region2R | | | 94.43 16 | 94.27 17 | 94.92 12 | 98.65 1 | 86.67 24 | 96.92 14 | 97.23 23 | 88.60 59 | 93.58 29 | 97.27 14 | 85.22 39 | 99.54 10 | 92.21 31 | 98.74 18 | 98.56 10 |
|
ACMMPR | | | 94.43 16 | 94.28 16 | 94.91 13 | 98.63 2 | 86.69 22 | 96.94 10 | 97.32 17 | 88.63 57 | 93.53 32 | 97.26 16 | 85.04 42 | 99.54 10 | 92.35 29 | 98.78 13 | 98.50 11 |
|
HFP-MVS | | | 94.52 12 | 94.40 13 | 94.86 15 | 98.61 3 | 86.81 17 | 96.94 10 | 97.34 12 | 88.63 57 | 93.65 25 | 97.21 19 | 86.10 29 | 99.49 16 | 92.35 29 | 98.77 14 | 98.30 26 |
|
#test# | | | 94.32 21 | 94.14 22 | 94.86 15 | 98.61 3 | 86.81 17 | 96.43 23 | 97.34 12 | 87.51 84 | 93.65 25 | 97.21 19 | 86.10 29 | 99.49 16 | 91.68 48 | 98.77 14 | 98.30 26 |
|
test_part2 | | | | | | 98.55 5 | 87.22 12 | | | | 96.40 4 | | | | | | |
|
v1.0 | | | 39.85 336 | 53.14 331 | 0.00 354 | 98.55 5 | 0.00 369 | 0.00 360 | 97.45 7 | 88.25 67 | 96.40 4 | 97.60 6 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
XVS | | | 94.45 14 | 94.32 14 | 94.85 17 | 98.54 7 | 86.60 27 | 96.93 12 | 97.19 24 | 90.66 22 | 92.85 39 | 97.16 24 | 85.02 43 | 99.49 16 | 91.99 39 | 98.56 35 | 98.47 14 |
|
X-MVStestdata | | | 88.31 140 | 86.13 188 | 94.85 17 | 98.54 7 | 86.60 27 | 96.93 12 | 97.19 24 | 90.66 22 | 92.85 39 | 23.41 360 | 85.02 43 | 99.49 16 | 91.99 39 | 98.56 35 | 98.47 14 |
|
mPP-MVS | | | 93.99 29 | 93.78 31 | 94.63 30 | 98.50 9 | 85.90 48 | 96.87 16 | 96.91 43 | 88.70 55 | 91.83 67 | 97.17 23 | 83.96 52 | 99.55 7 | 91.44 53 | 98.64 31 | 98.43 20 |
|
HSP-MVS | | | 95.30 4 | 95.48 3 | 94.76 25 | 98.49 10 | 86.52 29 | 96.91 15 | 96.73 56 | 91.73 9 | 96.10 7 | 96.69 39 | 89.90 2 | 99.30 29 | 94.70 3 | 98.04 49 | 98.45 18 |
|
MP-MVS | | | 94.25 22 | 94.07 25 | 94.77 24 | 98.47 11 | 86.31 37 | 96.71 20 | 96.98 35 | 89.04 47 | 91.98 63 | 97.19 21 | 85.43 37 | 99.56 2 | 92.06 38 | 98.79 11 | 98.44 19 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
MCST-MVS | | | 94.45 14 | 94.20 21 | 95.19 7 | 98.46 12 | 87.50 9 | 95.00 91 | 97.12 28 | 87.13 91 | 92.51 53 | 96.30 55 | 89.24 7 | 99.34 23 | 93.46 14 | 98.62 32 | 98.73 4 |
|
PGM-MVS | | | 93.96 30 | 93.72 33 | 94.68 28 | 98.43 13 | 86.22 40 | 95.30 65 | 97.78 1 | 87.45 85 | 93.26 33 | 97.33 12 | 84.62 47 | 99.51 14 | 90.75 62 | 98.57 34 | 98.32 25 |
|
zzz-MVS | | | 94.47 13 | 94.30 15 | 95.00 10 | 98.42 14 | 86.95 13 | 95.06 87 | 96.97 36 | 91.07 14 | 93.14 37 | 97.56 7 | 84.30 49 | 99.56 2 | 93.43 15 | 98.75 16 | 98.47 14 |
|
MTAPA | | | 94.42 18 | 94.22 18 | 95.00 10 | 98.42 14 | 86.95 13 | 94.36 144 | 96.97 36 | 91.07 14 | 93.14 37 | 97.56 7 | 84.30 49 | 99.56 2 | 93.43 15 | 98.75 16 | 98.47 14 |
|
HPM-MVS | | | 94.02 28 | 93.88 28 | 94.43 38 | 98.39 16 | 85.78 50 | 97.25 5 | 97.07 32 | 86.90 102 | 92.62 50 | 96.80 36 | 84.85 46 | 99.17 35 | 92.43 26 | 98.65 30 | 98.33 24 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
CP-MVS | | | 94.34 19 | 94.21 20 | 94.74 27 | 98.39 16 | 86.64 26 | 97.60 1 | 97.24 21 | 88.53 61 | 92.73 46 | 97.23 17 | 85.20 40 | 99.32 27 | 92.15 35 | 98.83 10 | 98.25 34 |
|
ESAPD | | | 95.57 1 | 95.67 1 | 95.25 6 | 98.36 18 | 87.28 11 | 95.56 59 | 97.51 4 | 89.13 45 | 97.14 2 | 97.91 3 | 91.64 1 | 99.62 1 | 94.61 5 | 99.17 2 | 98.86 2 |
|
HPM-MVS_fast | | | 93.40 42 | 93.22 40 | 93.94 49 | 98.36 18 | 84.83 58 | 97.15 7 | 96.80 51 | 85.77 120 | 92.47 54 | 97.13 25 | 82.38 62 | 99.07 44 | 90.51 64 | 98.40 39 | 97.92 59 |
|
DP-MVS Recon | | | 91.95 61 | 91.28 64 | 93.96 48 | 98.33 20 | 85.92 45 | 94.66 118 | 96.66 64 | 82.69 203 | 90.03 90 | 95.82 75 | 82.30 64 | 99.03 50 | 84.57 124 | 96.48 77 | 96.91 96 |
|
APDe-MVS | | | 95.46 2 | 95.64 2 | 94.91 13 | 98.26 21 | 86.29 39 | 97.46 2 | 97.40 10 | 89.03 48 | 96.20 6 | 98.10 1 | 89.39 6 | 99.34 23 | 95.88 1 | 99.03 3 | 99.10 1 |
|
TSAR-MVS + MP. | | | 94.85 9 | 94.94 8 | 94.58 32 | 98.25 22 | 86.33 35 | 96.11 34 | 96.62 67 | 88.14 70 | 96.10 7 | 96.96 29 | 89.09 8 | 98.94 65 | 94.48 6 | 98.68 24 | 98.48 13 |
|
HPM-MVS++ | | | 95.14 7 | 94.91 9 | 95.83 1 | 98.25 22 | 89.65 1 | 95.92 42 | 96.96 39 | 91.75 8 | 94.02 21 | 96.83 33 | 88.12 11 | 99.55 7 | 93.41 17 | 98.94 5 | 98.28 28 |
|
CPTT-MVS | | | 91.99 60 | 91.80 59 | 92.55 90 | 98.24 24 | 81.98 130 | 96.76 19 | 96.49 73 | 81.89 219 | 90.24 86 | 96.44 52 | 78.59 104 | 98.61 86 | 89.68 68 | 97.85 53 | 97.06 91 |
|
MP-MVS-pluss | | | 94.21 25 | 94.00 27 | 94.85 17 | 98.17 25 | 86.65 25 | 94.82 103 | 97.17 26 | 86.26 112 | 92.83 41 | 97.87 4 | 85.57 36 | 99.56 2 | 94.37 8 | 98.92 6 | 98.34 23 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
SMA-MVS | | | 95.19 6 | 95.06 7 | 95.57 2 | 98.12 26 | 88.48 4 | 96.26 28 | 97.28 20 | 85.90 117 | 97.67 1 | 98.07 2 | 88.41 10 | 99.56 2 | 94.66 4 | 99.19 1 | 98.67 5 |
|
CNVR-MVS | | | 95.40 3 | 95.37 4 | 95.50 4 | 98.11 27 | 88.51 3 | 95.29 67 | 96.96 39 | 92.09 3 | 95.32 11 | 97.08 26 | 89.49 5 | 99.33 26 | 95.10 2 | 98.85 8 | 98.66 6 |
|
114514_t | | | 89.51 109 | 88.50 117 | 92.54 91 | 98.11 27 | 81.99 129 | 95.16 80 | 96.36 82 | 70.19 329 | 85.81 155 | 95.25 89 | 76.70 120 | 98.63 84 | 82.07 160 | 96.86 68 | 97.00 93 |
|
ACMMP | | | 93.24 48 | 92.88 49 | 94.30 42 | 98.09 29 | 85.33 54 | 96.86 17 | 97.45 7 | 88.33 64 | 90.15 88 | 97.03 27 | 81.44 76 | 99.51 14 | 90.85 61 | 95.74 84 | 98.04 49 |
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 |
APD-MVS | | | 94.24 23 | 94.07 25 | 94.75 26 | 98.06 30 | 86.90 16 | 95.88 43 | 96.94 41 | 85.68 123 | 95.05 13 | 97.18 22 | 87.31 19 | 99.07 44 | 91.90 46 | 98.61 33 | 98.28 28 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
CSCG | | | 93.23 49 | 93.05 43 | 93.76 56 | 98.04 31 | 84.07 78 | 96.22 29 | 97.37 11 | 84.15 156 | 90.05 89 | 95.66 80 | 87.77 13 | 99.15 38 | 89.91 67 | 98.27 42 | 98.07 46 |
|
ACMMP_Plus | | | 94.74 11 | 94.56 12 | 95.28 5 | 98.02 32 | 87.70 5 | 95.68 51 | 97.34 12 | 88.28 66 | 95.30 12 | 97.67 5 | 85.90 33 | 99.54 10 | 93.91 11 | 98.95 4 | 98.60 8 |
|
APD-MVS_3200maxsize | | | 93.78 33 | 93.77 32 | 93.80 55 | 97.92 33 | 84.19 76 | 96.30 26 | 96.87 47 | 86.96 98 | 93.92 23 | 97.47 9 | 83.88 53 | 98.96 64 | 92.71 24 | 97.87 52 | 98.26 33 |
|
NCCC | | | 94.81 10 | 94.69 11 | 95.17 8 | 97.83 34 | 87.46 10 | 95.66 53 | 96.93 42 | 92.34 2 | 93.94 22 | 96.58 46 | 87.74 14 | 99.44 20 | 92.83 22 | 98.40 39 | 98.62 7 |
|
CDPH-MVS | | | 92.83 53 | 92.30 55 | 94.44 36 | 97.79 35 | 86.11 43 | 94.06 170 | 96.66 64 | 80.09 246 | 92.77 43 | 96.63 43 | 86.62 25 | 99.04 49 | 87.40 93 | 98.66 28 | 98.17 38 |
|
DP-MVS | | | 87.25 188 | 85.36 209 | 92.90 78 | 97.65 36 | 83.24 97 | 94.81 104 | 92.00 261 | 74.99 294 | 81.92 253 | 95.00 96 | 72.66 185 | 99.05 46 | 66.92 304 | 92.33 141 | 96.40 106 |
|
PAPM_NR | | | 91.22 74 | 90.78 75 | 92.52 92 | 97.60 37 | 81.46 140 | 94.37 140 | 96.24 88 | 86.39 110 | 87.41 128 | 94.80 104 | 82.06 71 | 98.48 92 | 82.80 148 | 95.37 91 | 97.61 69 |
|
TEST9 | | | | | | 97.53 38 | 86.49 30 | 94.07 167 | 96.78 52 | 81.61 232 | 92.77 43 | 96.20 60 | 87.71 15 | 99.12 41 | | | |
|
train_agg | | | 93.44 40 | 93.08 42 | 94.52 34 | 97.53 38 | 86.49 30 | 94.07 167 | 96.78 52 | 81.86 227 | 92.77 43 | 96.20 60 | 87.63 16 | 99.12 41 | 92.14 36 | 98.69 21 | 97.94 55 |
|
abl_6 | | | 93.18 50 | 93.05 43 | 93.57 59 | 97.52 40 | 84.27 75 | 95.53 60 | 96.67 63 | 87.85 76 | 93.20 35 | 97.22 18 | 80.35 84 | 99.18 34 | 91.91 43 | 97.21 62 | 97.26 79 |
|
test_8 | | | | | | 97.49 41 | 86.30 38 | 94.02 173 | 96.76 55 | 81.86 227 | 92.70 47 | 96.20 60 | 87.63 16 | 99.02 53 | | | |
|
agg_prior3 | | | 93.27 45 | 92.89 48 | 94.40 40 | 97.49 41 | 86.12 42 | 94.07 167 | 96.73 56 | 81.46 235 | 92.46 55 | 96.05 68 | 86.90 23 | 99.15 38 | 92.14 36 | 98.69 21 | 97.94 55 |
|
DeepC-MVS_fast | | 89.43 2 | 94.04 27 | 93.79 30 | 94.80 23 | 97.48 43 | 86.78 19 | 95.65 56 | 96.89 44 | 89.40 38 | 92.81 42 | 96.97 28 | 85.37 38 | 99.24 31 | 90.87 60 | 98.69 21 | 98.38 22 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
AdaColmap | | | 89.89 102 | 89.07 105 | 92.37 99 | 97.41 44 | 83.03 103 | 94.42 133 | 95.92 111 | 82.81 199 | 86.34 148 | 94.65 108 | 73.89 168 | 99.02 53 | 80.69 180 | 95.51 87 | 95.05 149 |
|
agg_prior1 | | | 93.29 44 | 92.97 46 | 94.26 43 | 97.38 45 | 85.92 45 | 93.92 178 | 96.72 58 | 81.96 214 | 92.16 59 | 96.23 58 | 87.85 12 | 98.97 61 | 91.95 42 | 98.55 37 | 97.90 60 |
|
agg_prior | | | | | | 97.38 45 | 85.92 45 | | 96.72 58 | | 92.16 59 | | | 98.97 61 | | | |
|
原ACMM1 | | | | | 92.01 110 | 97.34 47 | 81.05 152 | | 96.81 50 | 78.89 256 | 90.45 84 | 95.92 71 | 82.65 60 | 98.84 75 | 80.68 181 | 98.26 43 | 96.14 113 |
|
MSLP-MVS++ | | | 93.72 34 | 94.08 24 | 92.65 86 | 97.31 48 | 83.43 93 | 95.79 46 | 97.33 15 | 90.03 27 | 93.58 29 | 96.96 29 | 84.87 45 | 97.76 144 | 92.19 33 | 98.66 28 | 96.76 99 |
|
新几何1 | | | | | 93.10 68 | 97.30 49 | 84.35 74 | | 95.56 138 | 71.09 326 | 91.26 76 | 96.24 57 | 82.87 59 | 98.86 70 | 79.19 211 | 98.10 47 | 96.07 119 |
|
test_prior3 | | | 93.60 37 | 93.53 36 | 93.82 52 | 97.29 50 | 84.49 65 | 94.12 158 | 96.88 45 | 87.67 81 | 92.63 48 | 96.39 53 | 86.62 25 | 98.87 67 | 91.50 50 | 98.67 26 | 98.11 44 |
|
test_prior | | | | | 93.82 52 | 97.29 50 | 84.49 65 | | 96.88 45 | | | | | 98.87 67 | | | 98.11 44 |
|
1121 | | | 90.42 90 | 89.49 94 | 93.20 63 | 97.27 52 | 84.46 68 | 92.63 234 | 95.51 145 | 71.01 327 | 91.20 77 | 96.21 59 | 82.92 58 | 99.05 46 | 80.56 183 | 98.07 48 | 96.10 117 |
|
PLC | | 84.53 7 | 89.06 124 | 88.03 130 | 92.15 107 | 97.27 52 | 82.69 118 | 94.29 145 | 95.44 154 | 79.71 250 | 84.01 220 | 94.18 123 | 76.68 121 | 98.75 79 | 77.28 228 | 93.41 125 | 95.02 150 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
SD-MVS | | | 94.96 8 | 95.33 5 | 93.88 50 | 97.25 54 | 86.69 22 | 96.19 30 | 97.11 30 | 90.42 24 | 96.95 3 | 97.27 14 | 89.53 4 | 96.91 223 | 94.38 7 | 98.85 8 | 98.03 50 |
|
test12 | | | | | 94.34 41 | 97.13 55 | 86.15 41 | | 96.29 84 | | 91.04 79 | | 85.08 41 | 99.01 55 | | 98.13 46 | 97.86 61 |
|
MG-MVS | | | 91.77 63 | 91.70 60 | 92.00 112 | 97.08 56 | 80.03 178 | 93.60 199 | 95.18 174 | 87.85 76 | 90.89 80 | 96.47 51 | 82.06 71 | 98.36 97 | 85.07 116 | 97.04 65 | 97.62 68 |
|
SteuartSystems-ACMMP | | | 95.20 5 | 95.32 6 | 94.85 17 | 96.99 57 | 86.33 35 | 97.33 3 | 97.30 18 | 91.38 12 | 95.39 10 | 97.46 10 | 88.98 9 | 99.40 21 | 94.12 9 | 98.89 7 | 98.82 3 |
Skip Steuart: Steuart Systems R&D Blog. |
MVS_111021_HR | | | 93.45 39 | 93.31 38 | 93.84 51 | 96.99 57 | 84.84 57 | 93.24 215 | 97.24 21 | 88.76 54 | 91.60 71 | 95.85 74 | 86.07 31 | 98.66 81 | 91.91 43 | 98.16 45 | 98.03 50 |
|
CNLPA | | | 89.07 123 | 87.98 131 | 92.34 100 | 96.87 59 | 84.78 59 | 94.08 165 | 93.24 235 | 81.41 236 | 84.46 207 | 95.13 94 | 75.57 145 | 96.62 239 | 77.21 229 | 93.84 116 | 95.61 137 |
|
PHI-MVS | | | 93.89 32 | 93.65 34 | 94.62 31 | 96.84 60 | 86.43 32 | 96.69 21 | 97.49 5 | 85.15 135 | 93.56 31 | 96.28 56 | 85.60 35 | 99.31 28 | 92.45 25 | 98.79 11 | 98.12 43 |
|
旧先验1 | | | | | | 96.79 61 | 81.81 132 | | 95.67 130 | | | 96.81 34 | 86.69 24 | | | 97.66 56 | 96.97 94 |
|
LFMVS | | | 90.08 95 | 89.13 104 | 92.95 76 | 96.71 62 | 82.32 125 | 96.08 35 | 89.91 315 | 86.79 103 | 92.15 61 | 96.81 34 | 62.60 289 | 98.34 100 | 87.18 97 | 93.90 114 | 98.19 37 |
|
Anonymous202405211 | | | 87.68 163 | 86.13 188 | 92.31 101 | 96.66 63 | 80.74 162 | 94.87 100 | 91.49 279 | 80.47 243 | 89.46 95 | 95.44 83 | 54.72 325 | 98.23 105 | 82.19 158 | 89.89 171 | 97.97 53 |
|
TAPA-MVS | | 84.62 6 | 88.16 144 | 87.01 155 | 91.62 128 | 96.64 64 | 80.65 163 | 94.39 136 | 96.21 92 | 76.38 280 | 86.19 151 | 95.44 83 | 79.75 91 | 98.08 128 | 62.75 325 | 95.29 93 | 96.13 114 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
MAR-MVS | | | 90.30 91 | 89.37 98 | 93.07 72 | 96.61 65 | 84.48 67 | 95.68 51 | 95.67 130 | 82.36 207 | 87.85 117 | 92.85 169 | 76.63 122 | 98.80 77 | 80.01 193 | 96.68 71 | 95.91 124 |
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 |
VNet | | | 92.24 59 | 91.91 58 | 93.24 62 | 96.59 66 | 83.43 93 | 94.84 102 | 96.44 74 | 89.19 43 | 94.08 20 | 95.90 72 | 77.85 114 | 98.17 110 | 88.90 74 | 93.38 126 | 98.13 42 |
|
TSAR-MVS + GP. | | | 93.66 36 | 93.41 37 | 94.41 39 | 96.59 66 | 86.78 19 | 94.40 134 | 93.93 225 | 89.77 32 | 94.21 17 | 95.59 82 | 87.35 18 | 98.61 86 | 92.72 23 | 96.15 80 | 97.83 63 |
|
test222 | | | | | | 96.55 68 | 81.70 133 | 92.22 247 | 95.01 181 | 68.36 333 | 90.20 87 | 96.14 65 | 80.26 87 | | | 97.80 54 | 96.05 121 |
|
Anonymous20240529 | | | 88.09 147 | 86.59 178 | 92.58 89 | 96.53 69 | 81.92 131 | 95.99 38 | 95.84 119 | 74.11 302 | 89.06 100 | 95.21 91 | 61.44 297 | 98.81 76 | 83.67 138 | 87.47 211 | 97.01 92 |
|
Anonymous20231211 | | | 86.59 206 | 85.13 212 | 90.98 152 | 96.52 70 | 81.50 136 | 96.14 32 | 96.16 93 | 73.78 304 | 83.65 228 | 92.15 193 | 63.26 287 | 97.37 186 | 82.82 147 | 81.74 271 | 94.06 205 |
|
DeepPCF-MVS | | 89.96 1 | 94.20 26 | 94.77 10 | 92.49 93 | 96.52 70 | 80.00 179 | 94.00 175 | 97.08 31 | 90.05 26 | 95.65 9 | 97.29 13 | 89.66 3 | 98.97 61 | 93.95 10 | 98.71 19 | 98.50 11 |
|
testdata | | | | | 90.49 168 | 96.40 72 | 77.89 250 | | 95.37 160 | 72.51 316 | 93.63 27 | 96.69 39 | 82.08 69 | 97.65 149 | 83.08 141 | 97.39 60 | 95.94 123 |
|
PVSNet_Blended_VisFu | | | 91.38 71 | 90.91 72 | 92.80 81 | 96.39 73 | 83.17 99 | 94.87 100 | 96.66 64 | 83.29 179 | 89.27 96 | 94.46 113 | 80.29 86 | 99.17 35 | 87.57 91 | 95.37 91 | 96.05 121 |
|
API-MVS | | | 90.66 83 | 90.07 85 | 92.45 95 | 96.36 74 | 84.57 63 | 96.06 36 | 95.22 173 | 82.39 205 | 89.13 97 | 94.27 121 | 80.32 85 | 98.46 93 | 80.16 192 | 96.71 70 | 94.33 193 |
|
F-COLMAP | | | 87.95 153 | 86.80 162 | 91.40 134 | 96.35 75 | 80.88 158 | 94.73 109 | 95.45 152 | 79.65 251 | 82.04 251 | 94.61 109 | 71.13 202 | 98.50 91 | 76.24 239 | 91.05 153 | 94.80 168 |
|
VDD-MVS | | | 90.74 80 | 89.92 90 | 93.20 63 | 96.27 76 | 83.02 105 | 95.73 48 | 93.86 226 | 88.42 63 | 92.53 51 | 96.84 32 | 62.09 292 | 98.64 83 | 90.95 59 | 92.62 138 | 97.93 58 |
|
OMC-MVS | | | 91.23 73 | 90.62 76 | 93.08 70 | 96.27 76 | 84.07 78 | 93.52 201 | 95.93 110 | 86.95 99 | 89.51 93 | 96.13 66 | 78.50 106 | 98.35 99 | 85.84 111 | 92.90 135 | 96.83 98 |
|
view600 | | | 87.62 172 | 86.65 171 | 90.53 160 | 96.19 78 | 78.52 229 | 95.29 67 | 91.09 286 | 87.08 93 | 87.84 118 | 93.03 163 | 68.86 239 | 98.11 116 | 69.44 285 | 91.02 155 | 94.96 155 |
|
view800 | | | 87.62 172 | 86.65 171 | 90.53 160 | 96.19 78 | 78.52 229 | 95.29 67 | 91.09 286 | 87.08 93 | 87.84 118 | 93.03 163 | 68.86 239 | 98.11 116 | 69.44 285 | 91.02 155 | 94.96 155 |
|
conf0.05thres1000 | | | 87.62 172 | 86.65 171 | 90.53 160 | 96.19 78 | 78.52 229 | 95.29 67 | 91.09 286 | 87.08 93 | 87.84 118 | 93.03 163 | 68.86 239 | 98.11 116 | 69.44 285 | 91.02 155 | 94.96 155 |
|
tfpn | | | 87.62 172 | 86.65 171 | 90.53 160 | 96.19 78 | 78.52 229 | 95.29 67 | 91.09 286 | 87.08 93 | 87.84 118 | 93.03 163 | 68.86 239 | 98.11 116 | 69.44 285 | 91.02 155 | 94.96 155 |
|
CHOSEN 1792x2688 | | | 88.84 129 | 87.69 135 | 92.30 102 | 96.14 82 | 81.42 142 | 90.01 279 | 95.86 118 | 74.52 299 | 87.41 128 | 93.94 132 | 75.46 147 | 98.36 97 | 80.36 187 | 95.53 86 | 97.12 88 |
|
tfpn111 | | | 87.63 169 | 86.68 169 | 90.47 170 | 96.12 83 | 78.55 225 | 95.03 88 | 91.58 272 | 87.15 88 | 88.06 112 | 92.29 188 | 68.91 235 | 98.15 113 | 69.88 283 | 91.10 147 | 94.71 170 |
|
conf200view11 | | | 87.65 165 | 86.71 166 | 90.46 172 | 96.12 83 | 78.55 225 | 95.03 88 | 91.58 272 | 87.15 88 | 88.06 112 | 92.29 188 | 68.91 235 | 98.10 120 | 70.13 278 | 91.10 147 | 94.71 170 |
|
thres100view900 | | | 87.63 169 | 86.71 166 | 90.38 176 | 96.12 83 | 78.55 225 | 95.03 88 | 91.58 272 | 87.15 88 | 88.06 112 | 92.29 188 | 68.91 235 | 98.10 120 | 70.13 278 | 91.10 147 | 94.48 189 |
|
PVSNet_BlendedMVS | | | 89.98 97 | 89.70 91 | 90.82 154 | 96.12 83 | 81.25 145 | 93.92 178 | 96.83 48 | 83.49 173 | 89.10 98 | 92.26 191 | 81.04 80 | 98.85 73 | 86.72 106 | 87.86 209 | 92.35 281 |
|
PVSNet_Blended | | | 90.73 81 | 90.32 80 | 91.98 113 | 96.12 83 | 81.25 145 | 92.55 238 | 96.83 48 | 82.04 213 | 89.10 98 | 92.56 179 | 81.04 80 | 98.85 73 | 86.72 106 | 95.91 82 | 95.84 128 |
|
UA-Net | | | 92.83 53 | 92.54 53 | 93.68 57 | 96.10 88 | 84.71 60 | 95.66 53 | 96.39 80 | 91.92 4 | 93.22 34 | 96.49 50 | 83.16 56 | 98.87 67 | 84.47 125 | 95.47 89 | 97.45 75 |
|
thres600view7 | | | 87.65 165 | 86.67 170 | 90.59 157 | 96.08 89 | 78.72 220 | 94.88 99 | 91.58 272 | 87.06 97 | 88.08 111 | 92.30 187 | 68.91 235 | 98.10 120 | 70.05 282 | 91.10 147 | 94.96 155 |
|
DeepC-MVS | | 88.79 3 | 93.31 43 | 92.99 45 | 94.26 43 | 96.07 90 | 85.83 49 | 94.89 97 | 96.99 34 | 89.02 49 | 89.56 92 | 97.37 11 | 82.51 61 | 99.38 22 | 92.20 32 | 98.30 41 | 97.57 71 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
LS3D | | | 87.89 154 | 86.32 184 | 92.59 88 | 96.07 90 | 82.92 109 | 95.23 75 | 94.92 188 | 75.66 287 | 82.89 239 | 95.98 69 | 72.48 189 | 99.21 32 | 68.43 295 | 95.23 95 | 95.64 136 |
|
HyFIR lowres test | | | 88.09 147 | 86.81 161 | 91.93 116 | 96.00 92 | 80.63 164 | 90.01 279 | 95.79 123 | 73.42 307 | 87.68 126 | 92.10 198 | 73.86 169 | 97.96 135 | 80.75 179 | 91.70 143 | 97.19 84 |
|
tfpn200view9 | | | 87.58 178 | 86.64 175 | 90.41 173 | 95.99 93 | 78.64 222 | 94.58 121 | 91.98 263 | 86.94 100 | 88.09 109 | 91.77 209 | 69.18 232 | 98.10 120 | 70.13 278 | 91.10 147 | 94.48 189 |
|
thres400 | | | 87.62 172 | 86.64 175 | 90.57 158 | 95.99 93 | 78.64 222 | 94.58 121 | 91.98 263 | 86.94 100 | 88.09 109 | 91.77 209 | 69.18 232 | 98.10 120 | 70.13 278 | 91.10 147 | 94.96 155 |
|
MVS_111021_LR | | | 92.47 56 | 92.29 56 | 92.98 75 | 95.99 93 | 84.43 72 | 93.08 220 | 96.09 98 | 88.20 69 | 91.12 78 | 95.72 79 | 81.33 78 | 97.76 144 | 91.74 47 | 97.37 61 | 96.75 100 |
|
PatchMatch-RL | | | 86.77 202 | 85.54 202 | 90.47 170 | 95.88 96 | 82.71 117 | 90.54 272 | 92.31 251 | 79.82 249 | 84.32 214 | 91.57 219 | 68.77 243 | 96.39 252 | 73.16 262 | 93.48 124 | 92.32 282 |
|
EPP-MVSNet | | | 91.70 67 | 91.56 61 | 92.13 109 | 95.88 96 | 80.50 169 | 97.33 3 | 95.25 167 | 86.15 114 | 89.76 91 | 95.60 81 | 83.42 55 | 98.32 102 | 87.37 95 | 93.25 129 | 97.56 72 |
|
IS-MVSNet | | | 91.43 70 | 91.09 69 | 92.46 94 | 95.87 98 | 81.38 143 | 96.95 9 | 93.69 230 | 89.72 34 | 89.50 94 | 95.98 69 | 78.57 105 | 97.77 143 | 83.02 143 | 96.50 76 | 98.22 35 |
|
PAPR | | | 90.02 96 | 89.27 102 | 92.29 103 | 95.78 99 | 80.95 156 | 92.68 233 | 96.22 89 | 81.91 217 | 86.66 141 | 93.75 143 | 82.23 65 | 98.44 95 | 79.40 210 | 94.79 97 | 97.48 74 |
|
Vis-MVSNet (Re-imp) | | | 89.59 107 | 89.44 96 | 90.03 198 | 95.74 100 | 75.85 279 | 95.61 57 | 90.80 299 | 87.66 83 | 87.83 122 | 95.40 86 | 76.79 119 | 96.46 249 | 78.37 216 | 96.73 69 | 97.80 64 |
|
0601test | | | 90.69 82 | 90.02 89 | 92.71 84 | 95.72 101 | 82.41 124 | 94.11 160 | 95.12 176 | 85.63 124 | 91.49 72 | 94.70 105 | 74.75 155 | 98.42 96 | 86.13 110 | 92.53 139 | 97.31 78 |
|
MVS_0304 | | | 93.25 47 | 92.62 51 | 95.14 9 | 95.72 101 | 87.58 8 | 94.71 114 | 96.59 69 | 91.78 7 | 91.46 73 | 96.18 64 | 75.45 148 | 99.55 7 | 93.53 12 | 98.19 44 | 98.28 28 |
|
canonicalmvs | | | 93.27 45 | 92.75 50 | 94.85 17 | 95.70 103 | 87.66 6 | 96.33 25 | 96.41 77 | 90.00 28 | 94.09 19 | 94.60 110 | 82.33 63 | 98.62 85 | 92.40 28 | 92.86 136 | 98.27 31 |
|
CANet | | | 93.54 38 | 93.20 41 | 94.55 33 | 95.65 104 | 85.73 51 | 94.94 94 | 96.69 62 | 91.89 5 | 90.69 82 | 95.88 73 | 81.99 73 | 99.54 10 | 93.14 20 | 97.95 51 | 98.39 21 |
|
3Dnovator+ | | 87.14 4 | 92.42 58 | 91.37 62 | 95.55 3 | 95.63 105 | 88.73 2 | 97.07 8 | 96.77 54 | 90.84 17 | 84.02 219 | 96.62 44 | 75.95 137 | 99.34 23 | 87.77 88 | 97.68 55 | 98.59 9 |
|
alignmvs | | | 93.08 51 | 92.50 54 | 94.81 22 | 95.62 106 | 87.61 7 | 95.99 38 | 96.07 100 | 89.77 32 | 94.12 18 | 94.87 99 | 80.56 82 | 98.66 81 | 92.42 27 | 93.10 132 | 98.15 40 |
|
tfpn1000 | | | 86.06 215 | 84.92 219 | 89.49 222 | 95.54 107 | 77.79 253 | 94.72 112 | 89.07 329 | 82.05 211 | 85.36 187 | 91.94 205 | 68.32 258 | 96.65 237 | 67.04 301 | 90.24 165 | 94.02 208 |
|
Regformer-1 | | | 94.22 24 | 94.13 23 | 94.51 35 | 95.54 107 | 86.36 34 | 94.57 123 | 96.44 74 | 91.69 10 | 94.32 16 | 96.56 48 | 87.05 22 | 99.03 50 | 93.35 18 | 97.65 57 | 98.15 40 |
|
Regformer-2 | | | 94.33 20 | 94.22 18 | 94.68 28 | 95.54 107 | 86.75 21 | 94.57 123 | 96.70 60 | 91.84 6 | 94.41 14 | 96.56 48 | 87.19 20 | 99.13 40 | 93.50 13 | 97.65 57 | 98.16 39 |
|
tfpn_ndepth | | | 86.10 214 | 84.98 215 | 89.43 224 | 95.52 110 | 78.29 240 | 94.62 119 | 89.60 321 | 81.88 226 | 85.43 179 | 90.54 255 | 68.47 249 | 96.85 227 | 68.46 294 | 90.34 164 | 93.15 257 |
|
WTY-MVS | | | 89.60 106 | 88.92 109 | 91.67 127 | 95.47 111 | 81.15 150 | 92.38 243 | 94.78 195 | 83.11 183 | 89.06 100 | 94.32 116 | 78.67 103 | 96.61 241 | 81.57 169 | 90.89 159 | 97.24 80 |
|
DELS-MVS | | | 93.43 41 | 93.25 39 | 93.97 47 | 95.42 112 | 85.04 56 | 93.06 222 | 97.13 27 | 90.74 20 | 91.84 65 | 95.09 95 | 86.32 28 | 99.21 32 | 91.22 54 | 98.45 38 | 97.65 67 |
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 |
Regformer-3 | | | 93.68 35 | 93.64 35 | 93.81 54 | 95.36 113 | 84.61 61 | 94.68 115 | 95.83 120 | 91.27 13 | 93.60 28 | 96.71 37 | 85.75 34 | 98.86 70 | 92.87 21 | 96.65 72 | 97.96 54 |
|
Regformer-4 | | | 93.91 31 | 93.81 29 | 94.19 45 | 95.36 113 | 85.47 52 | 94.68 115 | 96.41 77 | 91.60 11 | 93.75 24 | 96.71 37 | 85.95 32 | 99.10 43 | 93.21 19 | 96.65 72 | 98.01 52 |
|
thres200 | | | 87.21 191 | 86.24 187 | 90.12 189 | 95.36 113 | 78.53 228 | 93.26 213 | 92.10 256 | 86.42 109 | 88.00 115 | 91.11 244 | 69.24 231 | 98.00 133 | 69.58 284 | 91.04 154 | 93.83 219 |
|
casdiffmvs1 | | | 92.43 57 | 92.18 57 | 93.17 65 | 95.33 116 | 83.03 103 | 95.08 84 | 96.41 77 | 83.18 182 | 93.20 35 | 94.49 112 | 83.84 54 | 98.29 104 | 92.16 34 | 95.96 81 | 98.20 36 |
|
Vis-MVSNet | | | 91.75 64 | 91.23 66 | 93.29 60 | 95.32 117 | 83.78 83 | 96.14 32 | 95.98 107 | 89.89 29 | 90.45 84 | 96.58 46 | 75.09 152 | 98.31 103 | 84.75 122 | 96.90 66 | 97.78 66 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
BH-RMVSNet | | | 88.37 138 | 87.48 138 | 91.02 147 | 95.28 118 | 79.45 194 | 92.89 228 | 93.07 238 | 85.45 128 | 86.91 136 | 94.84 103 | 70.35 216 | 97.76 144 | 73.97 257 | 94.59 102 | 95.85 127 |
|
COLMAP_ROB | | 80.39 16 | 83.96 262 | 82.04 268 | 89.74 209 | 95.28 118 | 79.75 184 | 94.25 147 | 92.28 252 | 75.17 292 | 78.02 289 | 93.77 141 | 58.60 313 | 97.84 141 | 65.06 318 | 85.92 223 | 91.63 294 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
conf0.01 | | | 85.83 222 | 84.54 228 | 89.71 211 | 95.26 120 | 77.63 259 | 94.21 150 | 89.33 322 | 81.89 219 | 84.94 194 | 91.51 223 | 68.43 251 | 96.80 228 | 66.05 307 | 89.23 183 | 94.71 170 |
|
conf0.002 | | | 85.83 222 | 84.54 228 | 89.71 211 | 95.26 120 | 77.63 259 | 94.21 150 | 89.33 322 | 81.89 219 | 84.94 194 | 91.51 223 | 68.43 251 | 96.80 228 | 66.05 307 | 89.23 183 | 94.71 170 |
|
thresconf0.02 | | | 85.75 226 | 84.54 228 | 89.38 227 | 95.26 120 | 77.63 259 | 94.21 150 | 89.33 322 | 81.89 219 | 84.94 194 | 91.51 223 | 68.43 251 | 96.80 228 | 66.05 307 | 89.23 183 | 93.70 229 |
|
tfpn_n400 | | | 85.75 226 | 84.54 228 | 89.38 227 | 95.26 120 | 77.63 259 | 94.21 150 | 89.33 322 | 81.89 219 | 84.94 194 | 91.51 223 | 68.43 251 | 96.80 228 | 66.05 307 | 89.23 183 | 93.70 229 |
|
tfpnconf | | | 85.75 226 | 84.54 228 | 89.38 227 | 95.26 120 | 77.63 259 | 94.21 150 | 89.33 322 | 81.89 219 | 84.94 194 | 91.51 223 | 68.43 251 | 96.80 228 | 66.05 307 | 89.23 183 | 93.70 229 |
|
tfpnview11 | | | 85.75 226 | 84.54 228 | 89.38 227 | 95.26 120 | 77.63 259 | 94.21 150 | 89.33 322 | 81.89 219 | 84.94 194 | 91.51 223 | 68.43 251 | 96.80 228 | 66.05 307 | 89.23 183 | 93.70 229 |
|
PS-MVSNAJ | | | 91.18 75 | 90.92 71 | 91.96 114 | 95.26 120 | 82.60 121 | 92.09 252 | 95.70 129 | 86.27 111 | 91.84 65 | 92.46 180 | 79.70 93 | 98.99 59 | 89.08 72 | 95.86 83 | 94.29 194 |
|
BH-untuned | | | 88.60 134 | 88.13 129 | 90.01 200 | 95.24 127 | 78.50 234 | 93.29 211 | 94.15 212 | 84.75 143 | 84.46 207 | 93.40 145 | 75.76 142 | 97.40 181 | 77.59 225 | 94.52 104 | 94.12 200 |
|
ab-mvs | | | 89.41 115 | 88.35 121 | 92.60 87 | 95.15 128 | 82.65 119 | 92.20 248 | 95.60 136 | 83.97 159 | 88.55 104 | 93.70 144 | 74.16 165 | 98.21 108 | 82.46 154 | 89.37 179 | 96.94 95 |
|
VDDNet | | | 89.56 108 | 88.49 119 | 92.76 83 | 95.07 129 | 82.09 127 | 96.30 26 | 93.19 236 | 81.05 240 | 91.88 64 | 96.86 31 | 61.16 302 | 98.33 101 | 88.43 80 | 92.49 140 | 97.84 62 |
|
AllTest | | | 83.42 267 | 81.39 271 | 89.52 219 | 95.01 130 | 77.79 253 | 93.12 217 | 90.89 297 | 77.41 272 | 76.12 306 | 93.34 146 | 54.08 328 | 97.51 157 | 68.31 296 | 84.27 238 | 93.26 251 |
|
TestCases | | | | | 89.52 219 | 95.01 130 | 77.79 253 | | 90.89 297 | 77.41 272 | 76.12 306 | 93.34 146 | 54.08 328 | 97.51 157 | 68.31 296 | 84.27 238 | 93.26 251 |
|
EI-MVSNet-Vis-set | | | 93.01 52 | 92.92 47 | 93.29 60 | 95.01 130 | 83.51 92 | 94.48 126 | 95.77 124 | 90.87 16 | 92.52 52 | 96.67 41 | 84.50 48 | 99.00 58 | 91.99 39 | 94.44 108 | 97.36 76 |
|
xiu_mvs_v2_base | | | 91.13 76 | 90.89 73 | 91.86 119 | 94.97 133 | 82.42 122 | 92.24 246 | 95.64 135 | 86.11 116 | 91.74 70 | 93.14 158 | 79.67 96 | 98.89 66 | 89.06 73 | 95.46 90 | 94.28 195 |
|
Test_1112_low_res | | | 87.65 165 | 86.51 180 | 91.08 143 | 94.94 134 | 79.28 208 | 91.77 255 | 94.30 208 | 76.04 285 | 83.51 232 | 92.37 184 | 77.86 113 | 97.73 148 | 78.69 215 | 89.13 191 | 96.22 111 |
|
1112_ss | | | 88.42 136 | 87.33 142 | 91.72 125 | 94.92 135 | 80.98 154 | 92.97 226 | 94.54 200 | 78.16 269 | 83.82 223 | 93.88 137 | 78.78 101 | 97.91 139 | 79.45 206 | 89.41 178 | 96.26 110 |
|
QAPM | | | 89.51 109 | 88.15 128 | 93.59 58 | 94.92 135 | 84.58 62 | 96.82 18 | 96.70 60 | 78.43 264 | 83.41 234 | 96.19 63 | 73.18 179 | 99.30 29 | 77.11 231 | 96.54 75 | 96.89 97 |
|
BH-w/o | | | 87.57 179 | 87.05 154 | 89.12 236 | 94.90 137 | 77.90 249 | 92.41 241 | 93.51 232 | 82.89 198 | 83.70 226 | 91.34 230 | 75.75 143 | 97.07 210 | 75.49 243 | 93.49 122 | 92.39 279 |
|
EI-MVSNet-UG-set | | | 92.74 55 | 92.62 51 | 93.12 67 | 94.86 138 | 83.20 98 | 94.40 134 | 95.74 127 | 90.71 21 | 92.05 62 | 96.60 45 | 84.00 51 | 98.99 59 | 91.55 49 | 93.63 119 | 97.17 85 |
|
HY-MVS | | 83.01 12 | 89.03 125 | 87.94 133 | 92.29 103 | 94.86 138 | 82.77 111 | 92.08 253 | 94.49 201 | 81.52 234 | 86.93 135 | 92.79 175 | 78.32 109 | 98.23 105 | 79.93 196 | 90.55 160 | 95.88 126 |
|
Fast-Effi-MVS+ | | | 89.41 115 | 88.64 114 | 91.71 126 | 94.74 140 | 80.81 160 | 93.54 200 | 95.10 177 | 83.11 183 | 86.82 139 | 90.67 251 | 79.74 92 | 97.75 147 | 80.51 185 | 93.55 120 | 96.57 104 |
|
ACMP | | 84.23 8 | 89.01 127 | 88.35 121 | 90.99 150 | 94.73 141 | 81.27 144 | 95.07 85 | 95.89 116 | 86.48 107 | 83.67 227 | 94.30 117 | 69.33 227 | 97.99 134 | 87.10 102 | 88.55 196 | 93.72 228 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
PVSNet | | 78.82 18 | 85.55 232 | 84.65 226 | 88.23 265 | 94.72 142 | 71.93 308 | 87.12 313 | 92.75 244 | 78.80 259 | 84.95 193 | 90.53 257 | 64.43 283 | 96.71 236 | 74.74 251 | 93.86 115 | 96.06 120 |
|
LCM-MVSNet-Re | | | 88.30 141 | 88.32 124 | 88.27 262 | 94.71 143 | 72.41 307 | 93.15 216 | 90.98 294 | 87.77 78 | 79.25 283 | 91.96 204 | 78.35 108 | 95.75 277 | 83.04 142 | 95.62 85 | 96.65 102 |
|
HQP_MVS | | | 90.60 87 | 90.19 82 | 91.82 122 | 94.70 144 | 82.73 115 | 95.85 44 | 96.22 89 | 90.81 18 | 86.91 136 | 94.86 100 | 74.23 161 | 98.12 114 | 88.15 82 | 89.99 168 | 94.63 175 |
|
plane_prior7 | | | | | | 94.70 144 | 82.74 114 | | | | | | | | | | |
|
casdiffmvs | | | 91.72 66 | 91.26 65 | 93.10 68 | 94.66 146 | 83.75 84 | 94.77 107 | 96.00 106 | 83.98 158 | 90.74 81 | 93.96 131 | 82.08 69 | 98.19 109 | 91.47 52 | 93.68 117 | 97.36 76 |
|
ACMH+ | | 81.04 14 | 85.05 241 | 83.46 253 | 89.82 205 | 94.66 146 | 79.37 202 | 94.44 131 | 94.12 214 | 82.19 209 | 78.04 288 | 92.82 172 | 58.23 314 | 97.54 155 | 73.77 259 | 82.90 252 | 92.54 273 |
|
ACMM | | 84.12 9 | 89.14 121 | 88.48 120 | 91.12 140 | 94.65 148 | 81.22 147 | 95.31 63 | 96.12 97 | 85.31 131 | 85.92 154 | 94.34 114 | 70.19 219 | 98.06 130 | 85.65 112 | 88.86 194 | 94.08 204 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
plane_prior1 | | | | | | 94.59 149 | | | | | | | | | | | |
|
3Dnovator | | 86.66 5 | 91.73 65 | 90.82 74 | 94.44 36 | 94.59 149 | 86.37 33 | 97.18 6 | 97.02 33 | 89.20 42 | 84.31 215 | 96.66 42 | 73.74 172 | 99.17 35 | 86.74 103 | 97.96 50 | 97.79 65 |
|
plane_prior6 | | | | | | 94.52 151 | 82.75 112 | | | | | | 74.23 161 | | | | |
|
UGNet | | | 89.95 99 | 88.95 108 | 92.95 76 | 94.51 152 | 83.31 96 | 95.70 50 | 95.23 171 | 89.37 39 | 87.58 127 | 93.94 132 | 64.00 284 | 98.78 78 | 83.92 135 | 96.31 79 | 96.74 101 |
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 |
LPG-MVS_test | | | 89.45 112 | 88.90 110 | 91.12 140 | 94.47 153 | 81.49 138 | 95.30 65 | 96.14 94 | 86.73 104 | 85.45 176 | 95.16 92 | 69.89 220 | 98.10 120 | 87.70 89 | 89.23 183 | 93.77 224 |
|
LGP-MVS_train | | | | | 91.12 140 | 94.47 153 | 81.49 138 | | 96.14 94 | 86.73 104 | 85.45 176 | 95.16 92 | 69.89 220 | 98.10 120 | 87.70 89 | 89.23 183 | 93.77 224 |
|
ACMH | | 80.38 17 | 85.36 234 | 83.68 246 | 90.39 174 | 94.45 155 | 80.63 164 | 94.73 109 | 94.85 191 | 82.09 210 | 77.24 295 | 92.65 177 | 60.01 308 | 97.58 152 | 72.25 266 | 84.87 233 | 92.96 262 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
LTVRE_ROB | | 82.13 13 | 86.26 212 | 84.90 220 | 90.34 179 | 94.44 156 | 81.50 136 | 92.31 245 | 94.89 189 | 83.03 190 | 79.63 280 | 92.67 176 | 69.69 223 | 97.79 142 | 71.20 270 | 86.26 222 | 91.72 292 |
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 |
MVS_Test | | | 91.31 72 | 91.11 67 | 91.93 116 | 94.37 157 | 80.14 173 | 93.46 204 | 95.80 122 | 86.46 108 | 91.35 75 | 93.77 141 | 82.21 66 | 98.09 127 | 87.57 91 | 94.95 96 | 97.55 73 |
|
NP-MVS | | | | | | 94.37 157 | 82.42 122 | | | | | 93.98 129 | | | | | |
|
TR-MVS | | | 86.78 200 | 85.76 200 | 89.82 205 | 94.37 157 | 78.41 236 | 92.47 240 | 92.83 241 | 81.11 239 | 86.36 147 | 92.40 182 | 68.73 244 | 97.48 159 | 73.75 260 | 89.85 173 | 93.57 242 |
|
Effi-MVS+ | | | 91.59 69 | 91.11 67 | 93.01 74 | 94.35 160 | 83.39 95 | 94.60 120 | 95.10 177 | 87.10 92 | 90.57 83 | 93.10 160 | 81.43 77 | 98.07 129 | 89.29 71 | 94.48 105 | 97.59 70 |
|
CLD-MVS | | | 89.47 111 | 88.90 110 | 91.18 139 | 94.22 161 | 82.07 128 | 92.13 250 | 96.09 98 | 87.90 74 | 85.37 186 | 92.45 181 | 74.38 159 | 97.56 154 | 87.15 98 | 90.43 161 | 93.93 210 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
HQP-NCC | | | | | | 94.17 162 | | 94.39 136 | | 88.81 51 | 85.43 179 | | | | | | |
|
ACMP_Plane | | | | | | 94.17 162 | | 94.39 136 | | 88.81 51 | 85.43 179 | | | | | | |
|
HQP-MVS | | | 89.80 103 | 89.28 101 | 91.34 135 | 94.17 162 | 81.56 134 | 94.39 136 | 96.04 104 | 88.81 51 | 85.43 179 | 93.97 130 | 73.83 170 | 97.96 135 | 87.11 100 | 89.77 174 | 94.50 186 |
|
XVG-OURS | | | 89.40 117 | 88.70 113 | 91.52 130 | 94.06 165 | 81.46 140 | 91.27 267 | 96.07 100 | 86.14 115 | 88.89 102 | 95.77 77 | 68.73 244 | 97.26 195 | 87.39 94 | 89.96 170 | 95.83 129 |
|
sss | | | 88.93 128 | 88.26 127 | 90.94 153 | 94.05 166 | 80.78 161 | 91.71 258 | 95.38 158 | 81.55 233 | 88.63 103 | 93.91 136 | 75.04 153 | 95.47 288 | 82.47 153 | 91.61 144 | 96.57 104 |
|
PCF-MVS | | 84.11 10 | 87.74 162 | 86.08 192 | 92.70 85 | 94.02 167 | 84.43 72 | 89.27 290 | 95.87 117 | 73.62 306 | 84.43 209 | 94.33 115 | 78.48 107 | 98.86 70 | 70.27 274 | 94.45 107 | 94.81 167 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
GBi-Net | | | 87.26 186 | 85.98 194 | 91.08 143 | 94.01 168 | 83.10 100 | 95.14 81 | 94.94 184 | 83.57 169 | 84.37 210 | 91.64 212 | 66.59 267 | 96.34 255 | 78.23 219 | 85.36 228 | 93.79 220 |
|
test1 | | | 87.26 186 | 85.98 194 | 91.08 143 | 94.01 168 | 83.10 100 | 95.14 81 | 94.94 184 | 83.57 169 | 84.37 210 | 91.64 212 | 66.59 267 | 96.34 255 | 78.23 219 | 85.36 228 | 93.79 220 |
|
FMVSNet2 | | | 87.19 192 | 85.82 199 | 91.30 136 | 94.01 168 | 83.67 87 | 94.79 105 | 94.94 184 | 83.57 169 | 83.88 221 | 92.05 202 | 66.59 267 | 96.51 245 | 77.56 226 | 85.01 232 | 93.73 227 |
|
XVG-OURS-SEG-HR | | | 89.95 99 | 89.45 95 | 91.47 132 | 94.00 171 | 81.21 148 | 91.87 254 | 96.06 102 | 85.78 119 | 88.55 104 | 95.73 78 | 74.67 157 | 97.27 193 | 88.71 76 | 89.64 176 | 95.91 124 |
|
FIs | | | 90.51 88 | 90.35 78 | 90.99 150 | 93.99 172 | 80.98 154 | 95.73 48 | 97.54 3 | 89.15 44 | 86.72 140 | 94.68 106 | 81.83 75 | 97.24 197 | 85.18 115 | 88.31 204 | 94.76 169 |
|
xiu_mvs_v1_base_debu | | | 90.64 84 | 90.05 86 | 92.40 96 | 93.97 173 | 84.46 68 | 93.32 206 | 95.46 148 | 85.17 132 | 92.25 56 | 94.03 124 | 70.59 211 | 98.57 88 | 90.97 56 | 94.67 98 | 94.18 196 |
|
xiu_mvs_v1_base | | | 90.64 84 | 90.05 86 | 92.40 96 | 93.97 173 | 84.46 68 | 93.32 206 | 95.46 148 | 85.17 132 | 92.25 56 | 94.03 124 | 70.59 211 | 98.57 88 | 90.97 56 | 94.67 98 | 94.18 196 |
|
xiu_mvs_v1_base_debi | | | 90.64 84 | 90.05 86 | 92.40 96 | 93.97 173 | 84.46 68 | 93.32 206 | 95.46 148 | 85.17 132 | 92.25 56 | 94.03 124 | 70.59 211 | 98.57 88 | 90.97 56 | 94.67 98 | 94.18 196 |
|
VPA-MVSNet | | | 89.62 105 | 88.96 107 | 91.60 129 | 93.86 176 | 82.89 110 | 95.46 61 | 97.33 15 | 87.91 73 | 88.43 106 | 93.31 150 | 74.17 164 | 97.40 181 | 87.32 96 | 82.86 253 | 94.52 184 |
|
MVSFormer | | | 91.68 68 | 91.30 63 | 92.80 81 | 93.86 176 | 83.88 81 | 95.96 40 | 95.90 114 | 84.66 145 | 91.76 68 | 94.91 97 | 77.92 111 | 97.30 189 | 89.64 69 | 97.11 63 | 97.24 80 |
|
lupinMVS | | | 90.92 78 | 90.21 81 | 93.03 73 | 93.86 176 | 83.88 81 | 92.81 230 | 93.86 226 | 79.84 248 | 91.76 68 | 94.29 118 | 77.92 111 | 98.04 131 | 90.48 65 | 97.11 63 | 97.17 85 |
|
IterMVS-LS | | | 88.36 139 | 87.91 134 | 89.70 213 | 93.80 179 | 78.29 240 | 93.73 190 | 95.08 179 | 85.73 121 | 84.75 201 | 91.90 207 | 79.88 89 | 96.92 222 | 83.83 136 | 82.51 255 | 93.89 212 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
MSDG | | | 84.86 248 | 83.09 259 | 90.14 188 | 93.80 179 | 80.05 176 | 89.18 293 | 93.09 237 | 78.89 256 | 78.19 286 | 91.91 206 | 65.86 277 | 97.27 193 | 68.47 293 | 88.45 200 | 93.11 258 |
|
FMVSNet3 | | | 87.40 184 | 86.11 190 | 91.30 136 | 93.79 181 | 83.64 88 | 94.20 156 | 94.81 194 | 83.89 160 | 84.37 210 | 91.87 208 | 68.45 250 | 96.56 242 | 78.23 219 | 85.36 228 | 93.70 229 |
|
FC-MVSNet-test | | | 90.27 92 | 90.18 83 | 90.53 160 | 93.71 182 | 79.85 183 | 95.77 47 | 97.59 2 | 89.31 40 | 86.27 149 | 94.67 107 | 81.93 74 | 97.01 214 | 84.26 130 | 88.09 207 | 94.71 170 |
|
TAMVS | | | 89.21 120 | 88.29 125 | 91.96 114 | 93.71 182 | 82.62 120 | 93.30 210 | 94.19 210 | 82.22 208 | 87.78 124 | 93.94 132 | 78.83 100 | 96.95 220 | 77.70 224 | 92.98 134 | 96.32 108 |
|
CDS-MVSNet | | | 89.45 112 | 88.51 116 | 92.29 103 | 93.62 184 | 83.61 90 | 93.01 223 | 94.68 197 | 81.95 215 | 87.82 123 | 93.24 154 | 78.69 102 | 96.99 215 | 80.34 188 | 93.23 130 | 96.28 109 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
UniMVSNet (Re) | | | 89.80 103 | 89.07 105 | 92.01 110 | 93.60 185 | 84.52 64 | 94.78 106 | 97.47 6 | 89.26 41 | 86.44 146 | 92.32 186 | 82.10 68 | 97.39 185 | 84.81 121 | 80.84 285 | 94.12 200 |
|
VPNet | | | 88.20 143 | 87.47 139 | 90.39 174 | 93.56 186 | 79.46 192 | 94.04 171 | 95.54 141 | 88.67 56 | 86.96 134 | 94.58 111 | 69.33 227 | 97.15 203 | 84.05 134 | 80.53 290 | 94.56 182 |
|
mvs_anonymous | | | 89.37 118 | 89.32 99 | 89.51 221 | 93.47 187 | 74.22 286 | 91.65 261 | 94.83 193 | 82.91 197 | 85.45 176 | 93.79 140 | 81.23 79 | 96.36 254 | 86.47 109 | 94.09 111 | 97.94 55 |
|
CANet_DTU | | | 90.26 93 | 89.41 97 | 92.81 80 | 93.46 188 | 83.01 106 | 93.48 202 | 94.47 202 | 89.43 37 | 87.76 125 | 94.23 122 | 70.54 215 | 99.03 50 | 84.97 117 | 96.39 78 | 96.38 107 |
|
UniMVSNet_NR-MVSNet | | | 89.92 101 | 89.29 100 | 91.81 124 | 93.39 189 | 83.72 85 | 94.43 132 | 97.12 28 | 89.80 31 | 86.46 143 | 93.32 149 | 83.16 56 | 97.23 199 | 84.92 118 | 81.02 281 | 94.49 188 |
|
Effi-MVS+-dtu | | | 88.65 133 | 88.35 121 | 89.54 218 | 93.33 190 | 76.39 274 | 94.47 129 | 94.36 205 | 87.70 79 | 85.43 179 | 89.56 273 | 73.45 175 | 97.26 195 | 85.57 113 | 91.28 146 | 94.97 152 |
|
mvs-test1 | | | 89.45 112 | 89.14 103 | 90.38 176 | 93.33 190 | 77.63 259 | 94.95 93 | 94.36 205 | 87.70 79 | 87.10 133 | 92.81 173 | 73.45 175 | 98.03 132 | 85.57 113 | 93.04 133 | 95.48 139 |
|
WR-MVS | | | 88.38 137 | 87.67 136 | 90.52 166 | 93.30 192 | 80.18 171 | 93.26 213 | 95.96 109 | 88.57 60 | 85.47 175 | 92.81 173 | 76.12 126 | 96.91 223 | 81.24 171 | 82.29 257 | 94.47 191 |
|
WR-MVS_H | | | 87.80 160 | 87.37 141 | 89.10 238 | 93.23 193 | 78.12 244 | 95.61 57 | 97.30 18 | 87.90 74 | 83.72 225 | 92.01 203 | 79.65 97 | 96.01 266 | 76.36 236 | 80.54 289 | 93.16 255 |
|
test_0402 | | | 81.30 290 | 79.17 294 | 87.67 274 | 93.19 194 | 78.17 243 | 92.98 225 | 91.71 268 | 75.25 291 | 76.02 309 | 90.31 261 | 59.23 311 | 96.37 253 | 50.22 342 | 83.63 245 | 88.47 336 |
|
OPM-MVS | | | 90.12 94 | 89.56 93 | 91.82 122 | 93.14 195 | 83.90 80 | 94.16 157 | 95.74 127 | 88.96 50 | 87.86 116 | 95.43 85 | 72.48 189 | 97.91 139 | 88.10 85 | 90.18 167 | 93.65 234 |
|
CP-MVSNet | | | 87.63 169 | 87.26 145 | 88.74 243 | 93.12 196 | 76.59 273 | 95.29 67 | 96.58 71 | 88.43 62 | 83.49 233 | 92.98 167 | 75.28 149 | 95.83 273 | 78.97 212 | 81.15 278 | 93.79 220 |
|
nrg030 | | | 91.08 77 | 90.39 77 | 93.17 65 | 93.07 197 | 86.91 15 | 96.41 24 | 96.26 85 | 88.30 65 | 88.37 107 | 94.85 102 | 82.19 67 | 97.64 151 | 91.09 55 | 82.95 251 | 94.96 155 |
|
PAPM | | | 86.68 203 | 85.39 208 | 90.53 160 | 93.05 198 | 79.33 207 | 89.79 283 | 94.77 196 | 78.82 258 | 81.95 252 | 93.24 154 | 76.81 118 | 97.30 189 | 66.94 302 | 93.16 131 | 94.95 162 |
|
diffmvs | | | 90.50 89 | 90.33 79 | 91.02 147 | 93.04 199 | 78.59 224 | 92.85 229 | 95.07 180 | 87.32 87 | 88.32 108 | 93.34 146 | 80.46 83 | 97.40 181 | 88.50 78 | 94.06 112 | 97.07 90 |
|
DU-MVS | | | 89.34 119 | 88.50 117 | 91.85 120 | 93.04 199 | 83.72 85 | 94.47 129 | 96.59 69 | 89.50 36 | 86.46 143 | 93.29 152 | 77.25 115 | 97.23 199 | 84.92 118 | 81.02 281 | 94.59 179 |
|
NR-MVSNet | | | 88.58 135 | 87.47 139 | 91.93 116 | 93.04 199 | 84.16 77 | 94.77 107 | 96.25 87 | 89.05 46 | 80.04 277 | 93.29 152 | 79.02 99 | 97.05 212 | 81.71 168 | 80.05 295 | 94.59 179 |
|
jason | | | 90.80 79 | 90.10 84 | 92.90 78 | 93.04 199 | 83.53 91 | 93.08 220 | 94.15 212 | 80.22 244 | 91.41 74 | 94.91 97 | 76.87 117 | 97.93 138 | 90.28 66 | 96.90 66 | 97.24 80 |
jason: jason. |
PS-CasMVS | | | 87.32 185 | 86.88 157 | 88.63 246 | 92.99 203 | 76.33 276 | 95.33 62 | 96.61 68 | 88.22 68 | 83.30 236 | 93.07 161 | 73.03 181 | 95.79 276 | 78.36 217 | 81.00 283 | 93.75 226 |
|
MVSTER | | | 88.84 129 | 88.29 125 | 90.51 167 | 92.95 204 | 80.44 170 | 93.73 190 | 95.01 181 | 84.66 145 | 87.15 131 | 93.12 159 | 72.79 183 | 97.21 201 | 87.86 87 | 87.36 214 | 93.87 215 |
|
RPSCF | | | 85.07 240 | 84.27 234 | 87.48 280 | 92.91 205 | 70.62 320 | 91.69 260 | 92.46 249 | 76.20 284 | 82.67 242 | 95.22 90 | 63.94 285 | 97.29 192 | 77.51 227 | 85.80 225 | 94.53 183 |
|
Anonymous20240521 | | | 86.87 197 | 85.95 196 | 89.64 215 | 92.89 206 | 78.88 219 | 95.66 53 | 96.05 103 | 84.77 142 | 81.92 253 | 92.39 183 | 71.54 197 | 96.96 218 | 76.46 235 | 81.87 267 | 93.08 260 |
|
FMVSNet1 | | | 85.85 220 | 84.11 236 | 91.08 143 | 92.81 207 | 83.10 100 | 95.14 81 | 94.94 184 | 81.64 230 | 82.68 241 | 91.64 212 | 59.01 312 | 96.34 255 | 75.37 245 | 83.78 241 | 93.79 220 |
|
tfpnnormal | | | 84.72 254 | 83.23 258 | 89.20 235 | 92.79 208 | 80.05 176 | 94.48 126 | 95.81 121 | 82.38 206 | 81.08 263 | 91.21 238 | 69.01 234 | 96.95 220 | 61.69 327 | 80.59 288 | 90.58 319 |
|
OpenMVS | | 83.78 11 | 88.74 132 | 87.29 143 | 93.08 70 | 92.70 209 | 85.39 53 | 96.57 22 | 96.43 76 | 78.74 261 | 80.85 265 | 96.07 67 | 69.64 224 | 99.01 55 | 78.01 222 | 96.65 72 | 94.83 166 |
|
TranMVSNet+NR-MVSNet | | | 88.84 129 | 87.95 132 | 91.49 131 | 92.68 210 | 83.01 106 | 94.92 96 | 96.31 83 | 89.88 30 | 85.53 170 | 93.85 139 | 76.63 122 | 96.96 218 | 81.91 164 | 79.87 300 | 94.50 186 |
|
MVS | | | 87.44 182 | 86.10 191 | 91.44 133 | 92.61 211 | 83.62 89 | 92.63 234 | 95.66 132 | 67.26 337 | 81.47 257 | 92.15 193 | 77.95 110 | 98.22 107 | 79.71 202 | 95.48 88 | 92.47 276 |
|
CHOSEN 280x420 | | | 85.15 239 | 83.99 238 | 88.65 245 | 92.47 212 | 78.40 237 | 79.68 345 | 92.76 243 | 74.90 296 | 81.41 259 | 89.59 271 | 69.85 222 | 95.51 284 | 79.92 197 | 95.29 93 | 92.03 286 |
|
1314 | | | 87.51 180 | 86.57 179 | 90.34 179 | 92.42 213 | 79.74 185 | 92.63 234 | 95.35 162 | 78.35 265 | 80.14 275 | 91.62 216 | 74.05 166 | 97.15 203 | 81.05 172 | 93.53 121 | 94.12 200 |
|
pcd1.5k->3k | | | 37.02 337 | 38.84 338 | 31.53 349 | 92.33 214 | 0.00 369 | 0.00 360 | 96.13 96 | 0.00 364 | 0.00 366 | 0.00 366 | 72.70 184 | 0.00 366 | 0.00 363 | 88.43 201 | 94.60 178 |
|
PEN-MVS | | | 86.80 199 | 86.27 186 | 88.40 259 | 92.32 215 | 75.71 280 | 95.18 78 | 96.38 81 | 87.97 71 | 82.82 240 | 93.15 157 | 73.39 177 | 95.92 269 | 76.15 240 | 79.03 304 | 93.59 241 |
|
Patchmatch-test1 | | | 85.81 224 | 84.71 224 | 89.12 236 | 92.15 216 | 76.60 272 | 91.12 270 | 91.69 270 | 83.53 172 | 85.50 173 | 88.56 286 | 66.79 265 | 95.00 305 | 72.69 264 | 90.35 163 | 95.76 132 |
|
XXY-MVS | | | 87.65 165 | 86.85 159 | 90.03 198 | 92.14 217 | 80.60 166 | 93.76 187 | 95.23 171 | 82.94 195 | 84.60 203 | 94.02 127 | 74.27 160 | 95.49 287 | 81.04 173 | 83.68 244 | 94.01 209 |
|
IB-MVS | | 80.51 15 | 85.24 238 | 83.26 257 | 91.19 138 | 92.13 218 | 79.86 182 | 91.75 256 | 91.29 284 | 83.28 180 | 80.66 268 | 88.49 287 | 61.28 298 | 98.46 93 | 80.99 176 | 79.46 302 | 95.25 146 |
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 |
cascas | | | 86.43 210 | 84.98 215 | 90.80 155 | 92.10 219 | 80.92 157 | 90.24 275 | 95.91 113 | 73.10 310 | 83.57 231 | 88.39 288 | 65.15 279 | 97.46 161 | 84.90 120 | 91.43 145 | 94.03 207 |
|
Fast-Effi-MVS+-dtu | | | 87.44 182 | 86.72 165 | 89.63 216 | 92.04 220 | 77.68 258 | 94.03 172 | 93.94 224 | 85.81 118 | 82.42 243 | 91.32 233 | 70.33 217 | 97.06 211 | 80.33 189 | 90.23 166 | 94.14 199 |
|
PS-MVSNAJss | | | 89.97 98 | 89.62 92 | 91.02 147 | 91.90 221 | 80.85 159 | 95.26 74 | 95.98 107 | 86.26 112 | 86.21 150 | 94.29 118 | 79.70 93 | 97.65 149 | 88.87 75 | 88.10 205 | 94.57 181 |
|
ITE_SJBPF | | | | | 88.24 264 | 91.88 222 | 77.05 269 | | 92.92 239 | 85.54 126 | 80.13 276 | 93.30 151 | 57.29 317 | 96.20 259 | 72.46 265 | 84.71 234 | 91.49 296 |
|
EI-MVSNet | | | 89.10 122 | 88.86 112 | 89.80 208 | 91.84 223 | 78.30 239 | 93.70 194 | 95.01 181 | 85.73 121 | 87.15 131 | 95.28 87 | 79.87 90 | 97.21 201 | 83.81 137 | 87.36 214 | 93.88 214 |
|
CVMVSNet | | | 84.69 256 | 84.79 223 | 84.37 314 | 91.84 223 | 64.92 337 | 93.70 194 | 91.47 280 | 66.19 339 | 86.16 152 | 95.28 87 | 67.18 263 | 93.33 320 | 80.89 178 | 90.42 162 | 94.88 164 |
|
MVS-HIRNet | | | 73.70 314 | 72.20 314 | 78.18 327 | 91.81 225 | 56.42 349 | 82.94 339 | 82.58 350 | 55.24 348 | 68.88 334 | 66.48 349 | 55.32 323 | 95.13 301 | 58.12 334 | 88.42 202 | 83.01 343 |
|
PatchmatchNet | | | 85.85 220 | 84.70 225 | 89.29 232 | 91.76 226 | 75.54 281 | 88.49 301 | 91.30 283 | 81.63 231 | 85.05 191 | 88.70 283 | 71.71 193 | 96.24 258 | 74.61 253 | 89.05 192 | 96.08 118 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
TransMVSNet (Re) | | | 84.43 259 | 83.06 260 | 88.54 255 | 91.72 227 | 78.44 235 | 95.18 78 | 92.82 242 | 82.73 201 | 79.67 279 | 92.12 195 | 73.49 174 | 95.96 268 | 71.10 273 | 68.73 339 | 91.21 301 |
|
semantic-postprocess | | | | | 88.18 266 | 91.71 228 | 76.87 271 | | 92.65 247 | 85.40 129 | 81.44 258 | 90.54 255 | 66.21 271 | 95.00 305 | 81.04 173 | 81.05 279 | 92.66 271 |
|
TinyColmap | | | 79.76 300 | 77.69 300 | 85.97 302 | 91.71 228 | 73.12 296 | 89.55 284 | 90.36 305 | 75.03 293 | 72.03 329 | 90.19 262 | 46.22 342 | 96.19 260 | 63.11 323 | 81.03 280 | 88.59 333 |
|
MDTV_nov1_ep13 | | | | 83.56 249 | | 91.69 230 | 69.93 324 | 87.75 309 | 91.54 277 | 78.60 262 | 84.86 200 | 88.90 279 | 69.54 225 | 96.03 264 | 70.25 275 | 88.93 193 | |
|
DTE-MVSNet | | | 86.11 213 | 85.48 206 | 87.98 269 | 91.65 231 | 74.92 283 | 94.93 95 | 95.75 126 | 87.36 86 | 82.26 245 | 93.04 162 | 72.85 182 | 95.82 274 | 74.04 256 | 77.46 310 | 93.20 253 |
|
PatchFormer-LS_test | | | 86.02 216 | 85.13 212 | 88.70 244 | 91.52 232 | 74.12 289 | 91.19 269 | 92.09 257 | 82.71 202 | 84.30 216 | 87.24 304 | 70.87 206 | 96.98 216 | 81.04 173 | 85.17 231 | 95.00 151 |
|
MIMVSNet | | | 82.59 275 | 80.53 278 | 88.76 242 | 91.51 233 | 78.32 238 | 86.57 316 | 90.13 309 | 79.32 252 | 80.70 267 | 88.69 284 | 52.98 330 | 93.07 325 | 66.03 313 | 88.86 194 | 94.90 163 |
|
tpmp4_e23 | | | 83.87 265 | 82.33 266 | 88.48 256 | 91.46 234 | 72.82 299 | 89.82 282 | 91.57 276 | 73.02 312 | 81.86 255 | 89.05 276 | 66.20 272 | 96.97 217 | 71.57 268 | 86.39 221 | 95.66 135 |
|
pm-mvs1 | | | 86.61 204 | 85.54 202 | 89.82 205 | 91.44 235 | 80.18 171 | 95.28 73 | 94.85 191 | 83.84 161 | 81.66 256 | 92.62 178 | 72.45 191 | 96.48 247 | 79.67 203 | 78.06 306 | 92.82 268 |
|
Baseline_NR-MVSNet | | | 87.07 194 | 86.63 177 | 88.40 259 | 91.44 235 | 77.87 251 | 94.23 149 | 92.57 248 | 84.12 157 | 85.74 161 | 92.08 199 | 77.25 115 | 96.04 263 | 82.29 157 | 79.94 298 | 91.30 300 |
|
IterMVS | | | 84.88 247 | 83.98 239 | 87.60 275 | 91.44 235 | 76.03 278 | 90.18 277 | 92.41 250 | 83.24 181 | 81.06 264 | 90.42 260 | 66.60 266 | 94.28 311 | 79.46 205 | 80.98 284 | 92.48 275 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
DWT-MVSNet_test | | | 84.95 245 | 83.68 246 | 88.77 241 | 91.43 238 | 73.75 292 | 91.74 257 | 90.98 294 | 80.66 242 | 83.84 222 | 87.36 302 | 62.44 290 | 97.11 207 | 78.84 214 | 85.81 224 | 95.46 140 |
|
MS-PatchMatch | | | 85.05 241 | 84.16 235 | 87.73 273 | 91.42 239 | 78.51 233 | 91.25 268 | 93.53 231 | 77.50 271 | 80.15 274 | 91.58 217 | 61.99 293 | 95.51 284 | 75.69 242 | 94.35 110 | 89.16 327 |
|
v16 | | | 84.96 244 | 83.74 243 | 88.62 247 | 91.40 240 | 79.48 190 | 93.83 181 | 94.04 215 | 83.03 190 | 76.54 300 | 86.59 308 | 76.11 129 | 95.42 290 | 80.33 189 | 71.80 323 | 90.95 308 |
|
tpm2 | | | 84.08 261 | 82.94 261 | 87.48 280 | 91.39 241 | 71.27 312 | 89.23 292 | 90.37 304 | 71.95 320 | 84.64 202 | 89.33 274 | 67.30 260 | 96.55 244 | 75.17 247 | 87.09 218 | 94.63 175 |
|
v1neww | | | 87.98 150 | 87.25 146 | 90.16 183 | 91.38 242 | 79.41 196 | 94.37 140 | 95.28 163 | 84.48 148 | 85.77 157 | 91.53 221 | 76.12 126 | 97.45 163 | 84.45 127 | 81.89 264 | 93.61 239 |
|
v7new | | | 87.98 150 | 87.25 146 | 90.16 183 | 91.38 242 | 79.41 196 | 94.37 140 | 95.28 163 | 84.48 148 | 85.77 157 | 91.53 221 | 76.12 126 | 97.45 163 | 84.45 127 | 81.89 264 | 93.61 239 |
|
v8 | | | 87.50 181 | 86.71 166 | 89.89 203 | 91.37 244 | 79.40 200 | 94.50 125 | 95.38 158 | 84.81 141 | 83.60 230 | 91.33 231 | 76.05 130 | 97.42 174 | 82.84 146 | 80.51 292 | 92.84 266 |
|
v18 | | | 84.97 243 | 83.76 241 | 88.60 249 | 91.36 245 | 79.41 196 | 93.82 183 | 94.04 215 | 83.00 193 | 76.61 299 | 86.60 307 | 76.19 124 | 95.43 289 | 80.39 186 | 71.79 324 | 90.96 306 |
|
v17 | | | 84.93 246 | 83.70 245 | 88.62 247 | 91.36 245 | 79.48 190 | 93.83 181 | 94.03 217 | 83.04 189 | 76.51 301 | 86.57 309 | 76.05 130 | 95.42 290 | 80.31 191 | 71.65 325 | 90.96 306 |
|
v6 | | | 87.98 150 | 87.25 146 | 90.16 183 | 91.36 245 | 79.39 201 | 94.37 140 | 95.27 166 | 84.48 148 | 85.78 156 | 91.51 223 | 76.15 125 | 97.46 161 | 84.46 126 | 81.88 266 | 93.62 238 |
|
ADS-MVSNet2 | | | 81.66 283 | 79.71 289 | 87.50 278 | 91.35 248 | 74.19 287 | 83.33 336 | 88.48 333 | 72.90 313 | 82.24 246 | 85.77 319 | 64.98 280 | 93.20 322 | 64.57 319 | 83.74 242 | 95.12 147 |
|
ADS-MVSNet | | | 81.56 285 | 79.78 287 | 86.90 293 | 91.35 248 | 71.82 309 | 83.33 336 | 89.16 328 | 72.90 313 | 82.24 246 | 85.77 319 | 64.98 280 | 93.76 315 | 64.57 319 | 83.74 242 | 95.12 147 |
|
V9 | | | 84.77 251 | 83.50 252 | 88.58 250 | 91.33 250 | 79.46 192 | 93.75 188 | 94.00 221 | 83.07 185 | 76.07 308 | 86.43 310 | 75.97 135 | 95.37 293 | 79.91 198 | 70.93 331 | 90.91 310 |
|
GA-MVS | | | 86.61 204 | 85.27 211 | 90.66 156 | 91.33 250 | 78.71 221 | 90.40 273 | 93.81 229 | 85.34 130 | 85.12 190 | 89.57 272 | 61.25 299 | 97.11 207 | 80.99 176 | 89.59 177 | 96.15 112 |
|
v12 | | | 84.74 252 | 83.46 253 | 88.58 250 | 91.32 252 | 79.50 187 | 93.75 188 | 94.01 218 | 83.06 186 | 75.98 310 | 86.41 314 | 75.82 141 | 95.36 296 | 79.87 199 | 70.89 332 | 90.89 312 |
|
v11 | | | 84.67 257 | 83.41 256 | 88.44 258 | 91.32 252 | 79.13 215 | 93.69 197 | 93.99 223 | 82.81 199 | 76.20 304 | 86.24 317 | 75.48 146 | 95.35 297 | 79.53 204 | 71.48 327 | 90.85 314 |
|
V14 | | | 84.79 249 | 83.52 251 | 88.57 253 | 91.32 252 | 79.43 195 | 93.72 192 | 94.01 218 | 83.06 186 | 76.22 303 | 86.43 310 | 76.01 134 | 95.37 293 | 79.96 195 | 70.99 329 | 90.91 310 |
|
v13 | | | 84.72 254 | 83.44 255 | 88.58 250 | 91.31 255 | 79.52 186 | 93.77 186 | 94.00 221 | 83.03 190 | 75.85 311 | 86.38 315 | 75.84 140 | 95.35 297 | 79.83 200 | 70.95 330 | 90.87 313 |
|
v15 | | | 84.79 249 | 83.53 250 | 88.57 253 | 91.30 256 | 79.41 196 | 93.70 194 | 94.01 218 | 83.06 186 | 76.27 302 | 86.42 313 | 76.03 133 | 95.38 292 | 80.01 193 | 71.00 328 | 90.92 309 |
|
v1141 | | | 87.84 156 | 87.09 150 | 90.11 194 | 91.23 257 | 79.25 210 | 94.08 165 | 95.24 168 | 84.44 152 | 85.69 164 | 91.31 234 | 75.91 138 | 97.44 170 | 84.17 132 | 81.74 271 | 93.63 237 |
|
divwei89l23v2f112 | | | 87.84 156 | 87.09 150 | 90.10 196 | 91.23 257 | 79.24 212 | 94.09 163 | 95.24 168 | 84.44 152 | 85.70 162 | 91.31 234 | 75.91 138 | 97.44 170 | 84.17 132 | 81.73 273 | 93.64 235 |
|
v1 | | | 87.85 155 | 87.10 149 | 90.11 194 | 91.21 259 | 79.24 212 | 94.09 163 | 95.24 168 | 84.44 152 | 85.70 162 | 91.31 234 | 75.96 136 | 97.45 163 | 84.18 131 | 81.73 273 | 93.64 235 |
|
v7 | | | 87.75 161 | 86.96 156 | 90.12 189 | 91.20 260 | 79.50 187 | 94.28 146 | 95.46 148 | 83.45 174 | 85.75 159 | 91.56 220 | 75.13 150 | 97.43 172 | 83.60 139 | 82.18 259 | 93.42 248 |
|
XVG-ACMP-BASELINE | | | 86.00 217 | 84.84 222 | 89.45 223 | 91.20 260 | 78.00 246 | 91.70 259 | 95.55 139 | 85.05 137 | 82.97 238 | 92.25 192 | 54.49 326 | 97.48 159 | 82.93 144 | 87.45 213 | 92.89 264 |
|
v10 | | | 87.25 188 | 86.38 181 | 89.85 204 | 91.19 262 | 79.50 187 | 94.48 126 | 95.45 152 | 83.79 164 | 83.62 229 | 91.19 239 | 75.13 150 | 97.42 174 | 81.94 163 | 80.60 287 | 92.63 272 |
|
FMVSNet5 | | | 81.52 286 | 79.60 290 | 87.27 282 | 91.17 263 | 77.95 247 | 91.49 263 | 92.26 253 | 76.87 277 | 76.16 305 | 87.91 297 | 51.67 331 | 92.34 327 | 67.74 300 | 81.16 276 | 91.52 295 |
|
USDC | | | 82.76 272 | 81.26 273 | 87.26 283 | 91.17 263 | 74.55 284 | 89.27 290 | 93.39 234 | 78.26 267 | 75.30 313 | 92.08 199 | 54.43 327 | 96.63 238 | 71.64 267 | 85.79 226 | 90.61 316 |
|
CostFormer | | | 85.77 225 | 84.94 218 | 88.26 263 | 91.16 265 | 72.58 306 | 89.47 288 | 91.04 293 | 76.26 283 | 86.45 145 | 89.97 266 | 70.74 209 | 96.86 226 | 82.35 155 | 87.07 219 | 95.34 145 |
|
tpm cat1 | | | 81.96 278 | 80.27 281 | 87.01 290 | 91.09 266 | 71.02 316 | 87.38 312 | 91.53 278 | 66.25 338 | 80.17 273 | 86.35 316 | 68.22 259 | 96.15 261 | 69.16 289 | 82.29 257 | 93.86 217 |
|
tpmvs | | | 83.35 270 | 82.07 267 | 87.20 288 | 91.07 267 | 71.00 317 | 88.31 304 | 91.70 269 | 78.91 255 | 80.49 271 | 87.18 305 | 69.30 230 | 97.08 209 | 68.12 299 | 83.56 246 | 93.51 246 |
|
v1144 | | | 87.61 177 | 86.79 163 | 90.06 197 | 91.01 268 | 79.34 204 | 93.95 177 | 95.42 157 | 83.36 178 | 85.66 166 | 91.31 234 | 74.98 154 | 97.42 174 | 83.37 140 | 82.06 260 | 93.42 248 |
|
v2v482 | | | 87.84 156 | 87.06 153 | 90.17 182 | 90.99 269 | 79.23 214 | 94.00 175 | 95.13 175 | 84.87 139 | 85.53 170 | 92.07 201 | 74.45 158 | 97.45 163 | 84.71 123 | 81.75 270 | 93.85 218 |
|
SixPastTwentyTwo | | | 83.91 263 | 82.90 262 | 86.92 292 | 90.99 269 | 70.67 319 | 93.48 202 | 91.99 262 | 85.54 126 | 77.62 293 | 92.11 197 | 60.59 304 | 96.87 225 | 76.05 241 | 77.75 307 | 93.20 253 |
|
test-LLR | | | 85.87 219 | 85.41 207 | 87.25 284 | 90.95 271 | 71.67 310 | 89.55 284 | 89.88 316 | 83.41 175 | 84.54 205 | 87.95 295 | 67.25 261 | 95.11 302 | 81.82 165 | 93.37 127 | 94.97 152 |
|
test-mter | | | 84.54 258 | 83.64 248 | 87.25 284 | 90.95 271 | 71.67 310 | 89.55 284 | 89.88 316 | 79.17 253 | 84.54 205 | 87.95 295 | 55.56 321 | 95.11 302 | 81.82 165 | 93.37 127 | 94.97 152 |
|
v148 | | | 87.04 195 | 86.32 184 | 89.21 234 | 90.94 273 | 77.26 267 | 93.71 193 | 94.43 203 | 84.84 140 | 84.36 213 | 90.80 249 | 76.04 132 | 97.05 212 | 82.12 159 | 79.60 301 | 93.31 250 |
|
mvs_tets | | | 88.06 149 | 87.28 144 | 90.38 176 | 90.94 273 | 79.88 181 | 95.22 76 | 95.66 132 | 85.10 136 | 84.21 218 | 93.94 132 | 63.53 286 | 97.40 181 | 88.50 78 | 88.40 203 | 93.87 215 |
|
MVP-Stereo | | | 85.97 218 | 84.86 221 | 89.32 231 | 90.92 275 | 82.19 126 | 92.11 251 | 94.19 210 | 78.76 260 | 78.77 285 | 91.63 215 | 68.38 257 | 96.56 242 | 75.01 250 | 93.95 113 | 89.20 326 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
Patchmatch-test | | | 81.37 288 | 79.30 292 | 87.58 276 | 90.92 275 | 74.16 288 | 80.99 342 | 87.68 339 | 70.52 328 | 76.63 298 | 88.81 280 | 71.21 201 | 92.76 326 | 60.01 333 | 86.93 220 | 95.83 129 |
|
jajsoiax | | | 88.24 142 | 87.50 137 | 90.48 169 | 90.89 277 | 80.14 173 | 95.31 63 | 95.65 134 | 84.97 138 | 84.24 217 | 94.02 127 | 65.31 278 | 97.42 174 | 88.56 77 | 88.52 198 | 93.89 212 |
|
tpmrst | | | 85.35 235 | 84.99 214 | 86.43 298 | 90.88 278 | 67.88 330 | 88.71 298 | 91.43 281 | 80.13 245 | 86.08 153 | 88.80 281 | 73.05 180 | 96.02 265 | 82.48 152 | 83.40 250 | 95.40 142 |
|
gg-mvs-nofinetune | | | 81.77 281 | 79.37 291 | 88.99 239 | 90.85 279 | 77.73 257 | 86.29 317 | 79.63 356 | 74.88 297 | 83.19 237 | 69.05 348 | 60.34 305 | 96.11 262 | 75.46 244 | 94.64 101 | 93.11 258 |
|
OurMVSNet-221017-0 | | | 85.35 235 | 84.64 227 | 87.49 279 | 90.77 280 | 72.59 305 | 94.01 174 | 94.40 204 | 84.72 144 | 79.62 281 | 93.17 156 | 61.91 294 | 96.72 234 | 81.99 162 | 81.16 276 | 93.16 255 |
|
v1192 | | | 87.25 188 | 86.33 183 | 90.00 201 | 90.76 281 | 79.04 216 | 93.80 184 | 95.48 147 | 82.57 204 | 85.48 174 | 91.18 240 | 73.38 178 | 97.42 174 | 82.30 156 | 82.06 260 | 93.53 243 |
|
test_djsdf | | | 89.03 125 | 88.64 114 | 90.21 181 | 90.74 282 | 79.28 208 | 95.96 40 | 95.90 114 | 84.66 145 | 85.33 188 | 92.94 168 | 74.02 167 | 97.30 189 | 89.64 69 | 88.53 197 | 94.05 206 |
|
v7n | | | 86.81 198 | 85.76 200 | 89.95 202 | 90.72 283 | 79.25 210 | 95.07 85 | 95.92 111 | 84.45 151 | 82.29 244 | 90.86 248 | 72.60 187 | 97.53 156 | 79.42 209 | 80.52 291 | 93.08 260 |
|
PVSNet_0 | | 73.20 20 | 77.22 307 | 74.83 310 | 84.37 314 | 90.70 284 | 71.10 315 | 83.09 338 | 89.67 319 | 72.81 315 | 73.93 320 | 83.13 329 | 60.79 303 | 93.70 316 | 68.54 292 | 50.84 350 | 88.30 337 |
|
DI_MVS_plusplus_test | | | 88.15 145 | 86.82 160 | 92.14 108 | 90.67 285 | 81.07 151 | 93.01 223 | 94.59 199 | 83.83 163 | 77.78 290 | 90.63 252 | 68.51 247 | 98.16 111 | 88.02 86 | 94.37 109 | 97.17 85 |
|
v144192 | | | 87.19 192 | 86.35 182 | 89.74 209 | 90.64 286 | 78.24 242 | 93.92 178 | 95.43 155 | 81.93 216 | 85.51 172 | 91.05 246 | 74.21 163 | 97.45 163 | 82.86 145 | 81.56 275 | 93.53 243 |
|
V42 | | | 87.68 163 | 86.86 158 | 90.15 187 | 90.58 287 | 80.14 173 | 94.24 148 | 95.28 163 | 83.66 166 | 85.67 165 | 91.33 231 | 74.73 156 | 97.41 179 | 84.43 129 | 81.83 268 | 92.89 264 |
|
CR-MVSNet | | | 85.35 235 | 83.76 241 | 90.12 189 | 90.58 287 | 79.34 204 | 85.24 325 | 91.96 265 | 78.27 266 | 85.55 168 | 87.87 298 | 71.03 204 | 95.61 279 | 73.96 258 | 89.36 180 | 95.40 142 |
|
RPMNet | | | 83.18 271 | 80.87 277 | 90.12 189 | 90.58 287 | 79.34 204 | 85.24 325 | 90.78 300 | 71.44 322 | 85.55 168 | 82.97 330 | 70.87 206 | 95.61 279 | 61.01 329 | 89.36 180 | 95.40 142 |
|
test_normal | | | 88.13 146 | 86.78 164 | 92.18 106 | 90.55 290 | 81.19 149 | 92.74 232 | 94.64 198 | 83.84 161 | 77.49 294 | 90.51 258 | 68.49 248 | 98.16 111 | 88.22 81 | 94.55 103 | 97.21 83 |
|
v1921920 | | | 86.97 196 | 86.06 193 | 89.69 214 | 90.53 291 | 78.11 245 | 93.80 184 | 95.43 155 | 81.90 218 | 85.33 188 | 91.05 246 | 72.66 185 | 97.41 179 | 82.05 161 | 81.80 269 | 93.53 243 |
|
v1240 | | | 86.78 200 | 85.85 198 | 89.56 217 | 90.45 292 | 77.79 253 | 93.61 198 | 95.37 160 | 81.65 229 | 85.43 179 | 91.15 242 | 71.50 199 | 97.43 172 | 81.47 170 | 82.05 262 | 93.47 247 |
|
tpm | | | 84.73 253 | 84.02 237 | 86.87 295 | 90.33 293 | 68.90 327 | 89.06 294 | 89.94 314 | 80.85 241 | 85.75 159 | 89.86 268 | 68.54 246 | 95.97 267 | 77.76 223 | 84.05 240 | 95.75 133 |
|
EG-PatchMatch MVS | | | 82.37 277 | 80.34 280 | 88.46 257 | 90.27 294 | 79.35 203 | 92.80 231 | 94.33 207 | 77.14 276 | 73.26 324 | 90.18 263 | 47.47 340 | 96.72 234 | 70.25 275 | 87.32 216 | 89.30 324 |
|
v748 | | | 86.27 211 | 85.28 210 | 89.25 233 | 90.26 295 | 77.58 266 | 94.89 97 | 95.50 146 | 84.28 155 | 81.41 259 | 90.46 259 | 72.57 188 | 97.32 188 | 79.81 201 | 78.36 305 | 92.84 266 |
|
EPNet_dtu | | | 86.49 209 | 85.94 197 | 88.14 267 | 90.24 296 | 72.82 299 | 94.11 160 | 92.20 254 | 86.66 106 | 79.42 282 | 92.36 185 | 73.52 173 | 95.81 275 | 71.26 269 | 93.66 118 | 95.80 131 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
EPMVS | | | 83.90 264 | 82.70 265 | 87.51 277 | 90.23 297 | 72.67 302 | 88.62 300 | 81.96 352 | 81.37 237 | 85.01 192 | 88.34 289 | 66.31 270 | 94.45 308 | 75.30 246 | 87.12 217 | 95.43 141 |
|
EPNet | | | 91.79 62 | 91.02 70 | 94.10 46 | 90.10 298 | 85.25 55 | 96.03 37 | 92.05 259 | 92.83 1 | 87.39 130 | 95.78 76 | 79.39 98 | 99.01 55 | 88.13 84 | 97.48 59 | 98.05 48 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
PatchT | | | 82.68 274 | 81.27 272 | 86.89 294 | 90.09 299 | 70.94 318 | 84.06 332 | 90.15 308 | 74.91 295 | 85.63 167 | 83.57 327 | 69.37 226 | 94.87 307 | 65.19 315 | 88.50 199 | 94.84 165 |
|
Patchmtry | | | 82.71 273 | 80.93 276 | 88.06 268 | 90.05 300 | 76.37 275 | 84.74 327 | 91.96 265 | 72.28 318 | 81.32 261 | 87.87 298 | 71.03 204 | 95.50 286 | 68.97 290 | 80.15 294 | 92.32 282 |
|
pmmvs4 | | | 85.43 233 | 83.86 240 | 90.16 183 | 90.02 301 | 82.97 108 | 90.27 274 | 92.67 246 | 75.93 286 | 80.73 266 | 91.74 211 | 71.05 203 | 95.73 278 | 78.85 213 | 83.46 248 | 91.78 289 |
|
TESTMET0.1,1 | | | 83.74 266 | 82.85 263 | 86.42 299 | 89.96 302 | 71.21 314 | 89.55 284 | 87.88 336 | 77.41 272 | 83.37 235 | 87.31 303 | 56.71 318 | 93.65 317 | 80.62 182 | 92.85 137 | 94.40 192 |
|
dp | | | 81.47 287 | 80.23 282 | 85.17 309 | 89.92 303 | 65.49 336 | 86.74 314 | 90.10 310 | 76.30 282 | 81.10 262 | 87.12 306 | 62.81 288 | 95.92 269 | 68.13 298 | 79.88 299 | 94.09 203 |
|
K. test v3 | | | 81.59 284 | 80.15 284 | 85.91 303 | 89.89 304 | 69.42 326 | 92.57 237 | 87.71 338 | 85.56 125 | 73.44 322 | 89.71 270 | 55.58 320 | 95.52 283 | 77.17 230 | 69.76 335 | 92.78 269 |
|
MDA-MVSNet-bldmvs | | | 78.85 305 | 76.31 306 | 86.46 297 | 89.76 305 | 73.88 291 | 88.79 297 | 90.42 303 | 79.16 254 | 59.18 346 | 88.33 290 | 60.20 306 | 94.04 313 | 62.00 326 | 68.96 337 | 91.48 297 |
|
GG-mvs-BLEND | | | | | 87.94 271 | 89.73 306 | 77.91 248 | 87.80 307 | 78.23 358 | | 80.58 269 | 83.86 325 | 59.88 309 | 95.33 299 | 71.20 270 | 92.22 142 | 90.60 318 |
|
gm-plane-assit | | | | | | 89.60 307 | 68.00 329 | | | 77.28 275 | | 88.99 277 | | 97.57 153 | 79.44 207 | | |
|
v52 | | | 86.50 207 | 85.53 205 | 89.39 225 | 89.17 308 | 78.99 217 | 94.72 112 | 95.54 141 | 83.59 167 | 82.10 248 | 90.60 254 | 71.59 196 | 97.45 163 | 82.52 150 | 79.99 297 | 91.73 291 |
|
anonymousdsp | | | 87.84 156 | 87.09 150 | 90.12 189 | 89.13 309 | 80.54 167 | 94.67 117 | 95.55 139 | 82.05 211 | 83.82 223 | 92.12 195 | 71.47 200 | 97.15 203 | 87.15 98 | 87.80 210 | 92.67 270 |
|
V4 | | | 86.50 207 | 85.54 202 | 89.39 225 | 89.13 309 | 78.99 217 | 94.73 109 | 95.54 141 | 83.59 167 | 82.10 248 | 90.61 253 | 71.60 195 | 97.45 163 | 82.52 150 | 80.01 296 | 91.74 290 |
|
N_pmnet | | | 68.89 320 | 68.44 321 | 70.23 336 | 89.07 311 | 28.79 365 | 88.06 305 | 19.50 367 | 69.47 331 | 71.86 330 | 84.93 322 | 61.24 300 | 91.75 332 | 54.70 337 | 77.15 311 | 90.15 320 |
|
pmmvs5 | | | 84.21 260 | 82.84 264 | 88.34 261 | 88.95 312 | 76.94 270 | 92.41 241 | 91.91 267 | 75.63 288 | 80.28 272 | 91.18 240 | 64.59 282 | 95.57 281 | 77.09 232 | 83.47 247 | 92.53 274 |
|
PMMVS | | | 85.71 231 | 84.96 217 | 87.95 270 | 88.90 313 | 77.09 268 | 88.68 299 | 90.06 311 | 72.32 317 | 86.47 142 | 90.76 250 | 72.15 192 | 94.40 309 | 81.78 167 | 93.49 122 | 92.36 280 |
|
JIA-IIPM | | | 81.04 291 | 78.98 297 | 87.25 284 | 88.64 314 | 73.48 294 | 81.75 341 | 89.61 320 | 73.19 309 | 82.05 250 | 73.71 345 | 66.07 276 | 95.87 272 | 71.18 272 | 84.60 235 | 92.41 278 |
|
Gipuma | | | 57.99 328 | 54.91 329 | 67.24 341 | 88.51 315 | 65.59 335 | 52.21 358 | 90.33 306 | 43.58 354 | 42.84 354 | 51.18 356 | 20.29 360 | 85.07 350 | 34.77 355 | 70.45 333 | 51.05 356 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
EU-MVSNet | | | 81.32 289 | 80.95 275 | 82.42 321 | 88.50 316 | 63.67 338 | 93.32 206 | 91.33 282 | 64.02 343 | 80.57 270 | 92.83 171 | 61.21 301 | 92.27 328 | 76.34 237 | 80.38 293 | 91.32 299 |
|
our_test_3 | | | 81.93 279 | 80.46 279 | 86.33 300 | 88.46 317 | 73.48 294 | 88.46 302 | 91.11 285 | 76.46 278 | 76.69 297 | 88.25 291 | 66.89 264 | 94.36 310 | 68.75 291 | 79.08 303 | 91.14 303 |
|
ppachtmachnet_test | | | 81.84 280 | 80.07 285 | 87.15 289 | 88.46 317 | 74.43 285 | 89.04 295 | 92.16 255 | 75.33 290 | 77.75 291 | 88.99 277 | 66.20 272 | 95.37 293 | 65.12 317 | 77.60 308 | 91.65 293 |
|
lessismore_v0 | | | | | 86.04 301 | 88.46 317 | 68.78 328 | | 80.59 354 | | 73.01 325 | 90.11 264 | 55.39 322 | 96.43 251 | 75.06 249 | 65.06 341 | 92.90 263 |
|
test0.0.03 1 | | | 82.41 276 | 81.69 269 | 84.59 312 | 88.23 320 | 72.89 298 | 90.24 275 | 87.83 337 | 83.41 175 | 79.86 278 | 89.78 269 | 67.25 261 | 88.99 338 | 65.18 316 | 83.42 249 | 91.90 288 |
|
MDA-MVSNet_test_wron | | | 79.21 304 | 77.19 304 | 85.29 307 | 88.22 321 | 72.77 301 | 85.87 320 | 90.06 311 | 74.34 300 | 62.62 345 | 87.56 301 | 66.14 274 | 91.99 330 | 66.90 305 | 73.01 318 | 91.10 305 |
|
YYNet1 | | | 79.22 303 | 77.20 303 | 85.28 308 | 88.20 322 | 72.66 303 | 85.87 320 | 90.05 313 | 74.33 301 | 62.70 344 | 87.61 300 | 66.09 275 | 92.03 329 | 66.94 302 | 72.97 319 | 91.15 302 |
|
Test4 | | | 85.75 226 | 83.72 244 | 91.83 121 | 88.08 323 | 81.03 153 | 92.48 239 | 95.54 141 | 83.38 177 | 73.40 323 | 88.57 285 | 50.99 333 | 97.37 186 | 86.61 108 | 94.47 106 | 97.09 89 |
|
pmmvs6 | | | 83.42 267 | 81.60 270 | 88.87 240 | 88.01 324 | 77.87 251 | 94.96 92 | 94.24 209 | 74.67 298 | 78.80 284 | 91.09 245 | 60.17 307 | 96.49 246 | 77.06 233 | 75.40 315 | 92.23 284 |
|
testgi | | | 80.94 294 | 80.20 283 | 83.18 318 | 87.96 325 | 66.29 333 | 91.28 266 | 90.70 302 | 83.70 165 | 78.12 287 | 92.84 170 | 51.37 332 | 90.82 335 | 63.34 322 | 82.46 256 | 92.43 277 |
|
LP | | | 75.51 311 | 72.15 315 | 85.61 305 | 87.86 326 | 73.93 290 | 80.20 344 | 88.43 334 | 67.39 334 | 70.05 332 | 80.56 338 | 58.18 315 | 93.18 323 | 46.28 348 | 70.36 334 | 89.71 323 |
|
Anonymous20231206 | | | 81.03 292 | 79.77 288 | 84.82 311 | 87.85 327 | 70.26 322 | 91.42 264 | 92.08 258 | 73.67 305 | 77.75 291 | 89.25 275 | 62.43 291 | 93.08 324 | 61.50 328 | 82.00 263 | 91.12 304 |
|
OpenMVS_ROB | | 74.94 19 | 79.51 301 | 77.03 305 | 86.93 291 | 87.00 328 | 76.23 277 | 92.33 244 | 90.74 301 | 68.93 332 | 74.52 317 | 88.23 292 | 49.58 335 | 96.62 239 | 57.64 335 | 84.29 237 | 87.94 338 |
|
LF4IMVS | | | 80.37 296 | 79.07 296 | 84.27 316 | 86.64 329 | 69.87 325 | 89.39 289 | 91.05 292 | 76.38 280 | 74.97 315 | 90.00 265 | 47.85 339 | 94.25 312 | 74.55 254 | 80.82 286 | 88.69 332 |
|
MIMVSNet1 | | | 79.38 302 | 77.28 302 | 85.69 304 | 86.35 330 | 73.67 293 | 91.61 262 | 92.75 244 | 78.11 270 | 72.64 327 | 88.12 293 | 48.16 338 | 91.97 331 | 60.32 330 | 77.49 309 | 91.43 298 |
|
test20.03 | | | 79.95 298 | 79.08 295 | 82.55 320 | 85.79 331 | 67.74 331 | 91.09 271 | 91.08 290 | 81.23 238 | 74.48 318 | 89.96 267 | 61.63 295 | 90.15 336 | 60.08 331 | 76.38 312 | 89.76 321 |
|
Patchmatch-RL test | | | 81.67 282 | 79.96 286 | 86.81 296 | 85.42 332 | 71.23 313 | 82.17 340 | 87.50 341 | 78.47 263 | 77.19 296 | 82.50 331 | 70.81 208 | 93.48 318 | 82.66 149 | 72.89 320 | 95.71 134 |
|
UnsupCasMVSNet_eth | | | 80.07 297 | 78.27 299 | 85.46 306 | 85.24 333 | 72.63 304 | 88.45 303 | 94.87 190 | 82.99 194 | 71.64 331 | 88.07 294 | 56.34 319 | 91.75 332 | 73.48 261 | 63.36 345 | 92.01 287 |
|
testing_2 | | | 83.40 269 | 81.02 274 | 90.56 159 | 85.06 334 | 80.51 168 | 91.37 265 | 95.57 137 | 82.92 196 | 67.06 338 | 85.54 321 | 49.47 336 | 97.24 197 | 86.74 103 | 85.44 227 | 93.93 210 |
|
pmmvs-eth3d | | | 80.97 293 | 78.72 298 | 87.74 272 | 84.99 335 | 79.97 180 | 90.11 278 | 91.65 271 | 75.36 289 | 73.51 321 | 86.03 318 | 59.45 310 | 93.96 314 | 75.17 247 | 72.21 321 | 89.29 325 |
|
testpf | | | 71.41 318 | 72.11 316 | 69.30 338 | 84.53 336 | 59.79 342 | 62.74 355 | 83.14 349 | 71.11 325 | 68.83 336 | 81.57 336 | 46.70 341 | 84.83 351 | 74.51 255 | 75.86 314 | 63.30 351 |
|
CMPMVS | | 59.16 21 | 80.52 295 | 79.20 293 | 84.48 313 | 83.98 337 | 67.63 332 | 89.95 281 | 93.84 228 | 64.79 342 | 66.81 339 | 91.14 243 | 57.93 316 | 95.17 300 | 76.25 238 | 88.10 205 | 90.65 315 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
UnsupCasMVSNet_bld | | | 76.23 310 | 73.27 312 | 85.09 310 | 83.79 338 | 72.92 297 | 85.65 324 | 93.47 233 | 71.52 321 | 68.84 335 | 79.08 341 | 49.77 334 | 93.21 321 | 66.81 306 | 60.52 347 | 89.13 329 |
|
PM-MVS | | | 78.11 306 | 76.12 308 | 84.09 317 | 83.54 339 | 70.08 323 | 88.97 296 | 85.27 346 | 79.93 247 | 74.73 316 | 86.43 310 | 34.70 351 | 93.48 318 | 79.43 208 | 72.06 322 | 88.72 331 |
|
DSMNet-mixed | | | 76.94 308 | 76.29 307 | 78.89 324 | 83.10 340 | 56.11 350 | 87.78 308 | 79.77 355 | 60.65 346 | 75.64 312 | 88.71 282 | 61.56 296 | 88.34 340 | 60.07 332 | 89.29 182 | 92.21 285 |
|
new_pmnet | | | 72.15 316 | 70.13 318 | 78.20 325 | 82.95 341 | 65.68 334 | 83.91 333 | 82.40 351 | 62.94 345 | 64.47 342 | 79.82 340 | 42.85 345 | 86.26 346 | 57.41 336 | 74.44 317 | 82.65 344 |
|
new-patchmatchnet | | | 76.41 309 | 75.17 309 | 80.13 323 | 82.65 342 | 59.61 343 | 87.66 310 | 91.08 290 | 78.23 268 | 69.85 333 | 83.22 328 | 54.76 324 | 91.63 334 | 64.14 321 | 64.89 342 | 89.16 327 |
|
testus | | | 74.41 313 | 73.35 311 | 77.59 329 | 82.49 343 | 57.08 346 | 86.02 318 | 90.21 307 | 72.28 318 | 72.89 326 | 84.32 324 | 37.08 349 | 86.96 344 | 52.24 339 | 82.65 254 | 88.73 330 |
|
test2356 | | | 74.50 312 | 73.27 312 | 78.20 325 | 80.81 344 | 59.84 341 | 83.76 335 | 88.33 335 | 71.43 323 | 72.37 328 | 81.84 334 | 45.60 343 | 86.26 346 | 50.97 340 | 84.32 236 | 88.50 334 |
|
ambc | | | | | 83.06 319 | 79.99 345 | 63.51 339 | 77.47 348 | 92.86 240 | | 74.34 319 | 84.45 323 | 28.74 352 | 95.06 304 | 73.06 263 | 68.89 338 | 90.61 316 |
|
1111 | | | 70.54 319 | 69.71 319 | 73.04 333 | 79.30 346 | 44.83 358 | 84.23 330 | 88.96 330 | 67.33 335 | 65.42 340 | 82.28 332 | 41.11 347 | 88.11 341 | 47.12 346 | 71.60 326 | 86.19 340 |
|
.test1245 | | | 57.63 329 | 61.79 326 | 45.14 347 | 79.30 346 | 44.83 358 | 84.23 330 | 88.96 330 | 67.33 335 | 65.42 340 | 82.28 332 | 41.11 347 | 88.11 341 | 47.12 346 | 0.39 361 | 2.46 362 |
|
TDRefinement | | | 79.81 299 | 77.34 301 | 87.22 287 | 79.24 348 | 75.48 282 | 93.12 217 | 92.03 260 | 76.45 279 | 75.01 314 | 91.58 217 | 49.19 337 | 96.44 250 | 70.22 277 | 69.18 336 | 89.75 322 |
|
test1235678 | | | 72.22 315 | 70.31 317 | 77.93 328 | 78.04 349 | 58.04 345 | 85.76 322 | 89.80 318 | 70.15 330 | 63.43 343 | 80.20 339 | 42.24 346 | 87.24 343 | 48.68 344 | 74.50 316 | 88.50 334 |
|
pmmvs3 | | | 71.81 317 | 68.71 320 | 81.11 322 | 75.86 350 | 70.42 321 | 86.74 314 | 83.66 348 | 58.95 347 | 68.64 337 | 80.89 337 | 36.93 350 | 89.52 337 | 63.10 324 | 63.59 344 | 83.39 342 |
|
DeepMVS_CX | | | | | 56.31 345 | 74.23 351 | 51.81 354 | | 56.67 365 | 44.85 352 | 48.54 352 | 75.16 343 | 27.87 354 | 58.74 361 | 40.92 352 | 52.22 349 | 58.39 355 |
|
test12356 | | | 64.99 323 | 63.78 322 | 68.61 340 | 72.69 352 | 39.14 361 | 78.46 346 | 87.61 340 | 64.91 341 | 55.77 347 | 77.48 342 | 28.10 353 | 85.59 348 | 44.69 349 | 64.35 343 | 81.12 346 |
|
FPMVS | | | 64.63 324 | 62.55 324 | 70.88 335 | 70.80 353 | 56.71 347 | 84.42 329 | 84.42 347 | 51.78 350 | 49.57 350 | 81.61 335 | 23.49 357 | 81.48 353 | 40.61 353 | 76.25 313 | 74.46 350 |
|
PMMVS2 | | | 59.60 326 | 56.40 328 | 69.21 339 | 68.83 354 | 46.58 356 | 73.02 353 | 77.48 359 | 55.07 349 | 49.21 351 | 72.95 347 | 17.43 362 | 80.04 354 | 49.32 343 | 44.33 351 | 80.99 347 |
|
testmv | | | 65.49 322 | 62.66 323 | 73.96 332 | 68.78 355 | 53.14 353 | 84.70 328 | 88.56 332 | 65.94 340 | 52.35 349 | 74.65 344 | 25.02 356 | 85.14 349 | 43.54 350 | 60.40 348 | 83.60 341 |
|
PNet_i23d | | | 50.48 332 | 47.18 333 | 60.36 343 | 68.59 356 | 44.56 360 | 72.75 354 | 72.61 360 | 43.92 353 | 33.91 357 | 60.19 354 | 6.16 364 | 73.52 357 | 38.50 354 | 28.04 354 | 63.01 352 |
|
wuyk23d | | | 21.27 340 | 20.48 341 | 23.63 351 | 68.59 356 | 36.41 363 | 49.57 359 | 6.85 368 | 9.37 360 | 7.89 363 | 4.46 365 | 4.03 367 | 31.37 362 | 17.47 360 | 16.07 360 | 3.12 360 |
|
no-one | | | 61.56 325 | 56.58 327 | 76.49 331 | 67.80 358 | 62.76 340 | 78.13 347 | 86.11 342 | 63.16 344 | 43.24 353 | 64.70 351 | 26.12 355 | 88.95 339 | 50.84 341 | 29.15 353 | 77.77 348 |
|
E-PMN | | | 43.23 334 | 42.29 335 | 46.03 346 | 65.58 359 | 37.41 362 | 73.51 350 | 64.62 361 | 33.99 357 | 28.47 360 | 47.87 357 | 19.90 361 | 67.91 358 | 22.23 358 | 24.45 356 | 32.77 357 |
|
LCM-MVSNet | | | 66.00 321 | 62.16 325 | 77.51 330 | 64.51 360 | 58.29 344 | 83.87 334 | 90.90 296 | 48.17 351 | 54.69 348 | 73.31 346 | 16.83 363 | 86.75 345 | 65.47 314 | 61.67 346 | 87.48 339 |
|
EMVS | | | 42.07 335 | 41.12 336 | 44.92 348 | 63.45 361 | 35.56 364 | 73.65 349 | 63.48 362 | 33.05 358 | 26.88 361 | 45.45 359 | 21.27 359 | 67.14 359 | 19.80 359 | 23.02 358 | 32.06 358 |
|
wuykxyi23d | | | 50.55 331 | 44.13 334 | 69.81 337 | 56.77 362 | 54.58 352 | 73.22 352 | 80.78 353 | 39.79 356 | 22.08 362 | 46.69 358 | 4.03 367 | 79.71 355 | 47.65 345 | 26.13 355 | 75.14 349 |
|
MVE | | 39.65 23 | 43.39 333 | 38.59 339 | 57.77 344 | 56.52 363 | 48.77 355 | 55.38 357 | 58.64 364 | 29.33 359 | 28.96 359 | 52.65 355 | 4.68 366 | 64.62 360 | 28.11 357 | 33.07 352 | 59.93 354 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
ANet_high | | | 58.88 327 | 54.22 330 | 72.86 334 | 56.50 364 | 56.67 348 | 80.75 343 | 86.00 343 | 73.09 311 | 37.39 355 | 64.63 352 | 22.17 358 | 79.49 356 | 43.51 351 | 23.96 357 | 82.43 345 |
|
PMVS | | 47.18 22 | 52.22 330 | 48.46 332 | 63.48 342 | 45.72 365 | 46.20 357 | 73.41 351 | 78.31 357 | 41.03 355 | 30.06 358 | 65.68 350 | 6.05 365 | 83.43 352 | 30.04 356 | 65.86 340 | 60.80 353 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
tmp_tt | | | 35.64 338 | 39.24 337 | 24.84 350 | 14.87 366 | 23.90 366 | 62.71 356 | 51.51 366 | 6.58 361 | 36.66 356 | 62.08 353 | 44.37 344 | 30.34 363 | 52.40 338 | 22.00 359 | 20.27 359 |
|
testmvs | | | 8.92 341 | 11.52 342 | 1.12 353 | 1.06 367 | 0.46 368 | 86.02 318 | 0.65 369 | 0.62 362 | 2.74 364 | 9.52 363 | 0.31 370 | 0.45 365 | 2.38 361 | 0.39 361 | 2.46 362 |
|
test123 | | | 8.76 342 | 11.22 343 | 1.39 352 | 0.85 368 | 0.97 367 | 85.76 322 | 0.35 370 | 0.54 363 | 2.45 365 | 8.14 364 | 0.60 369 | 0.48 364 | 2.16 362 | 0.17 363 | 2.71 361 |
|
cdsmvs_eth3d_5k | | | 22.14 339 | 29.52 340 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 95.76 125 | 0.00 364 | 0.00 366 | 94.29 118 | 75.66 144 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
pcd_1.5k_mvsjas | | | 6.64 344 | 8.86 345 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 79.70 93 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sosnet-low-res | | | 0.00 345 | 0.00 346 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sosnet | | | 0.00 345 | 0.00 346 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
uncertanet | | | 0.00 345 | 0.00 346 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
Regformer | | | 0.00 345 | 0.00 346 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
ab-mvs-re | | | 7.82 343 | 10.43 344 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 93.88 137 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
uanet | | | 0.00 345 | 0.00 346 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
GSMVS | | | | | | | | | | | | | | | | | 96.12 115 |
|
test_part1 | | | | | 0.00 354 | | 0.00 369 | 0.00 360 | 97.45 7 | | | | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sam_mvs1 | | | | | | | | | | | | | 71.70 194 | | | | 96.12 115 |
|
sam_mvs | | | | | | | | | | | | | 70.60 210 | | | | |
|
MTGPA | | | | | | | | | 96.97 36 | | | | | | | | |
|
test_post1 | | | | | | | | 88.00 306 | | | | 9.81 362 | 69.31 229 | 95.53 282 | 76.65 234 | | |
|
test_post | | | | | | | | | | | | 10.29 361 | 70.57 214 | 95.91 271 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 83.76 326 | 71.53 198 | 96.48 247 | | | |
|
MTMP | | | | | | | | 96.16 31 | 60.64 363 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 91.91 43 | 98.71 19 | 98.07 46 |
|
agg_prior2 | | | | | | | | | | | | | | | 90.54 63 | 98.68 24 | 98.27 31 |
|
test_prior4 | | | | | | | 85.96 44 | 94.11 160 | | | | | | | | | |
|
test_prior2 | | | | | | | | 94.12 158 | | 87.67 81 | 92.63 48 | 96.39 53 | 86.62 25 | | 91.50 50 | 98.67 26 | |
|
旧先验2 | | | | | | | | 93.36 205 | | 71.25 324 | 94.37 15 | | | 97.13 206 | 86.74 103 | | |
|
新几何2 | | | | | | | | 93.11 219 | | | | | | | | | |
|
无先验 | | | | | | | | 93.28 212 | 96.26 85 | 73.95 303 | | | | 99.05 46 | 80.56 183 | | 96.59 103 |
|
原ACMM2 | | | | | | | | 92.94 227 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 98.75 79 | 78.30 218 | | |
|
segment_acmp | | | | | | | | | | | | | 87.16 21 | | | | |
|
testdata1 | | | | | | | | 92.15 249 | | 87.94 72 | | | | | | | |
|
plane_prior5 | | | | | | | | | 96.22 89 | | | | | 98.12 114 | 88.15 82 | 89.99 168 | 94.63 175 |
|
plane_prior4 | | | | | | | | | | | | 94.86 100 | | | | | |
|
plane_prior3 | | | | | | | 82.75 112 | | | 90.26 25 | 86.91 136 | | | | | | |
|
plane_prior2 | | | | | | | | 95.85 44 | | 90.81 18 | | | | | | | |
|
plane_prior | | | | | | | 82.73 115 | 95.21 77 | | 89.66 35 | | | | | | 89.88 172 | |
|
n2 | | | | | | | | | 0.00 371 | | | | | | | | |
|
nn | | | | | | | | | 0.00 371 | | | | | | | | |
|
door-mid | | | | | | | | | 85.49 344 | | | | | | | | |
|
test11 | | | | | | | | | 96.57 72 | | | | | | | | |
|
door | | | | | | | | | 85.33 345 | | | | | | | | |
|
HQP5-MVS | | | | | | | 81.56 134 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 87.11 100 | | |
|
HQP4-MVS | | | | | | | | | | | 85.43 179 | | | 97.96 135 | | | 94.51 185 |
|
HQP3-MVS | | | | | | | | | 96.04 104 | | | | | | | 89.77 174 | |
|
HQP2-MVS | | | | | | | | | | | | | 73.83 170 | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 55.91 351 | 87.62 311 | | 73.32 308 | 84.59 204 | | 70.33 217 | | 74.65 252 | | 95.50 138 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 87.47 211 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 88.01 208 | |
|
Test By Simon | | | | | | | | | | | | | 80.02 88 | | | | |
|