HPM-MVS++ | | | 97.34 7 | 96.97 11 | 98.47 1 | 99.08 25 | 96.16 1 | 97.55 70 | 97.97 75 | 95.59 4 | 96.61 33 | 97.89 49 | 92.57 17 | 99.84 12 | 95.95 31 | 99.51 17 | 99.40 33 |
|
CNVR-MVS | | | 97.68 2 | 97.44 5 | 98.37 2 | 98.90 30 | 95.86 2 | 97.27 91 | 98.08 47 | 95.81 3 | 97.87 9 | 98.31 31 | 94.26 2 | 99.68 33 | 97.02 3 | 99.49 21 | 99.57 11 |
|
ACMMP_Plus | | | 97.20 9 | 96.86 16 | 98.23 3 | 99.09 24 | 95.16 6 | 97.60 66 | 98.19 31 | 92.82 76 | 97.93 8 | 98.74 3 | 91.60 36 | 99.86 6 | 96.26 19 | 99.52 15 | 99.67 2 |
|
MCST-MVS | | | 97.18 10 | 96.84 17 | 98.20 4 | 99.30 16 | 95.35 3 | 97.12 107 | 98.07 52 | 93.54 51 | 96.08 51 | 97.69 65 | 93.86 5 | 99.71 26 | 96.50 16 | 99.39 32 | 99.55 15 |
|
3Dnovator+ | | 91.43 4 | 95.40 58 | 94.48 75 | 98.16 5 | 96.90 113 | 95.34 4 | 98.48 14 | 97.87 80 | 94.65 27 | 88.53 213 | 98.02 45 | 83.69 125 | 99.71 26 | 93.18 88 | 98.96 63 | 99.44 30 |
|
NCCC | | | 97.30 8 | 97.03 9 | 98.11 6 | 98.77 33 | 95.06 8 | 97.34 85 | 98.04 61 | 95.96 2 | 97.09 25 | 97.88 51 | 93.18 9 | 99.71 26 | 95.84 34 | 99.17 49 | 99.56 13 |
|
APDe-MVS | | | 97.82 1 | 97.73 1 | 98.08 7 | 99.15 23 | 94.82 10 | 98.81 2 | 98.30 22 | 94.76 23 | 98.30 4 | 98.90 1 | 93.77 6 | 99.68 33 | 97.93 1 | 99.69 1 | 99.75 1 |
|
APD-MVS | | | 96.95 22 | 96.60 27 | 98.01 8 | 99.03 27 | 94.93 9 | 97.72 54 | 98.10 44 | 91.50 100 | 98.01 6 | 98.32 30 | 92.33 21 | 99.58 53 | 94.85 57 | 99.51 17 | 99.53 20 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
MP-MVS-pluss | | | 96.70 31 | 96.27 38 | 97.98 9 | 99.23 21 | 94.71 11 | 96.96 116 | 98.06 54 | 90.67 122 | 95.55 71 | 98.78 2 | 91.07 42 | 99.86 6 | 96.58 14 | 99.55 12 | 99.38 37 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
MPTG | | | 97.07 16 | 96.77 23 | 97.97 10 | 99.37 10 | 94.42 15 | 97.15 105 | 98.08 47 | 95.07 13 | 96.11 49 | 98.59 5 | 90.88 47 | 99.90 1 | 96.18 26 | 99.50 19 | 99.58 9 |
|
MTAPA | | | 97.08 15 | 96.78 22 | 97.97 10 | 99.37 10 | 94.42 15 | 97.24 93 | 98.08 47 | 95.07 13 | 96.11 49 | 98.59 5 | 90.88 47 | 99.90 1 | 96.18 26 | 99.50 19 | 99.58 9 |
|
SteuartSystems-ACMMP | | | 97.62 3 | 97.53 2 | 97.87 12 | 98.39 57 | 94.25 19 | 98.43 16 | 98.27 24 | 95.34 8 | 98.11 5 | 98.56 7 | 94.53 1 | 99.71 26 | 96.57 15 | 99.62 5 | 99.65 3 |
Skip Steuart: Steuart Systems R&D Blog. |
HFP-MVS | | | 97.14 13 | 96.92 14 | 97.83 13 | 99.42 3 | 94.12 24 | 98.52 10 | 98.32 19 | 93.21 58 | 97.18 18 | 98.29 34 | 92.08 26 | 99.83 13 | 95.63 38 | 99.59 7 | 99.54 17 |
|
#test# | | | 97.02 19 | 96.75 24 | 97.83 13 | 99.42 3 | 94.12 24 | 98.15 29 | 98.32 19 | 92.57 81 | 97.18 18 | 98.29 34 | 92.08 26 | 99.83 13 | 95.12 48 | 99.59 7 | 99.54 17 |
|
XVS | | | 97.18 10 | 96.96 12 | 97.81 15 | 99.38 8 | 94.03 28 | 98.59 7 | 98.20 29 | 94.85 16 | 96.59 35 | 98.29 34 | 91.70 34 | 99.80 17 | 95.66 36 | 99.40 30 | 99.62 5 |
|
X-MVStestdata | | | 91.71 160 | 89.67 213 | 97.81 15 | 99.38 8 | 94.03 28 | 98.59 7 | 98.20 29 | 94.85 16 | 96.59 35 | 32.69 329 | 91.70 34 | 99.80 17 | 95.66 36 | 99.40 30 | 99.62 5 |
|
ACMMPR | | | 97.07 16 | 96.84 17 | 97.79 17 | 99.44 2 | 93.88 30 | 98.52 10 | 98.31 21 | 93.21 58 | 97.15 20 | 98.33 28 | 91.35 39 | 99.86 6 | 95.63 38 | 99.59 7 | 99.62 5 |
|
alignmvs | | | 95.87 54 | 95.23 57 | 97.78 18 | 97.56 97 | 95.19 5 | 97.86 41 | 97.17 148 | 94.39 31 | 96.47 40 | 96.40 131 | 85.89 102 | 99.20 96 | 96.21 24 | 95.11 143 | 98.95 70 |
|
DeepC-MVS_fast | | 93.89 2 | 96.93 24 | 96.64 26 | 97.78 18 | 98.64 44 | 94.30 17 | 97.41 79 | 98.04 61 | 94.81 21 | 96.59 35 | 98.37 21 | 91.24 40 | 99.64 42 | 95.16 46 | 99.52 15 | 99.42 32 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
region2R | | | 97.07 16 | 96.84 17 | 97.77 20 | 99.46 1 | 93.79 34 | 98.52 10 | 98.24 26 | 93.19 61 | 97.14 21 | 98.34 25 | 91.59 37 | 99.87 5 | 95.46 43 | 99.59 7 | 99.64 4 |
|
CDPH-MVS | | | 95.97 51 | 95.38 53 | 97.77 20 | 98.93 29 | 94.44 14 | 96.35 178 | 97.88 78 | 86.98 223 | 96.65 32 | 97.89 49 | 91.99 30 | 99.47 76 | 92.26 94 | 99.46 23 | 99.39 34 |
|
canonicalmvs | | | 96.02 50 | 95.45 51 | 97.75 22 | 97.59 95 | 95.15 7 | 98.28 22 | 97.60 104 | 94.52 28 | 96.27 45 | 96.12 141 | 87.65 81 | 99.18 99 | 96.20 25 | 94.82 147 | 98.91 74 |
|
train_agg | | | 96.30 42 | 95.83 46 | 97.72 23 | 98.70 36 | 94.19 21 | 96.41 170 | 98.02 64 | 88.58 181 | 96.03 52 | 97.56 80 | 92.73 13 | 99.59 49 | 95.04 50 | 99.37 37 | 99.39 34 |
|
MP-MVS | | | 96.77 29 | 96.45 34 | 97.72 23 | 99.39 7 | 93.80 33 | 98.41 17 | 98.06 54 | 93.37 53 | 95.54 72 | 98.34 25 | 90.59 50 | 99.88 3 | 94.83 58 | 99.54 13 | 99.49 24 |
|
PHI-MVS | | | 96.77 29 | 96.46 33 | 97.71 25 | 98.40 55 | 94.07 26 | 98.21 28 | 98.45 15 | 89.86 140 | 97.11 24 | 98.01 46 | 92.52 19 | 99.69 31 | 96.03 30 | 99.53 14 | 99.36 39 |
|
TSAR-MVS + MP. | | | 97.42 5 | 97.33 6 | 97.69 26 | 99.25 18 | 94.24 20 | 98.07 34 | 97.85 84 | 93.72 45 | 98.57 2 | 98.35 22 | 93.69 7 | 99.40 85 | 97.06 2 | 99.46 23 | 99.44 30 |
|
Regformer-2 | | | 97.16 12 | 96.99 10 | 97.67 27 | 98.32 63 | 93.84 32 | 96.83 129 | 98.10 44 | 95.24 9 | 97.49 11 | 98.25 37 | 92.57 17 | 99.61 44 | 96.80 7 | 99.29 41 | 99.56 13 |
|
PGM-MVS | | | 96.81 27 | 96.53 30 | 97.65 28 | 99.35 13 | 93.53 42 | 97.65 60 | 98.98 1 | 92.22 86 | 97.14 21 | 98.44 14 | 91.17 41 | 99.85 9 | 94.35 65 | 99.46 23 | 99.57 11 |
|
test12 | | | | | 97.65 28 | 98.46 51 | 94.26 18 | | 97.66 99 | | 95.52 73 | | 90.89 46 | 99.46 77 | | 99.25 44 | 99.22 47 |
|
mPP-MVS | | | 96.86 25 | 96.60 27 | 97.64 30 | 99.40 5 | 93.44 44 | 98.50 13 | 98.09 46 | 93.27 57 | 95.95 58 | 98.33 28 | 91.04 43 | 99.88 3 | 95.20 45 | 99.57 11 | 99.60 8 |
|
CP-MVS | | | 97.02 19 | 96.81 20 | 97.64 30 | 99.33 14 | 93.54 41 | 98.80 3 | 98.28 23 | 92.99 67 | 96.45 42 | 98.30 33 | 91.90 31 | 99.85 9 | 95.61 40 | 99.68 2 | 99.54 17 |
|
HSP-MVS | | | 97.53 4 | 97.49 4 | 97.63 32 | 99.40 5 | 93.77 37 | 98.53 9 | 97.85 84 | 95.55 5 | 98.56 3 | 97.81 58 | 93.90 4 | 99.65 37 | 96.62 12 | 99.21 47 | 99.48 26 |
|
agg_prior3 | | | 96.16 47 | 95.67 48 | 97.62 33 | 98.67 38 | 93.88 30 | 96.41 170 | 98.00 68 | 87.93 200 | 95.81 62 | 97.47 84 | 92.33 21 | 99.59 49 | 95.04 50 | 99.37 37 | 99.39 34 |
|
agg_prior1 | | | 96.22 45 | 95.77 47 | 97.56 34 | 98.67 38 | 93.79 34 | 96.28 186 | 98.00 68 | 88.76 178 | 95.68 66 | 97.55 82 | 92.70 15 | 99.57 61 | 95.01 52 | 99.32 39 | 99.32 41 |
|
Regformer-1 | | | 97.10 14 | 96.96 12 | 97.54 35 | 98.32 63 | 93.48 43 | 96.83 129 | 97.99 73 | 95.20 11 | 97.46 12 | 98.25 37 | 92.48 20 | 99.58 53 | 96.79 9 | 99.29 41 | 99.55 15 |
|
3Dnovator | | 91.36 5 | 95.19 66 | 94.44 77 | 97.44 36 | 96.56 127 | 93.36 47 | 98.65 6 | 98.36 16 | 94.12 36 | 89.25 203 | 98.06 43 | 82.20 171 | 99.77 19 | 93.41 85 | 99.32 39 | 99.18 49 |
|
HPM-MVS | | | 96.69 32 | 96.45 34 | 97.40 37 | 99.36 12 | 93.11 51 | 98.87 1 | 98.06 54 | 91.17 111 | 96.40 43 | 97.99 47 | 90.99 44 | 99.58 53 | 95.61 40 | 99.61 6 | 99.49 24 |
|
DP-MVS Recon | | | 95.68 55 | 95.12 60 | 97.37 38 | 99.19 22 | 94.19 21 | 97.03 110 | 98.08 47 | 88.35 189 | 95.09 77 | 97.65 69 | 89.97 57 | 99.48 75 | 92.08 103 | 98.59 72 | 98.44 106 |
|
MVS_0305 | | | 96.22 45 | 95.84 45 | 97.36 39 | 97.72 89 | 93.01 53 | 96.93 123 | 97.86 82 | 95.55 5 | 94.80 80 | 97.78 60 | 86.05 101 | 99.83 13 | 96.71 11 | 99.16 50 | 99.25 46 |
|
1121 | | | 94.71 79 | 93.83 82 | 97.34 40 | 98.57 49 | 93.64 39 | 96.04 201 | 97.73 90 | 81.56 285 | 95.68 66 | 97.85 55 | 90.23 53 | 99.65 37 | 87.68 179 | 99.12 56 | 98.73 84 |
|
æ–°å‡ ä½•1 | | | | | 97.32 41 | 98.60 45 | 93.59 40 | | 97.75 88 | 81.58 283 | 95.75 65 | 97.85 55 | 90.04 56 | 99.67 35 | 86.50 202 | 99.13 53 | 98.69 88 |
|
DELS-MVS | | | 96.61 35 | 96.38 36 | 97.30 42 | 97.79 87 | 93.19 49 | 95.96 206 | 98.18 33 | 95.23 10 | 95.87 59 | 97.65 69 | 91.45 38 | 99.70 30 | 95.87 32 | 99.44 27 | 99.00 66 |
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 |
DeepC-MVS | | 93.07 3 | 96.06 48 | 95.66 49 | 97.29 43 | 97.96 81 | 93.17 50 | 97.30 90 | 98.06 54 | 93.92 40 | 93.38 101 | 98.66 4 | 86.83 91 | 99.73 22 | 95.60 42 | 99.22 46 | 98.96 68 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
ACMMP | | | 96.27 43 | 95.93 43 | 97.28 44 | 99.24 19 | 92.62 64 | 98.25 25 | 98.81 3 | 92.99 67 | 94.56 83 | 98.39 20 | 88.96 63 | 99.85 9 | 94.57 64 | 97.63 93 | 99.36 39 |
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 |
TSAR-MVS + GP. | | | 96.69 32 | 96.49 31 | 97.27 45 | 98.31 65 | 93.39 45 | 96.79 136 | 96.72 193 | 94.17 35 | 97.44 13 | 97.66 68 | 92.76 11 | 99.33 90 | 96.86 6 | 97.76 92 | 99.08 59 |
|
Regformer-4 | | | 96.97 21 | 96.87 15 | 97.25 46 | 98.34 60 | 92.66 63 | 96.96 116 | 98.01 66 | 95.12 12 | 97.14 21 | 98.42 16 | 91.82 32 | 99.61 44 | 96.90 5 | 99.13 53 | 99.50 22 |
|
test_prior3 | | | 96.46 39 | 96.20 41 | 97.23 47 | 98.67 38 | 92.99 54 | 96.35 178 | 98.00 68 | 92.80 77 | 96.03 52 | 97.59 76 | 92.01 28 | 99.41 83 | 95.01 52 | 99.38 33 | 99.29 43 |
|
test_prior | | | | | 97.23 47 | 98.67 38 | 92.99 54 | | 98.00 68 | | | | | 99.41 83 | | | 99.29 43 |
|
HPM-MVS_fast | | | 96.51 37 | 96.27 38 | 97.22 49 | 99.32 15 | 92.74 60 | 98.74 4 | 98.06 54 | 90.57 131 | 96.77 28 | 98.35 22 | 90.21 54 | 99.53 68 | 94.80 60 | 99.63 4 | 99.38 37 |
|
VNet | | | 95.89 53 | 95.45 51 | 97.21 50 | 98.07 79 | 92.94 57 | 97.50 73 | 98.15 35 | 93.87 41 | 97.52 10 | 97.61 75 | 85.29 108 | 99.53 68 | 95.81 35 | 95.27 141 | 99.16 50 |
|
UA-Net | | | 95.95 52 | 95.53 50 | 97.20 51 | 97.67 91 | 92.98 56 | 97.65 60 | 98.13 38 | 94.81 21 | 96.61 33 | 98.35 22 | 88.87 64 | 99.51 72 | 90.36 131 | 97.35 103 | 99.11 57 |
|
EPNet | | | 95.20 65 | 94.56 70 | 97.14 52 | 92.80 283 | 92.68 62 | 97.85 43 | 94.87 276 | 96.64 1 | 92.46 114 | 97.80 59 | 86.23 96 | 99.65 37 | 93.72 77 | 98.62 71 | 99.10 58 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
APD-MVS_3200maxsize | | | 96.81 27 | 96.71 25 | 97.12 53 | 99.01 28 | 92.31 70 | 97.98 36 | 98.06 54 | 93.11 64 | 97.44 13 | 98.55 9 | 90.93 45 | 99.55 63 | 96.06 28 | 99.25 44 | 99.51 21 |
|
SD-MVS | | | 97.41 6 | 97.53 2 | 97.06 54 | 98.57 49 | 94.46 13 | 97.92 38 | 98.14 37 | 94.82 20 | 99.01 1 | 98.55 9 | 94.18 3 | 97.41 255 | 96.94 4 | 99.64 3 | 99.32 41 |
|
Regformer-3 | | | 96.85 26 | 96.80 21 | 97.01 55 | 98.34 60 | 92.02 80 | 96.96 116 | 97.76 87 | 95.01 15 | 97.08 26 | 98.42 16 | 91.71 33 | 99.54 65 | 96.80 7 | 99.13 53 | 99.48 26 |
|
MVS_111021_HR | | | 96.68 34 | 96.58 29 | 96.99 56 | 98.46 51 | 92.31 70 | 96.20 194 | 98.90 2 | 94.30 33 | 95.86 60 | 97.74 63 | 92.33 21 | 99.38 88 | 96.04 29 | 99.42 28 | 99.28 45 |
|
abl_6 | | | 96.40 40 | 96.21 40 | 96.98 57 | 98.89 31 | 92.20 75 | 97.89 39 | 98.03 63 | 93.34 56 | 97.22 17 | 98.42 16 | 87.93 77 | 99.72 25 | 95.10 49 | 99.07 58 | 99.02 61 |
|
QAPM | | | 93.45 113 | 92.27 131 | 96.98 57 | 96.77 119 | 92.62 64 | 98.39 18 | 98.12 39 | 84.50 258 | 88.27 219 | 97.77 61 | 82.39 167 | 99.81 16 | 85.40 221 | 98.81 66 | 98.51 97 |
|
WTY-MVS | | | 94.71 79 | 94.02 79 | 96.79 59 | 97.71 90 | 92.05 78 | 96.59 161 | 97.35 138 | 90.61 128 | 94.64 82 | 96.93 100 | 86.41 95 | 99.39 86 | 91.20 125 | 94.71 151 | 98.94 71 |
|
CPTT-MVS | | | 95.57 57 | 95.19 58 | 96.70 60 | 99.27 17 | 91.48 95 | 98.33 20 | 98.11 42 | 87.79 203 | 95.17 76 | 98.03 44 | 87.09 89 | 99.61 44 | 93.51 80 | 99.42 28 | 99.02 61 |
|
sss | | | 94.51 81 | 93.80 83 | 96.64 61 | 97.07 107 | 91.97 83 | 96.32 182 | 98.06 54 | 88.94 169 | 94.50 84 | 96.78 104 | 84.60 117 | 99.27 93 | 91.90 106 | 96.02 129 | 98.68 89 |
|
ab-mvs | | | 93.57 110 | 92.55 123 | 96.64 61 | 97.28 100 | 91.96 84 | 95.40 231 | 97.45 124 | 89.81 144 | 93.22 102 | 96.28 135 | 79.62 214 | 99.46 77 | 90.74 126 | 93.11 162 | 98.50 99 |
|
EI-MVSNet-Vis-set | | | 96.51 37 | 96.47 32 | 96.63 63 | 98.24 69 | 91.20 105 | 96.89 126 | 97.73 90 | 94.74 24 | 96.49 39 | 98.49 11 | 90.88 47 | 99.58 53 | 96.44 17 | 98.32 76 | 99.13 54 |
|
114514_t | | | 93.95 97 | 93.06 106 | 96.63 63 | 99.07 26 | 91.61 91 | 97.46 78 | 97.96 76 | 77.99 301 | 93.00 105 | 97.57 78 | 86.14 100 | 99.33 90 | 89.22 148 | 99.15 51 | 98.94 71 |
|
HY-MVS | | 89.66 9 | 93.87 99 | 92.95 108 | 96.63 63 | 97.10 106 | 92.49 68 | 95.64 221 | 96.64 200 | 89.05 164 | 93.00 105 | 95.79 158 | 85.77 105 | 99.45 79 | 89.16 151 | 94.35 152 | 97.96 124 |
|
MSLP-MVS++ | | | 96.94 23 | 97.06 8 | 96.59 66 | 98.72 35 | 91.86 86 | 97.67 57 | 98.49 12 | 94.66 26 | 97.24 16 | 98.41 19 | 92.31 24 | 98.94 114 | 96.61 13 | 99.46 23 | 98.96 68 |
|
MVS_dtu | | | 94.12 89 | 93.32 100 | 96.52 67 | 95.99 156 | 92.02 80 | 96.24 192 | 96.49 205 | 94.28 34 | 92.95 110 | 97.02 99 | 79.10 220 | 99.64 42 | 90.61 128 | 97.17 107 | 97.90 127 |
|
LFMVS | | | 93.60 108 | 92.63 119 | 96.52 67 | 98.13 77 | 91.27 102 | 97.94 37 | 93.39 301 | 90.57 131 | 96.29 44 | 98.31 31 | 69.00 283 | 99.16 101 | 94.18 66 | 95.87 133 | 99.12 56 |
|
DP-MVS | | | 92.76 137 | 91.51 150 | 96.52 67 | 98.77 33 | 90.99 112 | 97.38 83 | 96.08 221 | 82.38 276 | 89.29 200 | 97.87 52 | 83.77 124 | 99.69 31 | 81.37 267 | 96.69 120 | 98.89 77 |
|
CNLPA | | | 94.28 83 | 93.53 91 | 96.52 67 | 98.38 58 | 92.55 66 | 96.59 161 | 96.88 187 | 90.13 136 | 91.91 128 | 97.24 90 | 85.21 109 | 99.09 109 | 87.64 182 | 97.83 87 | 97.92 126 |
|
Vis-MVSNet | | | 95.23 63 | 94.81 63 | 96.51 71 | 97.18 103 | 91.58 94 | 98.26 24 | 98.12 39 | 94.38 32 | 94.90 78 | 98.15 39 | 82.28 168 | 98.92 115 | 91.45 120 | 98.58 73 | 99.01 65 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MAR-MVS | | | 94.22 84 | 93.46 94 | 96.51 71 | 98.00 80 | 92.19 76 | 97.67 57 | 97.47 118 | 88.13 198 | 93.00 105 | 95.84 152 | 84.86 115 | 99.51 72 | 87.99 171 | 98.17 80 | 97.83 133 |
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 |
PAPR | | | 94.18 85 | 93.42 98 | 96.48 73 | 97.64 93 | 91.42 99 | 95.55 224 | 97.71 96 | 88.99 166 | 92.34 119 | 95.82 154 | 89.19 60 | 99.11 106 | 86.14 207 | 97.38 101 | 98.90 75 |
|
EI-MVSNet-UG-set | | | 96.34 41 | 96.30 37 | 96.47 74 | 98.20 73 | 90.93 116 | 96.86 127 | 97.72 93 | 94.67 25 | 96.16 48 | 98.46 12 | 90.43 51 | 99.58 53 | 96.23 20 | 97.96 85 | 98.90 75 |
|
LS3D | | | 93.57 110 | 92.61 121 | 96.47 74 | 97.59 95 | 91.61 91 | 97.67 57 | 97.72 93 | 85.17 248 | 90.29 158 | 98.34 25 | 84.60 117 | 99.73 22 | 83.85 247 | 98.27 77 | 98.06 123 |
|
CSCG | | | 96.05 49 | 95.91 44 | 96.46 76 | 99.24 19 | 90.47 128 | 98.30 21 | 98.57 11 | 89.01 165 | 93.97 94 | 97.57 78 | 92.62 16 | 99.76 20 | 94.66 63 | 99.27 43 | 99.15 52 |
|
MVS_test0326 | | | 94.10 91 | 93.32 100 | 96.44 77 | 96.14 150 | 91.94 85 | 96.26 187 | 97.05 164 | 94.12 36 | 92.25 121 | 96.47 127 | 79.44 216 | 99.59 49 | 90.37 130 | 97.82 88 | 97.80 134 |
|
OpenMVS | | 89.19 12 | 92.86 133 | 91.68 146 | 96.40 78 | 95.34 177 | 92.73 61 | 98.27 23 | 98.12 39 | 84.86 253 | 85.78 251 | 97.75 62 | 78.89 228 | 99.74 21 | 87.50 186 | 98.65 70 | 96.73 162 |
|
MVS_111021_LR | | | 96.24 44 | 96.19 42 | 96.39 79 | 98.23 72 | 91.35 100 | 96.24 192 | 98.79 4 | 93.99 39 | 95.80 63 | 97.65 69 | 89.92 58 | 99.24 95 | 95.87 32 | 99.20 48 | 98.58 91 |
|
原ACMM1 | | | | | 96.38 80 | 98.59 46 | 91.09 111 | | 97.89 77 | 87.41 212 | 95.22 75 | 97.68 66 | 90.25 52 | 99.54 65 | 87.95 172 | 99.12 56 | 98.49 101 |
|
PVSNet_Blended_VisFu | | | 95.27 62 | 94.91 62 | 96.38 80 | 98.20 73 | 90.86 118 | 97.27 91 | 98.25 25 | 90.21 134 | 94.18 90 | 97.27 88 | 87.48 85 | 99.73 22 | 93.53 79 | 97.77 91 | 98.55 92 |
|
Effi-MVS+ | | | 94.93 73 | 94.45 76 | 96.36 82 | 96.61 122 | 91.47 96 | 96.41 170 | 97.41 131 | 91.02 116 | 94.50 84 | 95.92 148 | 87.53 84 | 98.78 127 | 93.89 73 | 96.81 115 | 98.84 81 |
|
PCF-MVS | | 89.48 11 | 91.56 172 | 89.95 202 | 96.36 82 | 96.60 123 | 92.52 67 | 92.51 287 | 97.26 143 | 79.41 294 | 88.90 205 | 96.56 123 | 84.04 122 | 99.55 63 | 77.01 287 | 97.30 104 | 97.01 154 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
UGNet | | | 94.04 95 | 93.28 103 | 96.31 84 | 96.85 114 | 91.19 106 | 97.88 40 | 97.68 98 | 94.40 30 | 93.00 105 | 96.18 138 | 73.39 266 | 99.61 44 | 91.72 111 | 98.46 74 | 98.13 118 |
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 |
MG-MVS | | | 95.61 56 | 95.38 53 | 96.31 84 | 98.42 54 | 90.53 126 | 96.04 201 | 97.48 115 | 93.47 52 | 95.67 69 | 98.10 40 | 89.17 61 | 99.25 94 | 91.27 123 | 98.77 67 | 99.13 54 |
|
AdaColmap | | | 94.34 82 | 93.68 87 | 96.31 84 | 98.59 46 | 91.68 90 | 96.59 161 | 97.81 86 | 89.87 139 | 92.15 124 | 97.06 98 | 83.62 126 | 99.54 65 | 89.34 144 | 98.07 82 | 97.70 138 |
|
lupinMVS | | | 94.99 72 | 94.56 70 | 96.29 87 | 96.34 138 | 91.21 103 | 95.83 212 | 96.27 212 | 88.93 170 | 96.22 46 | 96.88 102 | 86.20 98 | 98.85 122 | 95.27 44 | 99.05 59 | 98.82 82 |
|
nrg030 | | | 94.05 94 | 93.31 102 | 96.27 88 | 95.22 187 | 94.59 12 | 98.34 19 | 97.46 120 | 92.93 74 | 91.21 146 | 96.64 114 | 87.23 88 | 98.22 165 | 94.99 55 | 85.80 239 | 95.98 180 |
|
PAPM_NR | | | 95.01 68 | 94.59 69 | 96.26 89 | 98.89 31 | 90.68 123 | 97.24 93 | 97.73 90 | 91.80 94 | 92.93 111 | 96.62 121 | 89.13 62 | 99.14 104 | 89.21 149 | 97.78 90 | 98.97 67 |
|
OMC-MVS | | | 95.09 67 | 94.70 67 | 96.25 90 | 98.46 51 | 91.28 101 | 96.43 168 | 97.57 107 | 92.04 89 | 94.77 81 | 97.96 48 | 87.01 90 | 99.09 109 | 91.31 122 | 96.77 116 | 98.36 113 |
|
1112_ss | | | 93.37 115 | 92.42 129 | 96.21 91 | 97.05 110 | 90.99 112 | 96.31 183 | 96.72 193 | 86.87 229 | 89.83 178 | 96.69 111 | 86.51 94 | 99.14 104 | 88.12 168 | 93.67 156 | 98.50 99 |
|
jason | | | 94.84 77 | 94.39 78 | 96.18 92 | 95.52 169 | 90.93 116 | 96.09 198 | 96.52 204 | 89.28 152 | 96.01 56 | 97.32 86 | 84.70 116 | 98.77 129 | 95.15 47 | 98.91 65 | 98.85 79 |
jason: jason. |
PLC | | 91.00 6 | 94.11 90 | 93.43 96 | 96.13 93 | 98.58 48 | 91.15 110 | 96.69 151 | 97.39 132 | 87.29 215 | 91.37 136 | 96.71 107 | 88.39 72 | 99.52 71 | 87.33 190 | 97.13 109 | 97.73 136 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
CHOSEN 1792x2688 | | | 94.15 86 | 93.51 92 | 96.06 94 | 98.27 66 | 89.38 157 | 95.18 241 | 98.48 14 | 85.60 243 | 93.76 96 | 97.11 96 | 83.15 132 | 99.61 44 | 91.33 121 | 98.72 69 | 99.19 48 |
|
IS-MVSNet | | | 94.90 74 | 94.52 73 | 96.05 95 | 97.67 91 | 90.56 125 | 98.44 15 | 96.22 216 | 93.21 58 | 93.99 92 | 97.74 63 | 85.55 106 | 98.45 152 | 89.98 132 | 97.86 86 | 99.14 53 |
|
VDD-MVS | | | 93.82 101 | 93.08 105 | 96.02 96 | 97.88 86 | 89.96 139 | 97.72 54 | 95.85 234 | 92.43 83 | 95.86 60 | 98.44 14 | 68.42 287 | 99.39 86 | 96.31 18 | 94.85 145 | 98.71 87 |
|
VDDNet | | | 93.05 125 | 92.07 133 | 96.02 96 | 96.84 115 | 90.39 130 | 98.08 33 | 95.85 234 | 86.22 237 | 95.79 64 | 98.46 12 | 67.59 290 | 99.19 97 | 94.92 56 | 94.85 145 | 98.47 104 |
|
MVSFormer | | | 95.37 59 | 95.16 59 | 95.99 98 | 96.34 138 | 91.21 103 | 98.22 26 | 97.57 107 | 91.42 104 | 96.22 46 | 97.32 86 | 86.20 98 | 97.92 216 | 94.07 67 | 99.05 59 | 98.85 79 |
|
CDS-MVSNet | | | 94.14 88 | 93.54 90 | 95.93 99 | 96.18 145 | 91.46 97 | 96.33 181 | 97.04 168 | 88.97 168 | 93.56 97 | 96.51 125 | 87.55 83 | 97.89 220 | 89.80 135 | 95.95 131 | 98.44 106 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
API-MVS | | | 94.84 77 | 94.49 74 | 95.90 100 | 97.90 85 | 92.00 82 | 97.80 46 | 97.48 115 | 89.19 155 | 94.81 79 | 96.71 107 | 88.84 65 | 99.17 100 | 88.91 157 | 98.76 68 | 96.53 165 |
|
HyFIR lowres test | | | 93.66 106 | 92.92 109 | 95.87 101 | 98.24 69 | 89.88 140 | 94.58 248 | 98.49 12 | 85.06 250 | 93.78 95 | 95.78 159 | 82.86 153 | 98.67 135 | 91.77 110 | 95.71 137 | 99.07 60 |
|
Test_1112_low_res | | | 92.84 135 | 91.84 141 | 95.85 102 | 97.04 111 | 89.97 137 | 95.53 226 | 96.64 200 | 85.38 244 | 89.65 188 | 95.18 184 | 85.86 103 | 99.10 107 | 87.70 177 | 93.58 161 | 98.49 101 |
|
PVSNet_Blended | | | 94.87 76 | 94.56 70 | 95.81 103 | 98.27 66 | 89.46 155 | 95.47 229 | 98.36 16 | 88.84 172 | 94.36 86 | 96.09 144 | 88.02 74 | 99.58 53 | 93.44 83 | 98.18 79 | 98.40 109 |
|
test_normal | | | 92.01 154 | 90.75 175 | 95.80 104 | 93.24 272 | 89.97 137 | 95.93 208 | 96.24 215 | 90.62 126 | 81.63 277 | 93.45 248 | 74.98 253 | 98.89 119 | 93.61 78 | 97.04 111 | 98.55 92 |
|
EPP-MVSNet | | | 95.22 64 | 95.04 61 | 95.76 105 | 97.49 98 | 89.56 149 | 98.67 5 | 97.00 172 | 90.69 121 | 94.24 89 | 97.62 74 | 89.79 59 | 98.81 125 | 93.39 86 | 96.49 124 | 98.92 73 |
|
xiu_mvs_v1_base_debu | | | 95.01 68 | 94.76 64 | 95.75 106 | 96.58 124 | 91.71 87 | 96.25 189 | 97.35 138 | 92.99 67 | 96.70 29 | 96.63 118 | 82.67 157 | 99.44 80 | 96.22 21 | 97.46 96 | 96.11 176 |
|
xiu_mvs_v1_base | | | 95.01 68 | 94.76 64 | 95.75 106 | 96.58 124 | 91.71 87 | 96.25 189 | 97.35 138 | 92.99 67 | 96.70 29 | 96.63 118 | 82.67 157 | 99.44 80 | 96.22 21 | 97.46 96 | 96.11 176 |
|
xiu_mvs_v1_base_debi | | | 95.01 68 | 94.76 64 | 95.75 106 | 96.58 124 | 91.71 87 | 96.25 189 | 97.35 138 | 92.99 67 | 96.70 29 | 96.63 118 | 82.67 157 | 99.44 80 | 96.22 21 | 97.46 96 | 96.11 176 |
|
DI_MVS_plusplus_test | | | 92.01 154 | 90.77 173 | 95.73 109 | 93.34 268 | 89.78 143 | 96.14 196 | 96.18 218 | 90.58 130 | 81.80 276 | 93.50 245 | 74.95 254 | 98.90 117 | 93.51 80 | 96.94 112 | 98.51 97 |
|
MVS_Test | | | 94.89 75 | 94.62 68 | 95.68 110 | 96.83 117 | 89.55 150 | 96.70 149 | 97.17 148 | 91.17 111 | 95.60 70 | 96.11 143 | 87.87 78 | 98.76 130 | 93.01 91 | 97.17 107 | 98.72 85 |
|
TAMVS | | | 94.01 96 | 93.46 94 | 95.64 111 | 96.16 147 | 90.45 129 | 96.71 146 | 96.89 186 | 89.27 153 | 93.46 100 | 96.92 101 | 87.29 87 | 97.94 212 | 88.70 163 | 95.74 135 | 98.53 94 |
|
UniMVSNet (Re) | | | 93.31 117 | 92.55 123 | 95.61 112 | 95.39 174 | 93.34 48 | 97.39 81 | 98.71 5 | 93.14 63 | 90.10 168 | 94.83 194 | 87.71 79 | 98.03 195 | 91.67 116 | 83.99 264 | 95.46 202 |
|
Fast-Effi-MVS+ | | | 93.46 112 | 92.75 114 | 95.59 113 | 96.77 119 | 90.03 131 | 96.81 133 | 97.13 154 | 88.19 194 | 91.30 141 | 94.27 223 | 86.21 97 | 98.63 137 | 87.66 181 | 96.46 126 | 98.12 119 |
|
PatchMatch-RL | | | 92.90 131 | 92.02 136 | 95.56 114 | 98.19 75 | 90.80 120 | 95.27 238 | 97.18 146 | 87.96 199 | 91.86 130 | 95.68 166 | 80.44 201 | 98.99 112 | 84.01 243 | 97.54 95 | 96.89 158 |
|
TAPA-MVS | | 90.10 7 | 92.30 146 | 91.22 159 | 95.56 114 | 98.33 62 | 89.60 147 | 96.79 136 | 97.65 101 | 81.83 280 | 91.52 133 | 97.23 91 | 87.94 76 | 98.91 116 | 71.31 301 | 98.37 75 | 98.17 117 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
NR-MVSNet | | | 92.34 143 | 91.27 156 | 95.53 116 | 94.95 200 | 93.05 52 | 97.39 81 | 98.07 52 | 92.65 80 | 84.46 259 | 95.71 163 | 85.00 112 | 97.77 231 | 89.71 137 | 83.52 272 | 95.78 189 |
|
MVS | | | 91.71 160 | 90.44 183 | 95.51 117 | 95.20 189 | 91.59 93 | 96.04 201 | 97.45 124 | 73.44 313 | 87.36 235 | 95.60 169 | 85.42 107 | 99.10 107 | 85.97 212 | 97.46 96 | 95.83 186 |
|
VPA-MVSNet | | | 93.24 119 | 92.48 128 | 95.51 117 | 95.70 165 | 92.39 69 | 97.86 41 | 98.66 9 | 92.30 85 | 92.09 126 | 95.37 177 | 80.49 200 | 98.40 154 | 93.95 70 | 85.86 238 | 95.75 193 |
|
PS-MVSNAJ | | | 95.37 59 | 95.33 55 | 95.49 119 | 97.35 99 | 90.66 124 | 95.31 235 | 97.48 115 | 93.85 42 | 96.51 38 | 95.70 165 | 88.65 68 | 99.65 37 | 94.80 60 | 98.27 77 | 96.17 171 |
|
DU-MVS | | | 92.90 131 | 92.04 134 | 95.49 119 | 94.95 200 | 92.83 58 | 97.16 104 | 98.24 26 | 93.02 66 | 90.13 164 | 95.71 163 | 83.47 127 | 97.85 222 | 91.71 112 | 83.93 265 | 95.78 189 |
|
diffmvs | | | 93.43 114 | 92.75 114 | 95.48 121 | 96.47 134 | 89.61 146 | 96.09 198 | 97.14 152 | 85.97 240 | 93.09 103 | 95.35 178 | 84.87 114 | 98.55 145 | 89.51 142 | 96.26 128 | 98.28 115 |
|
UniMVSNet_NR-MVSNet | | | 93.37 115 | 92.67 118 | 95.47 122 | 95.34 177 | 92.83 58 | 97.17 103 | 98.58 10 | 92.98 72 | 90.13 164 | 95.80 155 | 88.37 73 | 97.85 222 | 91.71 112 | 83.93 265 | 95.73 195 |
|
testdata | | | | | 95.46 123 | 98.18 76 | 88.90 168 | | 97.66 99 | 82.73 274 | 97.03 27 | 98.07 42 | 90.06 55 | 98.85 122 | 89.67 138 | 98.98 62 | 98.64 90 |
|
Test4 | | | 89.48 229 | 87.50 239 | 95.44 124 | 90.76 297 | 89.72 144 | 95.78 216 | 97.09 158 | 90.28 133 | 77.67 302 | 91.74 276 | 55.42 315 | 98.08 179 | 91.92 105 | 96.83 114 | 98.52 95 |
|
xiu_mvs_v2_base | | | 95.32 61 | 95.29 56 | 95.40 125 | 97.22 101 | 90.50 127 | 95.44 230 | 97.44 127 | 93.70 47 | 96.46 41 | 96.18 138 | 88.59 71 | 99.53 68 | 94.79 62 | 97.81 89 | 96.17 171 |
|
F-COLMAP | | | 93.58 109 | 92.98 107 | 95.37 126 | 98.40 55 | 88.98 166 | 97.18 102 | 97.29 142 | 87.75 205 | 90.49 153 | 97.10 97 | 85.21 109 | 99.50 74 | 86.70 199 | 96.72 119 | 97.63 139 |
|
FIs | | | 94.09 92 | 93.70 85 | 95.27 127 | 95.70 165 | 92.03 79 | 98.10 31 | 98.68 7 | 93.36 55 | 90.39 156 | 96.70 109 | 87.63 82 | 97.94 212 | 92.25 96 | 90.50 202 | 95.84 185 |
|
PAPM | | | 91.52 175 | 90.30 187 | 95.20 128 | 95.30 181 | 89.83 141 | 93.38 273 | 96.85 189 | 86.26 236 | 88.59 212 | 95.80 155 | 84.88 113 | 98.15 171 | 75.67 290 | 95.93 132 | 97.63 139 |
|
DeepPCF-MVS | | 93.97 1 | 96.61 35 | 97.09 7 | 95.15 129 | 98.09 78 | 86.63 232 | 96.00 205 | 98.15 35 | 95.43 7 | 97.95 7 | 98.56 7 | 93.40 8 | 99.36 89 | 96.77 10 | 99.48 22 | 99.45 28 |
|
1314 | | | 92.81 136 | 92.03 135 | 95.14 130 | 95.33 180 | 89.52 153 | 96.04 201 | 97.44 127 | 87.72 206 | 86.25 249 | 95.33 179 | 83.84 123 | 98.79 126 | 89.26 146 | 97.05 110 | 97.11 153 |
|
TranMVSNet+NR-MVSNet | | | 92.50 140 | 91.63 147 | 95.14 130 | 94.76 209 | 92.07 77 | 97.53 71 | 98.11 42 | 92.90 75 | 89.56 191 | 96.12 141 | 83.16 131 | 97.60 243 | 89.30 145 | 83.20 275 | 95.75 193 |
|
FC-MVSNet-test | | | 93.94 98 | 93.57 88 | 95.04 132 | 95.48 171 | 91.45 98 | 98.12 30 | 98.71 5 | 93.37 53 | 90.23 159 | 96.70 109 | 87.66 80 | 97.85 222 | 91.49 118 | 90.39 203 | 95.83 186 |
|
FMVSNet3 | | | 91.78 159 | 90.69 178 | 95.03 133 | 96.53 129 | 92.27 72 | 97.02 112 | 96.93 182 | 89.79 145 | 89.35 197 | 94.65 202 | 77.01 240 | 97.47 250 | 86.12 208 | 88.82 215 | 95.35 212 |
|
VPNet | | | 92.23 150 | 91.31 154 | 94.99 134 | 95.56 168 | 90.96 114 | 97.22 98 | 97.86 82 | 92.96 73 | 90.96 148 | 96.62 121 | 75.06 252 | 98.20 166 | 91.90 106 | 83.65 271 | 95.80 188 |
|
FMVSNet2 | | | 91.31 185 | 90.08 196 | 94.99 134 | 96.51 130 | 92.21 73 | 97.41 79 | 96.95 180 | 88.82 174 | 88.62 210 | 94.75 198 | 73.87 260 | 97.42 254 | 85.20 224 | 88.55 221 | 95.35 212 |
|
BH-RMVSNet | | | 92.72 138 | 91.97 138 | 94.97 136 | 97.16 104 | 87.99 199 | 96.15 195 | 95.60 242 | 90.62 126 | 91.87 129 | 97.15 95 | 78.41 233 | 98.57 143 | 83.16 252 | 97.60 94 | 98.36 113 |
|
MSDG | | | 91.42 179 | 90.24 191 | 94.96 137 | 97.15 105 | 88.91 167 | 93.69 267 | 96.32 210 | 85.72 242 | 86.93 244 | 96.47 127 | 80.24 205 | 98.98 113 | 80.57 269 | 95.05 144 | 96.98 155 |
|
XXY-MVS | | | 92.16 151 | 91.23 158 | 94.95 138 | 94.75 210 | 90.94 115 | 97.47 77 | 97.43 129 | 89.14 162 | 88.90 205 | 96.43 130 | 79.71 212 | 98.24 164 | 89.56 141 | 87.68 226 | 95.67 197 |
|
Vis-MVSNet (Re-imp) | | | 94.15 86 | 93.88 81 | 94.95 138 | 97.61 94 | 87.92 204 | 98.10 31 | 95.80 237 | 92.22 86 | 93.02 104 | 97.45 85 | 84.53 119 | 97.91 219 | 88.24 166 | 97.97 84 | 99.02 61 |
|
OPM-MVS | | | 93.28 118 | 92.76 112 | 94.82 140 | 94.63 214 | 90.77 122 | 96.65 154 | 97.18 146 | 93.72 45 | 91.68 131 | 97.26 89 | 79.33 218 | 98.63 137 | 92.13 100 | 92.28 170 | 95.07 227 |
|
HQP_MVS | | | 93.78 103 | 93.43 96 | 94.82 140 | 96.21 142 | 89.99 134 | 97.74 50 | 97.51 113 | 94.85 16 | 91.34 138 | 96.64 114 | 81.32 185 | 98.60 140 | 93.02 89 | 92.23 171 | 95.86 182 |
|
XVG-OURS-SEG-HR | | | 93.86 100 | 93.55 89 | 94.81 142 | 97.06 109 | 88.53 173 | 95.28 236 | 97.45 124 | 91.68 97 | 94.08 91 | 97.68 66 | 82.41 166 | 98.90 117 | 93.84 75 | 92.47 168 | 96.98 155 |
|
XVG-OURS | | | 93.72 105 | 93.35 99 | 94.80 143 | 97.07 107 | 88.61 171 | 94.79 245 | 97.46 120 | 91.97 92 | 93.99 92 | 97.86 54 | 81.74 180 | 98.88 121 | 92.64 93 | 92.67 167 | 96.92 157 |
|
IB-MVS | | 87.33 17 | 89.91 223 | 88.28 233 | 94.79 144 | 95.26 185 | 87.70 210 | 95.12 242 | 93.95 294 | 89.35 151 | 87.03 242 | 92.49 262 | 70.74 277 | 99.19 97 | 89.18 150 | 81.37 284 | 97.49 148 |
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 |
WR-MVS | | | 92.34 143 | 91.53 149 | 94.77 145 | 95.13 192 | 90.83 119 | 96.40 174 | 97.98 74 | 91.88 93 | 89.29 200 | 95.54 173 | 82.50 162 | 97.80 227 | 89.79 136 | 85.27 245 | 95.69 196 |
|
GA-MVS | | | 91.38 181 | 90.31 186 | 94.59 146 | 94.65 213 | 87.62 211 | 94.34 253 | 96.19 217 | 90.73 120 | 90.35 157 | 93.83 234 | 71.84 269 | 97.96 210 | 87.22 192 | 93.61 159 | 98.21 116 |
|
GBi-Net | | | 91.35 183 | 90.27 189 | 94.59 146 | 96.51 130 | 91.18 107 | 97.50 73 | 96.93 182 | 88.82 174 | 89.35 197 | 94.51 205 | 73.87 260 | 97.29 262 | 86.12 208 | 88.82 215 | 95.31 214 |
|
test1 | | | 91.35 183 | 90.27 189 | 94.59 146 | 96.51 130 | 91.18 107 | 97.50 73 | 96.93 182 | 88.82 174 | 89.35 197 | 94.51 205 | 73.87 260 | 97.29 262 | 86.12 208 | 88.82 215 | 95.31 214 |
|
FMVSNet1 | | | 89.88 225 | 88.31 232 | 94.59 146 | 95.41 173 | 91.18 107 | 97.50 73 | 96.93 182 | 86.62 232 | 87.41 233 | 94.51 205 | 65.94 297 | 97.29 262 | 83.04 254 | 87.43 229 | 95.31 214 |
|
cascas | | | 91.20 188 | 90.08 196 | 94.58 150 | 94.97 198 | 89.16 165 | 93.65 269 | 97.59 106 | 79.90 293 | 89.40 195 | 92.92 255 | 75.36 250 | 98.36 157 | 92.14 99 | 94.75 149 | 96.23 169 |
|
HQP-MVS | | | 93.19 121 | 92.74 116 | 94.54 151 | 95.86 158 | 89.33 158 | 96.65 154 | 97.39 132 | 93.55 48 | 90.14 160 | 95.87 150 | 80.95 189 | 98.50 149 | 92.13 100 | 92.10 176 | 95.78 189 |
|
PVSNet_BlendedMVS | | | 94.06 93 | 93.92 80 | 94.47 152 | 98.27 66 | 89.46 155 | 96.73 141 | 98.36 16 | 90.17 135 | 94.36 86 | 95.24 183 | 88.02 74 | 99.58 53 | 93.44 83 | 90.72 198 | 94.36 262 |
|
gg-mvs-nofinetune | | | 87.82 255 | 85.61 262 | 94.44 153 | 94.46 219 | 89.27 162 | 91.21 298 | 84.61 326 | 80.88 288 | 89.89 175 | 74.98 318 | 71.50 271 | 97.53 246 | 85.75 216 | 97.21 106 | 96.51 166 |
|
PS-MVSNAJss | | | 93.74 104 | 93.51 92 | 94.44 153 | 93.91 251 | 89.28 161 | 97.75 49 | 97.56 110 | 92.50 82 | 89.94 172 | 96.54 124 | 88.65 68 | 98.18 169 | 93.83 76 | 90.90 195 | 95.86 182 |
|
PMMVS | | | 92.86 133 | 92.34 130 | 94.42 155 | 94.92 202 | 86.73 228 | 94.53 250 | 96.38 208 | 84.78 255 | 94.27 88 | 95.12 188 | 83.13 134 | 98.40 154 | 91.47 119 | 96.49 124 | 98.12 119 |
|
MVSTER | | | 93.20 120 | 92.81 111 | 94.37 156 | 96.56 127 | 89.59 148 | 97.06 109 | 97.12 155 | 91.24 110 | 91.30 141 | 95.96 146 | 82.02 174 | 98.05 191 | 93.48 82 | 90.55 200 | 95.47 201 |
|
ACMM | | 89.79 8 | 92.96 128 | 92.50 127 | 94.35 157 | 96.30 140 | 88.71 169 | 97.58 69 | 97.36 137 | 91.40 106 | 90.53 152 | 96.65 113 | 79.77 211 | 98.75 131 | 91.24 124 | 91.64 182 | 95.59 198 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
CHOSEN 280x420 | | | 93.12 122 | 92.72 117 | 94.34 158 | 96.71 121 | 87.27 215 | 90.29 303 | 97.72 93 | 86.61 233 | 91.34 138 | 95.29 180 | 84.29 121 | 98.41 153 | 93.25 87 | 98.94 64 | 97.35 151 |
|
CLD-MVS | | | 92.98 127 | 92.53 125 | 94.32 159 | 96.12 152 | 89.20 163 | 95.28 236 | 97.47 118 | 92.66 79 | 89.90 173 | 95.62 168 | 80.58 198 | 98.40 154 | 92.73 92 | 92.40 169 | 95.38 210 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
testing_2 | | | 87.33 259 | 85.03 266 | 94.22 160 | 87.77 309 | 89.32 160 | 94.97 243 | 97.11 157 | 89.22 154 | 71.64 311 | 88.73 297 | 55.16 316 | 97.94 212 | 91.95 104 | 88.73 219 | 95.41 204 |
|
LTVRE_ROB | | 88.41 13 | 90.99 195 | 89.92 203 | 94.19 161 | 96.18 145 | 89.55 150 | 96.31 183 | 97.09 158 | 87.88 202 | 85.67 252 | 95.91 149 | 78.79 229 | 98.57 143 | 81.50 265 | 89.98 206 | 94.44 260 |
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 |
pmmvs4 | | | 90.93 197 | 89.85 206 | 94.17 162 | 93.34 268 | 90.79 121 | 94.60 247 | 96.02 222 | 84.62 256 | 87.45 231 | 95.15 185 | 81.88 178 | 97.45 251 | 87.70 177 | 87.87 225 | 94.27 266 |
|
TR-MVS | | | 91.48 176 | 90.59 181 | 94.16 163 | 96.40 136 | 87.33 213 | 95.67 218 | 95.34 255 | 87.68 207 | 91.46 134 | 95.52 174 | 76.77 241 | 98.35 158 | 82.85 256 | 93.61 159 | 96.79 161 |
|
LPG-MVS_test | | | 92.94 129 | 92.56 122 | 94.10 164 | 96.16 147 | 88.26 179 | 97.65 60 | 97.46 120 | 91.29 107 | 90.12 166 | 97.16 93 | 79.05 222 | 98.73 132 | 92.25 96 | 91.89 179 | 95.31 214 |
|
LGP-MVS_train | | | | | 94.10 164 | 96.16 147 | 88.26 179 | | 97.46 120 | 91.29 107 | 90.12 166 | 97.16 93 | 79.05 222 | 98.73 132 | 92.25 96 | 91.89 179 | 95.31 214 |
|
mvs_anonymous | | | 93.82 101 | 93.74 84 | 94.06 166 | 96.44 135 | 85.41 244 | 95.81 213 | 97.05 164 | 89.85 142 | 90.09 169 | 96.36 133 | 87.44 86 | 97.75 232 | 93.97 69 | 96.69 120 | 99.02 61 |
|
ACMP | | 89.59 10 | 92.62 139 | 92.14 132 | 94.05 167 | 96.40 136 | 88.20 185 | 97.36 84 | 97.25 145 | 91.52 99 | 88.30 217 | 96.64 114 | 78.46 232 | 98.72 134 | 91.86 109 | 91.48 186 | 95.23 221 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
jajsoiax | | | 92.42 142 | 91.89 140 | 94.03 168 | 93.33 270 | 88.50 174 | 97.73 52 | 97.53 111 | 92.00 91 | 88.85 207 | 96.50 126 | 75.62 249 | 98.11 175 | 93.88 74 | 91.56 185 | 95.48 199 |
|
test_djsdf | | | 93.07 124 | 92.76 112 | 94.00 169 | 93.49 264 | 88.70 170 | 98.22 26 | 97.57 107 | 91.42 104 | 90.08 170 | 95.55 172 | 82.85 154 | 97.92 216 | 94.07 67 | 91.58 184 | 95.40 208 |
|
AllTest | | | 90.23 217 | 88.98 224 | 93.98 170 | 97.94 83 | 86.64 229 | 96.51 165 | 95.54 245 | 85.38 244 | 85.49 254 | 96.77 105 | 70.28 279 | 99.15 102 | 80.02 272 | 92.87 163 | 96.15 173 |
|
TestCases | | | | | 93.98 170 | 97.94 83 | 86.64 229 | | 95.54 245 | 85.38 244 | 85.49 254 | 96.77 105 | 70.28 279 | 99.15 102 | 80.02 272 | 92.87 163 | 96.15 173 |
|
anonymousdsp | | | 92.16 151 | 91.55 148 | 93.97 172 | 92.58 287 | 89.55 150 | 97.51 72 | 97.42 130 | 89.42 150 | 88.40 214 | 94.84 193 | 80.66 197 | 97.88 221 | 91.87 108 | 91.28 190 | 94.48 258 |
|
pm-mvs1 | | | 90.72 205 | 89.65 215 | 93.96 173 | 94.29 226 | 89.63 145 | 97.79 47 | 96.82 190 | 89.07 163 | 86.12 250 | 95.48 175 | 78.61 230 | 97.78 229 | 86.97 197 | 81.67 282 | 94.46 259 |
|
WR-MVS_H | | | 92.00 156 | 91.35 151 | 93.95 174 | 95.09 194 | 89.47 154 | 98.04 35 | 98.68 7 | 91.46 102 | 88.34 215 | 94.68 200 | 85.86 103 | 97.56 244 | 85.77 215 | 84.24 262 | 94.82 245 |
|
CR-MVSNet | | | 90.82 200 | 89.77 209 | 93.95 174 | 94.45 220 | 87.19 219 | 90.23 304 | 95.68 240 | 86.89 228 | 92.40 115 | 92.36 267 | 80.91 192 | 97.05 266 | 81.09 268 | 93.95 154 | 97.60 144 |
|
RPMNet | | | 88.52 244 | 86.72 256 | 93.95 174 | 94.45 220 | 87.19 219 | 90.23 304 | 94.99 270 | 77.87 303 | 92.40 115 | 87.55 308 | 80.17 207 | 97.05 266 | 68.84 305 | 93.95 154 | 97.60 144 |
|
mvs_tets | | | 92.31 145 | 91.76 142 | 93.94 177 | 93.41 266 | 88.29 177 | 97.63 64 | 97.53 111 | 92.04 89 | 88.76 208 | 96.45 129 | 74.62 256 | 98.09 178 | 93.91 72 | 91.48 186 | 95.45 203 |
|
BH-untuned | | | 92.94 129 | 92.62 120 | 93.92 178 | 97.22 101 | 86.16 236 | 96.40 174 | 96.25 214 | 90.06 137 | 89.79 180 | 96.17 140 | 83.19 130 | 98.35 158 | 87.19 193 | 97.27 105 | 97.24 152 |
|
ACMH | | 87.59 16 | 90.53 211 | 89.42 218 | 93.87 179 | 96.21 142 | 87.92 204 | 97.24 93 | 96.94 181 | 88.45 185 | 83.91 267 | 96.27 136 | 71.92 268 | 98.62 139 | 84.43 235 | 89.43 211 | 95.05 232 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
CP-MVSNet | | | 91.89 158 | 91.24 157 | 93.82 180 | 95.05 195 | 88.57 172 | 97.82 45 | 98.19 31 | 91.70 96 | 88.21 220 | 95.76 160 | 81.96 175 | 97.52 247 | 87.86 173 | 84.65 259 | 95.37 211 |
|
v2v482 | | | 91.59 170 | 90.85 170 | 93.80 181 | 93.87 253 | 88.17 187 | 96.94 122 | 96.88 187 | 89.54 146 | 89.53 192 | 94.90 191 | 81.70 181 | 98.02 198 | 89.25 147 | 85.04 253 | 95.20 222 |
|
COLMAP_ROB | | 87.81 15 | 90.40 213 | 89.28 220 | 93.79 182 | 97.95 82 | 87.13 221 | 96.92 124 | 95.89 233 | 82.83 273 | 86.88 246 | 97.18 92 | 73.77 263 | 99.29 92 | 78.44 281 | 93.62 158 | 94.95 233 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
v1141 | | | 91.61 167 | 90.89 165 | 93.78 183 | 94.01 246 | 88.24 181 | 96.96 116 | 96.96 177 | 89.17 159 | 89.75 182 | 94.29 219 | 82.99 146 | 98.03 195 | 88.85 159 | 85.00 254 | 95.07 227 |
|
divwei89l23v2f112 | | | 91.61 167 | 90.89 165 | 93.78 183 | 94.01 246 | 88.22 183 | 96.96 116 | 96.96 177 | 89.17 159 | 89.75 182 | 94.28 221 | 83.02 144 | 98.03 195 | 88.86 158 | 84.98 256 | 95.08 225 |
|
v1 | | | 91.61 167 | 90.89 165 | 93.78 183 | 94.01 246 | 88.21 184 | 96.96 116 | 96.96 177 | 89.17 159 | 89.78 181 | 94.29 219 | 82.97 148 | 98.05 191 | 88.85 159 | 84.99 255 | 95.08 225 |
|
v1neww | | | 91.70 163 | 91.01 162 | 93.75 186 | 94.19 228 | 88.14 190 | 97.20 99 | 96.98 173 | 89.18 157 | 89.87 176 | 94.44 209 | 83.10 136 | 98.06 188 | 89.06 153 | 85.09 249 | 95.06 230 |
|
v7new | | | 91.70 163 | 91.01 162 | 93.75 186 | 94.19 228 | 88.14 190 | 97.20 99 | 96.98 173 | 89.18 157 | 89.87 176 | 94.44 209 | 83.10 136 | 98.06 188 | 89.06 153 | 85.09 249 | 95.06 230 |
|
v6 | | | 91.69 165 | 91.00 164 | 93.75 186 | 94.14 233 | 88.12 192 | 97.20 99 | 96.98 173 | 89.19 155 | 89.90 173 | 94.42 211 | 83.04 142 | 98.07 183 | 89.07 152 | 85.10 248 | 95.07 227 |
|
V42 | | | 91.58 171 | 90.87 168 | 93.73 189 | 94.05 245 | 88.50 174 | 97.32 88 | 96.97 176 | 88.80 177 | 89.71 184 | 94.33 216 | 82.54 161 | 98.05 191 | 89.01 155 | 85.07 251 | 94.64 255 |
|
PVSNet | | 86.66 18 | 92.24 149 | 91.74 145 | 93.73 189 | 97.77 88 | 83.69 263 | 92.88 282 | 96.72 193 | 87.91 201 | 93.00 105 | 94.86 192 | 78.51 231 | 99.05 111 | 86.53 200 | 97.45 100 | 98.47 104 |
|
MIMVSNet | | | 88.50 246 | 86.76 254 | 93.72 191 | 94.84 206 | 87.77 208 | 91.39 294 | 94.05 291 | 86.41 234 | 87.99 223 | 92.59 260 | 63.27 301 | 95.82 292 | 77.44 283 | 92.84 165 | 97.57 146 |
|
Patchmatch-test | | | 89.42 231 | 87.99 235 | 93.70 192 | 95.27 182 | 85.11 246 | 88.98 310 | 94.37 283 | 81.11 286 | 87.10 241 | 93.69 237 | 82.28 168 | 97.50 248 | 74.37 292 | 94.76 148 | 98.48 103 |
|
PS-CasMVS | | | 91.55 173 | 90.84 172 | 93.69 193 | 94.96 199 | 88.28 178 | 97.84 44 | 98.24 26 | 91.46 102 | 88.04 222 | 95.80 155 | 79.67 213 | 97.48 249 | 87.02 196 | 84.54 260 | 95.31 214 |
|
v1144 | | | 91.37 182 | 90.60 180 | 93.68 194 | 93.89 252 | 88.23 182 | 96.84 128 | 97.03 170 | 88.37 188 | 89.69 186 | 94.39 212 | 82.04 173 | 97.98 203 | 87.80 175 | 85.37 243 | 94.84 241 |
|
v7 | | | 91.47 177 | 90.73 176 | 93.68 194 | 94.13 234 | 88.16 188 | 97.09 108 | 97.05 164 | 88.38 187 | 89.80 179 | 94.52 204 | 82.21 170 | 98.01 199 | 88.00 170 | 85.42 242 | 94.87 239 |
|
GG-mvs-BLEND | | | | | 93.62 196 | 93.69 258 | 89.20 163 | 92.39 290 | 83.33 327 | | 87.98 224 | 89.84 283 | 71.00 275 | 96.87 272 | 82.08 264 | 95.40 139 | 94.80 247 |
|
Patchmatch-test1 | | | 91.54 174 | 90.85 170 | 93.59 197 | 95.59 167 | 84.95 250 | 94.72 246 | 95.58 244 | 90.82 117 | 92.25 121 | 93.58 242 | 75.80 246 | 97.41 255 | 83.35 249 | 95.98 130 | 98.40 109 |
|
PatchmatchNet | | | 91.91 157 | 91.35 151 | 93.59 197 | 95.38 175 | 84.11 258 | 93.15 278 | 95.39 249 | 89.54 146 | 92.10 125 | 93.68 238 | 82.82 155 | 98.13 172 | 84.81 227 | 95.32 140 | 98.52 95 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
v1192 | | | 91.07 192 | 90.23 192 | 93.58 199 | 93.70 257 | 87.82 207 | 96.73 141 | 97.07 161 | 87.77 204 | 89.58 189 | 94.32 217 | 80.90 195 | 97.97 206 | 86.52 201 | 85.48 240 | 94.95 233 |
|
v8 | | | 91.29 186 | 90.53 182 | 93.57 200 | 94.15 232 | 88.12 192 | 97.34 85 | 97.06 163 | 88.99 166 | 88.32 216 | 94.26 225 | 83.08 138 | 98.01 199 | 87.62 183 | 83.92 267 | 94.57 256 |
|
ADS-MVSNet | | | 89.89 224 | 88.68 228 | 93.53 201 | 95.86 158 | 84.89 251 | 90.93 299 | 95.07 267 | 83.23 271 | 91.28 144 | 91.81 274 | 79.01 226 | 97.85 222 | 79.52 274 | 91.39 188 | 97.84 131 |
|
v10 | | | 91.04 194 | 90.23 192 | 93.49 202 | 94.12 236 | 88.16 188 | 97.32 88 | 97.08 160 | 88.26 191 | 88.29 218 | 94.22 226 | 82.17 172 | 97.97 206 | 86.45 203 | 84.12 263 | 94.33 263 |
|
EI-MVSNet | | | 93.03 126 | 92.88 110 | 93.48 203 | 95.77 163 | 86.98 224 | 96.44 166 | 97.12 155 | 90.66 124 | 91.30 141 | 97.64 72 | 86.56 93 | 98.05 191 | 89.91 133 | 90.55 200 | 95.41 204 |
|
PEN-MVS | | | 91.20 188 | 90.44 183 | 93.48 203 | 94.49 218 | 87.91 206 | 97.76 48 | 98.18 33 | 91.29 107 | 87.78 225 | 95.74 162 | 80.35 203 | 97.33 260 | 85.46 220 | 82.96 276 | 95.19 223 |
|
mvs-test1 | | | 93.63 107 | 93.69 86 | 93.46 205 | 96.02 154 | 84.61 254 | 97.24 93 | 96.72 193 | 93.85 42 | 92.30 120 | 95.76 160 | 83.08 138 | 98.89 119 | 91.69 114 | 96.54 123 | 96.87 159 |
|
v7n | | | 90.76 201 | 89.86 205 | 93.45 206 | 93.54 261 | 87.60 212 | 97.70 56 | 97.37 135 | 88.85 171 | 87.65 229 | 94.08 229 | 81.08 187 | 98.10 176 | 84.68 230 | 83.79 270 | 94.66 254 |
|
v144192 | | | 91.06 193 | 90.28 188 | 93.39 207 | 93.66 259 | 87.23 218 | 96.83 129 | 97.07 161 | 87.43 211 | 89.69 186 | 94.28 221 | 81.48 182 | 98.00 202 | 87.18 194 | 84.92 257 | 94.93 237 |
|
DWT-MVSNet_test | | | 90.76 201 | 89.89 204 | 93.38 208 | 95.04 196 | 83.70 262 | 95.85 211 | 94.30 286 | 88.19 194 | 90.46 154 | 92.80 256 | 73.61 264 | 98.50 149 | 88.16 167 | 90.58 199 | 97.95 125 |
|
EPMVS | | | 90.70 207 | 89.81 208 | 93.37 209 | 94.73 211 | 84.21 256 | 93.67 268 | 88.02 320 | 89.50 148 | 92.38 117 | 93.49 246 | 77.82 238 | 97.78 229 | 86.03 211 | 92.68 166 | 98.11 122 |
|
IterMVS-LS | | | 92.29 147 | 91.94 139 | 93.34 210 | 96.25 141 | 86.97 225 | 96.57 164 | 97.05 164 | 90.67 122 | 89.50 194 | 94.80 196 | 86.59 92 | 97.64 240 | 89.91 133 | 86.11 237 | 95.40 208 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
BH-w/o | | | 92.14 153 | 91.75 143 | 93.31 211 | 96.99 112 | 85.73 239 | 95.67 218 | 95.69 239 | 88.73 179 | 89.26 202 | 94.82 195 | 82.97 148 | 98.07 183 | 85.26 223 | 96.32 127 | 96.13 175 |
|
v1921920 | | | 90.85 199 | 90.03 199 | 93.29 212 | 93.55 260 | 86.96 226 | 96.74 140 | 97.04 168 | 87.36 213 | 89.52 193 | 94.34 215 | 80.23 206 | 97.97 206 | 86.27 204 | 85.21 246 | 94.94 235 |
|
ACMH+ | | 87.92 14 | 90.20 218 | 89.18 222 | 93.25 213 | 96.48 133 | 86.45 233 | 96.99 114 | 96.68 198 | 88.83 173 | 84.79 258 | 96.22 137 | 70.16 281 | 98.53 146 | 84.42 236 | 88.04 223 | 94.77 251 |
|
v1240 | | | 90.70 207 | 89.85 206 | 93.23 214 | 93.51 263 | 86.80 227 | 96.61 159 | 97.02 171 | 87.16 217 | 89.58 189 | 94.31 218 | 79.55 215 | 97.98 203 | 85.52 219 | 85.44 241 | 94.90 238 |
|
PatchT | | | 88.87 237 | 87.42 242 | 93.22 215 | 94.08 242 | 85.10 247 | 89.51 308 | 94.64 278 | 81.92 279 | 92.36 118 | 88.15 303 | 80.05 208 | 97.01 270 | 72.43 297 | 93.65 157 | 97.54 147 |
|
Fast-Effi-MVS+-dtu | | | 92.29 147 | 91.99 137 | 93.21 216 | 95.27 182 | 85.52 243 | 97.03 110 | 96.63 202 | 92.09 88 | 89.11 204 | 95.14 186 | 80.33 204 | 98.08 179 | 87.54 185 | 94.74 150 | 96.03 179 |
|
PatchFormer-LS_test | | | 91.68 166 | 91.18 161 | 93.19 217 | 95.24 186 | 83.63 264 | 95.53 226 | 95.44 248 | 89.82 143 | 91.37 136 | 92.58 261 | 80.85 196 | 98.52 147 | 89.65 140 | 90.16 205 | 97.42 150 |
|
XVG-ACMP-BASELINE | | | 90.93 197 | 90.21 194 | 93.09 218 | 94.31 225 | 85.89 237 | 95.33 233 | 97.26 143 | 91.06 115 | 89.38 196 | 95.44 176 | 68.61 285 | 98.60 140 | 89.46 143 | 91.05 193 | 94.79 249 |
|
TransMVSNet (Re) | | | 88.94 234 | 87.56 237 | 93.08 219 | 94.35 223 | 88.45 176 | 97.73 52 | 95.23 260 | 87.47 210 | 84.26 262 | 95.29 180 | 79.86 210 | 97.33 260 | 79.44 277 | 74.44 310 | 93.45 275 |
|
DTE-MVSNet | | | 90.56 210 | 89.75 211 | 93.01 220 | 93.95 249 | 87.25 216 | 97.64 63 | 97.65 101 | 90.74 119 | 87.12 239 | 95.68 166 | 79.97 209 | 97.00 271 | 83.33 251 | 81.66 283 | 94.78 250 |
|
EPNet_dtu | | | 91.71 160 | 91.28 155 | 92.99 221 | 93.76 256 | 83.71 261 | 96.69 151 | 95.28 256 | 93.15 62 | 87.02 243 | 95.95 147 | 83.37 129 | 97.38 258 | 79.46 276 | 96.84 113 | 97.88 130 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
Baseline_NR-MVSNet | | | 91.20 188 | 90.62 179 | 92.95 222 | 93.83 254 | 88.03 198 | 97.01 113 | 95.12 265 | 88.42 186 | 89.70 185 | 95.13 187 | 83.47 127 | 97.44 252 | 89.66 139 | 83.24 274 | 93.37 277 |
|
pmmvs5 | | | 89.86 226 | 88.87 226 | 92.82 223 | 92.86 281 | 86.23 235 | 96.26 187 | 95.39 249 | 84.24 259 | 87.12 239 | 94.51 205 | 74.27 258 | 97.36 259 | 87.61 184 | 87.57 227 | 94.86 240 |
|
v52 | | | 90.70 207 | 90.00 200 | 92.82 223 | 93.24 272 | 87.03 222 | 97.60 66 | 97.14 152 | 88.21 192 | 87.69 227 | 93.94 231 | 80.91 192 | 98.07 183 | 87.39 187 | 83.87 269 | 93.36 278 |
|
V4 | | | 90.71 206 | 90.00 200 | 92.82 223 | 93.21 275 | 87.03 222 | 97.59 68 | 97.16 151 | 88.21 192 | 87.69 227 | 93.92 233 | 80.93 191 | 98.06 188 | 87.39 187 | 83.90 268 | 93.39 276 |
|
v148 | | | 90.99 195 | 90.38 185 | 92.81 226 | 93.83 254 | 85.80 238 | 96.78 138 | 96.68 198 | 89.45 149 | 88.75 209 | 93.93 232 | 82.96 150 | 97.82 226 | 87.83 174 | 83.25 273 | 94.80 247 |
|
Patchmtry | | | 88.64 242 | 87.25 246 | 92.78 227 | 94.09 240 | 86.64 229 | 89.82 307 | 95.68 240 | 80.81 290 | 87.63 230 | 92.36 267 | 80.91 192 | 97.03 268 | 78.86 279 | 85.12 247 | 94.67 253 |
|
v748 | | | 90.34 214 | 89.54 216 | 92.75 228 | 93.25 271 | 85.71 240 | 97.61 65 | 97.17 148 | 88.54 184 | 87.20 238 | 93.54 243 | 81.02 188 | 98.01 199 | 85.73 217 | 81.80 280 | 94.52 257 |
|
MVP-Stereo | | | 90.74 204 | 90.08 196 | 92.71 229 | 93.19 277 | 88.20 185 | 95.86 210 | 96.27 212 | 86.07 239 | 84.86 257 | 94.76 197 | 77.84 237 | 97.75 232 | 83.88 246 | 98.01 83 | 92.17 300 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
pmmvs6 | | | 87.81 256 | 86.19 258 | 92.69 230 | 91.32 294 | 86.30 234 | 97.34 85 | 96.41 207 | 80.59 292 | 84.05 266 | 94.37 214 | 67.37 292 | 97.67 237 | 84.75 228 | 79.51 290 | 94.09 268 |
|
Effi-MVS+-dtu | | | 93.08 123 | 93.21 104 | 92.68 231 | 96.02 154 | 83.25 266 | 97.14 106 | 96.72 193 | 93.85 42 | 91.20 147 | 93.44 249 | 83.08 138 | 98.30 162 | 91.69 114 | 95.73 136 | 96.50 167 |
|
CostFormer | | | 91.18 191 | 90.70 177 | 92.62 232 | 94.84 206 | 81.76 275 | 94.09 261 | 94.43 280 | 84.15 260 | 92.72 113 | 93.77 236 | 79.43 217 | 98.20 166 | 90.70 127 | 92.18 174 | 97.90 127 |
|
tpmp4_e23 | | | 89.58 228 | 88.59 229 | 92.54 233 | 95.16 190 | 81.53 276 | 94.11 260 | 95.09 266 | 81.66 281 | 88.60 211 | 93.44 249 | 75.11 251 | 98.33 161 | 82.45 261 | 91.72 181 | 97.75 135 |
|
LCM-MVSNet-Re | | | 92.50 140 | 92.52 126 | 92.44 234 | 96.82 118 | 81.89 274 | 96.92 124 | 93.71 296 | 92.41 84 | 84.30 261 | 94.60 203 | 85.08 111 | 97.03 268 | 91.51 117 | 97.36 102 | 98.40 109 |
|
ITE_SJBPF | | | | | 92.43 235 | 95.34 177 | 85.37 245 | | 95.92 226 | 91.47 101 | 87.75 226 | 96.39 132 | 71.00 275 | 97.96 210 | 82.36 262 | 89.86 209 | 93.97 269 |
|
v18 | | | 88.71 239 | 87.52 238 | 92.27 236 | 94.16 231 | 88.11 194 | 96.82 132 | 95.96 223 | 87.03 219 | 80.76 283 | 89.81 284 | 83.15 132 | 96.22 279 | 84.69 229 | 75.31 301 | 92.49 287 |
|
USDC | | | 88.94 234 | 87.83 236 | 92.27 236 | 94.66 212 | 84.96 249 | 93.86 264 | 95.90 228 | 87.34 214 | 83.40 269 | 95.56 171 | 67.43 291 | 98.19 168 | 82.64 260 | 89.67 210 | 93.66 272 |
|
v17 | | | 88.67 241 | 87.47 241 | 92.26 238 | 94.13 234 | 88.09 196 | 96.81 133 | 95.95 224 | 87.02 220 | 80.72 284 | 89.75 286 | 83.11 135 | 96.20 280 | 84.61 232 | 75.15 303 | 92.49 287 |
|
v16 | | | 88.69 240 | 87.50 239 | 92.26 238 | 94.19 228 | 88.11 194 | 96.81 133 | 95.95 224 | 87.01 221 | 80.71 285 | 89.80 285 | 83.08 138 | 96.20 280 | 84.61 232 | 75.34 300 | 92.48 289 |
|
tpm2 | | | 89.96 222 | 89.21 221 | 92.23 240 | 94.91 204 | 81.25 278 | 93.78 265 | 94.42 281 | 80.62 291 | 91.56 132 | 93.44 249 | 76.44 243 | 97.94 212 | 85.60 218 | 92.08 178 | 97.49 148 |
|
v15 | | | 88.53 243 | 87.31 243 | 92.20 241 | 94.09 240 | 88.05 197 | 96.72 144 | 95.90 228 | 87.01 221 | 80.53 288 | 89.60 290 | 83.02 144 | 96.13 282 | 84.29 237 | 74.64 304 | 92.41 293 |
|
V9 | | | 88.49 247 | 87.26 245 | 92.18 242 | 94.12 236 | 87.97 202 | 96.73 141 | 95.90 228 | 86.95 225 | 80.40 291 | 89.61 288 | 82.98 147 | 96.13 282 | 84.14 239 | 74.55 307 | 92.44 291 |
|
v12 | | | 88.46 248 | 87.23 248 | 92.17 243 | 94.10 239 | 87.99 199 | 96.71 146 | 95.90 228 | 86.91 226 | 80.34 293 | 89.58 291 | 82.92 151 | 96.11 286 | 84.09 240 | 74.50 309 | 92.42 292 |
|
V14 | | | 88.52 244 | 87.30 244 | 92.17 243 | 94.12 236 | 87.99 199 | 96.72 144 | 95.91 227 | 86.98 223 | 80.50 289 | 89.63 287 | 83.03 143 | 96.12 284 | 84.23 238 | 74.60 306 | 92.40 294 |
|
v13 | | | 88.45 249 | 87.22 249 | 92.16 245 | 94.08 242 | 87.95 203 | 96.71 146 | 95.90 228 | 86.86 230 | 80.27 295 | 89.55 292 | 82.92 151 | 96.12 284 | 84.02 242 | 74.63 305 | 92.40 294 |
|
test-LLR | | | 91.42 179 | 91.19 160 | 92.12 246 | 94.59 215 | 80.66 281 | 94.29 255 | 92.98 303 | 91.11 113 | 90.76 150 | 92.37 264 | 79.02 224 | 98.07 183 | 88.81 161 | 96.74 117 | 97.63 139 |
|
test-mter | | | 90.19 219 | 89.54 216 | 92.12 246 | 94.59 215 | 80.66 281 | 94.29 255 | 92.98 303 | 87.68 207 | 90.76 150 | 92.37 264 | 67.67 289 | 98.07 183 | 88.81 161 | 96.74 117 | 97.63 139 |
|
v11 | | | 88.41 250 | 87.19 252 | 92.08 248 | 94.08 242 | 87.77 208 | 96.75 139 | 95.85 234 | 86.74 231 | 80.50 289 | 89.50 293 | 82.49 163 | 96.08 287 | 83.55 248 | 75.20 302 | 92.38 296 |
|
ADS-MVSNet2 | | | 89.45 230 | 88.59 229 | 92.03 249 | 95.86 158 | 82.26 272 | 90.93 299 | 94.32 285 | 83.23 271 | 91.28 144 | 91.81 274 | 79.01 226 | 95.99 288 | 79.52 274 | 91.39 188 | 97.84 131 |
|
TESTMET0.1,1 | | | 90.06 221 | 89.42 218 | 91.97 250 | 94.41 222 | 80.62 283 | 94.29 255 | 91.97 310 | 87.28 216 | 90.44 155 | 92.47 263 | 68.79 284 | 97.67 237 | 88.50 165 | 96.60 122 | 97.61 143 |
|
JIA-IIPM | | | 88.26 252 | 87.04 253 | 91.91 251 | 93.52 262 | 81.42 277 | 89.38 309 | 94.38 282 | 80.84 289 | 90.93 149 | 80.74 315 | 79.22 219 | 97.92 216 | 82.76 257 | 91.62 183 | 96.38 168 |
|
tpmvs | | | 89.83 227 | 89.15 223 | 91.89 252 | 94.92 202 | 80.30 287 | 93.11 279 | 95.46 247 | 86.28 235 | 88.08 221 | 92.65 258 | 80.44 201 | 98.52 147 | 81.47 266 | 89.92 208 | 96.84 160 |
|
TDRefinement | | | 86.53 264 | 84.76 269 | 91.85 253 | 82.23 319 | 84.25 255 | 96.38 176 | 95.35 252 | 84.97 252 | 84.09 265 | 94.94 189 | 65.76 298 | 98.34 160 | 84.60 234 | 74.52 308 | 92.97 279 |
|
semantic-postprocess | | | | | 91.82 254 | 95.52 169 | 84.20 257 | | 96.15 219 | 90.61 128 | 87.39 234 | 94.27 223 | 75.63 248 | 96.44 275 | 87.34 189 | 86.88 234 | 94.82 245 |
|
tpm cat1 | | | 88.36 251 | 87.21 250 | 91.81 255 | 95.13 192 | 80.55 284 | 92.58 286 | 95.70 238 | 74.97 309 | 87.45 231 | 91.96 272 | 78.01 236 | 98.17 170 | 80.39 271 | 88.74 218 | 96.72 163 |
|
tpmrst | | | 91.44 178 | 91.32 153 | 91.79 256 | 95.15 191 | 79.20 296 | 93.42 272 | 95.37 251 | 88.55 183 | 93.49 99 | 93.67 239 | 82.49 163 | 98.27 163 | 90.41 129 | 89.34 212 | 97.90 127 |
|
MS-PatchMatch | | | 90.27 215 | 89.77 209 | 91.78 257 | 94.33 224 | 84.72 253 | 95.55 224 | 96.73 192 | 86.17 238 | 86.36 248 | 95.28 182 | 71.28 273 | 97.80 227 | 84.09 240 | 98.14 81 | 92.81 283 |
|
FMVSNet5 | | | 87.29 260 | 85.79 261 | 91.78 257 | 94.80 208 | 87.28 214 | 95.49 228 | 95.28 256 | 84.09 261 | 83.85 268 | 91.82 273 | 62.95 302 | 94.17 304 | 78.48 280 | 85.34 244 | 93.91 270 |
|
EG-PatchMatch MVS | | | 87.02 262 | 85.44 263 | 91.76 259 | 92.67 285 | 85.00 248 | 96.08 200 | 96.45 206 | 83.41 270 | 79.52 298 | 93.49 246 | 57.10 311 | 97.72 234 | 79.34 278 | 90.87 196 | 92.56 285 |
|
tpm | | | 90.25 216 | 89.74 212 | 91.76 259 | 93.92 250 | 79.73 292 | 93.98 262 | 93.54 300 | 88.28 190 | 91.99 127 | 93.25 252 | 77.51 239 | 97.44 252 | 87.30 191 | 87.94 224 | 98.12 119 |
|
IterMVS | | | 90.15 220 | 89.67 213 | 91.61 261 | 95.48 171 | 83.72 260 | 94.33 254 | 96.12 220 | 89.99 138 | 87.31 237 | 94.15 227 | 75.78 247 | 96.27 278 | 86.97 197 | 86.89 233 | 94.83 243 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
pmmvs-eth3d | | | 86.22 267 | 84.45 270 | 91.53 262 | 88.34 306 | 87.25 216 | 94.47 251 | 95.01 268 | 83.47 269 | 79.51 299 | 89.61 288 | 69.75 282 | 95.71 293 | 83.13 253 | 76.73 296 | 91.64 302 |
|
test_0402 | | | 86.46 265 | 84.79 268 | 91.45 263 | 95.02 197 | 85.55 242 | 96.29 185 | 94.89 274 | 80.90 287 | 82.21 271 | 93.97 230 | 68.21 288 | 97.29 262 | 62.98 311 | 88.68 220 | 91.51 304 |
|
OurMVSNet-221017-0 | | | 90.51 212 | 90.19 195 | 91.44 264 | 93.41 266 | 81.25 278 | 96.98 115 | 96.28 211 | 91.68 97 | 86.55 247 | 96.30 134 | 74.20 259 | 97.98 203 | 88.96 156 | 87.40 231 | 95.09 224 |
|
test0.0.03 1 | | | 89.37 232 | 88.70 227 | 91.41 265 | 92.47 288 | 85.63 241 | 95.22 240 | 92.70 306 | 91.11 113 | 86.91 245 | 93.65 240 | 79.02 224 | 93.19 309 | 78.00 282 | 89.18 213 | 95.41 204 |
|
TinyColmap | | | 86.82 263 | 85.35 265 | 91.21 266 | 94.91 204 | 82.99 267 | 93.94 263 | 94.02 293 | 83.58 267 | 81.56 278 | 94.68 200 | 62.34 304 | 98.13 172 | 75.78 289 | 87.35 232 | 92.52 286 |
|
MDA-MVSNet-bldmvs | | | 85.00 274 | 82.95 276 | 91.17 267 | 93.13 279 | 83.33 265 | 94.56 249 | 95.00 269 | 84.57 257 | 65.13 317 | 92.65 258 | 70.45 278 | 95.85 290 | 73.57 295 | 77.49 293 | 94.33 263 |
|
SixPastTwentyTwo | | | 89.15 233 | 88.54 231 | 90.98 268 | 93.49 264 | 80.28 288 | 96.70 149 | 94.70 277 | 90.78 118 | 84.15 264 | 95.57 170 | 71.78 270 | 97.71 235 | 84.63 231 | 85.07 251 | 94.94 235 |
|
LP | | | 84.13 277 | 81.85 282 | 90.97 269 | 93.20 276 | 82.12 273 | 87.68 314 | 94.27 288 | 76.80 304 | 81.93 274 | 88.52 298 | 72.97 267 | 95.95 289 | 59.53 316 | 81.73 281 | 94.84 241 |
|
PVSNet_0 | | 82.17 19 | 85.46 273 | 83.64 274 | 90.92 270 | 95.27 182 | 79.49 293 | 90.55 302 | 95.60 242 | 83.76 266 | 83.00 270 | 89.95 281 | 71.09 274 | 97.97 206 | 82.75 258 | 60.79 320 | 95.31 214 |
|
OpenMVS_ROB | | 81.14 20 | 84.42 276 | 82.28 277 | 90.83 271 | 90.06 299 | 84.05 259 | 95.73 217 | 94.04 292 | 73.89 312 | 80.17 297 | 91.53 278 | 59.15 308 | 97.64 240 | 66.92 307 | 89.05 214 | 90.80 307 |
|
Patchmatch-RL test | | | 87.38 258 | 86.24 257 | 90.81 272 | 88.74 305 | 78.40 299 | 88.12 313 | 93.17 302 | 87.11 218 | 82.17 272 | 89.29 294 | 81.95 176 | 95.60 295 | 88.64 164 | 77.02 294 | 98.41 108 |
|
dp | | | 88.90 236 | 88.26 234 | 90.81 272 | 94.58 217 | 76.62 301 | 92.85 283 | 94.93 273 | 85.12 249 | 90.07 171 | 93.07 253 | 75.81 245 | 98.12 174 | 80.53 270 | 87.42 230 | 97.71 137 |
|
MDA-MVSNet_test_wron | | | 85.87 270 | 84.23 272 | 90.80 274 | 92.38 289 | 82.57 268 | 93.17 276 | 95.15 263 | 82.15 277 | 67.65 313 | 92.33 270 | 78.20 234 | 95.51 297 | 77.33 284 | 79.74 288 | 94.31 265 |
|
YYNet1 | | | 85.87 270 | 84.23 272 | 90.78 275 | 92.38 289 | 82.46 270 | 93.17 276 | 95.14 264 | 82.12 278 | 67.69 312 | 92.36 267 | 78.16 235 | 95.50 298 | 77.31 285 | 79.73 289 | 94.39 261 |
|
UnsupCasMVSNet_eth | | | 85.99 269 | 84.45 270 | 90.62 276 | 89.97 300 | 82.40 271 | 93.62 270 | 97.37 135 | 89.86 140 | 78.59 301 | 92.37 264 | 65.25 299 | 95.35 299 | 82.27 263 | 70.75 313 | 94.10 267 |
|
MIMVSNet1 | | | 84.93 275 | 83.05 275 | 90.56 277 | 89.56 303 | 84.84 252 | 95.40 231 | 95.35 252 | 83.91 262 | 80.38 292 | 92.21 271 | 57.23 310 | 93.34 308 | 70.69 304 | 82.75 279 | 93.50 273 |
|
lessismore_v0 | | | | | 90.45 278 | 91.96 292 | 79.09 297 | | 87.19 323 | | 80.32 294 | 94.39 212 | 66.31 295 | 97.55 245 | 84.00 244 | 76.84 295 | 94.70 252 |
|
RPSCF | | | 90.75 203 | 90.86 169 | 90.42 279 | 96.84 115 | 76.29 302 | 95.61 223 | 96.34 209 | 83.89 263 | 91.38 135 | 97.87 52 | 76.45 242 | 98.78 127 | 87.16 195 | 92.23 171 | 96.20 170 |
|
K. test v3 | | | 87.64 257 | 86.75 255 | 90.32 280 | 93.02 280 | 79.48 294 | 96.61 159 | 92.08 309 | 90.66 124 | 80.25 296 | 94.09 228 | 67.21 293 | 96.65 274 | 85.96 213 | 80.83 287 | 94.83 243 |
|
testgi | | | 87.97 253 | 87.21 250 | 90.24 281 | 92.86 281 | 80.76 280 | 96.67 153 | 94.97 271 | 91.74 95 | 85.52 253 | 95.83 153 | 62.66 303 | 94.47 303 | 76.25 288 | 88.36 222 | 95.48 199 |
|
UnsupCasMVSNet_bld | | | 82.13 284 | 79.46 286 | 90.14 282 | 88.00 307 | 82.47 269 | 90.89 301 | 96.62 203 | 78.94 297 | 75.61 304 | 84.40 313 | 56.63 312 | 96.31 277 | 77.30 286 | 66.77 319 | 91.63 303 |
|
LF4IMVS | | | 87.94 254 | 87.25 246 | 89.98 283 | 92.38 289 | 80.05 291 | 94.38 252 | 95.25 259 | 87.59 209 | 84.34 260 | 94.74 199 | 64.31 300 | 97.66 239 | 84.83 226 | 87.45 228 | 92.23 298 |
|
Anonymous20231206 | | | 87.09 261 | 86.14 259 | 89.93 284 | 91.22 295 | 80.35 285 | 96.11 197 | 95.35 252 | 83.57 268 | 84.16 263 | 93.02 254 | 73.54 265 | 95.61 294 | 72.16 298 | 86.14 236 | 93.84 271 |
|
CVMVSNet | | | 91.23 187 | 91.75 143 | 89.67 285 | 95.77 163 | 74.69 304 | 96.44 166 | 94.88 275 | 85.81 241 | 92.18 123 | 97.64 72 | 79.07 221 | 95.58 296 | 88.06 169 | 95.86 134 | 98.74 83 |
|
test20.03 | | | 86.14 268 | 85.40 264 | 88.35 286 | 90.12 298 | 80.06 290 | 95.90 209 | 95.20 261 | 88.59 180 | 81.29 279 | 93.62 241 | 71.43 272 | 92.65 310 | 71.26 302 | 81.17 285 | 92.34 297 |
|
PM-MVS | | | 83.48 278 | 81.86 281 | 88.31 287 | 87.83 308 | 77.59 300 | 93.43 271 | 91.75 311 | 86.91 226 | 80.63 286 | 89.91 282 | 44.42 322 | 95.84 291 | 85.17 225 | 76.73 296 | 91.50 305 |
|
EU-MVSNet | | | 88.72 238 | 88.90 225 | 88.20 288 | 93.15 278 | 74.21 305 | 96.63 158 | 94.22 289 | 85.18 247 | 87.32 236 | 95.97 145 | 76.16 244 | 94.98 301 | 85.27 222 | 86.17 235 | 95.41 204 |
|
new_pmnet | | | 82.89 280 | 81.12 285 | 88.18 289 | 89.63 302 | 80.18 289 | 91.77 293 | 92.57 307 | 76.79 305 | 75.56 305 | 88.23 302 | 61.22 306 | 94.48 302 | 71.43 300 | 82.92 277 | 89.87 309 |
|
CMPMVS | | 62.92 21 | 85.62 272 | 84.92 267 | 87.74 290 | 89.14 304 | 73.12 308 | 94.17 258 | 96.80 191 | 73.98 311 | 73.65 307 | 94.93 190 | 66.36 294 | 97.61 242 | 83.95 245 | 91.28 190 | 92.48 289 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
pmmvs3 | | | 79.97 286 | 77.50 290 | 87.39 291 | 82.80 317 | 79.38 295 | 92.70 285 | 90.75 315 | 70.69 315 | 78.66 300 | 87.47 309 | 51.34 319 | 93.40 307 | 73.39 296 | 69.65 315 | 89.38 310 |
|
new-patchmatchnet | | | 83.18 279 | 81.87 280 | 87.11 292 | 86.88 311 | 75.99 303 | 93.70 266 | 95.18 262 | 85.02 251 | 77.30 303 | 88.40 300 | 65.99 296 | 93.88 306 | 74.19 294 | 70.18 314 | 91.47 306 |
|
DSMNet-mixed | | | 86.34 266 | 86.12 260 | 87.00 293 | 89.88 301 | 70.43 310 | 94.93 244 | 90.08 317 | 77.97 302 | 85.42 256 | 92.78 257 | 74.44 257 | 93.96 305 | 74.43 291 | 95.14 142 | 96.62 164 |
|
Anonymous20231211 | | | 78.22 290 | 75.30 291 | 86.99 294 | 86.14 312 | 74.16 306 | 95.62 222 | 93.88 295 | 66.43 316 | 74.44 306 | 87.86 305 | 41.39 323 | 95.11 300 | 62.49 312 | 69.46 316 | 91.71 301 |
|
ambc | | | | | 86.56 295 | 83.60 316 | 70.00 314 | 85.69 317 | 94.97 271 | | 80.60 287 | 88.45 299 | 37.42 324 | 96.84 273 | 82.69 259 | 75.44 299 | 92.86 280 |
|
MVS-HIRNet | | | 82.47 283 | 81.21 284 | 86.26 296 | 95.38 175 | 69.21 315 | 88.96 311 | 89.49 319 | 66.28 317 | 80.79 282 | 74.08 320 | 68.48 286 | 97.39 257 | 71.93 299 | 95.47 138 | 92.18 299 |
|
test2356 | | | 82.77 281 | 82.14 279 | 84.65 297 | 85.77 313 | 70.36 311 | 91.22 297 | 93.69 299 | 81.58 283 | 81.82 275 | 89.00 296 | 60.63 307 | 90.77 316 | 64.74 309 | 90.80 197 | 92.82 281 |
|
testus | | | 82.63 282 | 82.15 278 | 84.07 298 | 87.31 310 | 67.67 316 | 93.18 274 | 94.29 287 | 82.47 275 | 82.14 273 | 90.69 279 | 53.01 317 | 91.94 313 | 66.30 308 | 89.96 207 | 92.62 284 |
|
test1235678 | | | 79.82 287 | 78.53 288 | 83.69 299 | 82.55 318 | 67.55 317 | 92.50 288 | 94.13 290 | 79.28 295 | 72.10 310 | 86.45 311 | 57.27 309 | 90.68 317 | 61.60 314 | 80.90 286 | 92.82 281 |
|
LCM-MVSNet | | | 72.55 292 | 69.39 295 | 82.03 300 | 70.81 329 | 65.42 320 | 90.12 306 | 94.36 284 | 55.02 321 | 65.88 316 | 81.72 314 | 24.16 333 | 89.96 318 | 74.32 293 | 68.10 317 | 90.71 308 |
|
no-one | | | 68.12 296 | 63.78 299 | 81.13 301 | 74.01 324 | 70.22 313 | 87.61 315 | 90.71 316 | 72.63 314 | 53.13 322 | 71.89 321 | 30.29 327 | 91.45 314 | 61.53 315 | 32.21 325 | 81.72 317 |
|
1111 | | | 78.29 289 | 77.55 289 | 80.50 302 | 83.89 314 | 59.98 324 | 91.89 291 | 93.71 296 | 75.06 307 | 73.60 308 | 87.67 306 | 55.66 313 | 92.60 311 | 58.54 318 | 77.92 292 | 88.93 311 |
|
PMMVS2 | | | 70.19 295 | 66.92 297 | 80.01 303 | 76.35 321 | 65.67 319 | 86.22 316 | 87.58 322 | 64.83 319 | 62.38 318 | 80.29 317 | 26.78 331 | 88.49 322 | 63.79 310 | 54.07 321 | 85.88 314 |
|
testpf | | | 80.97 285 | 81.40 283 | 79.65 304 | 91.53 293 | 72.43 309 | 73.47 325 | 89.55 318 | 78.63 298 | 80.81 281 | 89.06 295 | 61.36 305 | 91.36 315 | 83.34 250 | 84.89 258 | 75.15 320 |
|
testmv | | | 72.22 293 | 70.02 293 | 78.82 305 | 73.06 327 | 61.75 322 | 91.24 296 | 92.31 308 | 74.45 310 | 61.06 319 | 80.51 316 | 34.21 325 | 88.63 321 | 55.31 321 | 68.07 318 | 86.06 313 |
|
N_pmnet | | | 78.73 288 | 78.71 287 | 78.79 306 | 92.80 283 | 46.50 332 | 94.14 259 | 43.71 335 | 78.61 299 | 80.83 280 | 91.66 277 | 74.94 255 | 96.36 276 | 67.24 306 | 84.45 261 | 93.50 273 |
|
test12356 | | | 74.97 291 | 74.13 292 | 77.49 307 | 78.81 320 | 56.23 328 | 88.53 312 | 92.75 305 | 75.14 306 | 67.50 314 | 85.07 312 | 44.88 321 | 89.96 318 | 58.71 317 | 75.75 298 | 86.26 312 |
|
ANet_high | | | 63.94 299 | 59.58 300 | 77.02 308 | 61.24 332 | 66.06 318 | 85.66 318 | 87.93 321 | 78.53 300 | 42.94 324 | 71.04 322 | 25.42 332 | 80.71 326 | 52.60 323 | 30.83 327 | 84.28 315 |
|
FPMVS | | | 71.27 294 | 69.85 294 | 75.50 309 | 74.64 322 | 59.03 326 | 91.30 295 | 91.50 312 | 58.80 320 | 57.92 320 | 88.28 301 | 29.98 329 | 85.53 324 | 53.43 322 | 82.84 278 | 81.95 316 |
|
Gipuma | | | 67.86 297 | 65.41 298 | 75.18 310 | 92.66 286 | 73.45 307 | 66.50 327 | 94.52 279 | 53.33 322 | 57.80 321 | 66.07 324 | 30.81 326 | 89.20 320 | 48.15 325 | 78.88 291 | 62.90 324 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
DeepMVS_CX | | | | | 74.68 311 | 90.84 296 | 64.34 321 | | 81.61 330 | 65.34 318 | 67.47 315 | 88.01 304 | 48.60 320 | 80.13 327 | 62.33 313 | 73.68 312 | 79.58 318 |
|
wuykxyi23d | | | 56.92 302 | 51.11 306 | 74.38 312 | 62.30 331 | 61.47 323 | 80.09 322 | 84.87 325 | 49.62 324 | 30.80 330 | 57.20 328 | 7.03 336 | 82.94 325 | 55.69 320 | 32.36 324 | 78.72 319 |
|
PNet_i23d | | | 59.01 300 | 55.87 301 | 68.44 313 | 73.98 325 | 51.37 329 | 81.36 321 | 82.41 328 | 52.37 323 | 42.49 326 | 70.39 323 | 11.39 334 | 79.99 328 | 49.77 324 | 38.71 323 | 73.97 321 |
|
PMVS | | 53.92 22 | 58.58 301 | 55.40 302 | 68.12 314 | 51.00 333 | 48.64 330 | 78.86 323 | 87.10 324 | 46.77 325 | 35.84 329 | 74.28 319 | 8.76 335 | 86.34 323 | 42.07 326 | 73.91 311 | 69.38 322 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
MVE | | 50.73 23 | 53.25 304 | 48.81 307 | 66.58 315 | 65.34 330 | 57.50 327 | 72.49 326 | 70.94 333 | 40.15 328 | 39.28 328 | 63.51 325 | 6.89 338 | 73.48 331 | 38.29 327 | 42.38 322 | 68.76 323 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
E-PMN | | | 53.28 303 | 52.56 304 | 55.43 316 | 74.43 323 | 47.13 331 | 83.63 320 | 76.30 331 | 42.23 326 | 42.59 325 | 62.22 326 | 28.57 330 | 74.40 329 | 31.53 328 | 31.51 326 | 44.78 325 |
|
EMVS | | | 52.08 305 | 51.31 305 | 54.39 317 | 72.62 328 | 45.39 333 | 83.84 319 | 75.51 332 | 41.13 327 | 40.77 327 | 59.65 327 | 30.08 328 | 73.60 330 | 28.31 329 | 29.90 328 | 44.18 326 |
|
.test1245 | | | 65.38 298 | 69.22 296 | 53.86 318 | 83.89 314 | 59.98 324 | 91.89 291 | 93.71 296 | 75.06 307 | 73.60 308 | 87.67 306 | 55.66 313 | 92.60 311 | 58.54 318 | 2.96 331 | 9.00 329 |
|
tmp_tt | | | 51.94 306 | 53.82 303 | 46.29 319 | 33.73 334 | 45.30 334 | 78.32 324 | 67.24 334 | 18.02 329 | 50.93 323 | 87.05 310 | 52.99 318 | 53.11 332 | 70.76 303 | 25.29 329 | 40.46 327 |
|
pcd1.5k->3k | | | 38.37 307 | 40.51 308 | 31.96 320 | 94.29 226 | 0.00 338 | 0.00 329 | 97.69 97 | 0.00 333 | 0.00 334 | 0.00 335 | 81.45 183 | 0.00 336 | 0.00 333 | 91.11 192 | 95.89 181 |
|
wuyk23d | | | 25.11 308 | 24.57 310 | 26.74 321 | 73.98 325 | 39.89 335 | 57.88 328 | 9.80 336 | 12.27 330 | 10.39 331 | 6.97 334 | 7.03 336 | 36.44 333 | 25.43 330 | 17.39 330 | 3.89 331 |
|
test123 | | | 13.04 311 | 15.66 312 | 5.18 322 | 4.51 336 | 3.45 336 | 92.50 288 | 1.81 338 | 2.50 332 | 7.58 333 | 20.15 331 | 3.67 339 | 2.18 335 | 7.13 332 | 1.07 333 | 9.90 328 |
|
testmvs | | | 13.36 310 | 16.33 311 | 4.48 323 | 5.04 335 | 2.26 337 | 93.18 274 | 3.28 337 | 2.70 331 | 8.24 332 | 21.66 330 | 2.29 340 | 2.19 334 | 7.58 331 | 2.96 331 | 9.00 329 |
|
cdsmvs_eth3d_5k | | | 23.24 309 | 30.99 309 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 97.63 103 | 0.00 333 | 0.00 334 | 96.88 102 | 84.38 120 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
pcd_1.5k_mvsjas | | | 7.39 313 | 9.85 314 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 88.65 68 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
sosnet-low-res | | | 0.00 314 | 0.00 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
sosnet | | | 0.00 314 | 0.00 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
uncertanet | | | 0.00 314 | 0.00 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
Regformer | | | 0.00 314 | 0.00 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
ab-mvs-re | | | 8.06 312 | 10.74 313 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 96.69 111 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
uanet | | | 0.00 314 | 0.00 315 | 0.00 324 | 0.00 337 | 0.00 338 | 0.00 329 | 0.00 339 | 0.00 333 | 0.00 334 | 0.00 335 | 0.00 341 | 0.00 336 | 0.00 333 | 0.00 334 | 0.00 332 |
|
sam_mvs1 | | | | | | | | | | | | | 82.76 156 | | | | |
|
sam_mvs | | | | | | | | | | | | | 81.94 177 | | | | |
|
MTGPA | | | | | | | | | 98.08 47 | | | | | | | | |
|
test_post1 | | | | | | | | 92.81 284 | | | | 16.58 333 | 80.53 199 | 97.68 236 | 86.20 206 | | |
|
test_post | | | | | | | | | | | | 17.58 332 | 81.76 179 | 98.08 179 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 90.45 280 | 82.65 160 | 98.10 176 | | | |
|
MTMP | | | | | | | | | 82.03 329 | | | | | | | | |
|
gm-plane-assit | | | | | | 93.22 274 | 78.89 298 | | | 84.82 254 | | 93.52 244 | | 98.64 136 | 87.72 176 | | |
|
test9_res | | | | | | | | | | | | | | | 94.81 59 | 99.38 33 | 99.45 28 |
|
TEST9 | | | | | | 98.70 36 | 94.19 21 | 96.41 170 | 98.02 64 | 88.17 196 | 96.03 52 | 97.56 80 | 92.74 12 | 99.59 49 | | | |
|
test_8 | | | | | | 98.67 38 | 94.06 27 | 96.37 177 | 98.01 66 | 88.58 181 | 95.98 57 | 97.55 82 | 92.73 13 | 99.58 53 | | | |
|
agg_prior2 | | | | | | | | | | | | | | | 93.94 71 | 99.38 33 | 99.50 22 |
|
agg_prior | | | | | | 98.67 38 | 93.79 34 | | 98.00 68 | | 95.68 66 | | | 99.57 61 | | | |
|
test_prior4 | | | | | | | 93.66 38 | 96.42 169 | | | | | | | | | |
|
test_prior2 | | | | | | | | 96.35 178 | | 92.80 77 | 96.03 52 | 97.59 76 | 92.01 28 | | 95.01 52 | 99.38 33 | |
|
旧先验2 | | | | | | | | 95.94 207 | | 81.66 281 | 97.34 15 | | | 98.82 124 | 92.26 94 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 95.79 214 | | | | | | | | | |
|
旧先验1 | | | | | | 98.38 58 | 93.38 46 | | 97.75 88 | | | 98.09 41 | 92.30 25 | | | 99.01 61 | 99.16 50 |
|
æ— å…ˆéªŒ | | | | | | | | 95.79 214 | 97.87 80 | 83.87 265 | | | | 99.65 37 | 87.68 179 | | 98.89 77 |
|
原ACMM2 | | | | | | | | 95.67 218 | | | | | | | | | |
|
test222 | | | | | | 98.24 69 | 92.21 73 | 95.33 233 | 97.60 104 | 79.22 296 | 95.25 74 | 97.84 57 | 88.80 66 | | | 99.15 51 | 98.72 85 |
|
testdata2 | | | | | | | | | | | | | | 99.67 35 | 85.96 213 | | |
|
segment_acmp | | | | | | | | | | | | | 92.89 10 | | | | |
|
testdata1 | | | | | | | | 95.26 239 | | 93.10 65 | | | | | | | |
|
plane_prior7 | | | | | | 96.21 142 | 89.98 136 | | | | | | | | | | |
|
plane_prior6 | | | | | | 96.10 153 | 90.00 132 | | | | | | 81.32 185 | | | | |
|
plane_prior5 | | | | | | | | | 97.51 113 | | | | | 98.60 140 | 93.02 89 | 92.23 171 | 95.86 182 |
|
plane_prior4 | | | | | | | | | | | | 96.64 114 | | | | | |
|
plane_prior3 | | | | | | | 90.00 132 | | | 94.46 29 | 91.34 138 | | | | | | |
|
plane_prior2 | | | | | | | | 97.74 50 | | 94.85 16 | | | | | | | |
|
plane_prior1 | | | | | | 96.14 150 | | | | | | | | | | | |
|
plane_prior | | | | | | | 89.99 134 | 97.24 93 | | 94.06 38 | | | | | | 92.16 175 | |
|
n2 | | | | | | | | | 0.00 339 | | | | | | | | |
|
nn | | | | | | | | | 0.00 339 | | | | | | | | |
|
door-mid | | | | | | | | | 91.06 314 | | | | | | | | |
|
test11 | | | | | | | | | 97.88 78 | | | | | | | | |
|
door | | | | | | | | | 91.13 313 | | | | | | | | |
|
HQP5-MVS | | | | | | | 89.33 158 | | | | | | | | | | |
|
HQP-NCC | | | | | | 95.86 158 | | 96.65 154 | | 93.55 48 | 90.14 160 | | | | | | |
|
ACMP_Plane | | | | | | 95.86 158 | | 96.65 154 | | 93.55 48 | 90.14 160 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 92.13 100 | | |
|
HQP4-MVS | | | | | | | | | | | 90.14 160 | | | 98.50 149 | | | 95.78 189 |
|
HQP3-MVS | | | | | | | | | 97.39 132 | | | | | | | 92.10 176 | |
|
HQP2-MVS | | | | | | | | | | | | | 80.95 189 | | | | |
|
NP-MVS | | | | | | 95.99 156 | 89.81 142 | | | | | 95.87 150 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 70.35 312 | 93.10 280 | | 83.88 264 | 93.55 98 | | 82.47 165 | | 86.25 205 | | 98.38 112 |
|
MDTV_nov1_ep13 | | | | 90.76 174 | | 95.22 187 | 80.33 286 | 93.03 281 | 95.28 256 | 88.14 197 | 92.84 112 | 93.83 234 | 81.34 184 | 98.08 179 | 82.86 255 | 94.34 153 | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 90.30 204 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 91.02 194 | |
|
Test By Simon | | | | | | | | | | | | | 88.73 67 | | | | |
|