ESAPD | | | 98.92 2 | 98.67 4 | 99.65 1 | 99.58 26 | 99.20 1 | 98.42 182 | 98.91 42 | 97.58 7 | 99.54 3 | 99.46 6 | 97.10 2 | 99.94 3 | 97.64 48 | 99.84 7 | 99.83 2 |
|
test_part2 | | | | | | 99.63 22 | 99.18 2 | | | | 99.27 8 | | | | | | |
|
HPM-MVS++ | | | 98.58 19 | 98.25 30 | 99.55 3 | 99.50 32 | 99.08 3 | 98.72 132 | 98.66 112 | 97.51 9 | 98.15 61 | 98.83 86 | 95.70 35 | 99.92 15 | 97.53 56 | 99.67 41 | 99.66 51 |
|
SMA-MVS | | | 98.58 19 | 98.25 30 | 99.56 2 | 99.51 30 | 99.04 4 | 98.95 74 | 98.80 72 | 93.67 182 | 99.37 6 | 99.52 3 | 96.52 10 | 99.89 29 | 98.06 26 | 99.81 9 | 99.76 21 |
|
APDe-MVS | | | 99.02 1 | 98.84 1 | 99.55 3 | 99.57 27 | 98.96 5 | 99.39 5 | 98.93 36 | 97.38 18 | 99.41 4 | 99.54 1 | 96.66 6 | 99.84 46 | 98.86 2 | 99.85 2 | 99.87 1 |
|
ACMMP_Plus | | | 98.61 14 | 98.30 26 | 99.55 3 | 99.62 24 | 98.95 6 | 98.82 102 | 98.81 65 | 95.80 74 | 99.16 16 | 99.47 5 | 95.37 42 | 99.92 15 | 97.89 34 | 99.75 31 | 99.79 5 |
|
MP-MVS-pluss | | | 98.31 42 | 97.92 45 | 99.49 6 | 99.72 11 | 98.88 7 | 98.43 180 | 98.78 76 | 94.10 151 | 97.69 93 | 99.42 7 | 95.25 48 | 99.92 15 | 98.09 25 | 99.80 11 | 99.67 49 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
MCST-MVS | | | 98.65 10 | 98.37 18 | 99.48 7 | 99.60 25 | 98.87 8 | 98.41 183 | 98.68 102 | 97.04 39 | 98.52 49 | 98.80 89 | 96.78 5 | 99.83 47 | 97.93 30 | 99.61 51 | 99.74 27 |
|
CNVR-MVS | | | 98.78 4 | 98.56 7 | 99.45 10 | 99.32 50 | 98.87 8 | 98.47 174 | 98.81 65 | 97.72 4 | 98.76 37 | 99.16 45 | 97.05 3 | 99.78 79 | 98.06 26 | 99.66 44 | 99.69 38 |
|
APD-MVS | | | 98.35 38 | 98.00 43 | 99.42 11 | 99.51 30 | 98.72 10 | 98.80 111 | 98.82 61 | 94.52 140 | 99.23 12 | 99.25 31 | 95.54 39 | 99.80 62 | 96.52 96 | 99.77 19 | 99.74 27 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
zzz-MVS | | | 98.55 24 | 98.25 30 | 99.46 8 | 99.76 1 | 98.64 11 | 98.55 163 | 98.74 84 | 97.27 26 | 98.02 70 | 99.39 9 | 94.81 57 | 99.96 1 | 97.91 31 | 99.79 12 | 99.77 15 |
|
MTAPA | | | 98.58 19 | 98.29 27 | 99.46 8 | 99.76 1 | 98.64 11 | 98.90 79 | 98.74 84 | 97.27 26 | 98.02 70 | 99.39 9 | 94.81 57 | 99.96 1 | 97.91 31 | 99.79 12 | 99.77 15 |
|
NCCC | | | 98.61 14 | 98.35 21 | 99.38 12 | 99.28 65 | 98.61 13 | 98.45 175 | 98.76 80 | 97.82 3 | 98.45 54 | 98.93 78 | 96.65 7 | 99.83 47 | 97.38 61 | 99.41 79 | 99.71 35 |
|
3Dnovator+ | | 94.38 6 | 97.43 76 | 96.78 91 | 99.38 12 | 97.83 185 | 98.52 14 | 99.37 7 | 98.71 96 | 97.09 38 | 92.99 263 | 99.13 47 | 89.36 145 | 99.89 29 | 96.97 70 | 99.57 58 | 99.71 35 |
|
TEST9 | | | | | | 99.31 52 | 98.50 15 | 97.92 236 | 98.73 89 | 92.63 221 | 97.74 89 | 98.68 100 | 96.20 14 | 99.80 62 | | | |
|
train_agg | | | 97.97 47 | 97.52 57 | 99.33 18 | 99.31 52 | 98.50 15 | 97.92 236 | 98.73 89 | 92.98 211 | 97.74 89 | 98.68 100 | 96.20 14 | 99.80 62 | 96.59 92 | 99.57 58 | 99.68 44 |
|
test_8 | | | | | | 99.29 60 | 98.44 17 | 97.89 244 | 98.72 91 | 92.98 211 | 97.70 92 | 98.66 103 | 96.20 14 | 99.80 62 | | | |
|
CDPH-MVS | | | 97.94 50 | 97.49 59 | 99.28 23 | 99.47 36 | 98.44 17 | 97.91 239 | 98.67 109 | 92.57 225 | 98.77 36 | 98.85 84 | 95.93 29 | 99.72 91 | 95.56 129 | 99.69 40 | 99.68 44 |
|
SteuartSystems-ACMMP | | | 98.90 3 | 98.75 2 | 99.36 14 | 99.22 76 | 98.43 19 | 99.10 53 | 98.87 51 | 97.38 18 | 99.35 7 | 99.40 8 | 97.78 1 | 99.87 38 | 97.77 41 | 99.85 2 | 99.78 8 |
Skip Steuart: Steuart Systems R&D Blog. |
GST-MVS | | | 98.43 32 | 98.12 38 | 99.34 15 | 99.72 11 | 98.38 20 | 99.09 54 | 98.82 61 | 95.71 77 | 98.73 39 | 99.06 59 | 95.27 46 | 99.93 10 | 97.07 68 | 99.63 49 | 99.72 32 |
|
agg_prior1 | | | 97.95 49 | 97.51 58 | 99.28 23 | 99.30 57 | 98.38 20 | 97.81 251 | 98.72 91 | 93.16 205 | 97.57 104 | 98.66 103 | 96.14 17 | 99.81 55 | 96.63 91 | 99.56 64 | 99.66 51 |
|
agg_prior | | | | | | 99.30 57 | 98.38 20 | | 98.72 91 | | 97.57 104 | | | 99.81 55 | | | |
|
canonicalmvs | | | 97.67 63 | 97.23 71 | 98.98 52 | 98.70 128 | 98.38 20 | 99.34 11 | 98.39 159 | 96.76 46 | 97.67 94 | 97.40 212 | 92.26 95 | 99.49 133 | 98.28 22 | 96.28 189 | 99.08 131 |
|
alignmvs | | | 97.56 69 | 97.07 79 | 99.01 49 | 98.66 132 | 98.37 24 | 98.83 100 | 98.06 225 | 96.74 47 | 98.00 76 | 97.65 195 | 90.80 128 | 99.48 137 | 98.37 19 | 96.56 171 | 99.19 113 |
|
SD-MVS | | | 98.64 11 | 98.68 3 | 98.53 78 | 99.33 47 | 98.36 25 | 98.90 79 | 98.85 55 | 97.28 22 | 99.72 1 | 99.39 9 | 96.63 8 | 97.60 310 | 98.17 23 | 99.85 2 | 99.64 56 |
|
XVS | | | 98.70 6 | 98.49 13 | 99.34 15 | 99.70 16 | 98.35 26 | 99.29 14 | 98.88 48 | 97.40 15 | 98.46 50 | 99.20 38 | 95.90 31 | 99.89 29 | 97.85 36 | 99.74 34 | 99.78 8 |
|
X-MVStestdata | | | 94.06 256 | 92.30 276 | 99.34 15 | 99.70 16 | 98.35 26 | 99.29 14 | 98.88 48 | 97.40 15 | 98.46 50 | 43.50 365 | 95.90 31 | 99.89 29 | 97.85 36 | 99.74 34 | 99.78 8 |
|
DP-MVS Recon | | | 97.86 54 | 97.46 62 | 99.06 48 | 99.53 29 | 98.35 26 | 98.33 190 | 98.89 45 | 92.62 222 | 98.05 66 | 98.94 77 | 95.34 44 | 99.65 105 | 96.04 110 | 99.42 78 | 99.19 113 |
|
HFP-MVS | | | 98.63 13 | 98.40 15 | 99.32 19 | 99.72 11 | 98.29 29 | 99.23 23 | 98.96 31 | 96.10 67 | 98.94 25 | 99.17 42 | 96.06 22 | 99.92 15 | 97.62 49 | 99.78 16 | 99.75 22 |
|
#test# | | | 98.54 26 | 98.27 28 | 99.32 19 | 99.72 11 | 98.29 29 | 98.98 71 | 98.96 31 | 95.65 81 | 98.94 25 | 99.17 42 | 96.06 22 | 99.92 15 | 97.21 64 | 99.78 16 | 99.75 22 |
|
TSAR-MVS + MP. | | | 98.78 4 | 98.62 5 | 99.24 28 | 99.69 18 | 98.28 31 | 99.14 45 | 98.66 112 | 96.84 44 | 99.56 2 | 99.31 23 | 96.34 12 | 99.70 96 | 98.32 20 | 99.73 36 | 99.73 29 |
|
HSP-MVS | | | 98.70 6 | 98.52 9 | 99.24 28 | 99.75 3 | 98.23 32 | 99.26 18 | 98.58 125 | 97.52 8 | 99.41 4 | 98.78 91 | 96.00 25 | 99.79 74 | 97.79 40 | 99.59 55 | 99.69 38 |
|
agg_prior3 | | | 97.87 53 | 97.42 64 | 99.23 30 | 99.29 60 | 98.23 32 | 97.92 236 | 98.72 91 | 92.38 238 | 97.59 103 | 98.64 105 | 96.09 20 | 99.79 74 | 96.59 92 | 99.57 58 | 99.68 44 |
|
test_prior3 | | | 98.22 45 | 97.90 46 | 99.19 31 | 99.31 52 | 98.22 34 | 97.80 252 | 98.84 56 | 96.12 65 | 97.89 83 | 98.69 98 | 95.96 27 | 99.70 96 | 96.89 76 | 99.60 52 | 99.65 53 |
|
test_prior | | | | | 99.19 31 | 99.31 52 | 98.22 34 | | 98.84 56 | | | | | 99.70 96 | | | 99.65 53 |
|
test12 | | | | | 99.18 35 | 99.16 81 | 98.19 36 | | 98.53 133 | | 98.07 65 | | 95.13 52 | 99.72 91 | | 99.56 64 | 99.63 58 |
|
MP-MVS | | | 98.33 41 | 98.01 42 | 99.28 23 | 99.75 3 | 98.18 37 | 99.22 29 | 98.79 74 | 96.13 64 | 97.92 81 | 99.23 32 | 94.54 62 | 99.94 3 | 96.74 88 | 99.78 16 | 99.73 29 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
region2R | | | 98.61 14 | 98.38 17 | 99.29 21 | 99.74 7 | 98.16 38 | 99.23 23 | 98.93 36 | 96.15 62 | 98.94 25 | 99.17 42 | 95.91 30 | 99.94 3 | 97.55 54 | 99.79 12 | 99.78 8 |
|
nrg030 | | | 96.28 126 | 95.72 128 | 97.96 116 | 96.90 242 | 98.15 39 | 99.39 5 | 98.31 169 | 95.47 87 | 94.42 208 | 98.35 132 | 92.09 102 | 98.69 220 | 97.50 57 | 89.05 287 | 97.04 222 |
|
ACMMPR | | | 98.59 17 | 98.36 19 | 99.29 21 | 99.74 7 | 98.15 39 | 99.23 23 | 98.95 33 | 96.10 67 | 98.93 29 | 99.19 41 | 95.70 35 | 99.94 3 | 97.62 49 | 99.79 12 | 99.78 8 |
|
PHI-MVS | | | 98.34 39 | 98.06 40 | 99.18 35 | 99.15 83 | 98.12 41 | 99.04 63 | 99.09 19 | 93.32 200 | 98.83 33 | 99.10 51 | 96.54 9 | 99.83 47 | 97.70 45 | 99.76 25 | 99.59 64 |
|
PGM-MVS | | | 98.49 29 | 98.23 34 | 99.27 26 | 99.72 11 | 98.08 42 | 98.99 68 | 99.49 5 | 95.43 90 | 99.03 19 | 99.32 22 | 95.56 37 | 99.94 3 | 96.80 86 | 99.77 19 | 99.78 8 |
|
mPP-MVS | | | 98.51 28 | 98.26 29 | 99.25 27 | 99.75 3 | 98.04 43 | 99.28 16 | 98.81 65 | 96.24 60 | 98.35 58 | 99.23 32 | 95.46 40 | 99.94 3 | 97.42 59 | 99.81 9 | 99.77 15 |
|
DeepC-MVS_fast | | 96.70 1 | 98.55 24 | 98.34 22 | 99.18 35 | 99.25 69 | 98.04 43 | 98.50 171 | 98.78 76 | 97.72 4 | 98.92 30 | 99.28 28 | 95.27 46 | 99.82 53 | 97.55 54 | 99.77 19 | 99.69 38 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
Regformer-2 | | | 98.69 8 | 98.52 9 | 99.19 31 | 99.35 42 | 98.01 45 | 98.37 186 | 98.81 65 | 97.48 12 | 99.21 13 | 99.21 35 | 96.13 18 | 99.80 62 | 98.40 18 | 99.73 36 | 99.75 22 |
|
test_prior4 | | | | | | | 98.01 45 | 97.86 247 | | | | | | | | | |
|
新几何1 | | | | | 99.16 38 | 99.34 44 | 98.01 45 | | 98.69 99 | 90.06 291 | 98.13 62 | 98.95 76 | 94.60 61 | 99.89 29 | 91.97 227 | 99.47 72 | 99.59 64 |
|
1121 | | | 97.37 82 | 96.77 95 | 99.16 38 | 99.34 44 | 97.99 48 | 98.19 209 | 98.68 102 | 90.14 290 | 98.01 74 | 98.97 69 | 94.80 59 | 99.87 38 | 93.36 186 | 99.46 75 | 99.61 59 |
|
APD-MVS_3200maxsize | | | 98.53 27 | 98.33 25 | 99.15 40 | 99.50 32 | 97.92 49 | 99.15 44 | 98.81 65 | 96.24 60 | 99.20 14 | 99.37 14 | 95.30 45 | 99.80 62 | 97.73 43 | 99.67 41 | 99.72 32 |
|
HPM-MVS_fast | | | 98.38 35 | 98.13 37 | 99.12 43 | 99.75 3 | 97.86 50 | 99.44 4 | 98.82 61 | 94.46 144 | 98.94 25 | 99.20 38 | 95.16 51 | 99.74 90 | 97.58 51 | 99.85 2 | 99.77 15 |
|
CP-MVS | | | 98.57 22 | 98.36 19 | 99.19 31 | 99.66 20 | 97.86 50 | 99.34 11 | 98.87 51 | 95.96 70 | 98.60 46 | 99.13 47 | 96.05 24 | 99.94 3 | 97.77 41 | 99.86 1 | 99.77 15 |
|
MVS_0304 | | | 97.70 61 | 97.25 69 | 99.07 46 | 98.90 104 | 97.83 52 | 98.20 205 | 98.74 84 | 97.51 9 | 98.03 69 | 99.06 59 | 86.12 233 | 99.93 10 | 99.02 1 | 99.64 47 | 99.44 87 |
|
HPM-MVS | | | 98.36 37 | 98.10 39 | 99.13 41 | 99.74 7 | 97.82 53 | 99.53 1 | 98.80 72 | 94.63 137 | 98.61 45 | 98.97 69 | 95.13 52 | 99.77 84 | 97.65 47 | 99.83 8 | 99.79 5 |
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023 |
Regformer-1 | | | 98.66 9 | 98.51 11 | 99.12 43 | 99.35 42 | 97.81 54 | 98.37 186 | 98.76 80 | 97.49 11 | 99.20 14 | 99.21 35 | 96.08 21 | 99.79 74 | 98.42 16 | 99.73 36 | 99.75 22 |
|
abl_6 | | | 98.30 43 | 98.03 41 | 99.13 41 | 99.56 28 | 97.76 55 | 99.13 49 | 98.82 61 | 96.14 63 | 99.26 10 | 99.37 14 | 93.33 79 | 99.93 10 | 96.96 72 | 99.67 41 | 99.69 38 |
|
DELS-MVS | | | 98.40 34 | 98.20 36 | 98.99 50 | 99.00 93 | 97.66 56 | 97.75 256 | 98.89 45 | 97.71 6 | 98.33 59 | 98.97 69 | 94.97 55 | 99.88 37 | 98.42 16 | 99.76 25 | 99.42 89 |
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 |
3Dnovator | | 94.51 5 | 97.46 71 | 96.93 84 | 99.07 46 | 97.78 187 | 97.64 57 | 99.35 10 | 99.06 21 | 97.02 40 | 93.75 242 | 99.16 45 | 89.25 148 | 99.92 15 | 97.22 63 | 99.75 31 | 99.64 56 |
|
114514_t | | | 96.93 102 | 96.27 113 | 98.92 56 | 99.50 32 | 97.63 58 | 98.85 96 | 98.90 43 | 84.80 338 | 97.77 86 | 99.11 49 | 92.84 85 | 99.66 104 | 94.85 148 | 99.77 19 | 99.47 80 |
|
ACMMP | | | 98.23 44 | 97.95 44 | 99.09 45 | 99.74 7 | 97.62 59 | 99.03 64 | 99.41 6 | 95.98 69 | 97.60 102 | 99.36 18 | 94.45 67 | 99.93 10 | 97.14 65 | 98.85 100 | 99.70 37 |
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 |
QAPM | | | 96.29 124 | 95.40 138 | 98.96 54 | 97.85 184 | 97.60 60 | 99.23 23 | 98.93 36 | 89.76 300 | 93.11 260 | 99.02 62 | 89.11 152 | 99.93 10 | 91.99 226 | 99.62 50 | 99.34 92 |
|
VNet | | | 97.79 57 | 97.40 65 | 98.96 54 | 98.88 113 | 97.55 61 | 98.63 149 | 98.93 36 | 96.74 47 | 99.02 20 | 98.84 85 | 90.33 136 | 99.83 47 | 98.53 10 | 96.66 167 | 99.50 74 |
|
FIs | | | 96.51 117 | 96.12 118 | 97.67 139 | 97.13 230 | 97.54 62 | 99.36 8 | 99.22 14 | 95.89 71 | 94.03 233 | 98.35 132 | 91.98 105 | 98.44 255 | 96.40 101 | 92.76 250 | 97.01 223 |
|
旧先验1 | | | | | | 99.29 60 | 97.48 63 | | 98.70 98 | | | 99.09 55 | 95.56 37 | | | 99.47 72 | 99.61 59 |
|
UA-Net | | | 97.96 48 | 97.62 51 | 98.98 52 | 98.86 115 | 97.47 64 | 98.89 83 | 99.08 20 | 96.67 50 | 98.72 40 | 99.54 1 | 93.15 82 | 99.81 55 | 94.87 147 | 98.83 101 | 99.65 53 |
|
UniMVSNet (Re) | | | 95.78 142 | 95.19 153 | 97.58 149 | 96.99 236 | 97.47 64 | 98.79 116 | 99.18 16 | 95.60 82 | 93.92 236 | 97.04 249 | 91.68 110 | 98.48 245 | 95.80 120 | 87.66 310 | 96.79 248 |
|
CNLPA | | | 97.45 74 | 97.03 81 | 98.73 63 | 99.05 87 | 97.44 66 | 98.07 224 | 98.53 133 | 95.32 103 | 96.80 135 | 98.53 114 | 93.32 80 | 99.72 91 | 94.31 165 | 99.31 85 | 99.02 135 |
|
Regformer-4 | | | 98.64 11 | 98.53 8 | 98.99 50 | 99.43 40 | 97.37 67 | 98.40 184 | 98.79 74 | 97.46 13 | 99.09 17 | 99.31 23 | 95.86 33 | 99.80 62 | 98.64 4 | 99.76 25 | 99.79 5 |
|
MVS_111021_HR | | | 98.47 30 | 98.34 22 | 98.88 59 | 99.22 76 | 97.32 68 | 97.91 239 | 99.58 3 | 97.20 30 | 98.33 59 | 99.00 67 | 95.99 26 | 99.64 107 | 98.05 28 | 99.76 25 | 99.69 38 |
|
OpenMVS | | 93.04 13 | 95.83 140 | 95.00 159 | 98.32 93 | 97.18 227 | 97.32 68 | 99.21 32 | 98.97 29 | 89.96 293 | 91.14 294 | 99.05 61 | 86.64 225 | 99.92 15 | 93.38 185 | 99.47 72 | 97.73 198 |
|
CANet | | | 98.05 46 | 97.76 48 | 98.90 58 | 98.73 123 | 97.27 70 | 98.35 188 | 98.78 76 | 97.37 20 | 97.72 91 | 98.96 74 | 91.53 117 | 99.92 15 | 98.79 3 | 99.65 45 | 99.51 72 |
|
FC-MVSNet-test | | | 96.42 120 | 96.05 119 | 97.53 152 | 96.95 237 | 97.27 70 | 99.36 8 | 99.23 12 | 95.83 73 | 93.93 235 | 98.37 130 | 92.00 104 | 98.32 274 | 96.02 111 | 92.72 251 | 97.00 224 |
|
VPA-MVSNet | | | 95.75 143 | 95.11 155 | 97.69 137 | 97.24 220 | 97.27 70 | 98.94 76 | 99.23 12 | 95.13 113 | 95.51 178 | 97.32 219 | 85.73 246 | 98.91 202 | 97.33 62 | 89.55 281 | 96.89 237 |
|
TSAR-MVS + GP. | | | 98.38 35 | 98.24 33 | 98.81 61 | 99.22 76 | 97.25 73 | 98.11 220 | 98.29 176 | 97.19 31 | 98.99 24 | 99.02 62 | 96.22 13 | 99.67 103 | 98.52 14 | 98.56 113 | 99.51 72 |
|
NR-MVSNet | | | 94.98 198 | 94.16 210 | 97.44 160 | 96.53 259 | 97.22 74 | 98.74 127 | 98.95 33 | 94.96 123 | 89.25 311 | 97.69 191 | 89.32 146 | 98.18 284 | 94.59 157 | 87.40 312 | 96.92 229 |
|
LS3D | | | 97.16 93 | 96.66 101 | 98.68 66 | 98.53 142 | 97.19 75 | 98.93 77 | 98.90 43 | 92.83 219 | 95.99 175 | 99.37 14 | 92.12 101 | 99.87 38 | 93.67 180 | 99.57 58 | 98.97 140 |
|
test222 | | | | | | 99.23 75 | 97.17 76 | 97.40 276 | 98.66 112 | 88.68 315 | 98.05 66 | 98.96 74 | 94.14 72 | | | 99.53 68 | 99.61 59 |
|
CPTT-MVS | | | 97.72 59 | 97.32 67 | 98.92 56 | 99.64 21 | 97.10 77 | 99.12 51 | 98.81 65 | 92.34 239 | 98.09 64 | 99.08 57 | 93.01 84 | 99.92 15 | 96.06 109 | 99.77 19 | 99.75 22 |
|
Regformer-3 | | | 98.59 17 | 98.50 12 | 98.86 60 | 99.43 40 | 97.05 78 | 98.40 184 | 98.68 102 | 97.43 14 | 99.06 18 | 99.31 23 | 95.80 34 | 99.77 84 | 98.62 6 | 99.76 25 | 99.78 8 |
|
HY-MVS | | 93.96 8 | 96.82 107 | 96.23 116 | 98.57 72 | 98.46 144 | 97.00 79 | 98.14 215 | 98.21 186 | 93.95 161 | 96.72 137 | 97.99 166 | 91.58 112 | 99.76 86 | 94.51 160 | 96.54 172 | 98.95 144 |
|
UniMVSNet_NR-MVSNet | | | 95.71 146 | 95.15 154 | 97.40 164 | 96.84 245 | 96.97 80 | 98.74 127 | 99.24 10 | 95.16 111 | 93.88 237 | 97.72 190 | 91.68 110 | 98.31 276 | 95.81 118 | 87.25 315 | 96.92 229 |
|
DU-MVS | | | 95.42 171 | 94.76 181 | 97.40 164 | 96.53 259 | 96.97 80 | 98.66 147 | 98.99 28 | 95.43 90 | 93.88 237 | 97.69 191 | 88.57 179 | 98.31 276 | 95.81 118 | 87.25 315 | 96.92 229 |
|
DeepC-MVS | | 95.98 3 | 97.88 52 | 97.58 53 | 98.77 62 | 99.25 69 | 96.93 82 | 98.83 100 | 98.75 83 | 96.96 42 | 96.89 129 | 99.50 4 | 90.46 133 | 99.87 38 | 97.84 38 | 99.76 25 | 99.52 69 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
PAPR | | | 96.84 106 | 96.24 115 | 98.65 68 | 98.72 127 | 96.92 83 | 97.36 282 | 98.57 126 | 93.33 199 | 96.67 138 | 97.57 202 | 94.30 70 | 99.56 123 | 91.05 248 | 98.59 111 | 99.47 80 |
|
MVS_111021_LR | | | 98.34 39 | 98.23 34 | 98.67 67 | 99.27 66 | 96.90 84 | 97.95 234 | 99.58 3 | 97.14 34 | 98.44 55 | 99.01 66 | 95.03 54 | 99.62 112 | 97.91 31 | 99.75 31 | 99.50 74 |
|
MAR-MVS | | | 96.91 103 | 96.40 109 | 98.45 84 | 98.69 130 | 96.90 84 | 98.66 147 | 98.68 102 | 92.40 237 | 97.07 117 | 97.96 167 | 91.54 116 | 99.75 88 | 93.68 179 | 98.92 95 | 98.69 156 |
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020 |
WTY-MVS | | | 97.37 82 | 96.92 85 | 98.72 64 | 98.86 115 | 96.89 86 | 98.31 195 | 98.71 96 | 95.26 105 | 97.67 94 | 98.56 113 | 92.21 98 | 99.78 79 | 95.89 115 | 96.85 162 | 99.48 79 |
|
MSLP-MVS++ | | | 98.56 23 | 98.57 6 | 98.55 74 | 99.26 68 | 96.80 87 | 98.71 133 | 99.05 23 | 97.28 22 | 98.84 31 | 99.28 28 | 96.47 11 | 99.40 142 | 98.52 14 | 99.70 39 | 99.47 80 |
|
API-MVS | | | 97.41 79 | 97.25 69 | 97.91 117 | 98.70 128 | 96.80 87 | 98.82 102 | 98.69 99 | 94.53 139 | 98.11 63 | 98.28 142 | 94.50 66 | 99.57 121 | 94.12 170 | 99.49 70 | 97.37 210 |
|
PCF-MVS | | 93.45 11 | 94.68 220 | 93.43 256 | 98.42 88 | 98.62 136 | 96.77 89 | 95.48 336 | 98.20 189 | 84.63 339 | 93.34 252 | 98.32 138 | 88.55 181 | 99.81 55 | 84.80 328 | 98.96 94 | 98.68 157 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
ab-mvs | | | 96.42 120 | 95.71 131 | 98.55 74 | 98.63 135 | 96.75 90 | 97.88 245 | 98.74 84 | 93.84 166 | 96.54 149 | 98.18 151 | 85.34 254 | 99.75 88 | 95.93 114 | 96.35 181 | 99.15 121 |
|
Effi-MVS+ | | | 97.12 95 | 96.69 98 | 98.39 90 | 98.19 161 | 96.72 91 | 97.37 280 | 98.43 154 | 93.71 175 | 97.65 98 | 98.02 161 | 92.20 99 | 99.25 154 | 96.87 82 | 97.79 144 | 99.19 113 |
|
casdiffmvs1 | | | 97.72 59 | 97.49 59 | 98.41 89 | 98.52 143 | 96.71 92 | 99.14 45 | 98.32 168 | 95.15 112 | 98.46 50 | 98.31 139 | 93.10 83 | 99.21 164 | 98.14 24 | 98.27 127 | 99.31 97 |
|
AdaColmap | | | 97.15 94 | 96.70 97 | 98.48 82 | 99.16 81 | 96.69 93 | 98.01 229 | 98.89 45 | 94.44 145 | 96.83 131 | 98.68 100 | 90.69 131 | 99.76 86 | 94.36 162 | 99.29 86 | 98.98 139 |
|
原ACMM1 | | | | | 98.65 68 | 99.32 50 | 96.62 94 | | 98.67 109 | 93.27 203 | 97.81 85 | 98.97 69 | 95.18 50 | 99.83 47 | 93.84 175 | 99.46 75 | 99.50 74 |
|
FMVSNet3 | | | 94.97 199 | 94.26 203 | 97.11 177 | 98.18 163 | 96.62 94 | 98.56 161 | 98.26 181 | 93.67 182 | 94.09 229 | 97.10 237 | 84.25 277 | 98.01 293 | 92.08 221 | 92.14 254 | 96.70 260 |
|
sss | | | 97.39 80 | 96.98 83 | 98.61 70 | 98.60 138 | 96.61 96 | 98.22 203 | 98.93 36 | 93.97 160 | 98.01 74 | 98.48 119 | 91.98 105 | 99.85 43 | 96.45 98 | 98.15 131 | 99.39 90 |
|
0601test | | | 97.22 88 | 96.78 91 | 98.54 76 | 98.73 123 | 96.60 97 | 98.45 175 | 98.31 169 | 94.70 129 | 98.02 70 | 98.42 124 | 90.80 128 | 99.70 96 | 96.81 84 | 96.79 164 | 99.34 92 |
|
Anonymous20240521 | | | 97.22 88 | 96.78 91 | 98.54 76 | 98.73 123 | 96.60 97 | 98.45 175 | 98.31 169 | 94.70 129 | 98.02 70 | 98.42 124 | 90.80 128 | 99.70 96 | 96.81 84 | 96.79 164 | 99.34 92 |
|
VPNet | | | 94.99 196 | 94.19 209 | 97.40 164 | 97.16 228 | 96.57 99 | 98.71 133 | 98.97 29 | 95.67 79 | 94.84 188 | 98.24 148 | 80.36 310 | 98.67 224 | 96.46 97 | 87.32 313 | 96.96 226 |
|
MVS | | | 94.67 221 | 93.54 250 | 98.08 109 | 96.88 243 | 96.56 100 | 98.19 209 | 98.50 142 | 78.05 352 | 92.69 269 | 98.02 161 | 91.07 124 | 99.63 110 | 90.09 266 | 98.36 122 | 98.04 186 |
|
XXY-MVS | | | 95.20 189 | 94.45 197 | 97.46 159 | 96.75 250 | 96.56 100 | 98.86 95 | 98.65 116 | 93.30 202 | 93.27 253 | 98.27 145 | 84.85 261 | 98.87 208 | 94.82 150 | 91.26 268 | 96.96 226 |
|
casdiffmvs | | | 97.42 77 | 97.12 74 | 98.31 94 | 98.35 147 | 96.55 102 | 99.05 60 | 98.20 189 | 94.97 122 | 97.55 106 | 98.11 155 | 92.33 93 | 99.18 167 | 97.70 45 | 97.85 142 | 99.18 117 |
|
PatchMatch-RL | | | 96.59 114 | 96.03 121 | 98.27 95 | 99.31 52 | 96.51 103 | 97.91 239 | 99.06 21 | 93.72 174 | 96.92 127 | 98.06 159 | 88.50 184 | 99.65 105 | 91.77 233 | 99.00 93 | 98.66 160 |
|
EI-MVSNet-Vis-set | | | 98.47 30 | 98.39 16 | 98.69 65 | 99.46 37 | 96.49 104 | 98.30 197 | 98.69 99 | 97.21 29 | 98.84 31 | 99.36 18 | 95.41 41 | 99.78 79 | 98.62 6 | 99.65 45 | 99.80 4 |
|
WR-MVS | | | 95.15 190 | 94.46 195 | 97.22 169 | 96.67 255 | 96.45 105 | 98.21 204 | 98.81 65 | 94.15 149 | 93.16 256 | 97.69 191 | 87.51 211 | 98.30 278 | 95.29 139 | 88.62 299 | 96.90 236 |
|
FMVSNet2 | | | 94.47 232 | 93.61 246 | 97.04 180 | 98.21 158 | 96.43 106 | 98.79 116 | 98.27 177 | 92.46 226 | 93.50 249 | 97.09 239 | 81.16 300 | 98.00 294 | 91.09 244 | 91.93 258 | 96.70 260 |
|
PAPM_NR | | | 97.46 71 | 97.11 76 | 98.50 80 | 99.50 32 | 96.41 107 | 98.63 149 | 98.60 119 | 95.18 109 | 97.06 118 | 98.06 159 | 94.26 71 | 99.57 121 | 93.80 177 | 98.87 99 | 99.52 69 |
|
1112_ss | | | 96.63 111 | 96.00 122 | 98.50 80 | 98.56 139 | 96.37 108 | 98.18 213 | 98.10 218 | 92.92 214 | 94.84 188 | 98.43 122 | 92.14 100 | 99.58 120 | 94.35 163 | 96.51 173 | 99.56 68 |
|
TranMVSNet+NR-MVSNet | | | 95.14 191 | 94.48 193 | 97.11 177 | 96.45 264 | 96.36 109 | 99.03 64 | 99.03 24 | 95.04 118 | 93.58 244 | 97.93 171 | 88.27 187 | 98.03 292 | 94.13 169 | 86.90 320 | 96.95 228 |
|
IS-MVSNet | | | 97.22 88 | 96.88 86 | 98.25 97 | 98.85 117 | 96.36 109 | 99.19 35 | 97.97 230 | 95.39 92 | 97.23 110 | 98.99 68 | 91.11 122 | 98.93 200 | 94.60 156 | 98.59 111 | 99.47 80 |
|
EI-MVSNet-UG-set | | | 98.41 33 | 98.34 22 | 98.61 70 | 99.45 38 | 96.32 111 | 98.28 199 | 98.68 102 | 97.17 32 | 98.74 38 | 99.37 14 | 95.25 48 | 99.79 74 | 98.57 8 | 99.54 67 | 99.73 29 |
|
LFMVS | | | 95.86 139 | 94.98 161 | 98.47 83 | 98.87 114 | 96.32 111 | 98.84 99 | 96.02 325 | 93.40 197 | 98.62 44 | 99.20 38 | 74.99 335 | 99.63 110 | 97.72 44 | 97.20 157 | 99.46 84 |
|
PLC | | 95.07 4 | 97.20 91 | 96.78 91 | 98.44 85 | 99.29 60 | 96.31 113 | 98.14 215 | 98.76 80 | 92.41 236 | 96.39 166 | 98.31 139 | 94.92 56 | 99.78 79 | 94.06 171 | 98.77 104 | 99.23 109 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
Vis-MVSNet | | | 97.42 77 | 97.11 76 | 98.34 92 | 98.66 132 | 96.23 114 | 99.22 29 | 99.00 26 | 96.63 52 | 98.04 68 | 99.21 35 | 88.05 195 | 99.35 147 | 96.01 112 | 99.21 87 | 99.45 86 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
DP-MVS | | | 96.59 114 | 95.93 123 | 98.57 72 | 99.34 44 | 96.19 115 | 98.70 136 | 98.39 159 | 89.45 308 | 94.52 197 | 99.35 20 | 91.85 107 | 99.85 43 | 92.89 205 | 98.88 97 | 99.68 44 |
|
EPNet | | | 97.28 86 | 96.87 87 | 98.51 79 | 94.98 327 | 96.14 116 | 98.90 79 | 97.02 295 | 98.28 1 | 95.99 175 | 99.11 49 | 91.36 118 | 99.89 29 | 96.98 69 | 99.19 88 | 99.50 74 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
diffmvs1 | | | 97.35 84 | 97.07 79 | 98.20 99 | 98.25 155 | 96.13 117 | 98.61 152 | 98.34 165 | 95.47 87 | 97.66 97 | 98.01 163 | 92.54 89 | 99.30 148 | 96.44 99 | 98.29 126 | 99.17 119 |
|
CANet_DTU | | | 96.96 101 | 96.55 104 | 98.21 98 | 98.17 165 | 96.07 118 | 97.98 232 | 98.21 186 | 97.24 28 | 97.13 113 | 98.93 78 | 86.88 222 | 99.91 24 | 95.00 146 | 99.37 83 | 98.66 160 |
|
xiu_mvs_v1_base_debu | | | 97.60 65 | 97.56 54 | 97.72 131 | 98.35 147 | 95.98 119 | 97.86 247 | 98.51 137 | 97.13 35 | 99.01 21 | 98.40 126 | 91.56 113 | 99.80 62 | 98.53 10 | 98.68 105 | 97.37 210 |
|
xiu_mvs_v1_base | | | 97.60 65 | 97.56 54 | 97.72 131 | 98.35 147 | 95.98 119 | 97.86 247 | 98.51 137 | 97.13 35 | 99.01 21 | 98.40 126 | 91.56 113 | 99.80 62 | 98.53 10 | 98.68 105 | 97.37 210 |
|
xiu_mvs_v1_base_debi | | | 97.60 65 | 97.56 54 | 97.72 131 | 98.35 147 | 95.98 119 | 97.86 247 | 98.51 137 | 97.13 35 | 99.01 21 | 98.40 126 | 91.56 113 | 99.80 62 | 98.53 10 | 98.68 105 | 97.37 210 |
|
CDS-MVSNet | | | 96.99 100 | 96.69 98 | 97.90 118 | 98.05 173 | 95.98 119 | 98.20 205 | 98.33 167 | 93.67 182 | 96.95 122 | 98.49 118 | 93.54 77 | 98.42 258 | 95.24 143 | 97.74 147 | 99.31 97 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
Fast-Effi-MVS+ | | | 96.28 126 | 95.70 132 | 98.03 112 | 98.29 154 | 95.97 123 | 98.58 156 | 98.25 182 | 91.74 254 | 95.29 182 | 97.23 225 | 91.03 125 | 99.15 169 | 92.90 203 | 97.96 136 | 98.97 140 |
|
MVS_Test | | | 97.28 86 | 97.00 82 | 98.13 105 | 98.33 152 | 95.97 123 | 98.74 127 | 98.07 223 | 94.27 147 | 98.44 55 | 98.07 158 | 92.48 90 | 99.26 153 | 96.43 100 | 98.19 130 | 99.16 120 |
|
MG-MVS | | | 97.81 56 | 97.60 52 | 98.44 85 | 99.12 85 | 95.97 123 | 97.75 256 | 98.78 76 | 96.89 43 | 98.46 50 | 99.22 34 | 93.90 76 | 99.68 102 | 94.81 151 | 99.52 69 | 99.67 49 |
|
test_normal | | | 94.72 216 | 93.59 247 | 98.11 107 | 95.30 324 | 95.95 126 | 97.91 239 | 97.39 275 | 94.64 136 | 85.70 328 | 95.88 306 | 80.52 308 | 99.36 146 | 96.69 89 | 98.30 125 | 99.01 138 |
|
tfpnnormal | | | 93.66 263 | 92.70 270 | 96.55 225 | 96.94 238 | 95.94 127 | 98.97 72 | 99.19 15 | 91.04 277 | 91.38 292 | 97.34 217 | 84.94 259 | 98.61 227 | 85.45 325 | 89.02 289 | 95.11 323 |
|
pmmvs4 | | | 94.69 217 | 93.99 223 | 96.81 193 | 95.74 309 | 95.94 127 | 97.40 276 | 97.67 242 | 90.42 285 | 93.37 251 | 97.59 200 | 89.08 153 | 98.20 283 | 92.97 198 | 91.67 262 | 96.30 301 |
|
Test_1112_low_res | | | 96.34 123 | 95.66 135 | 98.36 91 | 98.56 139 | 95.94 127 | 97.71 258 | 98.07 223 | 92.10 245 | 94.79 192 | 97.29 221 | 91.75 109 | 99.56 123 | 94.17 168 | 96.50 174 | 99.58 66 |
|
conf0.01 | | | 95.56 158 | 94.84 174 | 97.72 131 | 98.90 104 | 95.93 130 | 99.17 36 | 95.70 331 | 93.42 191 | 96.50 156 | 97.16 228 | 86.12 233 | 99.22 158 | 90.51 256 | 96.06 198 | 98.02 187 |
|
conf0.002 | | | 95.56 158 | 94.84 174 | 97.72 131 | 98.90 104 | 95.93 130 | 99.17 36 | 95.70 331 | 93.42 191 | 96.50 156 | 97.16 228 | 86.12 233 | 99.22 158 | 90.51 256 | 96.06 198 | 98.02 187 |
|
thresconf0.02 | | | 95.50 161 | 94.84 174 | 97.51 153 | 98.90 104 | 95.93 130 | 99.17 36 | 95.70 331 | 93.42 191 | 96.50 156 | 97.16 228 | 86.12 233 | 99.22 158 | 90.51 256 | 96.06 198 | 97.37 210 |
|
tfpn_n400 | | | 95.50 161 | 94.84 174 | 97.51 153 | 98.90 104 | 95.93 130 | 99.17 36 | 95.70 331 | 93.42 191 | 96.50 156 | 97.16 228 | 86.12 233 | 99.22 158 | 90.51 256 | 96.06 198 | 97.37 210 |
|
tfpnconf | | | 95.50 161 | 94.84 174 | 97.51 153 | 98.90 104 | 95.93 130 | 99.17 36 | 95.70 331 | 93.42 191 | 96.50 156 | 97.16 228 | 86.12 233 | 99.22 158 | 90.51 256 | 96.06 198 | 97.37 210 |
|
tfpnview11 | | | 95.50 161 | 94.84 174 | 97.51 153 | 98.90 104 | 95.93 130 | 99.17 36 | 95.70 331 | 93.42 191 | 96.50 156 | 97.16 228 | 86.12 233 | 99.22 158 | 90.51 256 | 96.06 198 | 97.37 210 |
|
MVSTER | | | 96.06 131 | 95.72 128 | 97.08 179 | 98.23 157 | 95.93 130 | 98.73 130 | 98.27 177 | 94.86 127 | 95.07 183 | 98.09 157 | 88.21 188 | 98.54 234 | 96.59 92 | 93.46 238 | 96.79 248 |
|
DI_MVS_plusplus_test | | | 94.74 215 | 93.62 245 | 98.09 108 | 95.34 323 | 95.92 137 | 98.09 223 | 97.34 277 | 94.66 135 | 85.89 325 | 95.91 305 | 80.49 309 | 99.38 145 | 96.66 90 | 98.22 128 | 98.97 140 |
|
OMC-MVS | | | 97.55 70 | 97.34 66 | 98.20 99 | 99.33 47 | 95.92 137 | 98.28 199 | 98.59 120 | 95.52 86 | 97.97 77 | 99.10 51 | 93.28 81 | 99.49 133 | 95.09 145 | 98.88 97 | 99.19 113 |
|
PVSNet_Blended_VisFu | | | 97.70 61 | 97.46 62 | 98.44 85 | 99.27 66 | 95.91 139 | 98.63 149 | 99.16 17 | 94.48 143 | 97.67 94 | 98.88 82 | 92.80 86 | 99.91 24 | 97.11 66 | 99.12 90 | 99.50 74 |
|
anonymousdsp | | | 95.42 171 | 94.91 169 | 96.94 187 | 95.10 326 | 95.90 140 | 99.14 45 | 98.41 155 | 93.75 170 | 93.16 256 | 97.46 207 | 87.50 213 | 98.41 265 | 95.63 128 | 94.03 227 | 96.50 291 |
|
UGNet | | | 96.78 108 | 96.30 112 | 98.19 102 | 98.24 156 | 95.89 141 | 98.88 86 | 98.93 36 | 97.39 17 | 96.81 134 | 97.84 179 | 82.60 294 | 99.90 27 | 96.53 95 | 99.49 70 | 98.79 151 |
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022 |
tfpn_ndepth | | | 95.53 160 | 94.90 170 | 97.39 167 | 98.96 101 | 95.88 142 | 99.05 60 | 95.27 340 | 93.80 169 | 96.95 122 | 96.93 264 | 85.53 249 | 99.40 142 | 91.54 238 | 96.10 197 | 96.89 237 |
|
Test4 | | | 92.21 284 | 90.34 300 | 97.82 124 | 92.83 341 | 95.87 143 | 97.94 235 | 98.05 228 | 94.50 141 | 82.12 344 | 94.48 322 | 59.54 357 | 98.54 234 | 95.39 134 | 98.22 128 | 99.06 133 |
|
WR-MVS_H | | | 95.05 194 | 94.46 195 | 96.81 193 | 96.86 244 | 95.82 144 | 99.24 21 | 99.24 10 | 93.87 165 | 92.53 274 | 96.84 274 | 90.37 134 | 98.24 282 | 93.24 189 | 87.93 305 | 96.38 297 |
|
MVSFormer | | | 97.57 68 | 97.49 59 | 97.84 121 | 98.07 170 | 95.76 145 | 99.47 2 | 98.40 157 | 94.98 120 | 98.79 34 | 98.83 86 | 92.34 91 | 98.41 265 | 96.91 74 | 99.59 55 | 99.34 92 |
|
lupinMVS | | | 97.44 75 | 97.22 72 | 98.12 106 | 98.07 170 | 95.76 145 | 97.68 261 | 97.76 238 | 94.50 141 | 98.79 34 | 98.61 107 | 92.34 91 | 99.30 148 | 97.58 51 | 99.59 55 | 99.31 97 |
|
tfpn1000 | | | 95.72 144 | 95.11 155 | 97.58 149 | 99.00 93 | 95.73 147 | 99.24 21 | 95.49 339 | 94.08 152 | 96.87 130 | 97.45 209 | 85.81 245 | 99.30 148 | 91.78 232 | 96.22 194 | 97.71 200 |
|
PAPM | | | 94.95 200 | 94.00 221 | 97.78 126 | 97.04 233 | 95.65 148 | 96.03 329 | 98.25 182 | 91.23 274 | 94.19 224 | 97.80 185 | 91.27 120 | 98.86 210 | 82.61 332 | 97.61 151 | 98.84 149 |
|
jason | | | 97.32 85 | 97.08 78 | 98.06 111 | 97.45 209 | 95.59 149 | 97.87 246 | 97.91 233 | 94.79 128 | 98.55 48 | 98.83 86 | 91.12 121 | 99.23 156 | 97.58 51 | 99.60 52 | 99.34 92 |
jason: jason. |
PS-MVSNAJ | | | 97.73 58 | 97.77 47 | 97.62 143 | 98.68 131 | 95.58 150 | 97.34 284 | 98.51 137 | 97.29 21 | 98.66 42 | 97.88 175 | 94.51 63 | 99.90 27 | 97.87 35 | 99.17 89 | 97.39 208 |
|
testing_2 | | | 90.61 308 | 88.50 315 | 96.95 186 | 90.08 349 | 95.57 151 | 97.69 260 | 98.06 225 | 93.02 209 | 76.55 350 | 92.48 345 | 61.18 356 | 98.44 255 | 95.45 133 | 91.98 257 | 96.84 244 |
|
CP-MVSNet | | | 94.94 202 | 94.30 202 | 96.83 192 | 96.72 252 | 95.56 152 | 99.11 52 | 98.95 33 | 93.89 163 | 92.42 279 | 97.90 173 | 87.19 216 | 98.12 286 | 94.32 164 | 88.21 302 | 96.82 247 |
|
HyFIR lowres test | | | 96.90 104 | 96.49 107 | 98.14 103 | 99.33 47 | 95.56 152 | 97.38 278 | 99.65 2 | 92.34 239 | 97.61 101 | 98.20 150 | 89.29 147 | 99.10 179 | 96.97 70 | 97.60 152 | 99.77 15 |
|
1314 | | | 96.25 128 | 95.73 127 | 97.79 125 | 97.13 230 | 95.55 154 | 98.19 209 | 98.59 120 | 93.47 189 | 92.03 287 | 97.82 183 | 91.33 119 | 99.49 133 | 94.62 155 | 98.44 118 | 98.32 181 |
|
thisisatest0530 | | | 96.01 132 | 95.36 143 | 97.97 114 | 98.38 146 | 95.52 155 | 98.88 86 | 94.19 355 | 94.04 154 | 97.64 99 | 98.31 139 | 83.82 289 | 99.46 139 | 95.29 139 | 97.70 149 | 98.93 145 |
|
test_djsdf | | | 96.00 133 | 95.69 133 | 96.93 188 | 95.72 311 | 95.49 156 | 99.47 2 | 98.40 157 | 94.98 120 | 94.58 195 | 97.86 176 | 89.16 151 | 98.41 265 | 96.91 74 | 94.12 225 | 96.88 239 |
|
xiu_mvs_v2_base | | | 97.66 64 | 97.70 50 | 97.56 151 | 98.61 137 | 95.46 157 | 97.44 273 | 98.46 147 | 97.15 33 | 98.65 43 | 98.15 152 | 94.33 69 | 99.80 62 | 97.84 38 | 98.66 109 | 97.41 206 |
|
Vis-MVSNet (Re-imp) | | | 96.87 105 | 96.55 104 | 97.83 122 | 98.73 123 | 95.46 157 | 99.20 33 | 98.30 174 | 94.96 123 | 96.60 144 | 98.87 83 | 90.05 139 | 98.59 230 | 93.67 180 | 98.60 110 | 99.46 84 |
|
EPP-MVSNet | | | 97.46 71 | 97.28 68 | 97.99 113 | 98.64 134 | 95.38 159 | 99.33 13 | 98.31 169 | 93.61 185 | 97.19 111 | 99.07 58 | 94.05 73 | 99.23 156 | 96.89 76 | 98.43 120 | 99.37 91 |
|
testdata | | | | | 98.26 96 | 99.20 79 | 95.36 160 | | 98.68 102 | 91.89 250 | 98.60 46 | 99.10 51 | 94.44 68 | 99.82 53 | 94.27 166 | 99.44 77 | 99.58 66 |
|
MSDG | | | 95.93 136 | 95.30 149 | 97.83 122 | 98.90 104 | 95.36 160 | 96.83 312 | 98.37 162 | 91.32 269 | 94.43 207 | 98.73 97 | 90.27 137 | 99.60 113 | 90.05 269 | 98.82 102 | 98.52 166 |
|
PVSNet_BlendedMVS | | | 96.73 109 | 96.60 102 | 97.12 176 | 99.25 69 | 95.35 162 | 98.26 201 | 99.26 8 | 94.28 146 | 97.94 79 | 97.46 207 | 92.74 87 | 99.81 55 | 96.88 79 | 93.32 243 | 96.20 303 |
|
PVSNet_Blended | | | 97.38 81 | 97.12 74 | 98.14 103 | 99.25 69 | 95.35 162 | 97.28 288 | 99.26 8 | 93.13 206 | 97.94 79 | 98.21 149 | 92.74 87 | 99.81 55 | 96.88 79 | 99.40 81 | 99.27 105 |
|
TAMVS | | | 97.02 99 | 96.79 90 | 97.70 136 | 98.06 172 | 95.31 164 | 98.52 166 | 98.31 169 | 93.95 161 | 97.05 119 | 98.61 107 | 93.49 78 | 98.52 241 | 95.33 136 | 97.81 143 | 99.29 103 |
|
PS-CasMVS | | | 94.67 221 | 93.99 223 | 96.71 197 | 96.68 254 | 95.26 165 | 99.13 49 | 99.03 24 | 93.68 180 | 92.33 280 | 97.95 168 | 85.35 253 | 98.10 287 | 93.59 182 | 88.16 304 | 96.79 248 |
|
diffmvs | | | 97.03 98 | 96.75 96 | 97.88 119 | 98.14 167 | 95.25 166 | 98.54 165 | 98.13 205 | 95.17 110 | 97.03 120 | 97.94 169 | 91.83 108 | 99.30 148 | 96.01 112 | 97.94 137 | 99.11 126 |
|
V42 | | | 94.78 210 | 94.14 212 | 96.70 199 | 96.33 278 | 95.22 167 | 98.97 72 | 98.09 221 | 92.32 241 | 94.31 214 | 97.06 244 | 88.39 185 | 98.55 233 | 92.90 203 | 88.87 294 | 96.34 299 |
|
pm-mvs1 | | | 93.94 259 | 93.06 263 | 96.59 217 | 96.49 262 | 95.16 168 | 98.95 74 | 98.03 229 | 92.32 241 | 91.08 295 | 97.84 179 | 84.54 270 | 98.41 265 | 92.16 219 | 86.13 326 | 96.19 304 |
|
CSCG | | | 97.85 55 | 97.74 49 | 98.20 99 | 99.67 19 | 95.16 168 | 99.22 29 | 99.32 7 | 93.04 208 | 97.02 121 | 98.92 80 | 95.36 43 | 99.91 24 | 97.43 58 | 99.64 47 | 99.52 69 |
|
thisisatest0515 | | | 95.61 153 | 94.89 171 | 97.76 128 | 98.15 166 | 95.15 170 | 96.77 313 | 94.41 350 | 92.95 213 | 97.18 112 | 97.43 211 | 84.78 262 | 99.45 140 | 94.63 153 | 97.73 148 | 98.68 157 |
|
VDDNet | | | 95.36 178 | 94.53 191 | 97.86 120 | 98.10 169 | 95.13 171 | 98.85 96 | 97.75 239 | 90.46 283 | 98.36 57 | 99.39 9 | 73.27 342 | 99.64 107 | 97.98 29 | 96.58 170 | 98.81 150 |
|
gg-mvs-nofinetune | | | 92.21 284 | 90.58 298 | 97.13 175 | 96.75 250 | 95.09 172 | 95.85 332 | 89.40 364 | 85.43 335 | 94.50 198 | 81.98 356 | 80.80 306 | 98.40 271 | 92.16 219 | 98.33 123 | 97.88 193 |
|
PS-MVSNAJss | | | 96.43 119 | 96.26 114 | 96.92 190 | 95.84 307 | 95.08 173 | 99.16 43 | 98.50 142 | 95.87 72 | 93.84 240 | 98.34 136 | 94.51 63 | 98.61 227 | 96.88 79 | 93.45 240 | 97.06 220 |
|
thres600view7 | | | 95.49 165 | 94.77 180 | 97.67 139 | 98.98 97 | 95.02 174 | 98.85 96 | 96.90 305 | 95.38 93 | 96.63 140 | 96.90 266 | 84.29 273 | 99.59 114 | 88.65 297 | 96.33 182 | 98.40 172 |
|
GBi-Net | | | 94.49 230 | 93.80 233 | 96.56 222 | 98.21 158 | 95.00 175 | 98.82 102 | 98.18 194 | 92.46 226 | 94.09 229 | 97.07 241 | 81.16 300 | 97.95 296 | 92.08 221 | 92.14 254 | 96.72 256 |
|
test1 | | | 94.49 230 | 93.80 233 | 96.56 222 | 98.21 158 | 95.00 175 | 98.82 102 | 98.18 194 | 92.46 226 | 94.09 229 | 97.07 241 | 81.16 300 | 97.95 296 | 92.08 221 | 92.14 254 | 96.72 256 |
|
FMVSNet1 | | | 93.19 275 | 92.07 278 | 96.56 222 | 97.54 201 | 95.00 175 | 98.82 102 | 98.18 194 | 90.38 286 | 92.27 281 | 97.07 241 | 73.68 341 | 97.95 296 | 89.36 284 | 91.30 266 | 96.72 256 |
|
tfpn200view9 | | | 95.32 182 | 94.62 187 | 97.43 161 | 98.94 102 | 94.98 178 | 98.68 142 | 96.93 303 | 95.33 101 | 96.55 147 | 96.53 285 | 84.23 278 | 99.56 123 | 88.11 304 | 96.29 185 | 97.76 195 |
|
GG-mvs-BLEND | | | | | 96.59 217 | 96.34 274 | 94.98 178 | 96.51 324 | 88.58 365 | | 93.10 261 | 94.34 325 | 80.34 311 | 98.05 291 | 89.53 280 | 96.99 160 | 96.74 253 |
|
thres400 | | | 95.38 175 | 94.62 187 | 97.65 142 | 98.94 102 | 94.98 178 | 98.68 142 | 96.93 303 | 95.33 101 | 96.55 147 | 96.53 285 | 84.23 278 | 99.56 123 | 88.11 304 | 96.29 185 | 98.40 172 |
|
F-COLMAP | | | 97.09 97 | 96.80 88 | 97.97 114 | 99.45 38 | 94.95 181 | 98.55 163 | 98.62 118 | 93.02 209 | 96.17 170 | 98.58 112 | 94.01 74 | 99.81 55 | 93.95 173 | 98.90 96 | 99.14 123 |
|
tfpn111 | | | 95.43 169 | 94.74 182 | 97.51 153 | 98.98 97 | 94.92 182 | 98.87 88 | 96.90 305 | 95.38 93 | 96.61 141 | 96.88 269 | 84.29 273 | 99.59 114 | 88.43 298 | 96.32 183 | 98.02 187 |
|
conf200view11 | | | 95.40 174 | 94.70 184 | 97.50 158 | 98.98 97 | 94.92 182 | 98.87 88 | 96.90 305 | 95.38 93 | 96.61 141 | 96.88 269 | 84.29 273 | 99.56 123 | 88.11 304 | 96.29 185 | 98.02 187 |
|
thres100view900 | | | 95.38 175 | 94.70 184 | 97.41 162 | 98.98 97 | 94.92 182 | 98.87 88 | 96.90 305 | 95.38 93 | 96.61 141 | 96.88 269 | 84.29 273 | 99.56 123 | 88.11 304 | 96.29 185 | 97.76 195 |
|
thres200 | | | 95.25 185 | 94.57 189 | 97.28 168 | 98.81 119 | 94.92 182 | 98.20 205 | 97.11 289 | 95.24 108 | 96.54 149 | 96.22 298 | 84.58 265 | 99.53 130 | 87.93 309 | 96.50 174 | 97.39 208 |
|
v1 | | | 94.75 213 | 94.11 216 | 96.69 200 | 96.27 286 | 94.87 186 | 98.69 138 | 98.12 208 | 92.43 234 | 94.32 213 | 96.94 260 | 88.71 176 | 98.54 234 | 92.66 209 | 88.84 297 | 96.67 266 |
|
v1141 | | | 94.75 213 | 94.11 216 | 96.67 206 | 96.27 286 | 94.86 187 | 98.69 138 | 98.12 208 | 92.43 234 | 94.31 214 | 96.94 260 | 88.78 172 | 98.48 245 | 92.63 210 | 88.85 296 | 96.67 266 |
|
view600 | | | 95.60 154 | 94.93 165 | 97.62 143 | 99.05 87 | 94.85 188 | 99.09 54 | 97.01 297 | 95.36 97 | 96.52 151 | 97.37 213 | 84.55 266 | 99.59 114 | 89.07 288 | 96.39 177 | 98.40 172 |
|
view800 | | | 95.60 154 | 94.93 165 | 97.62 143 | 99.05 87 | 94.85 188 | 99.09 54 | 97.01 297 | 95.36 97 | 96.52 151 | 97.37 213 | 84.55 266 | 99.59 114 | 89.07 288 | 96.39 177 | 98.40 172 |
|
conf0.05thres1000 | | | 95.60 154 | 94.93 165 | 97.62 143 | 99.05 87 | 94.85 188 | 99.09 54 | 97.01 297 | 95.36 97 | 96.52 151 | 97.37 213 | 84.55 266 | 99.59 114 | 89.07 288 | 96.39 177 | 98.40 172 |
|
tfpn | | | 95.60 154 | 94.93 165 | 97.62 143 | 99.05 87 | 94.85 188 | 99.09 54 | 97.01 297 | 95.36 97 | 96.52 151 | 97.37 213 | 84.55 266 | 99.59 114 | 89.07 288 | 96.39 177 | 98.40 172 |
|
v1neww | | | 94.83 205 | 94.22 204 | 96.68 203 | 96.39 267 | 94.85 188 | 98.87 88 | 98.11 213 | 92.45 231 | 94.45 200 | 97.06 244 | 88.82 167 | 98.54 234 | 92.93 200 | 88.91 292 | 96.65 271 |
|
v7new | | | 94.83 205 | 94.22 204 | 96.68 203 | 96.39 267 | 94.85 188 | 98.87 88 | 98.11 213 | 92.45 231 | 94.45 200 | 97.06 244 | 88.82 167 | 98.54 234 | 92.93 200 | 88.91 292 | 96.65 271 |
|
v18 | | | 92.10 286 | 90.97 286 | 95.50 270 | 96.34 274 | 94.85 188 | 98.82 102 | 97.52 253 | 89.99 292 | 85.31 332 | 93.26 330 | 88.90 161 | 96.92 322 | 88.82 293 | 79.77 341 | 94.73 329 |
|
divwei89l23v2f112 | | | 94.76 211 | 94.12 215 | 96.67 206 | 96.28 284 | 94.85 188 | 98.69 138 | 98.12 208 | 92.44 233 | 94.29 217 | 96.94 260 | 88.85 164 | 98.48 245 | 92.67 208 | 88.79 298 | 96.67 266 |
|
v6 | | | 94.83 205 | 94.21 207 | 96.69 200 | 96.36 271 | 94.85 188 | 98.87 88 | 98.11 213 | 92.46 226 | 94.44 206 | 97.05 248 | 88.76 173 | 98.57 232 | 92.95 199 | 88.92 291 | 96.65 271 |
|
tttt0517 | | | 96.07 130 | 95.51 137 | 97.78 126 | 98.41 145 | 94.84 197 | 99.28 16 | 94.33 352 | 94.26 148 | 97.64 99 | 98.64 105 | 84.05 282 | 99.47 138 | 95.34 135 | 97.60 152 | 99.03 134 |
|
v16 | | | 92.08 287 | 90.94 287 | 95.49 271 | 96.38 270 | 94.84 197 | 98.81 108 | 97.51 256 | 89.94 295 | 85.25 333 | 93.28 329 | 88.86 162 | 96.91 323 | 88.70 295 | 79.78 340 | 94.72 330 |
|
PEN-MVS | | | 94.42 234 | 93.73 240 | 96.49 229 | 96.28 284 | 94.84 197 | 99.17 36 | 99.00 26 | 93.51 187 | 92.23 282 | 97.83 182 | 86.10 240 | 97.90 300 | 92.55 213 | 86.92 319 | 96.74 253 |
|
v17 | | | 92.08 287 | 90.94 287 | 95.48 272 | 96.34 274 | 94.83 200 | 98.81 108 | 97.52 253 | 89.95 294 | 85.32 330 | 93.24 331 | 88.91 160 | 96.91 323 | 88.76 294 | 79.63 342 | 94.71 331 |
|
v15 | | | 91.94 289 | 90.77 291 | 95.43 277 | 96.31 282 | 94.83 200 | 98.77 119 | 97.50 259 | 89.92 296 | 85.13 334 | 93.08 334 | 88.76 173 | 96.86 325 | 88.40 299 | 79.10 344 | 94.61 335 |
|
v8 | | | 94.47 232 | 93.77 236 | 96.57 221 | 96.36 271 | 94.83 200 | 99.05 60 | 98.19 191 | 91.92 249 | 93.16 256 | 96.97 256 | 88.82 167 | 98.48 245 | 91.69 235 | 87.79 308 | 96.39 296 |
|
TAPA-MVS | | 93.98 7 | 95.35 179 | 94.56 190 | 97.74 130 | 99.13 84 | 94.83 200 | 98.33 190 | 98.64 117 | 86.62 324 | 96.29 168 | 98.61 107 | 94.00 75 | 99.29 152 | 80.00 337 | 99.41 79 | 99.09 128 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
V14 | | | 91.93 290 | 90.76 292 | 95.42 280 | 96.33 278 | 94.81 204 | 98.77 119 | 97.51 256 | 89.86 298 | 85.09 335 | 93.13 332 | 88.80 171 | 96.83 327 | 88.32 300 | 79.06 346 | 94.60 336 |
|
v12 | | | 91.89 292 | 90.70 294 | 95.43 277 | 96.31 282 | 94.80 205 | 98.76 122 | 97.50 259 | 89.76 300 | 84.95 338 | 93.00 337 | 88.82 167 | 96.82 329 | 88.23 302 | 79.00 348 | 94.68 334 |
|
v10 | | | 94.29 240 | 93.55 249 | 96.51 228 | 96.39 267 | 94.80 205 | 98.99 68 | 98.19 191 | 91.35 267 | 93.02 262 | 96.99 254 | 88.09 193 | 98.41 265 | 90.50 262 | 88.41 301 | 96.33 300 |
|
V9 | | | 91.91 291 | 90.73 293 | 95.45 274 | 96.32 281 | 94.80 205 | 98.77 119 | 97.50 259 | 89.81 299 | 85.03 337 | 93.08 334 | 88.76 173 | 96.86 325 | 88.24 301 | 79.03 347 | 94.69 332 |
|
v7 | | | 94.69 217 | 94.04 218 | 96.62 213 | 96.41 266 | 94.79 208 | 98.78 118 | 98.13 205 | 91.89 250 | 94.30 216 | 97.16 228 | 88.13 192 | 98.45 252 | 91.96 228 | 89.65 278 | 96.61 276 |
|
v2v482 | | | 94.69 217 | 94.03 219 | 96.65 208 | 96.17 291 | 94.79 208 | 98.67 145 | 98.08 222 | 92.72 220 | 94.00 234 | 97.16 228 | 87.69 208 | 98.45 252 | 92.91 202 | 88.87 294 | 96.72 256 |
|
v1144 | | | 94.59 226 | 93.92 226 | 96.60 216 | 96.21 288 | 94.78 210 | 98.59 154 | 98.14 204 | 91.86 253 | 94.21 223 | 97.02 251 | 87.97 196 | 98.41 265 | 91.72 234 | 89.57 279 | 96.61 276 |
|
v13 | | | 91.88 293 | 90.69 295 | 95.43 277 | 96.33 278 | 94.78 210 | 98.75 123 | 97.50 259 | 89.68 303 | 84.93 339 | 92.98 338 | 88.84 165 | 96.83 327 | 88.14 303 | 79.09 345 | 94.69 332 |
|
v11 | | | 91.85 294 | 90.68 296 | 95.36 282 | 96.34 274 | 94.74 212 | 98.80 111 | 97.43 270 | 89.60 306 | 85.09 335 | 93.03 336 | 88.53 182 | 96.75 330 | 87.37 312 | 79.96 339 | 94.58 337 |
|
TransMVSNet (Re) | | | 92.67 279 | 91.51 283 | 96.15 249 | 96.58 257 | 94.65 213 | 98.90 79 | 96.73 313 | 90.86 279 | 89.46 309 | 97.86 176 | 85.62 248 | 98.09 289 | 86.45 317 | 81.12 337 | 95.71 315 |
|
BH-RMVSNet | | | 95.92 137 | 95.32 147 | 97.69 137 | 98.32 153 | 94.64 214 | 98.19 209 | 97.45 268 | 94.56 138 | 96.03 173 | 98.61 107 | 85.02 257 | 99.12 172 | 90.68 252 | 99.06 91 | 99.30 101 |
|
OPM-MVS | | | 95.69 148 | 95.33 146 | 96.76 195 | 96.16 294 | 94.63 215 | 98.43 180 | 98.39 159 | 96.64 51 | 95.02 185 | 98.78 91 | 85.15 256 | 99.05 183 | 95.21 144 | 94.20 220 | 96.60 278 |
|
jajsoiax | | | 95.45 168 | 95.03 158 | 96.73 196 | 95.42 322 | 94.63 215 | 99.14 45 | 98.52 135 | 95.74 75 | 93.22 254 | 98.36 131 | 83.87 287 | 98.65 225 | 96.95 73 | 94.04 226 | 96.91 234 |
|
plane_prior7 | | | | | | 97.42 210 | 94.63 215 | | | | | | | | | | |
|
plane_prior6 | | | | | | 97.35 215 | 94.61 218 | | | | | | 87.09 217 | | | | |
|
plane_prior3 | | | | | | | 94.61 218 | | | 97.02 40 | 95.34 179 | | | | | | |
|
HQP_MVS | | | 96.14 129 | 95.90 124 | 96.85 191 | 97.42 210 | 94.60 220 | 98.80 111 | 98.56 127 | 97.28 22 | 95.34 179 | 98.28 142 | 87.09 217 | 99.03 188 | 96.07 107 | 94.27 217 | 96.92 229 |
|
plane_prior | | | | | | | 94.60 220 | 98.44 178 | | 96.74 47 | | | | | | 94.22 219 | |
|
CHOSEN 1792x2688 | | | 97.12 95 | 96.80 88 | 98.08 109 | 99.30 57 | 94.56 222 | 98.05 225 | 99.71 1 | 93.57 186 | 97.09 114 | 98.91 81 | 88.17 189 | 99.89 29 | 96.87 82 | 99.56 64 | 99.81 3 |
|
NP-MVS | | | | | | 97.28 218 | 94.51 223 | | | | | 97.73 188 | | | | | |
|
v1192 | | | 94.32 238 | 93.58 248 | 96.53 226 | 96.10 295 | 94.45 224 | 98.50 171 | 98.17 199 | 91.54 258 | 94.19 224 | 97.06 244 | 86.95 221 | 98.43 257 | 90.14 265 | 89.57 279 | 96.70 260 |
|
mvs_tets | | | 95.41 173 | 95.00 159 | 96.65 208 | 95.58 315 | 94.42 225 | 99.00 67 | 98.55 129 | 95.73 76 | 93.21 255 | 98.38 129 | 83.45 291 | 98.63 226 | 97.09 67 | 94.00 228 | 96.91 234 |
|
LTVRE_ROB | | 92.95 15 | 94.60 224 | 93.90 228 | 96.68 203 | 97.41 213 | 94.42 225 | 98.52 166 | 98.59 120 | 91.69 255 | 91.21 293 | 98.35 132 | 84.87 260 | 99.04 187 | 91.06 246 | 93.44 241 | 96.60 278 |
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 |
DTE-MVSNet | | | 93.98 258 | 93.26 261 | 96.14 250 | 96.06 297 | 94.39 227 | 99.20 33 | 98.86 54 | 93.06 207 | 91.78 288 | 97.81 184 | 85.87 244 | 97.58 311 | 90.53 255 | 86.17 324 | 96.46 295 |
|
v7n | | | 94.19 245 | 93.43 256 | 96.47 231 | 95.90 303 | 94.38 228 | 99.26 18 | 98.34 165 | 91.99 247 | 92.76 268 | 97.13 236 | 88.31 186 | 98.52 241 | 89.48 282 | 87.70 309 | 96.52 288 |
|
v144192 | | | 94.39 236 | 93.70 241 | 96.48 230 | 96.06 297 | 94.35 229 | 98.58 156 | 98.16 201 | 91.45 260 | 94.33 212 | 97.02 251 | 87.50 213 | 98.45 252 | 91.08 245 | 89.11 286 | 96.63 274 |
|
V4 | | | 94.18 247 | 93.52 251 | 96.13 251 | 95.89 304 | 94.31 230 | 99.23 23 | 98.22 185 | 91.42 262 | 92.82 266 | 96.89 267 | 87.93 198 | 98.52 241 | 91.51 239 | 87.81 306 | 95.58 318 |
|
v52 | | | 94.18 247 | 93.52 251 | 96.13 251 | 95.95 302 | 94.29 231 | 99.23 23 | 98.21 186 | 91.42 262 | 92.84 265 | 96.89 267 | 87.85 202 | 98.53 240 | 91.51 239 | 87.81 306 | 95.57 319 |
|
Anonymous20231211 | | | 94.10 252 | 93.26 261 | 96.61 214 | 99.11 86 | 94.28 232 | 99.01 66 | 98.88 48 | 86.43 326 | 92.81 267 | 97.57 202 | 81.66 299 | 98.68 223 | 94.83 149 | 89.02 289 | 96.88 239 |
|
cascas | | | 94.63 223 | 93.86 230 | 96.93 188 | 96.91 241 | 94.27 233 | 96.00 330 | 98.51 137 | 85.55 334 | 94.54 196 | 96.23 296 | 84.20 280 | 98.87 208 | 95.80 120 | 96.98 161 | 97.66 202 |
|
Anonymous20240529 | | | 95.10 192 | 94.22 204 | 97.75 129 | 99.01 92 | 94.26 234 | 98.87 88 | 98.83 60 | 85.79 333 | 96.64 139 | 98.97 69 | 78.73 317 | 99.85 43 | 96.27 103 | 94.89 214 | 99.12 125 |
|
HQP5-MVS | | | | | | | 94.25 235 | | | | | | | | | | |
|
HQP-MVS | | | 95.72 144 | 95.40 138 | 96.69 200 | 97.20 224 | 94.25 235 | 98.05 225 | 98.46 147 | 96.43 55 | 94.45 200 | 97.73 188 | 86.75 223 | 98.96 195 | 95.30 137 | 94.18 221 | 96.86 243 |
|
TR-MVS | | | 94.94 202 | 94.20 208 | 97.17 173 | 97.75 188 | 94.14 237 | 97.59 267 | 97.02 295 | 92.28 243 | 95.75 177 | 97.64 197 | 83.88 286 | 98.96 195 | 89.77 273 | 96.15 195 | 98.40 172 |
|
v1921920 | | | 94.20 244 | 93.47 255 | 96.40 237 | 95.98 300 | 94.08 238 | 98.52 166 | 98.15 202 | 91.33 268 | 94.25 220 | 97.20 227 | 86.41 228 | 98.42 258 | 90.04 270 | 89.39 284 | 96.69 265 |
|
Baseline_NR-MVSNet | | | 94.35 237 | 93.81 232 | 95.96 255 | 96.20 289 | 94.05 239 | 98.61 152 | 96.67 317 | 91.44 261 | 93.85 239 | 97.60 199 | 88.57 179 | 98.14 285 | 94.39 161 | 86.93 318 | 95.68 316 |
|
VDD-MVS | | | 95.82 141 | 95.23 151 | 97.61 148 | 98.84 118 | 93.98 240 | 98.68 142 | 97.40 273 | 95.02 119 | 97.95 78 | 99.34 21 | 74.37 340 | 99.78 79 | 98.64 4 | 96.80 163 | 99.08 131 |
|
PMMVS | | | 96.60 112 | 96.33 111 | 97.41 162 | 97.90 181 | 93.93 241 | 97.35 283 | 98.41 155 | 92.84 218 | 97.76 87 | 97.45 209 | 91.10 123 | 99.20 165 | 96.26 104 | 97.91 138 | 99.11 126 |
|
v1240 | | | 94.06 256 | 93.29 260 | 96.34 242 | 96.03 299 | 93.90 242 | 98.44 178 | 98.17 199 | 91.18 276 | 94.13 228 | 97.01 253 | 86.05 241 | 98.42 258 | 89.13 287 | 89.50 282 | 96.70 260 |
|
GA-MVS | | | 94.81 209 | 94.03 219 | 97.14 174 | 97.15 229 | 93.86 243 | 96.76 314 | 97.58 246 | 94.00 157 | 94.76 193 | 97.04 249 | 80.91 303 | 98.48 245 | 91.79 231 | 96.25 191 | 99.09 128 |
|
ACMM | | 93.85 9 | 95.69 148 | 95.38 142 | 96.61 214 | 97.61 195 | 93.84 244 | 98.91 78 | 98.44 151 | 95.25 106 | 94.28 218 | 98.47 120 | 86.04 243 | 99.12 172 | 95.50 131 | 93.95 230 | 96.87 241 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
mvs_anonymous | | | 96.70 110 | 96.53 106 | 97.18 172 | 98.19 161 | 93.78 245 | 98.31 195 | 98.19 191 | 94.01 156 | 94.47 199 | 98.27 145 | 92.08 103 | 98.46 250 | 97.39 60 | 97.91 138 | 99.31 97 |
|
XVG-OURS-SEG-HR | | | 96.51 117 | 96.34 110 | 97.02 181 | 98.77 121 | 93.76 246 | 97.79 254 | 98.50 142 | 95.45 89 | 96.94 124 | 99.09 55 | 87.87 201 | 99.55 129 | 96.76 87 | 95.83 207 | 97.74 197 |
|
XVG-OURS | | | 96.55 116 | 96.41 108 | 96.99 182 | 98.75 122 | 93.76 246 | 97.50 272 | 98.52 135 | 95.67 79 | 96.83 131 | 99.30 27 | 88.95 159 | 99.53 130 | 95.88 116 | 96.26 190 | 97.69 201 |
|
Anonymous202405211 | | | 95.28 184 | 94.49 192 | 97.67 139 | 99.00 93 | 93.75 248 | 98.70 136 | 97.04 293 | 90.66 280 | 96.49 162 | 98.80 89 | 78.13 320 | 99.83 47 | 96.21 106 | 95.36 211 | 99.44 87 |
|
CLD-MVS | | | 95.62 151 | 95.34 144 | 96.46 234 | 97.52 203 | 93.75 248 | 97.27 289 | 98.46 147 | 95.53 85 | 94.42 208 | 98.00 165 | 86.21 231 | 98.97 192 | 96.25 105 | 94.37 215 | 96.66 269 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
IterMVS-LS | | | 95.46 167 | 95.21 152 | 96.22 247 | 98.12 168 | 93.72 250 | 98.32 194 | 98.13 205 | 93.71 175 | 94.26 219 | 97.31 220 | 92.24 96 | 98.10 287 | 94.63 153 | 90.12 273 | 96.84 244 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
EI-MVSNet | | | 95.96 134 | 95.83 126 | 96.36 239 | 97.93 179 | 93.70 251 | 98.12 218 | 98.27 177 | 93.70 177 | 95.07 183 | 99.02 62 | 92.23 97 | 98.54 234 | 94.68 152 | 93.46 238 | 96.84 244 |
|
LPG-MVS_test | | | 95.62 151 | 95.34 144 | 96.47 231 | 97.46 206 | 93.54 252 | 98.99 68 | 98.54 130 | 94.67 133 | 94.36 210 | 98.77 93 | 85.39 251 | 99.11 176 | 95.71 124 | 94.15 223 | 96.76 251 |
|
LGP-MVS_train | | | | | 96.47 231 | 97.46 206 | 93.54 252 | | 98.54 130 | 94.67 133 | 94.36 210 | 98.77 93 | 85.39 251 | 99.11 176 | 95.71 124 | 94.15 223 | 96.76 251 |
|
ACMP | | 93.49 10 | 95.34 180 | 94.98 161 | 96.43 235 | 97.67 191 | 93.48 254 | 98.73 130 | 98.44 151 | 94.94 126 | 92.53 274 | 98.53 114 | 84.50 271 | 99.14 170 | 95.48 132 | 94.00 228 | 96.66 269 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
CR-MVSNet | | | 94.76 211 | 94.15 211 | 96.59 217 | 97.00 234 | 93.43 255 | 94.96 340 | 97.56 247 | 92.46 226 | 96.93 125 | 96.24 294 | 88.15 190 | 97.88 304 | 87.38 311 | 96.65 168 | 98.46 169 |
|
RPMNet | | | 92.52 281 | 91.17 284 | 96.59 217 | 97.00 234 | 93.43 255 | 94.96 340 | 97.26 285 | 82.27 345 | 96.93 125 | 92.12 348 | 86.98 220 | 97.88 304 | 76.32 346 | 96.65 168 | 98.46 169 |
|
IB-MVS | | 91.98 17 | 93.27 271 | 91.97 279 | 97.19 171 | 97.47 205 | 93.41 257 | 97.09 296 | 95.99 326 | 93.32 200 | 92.47 277 | 95.73 309 | 78.06 321 | 99.53 130 | 94.59 157 | 82.98 332 | 98.62 163 |
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 |
CHOSEN 280x420 | | | 97.18 92 | 97.18 73 | 97.20 170 | 98.81 119 | 93.27 258 | 95.78 334 | 99.15 18 | 95.25 106 | 96.79 136 | 98.11 155 | 92.29 94 | 99.07 182 | 98.56 9 | 99.85 2 | 99.25 107 |
|
ACMH | | 92.88 16 | 94.55 228 | 93.95 225 | 96.34 242 | 97.63 193 | 93.26 259 | 98.81 108 | 98.49 146 | 93.43 190 | 89.74 306 | 98.53 114 | 81.91 297 | 99.08 181 | 93.69 178 | 93.30 244 | 96.70 260 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
COLMAP_ROB | | 93.27 12 | 95.33 181 | 94.87 172 | 96.71 197 | 99.29 60 | 93.24 260 | 98.58 156 | 98.11 213 | 89.92 296 | 93.57 245 | 99.10 51 | 86.37 229 | 99.79 74 | 90.78 250 | 98.10 133 | 97.09 219 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
AllTest | | | 95.24 186 | 94.65 186 | 96.99 182 | 99.25 69 | 93.21 261 | 98.59 154 | 98.18 194 | 91.36 265 | 93.52 247 | 98.77 93 | 84.67 263 | 99.72 91 | 89.70 277 | 97.87 140 | 98.02 187 |
|
TestCases | | | | | 96.99 182 | 99.25 69 | 93.21 261 | | 98.18 194 | 91.36 265 | 93.52 247 | 98.77 93 | 84.67 263 | 99.72 91 | 89.70 277 | 97.87 140 | 98.02 187 |
|
MIMVSNet | | | 93.26 272 | 92.21 277 | 96.41 236 | 97.73 190 | 93.13 263 | 95.65 335 | 97.03 294 | 91.27 273 | 94.04 232 | 96.06 302 | 75.33 333 | 97.19 318 | 86.56 316 | 96.23 192 | 98.92 146 |
|
Patchmtry | | | 93.22 273 | 92.35 275 | 95.84 260 | 96.77 247 | 93.09 264 | 94.66 346 | 97.56 247 | 87.37 322 | 92.90 264 | 96.24 294 | 88.15 190 | 97.90 300 | 87.37 312 | 90.10 274 | 96.53 287 |
|
v148 | | | 94.29 240 | 93.76 238 | 95.91 257 | 96.10 295 | 92.93 265 | 98.58 156 | 97.97 230 | 92.59 224 | 93.47 250 | 96.95 258 | 88.53 182 | 98.32 274 | 92.56 212 | 87.06 317 | 96.49 292 |
|
test0.0.03 1 | | | 94.08 254 | 93.51 253 | 95.80 262 | 95.53 317 | 92.89 266 | 97.38 278 | 95.97 327 | 95.11 114 | 92.51 276 | 96.66 280 | 87.71 205 | 96.94 321 | 87.03 314 | 93.67 233 | 97.57 203 |
|
PatchT | | | 93.06 277 | 91.97 279 | 96.35 240 | 96.69 253 | 92.67 267 | 94.48 347 | 97.08 290 | 86.62 324 | 97.08 115 | 92.23 347 | 87.94 197 | 97.90 300 | 78.89 341 | 96.69 166 | 98.49 168 |
|
v748 | | | 93.75 262 | 93.06 263 | 95.82 261 | 95.73 310 | 92.64 268 | 99.25 20 | 98.24 184 | 91.60 257 | 92.22 283 | 96.52 287 | 87.60 210 | 98.46 250 | 90.64 253 | 85.72 327 | 96.36 298 |
|
MVP-Stereo | | | 94.28 242 | 93.92 226 | 95.35 283 | 94.95 328 | 92.60 269 | 97.97 233 | 97.65 243 | 91.61 256 | 90.68 300 | 97.09 239 | 86.32 230 | 98.42 258 | 89.70 277 | 99.34 84 | 95.02 326 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
pmmvs5 | | | 93.65 265 | 92.97 265 | 95.68 266 | 95.49 318 | 92.37 270 | 98.20 205 | 97.28 283 | 89.66 304 | 92.58 272 | 97.26 222 | 82.14 295 | 98.09 289 | 93.18 192 | 90.95 269 | 96.58 280 |
|
BH-untuned | | | 95.95 135 | 95.72 128 | 96.65 208 | 98.55 141 | 92.26 271 | 98.23 202 | 97.79 237 | 93.73 173 | 94.62 194 | 98.01 163 | 88.97 158 | 99.00 191 | 93.04 196 | 98.51 114 | 98.68 157 |
|
pmmvs-eth3d | | | 90.36 309 | 89.05 312 | 94.32 311 | 91.10 346 | 92.12 272 | 97.63 266 | 96.95 302 | 88.86 314 | 84.91 340 | 93.13 332 | 78.32 319 | 96.74 331 | 88.70 295 | 81.81 336 | 94.09 342 |
|
FMVSNet5 | | | 91.81 295 | 90.92 289 | 94.49 306 | 97.21 223 | 92.09 273 | 98.00 231 | 97.55 251 | 89.31 311 | 90.86 298 | 95.61 314 | 74.48 338 | 95.32 343 | 85.57 323 | 89.70 277 | 96.07 307 |
|
PVSNet | | 91.96 18 | 96.35 122 | 96.15 117 | 96.96 185 | 99.17 80 | 92.05 274 | 96.08 326 | 98.68 102 | 93.69 178 | 97.75 88 | 97.80 185 | 88.86 162 | 99.69 101 | 94.26 167 | 99.01 92 | 99.15 121 |
|
ACMH+ | | 92.99 14 | 94.30 239 | 93.77 236 | 95.88 259 | 97.81 186 | 92.04 275 | 98.71 133 | 98.37 162 | 93.99 158 | 90.60 301 | 98.47 120 | 80.86 305 | 99.05 183 | 92.75 207 | 92.40 253 | 96.55 285 |
|
ADS-MVSNet | | | 95.00 195 | 94.45 197 | 96.63 211 | 98.00 174 | 91.91 276 | 96.04 327 | 97.74 240 | 90.15 288 | 96.47 163 | 96.64 282 | 87.89 199 | 98.96 195 | 90.08 267 | 97.06 158 | 99.02 135 |
|
mvs-test1 | | | 96.60 112 | 96.68 100 | 96.37 238 | 97.89 182 | 91.81 277 | 98.56 161 | 98.10 218 | 96.57 53 | 96.52 151 | 97.94 169 | 90.81 126 | 99.45 140 | 95.72 122 | 98.01 134 | 97.86 194 |
|
BH-w/o | | | 95.38 175 | 95.08 157 | 96.26 246 | 98.34 151 | 91.79 278 | 97.70 259 | 97.43 270 | 92.87 217 | 94.24 221 | 97.22 226 | 88.66 177 | 98.84 211 | 91.55 237 | 97.70 149 | 98.16 184 |
|
Patchmatch-test | | | 94.42 234 | 93.68 243 | 96.63 211 | 97.60 196 | 91.76 279 | 94.83 344 | 97.49 265 | 89.45 308 | 94.14 227 | 97.10 237 | 88.99 154 | 98.83 213 | 85.37 326 | 98.13 132 | 99.29 103 |
|
EPMVS | | | 94.99 196 | 94.48 193 | 96.52 227 | 97.22 222 | 91.75 280 | 97.23 290 | 91.66 361 | 94.11 150 | 97.28 109 | 96.81 275 | 85.70 247 | 98.84 211 | 93.04 196 | 97.28 156 | 98.97 140 |
|
Fast-Effi-MVS+-dtu | | | 95.87 138 | 95.85 125 | 95.91 257 | 97.74 189 | 91.74 281 | 98.69 138 | 98.15 202 | 95.56 84 | 94.92 186 | 97.68 194 | 88.98 157 | 98.79 217 | 93.19 191 | 97.78 145 | 97.20 218 |
|
XVG-ACMP-BASELINE | | | 94.54 229 | 94.14 212 | 95.75 265 | 96.55 258 | 91.65 282 | 98.11 220 | 98.44 151 | 94.96 123 | 94.22 222 | 97.90 173 | 79.18 316 | 99.11 176 | 94.05 172 | 93.85 231 | 96.48 293 |
|
TDRefinement | | | 91.06 303 | 89.68 306 | 95.21 285 | 85.35 356 | 91.49 283 | 98.51 170 | 97.07 291 | 91.47 259 | 88.83 314 | 97.84 179 | 77.31 327 | 99.09 180 | 92.79 206 | 77.98 349 | 95.04 325 |
|
MDA-MVSNet-bldmvs | | | 89.97 311 | 88.35 317 | 94.83 298 | 95.21 325 | 91.34 284 | 97.64 264 | 97.51 256 | 88.36 317 | 71.17 356 | 96.13 301 | 79.22 315 | 96.63 336 | 83.65 329 | 86.27 323 | 96.52 288 |
|
ITE_SJBPF | | | | | 95.44 275 | 97.42 210 | 91.32 285 | | 97.50 259 | 95.09 117 | 93.59 243 | 98.35 132 | 81.70 298 | 98.88 207 | 89.71 276 | 93.39 242 | 96.12 305 |
|
Patchmatch-test1 | | | 95.32 182 | 94.97 163 | 96.35 240 | 97.67 191 | 91.29 286 | 97.33 285 | 97.60 245 | 94.68 132 | 96.92 127 | 96.95 258 | 83.97 284 | 98.50 244 | 91.33 243 | 98.32 124 | 99.25 107 |
|
pmmvs6 | | | 91.77 296 | 90.63 297 | 95.17 287 | 94.69 333 | 91.24 287 | 98.67 145 | 97.92 232 | 86.14 328 | 89.62 307 | 97.56 204 | 75.79 332 | 98.34 272 | 90.75 251 | 84.56 331 | 95.94 310 |
|
test_0402 | | | 91.32 299 | 90.27 301 | 94.48 307 | 96.60 256 | 91.12 288 | 98.50 171 | 97.22 287 | 86.10 329 | 88.30 316 | 96.98 255 | 77.65 325 | 97.99 295 | 78.13 343 | 92.94 249 | 94.34 338 |
|
MIMVSNet1 | | | 89.67 313 | 88.28 318 | 93.82 315 | 92.81 342 | 91.08 289 | 98.01 229 | 97.45 268 | 87.95 318 | 87.90 318 | 95.87 307 | 67.63 351 | 94.56 346 | 78.73 342 | 88.18 303 | 95.83 312 |
|
ppachtmachnet_test | | | 93.22 273 | 92.63 271 | 94.97 292 | 95.45 320 | 90.84 290 | 96.88 308 | 97.88 234 | 90.60 281 | 92.08 286 | 97.26 222 | 88.08 194 | 97.86 306 | 85.12 327 | 90.33 272 | 96.22 302 |
|
USDC | | | 93.33 270 | 92.71 269 | 95.21 285 | 96.83 246 | 90.83 291 | 96.91 302 | 97.50 259 | 93.84 166 | 90.72 299 | 98.14 153 | 77.69 323 | 98.82 214 | 89.51 281 | 93.21 247 | 95.97 309 |
|
DWT-MVSNet_test | | | 94.82 208 | 94.36 200 | 96.20 248 | 97.35 215 | 90.79 292 | 98.34 189 | 96.57 320 | 92.91 215 | 95.33 181 | 96.44 290 | 82.00 296 | 99.12 172 | 94.52 159 | 95.78 208 | 98.70 155 |
|
MDA-MVSNet_test_wron | | | 90.71 306 | 89.38 309 | 94.68 302 | 94.83 330 | 90.78 293 | 97.19 292 | 97.46 266 | 87.60 320 | 72.41 355 | 95.72 311 | 86.51 226 | 96.71 334 | 85.92 321 | 86.80 321 | 96.56 284 |
|
PatchmatchNet | | | 95.71 146 | 95.52 136 | 96.29 245 | 97.58 198 | 90.72 294 | 96.84 311 | 97.52 253 | 94.06 153 | 97.08 115 | 96.96 257 | 89.24 149 | 98.90 205 | 92.03 225 | 98.37 121 | 99.26 106 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
PatchFormer-LS_test | | | 95.47 166 | 95.27 150 | 96.08 253 | 97.59 197 | 90.66 295 | 98.10 222 | 97.34 277 | 93.98 159 | 96.08 171 | 96.15 300 | 87.65 209 | 99.12 172 | 95.27 141 | 95.24 212 | 98.44 171 |
|
YYNet1 | | | 90.70 307 | 89.39 308 | 94.62 304 | 94.79 331 | 90.65 296 | 97.20 291 | 97.46 266 | 87.54 321 | 72.54 354 | 95.74 308 | 86.51 226 | 96.66 335 | 86.00 320 | 86.76 322 | 96.54 286 |
|
JIA-IIPM | | | 93.35 268 | 92.49 273 | 95.92 256 | 96.48 263 | 90.65 296 | 95.01 339 | 96.96 301 | 85.93 331 | 96.08 171 | 87.33 352 | 87.70 207 | 98.78 218 | 91.35 242 | 95.58 209 | 98.34 179 |
|
semantic-postprocess | | | | | 94.85 296 | 97.98 178 | 90.56 298 | | 98.11 213 | 93.75 170 | 92.58 272 | 97.48 206 | 83.91 285 | 97.41 315 | 92.48 216 | 91.30 266 | 96.58 280 |
|
EPNet_dtu | | | 95.21 188 | 94.95 164 | 95.99 254 | 96.17 291 | 90.45 299 | 98.16 214 | 97.27 284 | 96.77 45 | 93.14 259 | 98.33 137 | 90.34 135 | 98.42 258 | 85.57 323 | 98.81 103 | 99.09 128 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
IterMVS | | | 94.09 253 | 93.85 231 | 94.80 299 | 97.99 176 | 90.35 300 | 97.18 293 | 98.12 208 | 93.68 180 | 92.46 278 | 97.34 217 | 84.05 282 | 97.41 315 | 92.51 215 | 91.33 265 | 96.62 275 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
Effi-MVS+-dtu | | | 96.29 124 | 96.56 103 | 95.51 269 | 97.89 182 | 90.22 301 | 98.80 111 | 98.10 218 | 96.57 53 | 96.45 165 | 96.66 280 | 90.81 126 | 98.91 202 | 95.72 122 | 97.99 135 | 97.40 207 |
|
testgi | | | 93.06 277 | 92.45 274 | 94.88 295 | 96.43 265 | 89.90 302 | 98.75 123 | 97.54 252 | 95.60 82 | 91.63 291 | 97.91 172 | 74.46 339 | 97.02 320 | 86.10 319 | 93.67 233 | 97.72 199 |
|
UnsupCasMVSNet_eth | | | 90.99 304 | 89.92 305 | 94.19 313 | 94.08 336 | 89.83 303 | 97.13 295 | 98.67 109 | 93.69 178 | 85.83 327 | 96.19 299 | 75.15 334 | 96.74 331 | 89.14 286 | 79.41 343 | 96.00 308 |
|
TinyColmap | | | 92.31 283 | 91.53 282 | 94.65 303 | 96.92 239 | 89.75 304 | 96.92 300 | 96.68 316 | 90.45 284 | 89.62 307 | 97.85 178 | 76.06 331 | 98.81 215 | 86.74 315 | 92.51 252 | 95.41 320 |
|
test-LLR | | | 95.10 192 | 94.87 172 | 95.80 262 | 96.77 247 | 89.70 305 | 96.91 302 | 95.21 341 | 95.11 114 | 94.83 190 | 95.72 311 | 87.71 205 | 98.97 192 | 93.06 194 | 98.50 115 | 98.72 153 |
|
test-mter | | | 94.08 254 | 93.51 253 | 95.80 262 | 96.77 247 | 89.70 305 | 96.91 302 | 95.21 341 | 92.89 216 | 94.83 190 | 95.72 311 | 77.69 323 | 98.97 192 | 93.06 194 | 98.50 115 | 98.72 153 |
|
our_test_3 | | | 93.65 265 | 93.30 259 | 94.69 301 | 95.45 320 | 89.68 307 | 96.91 302 | 97.65 243 | 91.97 248 | 91.66 290 | 96.88 269 | 89.67 141 | 97.93 299 | 88.02 308 | 91.49 264 | 96.48 293 |
|
DeepPCF-MVS | | 96.37 2 | 97.93 51 | 98.48 14 | 96.30 244 | 99.00 93 | 89.54 308 | 97.43 275 | 98.87 51 | 98.16 2 | 99.26 10 | 99.38 13 | 96.12 19 | 99.64 107 | 98.30 21 | 99.77 19 | 99.72 32 |
|
MS-PatchMatch | | | 93.84 261 | 93.63 244 | 94.46 309 | 96.18 290 | 89.45 309 | 97.76 255 | 98.27 177 | 92.23 244 | 92.13 285 | 97.49 205 | 79.50 313 | 98.69 220 | 89.75 275 | 99.38 82 | 95.25 321 |
|
OpenMVS_ROB | | 86.42 20 | 89.00 315 | 87.43 321 | 93.69 316 | 93.08 340 | 89.42 310 | 97.91 239 | 96.89 309 | 78.58 351 | 85.86 326 | 94.69 321 | 69.48 347 | 98.29 280 | 77.13 344 | 93.29 245 | 93.36 347 |
|
SixPastTwentyTwo | | | 93.34 269 | 92.86 266 | 94.75 300 | 95.67 312 | 89.41 311 | 98.75 123 | 96.67 317 | 93.89 163 | 90.15 304 | 98.25 147 | 80.87 304 | 98.27 281 | 90.90 249 | 90.64 270 | 96.57 282 |
|
K. test v3 | | | 92.55 280 | 91.91 281 | 94.48 307 | 95.64 313 | 89.24 312 | 99.07 59 | 94.88 345 | 94.04 154 | 86.78 321 | 97.59 200 | 77.64 326 | 97.64 309 | 92.08 221 | 89.43 283 | 96.57 282 |
|
OurMVSNet-221017-0 | | | 94.21 243 | 94.00 221 | 94.85 296 | 95.60 314 | 89.22 313 | 98.89 83 | 97.43 270 | 95.29 104 | 92.18 284 | 98.52 117 | 82.86 293 | 98.59 230 | 93.46 184 | 91.76 261 | 96.74 253 |
|
TESTMET0.1,1 | | | 94.18 247 | 93.69 242 | 95.63 267 | 96.92 239 | 89.12 314 | 96.91 302 | 94.78 346 | 93.17 204 | 94.88 187 | 96.45 289 | 78.52 318 | 98.92 201 | 93.09 193 | 98.50 115 | 98.85 147 |
|
CostFormer | | | 94.95 200 | 94.73 183 | 95.60 268 | 97.28 218 | 89.06 315 | 97.53 270 | 96.89 309 | 89.66 304 | 96.82 133 | 96.72 278 | 86.05 241 | 98.95 199 | 95.53 130 | 96.13 196 | 98.79 151 |
|
tpm2 | | | 94.19 245 | 93.76 238 | 95.46 273 | 97.23 221 | 89.04 316 | 97.31 287 | 96.85 312 | 87.08 323 | 96.21 169 | 96.79 276 | 83.75 290 | 98.74 219 | 92.43 217 | 96.23 192 | 98.59 164 |
|
EG-PatchMatch MVS | | | 91.13 301 | 90.12 302 | 94.17 314 | 94.73 332 | 89.00 317 | 98.13 217 | 97.81 236 | 89.22 312 | 85.32 330 | 96.46 288 | 67.71 350 | 98.42 258 | 87.89 310 | 93.82 232 | 95.08 324 |
|
UnsupCasMVSNet_bld | | | 87.17 321 | 85.12 324 | 93.31 320 | 91.94 343 | 88.77 318 | 94.92 342 | 98.30 174 | 84.30 340 | 82.30 343 | 90.04 349 | 63.96 355 | 97.25 317 | 85.85 322 | 74.47 354 | 93.93 345 |
|
ADS-MVSNet2 | | | 94.58 227 | 94.40 199 | 95.11 289 | 98.00 174 | 88.74 319 | 96.04 327 | 97.30 281 | 90.15 288 | 96.47 163 | 96.64 282 | 87.89 199 | 97.56 312 | 90.08 267 | 97.06 158 | 99.02 135 |
|
LP | | | 91.12 302 | 89.99 304 | 94.53 305 | 96.35 273 | 88.70 320 | 93.86 351 | 97.35 276 | 84.88 337 | 90.98 296 | 94.77 320 | 84.40 272 | 97.43 314 | 75.41 348 | 91.89 260 | 97.47 204 |
|
LF4IMVS | | | 93.14 276 | 92.79 268 | 94.20 312 | 95.88 305 | 88.67 321 | 97.66 263 | 97.07 291 | 93.81 168 | 91.71 289 | 97.65 195 | 77.96 322 | 98.81 215 | 91.47 241 | 91.92 259 | 95.12 322 |
|
tpmvs | | | 94.60 224 | 94.36 200 | 95.33 284 | 97.46 206 | 88.60 322 | 96.88 308 | 97.68 241 | 91.29 271 | 93.80 241 | 96.42 291 | 88.58 178 | 99.24 155 | 91.06 246 | 96.04 204 | 98.17 183 |
|
tpmp4_e23 | | | 93.91 260 | 93.42 258 | 95.38 281 | 97.62 194 | 88.59 323 | 97.52 271 | 97.34 277 | 87.94 319 | 94.17 226 | 96.79 276 | 82.91 292 | 99.05 183 | 90.62 254 | 95.91 205 | 98.50 167 |
|
tpmrst | | | 95.63 150 | 95.69 133 | 95.44 275 | 97.54 201 | 88.54 324 | 96.97 298 | 97.56 247 | 93.50 188 | 97.52 107 | 96.93 264 | 89.49 142 | 99.16 168 | 95.25 142 | 96.42 176 | 98.64 162 |
|
lessismore_v0 | | | | | 94.45 310 | 94.93 329 | 88.44 325 | | 91.03 362 | | 86.77 322 | 97.64 197 | 76.23 330 | 98.42 258 | 90.31 264 | 85.64 328 | 96.51 290 |
|
MDTV_nov1_ep13 | | | | 95.40 138 | | 97.48 204 | 88.34 326 | 96.85 310 | 97.29 282 | 93.74 172 | 97.48 108 | 97.26 222 | 89.18 150 | 99.05 183 | 91.92 229 | 97.43 155 | |
|
new_pmnet | | | 90.06 310 | 89.00 313 | 93.22 322 | 94.18 334 | 88.32 327 | 96.42 325 | 96.89 309 | 86.19 327 | 85.67 329 | 93.62 327 | 77.18 328 | 97.10 319 | 81.61 334 | 89.29 285 | 94.23 339 |
|
test20.03 | | | 90.89 305 | 90.38 299 | 92.43 324 | 93.48 338 | 88.14 328 | 98.33 190 | 97.56 247 | 93.40 197 | 87.96 317 | 96.71 279 | 80.69 307 | 94.13 347 | 79.15 340 | 86.17 324 | 95.01 327 |
|
tpm cat1 | | | 93.36 267 | 92.80 267 | 95.07 290 | 97.58 198 | 87.97 329 | 96.76 314 | 97.86 235 | 82.17 346 | 93.53 246 | 96.04 303 | 86.13 232 | 99.13 171 | 89.24 285 | 95.87 206 | 98.10 185 |
|
tpm | | | 94.13 251 | 93.80 233 | 95.12 288 | 96.50 261 | 87.91 330 | 97.44 273 | 95.89 330 | 92.62 222 | 96.37 167 | 96.30 293 | 84.13 281 | 98.30 278 | 93.24 189 | 91.66 263 | 99.14 123 |
|
LCM-MVSNet-Re | | | 95.22 187 | 95.32 147 | 94.91 293 | 98.18 163 | 87.85 331 | 98.75 123 | 95.66 337 | 95.11 114 | 88.96 313 | 96.85 273 | 90.26 138 | 97.65 308 | 95.65 127 | 98.44 118 | 99.22 110 |
|
gm-plane-assit | | | | | | 95.88 305 | 87.47 332 | | | 89.74 302 | | 96.94 260 | | 99.19 166 | 93.32 188 | | |
|
Anonymous20231206 | | | 91.66 297 | 91.10 285 | 93.33 319 | 94.02 337 | 87.35 333 | 98.58 156 | 97.26 285 | 90.48 282 | 90.16 303 | 96.31 292 | 83.83 288 | 96.53 337 | 79.36 339 | 89.90 276 | 96.12 305 |
|
PVSNet_0 | | 88.72 19 | 91.28 300 | 90.03 303 | 95.00 291 | 97.99 176 | 87.29 334 | 94.84 343 | 98.50 142 | 92.06 246 | 89.86 305 | 95.19 315 | 79.81 312 | 99.39 144 | 92.27 218 | 69.79 355 | 98.33 180 |
|
pmmvs3 | | | 86.67 323 | 84.86 325 | 92.11 327 | 88.16 351 | 87.19 335 | 96.63 317 | 94.75 347 | 79.88 350 | 87.22 320 | 92.75 343 | 66.56 352 | 95.20 344 | 81.24 335 | 76.56 352 | 93.96 344 |
|
dp | | | 94.15 250 | 93.90 228 | 94.90 294 | 97.31 217 | 86.82 336 | 96.97 298 | 97.19 288 | 91.22 275 | 96.02 174 | 96.61 284 | 85.51 250 | 99.02 190 | 90.00 271 | 94.30 216 | 98.85 147 |
|
new-patchmatchnet | | | 88.50 319 | 87.45 320 | 91.67 328 | 90.31 348 | 85.89 337 | 97.16 294 | 97.33 280 | 89.47 307 | 83.63 342 | 92.77 342 | 76.38 329 | 95.06 345 | 82.70 331 | 77.29 350 | 94.06 343 |
|
Patchmatch-RL test | | | 91.49 298 | 90.85 290 | 93.41 318 | 91.37 345 | 84.40 338 | 92.81 352 | 95.93 329 | 91.87 252 | 87.25 319 | 94.87 319 | 88.99 154 | 96.53 337 | 92.54 214 | 82.00 334 | 99.30 101 |
|
MDTV_nov1_ep13_2view | | | | | | | 84.26 339 | 96.89 307 | | 90.97 278 | 97.90 82 | | 89.89 140 | | 93.91 174 | | 99.18 117 |
|
CVMVSNet | | | 95.43 169 | 96.04 120 | 93.57 317 | 97.93 179 | 83.62 340 | 98.12 218 | 98.59 120 | 95.68 78 | 96.56 145 | 99.02 62 | 87.51 211 | 97.51 313 | 93.56 183 | 97.44 154 | 99.60 62 |
|
EU-MVSNet | | | 93.66 263 | 94.14 212 | 92.25 326 | 95.96 301 | 83.38 341 | 98.52 166 | 98.12 208 | 94.69 131 | 92.61 271 | 98.13 154 | 87.36 215 | 96.39 339 | 91.82 230 | 90.00 275 | 96.98 225 |
|
PM-MVS | | | 87.77 320 | 86.55 322 | 91.40 329 | 91.03 347 | 83.36 342 | 96.92 300 | 95.18 343 | 91.28 272 | 86.48 324 | 93.42 328 | 53.27 358 | 96.74 331 | 89.43 283 | 81.97 335 | 94.11 341 |
|
testpf | | | 88.74 317 | 89.09 310 | 87.69 334 | 95.78 308 | 83.16 343 | 84.05 362 | 94.13 357 | 85.22 336 | 90.30 302 | 94.39 324 | 74.92 336 | 95.80 340 | 89.77 273 | 93.28 246 | 84.10 357 |
|
DSMNet-mixed | | | 92.52 281 | 92.58 272 | 92.33 325 | 94.15 335 | 82.65 344 | 98.30 197 | 94.26 353 | 89.08 313 | 92.65 270 | 95.73 309 | 85.01 258 | 95.76 341 | 86.24 318 | 97.76 146 | 98.59 164 |
|
MVS-HIRNet | | | 89.46 314 | 88.40 316 | 92.64 323 | 97.58 198 | 82.15 345 | 94.16 350 | 93.05 360 | 75.73 354 | 90.90 297 | 82.52 355 | 79.42 314 | 98.33 273 | 83.53 330 | 98.68 105 | 97.43 205 |
|
RPSCF | | | 94.87 204 | 95.40 138 | 93.26 321 | 98.89 112 | 82.06 346 | 98.33 190 | 98.06 225 | 90.30 287 | 96.56 145 | 99.26 30 | 87.09 217 | 99.49 133 | 93.82 176 | 96.32 183 | 98.24 182 |
|
Gipuma | | | 78.40 329 | 76.75 330 | 83.38 343 | 95.54 316 | 80.43 347 | 79.42 363 | 97.40 273 | 64.67 357 | 73.46 353 | 80.82 358 | 45.65 361 | 93.14 352 | 66.32 356 | 87.43 311 | 76.56 362 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
test2356 | | | 88.68 318 | 88.61 314 | 88.87 332 | 89.90 350 | 78.23 348 | 95.11 338 | 96.66 319 | 88.66 316 | 89.06 312 | 94.33 326 | 73.14 343 | 92.56 354 | 75.56 347 | 95.11 213 | 95.81 313 |
|
no-one | | | 74.41 332 | 70.76 334 | 85.35 340 | 79.88 361 | 76.83 349 | 94.68 345 | 94.22 354 | 80.33 349 | 63.81 359 | 79.73 359 | 35.45 366 | 93.36 351 | 71.78 350 | 36.99 363 | 85.86 356 |
|
CMPMVS | | 66.06 21 | 89.70 312 | 89.67 307 | 89.78 330 | 93.19 339 | 76.56 350 | 97.00 297 | 98.35 164 | 80.97 348 | 81.57 345 | 97.75 187 | 74.75 337 | 98.61 227 | 89.85 272 | 93.63 235 | 94.17 340 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
testus | | | 88.91 316 | 89.08 311 | 88.40 333 | 91.39 344 | 76.05 351 | 96.56 320 | 96.48 321 | 89.38 310 | 89.39 310 | 95.17 317 | 70.94 345 | 93.56 350 | 77.04 345 | 95.41 210 | 95.61 317 |
|
ambc | | | | | 89.49 331 | 86.66 355 | 75.78 352 | 92.66 353 | 96.72 314 | | 86.55 323 | 92.50 344 | 46.01 360 | 97.90 300 | 90.32 263 | 82.09 333 | 94.80 328 |
|
1111 | | | 84.94 325 | 84.30 326 | 86.86 336 | 87.59 352 | 75.10 353 | 96.63 317 | 96.43 322 | 82.53 343 | 80.75 347 | 92.91 340 | 68.94 348 | 93.79 348 | 68.24 354 | 84.66 330 | 91.70 349 |
|
.test1245 | | | 73.05 333 | 76.31 331 | 63.27 354 | 87.59 352 | 75.10 353 | 96.63 317 | 96.43 322 | 82.53 343 | 80.75 347 | 92.91 340 | 68.94 348 | 93.79 348 | 68.24 354 | 12.72 366 | 20.91 366 |
|
test1235678 | | | 86.26 324 | 85.81 323 | 87.62 335 | 86.97 354 | 75.00 355 | 96.55 322 | 96.32 324 | 86.08 330 | 81.32 346 | 92.98 338 | 73.10 344 | 92.05 355 | 71.64 351 | 87.32 313 | 95.81 313 |
|
PMMVS2 | | | 77.95 330 | 75.44 333 | 85.46 339 | 82.54 358 | 74.95 356 | 94.23 349 | 93.08 359 | 72.80 355 | 74.68 352 | 87.38 351 | 36.36 365 | 91.56 356 | 73.95 349 | 63.94 356 | 89.87 350 |
|
DeepMVS_CX | | | | | 86.78 337 | 97.09 232 | 72.30 357 | | 95.17 344 | 75.92 353 | 84.34 341 | 95.19 315 | 70.58 346 | 95.35 342 | 79.98 338 | 89.04 288 | 92.68 348 |
|
LCM-MVSNet | | | 78.70 328 | 76.24 332 | 86.08 338 | 77.26 366 | 71.99 358 | 94.34 348 | 96.72 314 | 61.62 359 | 76.53 351 | 89.33 350 | 33.91 367 | 92.78 353 | 81.85 333 | 74.60 353 | 93.46 346 |
|
ANet_high | | | 69.08 334 | 65.37 336 | 80.22 345 | 65.99 369 | 71.96 359 | 90.91 356 | 90.09 363 | 82.62 342 | 49.93 365 | 78.39 360 | 29.36 368 | 81.75 363 | 62.49 360 | 38.52 362 | 86.95 355 |
|
test12356 | | | 83.47 326 | 83.37 327 | 83.78 342 | 84.43 357 | 70.09 360 | 95.12 337 | 95.60 338 | 82.98 341 | 78.89 349 | 92.43 346 | 64.99 353 | 91.41 357 | 70.36 352 | 85.55 329 | 89.82 351 |
|
testmv | | | 78.74 327 | 77.35 328 | 82.89 344 | 78.16 365 | 69.30 361 | 95.87 331 | 94.65 348 | 81.11 347 | 70.98 357 | 87.11 353 | 46.31 359 | 90.42 358 | 65.28 357 | 76.72 351 | 88.95 352 |
|
wuykxyi23d | | | 63.73 340 | 58.86 342 | 78.35 347 | 67.62 368 | 67.90 362 | 86.56 359 | 87.81 367 | 58.26 360 | 42.49 367 | 70.28 364 | 11.55 372 | 85.05 361 | 63.66 358 | 41.50 359 | 82.11 359 |
|
MVE | | 62.14 22 | 63.28 341 | 59.38 341 | 74.99 349 | 74.33 367 | 65.47 363 | 85.55 360 | 80.50 371 | 52.02 363 | 51.10 364 | 75.00 363 | 10.91 374 | 80.50 364 | 51.60 362 | 53.40 357 | 78.99 360 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
N_pmnet | | | 87.12 322 | 87.77 319 | 85.17 341 | 95.46 319 | 61.92 364 | 97.37 280 | 70.66 372 | 85.83 332 | 88.73 315 | 96.04 303 | 85.33 255 | 97.76 307 | 80.02 336 | 90.48 271 | 95.84 311 |
|
FPMVS | | | 77.62 331 | 77.14 329 | 79.05 346 | 79.25 362 | 60.97 365 | 95.79 333 | 95.94 328 | 65.96 356 | 67.93 358 | 94.40 323 | 37.73 364 | 88.88 360 | 68.83 353 | 88.46 300 | 87.29 353 |
|
tmp_tt | | | 68.90 335 | 66.97 335 | 74.68 350 | 50.78 371 | 59.95 366 | 87.13 358 | 83.47 370 | 38.80 365 | 62.21 360 | 96.23 296 | 64.70 354 | 76.91 367 | 88.91 292 | 30.49 364 | 87.19 354 |
|
PNet_i23d | | | 67.70 336 | 65.07 337 | 75.60 348 | 78.61 363 | 59.61 367 | 89.14 357 | 88.24 366 | 61.83 358 | 52.37 363 | 80.89 357 | 18.91 369 | 84.91 362 | 62.70 359 | 52.93 358 | 82.28 358 |
|
E-PMN | | | 64.94 338 | 64.25 338 | 67.02 352 | 82.28 359 | 59.36 368 | 91.83 355 | 85.63 368 | 52.69 362 | 60.22 361 | 77.28 361 | 41.06 363 | 80.12 365 | 46.15 363 | 41.14 360 | 61.57 364 |
|
EMVS | | | 64.07 339 | 63.26 340 | 66.53 353 | 81.73 360 | 58.81 369 | 91.85 354 | 84.75 369 | 51.93 364 | 59.09 362 | 75.13 362 | 43.32 362 | 79.09 366 | 42.03 364 | 39.47 361 | 61.69 363 |
|
PMVS | | 61.03 23 | 65.95 337 | 63.57 339 | 73.09 351 | 57.90 370 | 51.22 370 | 85.05 361 | 93.93 358 | 54.45 361 | 44.32 366 | 83.57 354 | 13.22 370 | 89.15 359 | 58.68 361 | 81.00 338 | 78.91 361 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
wuyk23d | | | 30.17 344 | 30.18 346 | 30.16 356 | 78.61 363 | 43.29 371 | 66.79 364 | 14.21 373 | 17.31 366 | 14.82 370 | 11.93 370 | 11.55 372 | 41.43 368 | 37.08 365 | 19.30 365 | 5.76 368 |
|
test123 | | | 20.95 347 | 23.72 348 | 12.64 357 | 13.54 373 | 8.19 372 | 96.55 322 | 6.13 375 | 7.48 368 | 16.74 369 | 37.98 367 | 12.97 371 | 6.05 369 | 16.69 366 | 5.43 368 | 23.68 365 |
|
testmvs | | | 21.48 346 | 24.95 347 | 11.09 358 | 14.89 372 | 6.47 373 | 96.56 320 | 9.87 374 | 7.55 367 | 17.93 368 | 39.02 366 | 9.43 375 | 5.90 370 | 16.56 367 | 12.72 366 | 20.91 366 |
|
test_part1 | | | | | 0.00 359 | | 0.00 374 | 0.00 365 | 98.84 56 | | | | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
v1.0 | | | 41.12 342 | 54.83 343 | 0.00 359 | 99.63 22 | 0.00 374 | 0.00 365 | 98.84 56 | 96.40 58 | 99.27 8 | 99.31 23 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
cdsmvs_eth3d_5k | | | 23.98 345 | 31.98 345 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 98.59 120 | 0.00 369 | 0.00 371 | 98.61 107 | 90.60 132 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
pcd_1.5k_mvsjas | | | 7.88 349 | 10.50 350 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 94.51 63 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
pcd1.5k->3k | | | 39.42 343 | 41.78 344 | 32.35 355 | 96.17 291 | 0.00 374 | 0.00 365 | 98.54 130 | 0.00 369 | 0.00 371 | 0.00 371 | 87.78 204 | 0.00 371 | 0.00 368 | 93.56 237 | 97.06 220 |
|
sosnet-low-res | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
sosnet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
uncertanet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
Regformer | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
ab-mvs-re | | | 8.20 348 | 10.94 349 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 98.43 122 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
uanet | | | 0.00 350 | 0.00 351 | 0.00 359 | 0.00 374 | 0.00 374 | 0.00 365 | 0.00 376 | 0.00 369 | 0.00 371 | 0.00 371 | 0.00 376 | 0.00 371 | 0.00 368 | 0.00 369 | 0.00 369 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.20 111 |
|
sam_mvs1 | | | | | | | | | | | | | 89.45 143 | | | | 99.20 111 |
|
sam_mvs | | | | | | | | | | | | | 88.99 154 | | | | |
|
MTGPA | | | | | | | | | 98.74 84 | | | | | | | | |
|
test_post1 | | | | | | | | 96.68 316 | | | | 30.43 369 | 87.85 202 | 98.69 220 | 92.59 211 | | |
|
test_post | | | | | | | | | | | | 31.83 368 | 88.83 166 | 98.91 202 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 95.10 318 | 89.42 144 | 98.89 206 | | | |
|
MTMP | | | | | | | | 98.89 83 | 94.14 356 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 96.39 102 | 99.57 58 | 99.69 38 |
|
agg_prior2 | | | | | | | | | | | | | | | 95.87 117 | 99.57 58 | 99.68 44 |
|
test_prior2 | | | | | | | | 97.80 252 | | 96.12 65 | 97.89 83 | 98.69 98 | 95.96 27 | | 96.89 76 | 99.60 52 | |
|
旧先验2 | | | | | | | | 97.57 269 | | 91.30 270 | 98.67 41 | | | 99.80 62 | 95.70 126 | | |
|
新几何2 | | | | | | | | 97.64 264 | | | | | | | | | |
|
无先验 | | | | | | | | 97.58 268 | 98.72 91 | 91.38 264 | | | | 99.87 38 | 93.36 186 | | 99.60 62 |
|
原ACMM2 | | | | | | | | 97.67 262 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.89 29 | 91.65 236 | | |
|
segment_acmp | | | | | | | | | | | | | 96.85 4 | | | | |
|
testdata1 | | | | | | | | 97.32 286 | | 96.34 59 | | | | | | | |
|
plane_prior5 | | | | | | | | | 98.56 127 | | | | | 99.03 188 | 96.07 107 | 94.27 217 | 96.92 229 |
|
plane_prior4 | | | | | | | | | | | | 98.28 142 | | | | | |
|
plane_prior2 | | | | | | | | 98.80 111 | | 97.28 22 | | | | | | | |
|
plane_prior1 | | | | | | 97.37 214 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 376 | | | | | | | | |
|
nn | | | | | | | | | 0.00 376 | | | | | | | | |
|
door-mid | | | | | | | | | 94.37 351 | | | | | | | | |
|
test11 | | | | | | | | | 98.66 112 | | | | | | | | |
|
door | | | | | | | | | 94.64 349 | | | | | | | | |
|
HQP-NCC | | | | | | 97.20 224 | | 98.05 225 | | 96.43 55 | 94.45 200 | | | | | | |
|
ACMP_Plane | | | | | | 97.20 224 | | 98.05 225 | | 96.43 55 | 94.45 200 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 95.30 137 | | |
|
HQP4-MVS | | | | | | | | | | | 94.45 200 | | | 98.96 195 | | | 96.87 241 |
|
HQP3-MVS | | | | | | | | | 98.46 147 | | | | | | | 94.18 221 | |
|
HQP2-MVS | | | | | | | | | | | | | 86.75 223 | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 92.97 248 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 93.61 236 | |
|
Test By Simon | | | | | | | | | | | | | 94.64 60 | | | | |
|