region2R | | | 97.07 18 | 96.84 19 | 97.77 23 | 99.46 1 | 93.79 38 | 98.52 10 | 98.24 29 | 93.19 63 | 97.14 25 | 98.34 28 | 91.59 39 | 99.87 6 | 95.46 48 | 99.59 9 | 99.64 5 |
|
ACMMPR | | | 97.07 18 | 96.84 19 | 97.79 20 | 99.44 2 | 93.88 34 | 98.52 10 | 98.31 22 | 93.21 60 | 97.15 24 | 98.33 31 | 91.35 41 | 99.86 7 | 95.63 43 | 99.59 9 | 99.62 7 |
|
HFP-MVS | | | 97.14 15 | 96.92 16 | 97.83 16 | 99.42 3 | 94.12 28 | 98.52 10 | 98.32 20 | 93.21 60 | 97.18 22 | 98.29 37 | 92.08 28 | 99.83 14 | 95.63 43 | 99.59 9 | 99.54 19 |
|
#test# | | | 97.02 21 | 96.75 26 | 97.83 16 | 99.42 3 | 94.12 28 | 98.15 29 | 98.32 20 | 92.57 83 | 97.18 22 | 98.29 37 | 92.08 28 | 99.83 14 | 95.12 53 | 99.59 9 | 99.54 19 |
|
HSP-MVS | | | 97.53 5 | 97.49 5 | 97.63 35 | 99.40 5 | 93.77 41 | 98.53 9 | 97.85 91 | 95.55 5 | 98.56 5 | 97.81 62 | 93.90 5 | 99.65 41 | 96.62 15 | 99.21 50 | 99.48 28 |
|
mPP-MVS | | | 96.86 27 | 96.60 29 | 97.64 33 | 99.40 5 | 93.44 48 | 98.50 13 | 98.09 51 | 93.27 59 | 95.95 63 | 98.33 31 | 91.04 45 | 99.88 4 | 95.20 50 | 99.57 13 | 99.60 10 |
|
MP-MVS | | | 96.77 31 | 96.45 36 | 97.72 26 | 99.39 7 | 93.80 37 | 98.41 17 | 98.06 59 | 93.37 55 | 95.54 79 | 98.34 28 | 90.59 52 | 99.88 4 | 94.83 63 | 99.54 15 | 99.49 26 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
XVS | | | 97.18 12 | 96.96 14 | 97.81 18 | 99.38 8 | 94.03 32 | 98.59 7 | 98.20 32 | 94.85 18 | 96.59 40 | 98.29 37 | 91.70 36 | 99.80 20 | 95.66 40 | 99.40 32 | 99.62 7 |
|
X-MVStestdata | | | 91.71 182 | 89.67 240 | 97.81 18 | 99.38 8 | 94.03 32 | 98.59 7 | 98.20 32 | 94.85 18 | 96.59 40 | 32.69 360 | 91.70 36 | 99.80 20 | 95.66 40 | 99.40 32 | 99.62 7 |
|
zzz-MVS | | | 97.07 18 | 96.77 25 | 97.97 12 | 99.37 10 | 94.42 19 | 97.15 133 | 98.08 52 | 95.07 15 | 96.11 54 | 98.59 7 | 90.88 49 | 99.90 1 | 96.18 30 | 99.50 21 | 99.58 11 |
|
MTAPA | | | 97.08 17 | 96.78 24 | 97.97 12 | 99.37 10 | 94.42 19 | 97.24 120 | 98.08 52 | 95.07 15 | 96.11 54 | 98.59 7 | 90.88 49 | 99.90 1 | 96.18 30 | 99.50 21 | 99.58 11 |
|
HPM-MVS | | | 96.69 34 | 96.45 36 | 97.40 41 | 99.36 12 | 93.11 56 | 98.87 1 | 98.06 59 | 91.17 127 | 96.40 48 | 97.99 51 | 90.99 46 | 99.58 55 | 95.61 45 | 99.61 8 | 99.49 26 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
PGM-MVS | | | 96.81 29 | 96.53 32 | 97.65 31 | 99.35 13 | 93.53 46 | 97.65 74 | 98.98 1 | 92.22 89 | 97.14 25 | 98.44 17 | 91.17 43 | 99.85 10 | 94.35 70 | 99.46 25 | 99.57 13 |
|
CP-MVS | | | 97.02 21 | 96.81 22 | 97.64 33 | 99.33 14 | 93.54 45 | 98.80 3 | 98.28 24 | 92.99 69 | 96.45 47 | 98.30 36 | 91.90 33 | 99.85 10 | 95.61 45 | 99.68 3 | 99.54 19 |
|
HPM-MVS_fast | | | 96.51 39 | 96.27 40 | 97.22 52 | 99.32 15 | 92.74 64 | 98.74 4 | 98.06 59 | 90.57 148 | 96.77 32 | 98.35 25 | 90.21 56 | 99.53 71 | 94.80 65 | 99.63 6 | 99.38 39 |
|
MCST-MVS | | | 97.18 12 | 96.84 19 | 98.20 6 | 99.30 16 | 95.35 6 | 97.12 135 | 98.07 57 | 93.54 53 | 96.08 56 | 97.69 69 | 93.86 6 | 99.71 29 | 96.50 19 | 99.39 34 | 99.55 17 |
|
test_part2 | | | | | | 99.28 17 | 95.74 4 | | | | 98.10 8 | | | | | | |
|
v1.0 | | | 40.67 337 | 54.22 333 | 0.00 354 | 99.28 17 | 0.00 369 | 0.00 360 | 98.26 26 | 93.81 46 | 98.10 8 | 98.53 13 | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
CPTT-MVS | | | 95.57 61 | 95.19 62 | 96.70 63 | 99.27 19 | 91.48 99 | 98.33 20 | 98.11 47 | 87.79 230 | 95.17 83 | 98.03 47 | 87.09 94 | 99.61 47 | 93.51 85 | 99.42 30 | 99.02 65 |
|
TSAR-MVS + MP. | | | 97.42 6 | 97.33 7 | 97.69 29 | 99.25 20 | 94.24 24 | 98.07 34 | 97.85 91 | 93.72 47 | 98.57 4 | 98.35 25 | 93.69 8 | 99.40 89 | 97.06 3 | 99.46 25 | 99.44 32 |
|
CSCG | | | 96.05 51 | 95.91 47 | 96.46 79 | 99.24 21 | 90.47 134 | 98.30 21 | 98.57 11 | 89.01 184 | 93.97 102 | 97.57 82 | 92.62 18 | 99.76 23 | 94.66 68 | 99.27 45 | 99.15 55 |
|
ACMMP | | | 96.27 46 | 95.93 46 | 97.28 47 | 99.24 21 | 92.62 68 | 98.25 25 | 98.81 3 | 92.99 69 | 94.56 91 | 98.39 23 | 88.96 66 | 99.85 10 | 94.57 69 | 97.63 96 | 99.36 41 |
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 |
MP-MVS-pluss | | | 96.70 33 | 96.27 40 | 97.98 11 | 99.23 23 | 94.71 14 | 96.96 145 | 98.06 59 | 90.67 139 | 95.55 78 | 98.78 4 | 91.07 44 | 99.86 7 | 96.58 17 | 99.55 14 | 99.38 39 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
DP-MVS Recon | | | 95.68 59 | 95.12 64 | 97.37 42 | 99.19 24 | 94.19 25 | 97.03 138 | 98.08 52 | 88.35 216 | 95.09 84 | 97.65 73 | 89.97 59 | 99.48 79 | 92.08 110 | 98.59 75 | 98.44 116 |
|
ESAPD | | | 97.86 1 | 97.65 2 | 98.47 1 | 99.17 25 | 95.78 3 | 97.21 126 | 98.35 19 | 95.16 13 | 98.71 3 | 98.80 3 | 95.05 1 | 99.89 3 | 96.70 14 | 99.73 1 | 99.73 2 |
|
APDe-MVS | | | 97.82 2 | 97.73 1 | 98.08 9 | 99.15 26 | 94.82 13 | 98.81 2 | 98.30 23 | 94.76 25 | 98.30 6 | 98.90 2 | 93.77 7 | 99.68 37 | 97.93 1 | 99.69 2 | 99.75 1 |
|
ACMMP_Plus | | | 97.20 11 | 96.86 18 | 98.23 5 | 99.09 27 | 95.16 9 | 97.60 87 | 98.19 34 | 92.82 78 | 97.93 12 | 98.74 5 | 91.60 38 | 99.86 7 | 96.26 23 | 99.52 17 | 99.67 3 |
|
HPM-MVS++ | | | 97.34 9 | 96.97 13 | 98.47 1 | 99.08 28 | 96.16 1 | 97.55 94 | 97.97 80 | 95.59 4 | 96.61 38 | 97.89 53 | 92.57 19 | 99.84 13 | 95.95 35 | 99.51 19 | 99.40 35 |
|
114514_t | | | 93.95 103 | 93.06 112 | 96.63 66 | 99.07 29 | 91.61 95 | 97.46 102 | 97.96 81 | 77.99 333 | 93.00 127 | 97.57 82 | 86.14 106 | 99.33 94 | 89.22 156 | 99.15 54 | 98.94 76 |
|
SMA-MVS | | | 97.35 8 | 97.03 10 | 98.30 4 | 99.06 30 | 95.42 5 | 97.94 44 | 98.18 36 | 90.57 148 | 98.85 2 | 98.94 1 | 93.33 10 | 99.83 14 | 96.72 13 | 99.68 3 | 99.63 6 |
|
APD-MVS | | | 96.95 24 | 96.60 29 | 98.01 10 | 99.03 31 | 94.93 12 | 97.72 65 | 98.10 49 | 91.50 114 | 98.01 10 | 98.32 33 | 92.33 23 | 99.58 55 | 94.85 62 | 99.51 19 | 99.53 22 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
APD-MVS_3200maxsize | | | 96.81 29 | 96.71 27 | 97.12 56 | 99.01 32 | 92.31 74 | 97.98 43 | 98.06 59 | 93.11 66 | 97.44 17 | 98.55 11 | 90.93 47 | 99.55 66 | 96.06 32 | 99.25 46 | 99.51 23 |
|
CDPH-MVS | | | 95.97 54 | 95.38 57 | 97.77 23 | 98.93 33 | 94.44 18 | 96.35 209 | 97.88 86 | 86.98 251 | 96.65 36 | 97.89 53 | 91.99 32 | 99.47 80 | 92.26 101 | 99.46 25 | 99.39 36 |
|
CNVR-MVS | | | 97.68 3 | 97.44 6 | 98.37 3 | 98.90 34 | 95.86 2 | 97.27 118 | 98.08 52 | 95.81 3 | 97.87 13 | 98.31 34 | 94.26 3 | 99.68 37 | 97.02 4 | 99.49 23 | 99.57 13 |
|
abl_6 | | | 96.40 42 | 96.21 42 | 96.98 60 | 98.89 35 | 92.20 79 | 97.89 48 | 98.03 68 | 93.34 58 | 97.22 21 | 98.42 19 | 87.93 80 | 99.72 28 | 95.10 54 | 99.07 61 | 99.02 65 |
|
PAPM_NR | | | 95.01 73 | 94.59 74 | 96.26 94 | 98.89 35 | 90.68 129 | 97.24 120 | 97.73 97 | 91.80 108 | 92.93 132 | 96.62 128 | 89.13 65 | 99.14 109 | 89.21 157 | 97.78 93 | 98.97 72 |
|
NCCC | | | 97.30 10 | 97.03 10 | 98.11 8 | 98.77 37 | 95.06 11 | 97.34 112 | 98.04 66 | 95.96 2 | 97.09 29 | 97.88 55 | 93.18 11 | 99.71 29 | 95.84 38 | 99.17 53 | 99.56 15 |
|
DP-MVS | | | 92.76 142 | 91.51 165 | 96.52 71 | 98.77 37 | 90.99 118 | 97.38 109 | 96.08 232 | 82.38 306 | 89.29 228 | 97.87 56 | 83.77 129 | 99.69 35 | 81.37 287 | 96.69 123 | 98.89 82 |
|
MSLP-MVS++ | | | 96.94 25 | 97.06 9 | 96.59 69 | 98.72 39 | 91.86 89 | 97.67 71 | 98.49 12 | 94.66 28 | 97.24 20 | 98.41 22 | 92.31 26 | 98.94 130 | 96.61 16 | 99.46 25 | 98.96 73 |
|
TEST9 | | | | | | 98.70 40 | 94.19 25 | 96.41 201 | 98.02 69 | 88.17 223 | 96.03 57 | 97.56 84 | 92.74 14 | 99.59 52 | | | |
|
train_agg | | | 96.30 45 | 95.83 48 | 97.72 26 | 98.70 40 | 94.19 25 | 96.41 201 | 98.02 69 | 88.58 202 | 96.03 57 | 97.56 84 | 92.73 15 | 99.59 52 | 95.04 55 | 99.37 39 | 99.39 36 |
|
test_8 | | | | | | 98.67 42 | 94.06 31 | 96.37 208 | 98.01 71 | 88.58 202 | 95.98 62 | 97.55 86 | 92.73 15 | 99.58 55 | | | |
|
agg_prior3 | | | 96.16 49 | 95.67 50 | 97.62 36 | 98.67 42 | 93.88 34 | 96.41 201 | 98.00 73 | 87.93 227 | 95.81 67 | 97.47 88 | 92.33 23 | 99.59 52 | 95.04 55 | 99.37 39 | 99.39 36 |
|
agg_prior1 | | | 96.22 48 | 95.77 49 | 97.56 37 | 98.67 42 | 93.79 38 | 96.28 217 | 98.00 73 | 88.76 199 | 95.68 72 | 97.55 86 | 92.70 17 | 99.57 63 | 95.01 57 | 99.32 41 | 99.32 43 |
|
agg_prior | | | | | | 98.67 42 | 93.79 38 | | 98.00 73 | | 95.68 72 | | | 99.57 63 | | | |
|
test_prior3 | | | 96.46 41 | 96.20 43 | 97.23 50 | 98.67 42 | 92.99 58 | 96.35 209 | 98.00 73 | 92.80 79 | 96.03 57 | 97.59 80 | 92.01 30 | 99.41 87 | 95.01 57 | 99.38 35 | 99.29 45 |
|
test_prior | | | | | 97.23 50 | 98.67 42 | 92.99 58 | | 98.00 73 | | | | | 99.41 87 | | | 99.29 45 |
|
DeepC-MVS_fast | | 93.89 2 | 96.93 26 | 96.64 28 | 97.78 21 | 98.64 48 | 94.30 21 | 97.41 103 | 98.04 66 | 94.81 23 | 96.59 40 | 98.37 24 | 91.24 42 | 99.64 46 | 95.16 51 | 99.52 17 | 99.42 34 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
新几何1 | | | | | 97.32 44 | 98.60 49 | 93.59 44 | | 97.75 95 | 81.58 313 | 95.75 70 | 97.85 59 | 90.04 58 | 99.67 39 | 86.50 210 | 99.13 56 | 98.69 95 |
|
原ACMM1 | | | | | 96.38 85 | 98.59 50 | 91.09 117 | | 97.89 84 | 87.41 239 | 95.22 82 | 97.68 70 | 90.25 54 | 99.54 68 | 87.95 180 | 99.12 59 | 98.49 109 |
|
AdaColmap | | | 94.34 90 | 93.68 94 | 96.31 89 | 98.59 50 | 91.68 94 | 96.59 192 | 97.81 93 | 89.87 157 | 92.15 144 | 97.06 104 | 83.62 131 | 99.54 68 | 89.34 152 | 98.07 86 | 97.70 147 |
|
PLC | | 91.00 6 | 94.11 97 | 93.43 104 | 96.13 98 | 98.58 52 | 91.15 116 | 96.69 181 | 97.39 142 | 87.29 242 | 91.37 158 | 96.71 114 | 88.39 75 | 99.52 75 | 87.33 198 | 97.13 112 | 97.73 145 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
1121 | | | 94.71 85 | 93.83 89 | 97.34 43 | 98.57 53 | 93.64 43 | 96.04 231 | 97.73 97 | 81.56 315 | 95.68 72 | 97.85 59 | 90.23 55 | 99.65 41 | 87.68 187 | 99.12 59 | 98.73 90 |
|
SD-MVS | | | 97.41 7 | 97.53 3 | 97.06 57 | 98.57 53 | 94.46 17 | 97.92 46 | 98.14 42 | 94.82 22 | 99.01 1 | 98.55 11 | 94.18 4 | 97.41 284 | 96.94 5 | 99.64 5 | 99.32 43 |
|
test12 | | | | | 97.65 31 | 98.46 55 | 94.26 22 | | 97.66 107 | | 95.52 80 | | 90.89 48 | 99.46 81 | | 99.25 46 | 99.22 50 |
|
MVS_111021_HR | | | 96.68 36 | 96.58 31 | 96.99 59 | 98.46 55 | 92.31 74 | 96.20 225 | 98.90 2 | 94.30 36 | 95.86 65 | 97.74 67 | 92.33 23 | 99.38 92 | 96.04 33 | 99.42 30 | 99.28 48 |
|
OMC-MVS | | | 95.09 72 | 94.70 72 | 96.25 95 | 98.46 55 | 91.28 106 | 96.43 199 | 97.57 116 | 92.04 103 | 94.77 89 | 97.96 52 | 87.01 95 | 99.09 120 | 91.31 129 | 96.77 119 | 98.36 123 |
|
MG-MVS | | | 95.61 60 | 95.38 57 | 96.31 89 | 98.42 58 | 90.53 132 | 96.04 231 | 97.48 125 | 93.47 54 | 95.67 75 | 98.10 43 | 89.17 64 | 99.25 99 | 91.27 130 | 98.77 70 | 99.13 57 |
|
PHI-MVS | | | 96.77 31 | 96.46 35 | 97.71 28 | 98.40 59 | 94.07 30 | 98.21 28 | 98.45 15 | 89.86 158 | 97.11 28 | 98.01 49 | 92.52 21 | 99.69 35 | 96.03 34 | 99.53 16 | 99.36 41 |
|
F-COLMAP | | | 93.58 115 | 92.98 113 | 95.37 132 | 98.40 59 | 88.98 194 | 97.18 130 | 97.29 153 | 87.75 232 | 90.49 181 | 97.10 103 | 85.21 114 | 99.50 78 | 86.70 207 | 96.72 122 | 97.63 148 |
|
SteuartSystems-ACMMP | | | 97.62 4 | 97.53 3 | 97.87 14 | 98.39 61 | 94.25 23 | 98.43 16 | 98.27 25 | 95.34 9 | 98.11 7 | 98.56 9 | 94.53 2 | 99.71 29 | 96.57 18 | 99.62 7 | 99.65 4 |
Skip Steuart: Steuart Systems R&D Blog. |
旧先验1 | | | | | | 98.38 62 | 93.38 50 | | 97.75 95 | | | 98.09 44 | 92.30 27 | | | 99.01 64 | 99.16 53 |
|
CNLPA | | | 94.28 91 | 93.53 99 | 96.52 71 | 98.38 62 | 92.55 70 | 96.59 192 | 96.88 198 | 90.13 154 | 91.91 148 | 97.24 96 | 85.21 114 | 99.09 120 | 87.64 190 | 97.83 91 | 97.92 136 |
|
Regformer-3 | | | 96.85 28 | 96.80 23 | 97.01 58 | 98.34 64 | 92.02 85 | 96.96 145 | 97.76 94 | 95.01 17 | 97.08 30 | 98.42 19 | 91.71 35 | 99.54 68 | 96.80 9 | 99.13 56 | 99.48 28 |
|
Regformer-4 | | | 96.97 23 | 96.87 17 | 97.25 49 | 98.34 64 | 92.66 67 | 96.96 145 | 98.01 71 | 95.12 14 | 97.14 25 | 98.42 19 | 91.82 34 | 99.61 47 | 96.90 6 | 99.13 56 | 99.50 24 |
|
TAPA-MVS | | 90.10 7 | 92.30 161 | 91.22 175 | 95.56 121 | 98.33 66 | 89.60 161 | 96.79 166 | 97.65 109 | 81.83 310 | 91.52 155 | 97.23 97 | 87.94 79 | 98.91 132 | 71.31 332 | 98.37 79 | 98.17 127 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
Regformer-1 | | | 97.10 16 | 96.96 14 | 97.54 38 | 98.32 67 | 93.48 47 | 96.83 159 | 97.99 78 | 95.20 12 | 97.46 16 | 98.25 40 | 92.48 22 | 99.58 55 | 96.79 11 | 99.29 43 | 99.55 17 |
|
Regformer-2 | | | 97.16 14 | 96.99 12 | 97.67 30 | 98.32 67 | 93.84 36 | 96.83 159 | 98.10 49 | 95.24 10 | 97.49 15 | 98.25 40 | 92.57 19 | 99.61 47 | 96.80 9 | 99.29 43 | 99.56 15 |
|
TSAR-MVS + GP. | | | 96.69 34 | 96.49 33 | 97.27 48 | 98.31 69 | 93.39 49 | 96.79 166 | 96.72 204 | 94.17 37 | 97.44 17 | 97.66 72 | 92.76 13 | 99.33 94 | 96.86 8 | 97.76 95 | 99.08 62 |
|
CHOSEN 1792x2688 | | | 94.15 94 | 93.51 100 | 96.06 99 | 98.27 70 | 89.38 177 | 95.18 270 | 98.48 14 | 85.60 272 | 93.76 104 | 97.11 102 | 83.15 137 | 99.61 47 | 91.33 128 | 98.72 72 | 99.19 51 |
|
PVSNet_BlendedMVS | | | 94.06 99 | 93.92 87 | 94.47 178 | 98.27 70 | 89.46 170 | 96.73 171 | 98.36 16 | 90.17 153 | 94.36 94 | 95.24 195 | 88.02 77 | 99.58 55 | 93.44 88 | 90.72 224 | 94.36 292 |
|
PVSNet_Blended | | | 94.87 81 | 94.56 75 | 95.81 108 | 98.27 70 | 89.46 170 | 95.47 258 | 98.36 16 | 88.84 193 | 94.36 94 | 96.09 152 | 88.02 77 | 99.58 55 | 93.44 88 | 98.18 83 | 98.40 119 |
|
Anonymous20231211 | | | 90.63 237 | 89.42 245 | 94.27 186 | 98.24 73 | 89.19 191 | 98.05 35 | 97.89 84 | 79.95 323 | 88.25 248 | 94.96 201 | 72.56 296 | 98.13 198 | 89.70 146 | 85.14 275 | 95.49 226 |
|
EI-MVSNet-Vis-set | | | 96.51 39 | 96.47 34 | 96.63 66 | 98.24 73 | 91.20 111 | 96.89 154 | 97.73 97 | 94.74 26 | 96.49 44 | 98.49 14 | 90.88 49 | 99.58 55 | 96.44 20 | 98.32 80 | 99.13 57 |
|
test222 | | | | | | 98.24 73 | 92.21 77 | 95.33 262 | 97.60 112 | 79.22 328 | 95.25 81 | 97.84 61 | 88.80 69 | | | 99.15 54 | 98.72 91 |
|
HyFIR lowres test | | | 93.66 112 | 92.92 115 | 95.87 106 | 98.24 73 | 89.88 148 | 94.58 277 | 98.49 12 | 85.06 279 | 93.78 103 | 95.78 168 | 82.86 158 | 98.67 154 | 91.77 117 | 95.71 141 | 99.07 63 |
|
MVS_111021_LR | | | 96.24 47 | 96.19 44 | 96.39 84 | 98.23 77 | 91.35 105 | 96.24 223 | 98.79 4 | 93.99 40 | 95.80 68 | 97.65 73 | 89.92 60 | 99.24 100 | 95.87 36 | 99.20 51 | 98.58 99 |
|
EI-MVSNet-UG-set | | | 96.34 44 | 96.30 39 | 96.47 77 | 98.20 78 | 90.93 122 | 96.86 156 | 97.72 100 | 94.67 27 | 96.16 53 | 98.46 15 | 90.43 53 | 99.58 55 | 96.23 24 | 97.96 89 | 98.90 80 |
|
PVSNet_Blended_VisFu | | | 95.27 66 | 94.91 66 | 96.38 85 | 98.20 78 | 90.86 124 | 97.27 118 | 98.25 28 | 90.21 152 | 94.18 98 | 97.27 94 | 87.48 89 | 99.73 25 | 93.53 84 | 97.77 94 | 98.55 100 |
|
Anonymous202405211 | | | 92.07 170 | 90.83 191 | 95.76 110 | 98.19 80 | 88.75 197 | 97.58 90 | 95.00 283 | 86.00 268 | 93.64 105 | 97.45 89 | 66.24 326 | 99.53 71 | 90.68 137 | 92.71 190 | 99.01 69 |
|
PatchMatch-RL | | | 92.90 136 | 92.02 141 | 95.56 121 | 98.19 80 | 90.80 126 | 95.27 267 | 97.18 157 | 87.96 226 | 91.86 150 | 95.68 175 | 80.44 208 | 98.99 128 | 84.01 252 | 97.54 99 | 96.89 173 |
|
testdata | | | | | 95.46 129 | 98.18 82 | 88.90 196 | | 97.66 107 | 82.73 304 | 97.03 31 | 98.07 45 | 90.06 57 | 98.85 138 | 89.67 147 | 98.98 65 | 98.64 97 |
|
Anonymous20240529 | | | 91.98 175 | 90.73 195 | 95.73 115 | 98.14 83 | 89.40 176 | 97.99 42 | 97.72 100 | 79.63 325 | 93.54 109 | 97.41 91 | 69.94 311 | 99.56 65 | 91.04 133 | 91.11 217 | 98.22 125 |
|
LFMVS | | | 93.60 114 | 92.63 124 | 96.52 71 | 98.13 84 | 91.27 107 | 97.94 44 | 93.39 325 | 90.57 148 | 96.29 49 | 98.31 34 | 69.00 313 | 99.16 106 | 94.18 71 | 95.87 137 | 99.12 59 |
|
DeepPCF-MVS | | 93.97 1 | 96.61 37 | 97.09 8 | 95.15 141 | 98.09 85 | 86.63 262 | 96.00 235 | 98.15 40 | 95.43 7 | 97.95 11 | 98.56 9 | 93.40 9 | 99.36 93 | 96.77 12 | 99.48 24 | 99.45 30 |
|
VNet | | | 95.89 56 | 95.45 54 | 97.21 53 | 98.07 86 | 92.94 61 | 97.50 97 | 98.15 40 | 93.87 42 | 97.52 14 | 97.61 79 | 85.29 113 | 99.53 71 | 95.81 39 | 95.27 145 | 99.16 53 |
|
MAR-MVS | | | 94.22 92 | 93.46 102 | 96.51 74 | 98.00 87 | 92.19 80 | 97.67 71 | 97.47 128 | 88.13 225 | 93.00 127 | 95.84 161 | 84.86 119 | 99.51 76 | 87.99 179 | 98.17 84 | 97.83 142 |
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 |
view600 | | | 92.55 145 | 91.68 151 | 95.18 135 | 97.98 88 | 89.44 172 | 98.00 38 | 94.57 300 | 92.09 97 | 93.17 122 | 95.52 183 | 78.14 255 | 99.11 111 | 81.61 276 | 94.04 166 | 96.98 164 |
|
view800 | | | 92.55 145 | 91.68 151 | 95.18 135 | 97.98 88 | 89.44 172 | 98.00 38 | 94.57 300 | 92.09 97 | 93.17 122 | 95.52 183 | 78.14 255 | 99.11 111 | 81.61 276 | 94.04 166 | 96.98 164 |
|
conf0.05thres1000 | | | 92.55 145 | 91.68 151 | 95.18 135 | 97.98 88 | 89.44 172 | 98.00 38 | 94.57 300 | 92.09 97 | 93.17 122 | 95.52 183 | 78.14 255 | 99.11 111 | 81.61 276 | 94.04 166 | 96.98 164 |
|
tfpn | | | 92.55 145 | 91.68 151 | 95.18 135 | 97.98 88 | 89.44 172 | 98.00 38 | 94.57 300 | 92.09 97 | 93.17 122 | 95.52 183 | 78.14 255 | 99.11 111 | 81.61 276 | 94.04 166 | 96.98 164 |
|
DeepC-MVS | | 93.07 3 | 96.06 50 | 95.66 51 | 97.29 46 | 97.96 92 | 93.17 55 | 97.30 117 | 98.06 59 | 93.92 41 | 93.38 113 | 98.66 6 | 86.83 96 | 99.73 25 | 95.60 47 | 99.22 49 | 98.96 73 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
COLMAP_ROB | | 87.81 15 | 90.40 241 | 89.28 248 | 93.79 210 | 97.95 93 | 87.13 251 | 96.92 152 | 95.89 245 | 82.83 303 | 86.88 275 | 97.18 98 | 73.77 291 | 99.29 97 | 78.44 310 | 93.62 176 | 94.95 262 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
AllTest | | | 90.23 245 | 88.98 252 | 93.98 197 | 97.94 94 | 86.64 259 | 96.51 196 | 95.54 258 | 85.38 273 | 85.49 285 | 96.77 112 | 70.28 308 | 99.15 107 | 80.02 300 | 92.87 187 | 96.15 196 |
|
TestCases | | | | | 93.98 197 | 97.94 94 | 86.64 259 | | 95.54 258 | 85.38 273 | 85.49 285 | 96.77 112 | 70.28 308 | 99.15 107 | 80.02 300 | 92.87 187 | 96.15 196 |
|
tfpn111 | | | 92.45 152 | 91.58 158 | 95.06 145 | 97.92 96 | 89.37 178 | 97.71 67 | 94.66 295 | 92.20 91 | 93.31 115 | 94.90 205 | 78.06 259 | 99.11 111 | 81.37 287 | 94.06 164 | 96.70 179 |
|
conf200view11 | | | 92.45 152 | 91.58 158 | 95.05 146 | 97.92 96 | 89.37 178 | 97.71 67 | 94.66 295 | 92.20 91 | 93.31 115 | 94.90 205 | 78.06 259 | 99.08 122 | 81.40 283 | 94.08 160 | 96.70 179 |
|
thres100view900 | | | 92.43 154 | 91.58 158 | 94.98 151 | 97.92 96 | 89.37 178 | 97.71 67 | 94.66 295 | 92.20 91 | 93.31 115 | 94.90 205 | 78.06 259 | 99.08 122 | 81.40 283 | 94.08 160 | 96.48 187 |
|
thres600view7 | | | 92.49 151 | 91.60 157 | 95.18 135 | 97.91 99 | 89.47 168 | 97.65 74 | 94.66 295 | 92.18 96 | 93.33 114 | 94.91 204 | 78.06 259 | 99.10 117 | 81.61 276 | 94.06 164 | 96.98 164 |
|
API-MVS | | | 94.84 82 | 94.49 79 | 95.90 105 | 97.90 100 | 92.00 86 | 97.80 56 | 97.48 125 | 89.19 174 | 94.81 87 | 96.71 114 | 88.84 68 | 99.17 105 | 88.91 165 | 98.76 71 | 96.53 184 |
|
VDD-MVS | | | 93.82 107 | 93.08 111 | 96.02 101 | 97.88 101 | 89.96 146 | 97.72 65 | 95.85 246 | 92.43 86 | 95.86 65 | 98.44 17 | 68.42 317 | 99.39 90 | 96.31 21 | 94.85 150 | 98.71 93 |
|
tfpn200view9 | | | 92.38 157 | 91.52 163 | 94.95 154 | 97.85 102 | 89.29 184 | 97.41 103 | 94.88 290 | 92.19 94 | 93.27 119 | 94.46 229 | 78.17 252 | 99.08 122 | 81.40 283 | 94.08 160 | 96.48 187 |
|
thres400 | | | 92.42 155 | 91.52 163 | 95.12 144 | 97.85 102 | 89.29 184 | 97.41 103 | 94.88 290 | 92.19 94 | 93.27 119 | 94.46 229 | 78.17 252 | 99.08 122 | 81.40 283 | 94.08 160 | 96.98 164 |
|
DELS-MVS | | | 96.61 37 | 96.38 38 | 97.30 45 | 97.79 104 | 93.19 54 | 95.96 236 | 98.18 36 | 95.23 11 | 95.87 64 | 97.65 73 | 91.45 40 | 99.70 34 | 95.87 36 | 99.44 29 | 99.00 71 |
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 |
tfpn1000 | | | 91.99 174 | 91.05 178 | 94.80 162 | 97.78 105 | 89.66 159 | 97.91 47 | 92.90 336 | 88.99 185 | 91.73 151 | 94.84 210 | 78.99 236 | 98.33 186 | 82.41 272 | 93.91 172 | 96.40 189 |
|
PVSNet | | 86.66 18 | 92.24 164 | 91.74 150 | 93.73 217 | 97.77 106 | 83.69 293 | 92.88 313 | 96.72 204 | 87.91 228 | 93.00 127 | 94.86 209 | 78.51 247 | 99.05 126 | 86.53 208 | 97.45 104 | 98.47 112 |
|
MVS_0304 | | | 96.05 51 | 95.45 54 | 97.85 15 | 97.75 107 | 94.50 16 | 96.87 155 | 97.95 83 | 95.46 6 | 95.60 76 | 98.01 49 | 80.96 195 | 99.83 14 | 97.23 2 | 99.25 46 | 99.23 49 |
|
0601test | | | 94.78 84 | 94.23 84 | 96.43 81 | 97.74 108 | 91.22 108 | 96.85 157 | 97.10 168 | 91.23 125 | 95.71 71 | 96.93 106 | 84.30 125 | 99.31 96 | 93.10 94 | 95.12 147 | 98.75 88 |
|
tfpn_ndepth | | | 91.88 178 | 90.96 182 | 94.62 171 | 97.73 109 | 89.93 147 | 97.75 59 | 92.92 335 | 88.93 190 | 91.73 151 | 93.80 266 | 78.91 237 | 98.49 170 | 83.02 264 | 93.86 173 | 95.45 231 |
|
WTY-MVS | | | 94.71 85 | 94.02 86 | 96.79 62 | 97.71 110 | 92.05 83 | 96.59 192 | 97.35 148 | 90.61 145 | 94.64 90 | 96.93 106 | 86.41 101 | 99.39 90 | 91.20 132 | 94.71 156 | 98.94 76 |
|
UA-Net | | | 95.95 55 | 95.53 53 | 97.20 54 | 97.67 111 | 92.98 60 | 97.65 74 | 98.13 43 | 94.81 23 | 96.61 38 | 98.35 25 | 88.87 67 | 99.51 76 | 90.36 139 | 97.35 107 | 99.11 60 |
|
IS-MVSNet | | | 94.90 79 | 94.52 78 | 96.05 100 | 97.67 111 | 90.56 131 | 98.44 15 | 96.22 227 | 93.21 60 | 93.99 100 | 97.74 67 | 85.55 111 | 98.45 171 | 89.98 140 | 97.86 90 | 99.14 56 |
|
PAPR | | | 94.18 93 | 93.42 106 | 96.48 76 | 97.64 113 | 91.42 104 | 95.55 253 | 97.71 104 | 88.99 185 | 92.34 140 | 95.82 163 | 89.19 62 | 99.11 111 | 86.14 215 | 97.38 105 | 98.90 80 |
|
CANet | | | 96.39 43 | 96.02 45 | 97.50 39 | 97.62 114 | 93.38 50 | 97.02 140 | 97.96 81 | 95.42 8 | 94.86 86 | 97.81 62 | 87.38 91 | 99.82 18 | 96.88 7 | 99.20 51 | 99.29 45 |
|
thres200 | | | 92.23 165 | 91.39 166 | 94.75 166 | 97.61 115 | 89.03 193 | 96.60 191 | 95.09 279 | 92.08 102 | 93.28 118 | 94.00 259 | 78.39 250 | 99.04 127 | 81.26 295 | 94.18 159 | 96.19 193 |
|
Vis-MVSNet (Re-imp) | | | 94.15 94 | 93.88 88 | 94.95 154 | 97.61 115 | 87.92 234 | 98.10 31 | 95.80 249 | 92.22 89 | 93.02 126 | 97.45 89 | 84.53 123 | 97.91 248 | 88.24 174 | 97.97 88 | 99.02 65 |
|
canonicalmvs | | | 96.02 53 | 95.45 54 | 97.75 25 | 97.59 117 | 95.15 10 | 98.28 22 | 97.60 112 | 94.52 30 | 96.27 50 | 96.12 149 | 87.65 85 | 99.18 104 | 96.20 29 | 94.82 152 | 98.91 79 |
|
LS3D | | | 93.57 116 | 92.61 126 | 96.47 77 | 97.59 117 | 91.61 95 | 97.67 71 | 97.72 100 | 85.17 277 | 90.29 186 | 98.34 28 | 84.60 121 | 99.73 25 | 83.85 256 | 98.27 81 | 98.06 133 |
|
alignmvs | | | 95.87 57 | 95.23 61 | 97.78 21 | 97.56 119 | 95.19 8 | 97.86 50 | 97.17 159 | 94.39 33 | 96.47 45 | 96.40 138 | 85.89 107 | 99.20 101 | 96.21 28 | 95.11 148 | 98.95 75 |
|
conf0.01 | | | 91.74 180 | 90.67 199 | 94.94 157 | 97.55 120 | 89.68 153 | 97.64 78 | 93.14 327 | 88.43 207 | 91.24 168 | 94.30 241 | 78.91 237 | 98.45 171 | 81.28 289 | 93.57 180 | 96.70 179 |
|
conf0.002 | | | 91.74 180 | 90.67 199 | 94.94 157 | 97.55 120 | 89.68 153 | 97.64 78 | 93.14 327 | 88.43 207 | 91.24 168 | 94.30 241 | 78.91 237 | 98.45 171 | 81.28 289 | 93.57 180 | 96.70 179 |
|
thresconf0.02 | | | 91.69 187 | 90.67 199 | 94.75 166 | 97.55 120 | 89.68 153 | 97.64 78 | 93.14 327 | 88.43 207 | 91.24 168 | 94.30 241 | 78.91 237 | 98.45 171 | 81.28 289 | 93.57 180 | 96.11 199 |
|
tfpn_n400 | | | 91.69 187 | 90.67 199 | 94.75 166 | 97.55 120 | 89.68 153 | 97.64 78 | 93.14 327 | 88.43 207 | 91.24 168 | 94.30 241 | 78.91 237 | 98.45 171 | 81.28 289 | 93.57 180 | 96.11 199 |
|
tfpnconf | | | 91.69 187 | 90.67 199 | 94.75 166 | 97.55 120 | 89.68 153 | 97.64 78 | 93.14 327 | 88.43 207 | 91.24 168 | 94.30 241 | 78.91 237 | 98.45 171 | 81.28 289 | 93.57 180 | 96.11 199 |
|
tfpnview11 | | | 91.69 187 | 90.67 199 | 94.75 166 | 97.55 120 | 89.68 153 | 97.64 78 | 93.14 327 | 88.43 207 | 91.24 168 | 94.30 241 | 78.91 237 | 98.45 171 | 81.28 289 | 93.57 180 | 96.11 199 |
|
EPP-MVSNet | | | 95.22 69 | 95.04 65 | 95.76 110 | 97.49 126 | 89.56 163 | 98.67 5 | 97.00 183 | 90.69 138 | 94.24 97 | 97.62 78 | 89.79 61 | 98.81 142 | 93.39 91 | 96.49 129 | 98.92 78 |
|
PS-MVSNAJ | | | 95.37 63 | 95.33 59 | 95.49 126 | 97.35 127 | 90.66 130 | 95.31 264 | 97.48 125 | 93.85 43 | 96.51 43 | 95.70 174 | 88.65 71 | 99.65 41 | 94.80 65 | 98.27 81 | 96.17 194 |
|
casdiffmvs1 | | | 95.77 58 | 95.55 52 | 96.44 80 | 97.30 128 | 91.43 103 | 97.57 92 | 97.58 115 | 91.21 126 | 96.65 36 | 96.60 130 | 89.18 63 | 98.83 140 | 96.27 22 | 97.60 97 | 99.05 64 |
|
ab-mvs | | | 93.57 116 | 92.55 128 | 96.64 64 | 97.28 129 | 91.96 88 | 95.40 260 | 97.45 134 | 89.81 162 | 93.22 121 | 96.28 142 | 79.62 222 | 99.46 81 | 90.74 135 | 93.11 186 | 98.50 107 |
|
xiu_mvs_v2_base | | | 95.32 65 | 95.29 60 | 95.40 131 | 97.22 130 | 90.50 133 | 95.44 259 | 97.44 137 | 93.70 49 | 96.46 46 | 96.18 145 | 88.59 74 | 99.53 71 | 94.79 67 | 97.81 92 | 96.17 194 |
|
BH-untuned | | | 92.94 134 | 92.62 125 | 93.92 206 | 97.22 130 | 86.16 266 | 96.40 205 | 96.25 225 | 90.06 155 | 89.79 208 | 96.17 148 | 83.19 135 | 98.35 183 | 87.19 201 | 97.27 109 | 97.24 161 |
|
Vis-MVSNet | | | 95.23 67 | 94.81 68 | 96.51 74 | 97.18 132 | 91.58 98 | 98.26 24 | 98.12 44 | 94.38 34 | 94.90 85 | 98.15 42 | 82.28 173 | 98.92 131 | 91.45 127 | 98.58 76 | 99.01 69 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
BH-RMVSNet | | | 92.72 143 | 91.97 143 | 94.97 152 | 97.16 133 | 87.99 229 | 96.15 226 | 95.60 255 | 90.62 143 | 91.87 149 | 97.15 101 | 78.41 249 | 98.57 162 | 83.16 261 | 97.60 97 | 98.36 123 |
|
MSDG | | | 91.42 205 | 90.24 218 | 94.96 153 | 97.15 134 | 88.91 195 | 93.69 297 | 96.32 221 | 85.72 271 | 86.93 273 | 96.47 135 | 80.24 212 | 98.98 129 | 80.57 297 | 95.05 149 | 96.98 164 |
|
HY-MVS | | 89.66 9 | 93.87 105 | 92.95 114 | 96.63 66 | 97.10 135 | 92.49 72 | 95.64 251 | 96.64 212 | 89.05 183 | 93.00 127 | 95.79 167 | 85.77 110 | 99.45 83 | 89.16 159 | 94.35 157 | 97.96 134 |
|
XVG-OURS | | | 93.72 111 | 93.35 107 | 94.80 162 | 97.07 136 | 88.61 200 | 94.79 274 | 97.46 130 | 91.97 106 | 93.99 100 | 97.86 58 | 81.74 185 | 98.88 137 | 92.64 100 | 92.67 192 | 96.92 172 |
|
sss | | | 94.51 87 | 93.80 90 | 96.64 64 | 97.07 136 | 91.97 87 | 96.32 213 | 98.06 59 | 88.94 189 | 94.50 92 | 96.78 111 | 84.60 121 | 99.27 98 | 91.90 113 | 96.02 133 | 98.68 96 |
|
XVG-OURS-SEG-HR | | | 93.86 106 | 93.55 97 | 94.81 161 | 97.06 138 | 88.53 202 | 95.28 265 | 97.45 134 | 91.68 111 | 94.08 99 | 97.68 70 | 82.41 171 | 98.90 133 | 93.84 80 | 92.47 193 | 96.98 164 |
|
1112_ss | | | 93.37 120 | 92.42 134 | 96.21 96 | 97.05 139 | 90.99 118 | 96.31 214 | 96.72 204 | 86.87 257 | 89.83 206 | 96.69 118 | 86.51 100 | 99.14 109 | 88.12 176 | 93.67 174 | 98.50 107 |
|
Test_1112_low_res | | | 92.84 140 | 91.84 146 | 95.85 107 | 97.04 140 | 89.97 144 | 95.53 255 | 96.64 212 | 85.38 273 | 89.65 216 | 95.18 196 | 85.86 108 | 99.10 117 | 87.70 185 | 93.58 179 | 98.49 109 |
|
BH-w/o | | | 92.14 169 | 91.75 148 | 93.31 240 | 96.99 141 | 85.73 269 | 95.67 248 | 95.69 251 | 88.73 200 | 89.26 230 | 94.82 213 | 82.97 153 | 98.07 210 | 85.26 232 | 96.32 132 | 96.13 198 |
|
casdiffmvs | | | 95.23 67 | 94.84 67 | 96.40 82 | 96.90 142 | 91.71 90 | 97.36 110 | 97.30 152 | 91.02 132 | 94.81 87 | 96.18 145 | 87.74 82 | 98.77 146 | 95.65 42 | 96.55 127 | 98.71 93 |
|
3Dnovator+ | | 91.43 4 | 95.40 62 | 94.48 80 | 98.16 7 | 96.90 142 | 95.34 7 | 98.48 14 | 97.87 88 | 94.65 29 | 88.53 241 | 98.02 48 | 83.69 130 | 99.71 29 | 93.18 93 | 98.96 66 | 99.44 32 |
|
UGNet | | | 94.04 101 | 93.28 109 | 96.31 89 | 96.85 144 | 91.19 112 | 97.88 49 | 97.68 106 | 94.40 32 | 93.00 127 | 96.18 145 | 73.39 294 | 99.61 47 | 91.72 118 | 98.46 77 | 98.13 128 |
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 |
VDDNet | | | 93.05 130 | 92.07 138 | 96.02 101 | 96.84 145 | 90.39 136 | 98.08 33 | 95.85 246 | 86.22 265 | 95.79 69 | 98.46 15 | 67.59 320 | 99.19 102 | 94.92 61 | 94.85 150 | 98.47 112 |
|
RPSCF | | | 90.75 230 | 90.86 187 | 90.42 310 | 96.84 145 | 76.29 334 | 95.61 252 | 96.34 220 | 83.89 293 | 91.38 157 | 97.87 56 | 76.45 270 | 98.78 144 | 87.16 203 | 92.23 196 | 96.20 192 |
|
MVS_Test | | | 94.89 80 | 94.62 73 | 95.68 117 | 96.83 147 | 89.55 164 | 96.70 179 | 97.17 159 | 91.17 127 | 95.60 76 | 96.11 151 | 87.87 81 | 98.76 148 | 93.01 97 | 97.17 111 | 98.72 91 |
|
LCM-MVSNet-Re | | | 92.50 149 | 92.52 131 | 92.44 263 | 96.82 148 | 81.89 306 | 96.92 152 | 93.71 320 | 92.41 87 | 84.30 294 | 94.60 223 | 85.08 116 | 97.03 297 | 91.51 124 | 97.36 106 | 98.40 119 |
|
Fast-Effi-MVS+ | | | 93.46 118 | 92.75 120 | 95.59 120 | 96.77 149 | 90.03 138 | 96.81 163 | 97.13 164 | 88.19 221 | 91.30 163 | 94.27 251 | 86.21 103 | 98.63 156 | 87.66 189 | 96.46 131 | 98.12 129 |
|
QAPM | | | 93.45 119 | 92.27 136 | 96.98 60 | 96.77 149 | 92.62 68 | 98.39 18 | 98.12 44 | 84.50 287 | 88.27 247 | 97.77 65 | 82.39 172 | 99.81 19 | 85.40 229 | 98.81 69 | 98.51 105 |
|
CHOSEN 280x420 | | | 93.12 127 | 92.72 122 | 94.34 184 | 96.71 151 | 87.27 245 | 90.29 334 | 97.72 100 | 86.61 261 | 91.34 160 | 95.29 192 | 84.29 126 | 98.41 178 | 93.25 92 | 98.94 67 | 97.35 160 |
|
Effi-MVS+ | | | 94.93 78 | 94.45 81 | 96.36 87 | 96.61 152 | 91.47 100 | 96.41 201 | 97.41 141 | 91.02 132 | 94.50 92 | 95.92 157 | 87.53 88 | 98.78 144 | 93.89 78 | 96.81 118 | 98.84 86 |
|
PCF-MVS | | 89.48 11 | 91.56 198 | 89.95 229 | 96.36 87 | 96.60 153 | 92.52 71 | 92.51 318 | 97.26 154 | 79.41 326 | 88.90 233 | 96.56 131 | 84.04 127 | 99.55 66 | 77.01 316 | 97.30 108 | 97.01 163 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
xiu_mvs_v1_base_debu | | | 95.01 73 | 94.76 69 | 95.75 112 | 96.58 154 | 91.71 90 | 96.25 220 | 97.35 148 | 92.99 69 | 96.70 33 | 96.63 125 | 82.67 162 | 99.44 84 | 96.22 25 | 97.46 100 | 96.11 199 |
|
xiu_mvs_v1_base | | | 95.01 73 | 94.76 69 | 95.75 112 | 96.58 154 | 91.71 90 | 96.25 220 | 97.35 148 | 92.99 69 | 96.70 33 | 96.63 125 | 82.67 162 | 99.44 84 | 96.22 25 | 97.46 100 | 96.11 199 |
|
xiu_mvs_v1_base_debi | | | 95.01 73 | 94.76 69 | 95.75 112 | 96.58 154 | 91.71 90 | 96.25 220 | 97.35 148 | 92.99 69 | 96.70 33 | 96.63 125 | 82.67 162 | 99.44 84 | 96.22 25 | 97.46 100 | 96.11 199 |
|
MVSTER | | | 93.20 125 | 92.81 117 | 94.37 182 | 96.56 157 | 89.59 162 | 97.06 137 | 97.12 165 | 91.24 124 | 91.30 163 | 95.96 154 | 82.02 179 | 98.05 218 | 93.48 87 | 90.55 226 | 95.47 229 |
|
3Dnovator | | 91.36 5 | 95.19 71 | 94.44 82 | 97.44 40 | 96.56 157 | 93.36 52 | 98.65 6 | 98.36 16 | 94.12 38 | 89.25 231 | 98.06 46 | 82.20 176 | 99.77 22 | 93.41 90 | 99.32 41 | 99.18 52 |
|
FMVSNet3 | | | 91.78 179 | 90.69 198 | 95.03 148 | 96.53 159 | 92.27 76 | 97.02 140 | 96.93 193 | 89.79 163 | 89.35 225 | 94.65 221 | 77.01 268 | 97.47 279 | 86.12 216 | 88.82 241 | 95.35 241 |
|
GBi-Net | | | 91.35 209 | 90.27 216 | 94.59 172 | 96.51 160 | 91.18 113 | 97.50 97 | 96.93 193 | 88.82 195 | 89.35 225 | 94.51 225 | 73.87 288 | 97.29 291 | 86.12 216 | 88.82 241 | 95.31 243 |
|
test1 | | | 91.35 209 | 90.27 216 | 94.59 172 | 96.51 160 | 91.18 113 | 97.50 97 | 96.93 193 | 88.82 195 | 89.35 225 | 94.51 225 | 73.87 288 | 97.29 291 | 86.12 216 | 88.82 241 | 95.31 243 |
|
FMVSNet2 | | | 91.31 212 | 90.08 223 | 94.99 149 | 96.51 160 | 92.21 77 | 97.41 103 | 96.95 191 | 88.82 195 | 88.62 238 | 94.75 217 | 73.87 288 | 97.42 283 | 85.20 233 | 88.55 247 | 95.35 241 |
|
ACMH+ | | 87.92 14 | 90.20 246 | 89.18 250 | 93.25 242 | 96.48 163 | 86.45 263 | 96.99 143 | 96.68 209 | 88.83 194 | 84.79 291 | 96.22 144 | 70.16 310 | 98.53 164 | 84.42 245 | 88.04 249 | 94.77 280 |
|
CANet_DTU | | | 94.37 89 | 93.65 95 | 96.55 70 | 96.46 164 | 92.13 81 | 96.21 224 | 96.67 211 | 94.38 34 | 93.53 110 | 97.03 105 | 79.34 225 | 99.71 29 | 90.76 134 | 98.45 78 | 97.82 143 |
|
mvs_anonymous | | | 93.82 107 | 93.74 91 | 94.06 193 | 96.44 165 | 85.41 274 | 95.81 243 | 97.05 175 | 89.85 160 | 90.09 197 | 96.36 140 | 87.44 90 | 97.75 261 | 93.97 74 | 96.69 123 | 99.02 65 |
|
TR-MVS | | | 91.48 202 | 90.59 207 | 94.16 190 | 96.40 166 | 87.33 243 | 95.67 248 | 95.34 268 | 87.68 234 | 91.46 156 | 95.52 183 | 76.77 269 | 98.35 183 | 82.85 266 | 93.61 177 | 96.79 176 |
|
ACMP | | 89.59 10 | 92.62 144 | 92.14 137 | 94.05 194 | 96.40 166 | 88.20 215 | 97.36 110 | 97.25 156 | 91.52 113 | 88.30 245 | 96.64 121 | 78.46 248 | 98.72 152 | 91.86 116 | 91.48 211 | 95.23 250 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
MVSFormer | | | 95.37 63 | 95.16 63 | 95.99 103 | 96.34 168 | 91.21 109 | 98.22 26 | 97.57 116 | 91.42 118 | 96.22 51 | 97.32 92 | 86.20 104 | 97.92 245 | 94.07 72 | 99.05 62 | 98.85 84 |
|
lupinMVS | | | 94.99 77 | 94.56 75 | 96.29 92 | 96.34 168 | 91.21 109 | 95.83 242 | 96.27 223 | 88.93 190 | 96.22 51 | 96.88 109 | 86.20 104 | 98.85 138 | 95.27 49 | 99.05 62 | 98.82 87 |
|
diffmvs | | | 94.47 88 | 94.23 84 | 95.18 135 | 96.32 170 | 88.22 212 | 96.27 218 | 97.04 178 | 92.55 84 | 93.60 106 | 95.94 156 | 86.79 97 | 98.70 153 | 92.98 98 | 96.61 125 | 98.63 98 |
|
ACMM | | 89.79 8 | 92.96 133 | 92.50 132 | 94.35 183 | 96.30 171 | 88.71 198 | 97.58 90 | 97.36 147 | 91.40 120 | 90.53 180 | 96.65 120 | 79.77 219 | 98.75 149 | 91.24 131 | 91.64 207 | 95.59 225 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
IterMVS-LS | | | 92.29 162 | 91.94 144 | 93.34 239 | 96.25 172 | 86.97 255 | 96.57 195 | 97.05 175 | 90.67 139 | 89.50 222 | 94.80 215 | 86.59 98 | 97.64 269 | 89.91 141 | 86.11 264 | 95.40 237 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
HQP_MVS | | | 93.78 109 | 93.43 104 | 94.82 159 | 96.21 173 | 89.99 141 | 97.74 61 | 97.51 123 | 94.85 18 | 91.34 160 | 96.64 121 | 81.32 191 | 98.60 159 | 93.02 95 | 92.23 196 | 95.86 209 |
|
plane_prior7 | | | | | | 96.21 173 | 89.98 143 | | | | | | | | | | |
|
ACMH | | 87.59 16 | 90.53 239 | 89.42 245 | 93.87 207 | 96.21 173 | 87.92 234 | 97.24 120 | 96.94 192 | 88.45 206 | 83.91 300 | 96.27 143 | 71.92 297 | 98.62 158 | 84.43 244 | 89.43 237 | 95.05 261 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
CDS-MVSNet | | | 94.14 96 | 93.54 98 | 95.93 104 | 96.18 176 | 91.46 101 | 96.33 212 | 97.04 178 | 88.97 188 | 93.56 107 | 96.51 133 | 87.55 87 | 97.89 249 | 89.80 143 | 95.95 135 | 98.44 116 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
LTVRE_ROB | | 88.41 13 | 90.99 222 | 89.92 230 | 94.19 188 | 96.18 176 | 89.55 164 | 96.31 214 | 97.09 169 | 87.88 229 | 85.67 283 | 95.91 158 | 78.79 245 | 98.57 162 | 81.50 281 | 89.98 232 | 94.44 290 |
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 |
LPG-MVS_test | | | 92.94 134 | 92.56 127 | 94.10 191 | 96.16 178 | 88.26 208 | 97.65 74 | 97.46 130 | 91.29 121 | 90.12 194 | 97.16 99 | 79.05 229 | 98.73 150 | 92.25 103 | 91.89 204 | 95.31 243 |
|
LGP-MVS_train | | | | | 94.10 191 | 96.16 178 | 88.26 208 | | 97.46 130 | 91.29 121 | 90.12 194 | 97.16 99 | 79.05 229 | 98.73 150 | 92.25 103 | 91.89 204 | 95.31 243 |
|
TAMVS | | | 94.01 102 | 93.46 102 | 95.64 118 | 96.16 178 | 90.45 135 | 96.71 176 | 96.89 197 | 89.27 172 | 93.46 112 | 96.92 108 | 87.29 92 | 97.94 241 | 88.70 171 | 95.74 139 | 98.53 102 |
|
plane_prior1 | | | | | | 96.14 181 | | | | | | | | | | | |
|
CLD-MVS | | | 92.98 132 | 92.53 130 | 94.32 185 | 96.12 182 | 89.20 189 | 95.28 265 | 97.47 128 | 92.66 81 | 89.90 201 | 95.62 177 | 80.58 205 | 98.40 179 | 92.73 99 | 92.40 194 | 95.38 239 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
plane_prior6 | | | | | | 96.10 183 | 90.00 139 | | | | | | 81.32 191 | | | | |
|
Effi-MVS+-dtu | | | 93.08 128 | 93.21 110 | 92.68 260 | 96.02 184 | 83.25 297 | 97.14 134 | 96.72 204 | 93.85 43 | 91.20 175 | 93.44 281 | 83.08 143 | 98.30 188 | 91.69 121 | 95.73 140 | 96.50 186 |
|
mvs-test1 | | | 93.63 113 | 93.69 93 | 93.46 234 | 96.02 184 | 84.61 284 | 97.24 120 | 96.72 204 | 93.85 43 | 92.30 141 | 95.76 169 | 83.08 143 | 98.89 135 | 91.69 121 | 96.54 128 | 96.87 174 |
|
NP-MVS | | | | | | 95.99 186 | 89.81 150 | | | | | 95.87 159 | | | | | |
|
ADS-MVSNet2 | | | 89.45 259 | 88.59 257 | 92.03 278 | 95.86 187 | 82.26 304 | 90.93 330 | 94.32 310 | 83.23 301 | 91.28 166 | 91.81 306 | 79.01 233 | 95.99 319 | 79.52 302 | 91.39 213 | 97.84 140 |
|
ADS-MVSNet | | | 89.89 252 | 88.68 256 | 93.53 230 | 95.86 187 | 84.89 281 | 90.93 330 | 95.07 281 | 83.23 301 | 91.28 166 | 91.81 306 | 79.01 233 | 97.85 251 | 79.52 302 | 91.39 213 | 97.84 140 |
|
HQP-NCC | | | | | | 95.86 187 | | 96.65 184 | | 93.55 50 | 90.14 188 | | | | | | |
|
ACMP_Plane | | | | | | 95.86 187 | | 96.65 184 | | 93.55 50 | 90.14 188 | | | | | | |
|
HQP-MVS | | | 93.19 126 | 92.74 121 | 94.54 177 | 95.86 187 | 89.33 181 | 96.65 184 | 97.39 142 | 93.55 50 | 90.14 188 | 95.87 159 | 80.95 196 | 98.50 167 | 92.13 107 | 92.10 201 | 95.78 216 |
|
EI-MVSNet | | | 93.03 131 | 92.88 116 | 93.48 232 | 95.77 192 | 86.98 254 | 96.44 197 | 97.12 165 | 90.66 141 | 91.30 163 | 97.64 76 | 86.56 99 | 98.05 218 | 89.91 141 | 90.55 226 | 95.41 233 |
|
CVMVSNet | | | 91.23 214 | 91.75 148 | 89.67 316 | 95.77 192 | 74.69 336 | 96.44 197 | 94.88 290 | 85.81 269 | 92.18 143 | 97.64 76 | 79.07 228 | 95.58 327 | 88.06 177 | 95.86 138 | 98.74 89 |
|
FIs | | | 94.09 98 | 93.70 92 | 95.27 133 | 95.70 194 | 92.03 84 | 98.10 31 | 98.68 7 | 93.36 57 | 90.39 184 | 96.70 116 | 87.63 86 | 97.94 241 | 92.25 103 | 90.50 228 | 95.84 212 |
|
VPA-MVSNet | | | 93.24 124 | 92.48 133 | 95.51 124 | 95.70 194 | 92.39 73 | 97.86 50 | 98.66 9 | 92.30 88 | 92.09 146 | 95.37 190 | 80.49 207 | 98.40 179 | 93.95 75 | 85.86 265 | 95.75 220 |
|
Patchmatch-test1 | | | 91.54 200 | 90.85 188 | 93.59 226 | 95.59 196 | 84.95 280 | 94.72 275 | 95.58 257 | 90.82 134 | 92.25 142 | 93.58 274 | 75.80 274 | 97.41 284 | 83.35 258 | 95.98 134 | 98.40 119 |
|
VPNet | | | 92.23 165 | 91.31 170 | 94.99 149 | 95.56 197 | 90.96 120 | 97.22 125 | 97.86 90 | 92.96 75 | 90.96 176 | 96.62 128 | 75.06 280 | 98.20 192 | 91.90 113 | 83.65 302 | 95.80 215 |
|
semantic-postprocess | | | | | 91.82 283 | 95.52 198 | 84.20 287 | | 96.15 230 | 90.61 145 | 87.39 263 | 94.27 251 | 75.63 276 | 96.44 306 | 87.34 197 | 86.88 260 | 94.82 274 |
|
jason | | | 94.84 82 | 94.39 83 | 96.18 97 | 95.52 198 | 90.93 122 | 96.09 229 | 96.52 216 | 89.28 171 | 96.01 61 | 97.32 92 | 84.70 120 | 98.77 146 | 95.15 52 | 98.91 68 | 98.85 84 |
jason: jason. |
FC-MVSNet-test | | | 93.94 104 | 93.57 96 | 95.04 147 | 95.48 200 | 91.45 102 | 98.12 30 | 98.71 5 | 93.37 55 | 90.23 187 | 96.70 116 | 87.66 84 | 97.85 251 | 91.49 125 | 90.39 229 | 95.83 213 |
|
IterMVS | | | 90.15 248 | 89.67 240 | 91.61 290 | 95.48 200 | 83.72 290 | 94.33 283 | 96.12 231 | 89.99 156 | 87.31 266 | 94.15 256 | 75.78 275 | 96.27 309 | 86.97 205 | 86.89 259 | 94.83 272 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
FMVSNet1 | | | 89.88 253 | 88.31 261 | 94.59 172 | 95.41 202 | 91.18 113 | 97.50 97 | 96.93 193 | 86.62 260 | 87.41 262 | 94.51 225 | 65.94 328 | 97.29 291 | 83.04 263 | 87.43 255 | 95.31 243 |
|
UniMVSNet (Re) | | | 93.31 122 | 92.55 128 | 95.61 119 | 95.39 203 | 93.34 53 | 97.39 107 | 98.71 5 | 93.14 65 | 90.10 196 | 94.83 212 | 87.71 83 | 98.03 224 | 91.67 123 | 83.99 295 | 95.46 230 |
|
MVS-HIRNet | | | 82.47 314 | 81.21 315 | 86.26 326 | 95.38 204 | 69.21 346 | 88.96 342 | 89.49 351 | 66.28 348 | 80.79 315 | 74.08 351 | 68.48 316 | 97.39 286 | 71.93 330 | 95.47 142 | 92.18 332 |
|
PatchmatchNet | | | 91.91 176 | 91.35 167 | 93.59 226 | 95.38 204 | 84.11 288 | 93.15 309 | 95.39 262 | 89.54 164 | 92.10 145 | 93.68 270 | 82.82 160 | 98.13 198 | 84.81 236 | 95.32 144 | 98.52 103 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
UniMVSNet_NR-MVSNet | | | 93.37 120 | 92.67 123 | 95.47 128 | 95.34 206 | 92.83 62 | 97.17 131 | 98.58 10 | 92.98 74 | 90.13 192 | 95.80 164 | 88.37 76 | 97.85 251 | 91.71 119 | 83.93 296 | 95.73 222 |
|
ITE_SJBPF | | | | | 92.43 264 | 95.34 206 | 85.37 275 | | 95.92 238 | 91.47 115 | 87.75 255 | 96.39 139 | 71.00 304 | 97.96 239 | 82.36 273 | 89.86 235 | 93.97 301 |
|
OpenMVS | | 89.19 12 | 92.86 138 | 91.68 151 | 96.40 82 | 95.34 206 | 92.73 65 | 98.27 23 | 98.12 44 | 84.86 282 | 85.78 282 | 97.75 66 | 78.89 244 | 99.74 24 | 87.50 194 | 98.65 73 | 96.73 177 |
|
1314 | | | 92.81 141 | 92.03 140 | 95.14 142 | 95.33 209 | 89.52 167 | 96.04 231 | 97.44 137 | 87.72 233 | 86.25 279 | 95.33 191 | 83.84 128 | 98.79 143 | 89.26 154 | 97.05 113 | 97.11 162 |
|
PAPM | | | 91.52 201 | 90.30 214 | 95.20 134 | 95.30 210 | 89.83 149 | 93.38 304 | 96.85 200 | 86.26 264 | 88.59 240 | 95.80 164 | 84.88 118 | 98.15 197 | 75.67 320 | 95.93 136 | 97.63 148 |
|
Fast-Effi-MVS+-dtu | | | 92.29 162 | 91.99 142 | 93.21 245 | 95.27 211 | 85.52 273 | 97.03 138 | 96.63 214 | 92.09 97 | 89.11 232 | 95.14 198 | 80.33 211 | 98.08 206 | 87.54 193 | 94.74 155 | 96.03 206 |
|
Patchmatch-test | | | 89.42 260 | 87.99 264 | 93.70 220 | 95.27 211 | 85.11 276 | 88.98 341 | 94.37 308 | 81.11 316 | 87.10 270 | 93.69 269 | 82.28 173 | 97.50 277 | 74.37 323 | 94.76 153 | 98.48 111 |
|
PVSNet_0 | | 82.17 19 | 85.46 304 | 83.64 305 | 90.92 301 | 95.27 211 | 79.49 325 | 90.55 333 | 95.60 255 | 83.76 296 | 83.00 303 | 89.95 313 | 71.09 303 | 97.97 235 | 82.75 268 | 60.79 350 | 95.31 243 |
|
IB-MVS | | 87.33 17 | 89.91 251 | 88.28 262 | 94.79 164 | 95.26 214 | 87.70 240 | 95.12 271 | 93.95 319 | 89.35 170 | 87.03 271 | 92.49 294 | 70.74 306 | 99.19 102 | 89.18 158 | 81.37 315 | 97.49 157 |
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 |
PatchFormer-LS_test | | | 91.68 192 | 91.18 177 | 93.19 246 | 95.24 215 | 83.63 294 | 95.53 255 | 95.44 261 | 89.82 161 | 91.37 158 | 92.58 293 | 80.85 203 | 98.52 165 | 89.65 149 | 90.16 231 | 97.42 159 |
|
nrg030 | | | 94.05 100 | 93.31 108 | 96.27 93 | 95.22 216 | 94.59 15 | 98.34 19 | 97.46 130 | 92.93 76 | 91.21 174 | 96.64 121 | 87.23 93 | 98.22 191 | 94.99 60 | 85.80 266 | 95.98 207 |
|
MDTV_nov1_ep13 | | | | 90.76 193 | | 95.22 216 | 80.33 318 | 93.03 312 | 95.28 269 | 88.14 224 | 92.84 133 | 93.83 264 | 81.34 190 | 98.08 206 | 82.86 265 | 94.34 158 | |
|
MVS | | | 91.71 182 | 90.44 209 | 95.51 124 | 95.20 218 | 91.59 97 | 96.04 231 | 97.45 134 | 73.44 345 | 87.36 264 | 95.60 178 | 85.42 112 | 99.10 117 | 85.97 220 | 97.46 100 | 95.83 213 |
|
tpmp4_e23 | | | 89.58 257 | 88.59 257 | 92.54 262 | 95.16 219 | 81.53 308 | 94.11 289 | 95.09 279 | 81.66 311 | 88.60 239 | 93.44 281 | 75.11 279 | 98.33 186 | 82.45 271 | 91.72 206 | 97.75 144 |
|
tfpnnormal | | | 89.70 256 | 88.40 260 | 93.60 225 | 95.15 220 | 90.10 137 | 97.56 93 | 98.16 39 | 87.28 243 | 86.16 280 | 94.63 222 | 77.57 266 | 98.05 218 | 74.48 321 | 84.59 290 | 92.65 316 |
|
tpmrst | | | 91.44 204 | 91.32 169 | 91.79 285 | 95.15 220 | 79.20 328 | 93.42 303 | 95.37 264 | 88.55 204 | 93.49 111 | 93.67 271 | 82.49 168 | 98.27 189 | 90.41 138 | 89.34 238 | 97.90 137 |
|
WR-MVS | | | 92.34 158 | 91.53 162 | 94.77 165 | 95.13 222 | 90.83 125 | 96.40 205 | 97.98 79 | 91.88 107 | 89.29 228 | 95.54 182 | 82.50 167 | 97.80 256 | 89.79 144 | 85.27 273 | 95.69 223 |
|
tpm cat1 | | | 88.36 281 | 87.21 281 | 91.81 284 | 95.13 222 | 80.55 316 | 92.58 317 | 95.70 250 | 74.97 341 | 87.45 260 | 91.96 304 | 78.01 263 | 98.17 196 | 80.39 299 | 88.74 244 | 96.72 178 |
|
WR-MVS_H | | | 92.00 173 | 91.35 167 | 93.95 202 | 95.09 224 | 89.47 168 | 98.04 36 | 98.68 7 | 91.46 116 | 88.34 243 | 94.68 219 | 85.86 108 | 97.56 273 | 85.77 223 | 84.24 293 | 94.82 274 |
|
CP-MVSNet | | | 91.89 177 | 91.24 173 | 93.82 208 | 95.05 225 | 88.57 201 | 97.82 55 | 98.19 34 | 91.70 110 | 88.21 249 | 95.76 169 | 81.96 180 | 97.52 276 | 87.86 181 | 84.65 289 | 95.37 240 |
|
DWT-MVSNet_test | | | 90.76 228 | 89.89 231 | 93.38 237 | 95.04 226 | 83.70 292 | 95.85 241 | 94.30 311 | 88.19 221 | 90.46 182 | 92.80 288 | 73.61 292 | 98.50 167 | 88.16 175 | 90.58 225 | 97.95 135 |
|
test_0402 | | | 86.46 296 | 84.79 299 | 91.45 293 | 95.02 227 | 85.55 272 | 96.29 216 | 94.89 289 | 80.90 317 | 82.21 304 | 93.97 260 | 68.21 318 | 97.29 291 | 62.98 342 | 88.68 246 | 91.51 336 |
|
cascas | | | 91.20 215 | 90.08 223 | 94.58 176 | 94.97 228 | 89.16 192 | 93.65 299 | 97.59 114 | 79.90 324 | 89.40 223 | 92.92 287 | 75.36 278 | 98.36 182 | 92.14 106 | 94.75 154 | 96.23 191 |
|
PS-CasMVS | | | 91.55 199 | 90.84 190 | 93.69 221 | 94.96 229 | 88.28 207 | 97.84 54 | 98.24 29 | 91.46 116 | 88.04 251 | 95.80 164 | 79.67 221 | 97.48 278 | 87.02 204 | 84.54 291 | 95.31 243 |
|
DU-MVS | | | 92.90 136 | 92.04 139 | 95.49 126 | 94.95 230 | 92.83 62 | 97.16 132 | 98.24 29 | 93.02 68 | 90.13 192 | 95.71 172 | 83.47 132 | 97.85 251 | 91.71 119 | 83.93 296 | 95.78 216 |
|
NR-MVSNet | | | 92.34 158 | 91.27 172 | 95.53 123 | 94.95 230 | 93.05 57 | 97.39 107 | 98.07 57 | 92.65 82 | 84.46 292 | 95.71 172 | 85.00 117 | 97.77 260 | 89.71 145 | 83.52 303 | 95.78 216 |
|
Anonymous20240521 | | | 91.32 211 | 90.43 211 | 93.98 197 | 94.93 232 | 89.28 186 | 98.04 36 | 97.53 120 | 89.49 167 | 86.68 276 | 94.82 213 | 81.72 186 | 98.05 218 | 85.31 230 | 85.39 270 | 94.61 285 |
|
tpmvs | | | 89.83 255 | 89.15 251 | 91.89 281 | 94.92 233 | 80.30 319 | 93.11 310 | 95.46 260 | 86.28 263 | 88.08 250 | 92.65 290 | 80.44 208 | 98.52 165 | 81.47 282 | 89.92 234 | 96.84 175 |
|
PMMVS | | | 92.86 138 | 92.34 135 | 94.42 181 | 94.92 233 | 86.73 258 | 94.53 279 | 96.38 219 | 84.78 284 | 94.27 96 | 95.12 200 | 83.13 139 | 98.40 179 | 91.47 126 | 96.49 129 | 98.12 129 |
|
tpm2 | | | 89.96 250 | 89.21 249 | 92.23 269 | 94.91 235 | 81.25 310 | 93.78 294 | 94.42 306 | 80.62 321 | 91.56 154 | 93.44 281 | 76.44 271 | 97.94 241 | 85.60 226 | 92.08 203 | 97.49 157 |
|
TinyColmap | | | 86.82 294 | 85.35 296 | 91.21 296 | 94.91 235 | 82.99 298 | 93.94 292 | 94.02 318 | 83.58 297 | 81.56 311 | 94.68 219 | 62.34 335 | 98.13 198 | 75.78 318 | 87.35 258 | 92.52 319 |
|
CostFormer | | | 91.18 218 | 90.70 197 | 92.62 261 | 94.84 237 | 81.76 307 | 94.09 290 | 94.43 305 | 84.15 290 | 92.72 134 | 93.77 267 | 79.43 224 | 98.20 192 | 90.70 136 | 92.18 199 | 97.90 137 |
|
MIMVSNet | | | 88.50 276 | 86.76 285 | 93.72 219 | 94.84 237 | 87.77 238 | 91.39 325 | 94.05 316 | 86.41 262 | 87.99 252 | 92.59 292 | 63.27 332 | 95.82 323 | 77.44 312 | 92.84 189 | 97.57 155 |
|
FMVSNet5 | | | 87.29 291 | 85.79 292 | 91.78 286 | 94.80 239 | 87.28 244 | 95.49 257 | 95.28 269 | 84.09 291 | 83.85 301 | 91.82 305 | 62.95 333 | 94.17 334 | 78.48 309 | 85.34 272 | 93.91 302 |
|
TranMVSNet+NR-MVSNet | | | 92.50 149 | 91.63 156 | 95.14 142 | 94.76 240 | 92.07 82 | 97.53 95 | 98.11 47 | 92.90 77 | 89.56 219 | 96.12 149 | 83.16 136 | 97.60 272 | 89.30 153 | 83.20 306 | 95.75 220 |
|
XXY-MVS | | | 92.16 167 | 91.23 174 | 94.95 154 | 94.75 241 | 90.94 121 | 97.47 101 | 97.43 139 | 89.14 181 | 88.90 233 | 96.43 137 | 79.71 220 | 98.24 190 | 89.56 150 | 87.68 252 | 95.67 224 |
|
EPMVS | | | 90.70 234 | 89.81 235 | 93.37 238 | 94.73 242 | 84.21 286 | 93.67 298 | 88.02 352 | 89.50 166 | 92.38 138 | 93.49 278 | 77.82 265 | 97.78 258 | 86.03 219 | 92.68 191 | 98.11 132 |
|
USDC | | | 88.94 263 | 87.83 266 | 92.27 265 | 94.66 243 | 84.96 279 | 93.86 293 | 95.90 240 | 87.34 241 | 83.40 302 | 95.56 180 | 67.43 321 | 98.19 194 | 82.64 270 | 89.67 236 | 93.66 304 |
|
GA-MVS | | | 91.38 207 | 90.31 213 | 94.59 172 | 94.65 244 | 87.62 241 | 94.34 282 | 96.19 228 | 90.73 137 | 90.35 185 | 93.83 264 | 71.84 298 | 97.96 239 | 87.22 200 | 93.61 177 | 98.21 126 |
|
OPM-MVS | | | 93.28 123 | 92.76 118 | 94.82 159 | 94.63 245 | 90.77 128 | 96.65 184 | 97.18 157 | 93.72 47 | 91.68 153 | 97.26 95 | 79.33 226 | 98.63 156 | 92.13 107 | 92.28 195 | 95.07 256 |
|
test-LLR | | | 91.42 205 | 91.19 176 | 92.12 275 | 94.59 246 | 80.66 313 | 94.29 284 | 92.98 333 | 91.11 129 | 90.76 178 | 92.37 296 | 79.02 231 | 98.07 210 | 88.81 169 | 96.74 120 | 97.63 148 |
|
test-mter | | | 90.19 247 | 89.54 243 | 92.12 275 | 94.59 246 | 80.66 313 | 94.29 284 | 92.98 333 | 87.68 234 | 90.76 178 | 92.37 296 | 67.67 319 | 98.07 210 | 88.81 169 | 96.74 120 | 97.63 148 |
|
dp | | | 88.90 265 | 88.26 263 | 90.81 303 | 94.58 248 | 76.62 333 | 92.85 314 | 94.93 288 | 85.12 278 | 90.07 199 | 93.07 285 | 75.81 273 | 98.12 201 | 80.53 298 | 87.42 256 | 97.71 146 |
|
PEN-MVS | | | 91.20 215 | 90.44 209 | 93.48 232 | 94.49 249 | 87.91 236 | 97.76 58 | 98.18 36 | 91.29 121 | 87.78 254 | 95.74 171 | 80.35 210 | 97.33 289 | 85.46 228 | 82.96 307 | 95.19 252 |
|
gg-mvs-nofinetune | | | 87.82 286 | 85.61 293 | 94.44 179 | 94.46 250 | 89.27 188 | 91.21 329 | 84.61 358 | 80.88 318 | 89.89 203 | 74.98 349 | 71.50 300 | 97.53 275 | 85.75 224 | 97.21 110 | 96.51 185 |
|
CR-MVSNet | | | 90.82 227 | 89.77 236 | 93.95 202 | 94.45 251 | 87.19 249 | 90.23 335 | 95.68 253 | 86.89 256 | 92.40 136 | 92.36 299 | 80.91 199 | 97.05 295 | 81.09 296 | 93.95 170 | 97.60 153 |
|
RPMNet | | | 88.52 274 | 86.72 287 | 93.95 202 | 94.45 251 | 87.19 249 | 90.23 335 | 94.99 285 | 77.87 335 | 92.40 136 | 87.55 339 | 80.17 214 | 97.05 295 | 68.84 336 | 93.95 170 | 97.60 153 |
|
TESTMET0.1,1 | | | 90.06 249 | 89.42 245 | 91.97 279 | 94.41 253 | 80.62 315 | 94.29 284 | 91.97 342 | 87.28 243 | 90.44 183 | 92.47 295 | 68.79 314 | 97.67 266 | 88.50 173 | 96.60 126 | 97.61 152 |
|
TransMVSNet (Re) | | | 88.94 263 | 87.56 267 | 93.08 248 | 94.35 254 | 88.45 205 | 97.73 63 | 95.23 273 | 87.47 237 | 84.26 295 | 95.29 192 | 79.86 218 | 97.33 289 | 79.44 306 | 74.44 341 | 93.45 307 |
|
MS-PatchMatch | | | 90.27 243 | 89.77 236 | 91.78 286 | 94.33 255 | 84.72 283 | 95.55 253 | 96.73 203 | 86.17 266 | 86.36 278 | 95.28 194 | 71.28 302 | 97.80 256 | 84.09 249 | 98.14 85 | 92.81 315 |
|
XVG-ACMP-BASELINE | | | 90.93 224 | 90.21 221 | 93.09 247 | 94.31 256 | 85.89 267 | 95.33 262 | 97.26 154 | 91.06 131 | 89.38 224 | 95.44 189 | 68.61 315 | 98.60 159 | 89.46 151 | 91.05 219 | 94.79 278 |
|
pcd1.5k->3k | | | 38.37 338 | 40.51 339 | 31.96 350 | 94.29 257 | 0.00 369 | 0.00 360 | 97.69 105 | 0.00 364 | 0.00 366 | 0.00 366 | 81.45 189 | 0.00 366 | 0.00 363 | 91.11 217 | 95.89 208 |
|
pm-mvs1 | | | 90.72 232 | 89.65 242 | 93.96 201 | 94.29 257 | 89.63 160 | 97.79 57 | 96.82 201 | 89.07 182 | 86.12 281 | 95.48 188 | 78.61 246 | 97.78 258 | 86.97 205 | 81.67 313 | 94.46 289 |
|
v1neww | | | 91.70 185 | 91.01 179 | 93.75 214 | 94.19 259 | 88.14 220 | 97.20 127 | 96.98 184 | 89.18 176 | 89.87 204 | 94.44 231 | 83.10 141 | 98.06 215 | 89.06 161 | 85.09 278 | 95.06 259 |
|
v7new | | | 91.70 185 | 91.01 179 | 93.75 214 | 94.19 259 | 88.14 220 | 97.20 127 | 96.98 184 | 89.18 176 | 89.87 204 | 94.44 231 | 83.10 141 | 98.06 215 | 89.06 161 | 85.09 278 | 95.06 259 |
|
v16 | | | 88.69 270 | 87.50 269 | 92.26 267 | 94.19 259 | 88.11 224 | 96.81 163 | 95.95 236 | 87.01 249 | 80.71 318 | 89.80 317 | 83.08 143 | 96.20 311 | 84.61 241 | 75.34 331 | 92.48 322 |
|
v18 | | | 88.71 269 | 87.52 268 | 92.27 265 | 94.16 262 | 88.11 224 | 96.82 162 | 95.96 235 | 87.03 247 | 80.76 316 | 89.81 316 | 83.15 137 | 96.22 310 | 84.69 238 | 75.31 332 | 92.49 320 |
|
v8 | | | 91.29 213 | 90.53 208 | 93.57 229 | 94.15 263 | 88.12 222 | 97.34 112 | 97.06 174 | 88.99 185 | 88.32 244 | 94.26 253 | 83.08 143 | 98.01 228 | 87.62 191 | 83.92 298 | 94.57 286 |
|
v6 | | | 91.69 187 | 91.00 181 | 93.75 214 | 94.14 264 | 88.12 222 | 97.20 127 | 96.98 184 | 89.19 174 | 89.90 201 | 94.42 233 | 83.04 147 | 98.07 210 | 89.07 160 | 85.10 277 | 95.07 256 |
|
v17 | | | 88.67 271 | 87.47 271 | 92.26 267 | 94.13 265 | 88.09 226 | 96.81 163 | 95.95 236 | 87.02 248 | 80.72 317 | 89.75 318 | 83.11 140 | 96.20 311 | 84.61 241 | 75.15 334 | 92.49 320 |
|
v7 | | | 91.47 203 | 90.73 195 | 93.68 222 | 94.13 265 | 88.16 218 | 97.09 136 | 97.05 175 | 88.38 214 | 89.80 207 | 94.52 224 | 82.21 175 | 98.01 228 | 88.00 178 | 85.42 269 | 94.87 268 |
|
V14 | | | 88.52 274 | 87.30 274 | 92.17 272 | 94.12 267 | 87.99 229 | 96.72 174 | 95.91 239 | 86.98 251 | 80.50 322 | 89.63 319 | 83.03 148 | 96.12 315 | 84.23 247 | 74.60 337 | 92.40 327 |
|
v10 | | | 91.04 221 | 90.23 219 | 93.49 231 | 94.12 267 | 88.16 218 | 97.32 115 | 97.08 171 | 88.26 218 | 88.29 246 | 94.22 254 | 82.17 177 | 97.97 235 | 86.45 211 | 84.12 294 | 94.33 293 |
|
V9 | | | 88.49 277 | 87.26 276 | 92.18 271 | 94.12 267 | 87.97 232 | 96.73 171 | 95.90 240 | 86.95 253 | 80.40 324 | 89.61 320 | 82.98 152 | 96.13 313 | 84.14 248 | 74.55 338 | 92.44 324 |
|
v12 | | | 88.46 278 | 87.23 279 | 92.17 272 | 94.10 270 | 87.99 229 | 96.71 176 | 95.90 240 | 86.91 254 | 80.34 326 | 89.58 323 | 82.92 156 | 96.11 317 | 84.09 249 | 74.50 340 | 92.42 325 |
|
v15 | | | 88.53 273 | 87.31 273 | 92.20 270 | 94.09 271 | 88.05 227 | 96.72 174 | 95.90 240 | 87.01 249 | 80.53 321 | 89.60 322 | 83.02 149 | 96.13 313 | 84.29 246 | 74.64 335 | 92.41 326 |
|
Patchmtry | | | 88.64 272 | 87.25 277 | 92.78 256 | 94.09 271 | 86.64 259 | 89.82 338 | 95.68 253 | 80.81 320 | 87.63 259 | 92.36 299 | 80.91 199 | 97.03 297 | 78.86 308 | 85.12 276 | 94.67 282 |
|
v13 | | | 88.45 279 | 87.22 280 | 92.16 274 | 94.08 273 | 87.95 233 | 96.71 176 | 95.90 240 | 86.86 258 | 80.27 328 | 89.55 324 | 82.92 156 | 96.12 315 | 84.02 251 | 74.63 336 | 92.40 327 |
|
v11 | | | 88.41 280 | 87.19 283 | 92.08 277 | 94.08 273 | 87.77 238 | 96.75 169 | 95.85 246 | 86.74 259 | 80.50 322 | 89.50 325 | 82.49 168 | 96.08 318 | 83.55 257 | 75.20 333 | 92.38 329 |
|
PatchT | | | 88.87 266 | 87.42 272 | 93.22 244 | 94.08 273 | 85.10 277 | 89.51 339 | 94.64 299 | 81.92 309 | 92.36 139 | 88.15 335 | 80.05 215 | 97.01 299 | 72.43 328 | 93.65 175 | 97.54 156 |
|
V42 | | | 91.58 197 | 90.87 186 | 93.73 217 | 94.05 276 | 88.50 203 | 97.32 115 | 96.97 187 | 88.80 198 | 89.71 212 | 94.33 238 | 82.54 166 | 98.05 218 | 89.01 163 | 85.07 280 | 94.64 284 |
|
v1141 | | | 91.61 193 | 90.89 183 | 93.78 211 | 94.01 277 | 88.24 210 | 96.96 145 | 96.96 188 | 89.17 178 | 89.75 210 | 94.29 247 | 82.99 151 | 98.03 224 | 88.85 167 | 85.00 283 | 95.07 256 |
|
divwei89l23v2f112 | | | 91.61 193 | 90.89 183 | 93.78 211 | 94.01 277 | 88.22 212 | 96.96 145 | 96.96 188 | 89.17 178 | 89.75 210 | 94.28 249 | 83.02 149 | 98.03 224 | 88.86 166 | 84.98 286 | 95.08 254 |
|
v1 | | | 91.61 193 | 90.89 183 | 93.78 211 | 94.01 277 | 88.21 214 | 96.96 145 | 96.96 188 | 89.17 178 | 89.78 209 | 94.29 247 | 82.97 153 | 98.05 218 | 88.85 167 | 84.99 284 | 95.08 254 |
|
DTE-MVSNet | | | 90.56 238 | 89.75 238 | 93.01 249 | 93.95 280 | 87.25 246 | 97.64 78 | 97.65 109 | 90.74 136 | 87.12 268 | 95.68 175 | 79.97 217 | 97.00 300 | 83.33 260 | 81.66 314 | 94.78 279 |
|
tpm | | | 90.25 244 | 89.74 239 | 91.76 288 | 93.92 281 | 79.73 324 | 93.98 291 | 93.54 324 | 88.28 217 | 91.99 147 | 93.25 284 | 77.51 267 | 97.44 281 | 87.30 199 | 87.94 250 | 98.12 129 |
|
PS-MVSNAJss | | | 93.74 110 | 93.51 100 | 94.44 179 | 93.91 282 | 89.28 186 | 97.75 59 | 97.56 119 | 92.50 85 | 89.94 200 | 96.54 132 | 88.65 71 | 98.18 195 | 93.83 81 | 90.90 221 | 95.86 209 |
|
v1144 | | | 91.37 208 | 90.60 206 | 93.68 222 | 93.89 283 | 88.23 211 | 96.84 158 | 97.03 181 | 88.37 215 | 89.69 214 | 94.39 234 | 82.04 178 | 97.98 232 | 87.80 183 | 85.37 271 | 94.84 270 |
|
v2v482 | | | 91.59 196 | 90.85 188 | 93.80 209 | 93.87 284 | 88.17 217 | 96.94 151 | 96.88 198 | 89.54 164 | 89.53 220 | 94.90 205 | 81.70 187 | 98.02 227 | 89.25 155 | 85.04 282 | 95.20 251 |
|
v148 | | | 90.99 222 | 90.38 212 | 92.81 255 | 93.83 285 | 85.80 268 | 96.78 168 | 96.68 209 | 89.45 168 | 88.75 237 | 93.93 262 | 82.96 155 | 97.82 255 | 87.83 182 | 83.25 304 | 94.80 276 |
|
Baseline_NR-MVSNet | | | 91.20 215 | 90.62 205 | 92.95 251 | 93.83 285 | 88.03 228 | 97.01 142 | 95.12 278 | 88.42 213 | 89.70 213 | 95.13 199 | 83.47 132 | 97.44 281 | 89.66 148 | 83.24 305 | 93.37 309 |
|
EPNet_dtu | | | 91.71 182 | 91.28 171 | 92.99 250 | 93.76 287 | 83.71 291 | 96.69 181 | 95.28 269 | 93.15 64 | 87.02 272 | 95.95 155 | 83.37 134 | 97.38 287 | 79.46 305 | 96.84 116 | 97.88 139 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
v1192 | | | 91.07 219 | 90.23 219 | 93.58 228 | 93.70 288 | 87.82 237 | 96.73 171 | 97.07 172 | 87.77 231 | 89.58 217 | 94.32 239 | 80.90 202 | 97.97 235 | 86.52 209 | 85.48 267 | 94.95 262 |
|
GG-mvs-BLEND | | | | | 93.62 224 | 93.69 289 | 89.20 189 | 92.39 321 | 83.33 359 | | 87.98 253 | 89.84 315 | 71.00 304 | 96.87 302 | 82.08 275 | 95.40 143 | 94.80 276 |
|
v144192 | | | 91.06 220 | 90.28 215 | 93.39 236 | 93.66 290 | 87.23 248 | 96.83 159 | 97.07 172 | 87.43 238 | 89.69 214 | 94.28 249 | 81.48 188 | 98.00 231 | 87.18 202 | 84.92 287 | 94.93 266 |
|
v1921920 | | | 90.85 226 | 90.03 226 | 93.29 241 | 93.55 291 | 86.96 256 | 96.74 170 | 97.04 178 | 87.36 240 | 89.52 221 | 94.34 237 | 80.23 213 | 97.97 235 | 86.27 212 | 85.21 274 | 94.94 264 |
|
v7n | | | 90.76 228 | 89.86 232 | 93.45 235 | 93.54 292 | 87.60 242 | 97.70 70 | 97.37 145 | 88.85 192 | 87.65 258 | 94.08 258 | 81.08 193 | 98.10 203 | 84.68 239 | 83.79 301 | 94.66 283 |
|
JIA-IIPM | | | 88.26 283 | 87.04 284 | 91.91 280 | 93.52 293 | 81.42 309 | 89.38 340 | 94.38 307 | 80.84 319 | 90.93 177 | 80.74 346 | 79.22 227 | 97.92 245 | 82.76 267 | 91.62 208 | 96.38 190 |
|
v1240 | | | 90.70 234 | 89.85 233 | 93.23 243 | 93.51 294 | 86.80 257 | 96.61 189 | 97.02 182 | 87.16 245 | 89.58 217 | 94.31 240 | 79.55 223 | 97.98 232 | 85.52 227 | 85.44 268 | 94.90 267 |
|
test_djsdf | | | 93.07 129 | 92.76 118 | 94.00 196 | 93.49 295 | 88.70 199 | 98.22 26 | 97.57 116 | 91.42 118 | 90.08 198 | 95.55 181 | 82.85 159 | 97.92 245 | 94.07 72 | 91.58 209 | 95.40 237 |
|
SixPastTwentyTwo | | | 89.15 262 | 88.54 259 | 90.98 299 | 93.49 295 | 80.28 320 | 96.70 179 | 94.70 294 | 90.78 135 | 84.15 297 | 95.57 179 | 71.78 299 | 97.71 264 | 84.63 240 | 85.07 280 | 94.94 264 |
|
mvs_tets | | | 92.31 160 | 91.76 147 | 93.94 205 | 93.41 297 | 88.29 206 | 97.63 85 | 97.53 120 | 92.04 103 | 88.76 236 | 96.45 136 | 74.62 284 | 98.09 205 | 93.91 77 | 91.48 211 | 95.45 231 |
|
OurMVSNet-221017-0 | | | 90.51 240 | 90.19 222 | 91.44 294 | 93.41 297 | 81.25 310 | 96.98 144 | 96.28 222 | 91.68 111 | 86.55 277 | 96.30 141 | 74.20 287 | 97.98 232 | 88.96 164 | 87.40 257 | 95.09 253 |
|
pmmvs4 | | | 90.93 224 | 89.85 233 | 94.17 189 | 93.34 299 | 90.79 127 | 94.60 276 | 96.02 233 | 84.62 285 | 87.45 260 | 95.15 197 | 81.88 183 | 97.45 280 | 87.70 185 | 87.87 251 | 94.27 297 |
|
DI_MVS_plusplus_test | | | 92.01 171 | 90.77 192 | 95.73 115 | 93.34 299 | 89.78 151 | 96.14 227 | 96.18 229 | 90.58 147 | 81.80 309 | 93.50 277 | 74.95 282 | 98.90 133 | 93.51 85 | 96.94 115 | 98.51 105 |
|
jajsoiax | | | 92.42 155 | 91.89 145 | 94.03 195 | 93.33 301 | 88.50 203 | 97.73 63 | 97.53 120 | 92.00 105 | 88.85 235 | 96.50 134 | 75.62 277 | 98.11 202 | 93.88 79 | 91.56 210 | 95.48 227 |
|
v748 | | | 90.34 242 | 89.54 243 | 92.75 257 | 93.25 302 | 85.71 270 | 97.61 86 | 97.17 159 | 88.54 205 | 87.20 267 | 93.54 275 | 81.02 194 | 98.01 228 | 85.73 225 | 81.80 311 | 94.52 287 |
|
test_normal | | | 92.01 171 | 90.75 194 | 95.80 109 | 93.24 303 | 89.97 144 | 95.93 238 | 96.24 226 | 90.62 143 | 81.63 310 | 93.45 280 | 74.98 281 | 98.89 135 | 93.61 83 | 97.04 114 | 98.55 100 |
|
v52 | | | 90.70 234 | 90.00 227 | 92.82 252 | 93.24 303 | 87.03 252 | 97.60 87 | 97.14 163 | 88.21 219 | 87.69 256 | 93.94 261 | 80.91 199 | 98.07 210 | 87.39 195 | 83.87 300 | 93.36 310 |
|
gm-plane-assit | | | | | | 93.22 305 | 78.89 330 | | | 84.82 283 | | 93.52 276 | | 98.64 155 | 87.72 184 | | |
|
V4 | | | 90.71 233 | 90.00 227 | 92.82 252 | 93.21 306 | 87.03 252 | 97.59 89 | 97.16 162 | 88.21 219 | 87.69 256 | 93.92 263 | 80.93 198 | 98.06 215 | 87.39 195 | 83.90 299 | 93.39 308 |
|
LP | | | 84.13 308 | 81.85 313 | 90.97 300 | 93.20 307 | 82.12 305 | 87.68 345 | 94.27 313 | 76.80 336 | 81.93 307 | 88.52 330 | 72.97 295 | 95.95 320 | 59.53 346 | 81.73 312 | 94.84 270 |
|
MVP-Stereo | | | 90.74 231 | 90.08 223 | 92.71 258 | 93.19 308 | 88.20 215 | 95.86 240 | 96.27 223 | 86.07 267 | 84.86 290 | 94.76 216 | 77.84 264 | 97.75 261 | 83.88 255 | 98.01 87 | 92.17 333 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
EU-MVSNet | | | 88.72 268 | 88.90 253 | 88.20 319 | 93.15 309 | 74.21 337 | 96.63 188 | 94.22 314 | 85.18 276 | 87.32 265 | 95.97 153 | 76.16 272 | 94.98 331 | 85.27 231 | 86.17 262 | 95.41 233 |
|
MDA-MVSNet-bldmvs | | | 85.00 305 | 82.95 307 | 91.17 298 | 93.13 310 | 83.33 296 | 94.56 278 | 95.00 283 | 84.57 286 | 65.13 349 | 92.65 290 | 70.45 307 | 95.85 321 | 73.57 326 | 77.49 324 | 94.33 293 |
|
K. test v3 | | | 87.64 288 | 86.75 286 | 90.32 311 | 93.02 311 | 79.48 326 | 96.61 189 | 92.08 341 | 90.66 141 | 80.25 329 | 94.09 257 | 67.21 323 | 96.65 305 | 85.96 221 | 80.83 318 | 94.83 272 |
|
pmmvs5 | | | 89.86 254 | 88.87 254 | 92.82 252 | 92.86 312 | 86.23 265 | 96.26 219 | 95.39 262 | 84.24 289 | 87.12 268 | 94.51 225 | 74.27 286 | 97.36 288 | 87.61 192 | 87.57 253 | 94.86 269 |
|
testgi | | | 87.97 284 | 87.21 281 | 90.24 312 | 92.86 312 | 80.76 312 | 96.67 183 | 94.97 286 | 91.74 109 | 85.52 284 | 95.83 162 | 62.66 334 | 94.47 333 | 76.25 317 | 88.36 248 | 95.48 227 |
|
EPNet | | | 95.20 70 | 94.56 75 | 97.14 55 | 92.80 314 | 92.68 66 | 97.85 53 | 94.87 293 | 96.64 1 | 92.46 135 | 97.80 64 | 86.23 102 | 99.65 41 | 93.72 82 | 98.62 74 | 99.10 61 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
N_pmnet | | | 78.73 319 | 78.71 318 | 78.79 336 | 92.80 314 | 46.50 363 | 94.14 288 | 43.71 367 | 78.61 331 | 80.83 313 | 91.66 309 | 74.94 283 | 96.36 307 | 67.24 337 | 84.45 292 | 93.50 305 |
|
EG-PatchMatch MVS | | | 87.02 293 | 85.44 294 | 91.76 288 | 92.67 316 | 85.00 278 | 96.08 230 | 96.45 217 | 83.41 300 | 79.52 331 | 93.49 278 | 57.10 342 | 97.72 263 | 79.34 307 | 90.87 222 | 92.56 318 |
|
Gipuma | | | 67.86 327 | 65.41 328 | 75.18 340 | 92.66 317 | 73.45 338 | 66.50 358 | 94.52 304 | 53.33 353 | 57.80 353 | 66.07 355 | 30.81 356 | 89.20 350 | 48.15 355 | 78.88 322 | 62.90 356 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
anonymousdsp | | | 92.16 167 | 91.55 161 | 93.97 200 | 92.58 318 | 89.55 164 | 97.51 96 | 97.42 140 | 89.42 169 | 88.40 242 | 94.84 210 | 80.66 204 | 97.88 250 | 91.87 115 | 91.28 215 | 94.48 288 |
|
test0.0.03 1 | | | 89.37 261 | 88.70 255 | 91.41 295 | 92.47 319 | 85.63 271 | 95.22 269 | 92.70 338 | 91.11 129 | 86.91 274 | 93.65 272 | 79.02 231 | 93.19 339 | 78.00 311 | 89.18 239 | 95.41 233 |
|
our_test_3 | | | 88.78 267 | 87.98 265 | 91.20 297 | 92.45 320 | 82.53 300 | 93.61 301 | 95.69 251 | 85.77 270 | 84.88 289 | 93.71 268 | 79.99 216 | 96.78 304 | 79.47 304 | 86.24 261 | 94.28 296 |
|
ppachtmachnet_test | | | 88.35 282 | 87.29 275 | 91.53 291 | 92.45 320 | 83.57 295 | 93.75 295 | 95.97 234 | 84.28 288 | 85.32 288 | 94.18 255 | 79.00 235 | 96.93 301 | 75.71 319 | 84.99 284 | 94.10 298 |
|
YYNet1 | | | 85.87 301 | 84.23 303 | 90.78 306 | 92.38 322 | 82.46 302 | 93.17 307 | 95.14 277 | 82.12 308 | 67.69 344 | 92.36 299 | 78.16 254 | 95.50 329 | 77.31 314 | 79.73 320 | 94.39 291 |
|
MDA-MVSNet_test_wron | | | 85.87 301 | 84.23 303 | 90.80 305 | 92.38 322 | 82.57 299 | 93.17 307 | 95.15 276 | 82.15 307 | 67.65 345 | 92.33 302 | 78.20 251 | 95.51 328 | 77.33 313 | 79.74 319 | 94.31 295 |
|
LF4IMVS | | | 87.94 285 | 87.25 277 | 89.98 314 | 92.38 322 | 80.05 323 | 94.38 281 | 95.25 272 | 87.59 236 | 84.34 293 | 94.74 218 | 64.31 331 | 97.66 268 | 84.83 235 | 87.45 254 | 92.23 331 |
|
lessismore_v0 | | | | | 90.45 309 | 91.96 325 | 79.09 329 | | 87.19 355 | | 80.32 327 | 94.39 234 | 66.31 325 | 97.55 274 | 84.00 253 | 76.84 326 | 94.70 281 |
|
testpf | | | 80.97 316 | 81.40 314 | 79.65 334 | 91.53 326 | 72.43 340 | 73.47 356 | 89.55 350 | 78.63 330 | 80.81 314 | 89.06 327 | 61.36 336 | 91.36 345 | 83.34 259 | 84.89 288 | 75.15 352 |
|
pmmvs6 | | | 87.81 287 | 86.19 289 | 92.69 259 | 91.32 327 | 86.30 264 | 97.34 112 | 96.41 218 | 80.59 322 | 84.05 299 | 94.37 236 | 67.37 322 | 97.67 266 | 84.75 237 | 79.51 321 | 94.09 300 |
|
Anonymous20231206 | | | 87.09 292 | 86.14 290 | 89.93 315 | 91.22 328 | 80.35 317 | 96.11 228 | 95.35 265 | 83.57 298 | 84.16 296 | 93.02 286 | 73.54 293 | 95.61 325 | 72.16 329 | 86.14 263 | 93.84 303 |
|
DeepMVS_CX | | | | | 74.68 341 | 90.84 329 | 64.34 352 | | 81.61 362 | 65.34 349 | 67.47 347 | 88.01 336 | 48.60 351 | 80.13 357 | 62.33 343 | 73.68 343 | 79.58 350 |
|
Test4 | | | 89.48 258 | 87.50 269 | 95.44 130 | 90.76 330 | 89.72 152 | 95.78 246 | 97.09 169 | 90.28 151 | 77.67 335 | 91.74 308 | 55.42 346 | 98.08 206 | 91.92 112 | 96.83 117 | 98.52 103 |
|
test20.03 | | | 86.14 299 | 85.40 295 | 88.35 317 | 90.12 331 | 80.06 322 | 95.90 239 | 95.20 274 | 88.59 201 | 81.29 312 | 93.62 273 | 71.43 301 | 92.65 340 | 71.26 333 | 81.17 316 | 92.34 330 |
|
OpenMVS_ROB | | 81.14 20 | 84.42 307 | 82.28 308 | 90.83 302 | 90.06 332 | 84.05 289 | 95.73 247 | 94.04 317 | 73.89 344 | 80.17 330 | 91.53 310 | 59.15 339 | 97.64 269 | 66.92 338 | 89.05 240 | 90.80 339 |
|
UnsupCasMVSNet_eth | | | 85.99 300 | 84.45 301 | 90.62 307 | 89.97 333 | 82.40 303 | 93.62 300 | 97.37 145 | 89.86 158 | 78.59 334 | 92.37 296 | 65.25 330 | 95.35 330 | 82.27 274 | 70.75 344 | 94.10 298 |
|
DSMNet-mixed | | | 86.34 297 | 86.12 291 | 87.00 324 | 89.88 334 | 70.43 341 | 94.93 273 | 90.08 349 | 77.97 334 | 85.42 287 | 92.78 289 | 74.44 285 | 93.96 335 | 74.43 322 | 95.14 146 | 96.62 183 |
|
new_pmnet | | | 82.89 311 | 81.12 316 | 88.18 320 | 89.63 335 | 80.18 321 | 91.77 324 | 92.57 339 | 76.79 337 | 75.56 338 | 88.23 334 | 61.22 337 | 94.48 332 | 71.43 331 | 82.92 308 | 89.87 341 |
|
MIMVSNet1 | | | 84.93 306 | 83.05 306 | 90.56 308 | 89.56 336 | 84.84 282 | 95.40 260 | 95.35 265 | 83.91 292 | 80.38 325 | 92.21 303 | 57.23 341 | 93.34 338 | 70.69 335 | 82.75 310 | 93.50 305 |
|
CMPMVS | | 62.92 21 | 85.62 303 | 84.92 298 | 87.74 321 | 89.14 337 | 73.12 339 | 94.17 287 | 96.80 202 | 73.98 343 | 73.65 339 | 94.93 203 | 66.36 324 | 97.61 271 | 83.95 254 | 91.28 215 | 92.48 322 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
Patchmatch-RL test | | | 87.38 289 | 86.24 288 | 90.81 303 | 88.74 338 | 78.40 331 | 88.12 344 | 93.17 326 | 87.11 246 | 82.17 305 | 89.29 326 | 81.95 181 | 95.60 326 | 88.64 172 | 77.02 325 | 98.41 118 |
|
pmmvs-eth3d | | | 86.22 298 | 84.45 301 | 91.53 291 | 88.34 339 | 87.25 246 | 94.47 280 | 95.01 282 | 83.47 299 | 79.51 332 | 89.61 320 | 69.75 312 | 95.71 324 | 83.13 262 | 76.73 327 | 91.64 334 |
|
UnsupCasMVSNet_bld | | | 82.13 315 | 79.46 317 | 90.14 313 | 88.00 340 | 82.47 301 | 90.89 332 | 96.62 215 | 78.94 329 | 75.61 337 | 84.40 344 | 56.63 343 | 96.31 308 | 77.30 315 | 66.77 349 | 91.63 335 |
|
PM-MVS | | | 83.48 309 | 81.86 312 | 88.31 318 | 87.83 341 | 77.59 332 | 93.43 302 | 91.75 343 | 86.91 254 | 80.63 319 | 89.91 314 | 44.42 353 | 95.84 322 | 85.17 234 | 76.73 327 | 91.50 337 |
|
testing_2 | | | 87.33 290 | 85.03 297 | 94.22 187 | 87.77 342 | 89.32 183 | 94.97 272 | 97.11 167 | 89.22 173 | 71.64 343 | 88.73 329 | 55.16 347 | 97.94 241 | 91.95 111 | 88.73 245 | 95.41 233 |
|
testus | | | 82.63 313 | 82.15 309 | 84.07 328 | 87.31 343 | 67.67 347 | 93.18 305 | 94.29 312 | 82.47 305 | 82.14 306 | 90.69 311 | 53.01 348 | 91.94 343 | 66.30 339 | 89.96 233 | 92.62 317 |
|
new-patchmatchnet | | | 83.18 310 | 81.87 311 | 87.11 323 | 86.88 344 | 75.99 335 | 93.70 296 | 95.18 275 | 85.02 280 | 77.30 336 | 88.40 332 | 65.99 327 | 93.88 336 | 74.19 325 | 70.18 345 | 91.47 338 |
|
test2356 | | | 82.77 312 | 82.14 310 | 84.65 327 | 85.77 345 | 70.36 342 | 91.22 328 | 93.69 323 | 81.58 313 | 81.82 308 | 89.00 328 | 60.63 338 | 90.77 346 | 64.74 340 | 90.80 223 | 92.82 313 |
|
1111 | | | 78.29 320 | 77.55 320 | 80.50 332 | 83.89 346 | 59.98 355 | 91.89 322 | 93.71 320 | 75.06 339 | 73.60 340 | 87.67 337 | 55.66 344 | 92.60 341 | 58.54 348 | 77.92 323 | 88.93 343 |
|
.test1245 | | | 65.38 328 | 69.22 326 | 53.86 348 | 83.89 346 | 59.98 355 | 91.89 322 | 93.71 320 | 75.06 339 | 73.60 340 | 87.67 337 | 55.66 344 | 92.60 341 | 58.54 348 | 2.96 361 | 9.00 361 |
|
ambc | | | | | 86.56 325 | 83.60 348 | 70.00 345 | 85.69 348 | 94.97 286 | | 80.60 320 | 88.45 331 | 37.42 354 | 96.84 303 | 82.69 269 | 75.44 330 | 92.86 312 |
|
pmmvs3 | | | 79.97 317 | 77.50 321 | 87.39 322 | 82.80 349 | 79.38 327 | 92.70 316 | 90.75 347 | 70.69 347 | 78.66 333 | 87.47 340 | 51.34 350 | 93.40 337 | 73.39 327 | 69.65 346 | 89.38 342 |
|
test1235678 | | | 79.82 318 | 78.53 319 | 83.69 329 | 82.55 350 | 67.55 348 | 92.50 319 | 94.13 315 | 79.28 327 | 72.10 342 | 86.45 342 | 57.27 340 | 90.68 347 | 61.60 344 | 80.90 317 | 92.82 313 |
|
TDRefinement | | | 86.53 295 | 84.76 300 | 91.85 282 | 82.23 351 | 84.25 285 | 96.38 207 | 95.35 265 | 84.97 281 | 84.09 298 | 94.94 202 | 65.76 329 | 98.34 185 | 84.60 243 | 74.52 339 | 92.97 311 |
|
test12356 | | | 74.97 321 | 74.13 322 | 77.49 337 | 78.81 352 | 56.23 359 | 88.53 343 | 92.75 337 | 75.14 338 | 67.50 346 | 85.07 343 | 44.88 352 | 89.96 348 | 58.71 347 | 75.75 329 | 86.26 344 |
|
PMMVS2 | | | 70.19 325 | 66.92 327 | 80.01 333 | 76.35 353 | 65.67 350 | 86.22 347 | 87.58 354 | 64.83 350 | 62.38 350 | 80.29 348 | 26.78 361 | 88.49 352 | 63.79 341 | 54.07 351 | 85.88 346 |
|
FPMVS | | | 71.27 324 | 69.85 324 | 75.50 339 | 74.64 354 | 59.03 357 | 91.30 326 | 91.50 344 | 58.80 351 | 57.92 352 | 88.28 333 | 29.98 359 | 85.53 354 | 53.43 352 | 82.84 309 | 81.95 348 |
|
E-PMN | | | 53.28 333 | 52.56 335 | 55.43 346 | 74.43 355 | 47.13 362 | 83.63 351 | 76.30 363 | 42.23 357 | 42.59 357 | 62.22 357 | 28.57 360 | 74.40 359 | 31.53 358 | 31.51 356 | 44.78 357 |
|
no-one | | | 68.12 326 | 63.78 329 | 81.13 331 | 74.01 356 | 70.22 344 | 87.61 346 | 90.71 348 | 72.63 346 | 53.13 354 | 71.89 352 | 30.29 357 | 91.45 344 | 61.53 345 | 32.21 355 | 81.72 349 |
|
PNet_i23d | | | 59.01 330 | 55.87 331 | 68.44 343 | 73.98 357 | 51.37 360 | 81.36 352 | 82.41 360 | 52.37 354 | 42.49 358 | 70.39 354 | 11.39 364 | 79.99 358 | 49.77 354 | 38.71 353 | 73.97 353 |
|
wuyk23d | | | 25.11 339 | 24.57 341 | 26.74 351 | 73.98 357 | 39.89 366 | 57.88 359 | 9.80 368 | 12.27 361 | 10.39 363 | 6.97 365 | 7.03 366 | 36.44 363 | 25.43 360 | 17.39 360 | 3.89 363 |
|
testmv | | | 72.22 323 | 70.02 323 | 78.82 335 | 73.06 359 | 61.75 353 | 91.24 327 | 92.31 340 | 74.45 342 | 61.06 351 | 80.51 347 | 34.21 355 | 88.63 351 | 55.31 351 | 68.07 348 | 86.06 345 |
|
EMVS | | | 52.08 335 | 51.31 336 | 54.39 347 | 72.62 360 | 45.39 364 | 83.84 350 | 75.51 364 | 41.13 358 | 40.77 359 | 59.65 358 | 30.08 358 | 73.60 360 | 28.31 359 | 29.90 358 | 44.18 358 |
|
LCM-MVSNet | | | 72.55 322 | 69.39 325 | 82.03 330 | 70.81 361 | 65.42 351 | 90.12 337 | 94.36 309 | 55.02 352 | 65.88 348 | 81.72 345 | 24.16 363 | 89.96 348 | 74.32 324 | 68.10 347 | 90.71 340 |
|
MVE | | 50.73 23 | 53.25 334 | 48.81 338 | 66.58 345 | 65.34 362 | 57.50 358 | 72.49 357 | 70.94 365 | 40.15 359 | 39.28 360 | 63.51 356 | 6.89 368 | 73.48 361 | 38.29 357 | 42.38 352 | 68.76 355 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
wuykxyi23d | | | 56.92 332 | 51.11 337 | 74.38 342 | 62.30 363 | 61.47 354 | 80.09 353 | 84.87 357 | 49.62 355 | 30.80 362 | 57.20 359 | 7.03 366 | 82.94 355 | 55.69 350 | 32.36 354 | 78.72 351 |
|
ANet_high | | | 63.94 329 | 59.58 330 | 77.02 338 | 61.24 364 | 66.06 349 | 85.66 349 | 87.93 353 | 78.53 332 | 42.94 356 | 71.04 353 | 25.42 362 | 80.71 356 | 52.60 353 | 30.83 357 | 84.28 347 |
|
PMVS | | 53.92 22 | 58.58 331 | 55.40 332 | 68.12 344 | 51.00 365 | 48.64 361 | 78.86 354 | 87.10 356 | 46.77 356 | 35.84 361 | 74.28 350 | 8.76 365 | 86.34 353 | 42.07 356 | 73.91 342 | 69.38 354 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
tmp_tt | | | 51.94 336 | 53.82 334 | 46.29 349 | 33.73 366 | 45.30 365 | 78.32 355 | 67.24 366 | 18.02 360 | 50.93 355 | 87.05 341 | 52.99 349 | 53.11 362 | 70.76 334 | 25.29 359 | 40.46 359 |
|
testmvs | | | 13.36 341 | 16.33 342 | 4.48 353 | 5.04 367 | 2.26 368 | 93.18 305 | 3.28 369 | 2.70 362 | 8.24 364 | 21.66 361 | 2.29 370 | 2.19 364 | 7.58 361 | 2.96 361 | 9.00 361 |
|
test123 | | | 13.04 342 | 15.66 343 | 5.18 352 | 4.51 368 | 3.45 367 | 92.50 319 | 1.81 370 | 2.50 363 | 7.58 365 | 20.15 362 | 3.67 369 | 2.18 365 | 7.13 362 | 1.07 363 | 9.90 360 |
|
cdsmvs_eth3d_5k | | | 23.24 340 | 30.99 340 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 97.63 111 | 0.00 364 | 0.00 366 | 96.88 109 | 84.38 124 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
pcd_1.5k_mvsjas | | | 7.39 344 | 9.85 345 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 0.00 366 | 88.65 71 | 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 | | | 8.06 343 | 10.74 344 | 0.00 354 | 0.00 369 | 0.00 369 | 0.00 360 | 0.00 371 | 0.00 364 | 0.00 366 | 96.69 118 | 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 | | | | | | | | | | | | | | | | | 98.45 114 |
|
test_part1 | | | | | 0.00 354 | | 0.00 369 | 0.00 360 | 98.26 26 | | | | 0.00 371 | 0.00 366 | 0.00 363 | 0.00 364 | 0.00 364 |
|
sam_mvs1 | | | | | | | | | | | | | 82.76 161 | | | | 98.45 114 |
|
sam_mvs | | | | | | | | | | | | | 81.94 182 | | | | |
|
MTGPA | | | | | | | | | 98.08 52 | | | | | | | | |
|
test_post1 | | | | | | | | 92.81 315 | | | | 16.58 364 | 80.53 206 | 97.68 265 | 86.20 214 | | |
|
test_post | | | | | | | | | | | | 17.58 363 | 81.76 184 | 98.08 206 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 90.45 312 | 82.65 165 | 98.10 203 | | | |
|
MTMP | | | | | | | | 97.86 50 | 82.03 361 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 94.81 64 | 99.38 35 | 99.45 30 |
|
agg_prior2 | | | | | | | | | | | | | | | 93.94 76 | 99.38 35 | 99.50 24 |
|
test_prior4 | | | | | | | 93.66 42 | 96.42 200 | | | | | | | | | |
|
test_prior2 | | | | | | | | 96.35 209 | | 92.80 79 | 96.03 57 | 97.59 80 | 92.01 30 | | 95.01 57 | 99.38 35 | |
|
旧先验2 | | | | | | | | 95.94 237 | | 81.66 311 | 97.34 19 | | | 98.82 141 | 92.26 101 | | |
|
新几何2 | | | | | | | | 95.79 244 | | | | | | | | | |
|
无先验 | | | | | | | | 95.79 244 | 97.87 88 | 83.87 295 | | | | 99.65 41 | 87.68 187 | | 98.89 82 |
|
原ACMM2 | | | | | | | | 95.67 248 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.67 39 | 85.96 221 | | |
|
segment_acmp | | | | | | | | | | | | | 92.89 12 | | | | |
|
testdata1 | | | | | | | | 95.26 268 | | 93.10 67 | | | | | | | |
|
plane_prior5 | | | | | | | | | 97.51 123 | | | | | 98.60 159 | 93.02 95 | 92.23 196 | 95.86 209 |
|
plane_prior4 | | | | | | | | | | | | 96.64 121 | | | | | |
|
plane_prior3 | | | | | | | 90.00 139 | | | 94.46 31 | 91.34 160 | | | | | | |
|
plane_prior2 | | | | | | | | 97.74 61 | | 94.85 18 | | | | | | | |
|
plane_prior | | | | | | | 89.99 141 | 97.24 120 | | 94.06 39 | | | | | | 92.16 200 | |
|
n2 | | | | | | | | | 0.00 371 | | | | | | | | |
|
nn | | | | | | | | | 0.00 371 | | | | | | | | |
|
door-mid | | | | | | | | | 91.06 346 | | | | | | | | |
|
test11 | | | | | | | | | 97.88 86 | | | | | | | | |
|
door | | | | | | | | | 91.13 345 | | | | | | | | |
|
HQP5-MVS | | | | | | | 89.33 181 | | | | | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 92.13 107 | | |
|
HQP4-MVS | | | | | | | | | | | 90.14 188 | | | 98.50 167 | | | 95.78 216 |
|
HQP3-MVS | | | | | | | | | 97.39 142 | | | | | | | 92.10 201 | |
|
HQP2-MVS | | | | | | | | | | | | | 80.95 196 | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 70.35 343 | 93.10 311 | | 83.88 294 | 93.55 108 | | 82.47 170 | | 86.25 213 | | 98.38 122 |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 90.30 230 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 91.02 220 | |
|
Test By Simon | | | | | | | | | | | | | 88.73 70 | | | | |
|