test_part2 | | | | | | 99.63 21 | 99.18 1 | | | | 99.27 6 | | | | | | |
|
ESAPD | | | 98.70 5 | 98.39 15 | 99.62 1 | 99.63 21 | 99.18 1 | 98.55 152 | 98.84 54 | 96.40 57 | 99.27 6 | 99.31 21 | 97.38 2 | 99.93 9 | 96.37 95 | 99.78 14 | 99.76 20 |
|
HPM-MVS++ | | | 98.58 19 | 98.25 30 | 99.55 2 | 99.50 29 | 99.08 3 | 98.72 123 | 98.66 107 | 97.51 8 | 98.15 57 | 98.83 83 | 95.70 35 | 99.92 15 | 97.53 52 | 99.67 41 | 99.66 50 |
|
APDe-MVS | | | 99.02 1 | 98.84 1 | 99.55 2 | 99.57 25 | 98.96 4 | 99.39 5 | 98.93 36 | 97.38 17 | 99.41 3 | 99.54 1 | 96.66 7 | 99.84 44 | 98.86 2 | 99.85 2 | 99.87 1 |
|
ACMMP_Plus | | | 98.61 14 | 98.30 26 | 99.55 2 | 99.62 23 | 98.95 5 | 98.82 93 | 98.81 61 | 95.80 74 | 99.16 14 | 99.47 4 | 95.37 42 | 99.92 15 | 97.89 32 | 99.75 31 | 99.79 4 |
|
MP-MVS-pluss | | | 98.31 40 | 97.92 43 | 99.49 5 | 99.72 11 | 98.88 6 | 98.43 169 | 98.78 71 | 94.10 143 | 97.69 87 | 99.42 5 | 95.25 47 | 99.92 15 | 98.09 24 | 99.80 9 | 99.67 48 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
MCST-MVS | | | 98.65 10 | 98.37 18 | 99.48 6 | 99.60 24 | 98.87 7 | 98.41 171 | 98.68 97 | 97.04 38 | 98.52 46 | 98.80 86 | 96.78 6 | 99.83 45 | 97.93 28 | 99.61 50 | 99.74 27 |
|
CNVR-MVS | | | 98.78 3 | 98.56 6 | 99.45 9 | 99.32 47 | 98.87 7 | 98.47 165 | 98.81 61 | 97.72 4 | 98.76 35 | 99.16 44 | 97.05 4 | 99.78 76 | 98.06 25 | 99.66 44 | 99.69 37 |
|
APD-MVS | | | 98.35 36 | 98.00 41 | 99.42 10 | 99.51 28 | 98.72 9 | 98.80 102 | 98.82 58 | 94.52 133 | 99.23 10 | 99.25 30 | 95.54 39 | 99.80 59 | 96.52 89 | 99.77 19 | 99.74 27 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
MPTG | | | 98.55 23 | 98.25 30 | 99.46 7 | 99.76 1 | 98.64 10 | 98.55 152 | 98.74 79 | 97.27 25 | 98.02 66 | 99.39 7 | 94.81 56 | 99.96 1 | 97.91 29 | 99.79 10 | 99.77 14 |
|
MTAPA | | | 98.58 19 | 98.29 27 | 99.46 7 | 99.76 1 | 98.64 10 | 98.90 73 | 98.74 79 | 97.27 25 | 98.02 66 | 99.39 7 | 94.81 56 | 99.96 1 | 97.91 29 | 99.79 10 | 99.77 14 |
|
NCCC | | | 98.61 14 | 98.35 21 | 99.38 11 | 99.28 62 | 98.61 12 | 98.45 166 | 98.76 75 | 97.82 3 | 98.45 50 | 98.93 75 | 96.65 8 | 99.83 45 | 97.38 57 | 99.41 78 | 99.71 34 |
|
3Dnovator+ | | 94.38 6 | 97.43 73 | 96.78 86 | 99.38 11 | 97.83 171 | 98.52 13 | 99.37 7 | 98.71 91 | 97.09 37 | 92.99 250 | 99.13 46 | 89.36 138 | 99.89 29 | 96.97 65 | 99.57 57 | 99.71 34 |
|
TEST9 | | | | | | 99.31 49 | 98.50 14 | 97.92 225 | 98.73 84 | 92.63 210 | 97.74 83 | 98.68 96 | 96.20 14 | 99.80 59 | | | |
|
train_agg | | | 97.97 45 | 97.52 55 | 99.33 16 | 99.31 49 | 98.50 14 | 97.92 225 | 98.73 84 | 92.98 201 | 97.74 83 | 98.68 96 | 96.20 14 | 99.80 59 | 96.59 85 | 99.57 57 | 99.68 43 |
|
test_8 | | | | | | 99.29 57 | 98.44 16 | 97.89 233 | 98.72 86 | 92.98 201 | 97.70 86 | 98.66 99 | 96.20 14 | 99.80 59 | | | |
|
CDPH-MVS | | | 97.94 48 | 97.49 57 | 99.28 21 | 99.47 33 | 98.44 16 | 97.91 228 | 98.67 104 | 92.57 214 | 98.77 34 | 98.85 81 | 95.93 29 | 99.72 88 | 95.56 120 | 99.69 40 | 99.68 43 |
|
SteuartSystems-ACMMP | | | 98.90 2 | 98.75 2 | 99.36 13 | 99.22 73 | 98.43 18 | 99.10 51 | 98.87 49 | 97.38 17 | 99.35 5 | 99.40 6 | 97.78 1 | 99.87 37 | 97.77 39 | 99.85 2 | 99.78 7 |
Skip Steuart: Steuart Systems R&D Blog. |
agg_prior1 | | | 97.95 47 | 97.51 56 | 99.28 21 | 99.30 54 | 98.38 19 | 97.81 240 | 98.72 86 | 93.16 195 | 97.57 95 | 98.66 99 | 96.14 17 | 99.81 52 | 96.63 84 | 99.56 63 | 99.66 50 |
|
agg_prior | | | | | | 99.30 54 | 98.38 19 | | 98.72 86 | | 97.57 95 | | | 99.81 52 | | | |
|
canonicalmvs | | | 97.67 60 | 97.23 68 | 98.98 50 | 98.70 120 | 98.38 19 | 99.34 11 | 98.39 154 | 96.76 45 | 97.67 88 | 97.40 199 | 92.26 91 | 99.49 128 | 98.28 22 | 96.28 180 | 99.08 122 |
|
alignmvs | | | 97.56 66 | 97.07 75 | 99.01 47 | 98.66 124 | 98.37 22 | 98.83 91 | 98.06 215 | 96.74 46 | 98.00 70 | 97.65 184 | 90.80 123 | 99.48 132 | 98.37 19 | 96.56 162 | 99.19 108 |
|
SD-MVS | | | 98.64 11 | 98.68 3 | 98.53 74 | 99.33 44 | 98.36 23 | 98.90 73 | 98.85 53 | 97.28 21 | 99.72 1 | 99.39 7 | 96.63 9 | 97.60 296 | 98.17 23 | 99.85 2 | 99.64 55 |
|
XVS | | | 98.70 5 | 98.49 12 | 99.34 14 | 99.70 15 | 98.35 24 | 99.29 14 | 98.88 47 | 97.40 14 | 98.46 47 | 99.20 37 | 95.90 31 | 99.89 29 | 97.85 34 | 99.74 34 | 99.78 7 |
|
X-MVStestdata | | | 94.06 243 | 92.30 261 | 99.34 14 | 99.70 15 | 98.35 24 | 99.29 14 | 98.88 47 | 97.40 14 | 98.46 47 | 43.50 351 | 95.90 31 | 99.89 29 | 97.85 34 | 99.74 34 | 99.78 7 |
|
DP-MVS Recon | | | 97.86 52 | 97.46 59 | 99.06 46 | 99.53 27 | 98.35 24 | 98.33 178 | 98.89 44 | 92.62 211 | 98.05 62 | 98.94 74 | 95.34 44 | 99.65 100 | 96.04 102 | 99.42 77 | 99.19 108 |
|
HFP-MVS | | | 98.63 13 | 98.40 14 | 99.32 17 | 99.72 11 | 98.29 27 | 99.23 22 | 98.96 31 | 96.10 67 | 98.94 23 | 99.17 41 | 96.06 22 | 99.92 15 | 97.62 45 | 99.78 14 | 99.75 22 |
|
#test# | | | 98.54 25 | 98.27 28 | 99.32 17 | 99.72 11 | 98.29 27 | 98.98 66 | 98.96 31 | 95.65 80 | 98.94 23 | 99.17 41 | 96.06 22 | 99.92 15 | 97.21 60 | 99.78 14 | 99.75 22 |
|
TSAR-MVS + MP. | | | 98.78 3 | 98.62 4 | 99.24 26 | 99.69 17 | 98.28 29 | 99.14 44 | 98.66 107 | 96.84 43 | 99.56 2 | 99.31 21 | 96.34 12 | 99.70 93 | 98.32 20 | 99.73 36 | 99.73 29 |
|
HSP-MVS | | | 98.70 5 | 98.52 8 | 99.24 26 | 99.75 3 | 98.23 30 | 99.26 17 | 98.58 120 | 97.52 7 | 99.41 3 | 98.78 87 | 96.00 25 | 99.79 71 | 97.79 38 | 99.59 54 | 99.69 37 |
|
agg_prior3 | | | 97.87 51 | 97.42 61 | 99.23 28 | 99.29 57 | 98.23 30 | 97.92 225 | 98.72 86 | 92.38 227 | 97.59 94 | 98.64 101 | 96.09 20 | 99.79 71 | 96.59 85 | 99.57 57 | 99.68 43 |
|
test_prior3 | | | 98.22 43 | 97.90 44 | 99.19 29 | 99.31 49 | 98.22 32 | 97.80 241 | 98.84 54 | 96.12 65 | 97.89 77 | 98.69 94 | 95.96 27 | 99.70 93 | 96.89 71 | 99.60 51 | 99.65 52 |
|
test_prior | | | | | 99.19 29 | 99.31 49 | 98.22 32 | | 98.84 54 | | | | | 99.70 93 | | | 99.65 52 |
|
test12 | | | | | 99.18 33 | 99.16 78 | 98.19 34 | | 98.53 128 | | 98.07 61 | | 95.13 51 | 99.72 88 | | 99.56 63 | 99.63 57 |
|
MP-MVS | | | 98.33 39 | 98.01 40 | 99.28 21 | 99.75 3 | 98.18 35 | 99.22 28 | 98.79 69 | 96.13 64 | 97.92 75 | 99.23 31 | 94.54 61 | 99.94 3 | 96.74 81 | 99.78 14 | 99.73 29 |
|
region2R | | | 98.61 14 | 98.38 17 | 99.29 19 | 99.74 7 | 98.16 36 | 99.23 22 | 98.93 36 | 96.15 62 | 98.94 23 | 99.17 41 | 95.91 30 | 99.94 3 | 97.55 50 | 99.79 10 | 99.78 7 |
|
nrg030 | | | 96.28 119 | 95.72 121 | 97.96 109 | 96.90 228 | 98.15 37 | 99.39 5 | 98.31 162 | 95.47 86 | 94.42 195 | 98.35 125 | 92.09 98 | 98.69 209 | 97.50 53 | 89.05 274 | 97.04 211 |
|
ACMMPR | | | 98.59 17 | 98.36 19 | 99.29 19 | 99.74 7 | 98.15 37 | 99.23 22 | 98.95 33 | 96.10 67 | 98.93 27 | 99.19 40 | 95.70 35 | 99.94 3 | 97.62 45 | 99.79 10 | 99.78 7 |
|
PHI-MVS | | | 98.34 37 | 98.06 38 | 99.18 33 | 99.15 80 | 98.12 39 | 99.04 59 | 99.09 19 | 93.32 190 | 98.83 31 | 99.10 50 | 96.54 10 | 99.83 45 | 97.70 43 | 99.76 25 | 99.59 63 |
|
PGM-MVS | | | 98.49 28 | 98.23 33 | 99.27 24 | 99.72 11 | 98.08 40 | 98.99 63 | 99.49 5 | 95.43 88 | 99.03 17 | 99.32 20 | 95.56 37 | 99.94 3 | 96.80 79 | 99.77 19 | 99.78 7 |
|
mPP-MVS | | | 98.51 27 | 98.26 29 | 99.25 25 | 99.75 3 | 98.04 41 | 99.28 16 | 98.81 61 | 96.24 60 | 98.35 54 | 99.23 31 | 95.46 40 | 99.94 3 | 97.42 55 | 99.81 8 | 99.77 14 |
|
DeepC-MVS_fast | | 96.70 1 | 98.55 23 | 98.34 22 | 99.18 33 | 99.25 66 | 98.04 41 | 98.50 162 | 98.78 71 | 97.72 4 | 98.92 28 | 99.28 27 | 95.27 46 | 99.82 50 | 97.55 50 | 99.77 19 | 99.69 37 |
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 8 | 99.19 29 | 99.35 39 | 98.01 43 | 98.37 174 | 98.81 61 | 97.48 11 | 99.21 11 | 99.21 34 | 96.13 18 | 99.80 59 | 98.40 18 | 99.73 36 | 99.75 22 |
|
test_prior4 | | | | | | | 98.01 43 | 97.86 236 | | | | | | | | | |
|
新几何1 | | | | | 99.16 36 | 99.34 41 | 98.01 43 | | 98.69 94 | 90.06 278 | 98.13 58 | 98.95 73 | 94.60 60 | 99.89 29 | 91.97 215 | 99.47 71 | 99.59 63 |
|
1121 | | | 97.37 78 | 96.77 88 | 99.16 36 | 99.34 41 | 97.99 46 | 98.19 197 | 98.68 97 | 90.14 276 | 98.01 68 | 98.97 67 | 94.80 58 | 99.87 37 | 93.36 174 | 99.46 74 | 99.61 58 |
|
APD-MVS_3200maxsize | | | 98.53 26 | 98.33 25 | 99.15 38 | 99.50 29 | 97.92 47 | 99.15 43 | 98.81 61 | 96.24 60 | 99.20 12 | 99.37 12 | 95.30 45 | 99.80 59 | 97.73 41 | 99.67 41 | 99.72 32 |
|
HPM-MVS_fast | | | 98.38 33 | 98.13 36 | 99.12 41 | 99.75 3 | 97.86 48 | 99.44 4 | 98.82 58 | 94.46 137 | 98.94 23 | 99.20 37 | 95.16 50 | 99.74 87 | 97.58 47 | 99.85 2 | 99.77 14 |
|
CP-MVS | | | 98.57 21 | 98.36 19 | 99.19 29 | 99.66 19 | 97.86 48 | 99.34 11 | 98.87 49 | 95.96 70 | 98.60 43 | 99.13 46 | 96.05 24 | 99.94 3 | 97.77 39 | 99.86 1 | 99.77 14 |
|
MVS_0304 | | | 97.70 58 | 97.25 66 | 99.07 44 | 98.90 98 | 97.83 50 | 98.20 193 | 98.74 79 | 97.51 8 | 98.03 65 | 99.06 58 | 86.12 225 | 99.93 9 | 99.02 1 | 99.64 47 | 99.44 86 |
|
HPM-MVS | | | 98.36 35 | 98.10 37 | 99.13 39 | 99.74 7 | 97.82 51 | 99.53 1 | 98.80 68 | 94.63 130 | 98.61 42 | 98.97 67 | 95.13 51 | 99.77 81 | 97.65 44 | 99.83 7 | 99.79 4 |
|
Regformer-1 | | | 98.66 9 | 98.51 10 | 99.12 41 | 99.35 39 | 97.81 52 | 98.37 174 | 98.76 75 | 97.49 10 | 99.20 12 | 99.21 34 | 96.08 21 | 99.79 71 | 98.42 16 | 99.73 36 | 99.75 22 |
|
abl_6 | | | 98.30 41 | 98.03 39 | 99.13 39 | 99.56 26 | 97.76 53 | 99.13 47 | 98.82 58 | 96.14 63 | 99.26 8 | 99.37 12 | 93.33 78 | 99.93 9 | 96.96 67 | 99.67 41 | 99.69 37 |
|
DELS-MVS | | | 98.40 32 | 98.20 35 | 98.99 48 | 99.00 88 | 97.66 54 | 97.75 245 | 98.89 44 | 97.71 6 | 98.33 55 | 98.97 67 | 94.97 54 | 99.88 36 | 98.42 16 | 99.76 25 | 99.42 87 |
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 68 | 96.93 79 | 99.07 44 | 97.78 173 | 97.64 55 | 99.35 10 | 99.06 21 | 97.02 39 | 93.75 229 | 99.16 44 | 89.25 141 | 99.92 15 | 97.22 59 | 99.75 31 | 99.64 55 |
|
114514_t | | | 96.93 94 | 96.27 105 | 98.92 54 | 99.50 29 | 97.63 56 | 98.85 87 | 98.90 42 | 84.80 323 | 97.77 80 | 99.11 48 | 92.84 83 | 99.66 99 | 94.85 137 | 99.77 19 | 99.47 79 |
|
ACMMP | | | 98.23 42 | 97.95 42 | 99.09 43 | 99.74 7 | 97.62 57 | 99.03 60 | 99.41 6 | 95.98 69 | 97.60 93 | 99.36 16 | 94.45 66 | 99.93 9 | 97.14 61 | 98.85 99 | 99.70 36 |
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 | | | 96.29 117 | 95.40 130 | 98.96 52 | 97.85 170 | 97.60 58 | 99.23 22 | 98.93 36 | 89.76 287 | 93.11 247 | 99.02 60 | 89.11 145 | 99.93 9 | 91.99 214 | 99.62 49 | 99.34 90 |
|
VNet | | | 97.79 55 | 97.40 62 | 98.96 52 | 98.88 107 | 97.55 59 | 98.63 139 | 98.93 36 | 96.74 46 | 99.02 18 | 98.84 82 | 90.33 129 | 99.83 45 | 98.53 10 | 96.66 158 | 99.50 73 |
|
FIs | | | 96.51 109 | 96.12 110 | 97.67 128 | 97.13 216 | 97.54 60 | 99.36 8 | 99.22 14 | 95.89 71 | 94.03 220 | 98.35 125 | 91.98 101 | 98.44 243 | 96.40 93 | 92.76 239 | 97.01 212 |
|
旧先验1 | | | | | | 99.29 57 | 97.48 61 | | 98.70 93 | | | 99.09 54 | 95.56 37 | | | 99.47 71 | 99.61 58 |
|
UA-Net | | | 97.96 46 | 97.62 49 | 98.98 50 | 98.86 109 | 97.47 62 | 98.89 77 | 99.08 20 | 96.67 49 | 98.72 37 | 99.54 1 | 93.15 81 | 99.81 52 | 94.87 136 | 98.83 100 | 99.65 52 |
|
UniMVSNet (Re) | | | 95.78 133 | 95.19 144 | 97.58 137 | 96.99 222 | 97.47 62 | 98.79 107 | 99.18 16 | 95.60 81 | 93.92 223 | 97.04 235 | 91.68 105 | 98.48 233 | 95.80 111 | 87.66 296 | 96.79 236 |
|
CNLPA | | | 97.45 71 | 97.03 76 | 98.73 61 | 99.05 83 | 97.44 64 | 98.07 212 | 98.53 128 | 95.32 101 | 96.80 124 | 98.53 109 | 93.32 79 | 99.72 88 | 94.31 152 | 99.31 84 | 99.02 125 |
|
Regformer-4 | | | 98.64 11 | 98.53 7 | 98.99 48 | 99.43 37 | 97.37 65 | 98.40 172 | 98.79 69 | 97.46 12 | 99.09 15 | 99.31 21 | 95.86 33 | 99.80 59 | 98.64 4 | 99.76 25 | 99.79 4 |
|
MVS_111021_HR | | | 98.47 29 | 98.34 22 | 98.88 57 | 99.22 73 | 97.32 66 | 97.91 228 | 99.58 3 | 97.20 29 | 98.33 55 | 99.00 65 | 95.99 26 | 99.64 102 | 98.05 26 | 99.76 25 | 99.69 37 |
|
OpenMVS | | 93.04 13 | 95.83 131 | 95.00 150 | 98.32 88 | 97.18 213 | 97.32 66 | 99.21 31 | 98.97 29 | 89.96 280 | 91.14 278 | 99.05 59 | 86.64 217 | 99.92 15 | 93.38 173 | 99.47 71 | 97.73 187 |
|
CANet | | | 98.05 44 | 97.76 46 | 98.90 56 | 98.73 117 | 97.27 68 | 98.35 176 | 98.78 71 | 97.37 19 | 97.72 85 | 98.96 71 | 91.53 112 | 99.92 15 | 98.79 3 | 99.65 45 | 99.51 71 |
|
FC-MVSNet-test | | | 96.42 112 | 96.05 111 | 97.53 140 | 96.95 223 | 97.27 68 | 99.36 8 | 99.23 12 | 95.83 73 | 93.93 222 | 98.37 123 | 92.00 100 | 98.32 262 | 96.02 103 | 92.72 240 | 97.00 213 |
|
VPA-MVSNet | | | 95.75 134 | 95.11 146 | 97.69 126 | 97.24 206 | 97.27 68 | 98.94 70 | 99.23 12 | 95.13 109 | 95.51 165 | 97.32 206 | 85.73 238 | 98.91 191 | 97.33 58 | 89.55 268 | 96.89 226 |
|
TSAR-MVS + GP. | | | 98.38 33 | 98.24 32 | 98.81 59 | 99.22 73 | 97.25 71 | 98.11 208 | 98.29 167 | 97.19 30 | 98.99 22 | 99.02 60 | 96.22 13 | 99.67 98 | 98.52 14 | 98.56 112 | 99.51 71 |
|
NR-MVSNet | | | 94.98 186 | 94.16 198 | 97.44 148 | 96.53 245 | 97.22 72 | 98.74 118 | 98.95 33 | 94.96 118 | 89.25 295 | 97.69 180 | 89.32 139 | 98.18 272 | 94.59 144 | 87.40 298 | 96.92 218 |
|
LS3D | | | 97.16 86 | 96.66 93 | 98.68 64 | 98.53 134 | 97.19 73 | 98.93 71 | 98.90 42 | 92.83 208 | 95.99 162 | 99.37 12 | 92.12 97 | 99.87 37 | 93.67 168 | 99.57 57 | 98.97 130 |
|
test222 | | | | | | 99.23 72 | 97.17 74 | 97.40 265 | 98.66 107 | 88.68 302 | 98.05 62 | 98.96 71 | 94.14 71 | | | 99.53 67 | 99.61 58 |
|
CPTT-MVS | | | 97.72 57 | 97.32 64 | 98.92 54 | 99.64 20 | 97.10 75 | 99.12 49 | 98.81 61 | 92.34 228 | 98.09 60 | 99.08 56 | 93.01 82 | 99.92 15 | 96.06 101 | 99.77 19 | 99.75 22 |
|
Regformer-3 | | | 98.59 17 | 98.50 11 | 98.86 58 | 99.43 37 | 97.05 76 | 98.40 172 | 98.68 97 | 97.43 13 | 99.06 16 | 99.31 21 | 95.80 34 | 99.77 81 | 98.62 6 | 99.76 25 | 99.78 7 |
|
HY-MVS | | 93.96 8 | 96.82 99 | 96.23 108 | 98.57 70 | 98.46 135 | 97.00 77 | 98.14 203 | 98.21 178 | 93.95 152 | 96.72 126 | 97.99 155 | 91.58 107 | 99.76 83 | 94.51 147 | 96.54 163 | 98.95 134 |
|
UniMVSNet_NR-MVSNet | | | 95.71 137 | 95.15 145 | 97.40 152 | 96.84 231 | 96.97 78 | 98.74 118 | 99.24 10 | 95.16 108 | 93.88 224 | 97.72 179 | 91.68 105 | 98.31 264 | 95.81 109 | 87.25 301 | 96.92 218 |
|
DU-MVS | | | 95.42 161 | 94.76 171 | 97.40 152 | 96.53 245 | 96.97 78 | 98.66 137 | 98.99 28 | 95.43 88 | 93.88 224 | 97.69 180 | 88.57 172 | 98.31 264 | 95.81 109 | 87.25 301 | 96.92 218 |
|
DeepC-MVS | | 95.98 3 | 97.88 50 | 97.58 51 | 98.77 60 | 99.25 66 | 96.93 80 | 98.83 91 | 98.75 78 | 96.96 41 | 96.89 117 | 99.50 3 | 90.46 126 | 99.87 37 | 97.84 36 | 99.76 25 | 99.52 68 |
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 98 | 96.24 107 | 98.65 66 | 98.72 119 | 96.92 81 | 97.36 271 | 98.57 121 | 93.33 189 | 96.67 127 | 97.57 191 | 94.30 69 | 99.56 118 | 91.05 236 | 98.59 110 | 99.47 79 |
|
MVS_111021_LR | | | 98.34 37 | 98.23 33 | 98.67 65 | 99.27 63 | 96.90 82 | 97.95 223 | 99.58 3 | 97.14 33 | 98.44 51 | 99.01 64 | 95.03 53 | 99.62 107 | 97.91 29 | 99.75 31 | 99.50 73 |
|
MAR-MVS | | | 96.91 95 | 96.40 101 | 98.45 80 | 98.69 122 | 96.90 82 | 98.66 137 | 98.68 97 | 92.40 226 | 97.07 106 | 97.96 156 | 91.54 111 | 99.75 85 | 93.68 167 | 98.92 94 | 98.69 146 |
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 78 | 96.92 80 | 98.72 62 | 98.86 109 | 96.89 84 | 98.31 183 | 98.71 91 | 95.26 103 | 97.67 88 | 98.56 108 | 92.21 94 | 99.78 76 | 95.89 106 | 96.85 155 | 99.48 78 |
|
MSLP-MVS++ | | | 98.56 22 | 98.57 5 | 98.55 72 | 99.26 65 | 96.80 85 | 98.71 124 | 99.05 23 | 97.28 21 | 98.84 29 | 99.28 27 | 96.47 11 | 99.40 134 | 98.52 14 | 99.70 39 | 99.47 79 |
|
API-MVS | | | 97.41 75 | 97.25 66 | 97.91 110 | 98.70 120 | 96.80 85 | 98.82 93 | 98.69 94 | 94.53 132 | 98.11 59 | 98.28 133 | 94.50 65 | 99.57 116 | 94.12 157 | 99.49 69 | 97.37 199 |
|
PCF-MVS | | 93.45 11 | 94.68 208 | 93.43 244 | 98.42 84 | 98.62 128 | 96.77 87 | 95.48 322 | 98.20 181 | 84.63 324 | 93.34 239 | 98.32 131 | 88.55 174 | 99.81 52 | 84.80 314 | 98.96 93 | 98.68 147 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
ab-mvs | | | 96.42 112 | 95.71 124 | 98.55 72 | 98.63 127 | 96.75 88 | 97.88 234 | 98.74 79 | 93.84 157 | 96.54 137 | 98.18 142 | 85.34 246 | 99.75 85 | 95.93 105 | 96.35 172 | 99.15 114 |
|
Effi-MVS+ | | | 97.12 88 | 96.69 90 | 98.39 85 | 98.19 149 | 96.72 89 | 97.37 269 | 98.43 149 | 93.71 166 | 97.65 91 | 98.02 151 | 92.20 95 | 99.25 144 | 96.87 77 | 97.79 140 | 99.19 108 |
|
AdaColmap | | | 97.15 87 | 96.70 89 | 98.48 78 | 99.16 78 | 96.69 90 | 98.01 217 | 98.89 44 | 94.44 138 | 96.83 120 | 98.68 96 | 90.69 124 | 99.76 83 | 94.36 149 | 99.29 85 | 98.98 129 |
|
原ACMM1 | | | | | 98.65 66 | 99.32 47 | 96.62 91 | | 98.67 104 | 93.27 193 | 97.81 79 | 98.97 67 | 95.18 49 | 99.83 45 | 93.84 163 | 99.46 74 | 99.50 73 |
|
FMVSNet3 | | | 94.97 187 | 94.26 192 | 97.11 165 | 98.18 151 | 96.62 91 | 98.56 150 | 98.26 172 | 93.67 173 | 94.09 216 | 97.10 223 | 84.25 268 | 98.01 281 | 92.08 209 | 92.14 243 | 96.70 248 |
|
sss | | | 97.39 76 | 96.98 78 | 98.61 68 | 98.60 130 | 96.61 93 | 98.22 191 | 98.93 36 | 93.97 151 | 98.01 68 | 98.48 114 | 91.98 101 | 99.85 42 | 96.45 91 | 98.15 128 | 99.39 88 |
|
VPNet | | | 94.99 184 | 94.19 197 | 97.40 152 | 97.16 214 | 96.57 94 | 98.71 124 | 98.97 29 | 95.67 78 | 94.84 175 | 98.24 139 | 80.36 298 | 98.67 212 | 96.46 90 | 87.32 299 | 96.96 215 |
|
MVS | | | 94.67 209 | 93.54 238 | 98.08 102 | 96.88 229 | 96.56 95 | 98.19 197 | 98.50 137 | 78.05 337 | 92.69 255 | 98.02 151 | 91.07 119 | 99.63 105 | 90.09 254 | 98.36 121 | 98.04 175 |
|
XXY-MVS | | | 95.20 178 | 94.45 186 | 97.46 147 | 96.75 236 | 96.56 95 | 98.86 86 | 98.65 111 | 93.30 192 | 93.27 240 | 98.27 136 | 84.85 253 | 98.87 197 | 94.82 138 | 91.26 256 | 96.96 215 |
|
PatchMatch-RL | | | 96.59 106 | 96.03 113 | 98.27 89 | 99.31 49 | 96.51 97 | 97.91 228 | 99.06 21 | 93.72 165 | 96.92 115 | 98.06 149 | 88.50 177 | 99.65 100 | 91.77 221 | 99.00 92 | 98.66 149 |
|
EI-MVSNet-Vis-set | | | 98.47 29 | 98.39 15 | 98.69 63 | 99.46 34 | 96.49 98 | 98.30 185 | 98.69 94 | 97.21 28 | 98.84 29 | 99.36 16 | 95.41 41 | 99.78 76 | 98.62 6 | 99.65 45 | 99.80 3 |
|
WR-MVS | | | 95.15 179 | 94.46 184 | 97.22 157 | 96.67 241 | 96.45 99 | 98.21 192 | 98.81 61 | 94.15 141 | 93.16 243 | 97.69 180 | 87.51 203 | 98.30 266 | 95.29 129 | 88.62 285 | 96.90 225 |
|
FMVSNet2 | | | 94.47 220 | 93.61 234 | 97.04 168 | 98.21 146 | 96.43 100 | 98.79 107 | 98.27 168 | 92.46 215 | 93.50 236 | 97.09 225 | 81.16 288 | 98.00 282 | 91.09 232 | 91.93 247 | 96.70 248 |
|
PAPM_NR | | | 97.46 68 | 97.11 72 | 98.50 76 | 99.50 29 | 96.41 101 | 98.63 139 | 98.60 114 | 95.18 107 | 97.06 107 | 98.06 149 | 94.26 70 | 99.57 116 | 93.80 165 | 98.87 98 | 99.52 68 |
|
1112_ss | | | 96.63 103 | 96.00 114 | 98.50 76 | 98.56 131 | 96.37 102 | 98.18 201 | 98.10 208 | 92.92 203 | 94.84 175 | 98.43 117 | 92.14 96 | 99.58 115 | 94.35 150 | 96.51 164 | 99.56 67 |
|
TranMVSNet+NR-MVSNet | | | 95.14 180 | 94.48 182 | 97.11 165 | 96.45 250 | 96.36 103 | 99.03 60 | 99.03 24 | 95.04 114 | 93.58 231 | 97.93 159 | 88.27 180 | 98.03 280 | 94.13 156 | 86.90 306 | 96.95 217 |
|
IS-MVSNet | | | 97.22 83 | 96.88 81 | 98.25 91 | 98.85 111 | 96.36 103 | 99.19 34 | 97.97 220 | 95.39 90 | 97.23 100 | 98.99 66 | 91.11 117 | 98.93 189 | 94.60 143 | 98.59 110 | 99.47 79 |
|
EI-MVSNet-UG-set | | | 98.41 31 | 98.34 22 | 98.61 68 | 99.45 35 | 96.32 105 | 98.28 187 | 98.68 97 | 97.17 31 | 98.74 36 | 99.37 12 | 95.25 47 | 99.79 71 | 98.57 8 | 99.54 66 | 99.73 29 |
|
LFMVS | | | 95.86 130 | 94.98 152 | 98.47 79 | 98.87 108 | 96.32 105 | 98.84 90 | 96.02 313 | 93.40 187 | 98.62 41 | 99.20 37 | 74.99 321 | 99.63 105 | 97.72 42 | 97.20 150 | 99.46 83 |
|
PLC | | 95.07 4 | 97.20 84 | 96.78 86 | 98.44 81 | 99.29 57 | 96.31 107 | 98.14 203 | 98.76 75 | 92.41 225 | 96.39 153 | 98.31 132 | 94.92 55 | 99.78 76 | 94.06 158 | 98.77 103 | 99.23 104 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
Vis-MVSNet | | | 97.42 74 | 97.11 72 | 98.34 87 | 98.66 124 | 96.23 108 | 99.22 28 | 99.00 26 | 96.63 51 | 98.04 64 | 99.21 34 | 88.05 187 | 99.35 139 | 96.01 104 | 99.21 86 | 99.45 85 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
DP-MVS | | | 96.59 106 | 95.93 115 | 98.57 70 | 99.34 41 | 96.19 109 | 98.70 127 | 98.39 154 | 89.45 295 | 94.52 184 | 99.35 18 | 91.85 103 | 99.85 42 | 92.89 193 | 98.88 96 | 99.68 43 |
|
diffmvs | | | 96.32 116 | 95.74 119 | 98.07 104 | 98.26 143 | 96.14 110 | 98.53 156 | 98.23 176 | 90.10 277 | 96.88 118 | 97.73 176 | 90.16 132 | 99.15 157 | 93.90 162 | 97.85 138 | 98.91 136 |
|
EPNet | | | 97.28 81 | 96.87 82 | 98.51 75 | 94.98 311 | 96.14 110 | 98.90 73 | 97.02 283 | 98.28 1 | 95.99 162 | 99.11 48 | 91.36 113 | 99.89 29 | 96.98 64 | 99.19 87 | 99.50 73 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
CANet_DTU | | | 96.96 93 | 96.55 96 | 98.21 92 | 98.17 153 | 96.07 112 | 97.98 220 | 98.21 178 | 97.24 27 | 97.13 102 | 98.93 75 | 86.88 214 | 99.91 24 | 95.00 135 | 99.37 82 | 98.66 149 |
|
xiu_mvs_v1_base_debu | | | 97.60 62 | 97.56 52 | 97.72 120 | 98.35 136 | 95.98 113 | 97.86 236 | 98.51 132 | 97.13 34 | 99.01 19 | 98.40 119 | 91.56 108 | 99.80 59 | 98.53 10 | 98.68 104 | 97.37 199 |
|
xiu_mvs_v1_base | | | 97.60 62 | 97.56 52 | 97.72 120 | 98.35 136 | 95.98 113 | 97.86 236 | 98.51 132 | 97.13 34 | 99.01 19 | 98.40 119 | 91.56 108 | 99.80 59 | 98.53 10 | 98.68 104 | 97.37 199 |
|
xiu_mvs_v1_base_debi | | | 97.60 62 | 97.56 52 | 97.72 120 | 98.35 136 | 95.98 113 | 97.86 236 | 98.51 132 | 97.13 34 | 99.01 19 | 98.40 119 | 91.56 108 | 99.80 59 | 98.53 10 | 98.68 104 | 97.37 199 |
|
CDS-MVSNet | | | 96.99 92 | 96.69 90 | 97.90 111 | 98.05 159 | 95.98 113 | 98.20 193 | 98.33 161 | 93.67 173 | 96.95 110 | 98.49 113 | 93.54 76 | 98.42 246 | 95.24 132 | 97.74 143 | 99.31 93 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
Fast-Effi-MVS+ | | | 96.28 119 | 95.70 125 | 98.03 106 | 98.29 142 | 95.97 117 | 98.58 145 | 98.25 173 | 91.74 242 | 95.29 169 | 97.23 211 | 91.03 120 | 99.15 157 | 92.90 191 | 97.96 133 | 98.97 130 |
|
MVS_Test | | | 97.28 81 | 97.00 77 | 98.13 98 | 98.33 140 | 95.97 117 | 98.74 118 | 98.07 213 | 94.27 140 | 98.44 51 | 98.07 148 | 92.48 87 | 99.26 143 | 96.43 92 | 98.19 127 | 99.16 113 |
|
MG-MVS | | | 97.81 54 | 97.60 50 | 98.44 81 | 99.12 82 | 95.97 117 | 97.75 245 | 98.78 71 | 96.89 42 | 98.46 47 | 99.22 33 | 93.90 75 | 99.68 97 | 94.81 139 | 99.52 68 | 99.67 48 |
|
test_normal | | | 94.72 204 | 93.59 235 | 98.11 100 | 95.30 308 | 95.95 120 | 97.91 228 | 97.39 263 | 94.64 129 | 85.70 312 | 95.88 291 | 80.52 296 | 99.36 138 | 96.69 82 | 98.30 124 | 99.01 128 |
|
tfpnnormal | | | 93.66 250 | 92.70 256 | 96.55 212 | 96.94 224 | 95.94 121 | 98.97 67 | 99.19 15 | 91.04 265 | 91.38 276 | 97.34 204 | 84.94 251 | 98.61 215 | 85.45 312 | 89.02 276 | 95.11 309 |
|
pmmvs4 | | | 94.69 205 | 93.99 211 | 96.81 181 | 95.74 295 | 95.94 121 | 97.40 265 | 97.67 231 | 90.42 271 | 93.37 238 | 97.59 189 | 89.08 146 | 98.20 271 | 92.97 186 | 91.67 251 | 96.30 288 |
|
Test_1112_low_res | | | 96.34 115 | 95.66 128 | 98.36 86 | 98.56 131 | 95.94 121 | 97.71 247 | 98.07 213 | 92.10 234 | 94.79 179 | 97.29 208 | 91.75 104 | 99.56 118 | 94.17 155 | 96.50 165 | 99.58 65 |
|
conf0.01 | | | 95.56 148 | 94.84 164 | 97.72 120 | 98.90 98 | 95.93 124 | 99.17 35 | 95.70 319 | 93.42 181 | 96.50 144 | 97.16 214 | 86.12 225 | 99.22 148 | 90.51 244 | 96.06 189 | 98.02 176 |
|
conf0.002 | | | 95.56 148 | 94.84 164 | 97.72 120 | 98.90 98 | 95.93 124 | 99.17 35 | 95.70 319 | 93.42 181 | 96.50 144 | 97.16 214 | 86.12 225 | 99.22 148 | 90.51 244 | 96.06 189 | 98.02 176 |
|
thresconf0.02 | | | 95.50 151 | 94.84 164 | 97.51 141 | 98.90 98 | 95.93 124 | 99.17 35 | 95.70 319 | 93.42 181 | 96.50 144 | 97.16 214 | 86.12 225 | 99.22 148 | 90.51 244 | 96.06 189 | 97.37 199 |
|
tfpn_n400 | | | 95.50 151 | 94.84 164 | 97.51 141 | 98.90 98 | 95.93 124 | 99.17 35 | 95.70 319 | 93.42 181 | 96.50 144 | 97.16 214 | 86.12 225 | 99.22 148 | 90.51 244 | 96.06 189 | 97.37 199 |
|
tfpnconf | | | 95.50 151 | 94.84 164 | 97.51 141 | 98.90 98 | 95.93 124 | 99.17 35 | 95.70 319 | 93.42 181 | 96.50 144 | 97.16 214 | 86.12 225 | 99.22 148 | 90.51 244 | 96.06 189 | 97.37 199 |
|
tfpnview11 | | | 95.50 151 | 94.84 164 | 97.51 141 | 98.90 98 | 95.93 124 | 99.17 35 | 95.70 319 | 93.42 181 | 96.50 144 | 97.16 214 | 86.12 225 | 99.22 148 | 90.51 244 | 96.06 189 | 97.37 199 |
|
MVSTER | | | 96.06 123 | 95.72 121 | 97.08 167 | 98.23 145 | 95.93 124 | 98.73 121 | 98.27 168 | 94.86 122 | 95.07 170 | 98.09 147 | 88.21 181 | 98.54 222 | 96.59 85 | 93.46 227 | 96.79 236 |
|
DI_MVS_plusplus_test | | | 94.74 203 | 93.62 233 | 98.09 101 | 95.34 307 | 95.92 131 | 98.09 211 | 97.34 265 | 94.66 128 | 85.89 309 | 95.91 290 | 80.49 297 | 99.38 137 | 96.66 83 | 98.22 125 | 98.97 130 |
|
OMC-MVS | | | 97.55 67 | 97.34 63 | 98.20 93 | 99.33 44 | 95.92 131 | 98.28 187 | 98.59 115 | 95.52 85 | 97.97 71 | 99.10 50 | 93.28 80 | 99.49 128 | 95.09 134 | 98.88 96 | 99.19 108 |
|
PVSNet_Blended_VisFu | | | 97.70 58 | 97.46 59 | 98.44 81 | 99.27 63 | 95.91 133 | 98.63 139 | 99.16 17 | 94.48 136 | 97.67 88 | 98.88 79 | 92.80 84 | 99.91 24 | 97.11 62 | 99.12 89 | 99.50 73 |
|
anonymousdsp | | | 95.42 161 | 94.91 160 | 96.94 175 | 95.10 310 | 95.90 134 | 99.14 44 | 98.41 150 | 93.75 161 | 93.16 243 | 97.46 195 | 87.50 205 | 98.41 253 | 95.63 119 | 94.03 216 | 96.50 279 |
|
UGNet | | | 96.78 100 | 96.30 104 | 98.19 95 | 98.24 144 | 95.89 135 | 98.88 79 | 98.93 36 | 97.39 16 | 96.81 123 | 97.84 167 | 82.60 283 | 99.90 27 | 96.53 88 | 99.49 69 | 98.79 141 |
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 | | | 95.53 150 | 94.90 161 | 97.39 155 | 98.96 95 | 95.88 136 | 99.05 57 | 95.27 328 | 93.80 160 | 96.95 110 | 96.93 250 | 85.53 241 | 99.40 134 | 91.54 226 | 96.10 188 | 96.89 226 |
|
Test4 | | | 92.21 269 | 90.34 285 | 97.82 116 | 92.83 325 | 95.87 137 | 97.94 224 | 98.05 218 | 94.50 134 | 82.12 328 | 94.48 307 | 59.54 343 | 98.54 222 | 95.39 125 | 98.22 125 | 99.06 124 |
|
WR-MVS_H | | | 95.05 182 | 94.46 184 | 96.81 181 | 96.86 230 | 95.82 138 | 99.24 20 | 99.24 10 | 93.87 156 | 92.53 260 | 96.84 259 | 90.37 127 | 98.24 270 | 93.24 177 | 87.93 291 | 96.38 284 |
|
MVSFormer | | | 97.57 65 | 97.49 57 | 97.84 113 | 98.07 156 | 95.76 139 | 99.47 2 | 98.40 152 | 94.98 116 | 98.79 32 | 98.83 83 | 92.34 88 | 98.41 253 | 96.91 69 | 99.59 54 | 99.34 90 |
|
lupinMVS | | | 97.44 72 | 97.22 69 | 98.12 99 | 98.07 156 | 95.76 139 | 97.68 250 | 97.76 227 | 94.50 134 | 98.79 32 | 98.61 102 | 92.34 88 | 99.30 140 | 97.58 47 | 99.59 54 | 99.31 93 |
|
tfpn1000 | | | 95.72 135 | 95.11 146 | 97.58 137 | 99.00 88 | 95.73 141 | 99.24 20 | 95.49 327 | 94.08 144 | 96.87 119 | 97.45 197 | 85.81 237 | 99.30 140 | 91.78 220 | 96.22 185 | 97.71 189 |
|
PAPM | | | 94.95 188 | 94.00 209 | 97.78 118 | 97.04 219 | 95.65 142 | 96.03 315 | 98.25 173 | 91.23 262 | 94.19 211 | 97.80 173 | 91.27 115 | 98.86 199 | 82.61 318 | 97.61 145 | 98.84 139 |
|
jason | | | 97.32 80 | 97.08 74 | 98.06 105 | 97.45 195 | 95.59 143 | 97.87 235 | 97.91 223 | 94.79 123 | 98.55 45 | 98.83 83 | 91.12 116 | 99.23 146 | 97.58 47 | 99.60 51 | 99.34 90 |
jason: jason. |
PS-MVSNAJ | | | 97.73 56 | 97.77 45 | 97.62 131 | 98.68 123 | 95.58 144 | 97.34 273 | 98.51 132 | 97.29 20 | 98.66 39 | 97.88 163 | 94.51 62 | 99.90 27 | 97.87 33 | 99.17 88 | 97.39 197 |
|
testing_2 | | | 90.61 293 | 88.50 300 | 96.95 174 | 90.08 333 | 95.57 145 | 97.69 249 | 98.06 215 | 93.02 199 | 76.55 335 | 92.48 331 | 61.18 342 | 98.44 243 | 95.45 124 | 91.98 246 | 96.84 232 |
|
CP-MVSNet | | | 94.94 190 | 94.30 191 | 96.83 180 | 96.72 238 | 95.56 146 | 99.11 50 | 98.95 33 | 93.89 154 | 92.42 265 | 97.90 161 | 87.19 208 | 98.12 274 | 94.32 151 | 88.21 288 | 96.82 235 |
|
HyFIR lowres test | | | 96.90 96 | 96.49 99 | 98.14 96 | 99.33 44 | 95.56 146 | 97.38 267 | 99.65 2 | 92.34 228 | 97.61 92 | 98.20 141 | 89.29 140 | 99.10 168 | 96.97 65 | 97.60 146 | 99.77 14 |
|
1314 | | | 96.25 121 | 95.73 120 | 97.79 117 | 97.13 216 | 95.55 148 | 98.19 197 | 98.59 115 | 93.47 179 | 92.03 272 | 97.82 171 | 91.33 114 | 99.49 128 | 94.62 142 | 98.44 117 | 98.32 170 |
|
test_djsdf | | | 96.00 124 | 95.69 126 | 96.93 176 | 95.72 297 | 95.49 149 | 99.47 2 | 98.40 152 | 94.98 116 | 94.58 182 | 97.86 164 | 89.16 144 | 98.41 253 | 96.91 69 | 94.12 214 | 96.88 228 |
|
xiu_mvs_v2_base | | | 97.66 61 | 97.70 48 | 97.56 139 | 98.61 129 | 95.46 150 | 97.44 262 | 98.46 142 | 97.15 32 | 98.65 40 | 98.15 143 | 94.33 68 | 99.80 59 | 97.84 36 | 98.66 108 | 97.41 195 |
|
Vis-MVSNet (Re-imp) | | | 96.87 97 | 96.55 96 | 97.83 114 | 98.73 117 | 95.46 150 | 99.20 32 | 98.30 165 | 94.96 118 | 96.60 132 | 98.87 80 | 90.05 133 | 98.59 218 | 93.67 168 | 98.60 109 | 99.46 83 |
|
EPP-MVSNet | | | 97.46 68 | 97.28 65 | 97.99 107 | 98.64 126 | 95.38 152 | 99.33 13 | 98.31 162 | 93.61 175 | 97.19 101 | 99.07 57 | 94.05 72 | 99.23 146 | 96.89 71 | 98.43 119 | 99.37 89 |
|
testdata | | | | | 98.26 90 | 99.20 76 | 95.36 153 | | 98.68 97 | 91.89 238 | 98.60 43 | 99.10 50 | 94.44 67 | 99.82 50 | 94.27 153 | 99.44 76 | 99.58 65 |
|
MSDG | | | 95.93 127 | 95.30 140 | 97.83 114 | 98.90 98 | 95.36 153 | 96.83 299 | 98.37 157 | 91.32 257 | 94.43 194 | 98.73 93 | 90.27 130 | 99.60 108 | 90.05 257 | 98.82 101 | 98.52 155 |
|
PVSNet_BlendedMVS | | | 96.73 101 | 96.60 94 | 97.12 164 | 99.25 66 | 95.35 155 | 98.26 189 | 99.26 8 | 94.28 139 | 97.94 73 | 97.46 195 | 92.74 85 | 99.81 52 | 96.88 74 | 93.32 232 | 96.20 289 |
|
PVSNet_Blended | | | 97.38 77 | 97.12 71 | 98.14 96 | 99.25 66 | 95.35 155 | 97.28 277 | 99.26 8 | 93.13 196 | 97.94 73 | 98.21 140 | 92.74 85 | 99.81 52 | 96.88 74 | 99.40 80 | 99.27 100 |
|
TAMVS | | | 97.02 91 | 96.79 85 | 97.70 125 | 98.06 158 | 95.31 157 | 98.52 157 | 98.31 162 | 93.95 152 | 97.05 108 | 98.61 102 | 93.49 77 | 98.52 229 | 95.33 126 | 97.81 139 | 99.29 98 |
|
PS-CasMVS | | | 94.67 209 | 93.99 211 | 96.71 185 | 96.68 240 | 95.26 158 | 99.13 47 | 99.03 24 | 93.68 171 | 92.33 266 | 97.95 157 | 85.35 245 | 98.10 275 | 93.59 170 | 88.16 290 | 96.79 236 |
|
V42 | | | 94.78 198 | 94.14 200 | 96.70 187 | 96.33 264 | 95.22 159 | 98.97 67 | 98.09 211 | 92.32 230 | 94.31 201 | 97.06 230 | 88.39 178 | 98.55 221 | 92.90 191 | 88.87 280 | 96.34 286 |
|
pm-mvs1 | | | 93.94 246 | 93.06 249 | 96.59 204 | 96.49 248 | 95.16 160 | 98.95 69 | 98.03 219 | 92.32 230 | 91.08 279 | 97.84 167 | 84.54 261 | 98.41 253 | 92.16 207 | 86.13 312 | 96.19 290 |
|
CSCG | | | 97.85 53 | 97.74 47 | 98.20 93 | 99.67 18 | 95.16 160 | 99.22 28 | 99.32 7 | 93.04 198 | 97.02 109 | 98.92 77 | 95.36 43 | 99.91 24 | 97.43 54 | 99.64 47 | 99.52 68 |
|
VDDNet | | | 95.36 168 | 94.53 181 | 97.86 112 | 98.10 155 | 95.13 162 | 98.85 87 | 97.75 228 | 90.46 269 | 98.36 53 | 99.39 7 | 73.27 328 | 99.64 102 | 97.98 27 | 96.58 161 | 98.81 140 |
|
gg-mvs-nofinetune | | | 92.21 269 | 90.58 283 | 97.13 163 | 96.75 236 | 95.09 163 | 95.85 318 | 89.40 349 | 85.43 320 | 94.50 185 | 81.98 342 | 80.80 294 | 98.40 259 | 92.16 207 | 98.33 122 | 97.88 182 |
|
PS-MVSNAJss | | | 96.43 111 | 96.26 106 | 96.92 178 | 95.84 293 | 95.08 164 | 99.16 42 | 98.50 137 | 95.87 72 | 93.84 227 | 98.34 129 | 94.51 62 | 98.61 215 | 96.88 74 | 93.45 229 | 97.06 209 |
|
thres600view7 | | | 95.49 155 | 94.77 170 | 97.67 128 | 98.98 91 | 95.02 165 | 98.85 87 | 96.90 293 | 95.38 91 | 96.63 128 | 96.90 252 | 84.29 264 | 99.59 109 | 88.65 285 | 96.33 173 | 98.40 161 |
|
GBi-Net | | | 94.49 218 | 93.80 221 | 96.56 209 | 98.21 146 | 95.00 166 | 98.82 93 | 98.18 185 | 92.46 215 | 94.09 216 | 97.07 227 | 81.16 288 | 97.95 284 | 92.08 209 | 92.14 243 | 96.72 244 |
|
test1 | | | 94.49 218 | 93.80 221 | 96.56 209 | 98.21 146 | 95.00 166 | 98.82 93 | 98.18 185 | 92.46 215 | 94.09 216 | 97.07 227 | 81.16 288 | 97.95 284 | 92.08 209 | 92.14 243 | 96.72 244 |
|
FMVSNet1 | | | 93.19 260 | 92.07 263 | 96.56 209 | 97.54 187 | 95.00 166 | 98.82 93 | 98.18 185 | 90.38 272 | 92.27 267 | 97.07 227 | 73.68 327 | 97.95 284 | 89.36 272 | 91.30 254 | 96.72 244 |
|
tfpn200view9 | | | 95.32 172 | 94.62 177 | 97.43 149 | 98.94 96 | 94.98 169 | 98.68 132 | 96.93 291 | 95.33 99 | 96.55 135 | 96.53 270 | 84.23 269 | 99.56 118 | 88.11 292 | 96.29 176 | 97.76 184 |
|
GG-mvs-BLEND | | | | | 96.59 204 | 96.34 260 | 94.98 169 | 96.51 310 | 88.58 350 | | 93.10 248 | 94.34 310 | 80.34 299 | 98.05 279 | 89.53 268 | 96.99 153 | 96.74 241 |
|
thres400 | | | 95.38 165 | 94.62 177 | 97.65 130 | 98.94 96 | 94.98 169 | 98.68 132 | 96.93 291 | 95.33 99 | 96.55 135 | 96.53 270 | 84.23 269 | 99.56 118 | 88.11 292 | 96.29 176 | 98.40 161 |
|
F-COLMAP | | | 97.09 90 | 96.80 83 | 97.97 108 | 99.45 35 | 94.95 172 | 98.55 152 | 98.62 113 | 93.02 199 | 96.17 157 | 98.58 107 | 94.01 73 | 99.81 52 | 93.95 160 | 98.90 95 | 99.14 116 |
|
tfpn111 | | | 95.43 159 | 94.74 172 | 97.51 141 | 98.98 91 | 94.92 173 | 98.87 80 | 96.90 293 | 95.38 91 | 96.61 129 | 96.88 255 | 84.29 264 | 99.59 109 | 88.43 286 | 96.32 174 | 98.02 176 |
|
conf200view11 | | | 95.40 164 | 94.70 174 | 97.50 146 | 98.98 91 | 94.92 173 | 98.87 80 | 96.90 293 | 95.38 91 | 96.61 129 | 96.88 255 | 84.29 264 | 99.56 118 | 88.11 292 | 96.29 176 | 98.02 176 |
|
thres100view900 | | | 95.38 165 | 94.70 174 | 97.41 150 | 98.98 91 | 94.92 173 | 98.87 80 | 96.90 293 | 95.38 91 | 96.61 129 | 96.88 255 | 84.29 264 | 99.56 118 | 88.11 292 | 96.29 176 | 97.76 184 |
|
thres200 | | | 95.25 174 | 94.57 179 | 97.28 156 | 98.81 113 | 94.92 173 | 98.20 193 | 97.11 277 | 95.24 106 | 96.54 137 | 96.22 283 | 84.58 256 | 99.53 125 | 87.93 296 | 96.50 165 | 97.39 197 |
|
v1 | | | 94.75 201 | 94.11 204 | 96.69 188 | 96.27 272 | 94.87 177 | 98.69 128 | 98.12 198 | 92.43 223 | 94.32 200 | 96.94 246 | 88.71 169 | 98.54 222 | 92.66 197 | 88.84 283 | 96.67 254 |
|
v1141 | | | 94.75 201 | 94.11 204 | 96.67 194 | 96.27 272 | 94.86 178 | 98.69 128 | 98.12 198 | 92.43 223 | 94.31 201 | 96.94 246 | 88.78 165 | 98.48 233 | 92.63 198 | 88.85 282 | 96.67 254 |
|
view600 | | | 95.60 144 | 94.93 156 | 97.62 131 | 99.05 83 | 94.85 179 | 99.09 52 | 97.01 285 | 95.36 95 | 96.52 139 | 97.37 200 | 84.55 257 | 99.59 109 | 89.07 276 | 96.39 168 | 98.40 161 |
|
view800 | | | 95.60 144 | 94.93 156 | 97.62 131 | 99.05 83 | 94.85 179 | 99.09 52 | 97.01 285 | 95.36 95 | 96.52 139 | 97.37 200 | 84.55 257 | 99.59 109 | 89.07 276 | 96.39 168 | 98.40 161 |
|
conf0.05thres1000 | | | 95.60 144 | 94.93 156 | 97.62 131 | 99.05 83 | 94.85 179 | 99.09 52 | 97.01 285 | 95.36 95 | 96.52 139 | 97.37 200 | 84.55 257 | 99.59 109 | 89.07 276 | 96.39 168 | 98.40 161 |
|
tfpn | | | 95.60 144 | 94.93 156 | 97.62 131 | 99.05 83 | 94.85 179 | 99.09 52 | 97.01 285 | 95.36 95 | 96.52 139 | 97.37 200 | 84.55 257 | 99.59 109 | 89.07 276 | 96.39 168 | 98.40 161 |
|
v1neww | | | 94.83 193 | 94.22 193 | 96.68 191 | 96.39 253 | 94.85 179 | 98.87 80 | 98.11 203 | 92.45 220 | 94.45 187 | 97.06 230 | 88.82 160 | 98.54 222 | 92.93 188 | 88.91 278 | 96.65 259 |
|
v7new | | | 94.83 193 | 94.22 193 | 96.68 191 | 96.39 253 | 94.85 179 | 98.87 80 | 98.11 203 | 92.45 220 | 94.45 187 | 97.06 230 | 88.82 160 | 98.54 222 | 92.93 188 | 88.91 278 | 96.65 259 |
|
v18 | | | 92.10 271 | 90.97 271 | 95.50 257 | 96.34 260 | 94.85 179 | 98.82 93 | 97.52 241 | 89.99 279 | 85.31 316 | 93.26 315 | 88.90 154 | 96.92 308 | 88.82 281 | 79.77 327 | 94.73 315 |
|
divwei89l23v2f112 | | | 94.76 199 | 94.12 203 | 96.67 194 | 96.28 270 | 94.85 179 | 98.69 128 | 98.12 198 | 92.44 222 | 94.29 204 | 96.94 246 | 88.85 157 | 98.48 233 | 92.67 196 | 88.79 284 | 96.67 254 |
|
v6 | | | 94.83 193 | 94.21 195 | 96.69 188 | 96.36 257 | 94.85 179 | 98.87 80 | 98.11 203 | 92.46 215 | 94.44 193 | 97.05 234 | 88.76 166 | 98.57 220 | 92.95 187 | 88.92 277 | 96.65 259 |
|
v16 | | | 92.08 272 | 90.94 272 | 95.49 258 | 96.38 256 | 94.84 188 | 98.81 99 | 97.51 244 | 89.94 282 | 85.25 317 | 93.28 314 | 88.86 155 | 96.91 309 | 88.70 283 | 79.78 326 | 94.72 316 |
|
PEN-MVS | | | 94.42 222 | 93.73 228 | 96.49 216 | 96.28 270 | 94.84 188 | 99.17 35 | 99.00 26 | 93.51 177 | 92.23 268 | 97.83 170 | 86.10 232 | 97.90 287 | 92.55 201 | 86.92 305 | 96.74 241 |
|
v17 | | | 92.08 272 | 90.94 272 | 95.48 259 | 96.34 260 | 94.83 190 | 98.81 99 | 97.52 241 | 89.95 281 | 85.32 314 | 93.24 316 | 88.91 153 | 96.91 309 | 88.76 282 | 79.63 328 | 94.71 317 |
|
v15 | | | 91.94 274 | 90.77 276 | 95.43 264 | 96.31 268 | 94.83 190 | 98.77 110 | 97.50 247 | 89.92 283 | 85.13 318 | 93.08 319 | 88.76 166 | 96.86 311 | 88.40 287 | 79.10 330 | 94.61 321 |
|
v8 | | | 94.47 220 | 93.77 224 | 96.57 208 | 96.36 257 | 94.83 190 | 99.05 57 | 98.19 182 | 91.92 237 | 93.16 243 | 96.97 242 | 88.82 160 | 98.48 233 | 91.69 223 | 87.79 294 | 96.39 283 |
|
TAPA-MVS | | 93.98 7 | 95.35 169 | 94.56 180 | 97.74 119 | 99.13 81 | 94.83 190 | 98.33 178 | 98.64 112 | 86.62 311 | 96.29 155 | 98.61 102 | 94.00 74 | 99.29 142 | 80.00 323 | 99.41 78 | 99.09 119 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
V14 | | | 91.93 275 | 90.76 277 | 95.42 267 | 96.33 264 | 94.81 194 | 98.77 110 | 97.51 244 | 89.86 285 | 85.09 319 | 93.13 317 | 88.80 164 | 96.83 313 | 88.32 288 | 79.06 332 | 94.60 322 |
|
v12 | | | 91.89 277 | 90.70 279 | 95.43 264 | 96.31 268 | 94.80 195 | 98.76 113 | 97.50 247 | 89.76 287 | 84.95 322 | 93.00 322 | 88.82 160 | 96.82 315 | 88.23 290 | 79.00 334 | 94.68 320 |
|
v10 | | | 94.29 228 | 93.55 237 | 96.51 215 | 96.39 253 | 94.80 195 | 98.99 63 | 98.19 182 | 91.35 255 | 93.02 249 | 96.99 240 | 88.09 186 | 98.41 253 | 90.50 250 | 88.41 287 | 96.33 287 |
|
V9 | | | 91.91 276 | 90.73 278 | 95.45 261 | 96.32 267 | 94.80 195 | 98.77 110 | 97.50 247 | 89.81 286 | 85.03 321 | 93.08 319 | 88.76 166 | 96.86 311 | 88.24 289 | 79.03 333 | 94.69 318 |
|
v7 | | | 94.69 205 | 94.04 206 | 96.62 201 | 96.41 252 | 94.79 198 | 98.78 109 | 98.13 196 | 91.89 238 | 94.30 203 | 97.16 214 | 88.13 185 | 98.45 240 | 91.96 216 | 89.65 265 | 96.61 264 |
|
v2v482 | | | 94.69 205 | 94.03 207 | 96.65 196 | 96.17 277 | 94.79 198 | 98.67 135 | 98.08 212 | 92.72 209 | 94.00 221 | 97.16 214 | 87.69 200 | 98.45 240 | 92.91 190 | 88.87 280 | 96.72 244 |
|
v1144 | | | 94.59 214 | 93.92 214 | 96.60 203 | 96.21 274 | 94.78 200 | 98.59 143 | 98.14 195 | 91.86 241 | 94.21 210 | 97.02 237 | 87.97 188 | 98.41 253 | 91.72 222 | 89.57 266 | 96.61 264 |
|
v13 | | | 91.88 278 | 90.69 280 | 95.43 264 | 96.33 264 | 94.78 200 | 98.75 114 | 97.50 247 | 89.68 290 | 84.93 323 | 92.98 323 | 88.84 158 | 96.83 313 | 88.14 291 | 79.09 331 | 94.69 318 |
|
v11 | | | 91.85 279 | 90.68 281 | 95.36 269 | 96.34 260 | 94.74 202 | 98.80 102 | 97.43 258 | 89.60 293 | 85.09 319 | 93.03 321 | 88.53 175 | 96.75 316 | 87.37 299 | 79.96 325 | 94.58 323 |
|
TransMVSNet (Re) | | | 92.67 264 | 91.51 268 | 96.15 236 | 96.58 243 | 94.65 203 | 98.90 73 | 96.73 301 | 90.86 267 | 89.46 293 | 97.86 164 | 85.62 240 | 98.09 277 | 86.45 304 | 81.12 323 | 95.71 301 |
|
BH-RMVSNet | | | 95.92 128 | 95.32 138 | 97.69 126 | 98.32 141 | 94.64 204 | 98.19 197 | 97.45 256 | 94.56 131 | 96.03 160 | 98.61 102 | 85.02 249 | 99.12 161 | 90.68 240 | 99.06 90 | 99.30 96 |
|
OPM-MVS | | | 95.69 139 | 95.33 137 | 96.76 183 | 96.16 280 | 94.63 205 | 98.43 169 | 98.39 154 | 96.64 50 | 95.02 172 | 98.78 87 | 85.15 248 | 99.05 172 | 95.21 133 | 94.20 209 | 96.60 266 |
|
jajsoiax | | | 95.45 158 | 95.03 149 | 96.73 184 | 95.42 306 | 94.63 205 | 99.14 44 | 98.52 130 | 95.74 75 | 93.22 241 | 98.36 124 | 83.87 277 | 98.65 213 | 96.95 68 | 94.04 215 | 96.91 223 |
|
plane_prior7 | | | | | | 97.42 196 | 94.63 205 | | | | | | | | | | |
|
plane_prior6 | | | | | | 97.35 201 | 94.61 208 | | | | | | 87.09 209 | | | | |
|
plane_prior3 | | | | | | | 94.61 208 | | | 97.02 39 | 95.34 166 | | | | | | |
|
HQP_MVS | | | 96.14 122 | 95.90 116 | 96.85 179 | 97.42 196 | 94.60 210 | 98.80 102 | 98.56 122 | 97.28 21 | 95.34 166 | 98.28 133 | 87.09 209 | 99.03 177 | 96.07 99 | 94.27 206 | 96.92 218 |
|
plane_prior | | | | | | | 94.60 210 | 98.44 167 | | 96.74 46 | | | | | | 94.22 208 | |
|
CHOSEN 1792x2688 | | | 97.12 88 | 96.80 83 | 98.08 102 | 99.30 54 | 94.56 212 | 98.05 213 | 99.71 1 | 93.57 176 | 97.09 103 | 98.91 78 | 88.17 182 | 99.89 29 | 96.87 77 | 99.56 63 | 99.81 2 |
|
NP-MVS | | | | | | 97.28 204 | 94.51 213 | | | | | 97.73 176 | | | | | |
|
v1192 | | | 94.32 226 | 93.58 236 | 96.53 213 | 96.10 281 | 94.45 214 | 98.50 162 | 98.17 190 | 91.54 246 | 94.19 211 | 97.06 230 | 86.95 213 | 98.43 245 | 90.14 253 | 89.57 266 | 96.70 248 |
|
mvs_tets | | | 95.41 163 | 95.00 150 | 96.65 196 | 95.58 301 | 94.42 215 | 99.00 62 | 98.55 124 | 95.73 76 | 93.21 242 | 98.38 122 | 83.45 280 | 98.63 214 | 97.09 63 | 94.00 217 | 96.91 223 |
|
LTVRE_ROB | | 92.95 15 | 94.60 212 | 93.90 216 | 96.68 191 | 97.41 199 | 94.42 215 | 98.52 157 | 98.59 115 | 91.69 243 | 91.21 277 | 98.35 125 | 84.87 252 | 99.04 176 | 91.06 234 | 93.44 230 | 96.60 266 |
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 | | | 93.98 245 | 93.26 248 | 96.14 237 | 96.06 283 | 94.39 217 | 99.20 32 | 98.86 52 | 93.06 197 | 91.78 273 | 97.81 172 | 85.87 236 | 97.58 297 | 90.53 243 | 86.17 310 | 96.46 282 |
|
v7n | | | 94.19 233 | 93.43 244 | 96.47 218 | 95.90 289 | 94.38 218 | 99.26 17 | 98.34 160 | 91.99 236 | 92.76 254 | 97.13 222 | 88.31 179 | 98.52 229 | 89.48 270 | 87.70 295 | 96.52 276 |
|
v144192 | | | 94.39 224 | 93.70 229 | 96.48 217 | 96.06 283 | 94.35 219 | 98.58 145 | 98.16 192 | 91.45 248 | 94.33 199 | 97.02 237 | 87.50 205 | 98.45 240 | 91.08 233 | 89.11 273 | 96.63 262 |
|
V4 | | | 94.18 235 | 93.52 239 | 96.13 238 | 95.89 290 | 94.31 220 | 99.23 22 | 98.22 177 | 91.42 250 | 92.82 253 | 96.89 253 | 87.93 190 | 98.52 229 | 91.51 227 | 87.81 292 | 95.58 304 |
|
v52 | | | 94.18 235 | 93.52 239 | 96.13 238 | 95.95 288 | 94.29 221 | 99.23 22 | 98.21 178 | 91.42 250 | 92.84 252 | 96.89 253 | 87.85 194 | 98.53 228 | 91.51 227 | 87.81 292 | 95.57 305 |
|
cascas | | | 94.63 211 | 93.86 218 | 96.93 176 | 96.91 227 | 94.27 222 | 96.00 316 | 98.51 132 | 85.55 319 | 94.54 183 | 96.23 281 | 84.20 271 | 98.87 197 | 95.80 111 | 96.98 154 | 97.66 191 |
|
HQP5-MVS | | | | | | | 94.25 223 | | | | | | | | | | |
|
HQP-MVS | | | 95.72 135 | 95.40 130 | 96.69 188 | 97.20 210 | 94.25 223 | 98.05 213 | 98.46 142 | 96.43 54 | 94.45 187 | 97.73 176 | 86.75 215 | 98.96 184 | 95.30 127 | 94.18 210 | 96.86 231 |
|
TR-MVS | | | 94.94 190 | 94.20 196 | 97.17 161 | 97.75 174 | 94.14 225 | 97.59 256 | 97.02 283 | 92.28 232 | 95.75 164 | 97.64 186 | 83.88 276 | 98.96 184 | 89.77 261 | 96.15 186 | 98.40 161 |
|
v1921920 | | | 94.20 232 | 93.47 243 | 96.40 224 | 95.98 286 | 94.08 226 | 98.52 157 | 98.15 193 | 91.33 256 | 94.25 207 | 97.20 213 | 86.41 220 | 98.42 246 | 90.04 258 | 89.39 271 | 96.69 253 |
|
Baseline_NR-MVSNet | | | 94.35 225 | 93.81 220 | 95.96 242 | 96.20 275 | 94.05 227 | 98.61 142 | 96.67 305 | 91.44 249 | 93.85 226 | 97.60 188 | 88.57 172 | 98.14 273 | 94.39 148 | 86.93 304 | 95.68 302 |
|
VDD-MVS | | | 95.82 132 | 95.23 142 | 97.61 136 | 98.84 112 | 93.98 228 | 98.68 132 | 97.40 261 | 95.02 115 | 97.95 72 | 99.34 19 | 74.37 326 | 99.78 76 | 98.64 4 | 96.80 156 | 99.08 122 |
|
PMMVS | | | 96.60 104 | 96.33 103 | 97.41 150 | 97.90 167 | 93.93 229 | 97.35 272 | 98.41 150 | 92.84 207 | 97.76 81 | 97.45 197 | 91.10 118 | 99.20 154 | 96.26 97 | 97.91 134 | 99.11 118 |
|
v1240 | | | 94.06 243 | 93.29 247 | 96.34 229 | 96.03 285 | 93.90 230 | 98.44 167 | 98.17 190 | 91.18 264 | 94.13 215 | 97.01 239 | 86.05 233 | 98.42 246 | 89.13 275 | 89.50 269 | 96.70 248 |
|
GA-MVS | | | 94.81 197 | 94.03 207 | 97.14 162 | 97.15 215 | 93.86 231 | 96.76 300 | 97.58 234 | 94.00 148 | 94.76 180 | 97.04 235 | 80.91 291 | 98.48 233 | 91.79 219 | 96.25 182 | 99.09 119 |
|
ACMM | | 93.85 9 | 95.69 139 | 95.38 134 | 96.61 202 | 97.61 181 | 93.84 232 | 98.91 72 | 98.44 146 | 95.25 104 | 94.28 205 | 98.47 115 | 86.04 235 | 99.12 161 | 95.50 122 | 93.95 219 | 96.87 229 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
mvs_anonymous | | | 96.70 102 | 96.53 98 | 97.18 160 | 98.19 149 | 93.78 233 | 98.31 183 | 98.19 182 | 94.01 147 | 94.47 186 | 98.27 136 | 92.08 99 | 98.46 238 | 97.39 56 | 97.91 134 | 99.31 93 |
|
XVG-OURS-SEG-HR | | | 96.51 109 | 96.34 102 | 97.02 169 | 98.77 115 | 93.76 234 | 97.79 243 | 98.50 137 | 95.45 87 | 96.94 112 | 99.09 54 | 87.87 193 | 99.55 124 | 96.76 80 | 95.83 198 | 97.74 186 |
|
XVG-OURS | | | 96.55 108 | 96.41 100 | 96.99 170 | 98.75 116 | 93.76 234 | 97.50 261 | 98.52 130 | 95.67 78 | 96.83 120 | 99.30 26 | 88.95 152 | 99.53 125 | 95.88 107 | 96.26 181 | 97.69 190 |
|
CLD-MVS | | | 95.62 142 | 95.34 135 | 96.46 221 | 97.52 189 | 93.75 236 | 97.27 278 | 98.46 142 | 95.53 84 | 94.42 195 | 98.00 154 | 86.21 223 | 98.97 181 | 96.25 98 | 94.37 204 | 96.66 257 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
IterMVS-LS | | | 95.46 157 | 95.21 143 | 96.22 234 | 98.12 154 | 93.72 237 | 98.32 182 | 98.13 196 | 93.71 166 | 94.26 206 | 97.31 207 | 92.24 92 | 98.10 275 | 94.63 141 | 90.12 260 | 96.84 232 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
EI-MVSNet | | | 95.96 125 | 95.83 118 | 96.36 226 | 97.93 165 | 93.70 238 | 98.12 206 | 98.27 168 | 93.70 168 | 95.07 170 | 99.02 60 | 92.23 93 | 98.54 222 | 94.68 140 | 93.46 227 | 96.84 232 |
|
LPG-MVS_test | | | 95.62 142 | 95.34 135 | 96.47 218 | 97.46 192 | 93.54 239 | 98.99 63 | 98.54 125 | 94.67 126 | 94.36 197 | 98.77 89 | 85.39 243 | 99.11 165 | 95.71 115 | 94.15 212 | 96.76 239 |
|
LGP-MVS_train | | | | | 96.47 218 | 97.46 192 | 93.54 239 | | 98.54 125 | 94.67 126 | 94.36 197 | 98.77 89 | 85.39 243 | 99.11 165 | 95.71 115 | 94.15 212 | 96.76 239 |
|
ACMP | | 93.49 10 | 95.34 170 | 94.98 152 | 96.43 222 | 97.67 177 | 93.48 241 | 98.73 121 | 98.44 146 | 94.94 121 | 92.53 260 | 98.53 109 | 84.50 262 | 99.14 159 | 95.48 123 | 94.00 217 | 96.66 257 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
CR-MVSNet | | | 94.76 199 | 94.15 199 | 96.59 204 | 97.00 220 | 93.43 242 | 94.96 326 | 97.56 235 | 92.46 215 | 96.93 113 | 96.24 279 | 88.15 183 | 97.88 291 | 87.38 298 | 96.65 159 | 98.46 158 |
|
RPMNet | | | 92.52 266 | 91.17 269 | 96.59 204 | 97.00 220 | 93.43 242 | 94.96 326 | 97.26 273 | 82.27 330 | 96.93 113 | 92.12 334 | 86.98 212 | 97.88 291 | 76.32 332 | 96.65 159 | 98.46 158 |
|
IB-MVS | | 91.98 17 | 93.27 257 | 91.97 264 | 97.19 159 | 97.47 191 | 93.41 244 | 97.09 285 | 95.99 314 | 93.32 190 | 92.47 263 | 95.73 294 | 78.06 307 | 99.53 125 | 94.59 144 | 82.98 318 | 98.62 152 |
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 85 | 97.18 70 | 97.20 158 | 98.81 113 | 93.27 245 | 95.78 320 | 99.15 18 | 95.25 104 | 96.79 125 | 98.11 146 | 92.29 90 | 99.07 171 | 98.56 9 | 99.85 2 | 99.25 102 |
|
ACMH | | 92.88 16 | 94.55 216 | 93.95 213 | 96.34 229 | 97.63 179 | 93.26 246 | 98.81 99 | 98.49 141 | 93.43 180 | 89.74 290 | 98.53 109 | 81.91 286 | 99.08 170 | 93.69 166 | 93.30 233 | 96.70 248 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
COLMAP_ROB | | 93.27 12 | 95.33 171 | 94.87 162 | 96.71 185 | 99.29 57 | 93.24 247 | 98.58 145 | 98.11 203 | 89.92 283 | 93.57 232 | 99.10 50 | 86.37 221 | 99.79 71 | 90.78 238 | 98.10 130 | 97.09 208 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
AllTest | | | 95.24 175 | 94.65 176 | 96.99 170 | 99.25 66 | 93.21 248 | 98.59 143 | 98.18 185 | 91.36 253 | 93.52 234 | 98.77 89 | 84.67 254 | 99.72 88 | 89.70 265 | 97.87 136 | 98.02 176 |
|
TestCases | | | | | 96.99 170 | 99.25 66 | 93.21 248 | | 98.18 185 | 91.36 253 | 93.52 234 | 98.77 89 | 84.67 254 | 99.72 88 | 89.70 265 | 97.87 136 | 98.02 176 |
|
MIMVSNet | | | 93.26 258 | 92.21 262 | 96.41 223 | 97.73 176 | 93.13 250 | 95.65 321 | 97.03 282 | 91.27 261 | 94.04 219 | 96.06 287 | 75.33 319 | 97.19 304 | 86.56 303 | 96.23 183 | 98.92 135 |
|
Patchmtry | | | 93.22 259 | 92.35 260 | 95.84 247 | 96.77 233 | 93.09 251 | 94.66 332 | 97.56 235 | 87.37 309 | 92.90 251 | 96.24 279 | 88.15 183 | 97.90 287 | 87.37 299 | 90.10 261 | 96.53 275 |
|
v148 | | | 94.29 228 | 93.76 226 | 95.91 244 | 96.10 281 | 92.93 252 | 98.58 145 | 97.97 220 | 92.59 213 | 93.47 237 | 96.95 244 | 88.53 175 | 98.32 262 | 92.56 200 | 87.06 303 | 96.49 280 |
|
test0.0.03 1 | | | 94.08 241 | 93.51 241 | 95.80 249 | 95.53 303 | 92.89 253 | 97.38 267 | 95.97 315 | 95.11 110 | 92.51 262 | 96.66 265 | 87.71 197 | 96.94 307 | 87.03 301 | 93.67 222 | 97.57 192 |
|
PatchT | | | 93.06 262 | 91.97 264 | 96.35 227 | 96.69 239 | 92.67 254 | 94.48 333 | 97.08 278 | 86.62 311 | 97.08 104 | 92.23 333 | 87.94 189 | 97.90 287 | 78.89 327 | 96.69 157 | 98.49 157 |
|
v748 | | | 93.75 249 | 93.06 249 | 95.82 248 | 95.73 296 | 92.64 255 | 99.25 19 | 98.24 175 | 91.60 245 | 92.22 269 | 96.52 272 | 87.60 202 | 98.46 238 | 90.64 241 | 85.72 313 | 96.36 285 |
|
MVP-Stereo | | | 94.28 230 | 93.92 214 | 95.35 270 | 94.95 312 | 92.60 256 | 97.97 221 | 97.65 232 | 91.61 244 | 90.68 284 | 97.09 225 | 86.32 222 | 98.42 246 | 89.70 265 | 99.34 83 | 95.02 312 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
pmmvs5 | | | 93.65 252 | 92.97 251 | 95.68 253 | 95.49 304 | 92.37 257 | 98.20 193 | 97.28 271 | 89.66 291 | 92.58 258 | 97.26 209 | 82.14 284 | 98.09 277 | 93.18 180 | 90.95 257 | 96.58 268 |
|
BH-untuned | | | 95.95 126 | 95.72 121 | 96.65 196 | 98.55 133 | 92.26 258 | 98.23 190 | 97.79 226 | 93.73 164 | 94.62 181 | 98.01 153 | 88.97 151 | 99.00 180 | 93.04 184 | 98.51 113 | 98.68 147 |
|
pmmvs-eth3d | | | 90.36 294 | 89.05 297 | 94.32 296 | 91.10 330 | 92.12 259 | 97.63 255 | 96.95 290 | 88.86 301 | 84.91 324 | 93.13 317 | 78.32 306 | 96.74 317 | 88.70 283 | 81.81 322 | 94.09 329 |
|
FMVSNet5 | | | 91.81 280 | 90.92 274 | 94.49 291 | 97.21 209 | 92.09 260 | 98.00 219 | 97.55 239 | 89.31 298 | 90.86 282 | 95.61 299 | 74.48 324 | 95.32 330 | 85.57 310 | 89.70 264 | 96.07 293 |
|
PVSNet | | 91.96 18 | 96.35 114 | 96.15 109 | 96.96 173 | 99.17 77 | 92.05 261 | 96.08 312 | 98.68 97 | 93.69 169 | 97.75 82 | 97.80 173 | 88.86 155 | 99.69 96 | 94.26 154 | 99.01 91 | 99.15 114 |
|
ACMH+ | | 92.99 14 | 94.30 227 | 93.77 224 | 95.88 246 | 97.81 172 | 92.04 262 | 98.71 124 | 98.37 157 | 93.99 149 | 90.60 285 | 98.47 115 | 80.86 293 | 99.05 172 | 92.75 195 | 92.40 242 | 96.55 273 |
|
ADS-MVSNet | | | 95.00 183 | 94.45 186 | 96.63 199 | 98.00 160 | 91.91 263 | 96.04 313 | 97.74 229 | 90.15 274 | 96.47 150 | 96.64 267 | 87.89 191 | 98.96 184 | 90.08 255 | 97.06 151 | 99.02 125 |
|
mvs-test1 | | | 96.60 104 | 96.68 92 | 96.37 225 | 97.89 168 | 91.81 264 | 98.56 150 | 98.10 208 | 96.57 52 | 96.52 139 | 97.94 158 | 90.81 121 | 99.45 133 | 95.72 113 | 98.01 131 | 97.86 183 |
|
BH-w/o | | | 95.38 165 | 95.08 148 | 96.26 233 | 98.34 139 | 91.79 265 | 97.70 248 | 97.43 258 | 92.87 206 | 94.24 208 | 97.22 212 | 88.66 170 | 98.84 200 | 91.55 225 | 97.70 144 | 98.16 173 |
|
Patchmatch-test | | | 94.42 222 | 93.68 231 | 96.63 199 | 97.60 182 | 91.76 266 | 94.83 330 | 97.49 253 | 89.45 295 | 94.14 214 | 97.10 223 | 88.99 147 | 98.83 202 | 85.37 313 | 98.13 129 | 99.29 98 |
|
EPMVS | | | 94.99 184 | 94.48 182 | 96.52 214 | 97.22 208 | 91.75 267 | 97.23 279 | 91.66 346 | 94.11 142 | 97.28 99 | 96.81 260 | 85.70 239 | 98.84 200 | 93.04 184 | 97.28 149 | 98.97 130 |
|
Fast-Effi-MVS+-dtu | | | 95.87 129 | 95.85 117 | 95.91 244 | 97.74 175 | 91.74 268 | 98.69 128 | 98.15 193 | 95.56 83 | 94.92 173 | 97.68 183 | 88.98 150 | 98.79 206 | 93.19 179 | 97.78 141 | 97.20 207 |
|
XVG-ACMP-BASELINE | | | 94.54 217 | 94.14 200 | 95.75 252 | 96.55 244 | 91.65 269 | 98.11 208 | 98.44 146 | 94.96 118 | 94.22 209 | 97.90 161 | 79.18 304 | 99.11 165 | 94.05 159 | 93.85 220 | 96.48 281 |
|
TDRefinement | | | 91.06 288 | 89.68 291 | 95.21 272 | 85.35 341 | 91.49 270 | 98.51 161 | 97.07 279 | 91.47 247 | 88.83 298 | 97.84 167 | 77.31 313 | 99.09 169 | 92.79 194 | 77.98 335 | 95.04 311 |
|
MDA-MVSNet-bldmvs | | | 89.97 296 | 88.35 302 | 94.83 284 | 95.21 309 | 91.34 271 | 97.64 253 | 97.51 244 | 88.36 304 | 71.17 341 | 96.13 286 | 79.22 303 | 96.63 322 | 83.65 315 | 86.27 309 | 96.52 276 |
|
ITE_SJBPF | | | | | 95.44 262 | 97.42 196 | 91.32 272 | | 97.50 247 | 95.09 113 | 93.59 230 | 98.35 125 | 81.70 287 | 98.88 196 | 89.71 264 | 93.39 231 | 96.12 291 |
|
Patchmatch-test1 | | | 95.32 172 | 94.97 154 | 96.35 227 | 97.67 177 | 91.29 273 | 97.33 274 | 97.60 233 | 94.68 125 | 96.92 115 | 96.95 244 | 83.97 274 | 98.50 232 | 91.33 231 | 98.32 123 | 99.25 102 |
|
pmmvs6 | | | 91.77 281 | 90.63 282 | 95.17 274 | 94.69 317 | 91.24 274 | 98.67 135 | 97.92 222 | 86.14 314 | 89.62 291 | 97.56 192 | 75.79 318 | 98.34 260 | 90.75 239 | 84.56 317 | 95.94 296 |
|
test_0402 | | | 91.32 284 | 90.27 286 | 94.48 292 | 96.60 242 | 91.12 275 | 98.50 162 | 97.22 275 | 86.10 315 | 88.30 300 | 96.98 241 | 77.65 311 | 97.99 283 | 78.13 329 | 92.94 238 | 94.34 325 |
|
MIMVSNet1 | | | 89.67 298 | 88.28 303 | 93.82 300 | 92.81 326 | 91.08 276 | 98.01 217 | 97.45 256 | 87.95 305 | 87.90 302 | 95.87 292 | 67.63 337 | 94.56 333 | 78.73 328 | 88.18 289 | 95.83 298 |
|
USDC | | | 93.33 256 | 92.71 255 | 95.21 272 | 96.83 232 | 90.83 277 | 96.91 291 | 97.50 247 | 93.84 157 | 90.72 283 | 98.14 144 | 77.69 309 | 98.82 203 | 89.51 269 | 93.21 236 | 95.97 295 |
|
DWT-MVSNet_test | | | 94.82 196 | 94.36 189 | 96.20 235 | 97.35 201 | 90.79 278 | 98.34 177 | 96.57 308 | 92.91 204 | 95.33 168 | 96.44 275 | 82.00 285 | 99.12 161 | 94.52 146 | 95.78 199 | 98.70 145 |
|
MDA-MVSNet_test_wron | | | 90.71 291 | 89.38 294 | 94.68 287 | 94.83 314 | 90.78 279 | 97.19 281 | 97.46 254 | 87.60 307 | 72.41 340 | 95.72 296 | 86.51 218 | 96.71 320 | 85.92 308 | 86.80 307 | 96.56 272 |
|
PatchmatchNet | | | 95.71 137 | 95.52 129 | 96.29 232 | 97.58 184 | 90.72 280 | 96.84 298 | 97.52 241 | 94.06 145 | 97.08 104 | 96.96 243 | 89.24 142 | 98.90 194 | 92.03 213 | 98.37 120 | 99.26 101 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
PatchFormer-LS_test | | | 95.47 156 | 95.27 141 | 96.08 240 | 97.59 183 | 90.66 281 | 98.10 210 | 97.34 265 | 93.98 150 | 96.08 158 | 96.15 285 | 87.65 201 | 99.12 161 | 95.27 130 | 95.24 202 | 98.44 160 |
|
YYNet1 | | | 90.70 292 | 89.39 293 | 94.62 289 | 94.79 315 | 90.65 282 | 97.20 280 | 97.46 254 | 87.54 308 | 72.54 339 | 95.74 293 | 86.51 218 | 96.66 321 | 86.00 307 | 86.76 308 | 96.54 274 |
|
JIA-IIPM | | | 93.35 254 | 92.49 258 | 95.92 243 | 96.48 249 | 90.65 282 | 95.01 325 | 96.96 289 | 85.93 317 | 96.08 158 | 87.33 338 | 87.70 199 | 98.78 207 | 91.35 230 | 95.58 200 | 98.34 168 |
|
semantic-postprocess | | | | | 94.85 282 | 97.98 164 | 90.56 284 | | 98.11 203 | 93.75 161 | 92.58 258 | 97.48 194 | 83.91 275 | 97.41 301 | 92.48 204 | 91.30 254 | 96.58 268 |
|
EPNet_dtu | | | 95.21 177 | 94.95 155 | 95.99 241 | 96.17 277 | 90.45 285 | 98.16 202 | 97.27 272 | 96.77 44 | 93.14 246 | 98.33 130 | 90.34 128 | 98.42 246 | 85.57 310 | 98.81 102 | 99.09 119 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
IterMVS | | | 94.09 240 | 93.85 219 | 94.80 285 | 97.99 162 | 90.35 286 | 97.18 282 | 98.12 198 | 93.68 171 | 92.46 264 | 97.34 204 | 84.05 273 | 97.41 301 | 92.51 203 | 91.33 253 | 96.62 263 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
Effi-MVS+-dtu | | | 96.29 117 | 96.56 95 | 95.51 256 | 97.89 168 | 90.22 287 | 98.80 102 | 98.10 208 | 96.57 52 | 96.45 152 | 96.66 265 | 90.81 121 | 98.91 191 | 95.72 113 | 97.99 132 | 97.40 196 |
|
testgi | | | 93.06 262 | 92.45 259 | 94.88 281 | 96.43 251 | 89.90 288 | 98.75 114 | 97.54 240 | 95.60 81 | 91.63 275 | 97.91 160 | 74.46 325 | 97.02 306 | 86.10 306 | 93.67 222 | 97.72 188 |
|
UnsupCasMVSNet_eth | | | 90.99 289 | 89.92 290 | 94.19 298 | 94.08 320 | 89.83 289 | 97.13 284 | 98.67 104 | 93.69 169 | 85.83 311 | 96.19 284 | 75.15 320 | 96.74 317 | 89.14 274 | 79.41 329 | 96.00 294 |
|
TinyColmap | | | 92.31 268 | 91.53 267 | 94.65 288 | 96.92 225 | 89.75 290 | 96.92 289 | 96.68 304 | 90.45 270 | 89.62 291 | 97.85 166 | 76.06 317 | 98.81 204 | 86.74 302 | 92.51 241 | 95.41 306 |
|
test-LLR | | | 95.10 181 | 94.87 162 | 95.80 249 | 96.77 233 | 89.70 291 | 96.91 291 | 95.21 329 | 95.11 110 | 94.83 177 | 95.72 296 | 87.71 197 | 98.97 181 | 93.06 182 | 98.50 114 | 98.72 143 |
|
test-mter | | | 94.08 241 | 93.51 241 | 95.80 249 | 96.77 233 | 89.70 291 | 96.91 291 | 95.21 329 | 92.89 205 | 94.83 177 | 95.72 296 | 77.69 309 | 98.97 181 | 93.06 182 | 98.50 114 | 98.72 143 |
|
DeepPCF-MVS | | 96.37 2 | 97.93 49 | 98.48 13 | 96.30 231 | 99.00 88 | 89.54 293 | 97.43 264 | 98.87 49 | 98.16 2 | 99.26 8 | 99.38 11 | 96.12 19 | 99.64 102 | 98.30 21 | 99.77 19 | 99.72 32 |
|
MS-PatchMatch | | | 93.84 248 | 93.63 232 | 94.46 294 | 96.18 276 | 89.45 294 | 97.76 244 | 98.27 168 | 92.23 233 | 92.13 271 | 97.49 193 | 79.50 301 | 98.69 209 | 89.75 263 | 99.38 81 | 95.25 307 |
|
OpenMVS_ROB | | 86.42 20 | 89.00 300 | 87.43 306 | 93.69 301 | 93.08 324 | 89.42 295 | 97.91 228 | 96.89 297 | 78.58 336 | 85.86 310 | 94.69 306 | 69.48 333 | 98.29 268 | 77.13 330 | 93.29 234 | 93.36 334 |
|
SixPastTwentyTwo | | | 93.34 255 | 92.86 252 | 94.75 286 | 95.67 298 | 89.41 296 | 98.75 114 | 96.67 305 | 93.89 154 | 90.15 288 | 98.25 138 | 80.87 292 | 98.27 269 | 90.90 237 | 90.64 258 | 96.57 270 |
|
K. test v3 | | | 92.55 265 | 91.91 266 | 94.48 292 | 95.64 299 | 89.24 297 | 99.07 56 | 94.88 333 | 94.04 146 | 86.78 305 | 97.59 189 | 77.64 312 | 97.64 295 | 92.08 209 | 89.43 270 | 96.57 270 |
|
OurMVSNet-221017-0 | | | 94.21 231 | 94.00 209 | 94.85 282 | 95.60 300 | 89.22 298 | 98.89 77 | 97.43 258 | 95.29 102 | 92.18 270 | 98.52 112 | 82.86 282 | 98.59 218 | 93.46 172 | 91.76 250 | 96.74 241 |
|
TESTMET0.1,1 | | | 94.18 235 | 93.69 230 | 95.63 254 | 96.92 225 | 89.12 299 | 96.91 291 | 94.78 334 | 93.17 194 | 94.88 174 | 96.45 274 | 78.52 305 | 98.92 190 | 93.09 181 | 98.50 114 | 98.85 137 |
|
CostFormer | | | 94.95 188 | 94.73 173 | 95.60 255 | 97.28 204 | 89.06 300 | 97.53 259 | 96.89 297 | 89.66 291 | 96.82 122 | 96.72 263 | 86.05 233 | 98.95 188 | 95.53 121 | 96.13 187 | 98.79 141 |
|
tpm2 | | | 94.19 233 | 93.76 226 | 95.46 260 | 97.23 207 | 89.04 301 | 97.31 276 | 96.85 300 | 87.08 310 | 96.21 156 | 96.79 261 | 83.75 279 | 98.74 208 | 92.43 205 | 96.23 183 | 98.59 153 |
|
EG-PatchMatch MVS | | | 91.13 286 | 90.12 287 | 94.17 299 | 94.73 316 | 89.00 302 | 98.13 205 | 97.81 225 | 89.22 299 | 85.32 314 | 96.46 273 | 67.71 336 | 98.42 246 | 87.89 297 | 93.82 221 | 95.08 310 |
|
UnsupCasMVSNet_bld | | | 87.17 306 | 85.12 309 | 93.31 305 | 91.94 327 | 88.77 303 | 94.92 328 | 98.30 165 | 84.30 325 | 82.30 327 | 90.04 335 | 63.96 341 | 97.25 303 | 85.85 309 | 74.47 341 | 93.93 332 |
|
ADS-MVSNet2 | | | 94.58 215 | 94.40 188 | 95.11 276 | 98.00 160 | 88.74 304 | 96.04 313 | 97.30 269 | 90.15 274 | 96.47 150 | 96.64 267 | 87.89 191 | 97.56 298 | 90.08 255 | 97.06 151 | 99.02 125 |
|
LP | | | 91.12 287 | 89.99 289 | 94.53 290 | 96.35 259 | 88.70 305 | 93.86 337 | 97.35 264 | 84.88 322 | 90.98 280 | 94.77 305 | 84.40 263 | 97.43 300 | 75.41 335 | 91.89 249 | 97.47 193 |
|
LF4IMVS | | | 93.14 261 | 92.79 254 | 94.20 297 | 95.88 291 | 88.67 306 | 97.66 252 | 97.07 279 | 93.81 159 | 91.71 274 | 97.65 184 | 77.96 308 | 98.81 204 | 91.47 229 | 91.92 248 | 95.12 308 |
|
tpmvs | | | 94.60 212 | 94.36 189 | 95.33 271 | 97.46 192 | 88.60 307 | 96.88 296 | 97.68 230 | 91.29 259 | 93.80 228 | 96.42 276 | 88.58 171 | 99.24 145 | 91.06 234 | 96.04 195 | 98.17 172 |
|
tpmp4_e23 | | | 93.91 247 | 93.42 246 | 95.38 268 | 97.62 180 | 88.59 308 | 97.52 260 | 97.34 265 | 87.94 306 | 94.17 213 | 96.79 261 | 82.91 281 | 99.05 172 | 90.62 242 | 95.91 196 | 98.50 156 |
|
tpmrst | | | 95.63 141 | 95.69 126 | 95.44 262 | 97.54 187 | 88.54 309 | 96.97 287 | 97.56 235 | 93.50 178 | 97.52 97 | 96.93 250 | 89.49 135 | 99.16 156 | 95.25 131 | 96.42 167 | 98.64 151 |
|
lessismore_v0 | | | | | 94.45 295 | 94.93 313 | 88.44 310 | | 91.03 347 | | 86.77 306 | 97.64 186 | 76.23 316 | 98.42 246 | 90.31 252 | 85.64 314 | 96.51 278 |
|
MDTV_nov1_ep13 | | | | 95.40 130 | | 97.48 190 | 88.34 311 | 96.85 297 | 97.29 270 | 93.74 163 | 97.48 98 | 97.26 209 | 89.18 143 | 99.05 172 | 91.92 217 | 97.43 148 | |
|
new_pmnet | | | 90.06 295 | 89.00 298 | 93.22 307 | 94.18 318 | 88.32 312 | 96.42 311 | 96.89 297 | 86.19 313 | 85.67 313 | 93.62 312 | 77.18 314 | 97.10 305 | 81.61 320 | 89.29 272 | 94.23 326 |
|
test20.03 | | | 90.89 290 | 90.38 284 | 92.43 309 | 93.48 322 | 88.14 313 | 98.33 178 | 97.56 235 | 93.40 187 | 87.96 301 | 96.71 264 | 80.69 295 | 94.13 334 | 79.15 326 | 86.17 310 | 95.01 313 |
|
tpm cat1 | | | 93.36 253 | 92.80 253 | 95.07 277 | 97.58 184 | 87.97 314 | 96.76 300 | 97.86 224 | 82.17 331 | 93.53 233 | 96.04 288 | 86.13 224 | 99.13 160 | 89.24 273 | 95.87 197 | 98.10 174 |
|
tpm | | | 94.13 239 | 93.80 221 | 95.12 275 | 96.50 247 | 87.91 315 | 97.44 262 | 95.89 318 | 92.62 211 | 96.37 154 | 96.30 278 | 84.13 272 | 98.30 266 | 93.24 177 | 91.66 252 | 99.14 116 |
|
LCM-MVSNet-Re | | | 95.22 176 | 95.32 138 | 94.91 279 | 98.18 151 | 87.85 316 | 98.75 114 | 95.66 325 | 95.11 110 | 88.96 297 | 96.85 258 | 90.26 131 | 97.65 294 | 95.65 118 | 98.44 117 | 99.22 105 |
|
gm-plane-assit | | | | | | 95.88 291 | 87.47 317 | | | 89.74 289 | | 96.94 246 | | 99.19 155 | 93.32 176 | | |
|
Anonymous20231206 | | | 91.66 282 | 91.10 270 | 93.33 304 | 94.02 321 | 87.35 318 | 98.58 145 | 97.26 273 | 90.48 268 | 90.16 287 | 96.31 277 | 83.83 278 | 96.53 323 | 79.36 325 | 89.90 263 | 96.12 291 |
|
PVSNet_0 | | 88.72 19 | 91.28 285 | 90.03 288 | 95.00 278 | 97.99 162 | 87.29 319 | 94.84 329 | 98.50 137 | 92.06 235 | 89.86 289 | 95.19 300 | 79.81 300 | 99.39 136 | 92.27 206 | 69.79 342 | 98.33 169 |
|
pmmvs3 | | | 86.67 308 | 84.86 310 | 92.11 312 | 88.16 336 | 87.19 320 | 96.63 303 | 94.75 335 | 79.88 335 | 87.22 304 | 92.75 328 | 66.56 338 | 95.20 331 | 81.24 321 | 76.56 338 | 93.96 331 |
|
dp | | | 94.15 238 | 93.90 216 | 94.90 280 | 97.31 203 | 86.82 321 | 96.97 287 | 97.19 276 | 91.22 263 | 96.02 161 | 96.61 269 | 85.51 242 | 99.02 179 | 90.00 259 | 94.30 205 | 98.85 137 |
|
new-patchmatchnet | | | 88.50 304 | 87.45 305 | 91.67 313 | 90.31 332 | 85.89 322 | 97.16 283 | 97.33 268 | 89.47 294 | 83.63 326 | 92.77 327 | 76.38 315 | 95.06 332 | 82.70 317 | 77.29 336 | 94.06 330 |
|
Patchmatch-RL test | | | 91.49 283 | 90.85 275 | 93.41 303 | 91.37 329 | 84.40 323 | 92.81 338 | 95.93 317 | 91.87 240 | 87.25 303 | 94.87 304 | 88.99 147 | 96.53 323 | 92.54 202 | 82.00 320 | 99.30 96 |
|
MDTV_nov1_ep13_2view | | | | | | | 84.26 324 | 96.89 295 | | 90.97 266 | 97.90 76 | | 89.89 134 | | 93.91 161 | | 99.18 112 |
|
CVMVSNet | | | 95.43 159 | 96.04 112 | 93.57 302 | 97.93 165 | 83.62 325 | 98.12 206 | 98.59 115 | 95.68 77 | 96.56 133 | 99.02 60 | 87.51 203 | 97.51 299 | 93.56 171 | 97.44 147 | 99.60 61 |
|
EU-MVSNet | | | 93.66 250 | 94.14 200 | 92.25 311 | 95.96 287 | 83.38 326 | 98.52 157 | 98.12 198 | 94.69 124 | 92.61 257 | 98.13 145 | 87.36 207 | 96.39 325 | 91.82 218 | 90.00 262 | 96.98 214 |
|
PM-MVS | | | 87.77 305 | 86.55 307 | 91.40 314 | 91.03 331 | 83.36 327 | 96.92 289 | 95.18 331 | 91.28 260 | 86.48 308 | 93.42 313 | 53.27 344 | 96.74 317 | 89.43 271 | 81.97 321 | 94.11 328 |
|
testpf | | | 88.74 302 | 89.09 295 | 87.69 320 | 95.78 294 | 83.16 328 | 84.05 348 | 94.13 342 | 85.22 321 | 90.30 286 | 94.39 309 | 74.92 322 | 95.80 327 | 89.77 261 | 93.28 235 | 84.10 344 |
|
DSMNet-mixed | | | 92.52 266 | 92.58 257 | 92.33 310 | 94.15 319 | 82.65 329 | 98.30 185 | 94.26 339 | 89.08 300 | 92.65 256 | 95.73 294 | 85.01 250 | 95.76 328 | 86.24 305 | 97.76 142 | 98.59 153 |
|
MVS-HIRNet | | | 89.46 299 | 88.40 301 | 92.64 308 | 97.58 184 | 82.15 330 | 94.16 336 | 93.05 345 | 75.73 339 | 90.90 281 | 82.52 341 | 79.42 302 | 98.33 261 | 83.53 316 | 98.68 104 | 97.43 194 |
|
RPSCF | | | 94.87 192 | 95.40 130 | 93.26 306 | 98.89 106 | 82.06 331 | 98.33 178 | 98.06 215 | 90.30 273 | 96.56 133 | 99.26 29 | 87.09 209 | 99.49 128 | 93.82 164 | 96.32 174 | 98.24 171 |
|
Gipuma | | | 78.40 315 | 76.75 316 | 83.38 329 | 95.54 302 | 80.43 332 | 79.42 349 | 97.40 261 | 64.67 343 | 73.46 338 | 80.82 344 | 45.65 348 | 93.14 339 | 66.32 343 | 87.43 297 | 76.56 349 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
Anonymous20231211 | | | 83.69 311 | 81.50 313 | 90.26 315 | 89.23 335 | 80.10 333 | 97.97 221 | 97.06 281 | 72.79 341 | 82.05 329 | 92.57 329 | 50.28 345 | 96.32 326 | 76.15 333 | 75.38 339 | 94.37 324 |
|
test2356 | | | 88.68 303 | 88.61 299 | 88.87 318 | 89.90 334 | 78.23 334 | 95.11 324 | 96.66 307 | 88.66 303 | 89.06 296 | 94.33 311 | 73.14 329 | 92.56 341 | 75.56 334 | 95.11 203 | 95.81 299 |
|
no-one | | | 74.41 318 | 70.76 320 | 85.35 326 | 79.88 346 | 76.83 335 | 94.68 331 | 94.22 340 | 80.33 334 | 63.81 344 | 79.73 345 | 35.45 353 | 93.36 338 | 71.78 337 | 36.99 350 | 85.86 343 |
|
CMPMVS | | 66.06 21 | 89.70 297 | 89.67 292 | 89.78 316 | 93.19 323 | 76.56 336 | 97.00 286 | 98.35 159 | 80.97 333 | 81.57 330 | 97.75 175 | 74.75 323 | 98.61 215 | 89.85 260 | 93.63 224 | 94.17 327 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
testus | | | 88.91 301 | 89.08 296 | 88.40 319 | 91.39 328 | 76.05 337 | 96.56 306 | 96.48 309 | 89.38 297 | 89.39 294 | 95.17 302 | 70.94 331 | 93.56 337 | 77.04 331 | 95.41 201 | 95.61 303 |
|
ambc | | | | | 89.49 317 | 86.66 340 | 75.78 338 | 92.66 339 | 96.72 302 | | 86.55 307 | 92.50 330 | 46.01 347 | 97.90 287 | 90.32 251 | 82.09 319 | 94.80 314 |
|
1111 | | | 84.94 310 | 84.30 311 | 86.86 322 | 87.59 337 | 75.10 339 | 96.63 303 | 96.43 310 | 82.53 328 | 80.75 332 | 92.91 325 | 68.94 334 | 93.79 335 | 68.24 341 | 84.66 316 | 91.70 336 |
|
.test1245 | | | 73.05 319 | 76.31 317 | 63.27 340 | 87.59 337 | 75.10 339 | 96.63 303 | 96.43 310 | 82.53 328 | 80.75 332 | 92.91 325 | 68.94 334 | 93.79 335 | 68.24 341 | 12.72 353 | 20.91 353 |
|
test1235678 | | | 86.26 309 | 85.81 308 | 87.62 321 | 86.97 339 | 75.00 341 | 96.55 308 | 96.32 312 | 86.08 316 | 81.32 331 | 92.98 323 | 73.10 330 | 92.05 342 | 71.64 338 | 87.32 299 | 95.81 299 |
|
PMMVS2 | | | 77.95 316 | 75.44 319 | 85.46 325 | 82.54 343 | 74.95 342 | 94.23 335 | 93.08 344 | 72.80 340 | 74.68 337 | 87.38 337 | 36.36 352 | 91.56 343 | 73.95 336 | 63.94 343 | 89.87 337 |
|
DeepMVS_CX | | | | | 86.78 323 | 97.09 218 | 72.30 343 | | 95.17 332 | 75.92 338 | 84.34 325 | 95.19 300 | 70.58 332 | 95.35 329 | 79.98 324 | 89.04 275 | 92.68 335 |
|
LCM-MVSNet | | | 78.70 314 | 76.24 318 | 86.08 324 | 77.26 351 | 71.99 344 | 94.34 334 | 96.72 302 | 61.62 345 | 76.53 336 | 89.33 336 | 33.91 354 | 92.78 340 | 81.85 319 | 74.60 340 | 93.46 333 |
|
ANet_high | | | 69.08 320 | 65.37 322 | 80.22 331 | 65.99 354 | 71.96 345 | 90.91 342 | 90.09 348 | 82.62 327 | 49.93 350 | 78.39 346 | 29.36 355 | 81.75 350 | 62.49 347 | 38.52 349 | 86.95 342 |
|
test12356 | | | 83.47 312 | 83.37 312 | 83.78 328 | 84.43 342 | 70.09 346 | 95.12 323 | 95.60 326 | 82.98 326 | 78.89 334 | 92.43 332 | 64.99 339 | 91.41 344 | 70.36 339 | 85.55 315 | 89.82 338 |
|
testmv | | | 78.74 313 | 77.35 314 | 82.89 330 | 78.16 350 | 69.30 347 | 95.87 317 | 94.65 336 | 81.11 332 | 70.98 342 | 87.11 339 | 46.31 346 | 90.42 345 | 65.28 344 | 76.72 337 | 88.95 339 |
|
wuykxyi23d | | | 63.73 326 | 58.86 328 | 78.35 333 | 67.62 353 | 67.90 348 | 86.56 345 | 87.81 352 | 58.26 346 | 42.49 352 | 70.28 350 | 11.55 359 | 85.05 348 | 63.66 345 | 41.50 346 | 82.11 346 |
|
MVE | | 62.14 22 | 63.28 327 | 59.38 327 | 74.99 335 | 74.33 352 | 65.47 349 | 85.55 346 | 80.50 356 | 52.02 349 | 51.10 349 | 75.00 349 | 10.91 361 | 80.50 351 | 51.60 349 | 53.40 344 | 78.99 347 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
N_pmnet | | | 87.12 307 | 87.77 304 | 85.17 327 | 95.46 305 | 61.92 350 | 97.37 269 | 70.66 357 | 85.83 318 | 88.73 299 | 96.04 288 | 85.33 247 | 97.76 293 | 80.02 322 | 90.48 259 | 95.84 297 |
|
FPMVS | | | 77.62 317 | 77.14 315 | 79.05 332 | 79.25 347 | 60.97 351 | 95.79 319 | 95.94 316 | 65.96 342 | 67.93 343 | 94.40 308 | 37.73 351 | 88.88 347 | 68.83 340 | 88.46 286 | 87.29 340 |
|
tmp_tt | | | 68.90 321 | 66.97 321 | 74.68 336 | 50.78 356 | 59.95 352 | 87.13 344 | 83.47 355 | 38.80 351 | 62.21 345 | 96.23 281 | 64.70 340 | 76.91 354 | 88.91 280 | 30.49 351 | 87.19 341 |
|
PNet_i23d | | | 67.70 322 | 65.07 323 | 75.60 334 | 78.61 348 | 59.61 353 | 89.14 343 | 88.24 351 | 61.83 344 | 52.37 348 | 80.89 343 | 18.91 356 | 84.91 349 | 62.70 346 | 52.93 345 | 82.28 345 |
|
E-PMN | | | 64.94 324 | 64.25 324 | 67.02 338 | 82.28 344 | 59.36 354 | 91.83 341 | 85.63 353 | 52.69 348 | 60.22 346 | 77.28 347 | 41.06 350 | 80.12 352 | 46.15 350 | 41.14 347 | 61.57 351 |
|
EMVS | | | 64.07 325 | 63.26 326 | 66.53 339 | 81.73 345 | 58.81 355 | 91.85 340 | 84.75 354 | 51.93 350 | 59.09 347 | 75.13 348 | 43.32 349 | 79.09 353 | 42.03 351 | 39.47 348 | 61.69 350 |
|
PMVS | | 61.03 23 | 65.95 323 | 63.57 325 | 73.09 337 | 57.90 355 | 51.22 356 | 85.05 347 | 93.93 343 | 54.45 347 | 44.32 351 | 83.57 340 | 13.22 357 | 89.15 346 | 58.68 348 | 81.00 324 | 78.91 348 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
wuyk23d | | | 30.17 329 | 30.18 331 | 30.16 342 | 78.61 348 | 43.29 357 | 66.79 350 | 14.21 358 | 17.31 352 | 14.82 355 | 11.93 356 | 11.55 359 | 41.43 355 | 37.08 352 | 19.30 352 | 5.76 355 |
|
test123 | | | 20.95 332 | 23.72 333 | 12.64 343 | 13.54 358 | 8.19 358 | 96.55 308 | 6.13 360 | 7.48 354 | 16.74 354 | 37.98 353 | 12.97 358 | 6.05 356 | 16.69 353 | 5.43 355 | 23.68 352 |
|
testmvs | | | 21.48 331 | 24.95 332 | 11.09 344 | 14.89 357 | 6.47 359 | 96.56 306 | 9.87 359 | 7.55 353 | 17.93 353 | 39.02 352 | 9.43 362 | 5.90 357 | 16.56 354 | 12.72 353 | 20.91 353 |
|
cdsmvs_eth3d_5k | | | 23.98 330 | 31.98 330 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 98.59 115 | 0.00 355 | 0.00 356 | 98.61 102 | 90.60 125 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
pcd_1.5k_mvsjas | | | 7.88 334 | 10.50 335 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 94.51 62 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
pcd1.5k->3k | | | 39.42 328 | 41.78 329 | 32.35 341 | 96.17 277 | 0.00 360 | 0.00 351 | 98.54 125 | 0.00 355 | 0.00 356 | 0.00 357 | 87.78 196 | 0.00 358 | 0.00 355 | 93.56 226 | 97.06 209 |
|
sosnet-low-res | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
sosnet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
uncertanet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
Regformer | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
ab-mvs-re | | | 8.20 333 | 10.94 334 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 98.43 117 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
uanet | | | 0.00 335 | 0.00 336 | 0.00 345 | 0.00 359 | 0.00 360 | 0.00 351 | 0.00 361 | 0.00 355 | 0.00 356 | 0.00 357 | 0.00 363 | 0.00 358 | 0.00 355 | 0.00 356 | 0.00 356 |
|
GSMVS | | | | | | | | | | | | | | | | | 99.20 106 |
|
test_part3 | | | | | | | | 98.55 152 | | 96.40 57 | | 99.31 21 | | 99.93 9 | 96.37 95 | | |
|
test_part1 | | | | | | | | | 98.84 54 | | | | 97.38 2 | | | 99.78 14 | 99.76 20 |
|
sam_mvs1 | | | | | | | | | | | | | 89.45 136 | | | | 99.20 106 |
|
sam_mvs | | | | | | | | | | | | | 88.99 147 | | | | |
|
MTGPA | | | | | | | | | 98.74 79 | | | | | | | | |
|
test_post1 | | | | | | | | 96.68 302 | | | | 30.43 355 | 87.85 194 | 98.69 209 | 92.59 199 | | |
|
test_post | | | | | | | | | | | | 31.83 354 | 88.83 159 | 98.91 191 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 95.10 303 | 89.42 137 | 98.89 195 | | | |
|
MTMP | | | | | | | | | 94.14 341 | | | | | | | | |
|
test9_res | | | | | | | | | | | | | | | 96.39 94 | 99.57 57 | 99.69 37 |
|
agg_prior2 | | | | | | | | | | | | | | | 95.87 108 | 99.57 57 | 99.68 43 |
|
test_prior2 | | | | | | | | 97.80 241 | | 96.12 65 | 97.89 77 | 98.69 94 | 95.96 27 | | 96.89 71 | 99.60 51 | |
|
旧先验2 | | | | | | | | 97.57 258 | | 91.30 258 | 98.67 38 | | | 99.80 59 | 95.70 117 | | |
|
新几何2 | | | | | | | | 97.64 253 | | | | | | | | | |
|
无先验 | | | | | | | | 97.58 257 | 98.72 86 | 91.38 252 | | | | 99.87 37 | 93.36 174 | | 99.60 61 |
|
原ACMM2 | | | | | | | | 97.67 251 | | | | | | | | | |
|
testdata2 | | | | | | | | | | | | | | 99.89 29 | 91.65 224 | | |
|
segment_acmp | | | | | | | | | | | | | 96.85 5 | | | | |
|
testdata1 | | | | | | | | 97.32 275 | | 96.34 59 | | | | | | | |
|
plane_prior5 | | | | | | | | | 98.56 122 | | | | | 99.03 177 | 96.07 99 | 94.27 206 | 96.92 218 |
|
plane_prior4 | | | | | | | | | | | | 98.28 133 | | | | | |
|
plane_prior2 | | | | | | | | 98.80 102 | | 97.28 21 | | | | | | | |
|
plane_prior1 | | | | | | 97.37 200 | | | | | | | | | | | |
|
n2 | | | | | | | | | 0.00 361 | | | | | | | | |
|
nn | | | | | | | | | 0.00 361 | | | | | | | | |
|
door-mid | | | | | | | | | 94.37 338 | | | | | | | | |
|
test11 | | | | | | | | | 98.66 107 | | | | | | | | |
|
door | | | | | | | | | 94.64 337 | | | | | | | | |
|
HQP-NCC | | | | | | 97.20 210 | | 98.05 213 | | 96.43 54 | 94.45 187 | | | | | | |
|
ACMP_Plane | | | | | | 97.20 210 | | 98.05 213 | | 96.43 54 | 94.45 187 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 95.30 127 | | |
|
HQP4-MVS | | | | | | | | | | | 94.45 187 | | | 98.96 184 | | | 96.87 229 |
|
HQP3-MVS | | | | | | | | | 98.46 142 | | | | | | | 94.18 210 | |
|
HQP2-MVS | | | | | | | | | | | | | 86.75 215 | | | | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 92.97 237 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 93.61 225 | |
|
Test By Simon | | | | | | | | | | | | | 94.64 59 | | | | |
|