65 478 | 94.93 320 | 66.36 441 | 97.61 380 | 83.95 389 | 91.28 323 | 92.48 454 |
| M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
| MS-PatchMatch | | | 90.27 345 | 89.77 341 | 91.78 396 | 94.33 385 | 84.72 394 | 95.55 346 | 96.73 299 | 86.17 387 | 86.36 404 | 95.28 305 | 71.28 400 | 97.80 359 | 84.09 386 | 98.14 147 | 92.81 446 |
|
| Effi-MVS+-dtu | | | 93.08 221 | 93.21 196 | 92.68 368 | 96.02 296 | 83.25 411 | 97.14 205 | 96.72 300 | 93.85 101 | 91.20 285 | 93.44 401 | 83.08 233 | 98.30 290 | 91.69 224 | 95.73 235 | 96.50 303 |
|
| TSAR-MVS + GP. | | | 96.69 67 | 96.49 71 | 97.27 68 | 98.31 93 | 93.39 68 | 96.79 243 | 96.72 300 | 94.17 89 | 97.44 66 | 97.66 154 | 92.76 34 | 99.33 140 | 96.86 62 | 97.76 162 | 99.08 99 |
|
| 1112_ss | | | 93.37 209 | 92.42 231 | 96.21 140 | 97.05 187 | 90.99 171 | 96.31 296 | 96.72 300 | 86.87 374 | 89.83 315 | 96.69 226 | 86.51 156 | 99.14 168 | 88.12 305 | 93.67 287 | 98.50 182 |
|
| PVSNet | | 86.66 18 | 92.24 259 | 91.74 254 | 93.73 314 | 97.77 141 | 83.69 408 | 92.88 447 | 96.72 300 | 87.91 345 | 93.00 233 | 94.86 324 | 78.51 332 | 99.05 187 | 86.53 348 | 97.45 171 | 98.47 187 |
|
| miper_lstm_enhance | | | 90.50 341 | 90.06 329 | 91.83 392 | 95.33 333 | 83.74 405 | 93.86 422 | 96.70 304 | 87.56 360 | 87.79 374 | 93.81 383 | 83.45 224 | 96.92 424 | 87.39 335 | 84.62 405 | 94.82 399 |
|
| v148 | | | 90.99 321 | 90.38 310 | 92.81 362 | 93.83 399 | 85.80 368 | 96.78 247 | 96.68 305 | 89.45 293 | 88.75 352 | 93.93 379 | 82.96 239 | 97.82 356 | 87.83 311 | 83.25 422 | 94.80 402 |
|
| ACMH+ | | 87.92 14 | 90.20 349 | 89.18 358 | 93.25 344 | 96.48 257 | 86.45 352 | 96.99 218 | 96.68 305 | 88.83 316 | 84.79 427 | 96.22 255 | 70.16 411 | 98.53 267 | 84.42 382 | 88.04 363 | 94.77 407 |
|
| CANet_DTU | | | 94.37 162 | 93.65 174 | 96.55 105 | 96.46 260 | 92.13 119 | 96.21 304 | 96.67 307 | 94.38 84 | 93.53 218 | 97.03 208 | 79.34 315 | 99.71 67 | 90.76 244 | 98.45 133 | 97.82 251 |
|
| cl____ | | | 90.96 324 | 90.32 312 | 92.89 358 | 95.37 327 | 86.21 358 | 94.46 399 | 96.64 308 | 87.82 349 | 88.15 369 | 94.18 367 | 82.98 237 | 97.54 391 | 87.70 319 | 85.59 387 | 94.92 386 |
|
| HY-MVS | | 89.66 9 | 93.87 188 | 92.95 205 | 96.63 99 | 97.10 181 | 92.49 105 | 95.64 343 | 96.64 308 | 89.05 305 | 93.00 233 | 95.79 280 | 85.77 174 | 99.45 129 | 89.16 288 | 94.35 266 | 97.96 237 |
|
| Test_1112_low_res | | | 92.84 236 | 91.84 249 | 95.85 169 | 97.04 189 | 89.97 219 | 95.53 348 | 96.64 308 | 85.38 397 | 89.65 322 | 95.18 310 | 85.86 170 | 99.10 173 | 87.70 319 | 93.58 292 | 98.49 184 |
|
| DIV-MVS_self_test | | | 90.97 323 | 90.33 311 | 92.88 359 | 95.36 328 | 86.19 360 | 94.46 399 | 96.63 311 | 87.82 349 | 88.18 367 | 94.23 364 | 82.99 236 | 97.53 393 | 87.72 316 | 85.57 388 | 94.93 384 |
|
| Fast-Effi-MVS+-dtu | | | 92.29 256 | 91.99 243 | 93.21 347 | 95.27 337 | 85.52 374 | 97.03 210 | 96.63 311 | 92.09 188 | 89.11 342 | 95.14 312 | 80.33 298 | 98.08 314 | 87.54 330 | 94.74 262 | 96.03 321 |
|
| UnsupCasMVSNet_bld | | | 82.13 439 | 79.46 444 | 90.14 429 | 88.00 477 | 82.47 423 | 90.89 468 | 96.62 313 | 78.94 464 | 75.61 473 | 84.40 481 | 56.63 473 | 96.31 438 | 77.30 443 | 66.77 485 | 91.63 465 |
|
| cl22 | | | 91.21 311 | 90.56 306 | 93.14 350 | 96.09 292 | 86.80 339 | 94.41 401 | 96.58 314 | 87.80 351 | 88.58 355 | 93.99 377 | 80.85 286 | 97.62 379 | 89.87 265 | 86.93 375 | 94.99 379 |
|
| jason | | | 94.84 147 | 94.39 153 | 96.18 142 | 95.52 316 | 90.93 177 | 96.09 312 | 96.52 315 | 89.28 297 | 96.01 131 | 97.32 181 | 84.70 200 | 98.77 220 | 95.15 125 | 98.91 112 | 98.85 144 |
| jason: jason. |
| tt0805 | | | 91.09 316 | 90.07 328 | 94.16 287 | 95.61 311 | 88.31 291 | 97.56 145 | 96.51 316 | 89.56 287 | 89.17 340 | 95.64 289 | 67.08 439 | 98.38 282 | 91.07 236 | 88.44 360 | 95.80 329 |
|
| AUN-MVS | | | 91.76 276 | 90.75 294 | 94.81 242 | 97.00 194 | 88.57 281 | 96.65 261 | 96.49 317 | 89.63 285 | 92.15 252 | 96.12 261 | 78.66 330 | 98.50 269 | 90.83 240 | 79.18 441 | 97.36 273 |
|
| hse-mvs2 | | | 93.45 207 | 92.99 201 | 94.81 242 | 97.02 192 | 88.59 280 | 96.69 257 | 96.47 318 | 95.19 36 | 96.74 90 | 96.16 259 | 83.67 219 | 98.48 272 | 95.85 102 | 79.13 442 | 97.35 275 |
|
| SD_0403 | | | 90.01 353 | 90.02 331 | 89.96 432 | 95.65 310 | 76.76 469 | 95.76 334 | 96.46 319 | 90.58 258 | 86.59 401 | 96.29 251 | 82.12 260 | 94.78 461 | 73.00 465 | 93.76 285 | 98.35 201 |
|
| EG-PatchMatch MVS | | | 87.02 399 | 85.44 400 | 91.76 398 | 92.67 433 | 85.00 388 | 96.08 313 | 96.45 320 | 83.41 431 | 79.52 462 | 93.49 398 | 57.10 472 | 97.72 368 | 79.34 434 | 90.87 332 | 92.56 451 |
|
| KD-MVS_self_test | | | 85.95 418 | 84.95 410 | 88.96 444 | 89.55 461 | 79.11 463 | 95.13 375 | 96.42 321 | 85.91 390 | 84.07 437 | 90.48 443 | 70.03 413 | 94.82 460 | 80.04 426 | 72.94 466 | 92.94 444 |
|
| FE-MVSNET2 | | | 86.36 409 | 84.68 416 | 91.39 406 | 87.67 479 | 86.47 351 | 96.21 304 | 96.41 322 | 87.87 347 | 79.31 464 | 89.64 451 | 65.29 452 | 95.58 452 | 82.42 405 | 77.28 448 | 92.14 462 |
|
| pmmvs6 | | | 87.81 385 | 86.19 393 | 92.69 367 | 91.32 447 | 86.30 355 | 97.34 179 | 96.41 322 | 80.59 458 | 84.05 438 | 94.37 352 | 67.37 434 | 97.67 371 | 84.75 377 | 79.51 440 | 94.09 428 |
|
| PMMVS | | | 92.86 234 | 92.34 232 | 94.42 270 | 94.92 359 | 86.73 342 | 94.53 392 | 96.38 324 | 84.78 409 | 94.27 192 | 95.12 314 | 83.13 232 | 98.40 276 | 91.47 228 | 96.49 215 | 98.12 222 |
|
| RPSCF | | | 90.75 330 | 90.86 286 | 90.42 426 | 96.84 208 | 76.29 472 | 95.61 344 | 96.34 325 | 83.89 419 | 91.38 273 | 97.87 125 | 76.45 355 | 98.78 216 | 87.16 342 | 92.23 305 | 96.20 310 |
|
| BP-MVS1 | | | 95.89 98 | 95.49 97 | 97.08 82 | 96.67 229 | 93.20 78 | 98.08 59 | 96.32 326 | 94.56 72 | 96.32 116 | 97.84 131 | 84.07 214 | 99.15 165 | 96.75 64 | 98.78 116 | 98.90 132 |
|
| MSDG | | | 91.42 298 | 90.24 318 | 94.96 235 | 97.15 179 | 88.91 270 | 93.69 430 | 96.32 326 | 85.72 393 | 86.93 397 | 96.47 242 | 80.24 299 | 98.98 193 | 80.57 423 | 95.05 255 | 96.98 286 |
|
| blended_shiyan6 | | | 87.55 389 | 85.52 399 | 93.64 324 | 88.78 467 | 88.50 286 | 95.23 366 | 96.30 328 | 82.80 437 | 86.09 411 | 87.70 468 | 73.69 384 | 97.56 384 | 87.70 319 | 71.36 472 | 94.86 389 |
|
| blend_shiyan4 | | | 86.87 400 | 84.61 417 | 93.67 322 | 88.87 465 | 88.70 276 | 95.17 373 | 96.30 328 | 82.80 437 | 86.16 407 | 87.11 472 | 65.12 455 | 97.55 386 | 87.73 314 | 72.21 468 | 94.75 408 |
|
| WBMVS | | | 90.69 335 | 89.99 332 | 92.81 362 | 96.48 257 | 85.00 388 | 95.21 369 | 96.30 328 | 89.46 292 | 89.04 343 | 94.05 374 | 72.45 393 | 97.82 356 | 89.46 275 | 87.41 372 | 95.61 340 |
|
| blended_shiyan8 | | | 87.58 388 | 85.55 398 | 93.66 323 | 88.76 469 | 88.54 283 | 95.21 369 | 96.29 331 | 82.81 436 | 86.25 405 | 87.73 467 | 73.70 383 | 97.58 383 | 87.81 312 | 71.42 471 | 94.85 392 |
|
| OurMVSNet-221017-0 | | | 90.51 340 | 90.19 323 | 91.44 404 | 93.41 418 | 81.25 433 | 96.98 219 | 96.28 332 | 91.68 201 | 86.55 402 | 96.30 250 | 74.20 377 | 97.98 330 | 88.96 293 | 87.40 373 | 95.09 375 |
|
| wanda-best-256-512 | | | 87.29 392 | 85.21 404 | 93.53 332 | 88.54 473 | 88.21 298 | 94.51 395 | 96.27 333 | 82.69 440 | 85.92 413 | 86.89 475 | 73.04 387 | 97.55 386 | 87.68 323 | 71.36 472 | 94.83 394 |
|
| FE-blended-shiyan7 | | | 87.29 392 | 85.21 404 | 93.53 332 | 88.54 473 | 88.21 298 | 94.51 395 | 96.27 333 | 82.69 440 | 85.92 413 | 86.89 475 | 73.03 388 | 97.55 386 | 87.68 323 | 71.36 472 | 94.83 394 |
|
| MVP-Stereo | | | 90.74 331 | 90.08 325 | 92.71 366 | 93.19 423 | 88.20 300 | 95.86 326 | 96.27 333 | 86.07 388 | 84.86 426 | 94.76 329 | 77.84 344 | 97.75 366 | 83.88 391 | 98.01 153 | 92.17 461 |
| Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
| lupinMVS | | | 94.99 140 | 94.56 143 | 96.29 134 | 96.34 269 | 91.21 159 | 95.83 328 | 96.27 333 | 88.93 312 | 96.22 121 | 96.88 215 | 86.20 164 | 98.85 206 | 95.27 121 | 99.05 103 | 98.82 148 |
|
| BH-untuned | | | 92.94 229 | 92.62 221 | 93.92 307 | 97.22 172 | 86.16 361 | 96.40 285 | 96.25 337 | 90.06 273 | 89.79 316 | 96.17 258 | 83.19 229 | 98.35 284 | 87.19 340 | 97.27 181 | 97.24 280 |
|
| CL-MVSNet_self_test | | | 86.31 411 | 85.15 407 | 89.80 434 | 88.83 466 | 81.74 431 | 93.93 419 | 96.22 338 | 86.67 376 | 85.03 424 | 90.80 441 | 78.09 340 | 94.50 462 | 74.92 454 | 71.86 469 | 93.15 442 |
|
| IS-MVSNet | | | 94.90 142 | 94.52 147 | 96.05 151 | 97.67 147 | 90.56 192 | 98.44 26 | 96.22 338 | 93.21 128 | 93.99 202 | 97.74 145 | 85.55 183 | 98.45 273 | 89.98 261 | 97.86 157 | 99.14 89 |
|
| FA-MVS(test-final) | | | 93.52 202 | 92.92 206 | 95.31 214 | 96.77 222 | 88.54 283 | 94.82 384 | 96.21 340 | 89.61 286 | 94.20 195 | 95.25 308 | 83.24 227 | 99.14 168 | 90.01 260 | 96.16 224 | 98.25 210 |
|
| gbinet_0.2-2-1-0.02 | | | 87.30 391 | 85.16 406 | 93.69 318 | 88.70 472 | 88.81 273 | 95.14 374 | 96.20 341 | 83.03 434 | 86.14 409 | 87.06 473 | 71.26 401 | 97.40 405 | 87.46 334 | 71.49 470 | 94.86 389 |
|
| GA-MVS | | | 91.38 300 | 90.31 313 | 94.59 255 | 94.65 373 | 87.62 319 | 94.34 404 | 96.19 342 | 90.73 245 | 90.35 296 | 93.83 380 | 71.84 396 | 97.96 337 | 87.22 339 | 93.61 290 | 98.21 213 |
|
| LuminaMVS | | | 94.89 143 | 94.35 155 | 96.53 106 | 95.48 318 | 92.80 92 | 96.88 231 | 96.18 343 | 92.85 154 | 95.92 134 | 96.87 217 | 81.44 273 | 98.83 209 | 96.43 77 | 97.10 188 | 97.94 239 |
|
| IterMVS-SCA-FT | | | 90.31 343 | 89.81 339 | 91.82 393 | 95.52 316 | 84.20 400 | 94.30 407 | 96.15 344 | 90.61 255 | 87.39 383 | 94.27 361 | 75.80 361 | 96.44 435 | 87.34 336 | 86.88 379 | 94.82 399 |
|
| IterMVS | | | 90.15 351 | 89.67 345 | 91.61 400 | 95.48 318 | 83.72 406 | 94.33 405 | 96.12 345 | 89.99 274 | 87.31 386 | 94.15 369 | 75.78 363 | 96.27 439 | 86.97 345 | 86.89 378 | 94.83 394 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
| DP-MVS | | | 92.76 239 | 91.51 263 | 96.52 108 | 98.77 62 | 90.99 171 | 97.38 176 | 96.08 346 | 82.38 443 | 89.29 334 | 97.87 125 | 83.77 217 | 99.69 73 | 81.37 416 | 96.69 205 | 98.89 138 |
|
| pmmvs4 | | | 90.93 325 | 89.85 337 | 94.17 284 | 93.34 420 | 90.79 183 | 94.60 389 | 96.02 347 | 84.62 410 | 87.45 380 | 95.15 311 | 81.88 267 | 97.45 400 | 87.70 319 | 87.87 365 | 94.27 425 |
|
| ppachtmachnet_test | | | 88.35 380 | 87.29 379 | 91.53 401 | 92.45 439 | 83.57 409 | 93.75 426 | 95.97 348 | 84.28 413 | 85.32 422 | 94.18 367 | 79.00 327 | 96.93 423 | 75.71 450 | 84.99 401 | 94.10 426 |
|
| Anonymous20240521 | | | 86.42 408 | 85.44 400 | 89.34 441 | 90.33 454 | 79.79 453 | 96.73 251 | 95.92 349 | 83.71 424 | 83.25 443 | 91.36 438 | 63.92 457 | 96.01 440 | 78.39 438 | 85.36 392 | 92.22 459 |
|
| ITE_SJBPF | | | | | 92.43 371 | 95.34 330 | 85.37 381 | | 95.92 349 | 91.47 210 | 87.75 376 | 96.39 247 | 71.00 403 | 97.96 337 | 82.36 406 | 89.86 342 | 93.97 431 |
|
| test_fmvs2 | | | 89.77 362 | 89.93 334 | 89.31 442 | 93.68 404 | 76.37 471 | 97.64 134 | 95.90 351 | 89.84 279 | 91.49 271 | 96.26 254 | 58.77 468 | 97.10 415 | 94.65 152 | 91.13 325 | 94.46 416 |
|
| USDC | | | 88.94 371 | 87.83 376 | 92.27 378 | 94.66 372 | 84.96 390 | 93.86 422 | 95.90 351 | 87.34 365 | 83.40 441 | 95.56 293 | 67.43 433 | 98.19 300 | 82.64 404 | 89.67 344 | 93.66 435 |
|
| COLMAP_ROB |  | 87.81 15 | 90.40 342 | 89.28 355 | 93.79 312 | 97.95 129 | 87.13 333 | 96.92 225 | 95.89 353 | 82.83 435 | 86.88 399 | 97.18 192 | 73.77 381 | 99.29 147 | 78.44 437 | 93.62 289 | 94.95 380 |
| Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
| VDD-MVS | | | 93.82 190 | 93.08 199 | 96.02 154 | 97.88 135 | 89.96 220 | 97.72 119 | 95.85 354 | 92.43 171 | 95.86 136 | 98.44 64 | 68.42 429 | 99.39 135 | 96.31 79 | 94.85 256 | 98.71 165 |
|
| VDDNet | | | 93.05 223 | 92.07 238 | 96.02 154 | 96.84 208 | 90.39 200 | 98.08 59 | 95.85 354 | 86.22 386 | 95.79 139 | 98.46 62 | 67.59 432 | 99.19 156 | 94.92 132 | 94.85 256 | 98.47 187 |
|
| mvsmamba | | | 94.57 156 | 94.14 160 | 95.87 165 | 97.03 190 | 89.93 221 | 97.84 96 | 95.85 354 | 91.34 216 | 94.79 178 | 96.80 218 | 80.67 289 | 98.81 212 | 94.85 137 | 98.12 148 | 98.85 144 |
|
| Vis-MVSNet (Re-imp) | | | 94.15 170 | 93.88 167 | 94.95 236 | 97.61 155 | 87.92 310 | 98.10 57 | 95.80 357 | 92.22 179 | 93.02 232 | 97.45 173 | 84.53 203 | 97.91 349 | 88.24 304 | 97.97 154 | 99.02 104 |
|
| MM | | | 97.29 31 | 96.98 42 | 98.23 13 | 98.01 124 | 95.03 28 | 98.07 61 | 95.76 358 | 97.78 1 | 97.52 63 | 98.80 38 | 88.09 119 | 99.86 9 | 99.44 2 | 99.37 67 | 99.80 1 |
|
| KD-MVS_2432*1600 | | | 84.81 428 | 82.64 431 | 91.31 407 | 91.07 449 | 85.34 382 | 91.22 462 | 95.75 359 | 85.56 395 | 83.09 444 | 90.21 446 | 67.21 435 | 95.89 442 | 77.18 444 | 62.48 489 | 92.69 447 |
|
| miper_refine_blended | | | 84.81 428 | 82.64 431 | 91.31 407 | 91.07 449 | 85.34 382 | 91.22 462 | 95.75 359 | 85.56 395 | 83.09 444 | 90.21 446 | 67.21 435 | 95.89 442 | 77.18 444 | 62.48 489 | 92.69 447 |
|
| FE-MVS | | | 92.05 267 | 91.05 279 | 95.08 223 | 96.83 210 | 87.93 309 | 93.91 421 | 95.70 361 | 86.30 383 | 94.15 199 | 94.97 317 | 76.59 353 | 99.21 154 | 84.10 385 | 96.86 196 | 98.09 229 |
|
| tpm cat1 | | | 88.36 379 | 87.21 382 | 91.81 394 | 95.13 349 | 80.55 442 | 92.58 452 | 95.70 361 | 74.97 474 | 87.45 380 | 91.96 431 | 78.01 343 | 98.17 302 | 80.39 425 | 88.74 357 | 96.72 297 |
|
| our_test_3 | | | 88.78 375 | 87.98 375 | 91.20 411 | 92.45 439 | 82.53 420 | 93.61 434 | 95.69 363 | 85.77 392 | 84.88 425 | 93.71 385 | 79.99 304 | 96.78 431 | 79.47 431 | 86.24 381 | 94.28 424 |
|
| BH-w/o | | | 92.14 264 | 91.75 252 | 93.31 342 | 96.99 195 | 85.73 371 | 95.67 338 | 95.69 363 | 88.73 322 | 89.26 336 | 94.82 327 | 82.97 238 | 98.07 318 | 85.26 372 | 96.32 223 | 96.13 317 |
|
| CR-MVSNet | | | 90.82 328 | 89.77 341 | 93.95 301 | 94.45 381 | 87.19 330 | 90.23 471 | 95.68 365 | 86.89 373 | 92.40 242 | 92.36 423 | 80.91 283 | 97.05 418 | 81.09 420 | 93.95 282 | 97.60 263 |
|
| Patchmtry | | | 88.64 377 | 87.25 380 | 92.78 364 | 94.09 391 | 86.64 343 | 89.82 475 | 95.68 365 | 80.81 455 | 87.63 378 | 92.36 423 | 80.91 283 | 97.03 419 | 78.86 435 | 85.12 397 | 94.67 411 |
|
| testing91 | | | 91.90 272 | 91.02 280 | 94.53 263 | 96.54 248 | 86.55 349 | 95.86 326 | 95.64 367 | 91.77 198 | 91.89 261 | 93.47 400 | 69.94 414 | 98.86 204 | 90.23 259 | 93.86 284 | 98.18 215 |
|
| BH-RMVSNet | | | 92.72 241 | 91.97 244 | 94.97 234 | 97.16 176 | 87.99 308 | 96.15 310 | 95.60 368 | 90.62 254 | 91.87 262 | 97.15 195 | 78.41 334 | 98.57 264 | 83.16 394 | 97.60 164 | 98.36 199 |
|
| PVSNet_0 | | 82.17 19 | 85.46 423 | 83.64 424 | 90.92 415 | 95.27 337 | 79.49 459 | 90.55 469 | 95.60 368 | 83.76 423 | 83.00 446 | 89.95 448 | 71.09 402 | 97.97 333 | 82.75 402 | 60.79 491 | 95.31 360 |
|
| guyue | | | 95.17 128 | 94.96 123 | 95.82 171 | 96.97 197 | 89.65 231 | 97.56 145 | 95.58 370 | 94.82 57 | 95.72 141 | 97.42 176 | 82.90 240 | 98.84 208 | 96.71 67 | 96.93 193 | 98.96 116 |
|
| SCA | | | 91.84 274 | 91.18 276 | 93.83 309 | 95.59 312 | 84.95 391 | 94.72 386 | 95.58 370 | 90.82 241 | 92.25 250 | 93.69 387 | 75.80 361 | 98.10 309 | 86.20 354 | 95.98 226 | 98.45 189 |
|
| MonoMVSNet | | | 91.92 270 | 91.77 250 | 92.37 372 | 92.94 427 | 83.11 414 | 97.09 208 | 95.55 372 | 92.91 149 | 90.85 288 | 94.55 340 | 81.27 277 | 96.52 434 | 93.01 197 | 87.76 366 | 97.47 269 |
|
| usedtu_blend_shiyan5 | | | 87.06 398 | 84.84 412 | 93.69 318 | 88.54 473 | 88.70 276 | 95.83 328 | 95.54 373 | 78.74 465 | 85.92 413 | 86.89 475 | 73.03 388 | 97.55 386 | 87.73 314 | 71.36 472 | 94.83 394 |
|
| AllTest | | | 90.23 347 | 88.98 361 | 93.98 297 | 97.94 130 | 86.64 343 | 96.51 274 | 95.54 373 | 85.38 397 | 85.49 419 | 96.77 220 | 70.28 409 | 99.15 165 | 80.02 427 | 92.87 294 | 96.15 315 |
|
| TestCases | | | | | 93.98 297 | 97.94 130 | 86.64 343 | | 95.54 373 | 85.38 397 | 85.49 419 | 96.77 220 | 70.28 409 | 99.15 165 | 80.02 427 | 92.87 294 | 96.15 315 |
|
| mmtdpeth | | | 89.70 364 | 88.96 362 | 91.90 389 | 95.84 304 | 84.42 396 | 97.46 165 | 95.53 376 | 90.27 267 | 94.46 188 | 90.50 442 | 69.74 418 | 98.95 194 | 97.39 53 | 69.48 479 | 92.34 455 |
|
| tpmvs | | | 89.83 361 | 89.15 359 | 91.89 390 | 94.92 359 | 80.30 446 | 93.11 443 | 95.46 377 | 86.28 384 | 88.08 370 | 92.65 413 | 80.44 295 | 98.52 268 | 81.47 412 | 89.92 341 | 96.84 293 |
|
| pmmvs5 | | | 89.86 360 | 88.87 365 | 92.82 361 | 92.86 429 | 86.23 357 | 96.26 299 | 95.39 378 | 84.24 414 | 87.12 388 | 94.51 343 | 74.27 376 | 97.36 408 | 87.61 329 | 87.57 368 | 94.86 389 |
|
| PatchmatchNet |  | | 91.91 271 | 91.35 265 | 93.59 328 | 95.38 325 | 84.11 401 | 93.15 442 | 95.39 378 | 89.54 288 | 92.10 255 | 93.68 389 | 82.82 243 | 98.13 304 | 84.81 376 | 95.32 248 | 98.52 179 |
| Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
| tpmrst | | | 91.44 297 | 91.32 267 | 91.79 395 | 95.15 347 | 79.20 462 | 93.42 437 | 95.37 380 | 88.55 327 | 93.49 221 | 93.67 390 | 82.49 252 | 98.27 293 | 90.41 254 | 89.34 347 | 97.90 241 |
|
| Anonymous20231206 | | | 87.09 397 | 86.14 394 | 89.93 433 | 91.22 448 | 80.35 444 | 96.11 311 | 95.35 381 | 83.57 426 | 84.16 433 | 93.02 408 | 73.54 385 | 95.61 450 | 72.16 467 | 86.14 383 | 93.84 433 |
|
| MIMVSNet1 | | | 84.93 426 | 83.05 428 | 90.56 424 | 89.56 460 | 84.84 393 | 95.40 354 | 95.35 381 | 83.91 418 | 80.38 458 | 92.21 428 | 57.23 471 | 93.34 476 | 70.69 473 | 82.75 428 | 93.50 437 |
|
| TDRefinement | | | 86.53 404 | 84.76 414 | 91.85 391 | 82.23 491 | 84.25 398 | 96.38 287 | 95.35 381 | 84.97 406 | 84.09 436 | 94.94 319 | 65.76 448 | 98.34 287 | 84.60 380 | 74.52 459 | 92.97 443 |
|
| TR-MVS | | | 91.48 296 | 90.59 304 | 94.16 287 | 96.40 263 | 87.33 323 | 95.67 338 | 95.34 384 | 87.68 357 | 91.46 272 | 95.52 296 | 76.77 352 | 98.35 284 | 82.85 399 | 93.61 290 | 96.79 295 |
|
| EPNet_dtu | | | 91.71 277 | 91.28 270 | 92.99 354 | 93.76 401 | 83.71 407 | 96.69 257 | 95.28 385 | 93.15 135 | 87.02 393 | 95.95 269 | 83.37 225 | 97.38 407 | 79.46 432 | 96.84 197 | 97.88 243 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| FMVSNet5 | | | 87.29 392 | 85.79 396 | 91.78 396 | 94.80 366 | 87.28 325 | 95.49 350 | 95.28 385 | 84.09 416 | 83.85 440 | 91.82 432 | 62.95 460 | 94.17 467 | 78.48 436 | 85.34 393 | 93.91 432 |
|
| MDTV_nov1_ep13 | | | | 90.76 292 | | 95.22 341 | 80.33 445 | 93.03 445 | 95.28 385 | 88.14 340 | 92.84 239 | 93.83 380 | 81.34 274 | 98.08 314 | 82.86 397 | 94.34 267 | |
|
| LF4IMVS | | | 87.94 383 | 87.25 380 | 89.98 431 | 92.38 441 | 80.05 452 | 94.38 402 | 95.25 388 | 87.59 359 | 84.34 430 | 94.74 331 | 64.31 456 | 97.66 375 | 84.83 375 | 87.45 369 | 92.23 458 |
|
| TransMVSNet (Re) | | | 88.94 371 | 87.56 377 | 93.08 352 | 94.35 384 | 88.45 289 | 97.73 116 | 95.23 389 | 87.47 361 | 84.26 432 | 95.29 303 | 79.86 307 | 97.33 409 | 79.44 433 | 74.44 461 | 93.45 439 |
|
| test20.03 | | | 86.14 415 | 85.40 402 | 88.35 445 | 90.12 455 | 80.06 451 | 95.90 325 | 95.20 390 | 88.59 323 | 81.29 453 | 93.62 392 | 71.43 399 | 92.65 480 | 71.26 471 | 81.17 433 | 92.34 455 |
|
| new-patchmatchnet | | | 83.18 435 | 81.87 438 | 87.11 453 | 86.88 482 | 75.99 473 | 93.70 428 | 95.18 391 | 85.02 405 | 77.30 471 | 88.40 460 | 65.99 446 | 93.88 472 | 74.19 459 | 70.18 477 | 91.47 470 |
|
| MDA-MVSNet_test_wron | | | 85.87 420 | 84.23 421 | 90.80 421 | 92.38 441 | 82.57 419 | 93.17 440 | 95.15 392 | 82.15 444 | 67.65 484 | 92.33 426 | 78.20 336 | 95.51 454 | 77.33 441 | 79.74 437 | 94.31 423 |
|
| YYNet1 | | | 85.87 420 | 84.23 421 | 90.78 422 | 92.38 441 | 82.46 424 | 93.17 440 | 95.14 393 | 82.12 445 | 67.69 482 | 92.36 423 | 78.16 339 | 95.50 455 | 77.31 442 | 79.73 438 | 94.39 419 |
|
| Baseline_NR-MVSNet | | | 91.20 312 | 90.62 302 | 92.95 356 | 93.83 399 | 88.03 306 | 97.01 215 | 95.12 394 | 88.42 331 | 89.70 319 | 95.13 313 | 83.47 222 | 97.44 401 | 89.66 271 | 83.24 423 | 93.37 440 |
|
| thres200 | | | 92.23 260 | 91.39 264 | 94.75 249 | 97.61 155 | 89.03 264 | 96.60 269 | 95.09 395 | 92.08 189 | 93.28 227 | 94.00 376 | 78.39 335 | 99.04 190 | 81.26 419 | 94.18 273 | 96.19 311 |
|
| ADS-MVSNet | | | 89.89 357 | 88.68 367 | 93.53 332 | 95.86 299 | 84.89 392 | 90.93 466 | 95.07 396 | 83.23 432 | 91.28 281 | 91.81 433 | 79.01 325 | 97.85 352 | 79.52 429 | 91.39 321 | 97.84 248 |
|
| pmmvs-eth3d | | | 86.22 413 | 84.45 418 | 91.53 401 | 88.34 476 | 87.25 327 | 94.47 397 | 95.01 397 | 83.47 428 | 79.51 463 | 89.61 452 | 69.75 417 | 95.71 447 | 83.13 395 | 76.73 452 | 91.64 464 |
|
| Anonymous202405211 | | | 92.07 266 | 90.83 290 | 95.76 180 | 98.19 110 | 88.75 274 | 97.58 141 | 95.00 398 | 86.00 389 | 93.64 213 | 97.45 173 | 66.24 444 | 99.53 113 | 90.68 247 | 92.71 299 | 99.01 107 |
|
| MDA-MVSNet-bldmvs | | | 85.00 425 | 82.95 430 | 91.17 413 | 93.13 425 | 83.33 410 | 94.56 391 | 95.00 398 | 84.57 411 | 65.13 488 | 92.65 413 | 70.45 408 | 95.85 444 | 73.57 462 | 77.49 447 | 94.33 421 |
|
| ambc | | | | | 86.56 456 | 83.60 488 | 70.00 483 | 85.69 487 | 94.97 400 | | 80.60 457 | 88.45 459 | 37.42 490 | 96.84 428 | 82.69 403 | 75.44 457 | 92.86 445 |
|
| testgi | | | 87.97 382 | 87.21 382 | 90.24 428 | 92.86 429 | 80.76 437 | 96.67 260 | 94.97 400 | 91.74 199 | 85.52 418 | 95.83 275 | 62.66 463 | 94.47 464 | 76.25 448 | 88.36 361 | 95.48 343 |
|
| myMVS_eth3d28 | | | 91.52 293 | 90.97 282 | 93.17 348 | 96.91 200 | 83.24 412 | 95.61 344 | 94.96 402 | 92.24 178 | 91.98 258 | 93.28 405 | 69.31 419 | 98.40 276 | 88.71 299 | 95.68 237 | 97.88 243 |
|
| dp | | | 88.90 373 | 88.26 373 | 90.81 419 | 94.58 377 | 76.62 470 | 92.85 448 | 94.93 403 | 85.12 403 | 90.07 310 | 93.07 407 | 75.81 360 | 98.12 307 | 80.53 424 | 87.42 371 | 97.71 255 |
|
| test_fmvs3 | | | 83.21 434 | 83.02 429 | 83.78 460 | 86.77 483 | 68.34 486 | 96.76 249 | 94.91 404 | 86.49 379 | 84.14 435 | 89.48 453 | 36.04 491 | 91.73 482 | 91.86 218 | 80.77 435 | 91.26 472 |
|
| test_0402 | | | 86.46 407 | 84.79 413 | 91.45 403 | 95.02 353 | 85.55 373 | 96.29 298 | 94.89 405 | 80.90 452 | 82.21 449 | 93.97 378 | 68.21 430 | 97.29 411 | 62.98 482 | 88.68 358 | 91.51 467 |
|
| tfpn200view9 | | | 92.38 250 | 91.52 261 | 94.95 236 | 97.85 136 | 89.29 253 | 97.41 169 | 94.88 406 | 92.19 184 | 93.27 228 | 94.46 348 | 78.17 337 | 99.08 178 | 81.40 413 | 94.08 277 | 96.48 304 |
|
| CVMVSNet | | | 91.23 310 | 91.75 252 | 89.67 435 | 95.77 305 | 74.69 474 | 96.44 275 | 94.88 406 | 85.81 391 | 92.18 251 | 97.64 158 | 79.07 320 | 95.58 452 | 88.06 307 | 95.86 232 | 98.74 162 |
|
| thres400 | | | 92.42 248 | 91.52 261 | 95.12 222 | 97.85 136 | 89.29 253 | 97.41 169 | 94.88 406 | 92.19 184 | 93.27 228 | 94.46 348 | 78.17 337 | 99.08 178 | 81.40 413 | 94.08 277 | 96.98 286 |
|
| tt0320 | | | 85.39 424 | 83.12 427 | 92.19 382 | 93.44 417 | 85.79 369 | 96.19 307 | 94.87 409 | 71.19 482 | 82.92 447 | 91.76 435 | 58.43 469 | 96.81 429 | 81.03 421 | 78.26 446 | 93.98 430 |
|
| EPNet | | | 95.20 124 | 94.56 143 | 97.14 76 | 92.80 431 | 92.68 98 | 97.85 95 | 94.87 409 | 96.64 9 | 92.46 241 | 97.80 139 | 86.23 161 | 99.65 79 | 93.72 176 | 98.62 124 | 99.10 96 |
| Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
| testing99 | | | 91.62 284 | 90.72 297 | 94.32 276 | 96.48 257 | 86.11 366 | 95.81 330 | 94.76 411 | 91.55 203 | 91.75 266 | 93.44 401 | 68.55 427 | 98.82 210 | 90.43 253 | 93.69 286 | 98.04 233 |
|
| sc_t1 | | | 86.48 406 | 84.10 423 | 93.63 325 | 93.45 416 | 85.76 370 | 96.79 243 | 94.71 412 | 73.06 479 | 86.45 403 | 94.35 353 | 55.13 476 | 97.95 341 | 84.38 383 | 78.55 445 | 97.18 282 |
|
| SixPastTwentyTwo | | | 89.15 369 | 88.54 369 | 90.98 414 | 93.49 413 | 80.28 448 | 96.70 255 | 94.70 413 | 90.78 242 | 84.15 434 | 95.57 292 | 71.78 397 | 97.71 369 | 84.63 379 | 85.07 398 | 94.94 382 |
|
| thres100view900 | | | 92.43 247 | 91.58 258 | 94.98 232 | 97.92 132 | 89.37 249 | 97.71 121 | 94.66 414 | 92.20 182 | 93.31 226 | 94.90 322 | 78.06 341 | 99.08 178 | 81.40 413 | 94.08 277 | 96.48 304 |
|
| thres600view7 | | | 92.49 245 | 91.60 257 | 95.18 218 | 97.91 133 | 89.47 243 | 97.65 130 | 94.66 414 | 92.18 186 | 93.33 225 | 94.91 321 | 78.06 341 | 99.10 173 | 81.61 409 | 94.06 281 | 96.98 286 |
|
| PatchT | | | 88.87 374 | 87.42 378 | 93.22 346 | 94.08 392 | 85.10 386 | 89.51 476 | 94.64 416 | 81.92 446 | 92.36 245 | 88.15 463 | 80.05 303 | 97.01 421 | 72.43 466 | 93.65 288 | 97.54 266 |
|
| baseline1 | | | 92.82 237 | 91.90 247 | 95.55 196 | 97.20 174 | 90.77 185 | 97.19 200 | 94.58 417 | 92.20 182 | 92.36 245 | 96.34 249 | 84.16 212 | 98.21 297 | 89.20 286 | 83.90 418 | 97.68 257 |
|
| AstraMVS | | | 94.82 149 | 94.64 139 | 95.34 213 | 96.36 268 | 88.09 305 | 97.58 141 | 94.56 418 | 94.98 46 | 95.70 144 | 97.92 115 | 81.93 266 | 98.93 197 | 96.87 61 | 95.88 230 | 98.99 112 |
|
| UBG | | | 91.55 290 | 90.76 292 | 93.94 303 | 96.52 253 | 85.06 387 | 95.22 367 | 94.54 419 | 90.47 263 | 91.98 258 | 92.71 412 | 72.02 394 | 98.74 234 | 88.10 306 | 95.26 250 | 98.01 235 |
|
| Gipuma |  | | 67.86 456 | 65.41 458 | 75.18 473 | 92.66 434 | 73.45 478 | 66.50 494 | 94.52 420 | 53.33 493 | 57.80 494 | 66.07 494 | 30.81 493 | 89.20 486 | 48.15 491 | 78.88 444 | 62.90 494 |
| S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
| testing11 | | | 91.68 280 | 90.75 294 | 94.47 266 | 96.53 250 | 86.56 348 | 95.76 334 | 94.51 421 | 91.10 234 | 91.24 283 | 93.59 395 | 68.59 426 | 98.86 204 | 91.10 235 | 94.29 269 | 98.00 236 |
|
| CostFormer | | | 91.18 315 | 90.70 298 | 92.62 369 | 94.84 364 | 81.76 430 | 94.09 414 | 94.43 422 | 84.15 415 | 92.72 240 | 93.77 384 | 79.43 314 | 98.20 298 | 90.70 246 | 92.18 308 | 97.90 241 |
|
| tpm2 | | | 89.96 354 | 89.21 357 | 92.23 381 | 94.91 361 | 81.25 433 | 93.78 425 | 94.42 423 | 80.62 457 | 91.56 269 | 93.44 401 | 76.44 356 | 97.94 343 | 85.60 366 | 92.08 312 | 97.49 267 |
|
| testing3-2 | | | 92.10 265 | 92.05 239 | 92.27 378 | 97.71 145 | 79.56 456 | 97.42 167 | 94.41 424 | 93.53 114 | 93.22 230 | 95.49 297 | 69.16 421 | 99.11 171 | 93.25 187 | 94.22 271 | 98.13 220 |
|
| MGCNet | | | 96.74 64 | 96.31 81 | 98.02 21 | 96.87 204 | 94.65 32 | 97.58 141 | 94.39 425 | 96.47 12 | 97.16 75 | 98.39 68 | 87.53 136 | 99.87 7 | 98.97 20 | 99.41 59 | 99.55 43 |
|
| JIA-IIPM | | | 88.26 381 | 87.04 385 | 91.91 388 | 93.52 411 | 81.42 432 | 89.38 477 | 94.38 426 | 80.84 454 | 90.93 287 | 80.74 486 | 79.22 317 | 97.92 346 | 82.76 401 | 91.62 316 | 96.38 307 |
|
| dmvs_re | | | 90.21 348 | 89.50 350 | 92.35 373 | 95.47 322 | 85.15 384 | 95.70 337 | 94.37 427 | 90.94 240 | 88.42 357 | 93.57 396 | 74.63 373 | 95.67 449 | 82.80 400 | 89.57 345 | 96.22 309 |
|
| Patchmatch-test | | | 89.42 367 | 87.99 374 | 93.70 317 | 95.27 337 | 85.11 385 | 88.98 478 | 94.37 427 | 81.11 451 | 87.10 391 | 93.69 387 | 82.28 256 | 97.50 396 | 74.37 457 | 94.76 260 | 98.48 186 |
|
| LCM-MVSNet | | | 72.55 449 | 69.39 453 | 82.03 462 | 70.81 502 | 65.42 491 | 90.12 473 | 94.36 429 | 55.02 492 | 65.88 486 | 81.72 484 | 24.16 499 | 89.96 483 | 74.32 458 | 68.10 483 | 90.71 475 |
|
| ADS-MVSNet2 | | | 89.45 366 | 88.59 368 | 92.03 385 | 95.86 299 | 82.26 426 | 90.93 466 | 94.32 430 | 83.23 432 | 91.28 281 | 91.81 433 | 79.01 325 | 95.99 441 | 79.52 429 | 91.39 321 | 97.84 248 |
|
| mvs5depth | | | 86.53 404 | 85.08 408 | 90.87 416 | 88.74 470 | 82.52 421 | 91.91 457 | 94.23 431 | 86.35 382 | 87.11 390 | 93.70 386 | 66.52 440 | 97.76 364 | 81.37 416 | 75.80 454 | 92.31 457 |
|
| EU-MVSNet | | | 88.72 376 | 88.90 364 | 88.20 447 | 93.15 424 | 74.21 476 | 96.63 266 | 94.22 432 | 85.18 401 | 87.32 385 | 95.97 267 | 76.16 358 | 94.98 459 | 85.27 371 | 86.17 382 | 95.41 350 |
|
| usedtu_dtu_shiyan2 | | | 80.00 442 | 76.91 448 | 89.27 443 | 82.13 492 | 79.69 455 | 95.45 352 | 94.20 433 | 72.95 480 | 75.80 472 | 87.75 466 | 44.44 486 | 94.30 466 | 70.64 474 | 68.81 482 | 93.84 433 |
|
| tt0320-xc | | | 84.83 427 | 82.33 435 | 92.31 376 | 93.66 405 | 86.20 359 | 96.17 309 | 94.06 434 | 71.26 481 | 82.04 451 | 92.22 427 | 55.07 477 | 96.72 432 | 81.49 411 | 75.04 458 | 94.02 429 |
|
| MIMVSNet | | | 88.50 378 | 86.76 388 | 93.72 316 | 94.84 364 | 87.77 316 | 91.39 460 | 94.05 435 | 86.41 381 | 87.99 372 | 92.59 416 | 63.27 458 | 95.82 446 | 77.44 440 | 92.84 296 | 97.57 265 |
|
| OpenMVS_ROB |  | 81.14 20 | 84.42 430 | 82.28 436 | 90.83 417 | 90.06 456 | 84.05 403 | 95.73 336 | 94.04 436 | 73.89 477 | 80.17 461 | 91.53 437 | 59.15 467 | 97.64 376 | 66.92 480 | 89.05 351 | 90.80 474 |
|
| TinyColmap | | | 86.82 402 | 85.35 403 | 91.21 409 | 94.91 361 | 82.99 416 | 93.94 418 | 94.02 437 | 83.58 425 | 81.56 452 | 94.68 333 | 62.34 464 | 98.13 304 | 75.78 449 | 87.35 374 | 92.52 453 |
|
| ETVMVS | | | 90.52 339 | 89.14 360 | 94.67 252 | 96.81 214 | 87.85 314 | 95.91 324 | 93.97 438 | 89.71 282 | 92.34 248 | 92.48 418 | 65.41 450 | 97.96 337 | 81.37 416 | 94.27 270 | 98.21 213 |
|
| IB-MVS | | 87.33 17 | 89.91 355 | 88.28 372 | 94.79 246 | 95.26 340 | 87.70 317 | 95.12 376 | 93.95 439 | 89.35 296 | 87.03 392 | 92.49 417 | 70.74 406 | 99.19 156 | 89.18 287 | 81.37 432 | 97.49 267 |
| 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 |
| Syy-MVS | | | 87.13 396 | 87.02 386 | 87.47 451 | 95.16 344 | 73.21 479 | 95.00 378 | 93.93 440 | 88.55 327 | 86.96 394 | 91.99 429 | 75.90 359 | 94.00 469 | 61.59 484 | 94.11 274 | 95.20 368 |
|
| myMVS_eth3d | | | 87.18 395 | 86.38 391 | 89.58 436 | 95.16 344 | 79.53 457 | 95.00 378 | 93.93 440 | 88.55 327 | 86.96 394 | 91.99 429 | 56.23 474 | 94.00 469 | 75.47 453 | 94.11 274 | 95.20 368 |
|
| testing222 | | | 90.31 343 | 88.96 362 | 94.35 272 | 96.54 248 | 87.29 324 | 95.50 349 | 93.84 442 | 90.97 237 | 91.75 266 | 92.96 409 | 62.18 465 | 98.00 328 | 82.86 397 | 94.08 277 | 97.76 253 |
|
| test_f | | | 80.57 441 | 79.62 443 | 83.41 461 | 83.38 489 | 67.80 488 | 93.57 435 | 93.72 443 | 80.80 456 | 77.91 470 | 87.63 469 | 33.40 492 | 92.08 481 | 87.14 343 | 79.04 443 | 90.34 476 |
|
| LCM-MVSNet-Re | | | 92.50 243 | 92.52 227 | 92.44 370 | 96.82 212 | 81.89 429 | 96.92 225 | 93.71 444 | 92.41 172 | 84.30 431 | 94.60 338 | 85.08 192 | 97.03 419 | 91.51 226 | 97.36 174 | 98.40 195 |
|
| tpm | | | 90.25 346 | 89.74 344 | 91.76 398 | 93.92 395 | 79.73 454 | 93.98 415 | 93.54 445 | 88.28 334 | 91.99 257 | 93.25 406 | 77.51 347 | 97.44 401 | 87.30 338 | 87.94 364 | 98.12 222 |
|
| ET-MVSNet_ETH3D | | | 91.49 295 | 90.11 324 | 95.63 190 | 96.40 263 | 91.57 143 | 95.34 357 | 93.48 446 | 90.60 257 | 75.58 474 | 95.49 297 | 80.08 302 | 96.79 430 | 94.25 164 | 89.76 343 | 98.52 179 |
|
| LFMVS | | | 93.60 197 | 92.63 220 | 96.52 108 | 98.13 116 | 91.27 156 | 97.94 82 | 93.39 447 | 90.57 259 | 96.29 118 | 98.31 81 | 69.00 422 | 99.16 163 | 94.18 165 | 95.87 231 | 99.12 93 |
|
| MVStest1 | | | 82.38 438 | 80.04 442 | 89.37 439 | 87.63 480 | 82.83 417 | 95.03 377 | 93.37 448 | 73.90 476 | 73.50 479 | 94.35 353 | 62.89 461 | 93.25 478 | 73.80 460 | 65.92 486 | 92.04 463 |
|
| FE-MVSNET | | | 83.85 431 | 81.97 437 | 89.51 437 | 87.19 481 | 83.19 413 | 95.21 369 | 93.17 449 | 83.45 429 | 78.90 466 | 89.05 456 | 65.46 449 | 93.84 473 | 69.71 476 | 75.56 456 | 91.51 467 |
|
| Patchmatch-RL test | | | 87.38 390 | 86.24 392 | 90.81 419 | 88.74 470 | 78.40 466 | 88.12 485 | 93.17 449 | 87.11 370 | 82.17 450 | 89.29 454 | 81.95 264 | 95.60 451 | 88.64 301 | 77.02 449 | 98.41 194 |
|
| ttmdpeth | | | 85.91 419 | 84.76 414 | 89.36 440 | 89.14 462 | 80.25 449 | 95.66 341 | 93.16 451 | 83.77 422 | 83.39 442 | 95.26 307 | 66.24 444 | 95.26 458 | 80.65 422 | 75.57 455 | 92.57 450 |
|
| test-LLR | | | 91.42 298 | 91.19 275 | 92.12 383 | 94.59 375 | 80.66 439 | 94.29 408 | 92.98 452 | 91.11 232 | 90.76 290 | 92.37 420 | 79.02 323 | 98.07 318 | 88.81 296 | 96.74 202 | 97.63 258 |
|
| test-mter | | | 90.19 350 | 89.54 349 | 92.12 383 | 94.59 375 | 80.66 439 | 94.29 408 | 92.98 452 | 87.68 357 | 90.76 290 | 92.37 420 | 67.67 431 | 98.07 318 | 88.81 296 | 96.74 202 | 97.63 258 |
|
| WB-MVSnew | | | 89.88 358 | 89.56 348 | 90.82 418 | 94.57 378 | 83.06 415 | 95.65 342 | 92.85 454 | 87.86 348 | 90.83 289 | 94.10 370 | 79.66 311 | 96.88 426 | 76.34 447 | 94.19 272 | 92.54 452 |
|
| testing3 | | | 87.67 386 | 86.88 387 | 90.05 430 | 96.14 286 | 80.71 438 | 97.10 207 | 92.85 454 | 90.15 271 | 87.54 379 | 94.55 340 | 55.70 475 | 94.10 468 | 73.77 461 | 94.10 276 | 95.35 357 |
|
| test_method | | | 66.11 457 | 64.89 459 | 69.79 476 | 72.62 500 | 35.23 508 | 65.19 495 | 92.83 456 | 20.35 498 | 65.20 487 | 88.08 464 | 43.14 488 | 82.70 493 | 73.12 464 | 63.46 488 | 91.45 471 |
|
| test0.0.03 1 | | | 89.37 368 | 88.70 366 | 91.41 405 | 92.47 438 | 85.63 372 | 95.22 367 | 92.70 457 | 91.11 232 | 86.91 398 | 93.65 391 | 79.02 323 | 93.19 479 | 78.00 439 | 89.18 348 | 95.41 350 |
|
| new_pmnet | | | 82.89 436 | 81.12 441 | 88.18 448 | 89.63 459 | 80.18 450 | 91.77 458 | 92.57 458 | 76.79 472 | 75.56 475 | 88.23 462 | 61.22 466 | 94.48 463 | 71.43 469 | 82.92 426 | 89.87 477 |
|
| mvsany_test1 | | | 93.93 186 | 93.98 165 | 93.78 313 | 94.94 358 | 86.80 339 | 94.62 388 | 92.55 459 | 88.77 321 | 96.85 85 | 98.49 58 | 88.98 101 | 98.08 314 | 95.03 127 | 95.62 239 | 96.46 306 |
|
| 0.4-1-1-0.2 | | | 86.27 412 | 83.62 425 | 94.20 282 | 90.38 453 | 87.69 318 | 91.04 465 | 92.52 460 | 83.43 430 | 85.22 423 | 81.49 485 | 65.31 451 | 98.29 291 | 88.90 295 | 74.30 462 | 96.64 299 |
|
| 0.3-1-1-0.015 | | | 86.11 416 | 83.37 426 | 94.34 274 | 90.58 452 | 88.02 307 | 91.64 459 | 92.45 461 | 83.56 427 | 84.46 428 | 81.84 483 | 62.73 462 | 98.31 288 | 88.98 292 | 74.09 463 | 96.70 298 |
|
| thisisatest0515 | | | 92.29 256 | 91.30 269 | 95.25 216 | 96.60 236 | 88.90 271 | 94.36 403 | 92.32 462 | 87.92 344 | 93.43 223 | 94.57 339 | 77.28 348 | 99.00 191 | 89.42 277 | 95.86 232 | 97.86 247 |
|
| 0.4-1-1-0.1 | | | 86.83 401 | 84.27 420 | 94.50 264 | 91.39 446 | 88.23 296 | 92.62 451 | 92.27 463 | 84.04 417 | 86.01 412 | 83.30 482 | 65.29 452 | 98.31 288 | 89.08 289 | 74.45 460 | 96.96 290 |
|
| thisisatest0530 | | | 93.03 224 | 92.21 236 | 95.49 205 | 97.07 182 | 89.11 262 | 97.49 162 | 92.19 464 | 90.16 270 | 94.09 200 | 96.41 245 | 76.43 357 | 99.05 187 | 90.38 255 | 95.68 237 | 98.31 207 |
|
| tttt0517 | | | 92.96 227 | 92.33 233 | 94.87 239 | 97.11 180 | 87.16 332 | 97.97 78 | 92.09 465 | 90.63 253 | 93.88 207 | 97.01 209 | 76.50 354 | 99.06 184 | 90.29 258 | 95.45 246 | 98.38 197 |
|
| K. test v3 | | | 87.64 387 | 86.75 389 | 90.32 427 | 93.02 426 | 79.48 460 | 96.61 267 | 92.08 466 | 90.66 251 | 80.25 460 | 94.09 372 | 67.21 435 | 96.65 433 | 85.96 362 | 80.83 434 | 94.83 394 |
|
| TESTMET0.1,1 | | | 90.06 352 | 89.42 352 | 91.97 386 | 94.41 383 | 80.62 441 | 94.29 408 | 91.97 467 | 87.28 367 | 90.44 294 | 92.47 419 | 68.79 423 | 97.67 371 | 88.50 303 | 96.60 209 | 97.61 262 |
|
| PM-MVS | | | 83.48 433 | 81.86 439 | 88.31 446 | 87.83 478 | 77.59 468 | 93.43 436 | 91.75 468 | 86.91 372 | 80.63 456 | 89.91 449 | 44.42 487 | 95.84 445 | 85.17 374 | 76.73 452 | 91.50 469 |
|
| baseline2 | | | 91.63 283 | 90.86 286 | 93.94 303 | 94.33 385 | 86.32 354 | 95.92 323 | 91.64 469 | 89.37 295 | 86.94 396 | 94.69 332 | 81.62 271 | 98.69 244 | 88.64 301 | 94.57 265 | 96.81 294 |
|
| APD_test1 | | | 79.31 444 | 77.70 446 | 84.14 459 | 89.11 464 | 69.07 485 | 92.36 456 | 91.50 470 | 69.07 484 | 73.87 477 | 92.63 415 | 39.93 489 | 94.32 465 | 70.54 475 | 80.25 436 | 89.02 479 |
|
| FPMVS | | | 71.27 450 | 69.85 452 | 75.50 472 | 74.64 497 | 59.03 497 | 91.30 461 | 91.50 470 | 58.80 489 | 57.92 493 | 88.28 461 | 29.98 495 | 85.53 492 | 53.43 489 | 82.84 427 | 81.95 485 |
|
| door | | | | | | | | | 91.13 472 | | | | | | | | |
|
| door-mid | | | | | | | | | 91.06 473 | | | | | | | | |
|
| EGC-MVSNET | | | 68.77 455 | 63.01 461 | 86.07 458 | 92.49 437 | 82.24 427 | 93.96 417 | 90.96 474 | 0.71 503 | 2.62 504 | 90.89 440 | 53.66 478 | 93.46 474 | 57.25 487 | 84.55 408 | 82.51 484 |
|
| mvsany_test3 | | | 83.59 432 | 82.44 434 | 87.03 454 | 83.80 486 | 73.82 477 | 93.70 428 | 90.92 475 | 86.42 380 | 82.51 448 | 90.26 445 | 46.76 485 | 95.71 447 | 90.82 241 | 76.76 451 | 91.57 466 |
|
| pmmvs3 | | | 79.97 443 | 77.50 447 | 87.39 452 | 82.80 490 | 79.38 461 | 92.70 450 | 90.75 476 | 70.69 483 | 78.66 467 | 87.47 471 | 51.34 481 | 93.40 475 | 73.39 463 | 69.65 478 | 89.38 478 |
|
| UWE-MVS | | | 89.91 355 | 89.48 351 | 91.21 409 | 95.88 298 | 78.23 467 | 94.91 381 | 90.26 477 | 89.11 302 | 92.35 247 | 94.52 342 | 68.76 424 | 97.96 337 | 83.95 389 | 95.59 240 | 97.42 271 |
|
| DSMNet-mixed | | | 86.34 410 | 86.12 395 | 87.00 455 | 89.88 458 | 70.43 481 | 94.93 380 | 90.08 478 | 77.97 469 | 85.42 421 | 92.78 411 | 74.44 375 | 93.96 471 | 74.43 456 | 95.14 251 | 96.62 300 |
|
| MVS-HIRNet | | | 82.47 437 | 81.21 440 | 86.26 457 | 95.38 325 | 69.21 484 | 88.96 479 | 89.49 479 | 66.28 486 | 80.79 455 | 74.08 491 | 68.48 428 | 97.39 406 | 71.93 468 | 95.47 245 | 92.18 460 |
|
| WB-MVS | | | 76.77 446 | 76.63 449 | 77.18 467 | 85.32 484 | 56.82 499 | 94.53 392 | 89.39 480 | 82.66 442 | 71.35 480 | 89.18 455 | 75.03 368 | 88.88 487 | 35.42 495 | 66.79 484 | 85.84 481 |
|
| test1111 | | | 93.19 216 | 92.82 210 | 94.30 279 | 97.58 161 | 84.56 395 | 98.21 48 | 89.02 481 | 93.53 114 | 94.58 183 | 98.21 88 | 72.69 390 | 99.05 187 | 93.06 193 | 98.48 131 | 99.28 77 |
|
| SSC-MVS | | | 76.05 447 | 75.83 450 | 76.72 471 | 84.77 485 | 56.22 500 | 94.32 406 | 88.96 482 | 81.82 448 | 70.52 481 | 88.91 457 | 74.79 372 | 88.71 488 | 33.69 496 | 64.71 487 | 85.23 482 |
|
| ECVR-MVS |  | | 93.19 216 | 92.73 216 | 94.57 260 | 97.66 149 | 85.41 378 | 98.21 48 | 88.23 483 | 93.43 121 | 94.70 180 | 98.21 88 | 72.57 391 | 99.07 182 | 93.05 194 | 98.49 129 | 99.25 80 |
|
| EPMVS | | | 90.70 333 | 89.81 339 | 93.37 340 | 94.73 370 | 84.21 399 | 93.67 431 | 88.02 484 | 89.50 290 | 92.38 244 | 93.49 398 | 77.82 345 | 97.78 361 | 86.03 360 | 92.68 300 | 98.11 228 |
|
| ANet_high | | | 63.94 459 | 59.58 462 | 77.02 468 | 61.24 504 | 66.06 489 | 85.66 488 | 87.93 485 | 78.53 467 | 42.94 496 | 71.04 493 | 25.42 498 | 80.71 495 | 52.60 490 | 30.83 497 | 84.28 483 |
|
| PMMVS2 | | | 70.19 451 | 66.92 455 | 80.01 463 | 76.35 496 | 65.67 490 | 86.22 486 | 87.58 486 | 64.83 488 | 62.38 489 | 80.29 488 | 26.78 497 | 88.49 490 | 63.79 481 | 54.07 493 | 85.88 480 |
|
| lessismore_v0 | | | | | 90.45 425 | 91.96 444 | 79.09 464 | | 87.19 487 | | 80.32 459 | 94.39 350 | 66.31 443 | 97.55 386 | 84.00 388 | 76.84 450 | 94.70 410 |
|
| PMVS |  | 53.92 22 | 58.58 460 | 55.40 463 | 68.12 477 | 51.00 505 | 48.64 502 | 78.86 491 | 87.10 488 | 46.77 494 | 35.84 500 | 74.28 490 | 8.76 503 | 86.34 491 | 42.07 493 | 73.91 464 | 69.38 491 |
| Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
| UWE-MVS-28 | | | 86.81 403 | 86.41 390 | 88.02 449 | 92.87 428 | 74.60 475 | 95.38 356 | 86.70 489 | 88.17 337 | 87.28 387 | 94.67 335 | 70.83 405 | 93.30 477 | 67.45 478 | 94.31 268 | 96.17 312 |
|
| test_vis1_rt | | | 86.16 414 | 85.06 409 | 89.46 438 | 93.47 415 | 80.46 443 | 96.41 281 | 86.61 490 | 85.22 400 | 79.15 465 | 88.64 458 | 52.41 480 | 97.06 417 | 93.08 192 | 90.57 334 | 90.87 473 |
|
| testf1 | | | 69.31 453 | 66.76 456 | 76.94 469 | 78.61 494 | 61.93 493 | 88.27 483 | 86.11 491 | 55.62 490 | 59.69 490 | 85.31 479 | 20.19 501 | 89.32 484 | 57.62 485 | 69.44 480 | 79.58 486 |
|
| APD_test2 | | | 69.31 453 | 66.76 456 | 76.94 469 | 78.61 494 | 61.93 493 | 88.27 483 | 86.11 491 | 55.62 490 | 59.69 490 | 85.31 479 | 20.19 501 | 89.32 484 | 57.62 485 | 69.44 480 | 79.58 486 |
|
| gg-mvs-nofinetune | | | 87.82 384 | 85.61 397 | 94.44 268 | 94.46 380 | 89.27 256 | 91.21 464 | 84.61 493 | 80.88 453 | 89.89 314 | 74.98 489 | 71.50 398 | 97.53 393 | 85.75 365 | 97.21 183 | 96.51 302 |
|
| dmvs_testset | | | 81.38 440 | 82.60 433 | 77.73 466 | 91.74 445 | 51.49 501 | 93.03 445 | 84.21 494 | 89.07 303 | 78.28 469 | 91.25 439 | 76.97 350 | 88.53 489 | 56.57 488 | 82.24 429 | 93.16 441 |
|
| GG-mvs-BLEND | | | | | 93.62 326 | 93.69 403 | 89.20 258 | 92.39 455 | 83.33 495 | | 87.98 373 | 89.84 450 | 71.00 403 | 96.87 427 | 82.08 408 | 95.40 247 | 94.80 402 |
|
| MTMP | | | | | | | | 97.86 92 | 82.03 496 | | | | | | | | |
|
| DeepMVS_CX |  | | | | 74.68 474 | 90.84 451 | 64.34 492 | | 81.61 497 | 65.34 487 | 67.47 485 | 88.01 465 | 48.60 484 | 80.13 496 | 62.33 483 | 73.68 465 | 79.58 486 |
|
| E-PMN | | | 53.28 461 | 52.56 465 | 55.43 480 | 74.43 498 | 47.13 503 | 83.63 490 | 76.30 498 | 42.23 495 | 42.59 497 | 62.22 496 | 28.57 496 | 74.40 497 | 31.53 497 | 31.51 496 | 44.78 495 |
|
| test2506 | | | 91.60 285 | 90.78 291 | 94.04 293 | 97.66 149 | 83.81 404 | 98.27 37 | 75.53 499 | 93.43 121 | 95.23 161 | 98.21 88 | 67.21 435 | 99.07 182 | 93.01 197 | 98.49 129 | 99.25 80 |
|
| EMVS | | | 52.08 463 | 51.31 466 | 54.39 481 | 72.62 500 | 45.39 505 | 83.84 489 | 75.51 500 | 41.13 496 | 40.77 498 | 59.65 497 | 30.08 494 | 73.60 498 | 28.31 499 | 29.90 498 | 44.18 496 |
|
| test_vis3_rt | | | 72.73 448 | 70.55 451 | 79.27 464 | 80.02 493 | 68.13 487 | 93.92 420 | 74.30 501 | 76.90 471 | 58.99 492 | 73.58 492 | 20.29 500 | 95.37 456 | 84.16 384 | 72.80 467 | 74.31 489 |
|
| MVE |  | 50.73 23 | 53.25 462 | 48.81 467 | 66.58 479 | 65.34 503 | 57.50 498 | 72.49 493 | 70.94 502 | 40.15 497 | 39.28 499 | 63.51 495 | 6.89 505 | 73.48 499 | 38.29 494 | 42.38 495 | 68.76 493 |
| Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
| tmp_tt | | | 51.94 464 | 53.82 464 | 46.29 482 | 33.73 506 | 45.30 506 | 78.32 492 | 67.24 503 | 18.02 499 | 50.93 495 | 87.05 474 | 52.99 479 | 53.11 501 | 70.76 472 | 25.29 499 | 40.46 497 |
|
| kuosan | | | 65.27 458 | 64.66 460 | 67.11 478 | 83.80 486 | 61.32 496 | 88.53 482 | 60.77 504 | 68.22 485 | 67.67 483 | 80.52 487 | 49.12 483 | 70.76 500 | 29.67 498 | 53.64 494 | 69.26 492 |
|
| dongtai | | | 69.99 452 | 69.33 454 | 71.98 475 | 88.78 467 | 61.64 495 | 89.86 474 | 59.93 505 | 75.67 473 | 74.96 476 | 85.45 478 | 50.19 482 | 81.66 494 | 43.86 492 | 55.27 492 | 72.63 490 |
|
| N_pmnet | | | 78.73 445 | 78.71 445 | 78.79 465 | 92.80 431 | 46.50 504 | 94.14 412 | 43.71 506 | 78.61 466 | 80.83 454 | 91.66 436 | 74.94 371 | 96.36 437 | 67.24 479 | 84.45 410 | 93.50 437 |
|
| wuyk23d | | | 25.11 465 | 24.57 469 | 26.74 483 | 73.98 499 | 39.89 507 | 57.88 496 | 9.80 507 | 12.27 500 | 10.39 501 | 6.97 503 | 7.03 504 | 36.44 502 | 25.43 500 | 17.39 500 | 3.89 500 |
|
| testmvs | | | 13.36 467 | 16.33 470 | 4.48 485 | 5.04 507 | 2.26 510 | 93.18 439 | 3.28 508 | 2.70 501 | 8.24 502 | 21.66 499 | 2.29 507 | 2.19 503 | 7.58 501 | 2.96 501 | 9.00 499 |
|
| test123 | | | 13.04 468 | 15.66 471 | 5.18 484 | 4.51 508 | 3.45 509 | 92.50 454 | 1.81 509 | 2.50 502 | 7.58 503 | 20.15 500 | 3.67 506 | 2.18 504 | 7.13 502 | 1.07 502 | 9.90 498 |
|
| 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 |
|
| pcd_1.5k_mvsjas | | | 7.39 470 | 9.85 473 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 0.00 504 | 88.65 109 | 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 |
|
| n2 | | | | | | | | | 0.00 510 | | | | | | | | |
|
| nn | | | | | | | | | 0.00 510 | | | | | | | | |
|
| ab-mvs-re | | | 8.06 469 | 10.74 472 | 0.00 486 | 0.00 509 | 0.00 511 | 0.00 497 | 0.00 510 | 0.00 504 | 0.00 505 | 96.69 226 | 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 |
|
| WAC-MVS | | | | | | | 79.53 457 | | | | | | | | 75.56 452 | | |
|
| PC_three_1452 | | | | | | | | | | 90.77 243 | 98.89 26 | 98.28 86 | 96.24 1 | 98.35 284 | 95.76 106 | 99.58 23 | 99.59 32 |
|
| eth-test2 | | | | | | 0.00 509 | | | | | | | | | | | |
|
| eth-test | | | | | | 0.00 509 | | | | | | | | | | | |
|
| OPU-MVS | | | | | 98.55 4 | 98.82 61 | 96.86 3 | 98.25 40 | | | | 98.26 87 | 96.04 2 | 99.24 151 | 95.36 120 | 99.59 19 | 99.56 40 |
|
| test_0728_THIRD | | | | | | | | | | 94.78 61 | 98.73 30 | 98.87 31 | 95.87 4 | 99.84 26 | 97.45 45 | 99.72 2 | 99.77 3 |
|
| GSMVS | | | | | | | | | | | | | | | | | 98.45 189 |
|
| test_part2 | | | | | | 99.28 30 | 95.74 10 | | | | 98.10 49 | | | | | | |
|
| sam_mvs1 | | | | | | | | | | | | | 82.76 244 | | | | 98.45 189 |
|
| sam_mvs | | | | | | | | | | | | | 81.94 265 | | | | |
|
| test_post1 | | | | | | | | 92.81 449 | | | | 16.58 502 | 80.53 293 | 97.68 370 | 86.20 354 | | |
|
| test_post | | | | | | | | | | | | 17.58 501 | 81.76 268 | 98.08 314 | | | |
|
| patchmatchnet-post | | | | | | | | | | | | 90.45 444 | 82.65 249 | 98.10 309 | | | |
|
| gm-plane-assit | | | | | | 93.22 422 | 78.89 465 | | | 84.82 408 | | 93.52 397 | | 98.64 254 | 87.72 316 | | |
|
| test9_res | | | | | | | | | | | | | | | 94.81 143 | 99.38 64 | 99.45 59 |
|
| agg_prior2 | | | | | | | | | | | | | | | 93.94 170 | 99.38 64 | 99.50 52 |
|
| test_prior4 | | | | | | | 93.66 63 | 96.42 280 | | | | | | | | | |
|
| test_prior2 | | | | | | | | 96.35 290 | | 92.80 157 | 96.03 128 | 97.59 165 | 92.01 50 | | 95.01 128 | 99.38 64 | |
|
| 旧先验2 | | | | | | | | 95.94 321 | | 81.66 449 | 97.34 71 | | | 98.82 210 | 92.26 203 | | |
|
| 新几何2 | | | | | | | | 95.79 332 | | | | | | | | | |
|
| 原ACMM2 | | | | | | | | 95.67 338 | | | | | | | | | |
|
| testdata2 | | | | | | | | | | | | | | 99.67 77 | 85.96 362 | | |
|
| segment_acmp | | | | | | | | | | | | | 92.89 33 | | | | |
|
| testdata1 | | | | | | | | 95.26 365 | | 93.10 138 | | | | | | | |
|
| plane_prior7 | | | | | | 96.21 273 | 89.98 217 | | | | | | | | | | |
|
| plane_prior6 | | | | | | 96.10 291 | 90.00 213 | | | | | | 81.32 275 | | | | |
|
| plane_prior4 | | | | | | | | | | | | 96.64 229 | | | | | |
|
| plane_prior3 | | | | | | | 90.00 213 | | | 94.46 78 | 91.34 275 | | | | | | |
|
| plane_prior2 | | | | | | | | 97.74 114 | | 94.85 53 | | | | | | | |
|
| plane_prior1 | | | | | | 96.14 286 | | | | | | | | | | | |
|
| plane_prior | | | | | | | 89.99 215 | 97.24 192 | | 94.06 93 | | | | | | 92.16 309 | |
|
| HQP5-MVS | | | | | | | 89.33 251 | | | | | | | | | | |
|
| HQP-NCC | | | | | | 95.86 299 | | 96.65 261 | | 93.55 110 | 90.14 299 | | | | | | |
|
| ACMP_Plane | | | | | | 95.86 299 | | 96.65 261 | | 93.55 110 | 90.14 299 | | | | | | |
|
| BP-MVS | | | | | | | | | | | | | | | 92.13 211 | | |
|
| HQP4-MVS | | | | | | | | | | | 90.14 299 | | | 98.50 269 | | | 95.78 331 |
|
| HQP2-MVS | | | | | | | | | | | | | 80.95 281 | | | | |
|
| NP-MVS | | | | | | 95.99 297 | 89.81 225 | | | | | 95.87 272 | | | | | |
|
| MDTV_nov1_ep13_2view | | | | | | | 70.35 482 | 93.10 444 | | 83.88 420 | 93.55 216 | | 82.47 253 | | 86.25 353 | | 98.38 197 |
|
| ACMMP++_ref | | | | | | | | | | | | | | | | 90.30 339 | |
|
| ACMMP++ | | | | | | | | | | | | | | | | 91.02 328 | |
|
| Test By Simon | | | | | | | | | | | | | 88.73 108 | | | | |
|