HSP-MVS | | | 89.28 1 | 89.76 1 | 87.85 17 | 94.28 15 | 73.46 14 | 92.90 8 | 92.73 36 | 80.27 12 | 91.35 1 | 94.16 20 | 78.35 2 | 96.77 7 | 89.59 1 | 94.22 41 | 93.33 51 |
|
APDe-MVS | | | 89.15 2 | 89.63 2 | 87.73 19 | 94.49 8 | 71.69 40 | 93.83 2 | 93.96 2 | 75.70 71 | 91.06 2 | 96.03 1 | 76.84 3 | 97.03 3 | 89.09 2 | 95.65 13 | 94.47 11 |
|
HPM-MVS++ | | | 89.02 3 | 89.15 3 | 88.63 1 | 95.01 1 | 76.03 1 | 92.38 14 | 92.85 32 | 80.26 13 | 87.78 11 | 94.27 16 | 75.89 7 | 96.81 6 | 87.45 9 | 96.44 1 | 93.05 61 |
|
CNVR-MVS | | | 88.93 4 | 89.13 4 | 88.33 3 | 94.77 2 | 73.82 6 | 90.51 39 | 93.00 24 | 80.90 9 | 88.06 9 | 94.06 24 | 76.43 4 | 96.84 5 | 88.48 4 | 95.99 4 | 94.34 14 |
|
SteuartSystems-ACMMP | | | 88.72 5 | 88.86 5 | 88.32 4 | 92.14 52 | 72.96 19 | 93.73 3 | 93.67 6 | 80.19 14 | 88.10 8 | 94.80 4 | 73.76 20 | 97.11 1 | 87.51 8 | 95.82 8 | 94.90 4 |
Skip Steuart: Steuart Systems R&D Blog. |
DeepPCF-MVS | | 80.84 1 | 88.10 6 | 88.56 6 | 86.73 38 | 92.24 50 | 69.03 78 | 89.57 61 | 93.39 13 | 77.53 38 | 89.79 4 | 94.12 22 | 78.98 1 | 96.58 19 | 85.66 12 | 95.72 9 | 94.58 7 |
|
SD-MVS | | | 88.06 7 | 88.50 7 | 86.71 39 | 92.60 48 | 72.71 24 | 91.81 23 | 93.19 18 | 77.87 31 | 90.32 3 | 94.00 25 | 74.83 10 | 93.78 111 | 87.63 7 | 94.27 40 | 93.65 40 |
|
NCCC | | | 88.06 7 | 88.01 10 | 88.24 5 | 94.41 12 | 73.62 7 | 91.22 30 | 92.83 33 | 81.50 6 | 85.79 21 | 93.47 33 | 73.02 24 | 97.00 4 | 84.90 17 | 94.94 24 | 94.10 20 |
|
ACMMP_Plus | | | 88.05 9 | 88.08 9 | 87.94 10 | 93.70 23 | 73.05 18 | 90.86 33 | 93.59 7 | 76.27 64 | 88.14 7 | 95.09 3 | 71.06 36 | 96.67 12 | 87.67 6 | 96.37 2 | 94.09 21 |
|
TSAR-MVS + MP. | | | 88.02 10 | 88.11 8 | 87.72 21 | 93.68 25 | 72.13 36 | 91.41 26 | 92.35 46 | 74.62 88 | 88.90 5 | 93.85 27 | 75.75 8 | 96.00 32 | 87.80 5 | 94.63 31 | 95.04 2 |
|
MP-MVS | | | 87.71 11 | 87.64 12 | 87.93 13 | 94.36 14 | 73.88 4 | 92.71 13 | 92.65 39 | 77.57 34 | 83.84 47 | 94.40 15 | 72.24 30 | 96.28 24 | 85.65 13 | 95.30 21 | 93.62 42 |
|
MP-MVS-pluss | | | 87.67 12 | 87.72 11 | 87.54 26 | 93.64 26 | 72.04 37 | 89.80 55 | 93.50 9 | 75.17 82 | 86.34 16 | 95.29 2 | 70.86 37 | 96.00 32 | 88.78 3 | 96.04 3 | 94.58 7 |
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss |
HFP-MVS | | | 87.58 13 | 87.47 14 | 87.94 10 | 94.58 5 | 73.54 11 | 93.04 5 | 93.24 15 | 76.78 51 | 84.91 29 | 94.44 12 | 70.78 38 | 96.61 15 | 84.53 22 | 94.89 26 | 93.66 35 |
|
MPTG | | | 87.53 14 | 87.41 15 | 87.90 14 | 94.18 19 | 74.25 2 | 90.23 47 | 92.02 56 | 79.45 18 | 85.88 18 | 94.80 4 | 68.07 56 | 96.21 26 | 86.69 10 | 95.34 17 | 93.23 53 |
|
ACMMPR | | | 87.44 15 | 87.23 17 | 88.08 7 | 94.64 3 | 73.59 8 | 93.04 5 | 93.20 17 | 76.78 51 | 84.66 35 | 94.52 7 | 68.81 54 | 96.65 13 | 84.53 22 | 94.90 25 | 94.00 27 |
|
APD-MVS | | | 87.44 15 | 87.52 13 | 87.19 30 | 94.24 16 | 72.39 32 | 91.86 22 | 92.83 33 | 73.01 115 | 88.58 6 | 94.52 7 | 73.36 21 | 96.49 20 | 84.26 26 | 95.01 23 | 92.70 68 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
region2R | | | 87.42 17 | 87.20 18 | 88.09 6 | 94.63 4 | 73.55 9 | 93.03 7 | 93.12 20 | 76.73 54 | 84.45 38 | 94.52 7 | 69.09 52 | 96.70 10 | 84.37 25 | 94.83 28 | 94.03 24 |
|
MCST-MVS | | | 87.37 18 | 87.25 16 | 87.73 19 | 94.53 7 | 72.46 31 | 89.82 53 | 93.82 4 | 73.07 114 | 84.86 34 | 92.89 45 | 76.22 5 | 96.33 22 | 84.89 19 | 95.13 22 | 94.40 12 |
|
#test# | | | 87.33 19 | 87.13 19 | 87.94 10 | 94.58 5 | 73.54 11 | 92.34 15 | 93.24 15 | 75.23 79 | 84.91 29 | 94.44 12 | 70.78 38 | 96.61 15 | 83.75 29 | 94.89 26 | 93.66 35 |
|
MTAPA | | | 87.23 20 | 87.00 20 | 87.90 14 | 94.18 19 | 74.25 2 | 86.58 159 | 92.02 56 | 79.45 18 | 85.88 18 | 94.80 4 | 68.07 56 | 96.21 26 | 86.69 10 | 95.34 17 | 93.23 53 |
|
XVS | | | 87.18 21 | 86.91 23 | 88.00 8 | 94.42 10 | 73.33 16 | 92.78 9 | 92.99 26 | 79.14 20 | 83.67 50 | 94.17 19 | 67.45 63 | 96.60 17 | 83.06 35 | 94.50 33 | 94.07 22 |
|
HPM-MVS | | | 87.11 22 | 86.98 21 | 87.50 27 | 93.88 22 | 72.16 35 | 92.19 18 | 93.33 14 | 76.07 67 | 83.81 48 | 93.95 26 | 69.77 47 | 96.01 31 | 85.15 14 | 94.66 30 | 94.32 15 |
|
CP-MVS | | | 87.11 22 | 86.92 22 | 87.68 24 | 94.20 18 | 73.86 5 | 93.98 1 | 92.82 35 | 76.62 56 | 83.68 49 | 94.46 11 | 67.93 58 | 95.95 34 | 84.20 27 | 94.39 36 | 93.23 53 |
|
DeepC-MVS | | 79.81 2 | 87.08 24 | 86.88 24 | 87.69 23 | 91.16 62 | 72.32 34 | 90.31 45 | 93.94 3 | 77.12 43 | 82.82 59 | 94.23 18 | 72.13 31 | 97.09 2 | 84.83 20 | 95.37 16 | 93.65 40 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DeepC-MVS_fast | | 79.65 3 | 86.91 25 | 86.62 26 | 87.76 18 | 93.52 28 | 72.37 33 | 91.26 27 | 93.04 21 | 76.62 56 | 84.22 43 | 93.36 35 | 71.44 34 | 96.76 8 | 80.82 50 | 95.33 19 | 94.16 18 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
test_prior3 | | | 86.73 26 | 86.86 25 | 86.33 45 | 92.61 46 | 69.59 70 | 88.85 78 | 92.97 29 | 75.41 75 | 84.91 29 | 93.54 29 | 74.28 17 | 95.48 42 | 83.31 31 | 95.86 6 | 93.91 29 |
|
PGM-MVS | | | 86.68 27 | 86.27 30 | 87.90 14 | 94.22 17 | 73.38 15 | 90.22 48 | 93.04 21 | 75.53 73 | 83.86 46 | 94.42 14 | 67.87 60 | 96.64 14 | 82.70 40 | 94.57 32 | 93.66 35 |
|
mPP-MVS | | | 86.67 28 | 86.32 29 | 87.72 21 | 94.41 12 | 73.55 9 | 92.74 11 | 92.22 49 | 76.87 49 | 82.81 60 | 94.25 17 | 66.44 70 | 96.24 25 | 82.88 39 | 94.28 39 | 93.38 48 |
|
Regformer-2 | | | 86.63 29 | 86.53 27 | 86.95 35 | 89.33 91 | 71.24 44 | 88.43 91 | 92.05 55 | 82.50 1 | 86.88 14 | 90.09 93 | 74.45 12 | 95.61 38 | 84.38 24 | 90.63 67 | 94.01 26 |
|
train_agg | | | 86.43 30 | 86.20 31 | 87.13 32 | 93.26 33 | 72.96 19 | 88.75 83 | 91.89 65 | 68.69 184 | 85.00 27 | 93.10 39 | 74.43 13 | 95.41 47 | 84.97 15 | 95.71 10 | 93.02 62 |
|
PHI-MVS | | | 86.43 30 | 86.17 33 | 87.24 29 | 90.88 67 | 70.96 47 | 92.27 17 | 94.07 1 | 72.45 126 | 85.22 25 | 91.90 57 | 69.47 49 | 96.42 21 | 83.28 33 | 95.94 5 | 94.35 13 |
|
Regformer-1 | | | 86.41 32 | 86.33 28 | 86.64 40 | 89.33 91 | 70.93 49 | 88.43 91 | 91.39 85 | 82.14 3 | 86.65 15 | 90.09 93 | 74.39 15 | 95.01 63 | 83.97 28 | 90.63 67 | 93.97 28 |
|
CSCG | | | 86.41 32 | 86.19 32 | 87.07 34 | 92.91 40 | 72.48 30 | 90.81 34 | 93.56 8 | 73.95 96 | 83.16 55 | 91.07 74 | 75.94 6 | 95.19 54 | 79.94 57 | 94.38 37 | 93.55 44 |
|
agg_prior1 | | | 86.22 34 | 86.09 34 | 86.62 41 | 92.85 41 | 71.94 38 | 88.59 88 | 91.78 71 | 68.96 181 | 84.41 39 | 93.18 38 | 74.94 9 | 94.93 64 | 84.75 21 | 95.33 19 | 93.01 64 |
|
agg_prior3 | | | 86.16 35 | 85.85 37 | 87.10 33 | 93.31 30 | 72.86 23 | 88.77 81 | 91.68 75 | 68.29 190 | 84.26 42 | 92.83 47 | 72.83 25 | 95.42 46 | 84.97 15 | 95.71 10 | 93.02 62 |
|
APD-MVS_3200maxsize | | | 85.97 36 | 85.88 35 | 86.22 48 | 92.69 44 | 69.53 72 | 91.93 21 | 92.99 26 | 73.54 103 | 85.94 17 | 94.51 10 | 65.80 77 | 95.61 38 | 83.04 37 | 92.51 52 | 93.53 46 |
|
canonicalmvs | | | 85.91 37 | 85.87 36 | 86.04 52 | 89.84 81 | 69.44 76 | 90.45 43 | 93.00 24 | 76.70 55 | 88.01 10 | 91.23 71 | 73.28 22 | 93.91 102 | 81.50 46 | 88.80 85 | 94.77 5 |
|
ACMMP | | | 85.89 38 | 85.39 40 | 87.38 28 | 93.59 27 | 72.63 26 | 92.74 11 | 93.18 19 | 76.78 51 | 80.73 80 | 93.82 28 | 64.33 85 | 96.29 23 | 82.67 41 | 90.69 66 | 93.23 53 |
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 |
CDPH-MVS | | | 85.76 39 | 85.29 44 | 87.17 31 | 93.49 29 | 71.08 45 | 88.58 89 | 92.42 44 | 68.32 189 | 84.61 36 | 93.48 31 | 72.32 29 | 96.15 29 | 79.00 59 | 95.43 15 | 94.28 17 |
|
TSAR-MVS + GP. | | | 85.71 40 | 85.33 41 | 86.84 36 | 91.34 60 | 72.50 29 | 89.07 73 | 87.28 200 | 76.41 58 | 85.80 20 | 90.22 91 | 74.15 19 | 95.37 51 | 81.82 44 | 91.88 54 | 92.65 71 |
|
Regformer-4 | | | 85.68 41 | 85.45 39 | 86.35 44 | 88.95 104 | 69.67 69 | 88.29 100 | 91.29 87 | 81.73 4 | 85.36 23 | 90.01 95 | 72.62 27 | 95.35 52 | 83.28 33 | 87.57 100 | 94.03 24 |
|
alignmvs | | | 85.48 42 | 85.32 42 | 85.96 53 | 89.51 87 | 69.47 74 | 89.74 57 | 92.47 40 | 76.17 65 | 87.73 12 | 91.46 69 | 70.32 41 | 93.78 111 | 81.51 45 | 88.95 82 | 94.63 6 |
|
3Dnovator+ | | 77.84 4 | 85.48 42 | 84.47 51 | 88.51 2 | 91.08 63 | 73.49 13 | 93.18 4 | 93.78 5 | 80.79 10 | 76.66 141 | 93.37 34 | 60.40 159 | 96.75 9 | 77.20 77 | 93.73 44 | 95.29 1 |
|
MVS_0305 | | | 85.44 44 | 84.74 50 | 87.55 25 | 89.80 83 | 71.64 41 | 89.65 59 | 90.50 106 | 81.57 5 | 80.44 82 | 90.58 85 | 63.40 93 | 96.68 11 | 83.43 30 | 93.30 45 | 94.31 16 |
|
MSLP-MVS++ | | | 85.43 45 | 85.76 38 | 84.45 80 | 91.93 55 | 70.24 57 | 90.71 36 | 92.86 31 | 77.46 40 | 84.22 43 | 92.81 50 | 67.16 66 | 92.94 151 | 80.36 53 | 94.35 38 | 90.16 146 |
|
DELS-MVS | | | 85.41 46 | 85.30 43 | 85.77 54 | 88.49 120 | 67.93 106 | 85.52 188 | 93.44 11 | 78.70 27 | 83.63 52 | 89.03 116 | 74.57 11 | 95.71 37 | 80.26 55 | 94.04 42 | 93.66 35 |
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 |
HPM-MVS_fast | | | 85.35 47 | 84.95 47 | 86.57 43 | 93.69 24 | 70.58 55 | 92.15 19 | 91.62 76 | 73.89 97 | 82.67 62 | 94.09 23 | 62.60 119 | 95.54 41 | 80.93 48 | 92.93 47 | 93.57 43 |
|
Regformer-3 | | | 85.23 48 | 85.07 45 | 85.70 55 | 88.95 104 | 69.01 80 | 88.29 100 | 89.91 133 | 80.95 8 | 85.01 26 | 90.01 95 | 72.45 28 | 94.19 89 | 82.50 42 | 87.57 100 | 93.90 31 |
|
abl_6 | | | 85.23 48 | 84.95 47 | 86.07 51 | 92.23 51 | 70.48 56 | 90.80 35 | 92.08 54 | 73.51 104 | 85.26 24 | 94.16 20 | 62.75 112 | 95.92 35 | 82.46 43 | 91.30 61 | 91.81 95 |
|
MVS_111021_HR | | | 85.14 50 | 84.75 49 | 86.32 47 | 91.65 58 | 72.70 25 | 85.98 174 | 90.33 115 | 76.11 66 | 82.08 65 | 91.61 64 | 71.36 35 | 94.17 91 | 81.02 47 | 92.58 51 | 92.08 88 |
|
UA-Net | | | 85.08 51 | 84.96 46 | 85.45 56 | 92.07 53 | 68.07 104 | 89.78 56 | 90.86 97 | 82.48 2 | 84.60 37 | 93.20 37 | 69.35 50 | 95.22 53 | 71.39 139 | 90.88 65 | 93.07 60 |
|
EI-MVSNet-Vis-set | | | 84.19 52 | 83.81 52 | 85.31 58 | 88.18 129 | 67.85 107 | 87.66 115 | 89.73 137 | 80.05 16 | 82.95 56 | 89.59 102 | 70.74 40 | 94.82 71 | 80.66 52 | 84.72 131 | 93.28 52 |
|
nrg030 | | | 83.88 53 | 83.53 53 | 84.96 68 | 86.77 162 | 69.28 77 | 90.46 42 | 92.67 37 | 74.79 86 | 82.95 56 | 91.33 70 | 72.70 26 | 93.09 145 | 80.79 51 | 79.28 184 | 92.50 74 |
|
EI-MVSNet-UG-set | | | 83.81 54 | 83.38 55 | 85.09 65 | 87.87 136 | 67.53 111 | 87.44 126 | 89.66 138 | 79.74 17 | 82.23 64 | 89.41 111 | 70.24 42 | 94.74 73 | 79.95 56 | 83.92 137 | 92.99 65 |
|
CPTT-MVS | | | 83.73 55 | 83.33 56 | 84.92 71 | 93.28 32 | 70.86 51 | 92.09 20 | 90.38 110 | 68.75 183 | 79.57 86 | 92.83 47 | 60.60 155 | 93.04 148 | 80.92 49 | 91.56 58 | 90.86 116 |
|
EPNet | | | 83.72 56 | 82.92 62 | 86.14 50 | 84.22 192 | 69.48 73 | 91.05 32 | 85.27 220 | 81.30 7 | 76.83 138 | 91.65 61 | 66.09 73 | 95.56 40 | 76.00 88 | 93.85 43 | 93.38 48 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
HQP_MVS | | | 83.64 57 | 83.14 57 | 85.14 63 | 90.08 76 | 68.71 90 | 91.25 28 | 92.44 41 | 79.12 22 | 78.92 93 | 91.00 78 | 60.42 157 | 95.38 49 | 78.71 62 | 86.32 118 | 91.33 104 |
|
Effi-MVS+ | | | 83.62 58 | 83.08 58 | 85.24 61 | 88.38 125 | 67.45 112 | 88.89 76 | 89.15 154 | 75.50 74 | 82.27 63 | 88.28 133 | 69.61 48 | 94.45 80 | 77.81 71 | 87.84 98 | 93.84 33 |
|
OPM-MVS | | | 83.50 59 | 82.95 61 | 85.14 63 | 88.79 112 | 70.95 48 | 89.13 72 | 91.52 80 | 77.55 37 | 80.96 78 | 91.75 59 | 60.71 151 | 94.50 79 | 79.67 58 | 86.51 116 | 89.97 158 |
|
Vis-MVSNet | | | 83.46 60 | 82.80 64 | 85.43 57 | 90.25 74 | 68.74 88 | 90.30 46 | 90.13 124 | 76.33 63 | 80.87 79 | 92.89 45 | 61.00 148 | 94.20 88 | 72.45 127 | 90.97 63 | 93.35 50 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MG-MVS | | | 83.41 61 | 83.45 54 | 83.28 116 | 92.74 43 | 62.28 214 | 88.17 104 | 89.50 142 | 75.22 80 | 81.49 71 | 92.74 51 | 66.75 67 | 95.11 57 | 72.85 120 | 91.58 57 | 92.45 75 |
|
EPP-MVSNet | | | 83.40 62 | 83.02 60 | 84.57 76 | 90.13 75 | 64.47 176 | 92.32 16 | 90.73 98 | 74.45 90 | 79.35 89 | 91.10 72 | 69.05 53 | 95.12 56 | 72.78 121 | 87.22 107 | 94.13 19 |
|
3Dnovator | | 76.31 5 | 83.38 63 | 82.31 69 | 86.59 42 | 87.94 135 | 72.94 22 | 90.64 37 | 92.14 53 | 77.21 41 | 75.47 155 | 92.83 47 | 58.56 166 | 94.72 74 | 73.24 117 | 92.71 50 | 92.13 86 |
|
MVS_Test | | | 83.15 64 | 83.06 59 | 83.41 113 | 86.86 159 | 63.21 200 | 86.11 172 | 92.00 59 | 74.31 91 | 82.87 58 | 89.44 110 | 70.03 43 | 93.21 136 | 77.39 76 | 88.50 94 | 93.81 34 |
|
IS-MVSNet | | | 83.15 64 | 82.81 63 | 84.18 89 | 89.94 79 | 63.30 197 | 91.59 24 | 88.46 181 | 79.04 24 | 79.49 87 | 92.16 52 | 65.10 81 | 94.28 83 | 67.71 159 | 91.86 55 | 94.95 3 |
|
DP-MVS Recon | | | 83.11 66 | 82.09 71 | 86.15 49 | 94.44 9 | 70.92 50 | 88.79 80 | 92.20 50 | 70.53 153 | 79.17 90 | 91.03 77 | 64.12 87 | 96.03 30 | 68.39 158 | 90.14 72 | 91.50 101 |
|
PAPM_NR | | | 83.02 67 | 82.41 66 | 84.82 73 | 92.47 49 | 66.37 129 | 87.93 111 | 91.80 69 | 73.82 98 | 77.32 130 | 90.66 83 | 67.90 59 | 94.90 68 | 70.37 143 | 89.48 79 | 93.19 57 |
|
VDD-MVS | | | 83.01 68 | 82.36 68 | 84.96 68 | 91.02 64 | 66.40 128 | 88.91 75 | 88.11 184 | 77.57 34 | 84.39 41 | 93.29 36 | 52.19 214 | 93.91 102 | 77.05 80 | 88.70 87 | 94.57 9 |
|
MVSFormer | | | 82.85 69 | 82.05 72 | 85.24 61 | 87.35 149 | 70.21 58 | 90.50 40 | 90.38 110 | 68.55 186 | 81.32 72 | 89.47 105 | 61.68 133 | 93.46 127 | 78.98 60 | 90.26 70 | 92.05 89 |
|
OMC-MVS | | | 82.69 70 | 81.97 75 | 84.85 72 | 88.75 114 | 67.42 113 | 87.98 107 | 90.87 96 | 74.92 85 | 79.72 85 | 91.65 61 | 62.19 130 | 93.96 97 | 75.26 100 | 86.42 117 | 93.16 58 |
|
PVSNet_Blended_VisFu | | | 82.62 71 | 81.83 76 | 84.96 68 | 90.80 69 | 69.76 67 | 88.74 85 | 91.70 74 | 69.39 167 | 78.96 92 | 88.46 129 | 65.47 78 | 94.87 70 | 74.42 104 | 88.57 90 | 90.24 144 |
|
MVS_111021_LR | | | 82.61 72 | 82.11 70 | 84.11 90 | 88.82 109 | 71.58 42 | 85.15 191 | 86.16 213 | 74.69 87 | 80.47 81 | 91.04 75 | 62.29 127 | 90.55 211 | 80.33 54 | 90.08 73 | 90.20 145 |
|
HQP-MVS | | | 82.61 72 | 82.02 73 | 84.37 82 | 89.33 91 | 66.98 121 | 89.17 67 | 92.19 51 | 76.41 58 | 77.23 133 | 90.23 90 | 60.17 160 | 95.11 57 | 77.47 74 | 85.99 122 | 91.03 110 |
|
CLD-MVS | | | 82.31 74 | 81.65 77 | 84.29 86 | 88.47 121 | 67.73 110 | 85.81 180 | 92.35 46 | 75.78 69 | 78.33 107 | 86.58 181 | 64.01 88 | 94.35 81 | 76.05 87 | 87.48 105 | 90.79 117 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
VNet | | | 82.21 75 | 82.41 66 | 81.62 176 | 90.82 68 | 60.93 221 | 84.47 203 | 89.78 135 | 76.36 62 | 84.07 45 | 91.88 58 | 64.71 84 | 90.26 213 | 70.68 140 | 88.89 83 | 93.66 35 |
|
LPG-MVS_test | | | 82.08 76 | 81.27 80 | 84.50 78 | 89.23 99 | 68.76 86 | 90.22 48 | 91.94 63 | 75.37 77 | 76.64 142 | 91.51 66 | 54.29 198 | 94.91 66 | 78.44 64 | 83.78 138 | 89.83 162 |
|
FIs | | | 82.07 77 | 82.42 65 | 81.04 189 | 88.80 111 | 58.34 240 | 88.26 102 | 93.49 10 | 76.93 48 | 78.47 101 | 91.04 75 | 69.92 45 | 92.34 169 | 69.87 147 | 84.97 127 | 92.44 76 |
|
PS-MVSNAJss | | | 82.07 77 | 81.31 79 | 84.34 85 | 86.51 164 | 67.27 117 | 89.27 65 | 91.51 81 | 71.75 135 | 79.37 88 | 90.22 91 | 63.15 100 | 94.27 84 | 77.69 72 | 82.36 154 | 91.49 102 |
|
API-MVS | | | 81.99 79 | 81.23 81 | 84.26 87 | 90.94 65 | 70.18 63 | 91.10 31 | 89.32 147 | 71.51 141 | 78.66 97 | 88.28 133 | 65.26 79 | 95.10 60 | 64.74 186 | 91.23 62 | 87.51 223 |
|
UniMVSNet_NR-MVSNet | | | 81.88 80 | 81.54 78 | 82.92 136 | 88.46 122 | 63.46 193 | 87.13 138 | 92.37 45 | 80.19 14 | 78.38 105 | 89.14 113 | 71.66 33 | 93.05 146 | 70.05 144 | 76.46 217 | 92.25 82 |
|
MAR-MVS | | | 81.84 81 | 80.70 87 | 85.27 60 | 91.32 61 | 71.53 43 | 89.82 53 | 90.92 95 | 69.77 162 | 78.50 99 | 86.21 191 | 62.36 126 | 94.52 78 | 65.36 180 | 92.05 53 | 89.77 165 |
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 |
LFMVS | | | 81.82 82 | 81.23 81 | 83.57 108 | 91.89 56 | 63.43 195 | 89.84 52 | 81.85 252 | 77.04 46 | 83.21 53 | 93.10 39 | 52.26 213 | 93.43 131 | 71.98 133 | 89.95 75 | 93.85 32 |
|
xiu_mvs_v2_base | | | 81.69 83 | 81.05 84 | 83.60 106 | 89.15 102 | 68.03 105 | 84.46 205 | 90.02 129 | 70.67 151 | 81.30 74 | 86.53 184 | 63.17 99 | 94.19 89 | 75.60 96 | 88.54 92 | 88.57 201 |
|
PS-MVSNAJ | | | 81.69 83 | 81.02 85 | 83.70 104 | 89.51 87 | 68.21 102 | 84.28 211 | 90.09 125 | 70.79 148 | 81.26 75 | 85.62 203 | 63.15 100 | 94.29 82 | 75.62 95 | 88.87 84 | 88.59 199 |
|
PAPR | | | 81.66 85 | 80.89 86 | 83.99 98 | 90.27 73 | 64.00 186 | 86.76 154 | 91.77 73 | 68.84 182 | 77.13 137 | 89.50 103 | 67.63 61 | 94.88 69 | 67.55 161 | 88.52 93 | 93.09 59 |
|
UniMVSNet (Re) | | | 81.60 86 | 81.11 83 | 83.09 124 | 88.38 125 | 64.41 178 | 87.60 116 | 93.02 23 | 78.42 30 | 78.56 98 | 88.16 135 | 69.78 46 | 93.26 135 | 69.58 149 | 76.49 216 | 91.60 97 |
|
FC-MVSNet-test | | | 81.52 87 | 82.02 73 | 80.03 204 | 88.42 124 | 55.97 270 | 87.95 109 | 93.42 12 | 77.10 44 | 77.38 128 | 90.98 80 | 69.96 44 | 91.79 177 | 68.46 157 | 84.50 132 | 92.33 78 |
|
VDDNet | | | 81.52 87 | 80.67 88 | 84.05 93 | 90.44 71 | 64.13 182 | 89.73 58 | 85.91 216 | 71.11 144 | 83.18 54 | 93.48 31 | 50.54 232 | 93.49 126 | 73.40 116 | 88.25 96 | 94.54 10 |
|
ACMP | | 74.13 6 | 81.51 89 | 80.57 89 | 84.36 83 | 89.42 89 | 68.69 93 | 89.97 51 | 91.50 83 | 74.46 89 | 75.04 171 | 90.41 87 | 53.82 203 | 94.54 76 | 77.56 73 | 82.91 146 | 89.86 161 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
jason | | | 81.39 90 | 80.29 94 | 84.70 75 | 86.63 163 | 69.90 65 | 85.95 175 | 86.77 204 | 63.24 232 | 81.07 77 | 89.47 105 | 61.08 147 | 92.15 173 | 78.33 67 | 90.07 74 | 92.05 89 |
jason: jason. |
lupinMVS | | | 81.39 90 | 80.27 95 | 84.76 74 | 87.35 149 | 70.21 58 | 85.55 185 | 86.41 208 | 62.85 238 | 81.32 72 | 88.61 124 | 61.68 133 | 92.24 172 | 78.41 66 | 90.26 70 | 91.83 93 |
|
DU-MVS | | | 81.12 92 | 80.52 91 | 82.90 137 | 87.80 139 | 63.46 193 | 87.02 143 | 91.87 67 | 79.01 25 | 78.38 105 | 89.07 114 | 65.02 82 | 93.05 146 | 70.05 144 | 76.46 217 | 92.20 83 |
|
PVSNet_Blended | | | 80.98 93 | 80.34 92 | 82.90 137 | 88.85 106 | 65.40 145 | 84.43 207 | 92.00 59 | 67.62 194 | 78.11 116 | 85.05 215 | 66.02 75 | 94.27 84 | 71.52 137 | 89.50 78 | 89.01 181 |
|
mvs-test1 | | | 80.88 94 | 79.40 112 | 85.29 59 | 85.13 179 | 69.75 68 | 89.28 64 | 88.10 186 | 74.99 83 | 76.44 145 | 86.72 168 | 57.27 175 | 94.26 87 | 73.53 114 | 83.18 144 | 91.87 92 |
|
QAPM | | | 80.88 94 | 79.50 110 | 85.03 66 | 88.01 134 | 68.97 82 | 91.59 24 | 92.00 59 | 66.63 203 | 75.15 168 | 92.16 52 | 57.70 171 | 95.45 44 | 63.52 190 | 88.76 86 | 90.66 125 |
|
1121 | | | 80.84 96 | 79.77 100 | 84.05 93 | 93.11 37 | 70.78 52 | 84.66 198 | 85.42 219 | 57.37 280 | 81.76 70 | 92.02 54 | 63.41 92 | 94.12 92 | 67.28 164 | 92.93 47 | 87.26 230 |
|
TranMVSNet+NR-MVSNet | | | 80.84 96 | 80.31 93 | 82.42 155 | 87.85 137 | 62.33 212 | 87.74 114 | 91.33 86 | 80.55 11 | 77.99 119 | 89.86 97 | 65.23 80 | 92.62 159 | 67.05 168 | 75.24 235 | 92.30 80 |
|
UGNet | | | 80.83 98 | 79.59 105 | 84.54 77 | 88.04 132 | 68.09 103 | 89.42 62 | 88.16 183 | 76.95 47 | 76.22 147 | 89.46 107 | 49.30 240 | 93.94 99 | 68.48 156 | 90.31 69 | 91.60 97 |
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 |
Fast-Effi-MVS+ | | | 80.81 99 | 79.92 98 | 83.47 109 | 88.85 106 | 64.51 170 | 85.53 187 | 89.39 145 | 70.79 148 | 78.49 100 | 85.06 214 | 67.54 62 | 93.58 122 | 67.03 169 | 86.58 114 | 92.32 79 |
|
XVG-OURS-SEG-HR | | | 80.81 99 | 79.76 101 | 83.96 100 | 85.60 173 | 68.78 85 | 83.54 222 | 90.50 106 | 70.66 152 | 76.71 140 | 91.66 60 | 60.69 152 | 91.26 194 | 76.94 81 | 81.58 160 | 91.83 93 |
|
xiu_mvs_v1_base_debu | | | 80.80 101 | 79.72 102 | 84.03 95 | 87.35 149 | 70.19 60 | 85.56 182 | 88.77 173 | 69.06 176 | 81.83 66 | 88.16 135 | 50.91 226 | 92.85 153 | 78.29 68 | 87.56 102 | 89.06 174 |
|
xiu_mvs_v1_base | | | 80.80 101 | 79.72 102 | 84.03 95 | 87.35 149 | 70.19 60 | 85.56 182 | 88.77 173 | 69.06 176 | 81.83 66 | 88.16 135 | 50.91 226 | 92.85 153 | 78.29 68 | 87.56 102 | 89.06 174 |
|
xiu_mvs_v1_base_debi | | | 80.80 101 | 79.72 102 | 84.03 95 | 87.35 149 | 70.19 60 | 85.56 182 | 88.77 173 | 69.06 176 | 81.83 66 | 88.16 135 | 50.91 226 | 92.85 153 | 78.29 68 | 87.56 102 | 89.06 174 |
|
ACMM | | 73.20 8 | 80.78 104 | 79.84 99 | 83.58 107 | 89.31 96 | 68.37 97 | 89.99 50 | 91.60 77 | 70.28 156 | 77.25 131 | 89.66 100 | 53.37 205 | 93.53 125 | 74.24 107 | 82.85 147 | 88.85 185 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
114514_t | | | 80.68 105 | 79.51 109 | 84.20 88 | 94.09 21 | 67.27 117 | 89.64 60 | 91.11 92 | 58.75 270 | 74.08 178 | 90.72 82 | 58.10 169 | 95.04 62 | 69.70 148 | 89.42 80 | 90.30 143 |
|
VPA-MVSNet | | | 80.60 106 | 80.55 90 | 80.76 193 | 88.07 131 | 60.80 224 | 86.86 148 | 91.58 78 | 75.67 72 | 80.24 83 | 89.45 109 | 63.34 94 | 90.25 214 | 70.51 142 | 79.22 185 | 91.23 107 |
|
PVSNet_BlendedMVS | | | 80.60 106 | 80.02 96 | 82.36 157 | 88.85 106 | 65.40 145 | 86.16 170 | 92.00 59 | 69.34 170 | 78.11 116 | 86.09 194 | 66.02 75 | 94.27 84 | 71.52 137 | 82.06 155 | 87.39 225 |
|
AdaColmap | | | 80.58 108 | 79.42 111 | 84.06 92 | 93.09 38 | 68.91 83 | 89.36 63 | 88.97 164 | 69.27 171 | 75.70 154 | 89.69 99 | 57.20 178 | 95.77 36 | 63.06 194 | 88.41 95 | 87.50 224 |
|
EI-MVSNet | | | 80.52 109 | 79.98 97 | 82.12 159 | 84.28 189 | 63.19 202 | 86.41 164 | 88.95 166 | 74.18 93 | 78.69 95 | 87.54 149 | 66.62 68 | 92.43 164 | 72.57 126 | 80.57 171 | 90.74 120 |
|
XVG-OURS | | | 80.41 110 | 79.23 122 | 83.97 99 | 85.64 172 | 69.02 79 | 83.03 225 | 90.39 109 | 71.09 145 | 77.63 125 | 91.49 68 | 54.62 196 | 91.35 192 | 75.71 93 | 83.47 140 | 91.54 99 |
|
v1neww | | | 80.40 111 | 79.54 106 | 82.98 131 | 84.10 200 | 64.51 170 | 87.57 118 | 90.22 119 | 73.25 107 | 78.47 101 | 86.65 176 | 62.83 108 | 93.86 105 | 75.72 91 | 77.02 203 | 90.58 131 |
|
v7new | | | 80.40 111 | 79.54 106 | 82.98 131 | 84.10 200 | 64.51 170 | 87.57 118 | 90.22 119 | 73.25 107 | 78.47 101 | 86.65 176 | 62.83 108 | 93.86 105 | 75.72 91 | 77.02 203 | 90.58 131 |
|
v6 | | | 80.40 111 | 79.54 106 | 82.98 131 | 84.09 202 | 64.50 174 | 87.57 118 | 90.22 119 | 73.25 107 | 78.47 101 | 86.63 178 | 62.84 107 | 93.86 105 | 75.73 90 | 77.02 203 | 90.58 131 |
|
PCF-MVS | | 73.52 7 | 80.38 114 | 78.84 128 | 85.01 67 | 87.71 142 | 68.99 81 | 83.65 219 | 91.46 84 | 63.00 235 | 77.77 123 | 90.28 88 | 66.10 72 | 95.09 61 | 61.40 210 | 88.22 97 | 90.94 114 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
X-MVStestdata | | | 80.37 115 | 77.83 150 | 88.00 8 | 94.42 10 | 73.33 16 | 92.78 9 | 92.99 26 | 79.14 20 | 83.67 50 | 12.47 327 | 67.45 63 | 96.60 17 | 83.06 35 | 94.50 33 | 94.07 22 |
|
test_djsdf | | | 80.30 116 | 79.32 115 | 83.27 117 | 83.98 209 | 65.37 148 | 90.50 40 | 90.38 110 | 68.55 186 | 76.19 148 | 88.70 120 | 56.44 182 | 93.46 127 | 78.98 60 | 80.14 178 | 90.97 113 |
|
v7 | | | 80.24 117 | 79.26 121 | 83.15 121 | 84.07 206 | 64.94 159 | 87.56 121 | 90.67 99 | 72.26 130 | 78.28 108 | 86.51 185 | 61.45 138 | 94.03 96 | 75.14 101 | 77.41 197 | 90.49 136 |
|
v2v482 | | | 80.23 118 | 79.29 119 | 83.05 127 | 83.62 218 | 64.14 181 | 87.04 142 | 89.97 130 | 73.61 100 | 78.18 115 | 87.22 158 | 61.10 146 | 93.82 108 | 76.11 86 | 76.78 214 | 91.18 108 |
|
NR-MVSNet | | | 80.23 118 | 79.38 113 | 82.78 147 | 87.80 139 | 63.34 196 | 86.31 167 | 91.09 93 | 79.01 25 | 72.17 197 | 89.07 114 | 67.20 65 | 92.81 157 | 66.08 175 | 75.65 226 | 92.20 83 |
|
v1141 | | | 80.19 120 | 79.31 116 | 82.85 140 | 83.84 212 | 64.12 183 | 87.14 135 | 90.08 126 | 73.13 110 | 78.27 109 | 86.39 187 | 62.67 117 | 93.75 115 | 75.40 98 | 76.83 211 | 90.68 122 |
|
divwei89l23v2f112 | | | 80.19 120 | 79.31 116 | 82.85 140 | 83.84 212 | 64.11 185 | 87.13 138 | 90.08 126 | 73.13 110 | 78.27 109 | 86.39 187 | 62.69 115 | 93.75 115 | 75.40 98 | 76.82 212 | 90.68 122 |
|
v1 | | | 80.19 120 | 79.31 116 | 82.85 140 | 83.83 214 | 64.12 183 | 87.14 135 | 90.07 128 | 73.13 110 | 78.27 109 | 86.38 189 | 62.72 114 | 93.75 115 | 75.41 97 | 76.82 212 | 90.68 122 |
|
MVS_dtu | | | 80.14 123 | 79.28 120 | 82.72 149 | 83.83 214 | 63.10 203 | 86.76 154 | 88.55 179 | 75.80 68 | 73.83 180 | 87.59 145 | 54.43 197 | 92.97 150 | 72.96 119 | 89.78 77 | 92.09 87 |
|
IterMVS-LS | | | 80.06 124 | 79.38 113 | 82.11 160 | 85.89 168 | 63.20 201 | 86.79 151 | 89.34 146 | 74.19 92 | 75.45 157 | 86.72 168 | 66.62 68 | 92.39 166 | 72.58 125 | 76.86 208 | 90.75 119 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
Effi-MVS+-dtu | | | 80.03 125 | 78.57 134 | 84.42 81 | 85.13 179 | 68.74 88 | 88.77 81 | 88.10 186 | 74.99 83 | 74.97 172 | 83.49 231 | 57.27 175 | 93.36 132 | 73.53 114 | 80.88 165 | 91.18 108 |
|
v1144 | | | 80.03 125 | 79.03 125 | 83.01 129 | 83.78 216 | 64.51 170 | 87.11 140 | 90.57 104 | 71.96 134 | 78.08 118 | 86.20 192 | 61.41 139 | 93.94 99 | 74.93 102 | 77.23 199 | 90.60 128 |
|
v8 | | | 79.97 127 | 79.02 126 | 82.80 144 | 84.09 202 | 64.50 174 | 87.96 108 | 90.29 118 | 74.13 95 | 75.24 166 | 86.81 165 | 62.88 105 | 93.89 104 | 74.39 105 | 75.40 231 | 90.00 157 |
|
DI_MVS_plusplus_test | | | 79.89 128 | 78.58 133 | 83.85 103 | 82.89 238 | 65.32 149 | 86.12 171 | 89.55 140 | 69.64 166 | 70.55 212 | 85.82 199 | 57.24 177 | 93.81 109 | 76.85 82 | 88.55 91 | 92.41 77 |
|
test_normal | | | 79.81 129 | 78.45 136 | 83.89 102 | 82.70 242 | 65.40 145 | 85.82 179 | 89.48 143 | 69.39 167 | 70.12 221 | 85.66 202 | 57.15 179 | 93.71 120 | 77.08 79 | 88.62 89 | 92.56 73 |
|
OpenMVS | | 72.83 10 | 79.77 130 | 78.33 142 | 84.09 91 | 85.17 176 | 69.91 64 | 90.57 38 | 90.97 94 | 66.70 199 | 72.17 197 | 91.91 56 | 54.70 194 | 93.96 97 | 61.81 207 | 90.95 64 | 88.41 207 |
|
v10 | | | 79.74 131 | 78.67 129 | 82.97 135 | 84.06 207 | 64.95 158 | 87.88 113 | 90.62 102 | 73.11 113 | 75.11 169 | 86.56 182 | 61.46 137 | 94.05 95 | 73.68 110 | 75.55 228 | 89.90 159 |
|
BH-RMVSNet | | | 79.61 132 | 78.44 138 | 83.14 122 | 89.38 90 | 65.93 135 | 84.95 194 | 87.15 201 | 73.56 102 | 78.19 114 | 89.79 98 | 56.67 181 | 93.36 132 | 59.53 225 | 86.74 112 | 90.13 148 |
|
v1192 | | | 79.59 133 | 78.43 139 | 83.07 126 | 83.55 220 | 64.52 168 | 86.93 146 | 90.58 103 | 70.83 147 | 77.78 122 | 85.90 195 | 59.15 163 | 93.94 99 | 73.96 109 | 77.19 201 | 90.76 118 |
|
diffmvs | | | 79.51 134 | 78.59 132 | 82.25 158 | 83.31 225 | 62.66 209 | 84.17 212 | 88.11 184 | 67.64 192 | 76.09 152 | 87.47 151 | 64.01 88 | 91.15 197 | 71.71 136 | 84.82 130 | 92.94 66 |
|
ab-mvs | | | 79.51 134 | 78.97 127 | 81.14 187 | 88.46 122 | 60.91 222 | 83.84 217 | 89.24 152 | 70.36 155 | 79.03 91 | 88.87 118 | 63.23 98 | 90.21 215 | 65.12 181 | 82.57 152 | 92.28 81 |
|
WR-MVS | | | 79.49 136 | 79.22 123 | 80.27 201 | 88.79 112 | 58.35 239 | 85.06 192 | 88.61 178 | 78.56 28 | 77.65 124 | 88.34 131 | 63.81 91 | 90.66 210 | 64.98 184 | 77.22 200 | 91.80 96 |
|
v144192 | | | 79.47 137 | 78.37 140 | 82.78 147 | 83.35 223 | 63.96 187 | 86.96 144 | 90.36 113 | 69.99 159 | 77.50 126 | 85.67 201 | 60.66 153 | 93.77 113 | 74.27 106 | 76.58 215 | 90.62 126 |
|
BH-untuned | | | 79.47 137 | 78.60 131 | 82.05 161 | 89.19 101 | 65.91 136 | 86.07 173 | 88.52 180 | 72.18 131 | 75.42 158 | 87.69 143 | 61.15 145 | 93.54 124 | 60.38 217 | 86.83 111 | 86.70 242 |
|
mvs_anonymous | | | 79.42 139 | 79.11 124 | 80.34 198 | 84.45 188 | 57.97 245 | 82.59 226 | 87.62 195 | 67.40 198 | 76.17 151 | 88.56 127 | 68.47 55 | 89.59 222 | 70.65 141 | 86.05 121 | 93.47 47 |
|
V42 | | | 79.38 140 | 78.24 144 | 82.83 143 | 81.10 263 | 65.50 144 | 85.55 185 | 89.82 134 | 71.57 140 | 78.21 113 | 86.12 193 | 60.66 153 | 93.18 140 | 75.64 94 | 75.46 230 | 89.81 164 |
|
jajsoiax | | | 79.29 141 | 77.96 147 | 83.27 117 | 84.68 185 | 66.57 127 | 89.25 66 | 90.16 123 | 69.20 173 | 75.46 156 | 89.49 104 | 45.75 259 | 93.13 143 | 76.84 83 | 80.80 167 | 90.11 149 |
|
v1921920 | | | 79.22 142 | 78.03 146 | 82.80 144 | 83.30 226 | 63.94 188 | 86.80 150 | 90.33 115 | 69.91 160 | 77.48 127 | 85.53 205 | 58.44 167 | 93.75 115 | 73.60 113 | 76.85 209 | 90.71 121 |
|
TAPA-MVS | | 73.13 9 | 79.15 143 | 77.94 148 | 82.79 146 | 89.59 85 | 62.99 207 | 88.16 105 | 91.51 81 | 65.77 211 | 77.14 136 | 91.09 73 | 60.91 149 | 93.21 136 | 50.26 273 | 87.05 109 | 92.17 85 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
mvs_tets | | | 79.13 144 | 77.77 153 | 83.22 119 | 84.70 184 | 66.37 129 | 89.17 67 | 90.19 122 | 69.38 169 | 75.40 159 | 89.46 107 | 44.17 265 | 93.15 141 | 76.78 84 | 80.70 169 | 90.14 147 |
|
CDS-MVSNet | | | 79.07 145 | 77.70 154 | 83.17 120 | 87.60 144 | 68.23 101 | 84.40 209 | 86.20 212 | 67.49 196 | 76.36 146 | 86.54 183 | 61.54 136 | 90.79 208 | 61.86 206 | 87.33 106 | 90.49 136 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
MVSTER | | | 79.01 146 | 77.88 149 | 82.38 156 | 83.07 232 | 64.80 162 | 84.08 216 | 88.95 166 | 69.01 180 | 78.69 95 | 87.17 161 | 54.70 194 | 92.43 164 | 74.69 103 | 80.57 171 | 89.89 160 |
|
v1240 | | | 78.99 147 | 77.78 152 | 82.64 152 | 83.21 227 | 63.54 191 | 86.62 158 | 90.30 117 | 69.74 165 | 77.33 129 | 85.68 200 | 57.04 180 | 93.76 114 | 73.13 118 | 76.92 206 | 90.62 126 |
|
v7n | | | 78.97 148 | 77.58 156 | 83.14 122 | 83.45 222 | 65.51 143 | 88.32 98 | 91.21 89 | 73.69 99 | 72.41 194 | 86.32 190 | 57.93 170 | 93.81 109 | 69.18 152 | 75.65 226 | 90.11 149 |
|
TAMVS | | | 78.89 149 | 77.51 157 | 83.03 128 | 87.80 139 | 67.79 109 | 84.72 197 | 85.05 223 | 67.63 193 | 76.75 139 | 87.70 142 | 62.25 128 | 90.82 207 | 58.53 234 | 87.13 108 | 90.49 136 |
|
v148 | | | 78.72 150 | 77.80 151 | 81.47 180 | 82.73 241 | 61.96 217 | 86.30 168 | 88.08 188 | 73.26 106 | 76.18 149 | 85.47 207 | 62.46 125 | 92.36 168 | 71.92 135 | 73.82 247 | 90.09 151 |
|
VPNet | | | 78.69 151 | 78.66 130 | 78.76 220 | 88.31 127 | 55.72 272 | 84.45 206 | 86.63 206 | 76.79 50 | 78.26 112 | 90.55 86 | 59.30 162 | 89.70 221 | 66.63 170 | 77.05 202 | 90.88 115 |
|
anonymousdsp | | | 78.60 152 | 77.15 162 | 82.98 131 | 80.51 269 | 67.08 119 | 87.24 133 | 89.53 141 | 65.66 213 | 75.16 167 | 87.19 160 | 52.52 207 | 92.25 171 | 77.17 78 | 79.34 183 | 89.61 168 |
|
WR-MVS_H | | | 78.51 153 | 78.49 135 | 78.56 223 | 88.02 133 | 56.38 265 | 88.43 91 | 92.67 37 | 77.14 42 | 73.89 179 | 87.55 148 | 66.25 71 | 89.24 228 | 58.92 229 | 73.55 249 | 90.06 155 |
|
GBi-Net | | | 78.40 154 | 77.40 158 | 81.40 182 | 87.60 144 | 63.01 204 | 88.39 95 | 89.28 148 | 71.63 137 | 75.34 161 | 87.28 154 | 54.80 190 | 91.11 198 | 62.72 195 | 79.57 179 | 90.09 151 |
|
test1 | | | 78.40 154 | 77.40 158 | 81.40 182 | 87.60 144 | 63.01 204 | 88.39 95 | 89.28 148 | 71.63 137 | 75.34 161 | 87.28 154 | 54.80 190 | 91.11 198 | 62.72 195 | 79.57 179 | 90.09 151 |
|
Vis-MVSNet (Re-imp) | | | 78.36 156 | 78.45 136 | 78.07 230 | 88.64 116 | 51.78 287 | 86.70 156 | 79.63 272 | 74.14 94 | 75.11 169 | 90.83 81 | 61.29 142 | 89.75 219 | 58.10 238 | 91.60 56 | 92.69 70 |
|
CP-MVSNet | | | 78.22 157 | 78.34 141 | 77.84 232 | 87.83 138 | 54.54 276 | 87.94 110 | 91.17 91 | 77.65 32 | 73.48 182 | 88.49 128 | 62.24 129 | 88.43 241 | 62.19 201 | 74.07 242 | 90.55 134 |
|
BH-w/o | | | 78.21 158 | 77.33 160 | 80.84 191 | 88.81 110 | 65.13 155 | 84.87 195 | 87.85 192 | 69.75 163 | 74.52 176 | 84.74 220 | 61.34 140 | 93.11 144 | 58.24 237 | 85.84 124 | 84.27 267 |
|
FMVSNet2 | | | 78.20 159 | 77.21 161 | 81.20 185 | 87.60 144 | 62.89 208 | 87.47 125 | 89.02 157 | 71.63 137 | 75.29 165 | 87.28 154 | 54.80 190 | 91.10 201 | 62.38 199 | 79.38 182 | 89.61 168 |
|
MVS | | | 78.19 160 | 76.99 164 | 81.78 166 | 85.66 171 | 66.99 120 | 84.66 198 | 90.47 108 | 55.08 290 | 72.02 201 | 85.27 210 | 63.83 90 | 94.11 94 | 66.10 174 | 89.80 76 | 84.24 268 |
|
Baseline_NR-MVSNet | | | 78.15 161 | 78.33 142 | 77.61 236 | 85.79 169 | 56.21 268 | 86.78 152 | 85.76 217 | 73.60 101 | 77.93 120 | 87.57 147 | 65.02 82 | 88.99 232 | 67.14 167 | 75.33 232 | 87.63 220 |
|
CNLPA | | | 78.08 162 | 76.79 168 | 81.97 163 | 90.40 72 | 71.07 46 | 87.59 117 | 84.55 226 | 66.03 210 | 72.38 195 | 89.64 101 | 57.56 173 | 86.04 259 | 59.61 223 | 83.35 141 | 88.79 188 |
|
PLC | | 70.83 11 | 78.05 163 | 76.37 174 | 83.08 125 | 91.88 57 | 67.80 108 | 88.19 103 | 89.46 144 | 64.33 225 | 69.87 227 | 88.38 130 | 53.66 204 | 93.58 122 | 58.86 230 | 82.73 149 | 87.86 216 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
Fast-Effi-MVS+-dtu | | | 78.02 164 | 76.49 171 | 82.62 153 | 83.16 231 | 66.96 123 | 86.94 145 | 87.45 199 | 72.45 126 | 71.49 207 | 84.17 222 | 54.79 193 | 91.58 189 | 67.61 160 | 80.31 175 | 89.30 172 |
|
PS-CasMVS | | | 78.01 165 | 78.09 145 | 77.77 234 | 87.71 142 | 54.39 278 | 88.02 106 | 91.22 88 | 77.50 39 | 73.26 184 | 88.64 123 | 60.73 150 | 88.41 242 | 61.88 205 | 73.88 246 | 90.53 135 |
|
v748 | | | 77.97 166 | 76.65 170 | 81.92 165 | 82.29 248 | 63.28 198 | 87.53 122 | 90.35 114 | 73.50 105 | 70.76 211 | 85.55 204 | 58.28 168 | 92.81 157 | 68.81 155 | 72.76 254 | 89.67 167 |
|
V4 | | | 77.95 167 | 76.37 174 | 82.67 150 | 79.40 280 | 65.52 141 | 86.43 162 | 89.94 131 | 72.28 128 | 72.14 200 | 84.95 216 | 55.72 185 | 93.44 129 | 73.64 111 | 72.86 252 | 89.05 178 |
|
HY-MVS | | 69.67 12 | 77.95 167 | 77.15 162 | 80.36 197 | 87.57 148 | 60.21 228 | 83.37 224 | 87.78 193 | 66.11 207 | 75.37 160 | 87.06 163 | 63.27 96 | 90.48 212 | 61.38 211 | 82.43 153 | 90.40 141 |
|
v52 | | | 77.94 169 | 76.37 174 | 82.67 150 | 79.39 281 | 65.52 141 | 86.43 162 | 89.94 131 | 72.28 128 | 72.15 199 | 84.94 217 | 55.70 186 | 93.44 129 | 73.64 111 | 72.84 253 | 89.06 174 |
|
FMVSNet3 | | | 77.88 170 | 76.85 166 | 80.97 190 | 86.84 160 | 62.36 211 | 86.52 161 | 88.77 173 | 71.13 143 | 75.34 161 | 86.66 175 | 54.07 201 | 91.10 201 | 62.72 195 | 79.57 179 | 89.45 170 |
|
Test4 | | | 77.83 171 | 75.90 188 | 83.62 105 | 80.24 271 | 65.25 151 | 85.27 190 | 90.67 99 | 69.03 179 | 66.48 262 | 83.75 227 | 43.07 270 | 93.00 149 | 75.93 89 | 88.66 88 | 92.62 72 |
|
PEN-MVS | | | 77.73 172 | 77.69 155 | 77.84 232 | 87.07 157 | 53.91 280 | 87.91 112 | 91.18 90 | 77.56 36 | 73.14 186 | 88.82 119 | 61.23 143 | 89.17 229 | 59.95 220 | 72.37 255 | 90.43 139 |
|
v16 | | | 77.69 173 | 76.36 177 | 81.68 173 | 84.15 197 | 64.63 167 | 87.33 128 | 88.99 161 | 72.69 124 | 69.31 235 | 82.08 244 | 62.80 111 | 91.79 177 | 72.70 123 | 67.23 277 | 88.63 193 |
|
v17 | | | 77.68 174 | 76.35 178 | 81.69 172 | 84.15 197 | 64.65 165 | 87.33 128 | 88.99 161 | 72.70 123 | 69.25 236 | 82.07 245 | 62.82 110 | 91.79 177 | 72.69 124 | 67.15 279 | 88.63 193 |
|
PAPM | | | 77.68 174 | 76.40 173 | 81.51 179 | 87.29 154 | 61.85 218 | 83.78 218 | 89.59 139 | 64.74 220 | 71.23 208 | 88.70 120 | 62.59 120 | 93.66 121 | 52.66 264 | 87.03 110 | 89.01 181 |
|
v18 | | | 77.67 176 | 76.35 178 | 81.64 175 | 84.09 202 | 64.47 176 | 87.27 131 | 89.01 159 | 72.59 125 | 69.39 232 | 82.04 246 | 62.85 106 | 91.80 176 | 72.72 122 | 67.20 278 | 88.63 193 |
|
HyFIR | | | 77.63 177 | 75.69 189 | 83.44 110 | 89.98 78 | 68.58 95 | 78.70 260 | 87.50 197 | 56.38 285 | 75.80 153 | 86.84 164 | 58.67 165 | 91.40 191 | 61.58 209 | 85.75 125 | 90.34 142 |
|
HyFIR lowres test | | | 77.53 178 | 75.40 193 | 83.94 101 | 89.59 85 | 66.62 125 | 80.36 244 | 88.64 177 | 56.29 286 | 76.45 144 | 85.17 211 | 57.64 172 | 93.28 134 | 61.34 212 | 83.10 145 | 91.91 91 |
|
V14 | | | 77.52 179 | 76.12 181 | 81.70 171 | 84.15 197 | 64.77 163 | 87.21 134 | 88.95 166 | 72.80 120 | 68.79 238 | 81.94 252 | 62.69 115 | 91.72 182 | 72.31 129 | 66.27 285 | 88.60 197 |
|
V9 | | | 77.52 179 | 76.11 184 | 81.73 170 | 84.19 196 | 64.89 160 | 87.26 132 | 88.94 169 | 72.87 119 | 68.65 241 | 81.96 251 | 62.65 118 | 91.72 182 | 72.27 130 | 66.24 286 | 88.60 197 |
|
v15 | | | 77.51 181 | 76.12 181 | 81.66 174 | 84.09 202 | 64.65 165 | 87.14 135 | 88.96 165 | 72.76 121 | 68.90 237 | 81.91 253 | 62.74 113 | 91.73 180 | 72.32 128 | 66.29 284 | 88.61 196 |
|
v12 | | | 77.51 181 | 76.09 185 | 81.76 169 | 84.22 192 | 64.99 157 | 87.30 130 | 88.93 170 | 72.92 116 | 68.48 245 | 81.97 249 | 62.54 122 | 91.70 185 | 72.24 131 | 66.21 288 | 88.58 200 |
|
v13 | | | 77.50 183 | 76.07 186 | 81.77 167 | 84.23 191 | 65.07 156 | 87.34 127 | 88.91 171 | 72.92 116 | 68.35 246 | 81.97 249 | 62.53 123 | 91.69 186 | 72.20 132 | 66.22 287 | 88.56 202 |
|
v11 | | | 77.45 184 | 76.06 187 | 81.59 178 | 84.22 192 | 64.52 168 | 87.11 140 | 89.02 157 | 72.76 121 | 68.76 239 | 81.90 254 | 62.09 131 | 91.71 184 | 71.98 133 | 66.73 280 | 88.56 202 |
|
FMVSNet1 | | | 77.44 185 | 76.12 181 | 81.40 182 | 86.81 161 | 63.01 204 | 88.39 95 | 89.28 148 | 70.49 154 | 74.39 177 | 87.28 154 | 49.06 243 | 91.11 198 | 60.91 214 | 78.52 187 | 90.09 151 |
|
TR-MVS | | | 77.44 185 | 76.18 180 | 81.20 185 | 88.24 128 | 63.24 199 | 84.61 201 | 86.40 209 | 67.55 195 | 77.81 121 | 86.48 186 | 54.10 200 | 93.15 141 | 57.75 241 | 82.72 150 | 87.20 231 |
|
1112_ss | | | 77.40 187 | 76.43 172 | 80.32 199 | 89.11 103 | 60.41 227 | 83.65 219 | 87.72 194 | 62.13 246 | 73.05 187 | 86.72 168 | 62.58 121 | 89.97 217 | 62.11 204 | 80.80 167 | 90.59 130 |
|
pm-mvs1 | | | 77.25 188 | 76.68 169 | 78.93 218 | 84.22 192 | 58.62 237 | 86.41 164 | 88.36 182 | 71.37 142 | 73.31 183 | 88.01 139 | 61.22 144 | 89.15 230 | 64.24 188 | 73.01 251 | 89.03 180 |
|
LCM-MVSNet-Re | | | 77.05 189 | 76.94 165 | 77.36 239 | 87.20 155 | 51.60 288 | 80.06 246 | 80.46 264 | 75.20 81 | 67.69 250 | 86.72 168 | 62.48 124 | 88.98 233 | 63.44 191 | 89.25 81 | 91.51 100 |
|
DTE-MVSNet | | | 76.99 190 | 76.80 167 | 77.54 238 | 86.24 166 | 53.06 284 | 87.52 123 | 90.66 101 | 77.08 45 | 72.50 192 | 88.67 122 | 60.48 156 | 89.52 223 | 57.33 245 | 70.74 266 | 90.05 156 |
|
LS3D | | | 76.95 191 | 74.82 197 | 83.37 114 | 90.45 70 | 67.36 116 | 89.15 71 | 86.94 203 | 61.87 248 | 69.52 230 | 90.61 84 | 51.71 219 | 94.53 77 | 46.38 287 | 86.71 113 | 88.21 209 |
|
GA-MVS | | | 76.87 192 | 75.17 195 | 81.97 163 | 82.75 240 | 62.58 210 | 81.44 238 | 86.35 211 | 72.16 133 | 74.74 174 | 82.89 234 | 46.20 254 | 92.02 175 | 68.85 154 | 81.09 163 | 91.30 106 |
|
DP-MVS | | | 76.78 193 | 74.57 199 | 83.42 111 | 93.29 31 | 69.46 75 | 88.55 90 | 83.70 233 | 63.98 229 | 70.20 217 | 88.89 117 | 54.01 202 | 94.80 72 | 46.66 284 | 81.88 158 | 86.01 252 |
|
cascas | | | 76.72 194 | 74.64 198 | 82.99 130 | 85.78 170 | 65.88 137 | 82.33 228 | 89.21 153 | 60.85 254 | 72.74 189 | 81.02 261 | 47.28 249 | 93.75 115 | 67.48 162 | 85.02 126 | 89.34 171 |
|
1314 | | | 76.53 195 | 75.30 194 | 80.21 202 | 83.93 210 | 62.32 213 | 84.66 198 | 88.81 172 | 60.23 258 | 70.16 220 | 84.07 224 | 55.30 189 | 90.73 209 | 67.37 163 | 83.21 143 | 87.59 222 |
|
Test_1112_low_res | | | 76.40 196 | 75.44 192 | 79.27 213 | 89.28 97 | 58.09 242 | 81.69 234 | 87.07 202 | 59.53 264 | 72.48 193 | 86.67 174 | 61.30 141 | 89.33 226 | 60.81 216 | 80.15 177 | 90.41 140 |
|
F-COLMAP | | | 76.38 197 | 74.33 203 | 82.50 154 | 89.28 97 | 66.95 124 | 88.41 94 | 89.03 156 | 64.05 227 | 66.83 258 | 88.61 124 | 46.78 252 | 92.89 152 | 57.48 242 | 78.55 186 | 87.67 219 |
|
LTVRE_ROB | | 69.57 13 | 76.25 198 | 74.54 201 | 81.41 181 | 88.60 117 | 64.38 179 | 79.24 254 | 89.12 155 | 70.76 150 | 69.79 229 | 87.86 140 | 49.09 242 | 93.20 138 | 56.21 251 | 80.16 176 | 86.65 243 |
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 |
MVP-Stereo | | | 76.12 199 | 74.46 202 | 81.13 188 | 85.37 175 | 69.79 66 | 84.42 208 | 87.95 190 | 65.03 218 | 67.46 252 | 85.33 209 | 53.28 206 | 91.73 180 | 58.01 239 | 83.27 142 | 81.85 287 |
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application. |
XVG-ACMP-BASELINE | | | 76.11 200 | 74.27 204 | 81.62 176 | 83.20 228 | 64.67 164 | 83.60 221 | 89.75 136 | 69.75 163 | 71.85 202 | 87.09 162 | 32.78 302 | 92.11 174 | 69.99 146 | 80.43 174 | 88.09 211 |
|
ACMH+ | | 68.96 14 | 76.01 201 | 74.01 205 | 82.03 162 | 88.60 117 | 65.31 150 | 88.86 77 | 87.55 196 | 70.25 157 | 67.75 249 | 87.47 151 | 41.27 280 | 93.19 139 | 58.37 235 | 75.94 222 | 87.60 221 |
|
ACMH | | 67.68 16 | 75.89 202 | 73.93 206 | 81.77 167 | 88.71 115 | 66.61 126 | 88.62 87 | 89.01 159 | 69.81 161 | 66.78 259 | 86.70 173 | 41.95 279 | 91.51 190 | 55.64 252 | 78.14 192 | 87.17 232 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
IB-MVS | | 68.01 15 | 75.85 203 | 73.36 210 | 83.31 115 | 84.76 183 | 66.03 132 | 83.38 223 | 85.06 222 | 70.21 158 | 69.40 231 | 81.05 260 | 45.76 258 | 94.66 75 | 65.10 182 | 75.49 229 | 89.25 173 |
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 |
testing_2 | | | 75.73 204 | 73.34 211 | 82.89 139 | 77.37 289 | 65.22 152 | 84.10 215 | 90.54 105 | 69.09 175 | 60.46 285 | 81.15 259 | 40.48 283 | 92.84 156 | 76.36 85 | 80.54 173 | 90.60 128 |
|
WTY-MVS | | | 75.65 205 | 75.68 190 | 75.57 253 | 86.40 165 | 56.82 256 | 77.92 266 | 82.40 245 | 65.10 217 | 76.18 149 | 87.72 141 | 63.13 103 | 80.90 281 | 60.31 218 | 81.96 156 | 89.00 183 |
|
EPNet_dtu | | | 75.46 206 | 74.86 196 | 77.23 242 | 82.57 245 | 54.60 275 | 86.89 147 | 83.09 239 | 71.64 136 | 66.25 264 | 85.86 197 | 55.99 184 | 88.04 246 | 54.92 254 | 86.55 115 | 89.05 178 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
XXY-MVS | | | 75.41 207 | 75.56 191 | 74.96 257 | 83.59 219 | 57.82 248 | 80.59 243 | 83.87 232 | 66.54 204 | 74.93 173 | 88.31 132 | 63.24 97 | 80.09 285 | 62.16 202 | 76.85 209 | 86.97 237 |
|
TransMVSNet (Re) | | | 75.39 208 | 74.56 200 | 77.86 231 | 85.50 174 | 57.10 254 | 86.78 152 | 86.09 215 | 72.17 132 | 71.53 206 | 87.34 153 | 63.01 104 | 89.31 227 | 56.84 248 | 61.83 296 | 87.17 232 |
|
CostFormer | | | 75.24 209 | 73.90 207 | 79.27 213 | 82.65 244 | 58.27 241 | 80.80 239 | 82.73 243 | 61.57 249 | 75.33 164 | 83.13 233 | 55.52 187 | 91.07 204 | 64.98 184 | 78.34 191 | 88.45 205 |
|
pmmvs6 | | | 74.69 210 | 73.39 209 | 78.61 222 | 81.38 258 | 57.48 251 | 86.64 157 | 87.95 190 | 64.99 219 | 70.18 218 | 86.61 179 | 50.43 233 | 89.52 223 | 62.12 203 | 70.18 268 | 88.83 186 |
|
PatchFormer-LS_test | | | 74.50 211 | 73.05 212 | 78.86 219 | 82.95 236 | 59.55 233 | 81.65 235 | 82.30 247 | 67.44 197 | 71.62 205 | 78.15 280 | 52.34 211 | 88.92 237 | 65.05 183 | 75.90 223 | 88.12 210 |
|
IterMVS | | | 74.29 212 | 72.94 213 | 78.35 228 | 81.53 256 | 63.49 192 | 81.58 236 | 82.49 244 | 68.06 191 | 69.99 224 | 83.69 229 | 51.66 220 | 85.54 262 | 65.85 177 | 71.64 261 | 86.01 252 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
OurMVSNet-221017-0 | | | 74.26 213 | 72.42 217 | 79.80 207 | 83.76 217 | 59.59 230 | 85.92 177 | 86.64 205 | 66.39 205 | 66.96 257 | 87.58 146 | 39.46 286 | 91.60 188 | 65.76 178 | 69.27 270 | 88.22 208 |
|
EG-PatchMatch MVS | | | 74.04 214 | 71.82 222 | 80.71 194 | 84.92 182 | 67.42 113 | 85.86 178 | 88.08 188 | 66.04 209 | 64.22 275 | 83.85 225 | 35.10 301 | 92.56 162 | 57.44 243 | 80.83 166 | 82.16 286 |
|
pmmvs4 | | | 74.03 215 | 71.91 219 | 80.39 196 | 81.96 251 | 68.32 98 | 81.45 237 | 82.14 249 | 59.32 265 | 69.87 227 | 85.13 212 | 52.40 210 | 88.13 245 | 60.21 219 | 74.74 238 | 84.73 265 |
|
MS-PatchMatch | | | 73.83 216 | 72.67 214 | 77.30 241 | 83.87 211 | 66.02 133 | 81.82 231 | 84.66 225 | 61.37 252 | 68.61 243 | 82.82 236 | 47.29 248 | 88.21 243 | 59.27 226 | 84.32 135 | 77.68 300 |
|
DWT-MVSNet_test | | | 73.70 217 | 71.86 220 | 79.21 215 | 82.91 237 | 58.94 235 | 82.34 227 | 82.17 248 | 65.21 215 | 71.05 210 | 78.31 278 | 44.21 264 | 90.17 216 | 63.29 193 | 77.28 198 | 88.53 204 |
|
sss | | | 73.60 218 | 73.64 208 | 73.51 268 | 82.80 239 | 55.01 274 | 76.12 272 | 81.69 253 | 62.47 243 | 74.68 175 | 85.85 198 | 57.32 174 | 78.11 293 | 60.86 215 | 80.93 164 | 87.39 225 |
|
Patchmatch-test1 | | | 73.49 219 | 71.85 221 | 78.41 227 | 84.05 208 | 62.17 215 | 79.96 248 | 79.29 274 | 66.30 206 | 72.38 195 | 79.58 273 | 51.95 217 | 85.08 266 | 55.46 253 | 77.67 195 | 87.99 212 |
|
tpmp4_e23 | | | 73.45 220 | 71.17 229 | 80.31 200 | 83.55 220 | 59.56 232 | 81.88 230 | 82.33 246 | 57.94 275 | 70.51 214 | 81.62 255 | 51.19 224 | 91.63 187 | 53.96 258 | 77.51 196 | 89.75 166 |
|
SixPastTwentyTwo | | | 73.37 221 | 71.26 228 | 79.70 208 | 85.08 181 | 57.89 247 | 85.57 181 | 83.56 234 | 71.03 146 | 65.66 266 | 85.88 196 | 42.10 277 | 92.57 161 | 59.11 228 | 63.34 293 | 88.65 192 |
|
CR-MVSNet | | | 73.37 221 | 71.27 227 | 79.67 209 | 81.32 261 | 65.19 153 | 75.92 274 | 80.30 266 | 59.92 261 | 72.73 190 | 81.19 257 | 52.50 208 | 86.69 253 | 59.84 221 | 77.71 193 | 87.11 235 |
|
MSDG | | | 73.36 223 | 70.99 230 | 80.49 195 | 84.51 187 | 65.80 138 | 80.71 241 | 86.13 214 | 65.70 212 | 65.46 267 | 83.74 228 | 44.60 262 | 90.91 206 | 51.13 268 | 76.89 207 | 84.74 264 |
|
tpm2 | | | 73.26 224 | 71.46 224 | 78.63 221 | 83.34 224 | 56.71 259 | 80.65 242 | 80.40 265 | 56.63 284 | 73.55 181 | 82.02 247 | 51.80 218 | 91.24 195 | 56.35 250 | 78.42 190 | 87.95 213 |
|
RPSCF | | | 73.23 225 | 71.46 224 | 78.54 224 | 82.50 246 | 59.85 229 | 82.18 229 | 82.84 242 | 58.96 267 | 71.15 209 | 89.41 111 | 45.48 261 | 84.77 268 | 58.82 231 | 71.83 260 | 91.02 112 |
|
PatchmatchNet | | | 73.12 226 | 71.33 226 | 78.49 226 | 83.18 229 | 60.85 223 | 79.63 250 | 78.57 276 | 64.13 226 | 71.73 203 | 79.81 272 | 51.20 223 | 85.97 260 | 57.40 244 | 76.36 219 | 88.66 191 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
COLMAP_ROB | | 66.92 17 | 73.01 227 | 70.41 234 | 80.81 192 | 87.13 156 | 65.63 140 | 88.30 99 | 84.19 230 | 62.96 236 | 63.80 278 | 87.69 143 | 38.04 292 | 92.56 162 | 46.66 284 | 74.91 236 | 84.24 268 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
CVMVSNet | | | 72.99 228 | 72.58 215 | 74.25 264 | 84.28 189 | 50.85 294 | 86.41 164 | 83.45 236 | 44.56 310 | 73.23 185 | 87.54 149 | 49.38 238 | 85.70 261 | 65.90 176 | 78.44 189 | 86.19 247 |
|
test-LLR | | | 72.94 229 | 72.43 216 | 74.48 261 | 81.35 259 | 58.04 243 | 78.38 261 | 77.46 281 | 66.66 200 | 69.95 225 | 79.00 276 | 48.06 246 | 79.24 287 | 66.13 172 | 84.83 128 | 86.15 248 |
|
test_0402 | | | 72.79 230 | 70.44 233 | 79.84 206 | 88.13 130 | 65.99 134 | 85.93 176 | 84.29 228 | 65.57 214 | 67.40 254 | 85.49 206 | 46.92 251 | 92.61 160 | 35.88 306 | 74.38 241 | 80.94 290 |
|
tpmrst | | | 72.39 231 | 72.13 218 | 73.18 270 | 80.54 268 | 49.91 298 | 79.91 249 | 79.08 275 | 63.11 233 | 71.69 204 | 79.95 269 | 55.32 188 | 82.77 276 | 65.66 179 | 73.89 245 | 86.87 238 |
|
PatchMatch-RL | | | 72.38 232 | 70.90 231 | 76.80 245 | 88.60 117 | 67.38 115 | 79.53 251 | 76.17 287 | 62.75 240 | 69.36 233 | 82.00 248 | 45.51 260 | 84.89 267 | 53.62 260 | 80.58 170 | 78.12 298 |
|
tpm | | | 72.37 233 | 71.71 223 | 74.35 263 | 82.19 249 | 52.00 285 | 79.22 255 | 77.29 283 | 64.56 222 | 72.95 188 | 83.68 230 | 51.35 221 | 83.26 275 | 58.33 236 | 75.80 224 | 87.81 217 |
|
PVSNet | | 64.34 18 | 72.08 234 | 70.87 232 | 75.69 251 | 86.21 167 | 56.44 263 | 74.37 284 | 80.73 261 | 62.06 247 | 70.17 219 | 82.23 242 | 42.86 272 | 83.31 274 | 54.77 255 | 84.45 134 | 87.32 228 |
|
RPMNet | | | 71.62 235 | 68.94 242 | 79.67 209 | 81.32 261 | 65.19 153 | 75.92 274 | 78.30 278 | 57.60 278 | 72.73 190 | 76.45 289 | 52.30 212 | 86.69 253 | 48.14 281 | 77.71 193 | 87.11 235 |
|
pmmvs5 | | | 71.55 236 | 70.20 236 | 75.61 252 | 77.83 286 | 56.39 264 | 81.74 233 | 80.89 258 | 57.76 276 | 67.46 252 | 84.49 221 | 49.26 241 | 85.32 265 | 57.08 247 | 75.29 233 | 85.11 261 |
|
test-mter | | | 71.41 237 | 70.39 235 | 74.48 261 | 81.35 259 | 58.04 243 | 78.38 261 | 77.46 281 | 60.32 257 | 69.95 225 | 79.00 276 | 36.08 299 | 79.24 287 | 66.13 172 | 84.83 128 | 86.15 248 |
|
K. test v3 | | | 71.19 238 | 68.51 244 | 79.21 215 | 83.04 234 | 57.78 249 | 84.35 210 | 76.91 285 | 72.90 118 | 62.99 281 | 82.86 235 | 39.27 287 | 91.09 203 | 61.65 208 | 52.66 311 | 88.75 189 |
|
tpmvs | | | 71.09 239 | 69.29 239 | 76.49 246 | 82.04 250 | 56.04 269 | 78.92 258 | 81.37 257 | 64.05 227 | 67.18 256 | 78.28 279 | 49.74 237 | 89.77 218 | 49.67 276 | 72.37 255 | 83.67 272 |
|
AllTest | | | 70.96 240 | 68.09 250 | 79.58 211 | 85.15 177 | 63.62 189 | 84.58 202 | 79.83 270 | 62.31 244 | 60.32 286 | 86.73 166 | 32.02 303 | 88.96 235 | 50.28 271 | 71.57 262 | 86.15 248 |
|
Patchmtry | | | 70.74 241 | 69.16 240 | 75.49 254 | 80.72 265 | 54.07 279 | 74.94 283 | 80.30 266 | 58.34 271 | 70.01 222 | 81.19 257 | 52.50 208 | 86.54 255 | 53.37 261 | 71.09 264 | 85.87 254 |
|
MIMVSNet | | | 70.69 242 | 69.30 238 | 74.88 258 | 84.52 186 | 56.35 266 | 75.87 276 | 79.42 273 | 64.59 221 | 67.76 248 | 82.41 239 | 41.10 281 | 81.54 280 | 46.64 286 | 81.34 161 | 86.75 241 |
|
tpm cat1 | | | 70.57 243 | 68.31 246 | 77.35 240 | 82.41 247 | 57.95 246 | 78.08 265 | 80.22 268 | 52.04 301 | 68.54 244 | 77.66 285 | 52.00 216 | 87.84 248 | 51.77 265 | 72.07 259 | 86.25 246 |
|
OpenMVS_ROB | | 64.09 19 | 70.56 244 | 68.19 247 | 77.65 235 | 80.26 270 | 59.41 234 | 85.01 193 | 82.96 241 | 58.76 269 | 65.43 268 | 82.33 240 | 37.63 295 | 91.23 196 | 45.34 292 | 76.03 221 | 82.32 284 |
|
pmmvs-eth3d | | | 70.50 245 | 67.83 254 | 78.52 225 | 77.37 289 | 66.18 131 | 81.82 231 | 81.51 255 | 58.90 268 | 63.90 277 | 80.42 266 | 42.69 273 | 86.28 258 | 58.56 233 | 65.30 290 | 83.11 278 |
|
USDC | | | 70.33 246 | 68.37 245 | 76.21 248 | 80.60 267 | 56.23 267 | 79.19 256 | 86.49 207 | 60.89 253 | 61.29 282 | 85.47 207 | 31.78 305 | 89.47 225 | 53.37 261 | 76.21 220 | 82.94 283 |
|
Patchmatch-RL test | | | 70.24 247 | 67.78 256 | 77.61 236 | 77.43 288 | 59.57 231 | 71.16 289 | 70.33 308 | 62.94 237 | 68.65 241 | 72.77 299 | 50.62 231 | 85.49 263 | 69.58 149 | 66.58 282 | 87.77 218 |
|
CMPMVS | | 51.72 21 | 70.19 248 | 68.16 248 | 76.28 247 | 73.15 305 | 57.55 250 | 79.47 252 | 83.92 231 | 48.02 308 | 56.48 300 | 84.81 218 | 43.13 269 | 86.42 257 | 62.67 198 | 81.81 159 | 84.89 262 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
gg-mvs-nofinetune | | | 69.95 249 | 67.96 251 | 75.94 249 | 83.07 232 | 54.51 277 | 77.23 269 | 70.29 309 | 63.11 233 | 70.32 216 | 62.33 311 | 43.62 267 | 88.69 239 | 53.88 259 | 87.76 99 | 84.62 266 |
|
TESTMET0.1,1 | | | 69.89 250 | 69.00 241 | 72.55 271 | 79.27 283 | 56.85 255 | 78.38 261 | 74.71 297 | 57.64 277 | 68.09 247 | 77.19 287 | 37.75 293 | 76.70 298 | 63.92 189 | 84.09 136 | 84.10 271 |
|
FMVSNet5 | | | 69.50 251 | 67.96 251 | 74.15 265 | 82.97 235 | 55.35 273 | 80.01 247 | 82.12 250 | 62.56 242 | 63.02 279 | 81.53 256 | 36.92 296 | 81.92 278 | 48.42 279 | 74.06 243 | 85.17 260 |
|
PMMVS | | | 69.34 252 | 68.67 243 | 71.35 277 | 75.67 296 | 62.03 216 | 75.17 278 | 73.46 302 | 50.00 306 | 68.68 240 | 79.05 274 | 52.07 215 | 78.13 292 | 61.16 213 | 82.77 148 | 73.90 307 |
|
EPMVS | | | 69.02 253 | 68.16 248 | 71.59 273 | 79.61 277 | 49.80 300 | 77.40 268 | 66.93 317 | 62.82 239 | 70.01 222 | 79.05 274 | 45.79 257 | 77.86 295 | 56.58 249 | 75.26 234 | 87.13 234 |
|
Anonymous20231206 | | | 68.60 254 | 67.80 255 | 71.02 279 | 80.23 272 | 50.75 295 | 78.30 264 | 80.47 263 | 56.79 283 | 66.11 265 | 82.63 238 | 46.35 253 | 78.95 289 | 43.62 295 | 75.70 225 | 83.36 275 |
|
MIMVSNet1 | | | 68.58 255 | 66.78 260 | 73.98 266 | 80.07 273 | 51.82 286 | 80.77 240 | 84.37 227 | 64.40 224 | 59.75 289 | 82.16 243 | 36.47 297 | 83.63 272 | 42.73 296 | 70.33 267 | 86.48 245 |
|
EU-MVSNet | | | 68.53 256 | 67.61 258 | 71.31 278 | 78.51 285 | 47.01 304 | 84.47 203 | 84.27 229 | 42.27 311 | 66.44 263 | 84.79 219 | 40.44 284 | 83.76 270 | 58.76 232 | 68.54 276 | 83.17 276 |
|
PatchT | | | 68.46 257 | 67.85 253 | 70.29 281 | 80.70 266 | 43.93 308 | 72.47 287 | 74.88 293 | 60.15 259 | 70.55 212 | 76.57 288 | 49.94 236 | 81.59 279 | 50.58 269 | 74.83 237 | 85.34 257 |
|
test0.0.03 1 | | | 68.00 258 | 67.69 257 | 68.90 286 | 77.55 287 | 47.43 302 | 75.70 277 | 72.95 304 | 66.66 200 | 66.56 260 | 82.29 241 | 48.06 246 | 75.87 302 | 44.97 293 | 74.51 240 | 83.41 274 |
|
TDRefinement | | | 67.49 259 | 64.34 265 | 76.92 243 | 73.47 303 | 61.07 220 | 84.86 196 | 82.98 240 | 59.77 262 | 58.30 292 | 85.13 212 | 26.06 310 | 87.89 247 | 47.92 282 | 60.59 301 | 81.81 288 |
|
test20.03 | | | 67.45 260 | 66.95 259 | 68.94 285 | 75.48 299 | 44.84 306 | 77.50 267 | 77.67 280 | 66.66 200 | 63.01 280 | 83.80 226 | 47.02 250 | 78.40 291 | 42.53 297 | 68.86 274 | 83.58 273 |
|
UnsupCasMVSNet_eth | | | 67.33 261 | 65.99 262 | 71.37 275 | 73.48 302 | 51.47 290 | 75.16 279 | 85.19 221 | 65.20 216 | 60.78 284 | 80.93 264 | 42.35 274 | 77.20 297 | 57.12 246 | 53.69 310 | 85.44 256 |
|
TinyColmap | | | 67.30 262 | 64.81 264 | 74.76 260 | 81.92 252 | 56.68 260 | 80.29 245 | 81.49 256 | 60.33 256 | 56.27 301 | 83.22 232 | 24.77 312 | 87.66 250 | 45.52 290 | 69.47 269 | 79.95 294 |
|
dp | | | 66.80 263 | 65.43 263 | 70.90 280 | 79.74 276 | 48.82 301 | 75.12 281 | 74.77 295 | 59.61 263 | 64.08 276 | 77.23 286 | 42.89 271 | 80.72 282 | 48.86 278 | 66.58 282 | 83.16 277 |
|
MDA-MVSNet-bldmvs | | | 66.68 264 | 63.66 267 | 75.75 250 | 79.28 282 | 60.56 226 | 73.92 285 | 78.35 277 | 64.43 223 | 50.13 311 | 79.87 271 | 44.02 266 | 83.67 271 | 46.10 288 | 56.86 305 | 83.03 280 |
|
testgi | | | 66.67 265 | 66.53 261 | 67.08 291 | 75.62 297 | 41.69 313 | 75.93 273 | 76.50 286 | 66.11 207 | 65.20 271 | 86.59 180 | 35.72 300 | 74.71 305 | 43.71 294 | 73.38 250 | 84.84 263 |
|
PM-MVS | | | 66.41 266 | 64.14 266 | 73.20 269 | 73.92 300 | 56.45 262 | 78.97 257 | 64.96 321 | 63.88 231 | 64.72 272 | 80.24 267 | 19.84 318 | 83.44 273 | 66.24 171 | 64.52 292 | 79.71 295 |
|
JIA-IIPM | | | 66.32 267 | 62.82 273 | 76.82 244 | 77.09 292 | 61.72 219 | 65.34 310 | 75.38 289 | 58.04 274 | 64.51 273 | 62.32 312 | 42.05 278 | 86.51 256 | 51.45 267 | 69.22 271 | 82.21 285 |
|
ADS-MVSNet2 | | | 66.20 268 | 63.33 268 | 74.82 259 | 79.92 274 | 58.75 236 | 67.55 306 | 75.19 291 | 53.37 297 | 65.25 269 | 75.86 290 | 42.32 275 | 80.53 283 | 41.57 298 | 68.91 272 | 85.18 258 |
|
YYNet1 | | | 65.03 269 | 62.91 271 | 71.38 274 | 75.85 295 | 56.60 261 | 69.12 300 | 74.66 299 | 57.28 281 | 54.12 303 | 77.87 283 | 45.85 256 | 74.48 306 | 49.95 274 | 61.52 298 | 83.05 279 |
|
MDA-MVSNet_test_wron | | | 65.03 269 | 62.92 270 | 71.37 275 | 75.93 294 | 56.73 257 | 69.09 301 | 74.73 296 | 57.28 281 | 54.03 304 | 77.89 282 | 45.88 255 | 74.39 307 | 49.89 275 | 61.55 297 | 82.99 281 |
|
Anonymous20231211 | | | 64.82 271 | 61.79 275 | 73.91 267 | 77.11 291 | 50.92 293 | 85.29 189 | 81.53 254 | 54.19 292 | 57.98 293 | 78.03 281 | 26.90 308 | 87.83 249 | 37.92 303 | 57.12 304 | 82.99 281 |
|
Patchmatch-test | | | 64.82 271 | 63.24 269 | 69.57 283 | 79.42 279 | 49.82 299 | 63.49 313 | 69.05 315 | 51.98 302 | 59.95 288 | 80.13 268 | 50.91 226 | 70.98 315 | 40.66 300 | 73.57 248 | 87.90 215 |
|
ADS-MVSNet | | | 64.36 273 | 62.88 272 | 68.78 288 | 79.92 274 | 47.17 303 | 67.55 306 | 71.18 307 | 53.37 297 | 65.25 269 | 75.86 290 | 42.32 275 | 73.99 309 | 41.57 298 | 68.91 272 | 85.18 258 |
|
LF4IMVS | | | 64.02 274 | 62.19 274 | 69.50 284 | 70.90 310 | 53.29 283 | 76.13 271 | 77.18 284 | 52.65 300 | 58.59 290 | 80.98 262 | 23.55 313 | 76.52 299 | 53.06 263 | 66.66 281 | 78.68 297 |
|
UnsupCasMVSNet_bld | | | 63.70 275 | 61.53 277 | 70.21 282 | 73.69 301 | 51.39 291 | 72.82 286 | 81.89 251 | 55.63 288 | 57.81 294 | 71.80 301 | 38.67 289 | 78.61 290 | 49.26 277 | 52.21 312 | 80.63 291 |
|
new-patchmatchnet | | | 61.73 276 | 61.73 276 | 61.70 299 | 72.74 306 | 24.50 329 | 69.16 299 | 78.03 279 | 61.40 250 | 56.72 299 | 75.53 292 | 38.42 290 | 76.48 300 | 45.95 289 | 57.67 303 | 84.13 270 |
|
PVSNet_0 | | 57.27 20 | 61.67 277 | 59.27 278 | 68.85 287 | 79.61 277 | 57.44 252 | 68.01 304 | 73.44 303 | 55.93 287 | 58.54 291 | 70.41 304 | 44.58 263 | 77.55 296 | 47.01 283 | 35.91 317 | 71.55 309 |
|
LP | | | 61.36 278 | 57.78 281 | 72.09 272 | 75.54 298 | 58.53 238 | 67.16 308 | 75.22 290 | 51.90 303 | 54.13 302 | 69.97 305 | 37.73 294 | 80.45 284 | 32.74 310 | 55.63 307 | 77.29 302 |
|
test2356 | | | 59.50 279 | 58.08 279 | 63.74 295 | 71.23 309 | 41.88 311 | 67.59 305 | 72.42 306 | 53.72 296 | 57.65 295 | 70.74 303 | 26.31 309 | 72.40 312 | 32.03 313 | 71.06 265 | 76.93 304 |
|
MVS-HIRNet | | | 59.14 280 | 57.67 282 | 63.57 296 | 81.65 254 | 43.50 309 | 71.73 288 | 65.06 320 | 39.59 315 | 51.43 309 | 57.73 315 | 38.34 291 | 82.58 277 | 39.53 301 | 73.95 244 | 64.62 314 |
|
testus | | | 59.00 281 | 57.91 280 | 62.25 298 | 72.25 307 | 39.09 316 | 69.74 294 | 75.02 292 | 53.04 299 | 57.21 297 | 73.72 297 | 18.76 320 | 70.33 316 | 32.86 309 | 68.57 275 | 77.35 301 |
|
test1235678 | | | 58.74 282 | 56.89 285 | 64.30 293 | 69.70 311 | 41.87 312 | 71.05 290 | 74.87 294 | 54.06 293 | 50.63 310 | 71.53 302 | 25.30 311 | 74.10 308 | 31.80 314 | 63.10 294 | 76.93 304 |
|
pmmvs3 | | | 57.79 283 | 54.26 287 | 68.37 289 | 64.02 317 | 56.72 258 | 75.12 281 | 65.17 319 | 40.20 313 | 52.93 307 | 69.86 306 | 20.36 317 | 75.48 304 | 45.45 291 | 55.25 309 | 72.90 308 |
|
DSMNet-mixed | | | 57.77 284 | 56.90 284 | 60.38 300 | 67.70 315 | 35.61 319 | 69.18 298 | 53.97 324 | 32.30 321 | 57.49 296 | 79.88 270 | 40.39 285 | 68.57 319 | 38.78 302 | 72.37 255 | 76.97 303 |
|
1111 | | | 57.11 285 | 56.82 286 | 57.97 303 | 69.10 312 | 28.28 324 | 68.90 302 | 74.54 300 | 54.01 294 | 53.71 305 | 74.51 294 | 23.09 314 | 67.90 320 | 32.28 311 | 61.26 299 | 77.73 299 |
|
testpf | | | 56.51 286 | 57.58 283 | 53.30 306 | 71.99 308 | 41.19 314 | 46.89 322 | 69.32 314 | 58.06 273 | 52.87 308 | 69.45 307 | 27.99 307 | 72.73 311 | 59.59 224 | 62.07 295 | 45.98 319 |
|
LCM-MVSNet | | | 54.25 287 | 49.68 293 | 67.97 290 | 53.73 324 | 45.28 305 | 66.85 309 | 80.78 260 | 35.96 317 | 39.45 316 | 62.23 313 | 8.70 330 | 78.06 294 | 48.24 280 | 51.20 313 | 80.57 292 |
|
testmv | | | 53.85 288 | 51.03 290 | 62.31 297 | 61.46 319 | 38.88 317 | 70.95 293 | 74.69 298 | 51.11 305 | 41.26 313 | 66.85 308 | 14.28 324 | 72.13 313 | 29.19 316 | 49.51 314 | 75.93 306 |
|
FPMVS | | | 53.68 289 | 51.64 289 | 59.81 301 | 65.08 316 | 51.03 292 | 69.48 297 | 69.58 312 | 41.46 312 | 40.67 314 | 72.32 300 | 16.46 323 | 70.00 317 | 24.24 321 | 65.42 289 | 58.40 316 |
|
N_pmnet | | | 52.79 290 | 53.26 288 | 51.40 309 | 78.99 284 | 7.68 333 | 69.52 296 | 3.89 333 | 51.63 304 | 57.01 298 | 74.98 293 | 40.83 282 | 65.96 322 | 37.78 304 | 64.67 291 | 80.56 293 |
|
no-one | | | 51.08 291 | 45.79 296 | 66.95 292 | 57.92 322 | 50.49 297 | 59.63 317 | 76.04 288 | 48.04 307 | 31.85 317 | 56.10 318 | 19.12 319 | 80.08 286 | 36.89 305 | 26.52 319 | 70.29 310 |
|
new_pmnet | | | 50.91 292 | 50.29 291 | 52.78 307 | 68.58 314 | 34.94 322 | 63.71 312 | 56.63 323 | 39.73 314 | 44.95 312 | 65.47 310 | 21.93 316 | 58.48 324 | 34.98 307 | 56.62 306 | 64.92 313 |
|
ANet_high | | | 50.57 293 | 46.10 295 | 63.99 294 | 48.67 327 | 39.13 315 | 70.99 292 | 80.85 259 | 61.39 251 | 31.18 319 | 57.70 316 | 17.02 322 | 73.65 310 | 31.22 315 | 15.89 326 | 79.18 296 |
|
test12356 | | | 49.28 294 | 48.51 294 | 51.59 308 | 62.06 318 | 19.11 330 | 60.40 315 | 72.45 305 | 47.60 309 | 40.64 315 | 65.68 309 | 13.84 325 | 68.72 318 | 27.29 318 | 46.67 316 | 66.94 312 |
|
.test1245 | | | 45.55 295 | 50.02 292 | 32.14 315 | 69.10 312 | 28.28 324 | 68.90 302 | 74.54 300 | 54.01 294 | 53.71 305 | 74.51 294 | 23.09 314 | 67.90 320 | 32.28 311 | 0.02 329 | 0.25 328 |
|
Gipuma | | | 45.18 296 | 41.86 297 | 55.16 305 | 77.03 293 | 51.52 289 | 32.50 325 | 80.52 262 | 32.46 319 | 27.12 320 | 35.02 322 | 9.52 329 | 75.50 303 | 22.31 322 | 60.21 302 | 38.45 321 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMVS | | 37.38 22 | 44.16 297 | 40.28 298 | 55.82 304 | 40.82 330 | 42.54 310 | 65.12 311 | 63.99 322 | 34.43 318 | 24.48 321 | 57.12 317 | 3.92 332 | 76.17 301 | 17.10 324 | 55.52 308 | 48.75 317 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
PMMVS2 | | | 40.82 298 | 38.86 299 | 46.69 311 | 53.84 323 | 16.45 331 | 48.61 321 | 49.92 326 | 37.49 316 | 31.67 318 | 60.97 314 | 8.14 331 | 56.42 325 | 28.42 317 | 30.72 318 | 67.19 311 |
|
wuykxyi23d | | | 39.76 299 | 33.18 302 | 59.51 302 | 46.98 328 | 44.01 307 | 57.70 318 | 67.74 316 | 24.13 323 | 13.98 328 | 34.33 323 | 1.27 335 | 71.33 314 | 34.23 308 | 18.23 322 | 63.18 315 |
|
PNet_i23d | | | 38.26 300 | 35.42 300 | 46.79 310 | 58.74 320 | 35.48 320 | 59.65 316 | 51.25 325 | 32.45 320 | 23.44 324 | 47.53 320 | 2.04 334 | 58.96 323 | 25.60 320 | 18.09 324 | 45.92 320 |
|
pcd1.5k->3k | | | 34.07 301 | 35.26 301 | 30.50 316 | 86.92 158 | 0.00 336 | 0.00 327 | 91.58 78 | 0.00 331 | 0.00 332 | 0.00 333 | 56.23 183 | 0.00 334 | 0.00 331 | 82.60 151 | 91.49 102 |
|
E-PMN | | | 31.77 302 | 30.64 303 | 35.15 313 | 52.87 325 | 27.67 326 | 57.09 319 | 47.86 327 | 24.64 322 | 16.40 326 | 33.05 324 | 11.23 327 | 54.90 326 | 14.46 326 | 18.15 323 | 22.87 323 |
|
EMVS | | | 30.81 303 | 29.65 304 | 34.27 314 | 50.96 326 | 25.95 328 | 56.58 320 | 46.80 328 | 24.01 324 | 15.53 327 | 30.68 325 | 12.47 326 | 54.43 327 | 12.81 327 | 17.05 325 | 22.43 324 |
|
MVE | | 26.22 23 | 30.37 304 | 25.89 306 | 43.81 312 | 44.55 329 | 35.46 321 | 28.87 326 | 39.07 329 | 18.20 325 | 18.58 325 | 40.18 321 | 2.68 333 | 47.37 328 | 17.07 325 | 23.78 321 | 48.60 318 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
cdsmvs_eth3d_5k | | | 19.96 305 | 26.61 305 | 0.00 322 | 0.00 335 | 0.00 336 | 0.00 327 | 89.26 151 | 0.00 331 | 0.00 332 | 88.61 124 | 61.62 135 | 0.00 334 | 0.00 331 | 0.00 332 | 0.00 330 |
|
tmp_tt | | | 18.61 306 | 21.40 307 | 10.23 319 | 4.82 332 | 10.11 332 | 34.70 324 | 30.74 331 | 1.48 328 | 23.91 323 | 26.07 326 | 28.42 306 | 13.41 331 | 27.12 319 | 15.35 327 | 7.17 325 |
|
wuyk23d | | | 16.82 307 | 15.94 308 | 19.46 318 | 58.74 320 | 31.45 323 | 39.22 323 | 3.74 334 | 6.84 327 | 6.04 329 | 2.70 330 | 1.27 335 | 24.29 330 | 10.54 328 | 14.40 328 | 2.63 326 |
|
ab-mvs-re | | | 7.23 308 | 9.64 309 | 0.00 322 | 0.00 335 | 0.00 336 | 0.00 327 | 0.00 337 | 0.00 331 | 0.00 332 | 86.72 168 | 0.00 339 | 0.00 334 | 0.00 331 | 0.00 332 | 0.00 330 |
|
test123 | | | 6.12 309 | 8.11 310 | 0.14 320 | 0.06 334 | 0.09 334 | 71.05 290 | 0.03 336 | 0.04 330 | 0.25 331 | 1.30 332 | 0.05 337 | 0.03 333 | 0.21 330 | 0.01 331 | 0.29 327 |
|
testmvs | | | 6.04 310 | 8.02 311 | 0.10 321 | 0.08 333 | 0.03 335 | 69.74 294 | 0.04 335 | 0.05 329 | 0.31 330 | 1.68 331 | 0.02 338 | 0.04 332 | 0.24 329 | 0.02 329 | 0.25 328 |
|
pcd_1.5k_mvsjas | | | 5.26 311 | 7.02 312 | 0.00 322 | 0.00 335 | 0.00 336 | 0.00 327 | 0.00 337 | 0.00 331 | 0.00 332 | 0.00 333 | 63.15 100 | 0.00 334 | 0.00 331 | 0.00 332 | 0.00 330 |
|
sosnet-low-res | | | 0.00 312 | 0.00 313 | 0.00 322 | 0.00 335 | 0.00 336 | 0.00 327 | 0.00 337 | 0.00 331 | 0.00 332 | 0.00 333 | 0.00 339 | 0.00 334 | 0.00 331 | 0.00 332 | 0.00 330 |
|
sosnet | | | 0.00 312 | 0.00 313 | 0.00 322 | 0.00 335 | 0.00 336 | 0.00 327 | 0.00 337 | 0.00 331 | 0.00 332 | 0.00 333 | 0.00 339 | 0.00 334 | 0.00 331 | 0.00 332 | 0.00 330 |
|
uncertanet | | | 0.00 312 | 0.00 313 | 0.00 322 | 0.00 335 | 0.00 336 | 0.00 327 | 0.00 337 | 0.00 331 | 0.00 332 | 0.00 333 | 0.00 339 | 0.00 334 | 0.00 331 | 0.00 332 | 0.00 330 |
|
Regformer | | | 0.00 312 | 0.00 313 | 0.00 322 | 0.00 335 | 0.00 336 | 0.00 327 | 0.00 337 | 0.00 331 | 0.00 332 | 0.00 333 | 0.00 339 | 0.00 334 | 0.00 331 | 0.00 332 | 0.00 330 |
|
uanet | | | 0.00 312 | 0.00 313 | 0.00 322 | 0.00 335 | 0.00 336 | 0.00 327 | 0.00 337 | 0.00 331 | 0.00 332 | 0.00 333 | 0.00 339 | 0.00 334 | 0.00 331 | 0.00 332 | 0.00 330 |
|
sam_mvs1 | | | | | | | | | | | | | 51.32 222 | | | | |
|
sam_mvs | | | | | | | | | | | | | 50.01 235 | | | | |
|
semantic-postprocess | | | | | 80.11 203 | 82.69 243 | 64.85 161 | | 83.47 235 | 69.16 174 | 70.49 215 | 84.15 223 | 50.83 230 | 88.15 244 | 69.23 151 | 72.14 258 | 87.34 227 |
|
ambc | | | | | 75.24 256 | 73.16 304 | 50.51 296 | 63.05 314 | 87.47 198 | | 64.28 274 | 77.81 284 | 17.80 321 | 89.73 220 | 57.88 240 | 60.64 300 | 85.49 255 |
|
MTGPA | | | | | | | | | 92.02 56 | | | | | | | | |
|
test_post1 | | | | | | | | 78.90 259 | | | | 5.43 329 | 48.81 245 | 85.44 264 | 59.25 227 | | |
|
test_post | | | | | | | | | | | | 5.46 328 | 50.36 234 | 84.24 269 | | | |
|
patchmatchnet-post | | | | | | | | | | | | 74.00 296 | 51.12 225 | 88.60 240 | | | |
|
GG-mvs-BLEND | | | | | 75.38 255 | 81.59 255 | 55.80 271 | 79.32 253 | 69.63 311 | | 67.19 255 | 73.67 298 | 43.24 268 | 88.90 238 | 50.41 270 | 84.50 132 | 81.45 289 |
|
MTMP | | | | | | | | | 32.83 330 | | | | | | | | |
|
gm-plane-assit | | | | | | 81.40 257 | 53.83 281 | | | 62.72 241 | | 80.94 263 | | 92.39 166 | 63.40 192 | | |
|
test9_res | | | | | | | | | | | | | | | 84.90 17 | 95.70 12 | 92.87 67 |
|
TEST9 | | | | | | 93.26 33 | 72.96 19 | 88.75 83 | 91.89 65 | 68.44 188 | 85.00 27 | 93.10 39 | 74.36 16 | 95.41 47 | | | |
|
test_8 | | | | | | 93.13 35 | 72.57 28 | 88.68 86 | 91.84 68 | 68.69 184 | 84.87 33 | 93.10 39 | 74.43 13 | 95.16 55 | | | |
|
agg_prior2 | | | | | | | | | | | | | | | 82.91 38 | 95.45 14 | 92.70 68 |
|
agg_prior | | | | | | 92.85 41 | 71.94 38 | | 91.78 71 | | 84.41 39 | | | 94.93 64 | | | |
|
TestCases | | | | | 79.58 211 | 85.15 177 | 63.62 189 | | 79.83 270 | 62.31 244 | 60.32 286 | 86.73 166 | 32.02 303 | 88.96 235 | 50.28 271 | 71.57 262 | 86.15 248 |
|
test_prior4 | | | | | | | 72.60 27 | 89.01 74 | | | | | | | | | |
|
test_prior2 | | | | | | | | 88.85 78 | | 75.41 75 | 84.91 29 | 93.54 29 | 74.28 17 | | 83.31 31 | 95.86 6 | |
|
test_prior | | | | | 86.33 45 | 92.61 46 | 69.59 70 | | 92.97 29 | | | | | 95.48 42 | | | 93.91 29 |
|
旧先验2 | | | | | | | | 86.56 160 | | 58.10 272 | 87.04 13 | | | 88.98 233 | 74.07 108 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 86.29 169 | | | | | | | | | |
|
æ–°å‡ ä½•1 | | | | | 83.42 111 | 93.13 35 | 70.71 53 | | 85.48 218 | 57.43 279 | 81.80 69 | 91.98 55 | 63.28 95 | 92.27 170 | 64.60 187 | 92.99 46 | 87.27 229 |
|
旧先验1 | | | | | | 91.96 54 | 65.79 139 | | 86.37 210 | | | 93.08 43 | 69.31 51 | | | 92.74 49 | 88.74 190 |
|
æ— å…ˆéªŒ | | | | | | | | 87.48 124 | 88.98 163 | 60.00 260 | | | | 94.12 92 | 67.28 164 | | 88.97 184 |
|
原ACMM2 | | | | | | | | 86.86 148 | | | | | | | | | |
|
原ACMM1 | | | | | 84.35 84 | 93.01 39 | 68.79 84 | | 92.44 41 | 63.96 230 | 81.09 76 | 91.57 65 | 66.06 74 | 95.45 44 | 67.19 166 | 94.82 29 | 88.81 187 |
|
test222 | | | | | | 91.50 59 | 68.26 100 | 84.16 213 | 83.20 238 | 54.63 291 | 79.74 84 | 91.63 63 | 58.97 164 | | | 91.42 59 | 86.77 240 |
|
testdata2 | | | | | | | | | | | | | | 91.01 205 | 62.37 200 | | |
|
segment_acmp | | | | | | | | | | | | | 73.08 23 | | | | |
|
testdata | | | | | 79.97 205 | 90.90 66 | 64.21 180 | | 84.71 224 | 59.27 266 | 85.40 22 | 92.91 44 | 62.02 132 | 89.08 231 | 68.95 153 | 91.37 60 | 86.63 244 |
|
testdata1 | | | | | | | | 84.14 214 | | 75.71 70 | | | | | | | |
|
test12 | | | | | 86.80 37 | 92.63 45 | 70.70 54 | | 91.79 70 | | 82.71 61 | | 71.67 32 | 96.16 28 | | 94.50 33 | 93.54 45 |
|
plane_prior7 | | | | | | 90.08 76 | 68.51 96 | | | | | | | | | | |
|
plane_prior6 | | | | | | 89.84 81 | 68.70 92 | | | | | | 60.42 157 | | | | |
|
plane_prior5 | | | | | | | | | 92.44 41 | | | | | 95.38 49 | 78.71 62 | 86.32 118 | 91.33 104 |
|
plane_prior4 | | | | | | | | | | | | 91.00 78 | | | | | |
|
plane_prior3 | | | | | | | 68.60 94 | | | 78.44 29 | 78.92 93 | | | | | | |
|
plane_prior2 | | | | | | | | 91.25 28 | | 79.12 22 | | | | | | | |
|
plane_prior1 | | | | | | 89.90 80 | | | | | | | | | | | |
|
plane_prior | | | | | | | 68.71 90 | 90.38 44 | | 77.62 33 | | | | | | 86.16 120 | |
|
n2 | | | | | | | | | 0.00 337 | | | | | | | | |
|
nn | | | | | | | | | 0.00 337 | | | | | | | | |
|
door-mid | | | | | | | | | 69.98 310 | | | | | | | | |
|
lessismore_v0 | | | | | 78.97 217 | 81.01 264 | 57.15 253 | | 65.99 318 | | 61.16 283 | 82.82 236 | 39.12 288 | 91.34 193 | 59.67 222 | 46.92 315 | 88.43 206 |
|
LGP-MVS_train | | | | | 84.50 78 | 89.23 99 | 68.76 86 | | 91.94 63 | 75.37 77 | 76.64 142 | 91.51 66 | 54.29 198 | 94.91 66 | 78.44 64 | 83.78 138 | 89.83 162 |
|
test11 | | | | | | | | | 92.23 48 | | | | | | | | |
|
door | | | | | | | | | 69.44 313 | | | | | | | | |
|
HQP5-MVS | | | | | | | 66.98 121 | | | | | | | | | | |
|
HQP-NCC | | | | | | 89.33 91 | | 89.17 67 | | 76.41 58 | 77.23 133 | | | | | | |
|
ACMP_Plane | | | | | | 89.33 91 | | 89.17 67 | | 76.41 58 | 77.23 133 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.47 74 | | |
|
HQP4-MVS | | | | | | | | | | | 77.24 132 | | | 95.11 57 | | | 91.03 110 |
|
HQP3-MVS | | | | | | | | | 92.19 51 | | | | | | | 85.99 122 | |
|
HQP2-MVS | | | | | | | | | | | | | 60.17 160 | | | | |
|
NP-MVS | | | | | | 89.62 84 | 68.32 98 | | | | | 90.24 89 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 37.79 318 | 75.16 279 | | 55.10 289 | 66.53 261 | | 49.34 239 | | 53.98 257 | | 87.94 214 |
|
MDTV_nov1_ep13 | | | | 69.97 237 | | 83.18 229 | 53.48 282 | 77.10 270 | 80.18 269 | 60.45 255 | 69.33 234 | 80.44 265 | 48.89 244 | 86.90 252 | 51.60 266 | 78.51 188 | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 81.95 157 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 81.25 162 | |
|
Test By Simon | | | | | | | | | | | | | 64.33 85 | | | | |
|
ITE_SJBPF | | | | | 78.22 229 | 81.77 253 | 60.57 225 | | 83.30 237 | 69.25 172 | 67.54 251 | 87.20 159 | 36.33 298 | 87.28 251 | 54.34 256 | 74.62 239 | 86.80 239 |
|
DeepMVS_CX | | | | | 27.40 317 | 40.17 331 | 26.90 327 | | 24.59 332 | 17.44 326 | 23.95 322 | 48.61 319 | 9.77 328 | 26.48 329 | 18.06 323 | 24.47 320 | 28.83 322 |
|