APDe-MVS | | | 89.15 1 | 89.63 1 | 87.73 15 | 94.49 8 | 71.69 34 | 93.83 2 | 93.96 2 | 75.70 64 | 91.06 1 | 96.03 1 | 76.84 2 | 97.03 3 | 89.09 1 | 95.65 11 | 94.47 9 |
|
HPM-MVS++ | | | 89.02 2 | 89.15 2 | 88.63 1 | 95.01 1 | 76.03 1 | 92.38 13 | 92.85 30 | 80.26 11 | 87.78 8 | 94.27 12 | 75.89 6 | 96.81 6 | 87.45 5 | 96.44 1 | 93.05 53 |
|
CNVR-MVS | | | 88.93 3 | 89.13 3 | 88.33 3 | 94.77 2 | 73.82 4 | 90.51 35 | 93.00 22 | 80.90 8 | 88.06 6 | 94.06 19 | 76.43 3 | 96.84 5 | 88.48 2 | 95.99 2 | 94.34 12 |
|
SteuartSystems-ACMMP | | | 88.72 4 | 88.86 4 | 88.32 4 | 92.14 46 | 72.96 15 | 93.73 3 | 93.67 6 | 80.19 12 | 88.10 5 | 94.80 2 | 73.76 18 | 97.11 1 | 87.51 4 | 95.82 6 | 94.90 3 |
Skip Steuart: Steuart Systems R&D Blog. |
DeepPCF-MVS | | 80.84 1 | 88.10 5 | 88.56 5 | 86.73 31 | 92.24 44 | 69.03 66 | 89.57 54 | 93.39 11 | 77.53 33 | 89.79 3 | 94.12 17 | 78.98 1 | 96.58 16 | 85.66 6 | 95.72 7 | 94.58 6 |
|
SD-MVS | | | 88.06 6 | 88.50 6 | 86.71 32 | 92.60 42 | 72.71 20 | 91.81 22 | 93.19 16 | 77.87 27 | 90.32 2 | 94.00 20 | 74.83 8 | 93.78 99 | 87.63 3 | 94.27 35 | 93.65 35 |
|
NCCC | | | 88.06 6 | 88.01 7 | 88.24 5 | 94.41 12 | 73.62 5 | 91.22 28 | 92.83 31 | 81.50 5 | 85.79 15 | 93.47 27 | 73.02 22 | 97.00 4 | 84.90 11 | 94.94 20 | 94.10 17 |
|
MP-MVS |  | | 87.71 8 | 87.64 8 | 87.93 12 | 94.36 14 | 73.88 2 | 92.71 12 | 92.65 36 | 77.57 30 | 83.84 41 | 94.40 11 | 72.24 28 | 96.28 21 | 85.65 7 | 95.30 17 | 93.62 37 |
|
HFP-MVS | | | 87.58 9 | 87.47 10 | 87.94 10 | 94.58 5 | 73.54 9 | 93.04 5 | 93.24 13 | 76.78 46 | 84.91 23 | 94.44 8 | 70.78 34 | 96.61 12 | 84.53 16 | 94.89 22 | 93.66 30 |
|
ACMMPR | | | 87.44 10 | 87.23 12 | 88.08 7 | 94.64 3 | 73.59 6 | 93.04 5 | 93.20 15 | 76.78 46 | 84.66 29 | 94.52 3 | 68.81 49 | 96.65 10 | 84.53 16 | 94.90 21 | 94.00 23 |
|
APD-MVS |  | | 87.44 10 | 87.52 9 | 87.19 23 | 94.24 15 | 72.39 28 | 91.86 21 | 92.83 31 | 73.01 102 | 88.58 4 | 94.52 3 | 73.36 19 | 96.49 17 | 84.26 20 | 95.01 19 | 92.70 60 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
region2R | | | 87.42 12 | 87.20 13 | 88.09 6 | 94.63 4 | 73.55 7 | 93.03 7 | 93.12 18 | 76.73 49 | 84.45 32 | 94.52 3 | 69.09 47 | 96.70 9 | 84.37 19 | 94.83 24 | 94.03 20 |
|
MCST-MVS | | | 87.37 13 | 87.25 11 | 87.73 15 | 94.53 7 | 72.46 27 | 89.82 48 | 93.82 4 | 73.07 101 | 84.86 28 | 92.89 39 | 76.22 4 | 96.33 19 | 84.89 13 | 95.13 18 | 94.40 10 |
|
#test# | | | 87.33 14 | 87.13 14 | 87.94 10 | 94.58 5 | 73.54 9 | 92.34 14 | 93.24 13 | 75.23 71 | 84.91 23 | 94.44 8 | 70.78 34 | 96.61 12 | 83.75 23 | 94.89 22 | 93.66 30 |
|
XVS | | | 87.18 15 | 86.91 17 | 88.00 8 | 94.42 10 | 73.33 13 | 92.78 8 | 92.99 24 | 79.14 16 | 83.67 44 | 94.17 15 | 67.45 55 | 96.60 14 | 83.06 28 | 94.50 28 | 94.07 18 |
|
HPM-MVS | | | 87.11 16 | 86.98 15 | 87.50 20 | 93.88 19 | 72.16 31 | 92.19 17 | 93.33 12 | 76.07 61 | 83.81 42 | 93.95 21 | 69.77 43 | 96.01 26 | 85.15 8 | 94.66 26 | 94.32 13 |
|
CP-MVS | | | 87.11 16 | 86.92 16 | 87.68 19 | 94.20 17 | 73.86 3 | 93.98 1 | 92.82 33 | 76.62 51 | 83.68 43 | 94.46 7 | 67.93 51 | 95.95 27 | 84.20 21 | 94.39 31 | 93.23 47 |
|
DeepC-MVS | | 79.81 2 | 87.08 18 | 86.88 18 | 87.69 18 | 91.16 56 | 72.32 30 | 90.31 41 | 93.94 3 | 77.12 38 | 82.82 53 | 94.23 14 | 72.13 29 | 97.09 2 | 84.83 14 | 95.37 14 | 93.65 35 |
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 19 | 86.62 20 | 87.76 14 | 93.52 22 | 72.37 29 | 91.26 25 | 93.04 19 | 76.62 51 | 84.22 37 | 93.36 29 | 71.44 32 | 96.76 7 | 80.82 42 | 95.33 15 | 94.16 15 |
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 20 | 86.86 19 | 86.33 38 | 92.61 40 | 69.59 58 | 88.85 68 | 92.97 27 | 75.41 67 | 84.91 23 | 93.54 23 | 74.28 15 | 95.48 34 | 83.31 24 | 95.86 4 | 93.91 25 |
|
PGM-MVS | | | 86.68 21 | 86.27 24 | 87.90 13 | 94.22 16 | 73.38 12 | 90.22 43 | 93.04 19 | 75.53 66 | 83.86 40 | 94.42 10 | 67.87 53 | 96.64 11 | 82.70 33 | 94.57 27 | 93.66 30 |
|
mPP-MVS | | | 86.67 22 | 86.32 23 | 87.72 17 | 94.41 12 | 73.55 7 | 92.74 10 | 92.22 45 | 76.87 44 | 82.81 54 | 94.25 13 | 66.44 62 | 96.24 22 | 82.88 32 | 94.28 34 | 93.38 43 |
|
Regformer-2 | | | 86.63 23 | 86.53 21 | 86.95 28 | 89.33 83 | 71.24 37 | 88.43 80 | 92.05 51 | 82.50 1 | 86.88 11 | 90.09 85 | 74.45 10 | 95.61 30 | 84.38 18 | 90.63 59 | 94.01 22 |
|
train_agg | | | 86.43 24 | 86.20 25 | 87.13 25 | 93.26 27 | 72.96 15 | 88.75 72 | 91.89 58 | 68.69 163 | 85.00 21 | 93.10 33 | 74.43 11 | 95.41 39 | 84.97 9 | 95.71 8 | 93.02 54 |
|
PHI-MVS | | | 86.43 24 | 86.17 27 | 87.24 22 | 90.88 61 | 70.96 40 | 92.27 16 | 94.07 1 | 72.45 113 | 85.22 19 | 91.90 51 | 69.47 44 | 96.42 18 | 83.28 26 | 95.94 3 | 94.35 11 |
|
Regformer-1 | | | 86.41 26 | 86.33 22 | 86.64 33 | 89.33 83 | 70.93 41 | 88.43 80 | 91.39 77 | 82.14 3 | 86.65 12 | 90.09 85 | 74.39 13 | 95.01 55 | 83.97 22 | 90.63 59 | 93.97 24 |
|
CSCG | | | 86.41 26 | 86.19 26 | 87.07 27 | 92.91 34 | 72.48 26 | 90.81 31 | 93.56 7 | 73.95 84 | 83.16 49 | 91.07 67 | 75.94 5 | 95.19 46 | 79.94 49 | 94.38 32 | 93.55 39 |
|
agg_prior1 | | | 86.22 28 | 86.09 28 | 86.62 34 | 92.85 35 | 71.94 32 | 88.59 77 | 91.78 64 | 68.96 160 | 84.41 33 | 93.18 32 | 74.94 7 | 94.93 56 | 84.75 15 | 95.33 15 | 93.01 56 |
|
agg_prior3 | | | 86.16 29 | 85.85 31 | 87.10 26 | 93.31 24 | 72.86 19 | 88.77 71 | 91.68 68 | 68.29 169 | 84.26 36 | 92.83 41 | 72.83 23 | 95.42 38 | 84.97 9 | 95.71 8 | 93.02 54 |
|
APD-MVS_3200maxsize | | | 85.97 30 | 85.88 29 | 86.22 41 | 92.69 38 | 69.53 60 | 91.93 20 | 92.99 24 | 73.54 91 | 85.94 13 | 94.51 6 | 65.80 69 | 95.61 30 | 83.04 30 | 92.51 45 | 93.53 41 |
|
canonicalmvs | | | 85.91 31 | 85.87 30 | 86.04 44 | 89.84 75 | 69.44 64 | 90.45 39 | 93.00 22 | 76.70 50 | 88.01 7 | 91.23 64 | 73.28 20 | 93.91 90 | 81.50 38 | 88.80 76 | 94.77 4 |
|
ACMMP |  | | 85.89 32 | 85.39 34 | 87.38 21 | 93.59 21 | 72.63 22 | 92.74 10 | 93.18 17 | 76.78 46 | 80.73 68 | 93.82 22 | 64.33 77 | 96.29 20 | 82.67 34 | 90.69 58 | 93.23 47 |
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 33 | 85.29 38 | 87.17 24 | 93.49 23 | 71.08 38 | 88.58 78 | 92.42 41 | 68.32 168 | 84.61 30 | 93.48 25 | 72.32 27 | 96.15 24 | 79.00 50 | 95.43 13 | 94.28 14 |
|
TSAR-MVS | | | 85.71 34 | 85.33 35 | 86.84 29 | 91.34 54 | 72.50 25 | 89.07 64 | 87.28 176 | 76.41 53 | 85.80 14 | 90.22 83 | 74.15 17 | 95.37 43 | 81.82 36 | 91.88 47 | 92.65 63 |
|
Regformer-4 | | | 85.68 35 | 85.45 33 | 86.35 37 | 88.95 95 | 69.67 57 | 88.29 89 | 91.29 79 | 81.73 4 | 85.36 17 | 90.01 87 | 72.62 25 | 95.35 44 | 83.28 26 | 87.57 89 | 94.03 20 |
|
alignmvs | | | 85.48 36 | 85.32 36 | 85.96 45 | 89.51 79 | 69.47 62 | 89.74 51 | 92.47 37 | 76.17 59 | 87.73 9 | 91.46 62 | 70.32 37 | 93.78 99 | 81.51 37 | 88.95 73 | 94.63 5 |
|
3Dnovator+ | | 77.84 4 | 85.48 36 | 84.47 43 | 88.51 2 | 91.08 57 | 73.49 11 | 93.18 4 | 93.78 5 | 80.79 9 | 76.66 127 | 93.37 28 | 60.40 147 | 96.75 8 | 77.20 64 | 93.73 38 | 95.29 1 |
|
MSLP-MVS | | | 85.43 38 | 85.76 32 | 84.45 69 | 91.93 49 | 70.24 49 | 90.71 32 | 92.86 29 | 77.46 35 | 84.22 37 | 92.81 44 | 67.16 58 | 92.94 135 | 80.36 45 | 94.35 33 | 90.16 133 |
|
DELS-MVS | | | 85.41 39 | 85.30 37 | 85.77 46 | 88.49 109 | 67.93 91 | 85.52 167 | 93.44 9 | 78.70 23 | 83.63 46 | 89.03 108 | 74.57 9 | 95.71 29 | 80.26 47 | 94.04 36 | 93.66 30 |
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 40 | 84.95 41 | 86.57 36 | 93.69 20 | 70.58 47 | 92.15 18 | 91.62 69 | 73.89 85 | 82.67 56 | 94.09 18 | 62.60 109 | 95.54 33 | 80.93 40 | 92.93 40 | 93.57 38 |
|
Regformer-3 | | | 85.23 41 | 85.07 39 | 85.70 47 | 88.95 95 | 69.01 68 | 88.29 89 | 89.91 123 | 80.95 7 | 85.01 20 | 90.01 87 | 72.45 26 | 94.19 78 | 82.50 35 | 87.57 89 | 93.90 27 |
|
MVS_111021_HR | | | 85.14 42 | 84.75 42 | 86.32 40 | 91.65 52 | 72.70 21 | 85.98 157 | 90.33 106 | 76.11 60 | 82.08 58 | 91.61 57 | 71.36 33 | 94.17 79 | 81.02 39 | 92.58 44 | 92.08 78 |
|
UA-Net | | | 85.08 43 | 84.96 40 | 85.45 48 | 92.07 47 | 68.07 90 | 89.78 50 | 90.86 89 | 82.48 2 | 84.60 31 | 93.20 31 | 69.35 45 | 95.22 45 | 71.39 121 | 90.88 57 | 93.07 52 |
|
EI-MVSNet-Vis-set | | | 84.19 44 | 83.81 44 | 85.31 50 | 88.18 117 | 67.85 92 | 87.66 104 | 89.73 127 | 80.05 14 | 82.95 50 | 89.59 94 | 70.74 36 | 94.82 63 | 80.66 44 | 84.72 115 | 93.28 46 |
|
nrg030 | | | 83.88 45 | 83.53 45 | 84.96 57 | 86.77 147 | 69.28 65 | 90.46 38 | 92.67 34 | 74.79 75 | 82.95 50 | 91.33 63 | 72.70 24 | 93.09 130 | 80.79 43 | 79.28 162 | 92.50 66 |
|
EI-MVSNet-UG-set | | | 83.81 46 | 83.38 47 | 85.09 54 | 87.87 124 | 67.53 96 | 87.44 115 | 89.66 128 | 79.74 15 | 82.23 57 | 89.41 103 | 70.24 38 | 94.74 65 | 79.95 48 | 83.92 120 | 92.99 57 |
|
CPTT-MVS | | | 83.73 47 | 83.33 48 | 84.92 60 | 93.28 26 | 70.86 43 | 92.09 19 | 90.38 101 | 68.75 162 | 79.57 73 | 92.83 41 | 60.60 143 | 93.04 133 | 80.92 41 | 91.56 51 | 90.86 103 |
|
EPNet | | | 83.72 48 | 82.92 52 | 86.14 43 | 84.22 175 | 69.48 61 | 91.05 30 | 85.27 196 | 81.30 6 | 76.83 124 | 91.65 54 | 66.09 65 | 95.56 32 | 76.00 74 | 93.85 37 | 93.38 43 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
HQP_MVS | | | 83.64 49 | 83.14 49 | 85.14 53 | 90.08 70 | 68.71 77 | 91.25 26 | 92.44 38 | 79.12 18 | 78.92 80 | 91.00 71 | 60.42 145 | 95.38 41 | 78.71 53 | 86.32 102 | 91.33 92 |
|
Vis-MVSNet |  | | 83.46 50 | 82.80 54 | 85.43 49 | 90.25 68 | 68.74 76 | 90.30 42 | 90.13 115 | 76.33 58 | 80.87 67 | 92.89 39 | 61.00 137 | 94.20 77 | 72.45 109 | 90.97 55 | 93.35 45 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MG-MVS | | | 83.41 51 | 83.45 46 | 83.28 98 | 92.74 37 | 62.28 192 | 88.17 93 | 89.50 131 | 75.22 72 | 81.49 61 | 92.74 45 | 66.75 59 | 95.11 49 | 72.85 102 | 91.58 50 | 92.45 67 |
|
EPP-MVSNet | | | 83.40 52 | 83.02 51 | 84.57 65 | 90.13 69 | 64.47 155 | 92.32 15 | 90.73 90 | 74.45 78 | 79.35 76 | 91.10 65 | 69.05 48 | 95.12 48 | 72.78 103 | 87.22 93 | 94.13 16 |
|
3Dnovator | | 76.31 5 | 83.38 53 | 82.31 59 | 86.59 35 | 87.94 123 | 72.94 18 | 90.64 33 | 92.14 49 | 77.21 36 | 75.47 139 | 92.83 41 | 58.56 154 | 94.72 66 | 73.24 100 | 92.71 43 | 92.13 77 |
|
MVS_Test | | | 83.15 54 | 83.06 50 | 83.41 95 | 86.86 144 | 63.21 179 | 86.11 155 | 92.00 52 | 74.31 79 | 82.87 52 | 89.44 102 | 70.03 39 | 93.21 121 | 77.39 63 | 88.50 84 | 93.81 29 |
|
IS-MVSNet | | | 83.15 54 | 82.81 53 | 84.18 77 | 89.94 73 | 63.30 176 | 91.59 23 | 88.46 163 | 79.04 20 | 79.49 74 | 92.16 46 | 65.10 73 | 94.28 73 | 67.71 140 | 91.86 48 | 94.95 2 |
|
DP-MVS Recon | | | 83.11 56 | 82.09 61 | 86.15 42 | 94.44 9 | 70.92 42 | 88.79 70 | 92.20 46 | 70.53 136 | 79.17 77 | 91.03 70 | 64.12 79 | 96.03 25 | 68.39 139 | 90.14 64 | 91.50 89 |
|
PAPM_NR | | | 83.02 57 | 82.41 56 | 84.82 62 | 92.47 43 | 66.37 110 | 87.93 100 | 91.80 62 | 73.82 86 | 77.32 116 | 90.66 76 | 67.90 52 | 94.90 60 | 70.37 125 | 89.48 70 | 93.19 49 |
|
VDD-MVS | | | 83.01 58 | 82.36 58 | 84.96 57 | 91.02 58 | 66.40 109 | 88.91 66 | 88.11 165 | 77.57 30 | 84.39 35 | 93.29 30 | 52.19 195 | 93.91 90 | 77.05 66 | 88.70 78 | 94.57 7 |
|
MVSFormer | | | 82.85 59 | 82.05 62 | 85.24 52 | 87.35 137 | 70.21 50 | 90.50 36 | 90.38 101 | 68.55 165 | 81.32 62 | 89.47 97 | 61.68 123 | 93.46 114 | 78.98 51 | 90.26 62 | 92.05 79 |
|
OMC-MVS | | | 82.69 60 | 81.97 65 | 84.85 61 | 88.75 103 | 67.42 97 | 87.98 96 | 90.87 88 | 74.92 74 | 79.72 72 | 91.65 54 | 62.19 120 | 93.96 85 | 75.26 85 | 86.42 101 | 93.16 50 |
|
PVSNet_Blended_VisFu | | | 82.62 61 | 81.83 66 | 84.96 57 | 90.80 63 | 69.76 56 | 88.74 74 | 91.70 67 | 69.39 150 | 78.96 79 | 88.46 121 | 65.47 70 | 94.87 62 | 74.42 89 | 88.57 81 | 90.24 131 |
|
MVS_111021_LR | | | 82.61 62 | 82.11 60 | 84.11 78 | 88.82 99 | 71.58 35 | 85.15 169 | 86.16 189 | 74.69 76 | 80.47 69 | 91.04 68 | 62.29 117 | 90.55 190 | 80.33 46 | 90.08 65 | 90.20 132 |
|
HQP-MVS | | | 82.61 62 | 82.02 63 | 84.37 70 | 89.33 83 | 66.98 104 | 89.17 59 | 92.19 47 | 76.41 53 | 77.23 119 | 90.23 82 | 60.17 148 | 95.11 49 | 77.47 61 | 85.99 106 | 91.03 97 |
|
CLD-MVS | | | 82.31 64 | 81.65 67 | 84.29 74 | 88.47 110 | 67.73 95 | 85.81 163 | 92.35 43 | 75.78 62 | 78.33 93 | 86.58 164 | 64.01 80 | 94.35 71 | 76.05 73 | 87.48 91 | 90.79 104 |
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 65 | 82.41 56 | 81.62 155 | 90.82 62 | 60.93 198 | 84.47 181 | 89.78 125 | 76.36 57 | 84.07 39 | 91.88 52 | 64.71 76 | 90.26 192 | 70.68 122 | 88.89 74 | 93.66 30 |
|
LPG-MVS_test | | | 82.08 66 | 81.27 70 | 84.50 67 | 89.23 91 | 68.76 74 | 90.22 43 | 91.94 56 | 75.37 69 | 76.64 128 | 91.51 59 | 54.29 181 | 94.91 58 | 78.44 55 | 83.78 121 | 89.83 148 |
|
FIs | | | 82.07 67 | 82.42 55 | 81.04 168 | 88.80 101 | 58.34 218 | 88.26 91 | 93.49 8 | 76.93 43 | 78.47 87 | 91.04 68 | 69.92 41 | 92.34 150 | 69.87 129 | 84.97 111 | 92.44 68 |
|
PS-MVSNAJss | | | 82.07 67 | 81.31 69 | 84.34 73 | 86.51 149 | 67.27 101 | 89.27 57 | 91.51 73 | 71.75 121 | 79.37 75 | 90.22 83 | 63.15 90 | 94.27 74 | 77.69 59 | 82.36 135 | 91.49 90 |
|
API-MVS | | | 81.99 69 | 81.23 71 | 84.26 75 | 90.94 59 | 70.18 52 | 91.10 29 | 89.32 135 | 71.51 127 | 78.66 84 | 88.28 125 | 65.26 71 | 95.10 52 | 64.74 165 | 91.23 54 | 87.51 198 |
|
UniMVSNet_NR-MVSNet | | | 81.88 70 | 81.54 68 | 82.92 117 | 88.46 111 | 63.46 172 | 87.13 126 | 92.37 42 | 80.19 12 | 78.38 91 | 89.14 105 | 71.66 31 | 93.05 131 | 70.05 126 | 76.46 194 | 92.25 73 |
|
MAR-MVS | | | 81.84 71 | 80.70 76 | 85.27 51 | 91.32 55 | 71.53 36 | 89.82 48 | 90.92 87 | 69.77 145 | 78.50 86 | 86.21 173 | 62.36 116 | 94.52 70 | 65.36 159 | 92.05 46 | 89.77 151 |
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 72 | 81.23 71 | 83.57 91 | 91.89 50 | 63.43 174 | 89.84 47 | 81.85 226 | 77.04 41 | 83.21 47 | 93.10 33 | 52.26 194 | 93.43 118 | 71.98 115 | 89.95 67 | 93.85 28 |
|
PS-MVSNAJ | | | 81.69 73 | 81.02 74 | 83.70 88 | 89.51 79 | 68.21 88 | 84.28 188 | 90.09 116 | 70.79 133 | 81.26 64 | 85.62 185 | 63.15 90 | 94.29 72 | 75.62 81 | 88.87 75 | 88.59 178 |
|
PAPR | | | 81.66 74 | 80.89 75 | 83.99 83 | 90.27 67 | 64.00 165 | 86.76 141 | 91.77 66 | 68.84 161 | 77.13 123 | 89.50 95 | 67.63 54 | 94.88 61 | 67.55 141 | 88.52 83 | 93.09 51 |
|
UniMVSNet (Re) | | | 81.60 75 | 81.11 73 | 83.09 106 | 88.38 114 | 64.41 157 | 87.60 105 | 93.02 21 | 78.42 26 | 78.56 85 | 88.16 126 | 69.78 42 | 93.26 120 | 69.58 131 | 76.49 193 | 91.60 85 |
|
FC-MVSNet-test | | | 81.52 76 | 82.02 63 | 80.03 181 | 88.42 113 | 55.97 246 | 87.95 98 | 93.42 10 | 77.10 39 | 77.38 114 | 90.98 73 | 69.96 40 | 91.79 157 | 68.46 138 | 84.50 116 | 92.33 70 |
|
VDDNet | | | 81.52 76 | 80.67 77 | 84.05 81 | 90.44 65 | 64.13 161 | 89.73 52 | 85.91 192 | 71.11 129 | 83.18 48 | 93.48 25 | 50.54 204 | 93.49 113 | 73.40 99 | 88.25 86 | 94.54 8 |
|
ACMP | | 74.13 6 | 81.51 78 | 80.57 78 | 84.36 71 | 89.42 81 | 68.69 80 | 89.97 46 | 91.50 75 | 74.46 77 | 75.04 154 | 90.41 79 | 53.82 186 | 94.54 68 | 77.56 60 | 82.91 127 | 89.86 147 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
jason | | | 81.39 79 | 80.29 83 | 84.70 64 | 86.63 148 | 69.90 54 | 85.95 158 | 86.77 180 | 63.24 208 | 81.07 66 | 89.47 97 | 61.08 136 | 92.15 153 | 78.33 58 | 90.07 66 | 92.05 79 |
jason: jason. |
lupinMVS | | | 81.39 79 | 80.27 84 | 84.76 63 | 87.35 137 | 70.21 50 | 85.55 165 | 86.41 184 | 62.85 214 | 81.32 62 | 88.61 116 | 61.68 123 | 92.24 152 | 78.41 57 | 90.26 62 | 91.83 81 |
|
DU-MVS | | | 81.12 81 | 80.52 80 | 82.90 118 | 87.80 127 | 63.46 172 | 87.02 131 | 91.87 60 | 79.01 21 | 78.38 91 | 89.07 106 | 65.02 74 | 93.05 131 | 70.05 126 | 76.46 194 | 92.20 74 |
|
PVSNet_Blended | | | 80.98 82 | 80.34 81 | 82.90 118 | 88.85 97 | 65.40 126 | 84.43 184 | 92.00 52 | 67.62 173 | 78.11 102 | 85.05 194 | 66.02 67 | 94.27 74 | 71.52 119 | 89.50 69 | 89.01 161 |
|
QAPM | | | 80.88 83 | 79.50 95 | 85.03 55 | 88.01 122 | 68.97 70 | 91.59 23 | 92.00 52 | 66.63 182 | 75.15 151 | 92.16 46 | 57.70 159 | 95.45 36 | 63.52 168 | 88.76 77 | 90.66 112 |
|
liao | | | 80.84 84 | 79.77 88 | 84.05 81 | 93.11 31 | 70.78 44 | 84.66 176 | 85.42 195 | 57.37 253 | 81.76 60 | 92.02 48 | 63.41 84 | 94.12 80 | 67.28 144 | 92.93 40 | 87.26 204 |
|
TranMVSNet+NR-MVSNet | | | 80.84 84 | 80.31 82 | 82.42 134 | 87.85 125 | 62.33 190 | 87.74 103 | 91.33 78 | 80.55 10 | 77.99 105 | 89.86 89 | 65.23 72 | 92.62 140 | 67.05 148 | 75.24 211 | 92.30 71 |
|
UGNet | | | 80.83 86 | 79.59 90 | 84.54 66 | 88.04 120 | 68.09 89 | 89.42 55 | 88.16 164 | 76.95 42 | 76.22 131 | 89.46 99 | 49.30 209 | 93.94 87 | 68.48 137 | 90.31 61 | 91.60 85 |
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 |
XVG-OURS-SEG-HR | | | 80.81 87 | 79.76 89 | 83.96 85 | 85.60 158 | 68.78 73 | 83.54 199 | 90.50 98 | 70.66 135 | 76.71 126 | 91.66 53 | 60.69 140 | 91.26 173 | 76.94 67 | 81.58 141 | 91.83 81 |
|
ACMM | | 73.20 8 | 80.78 88 | 79.84 87 | 83.58 90 | 89.31 88 | 68.37 84 | 89.99 45 | 91.60 70 | 70.28 139 | 77.25 117 | 89.66 92 | 53.37 188 | 93.53 112 | 74.24 92 | 82.85 128 | 88.85 165 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
114514_t | | | 80.68 89 | 79.51 94 | 84.20 76 | 94.09 18 | 67.27 101 | 89.64 53 | 91.11 84 | 58.75 244 | 74.08 160 | 90.72 75 | 58.10 157 | 95.04 54 | 69.70 130 | 89.42 71 | 90.30 130 |
|
VPA-MVSNet | | | 80.60 90 | 80.55 79 | 80.76 172 | 88.07 119 | 60.80 201 | 86.86 135 | 91.58 71 | 75.67 65 | 80.24 70 | 89.45 101 | 63.34 85 | 90.25 193 | 70.51 124 | 79.22 163 | 91.23 95 |
|
PVSNet_BlendedMVS | | | 80.60 90 | 80.02 85 | 82.36 136 | 88.85 97 | 65.40 126 | 86.16 153 | 92.00 52 | 69.34 153 | 78.11 102 | 86.09 176 | 66.02 67 | 94.27 74 | 71.52 119 | 82.06 136 | 87.39 200 |
|
AdaColmap |  | | 80.58 92 | 79.42 96 | 84.06 80 | 93.09 32 | 68.91 71 | 89.36 56 | 88.97 151 | 69.27 154 | 75.70 138 | 89.69 91 | 57.20 163 | 95.77 28 | 63.06 172 | 88.41 85 | 87.50 199 |
|
EI-MVSNet | | | 80.52 93 | 79.98 86 | 82.12 138 | 84.28 172 | 63.19 181 | 86.41 148 | 88.95 153 | 74.18 81 | 78.69 82 | 87.54 135 | 66.62 60 | 92.43 145 | 72.57 108 | 80.57 151 | 90.74 107 |
|
XVG-OURS | | | 80.41 94 | 79.23 105 | 83.97 84 | 85.64 157 | 69.02 67 | 83.03 202 | 90.39 100 | 71.09 130 | 77.63 111 | 91.49 61 | 54.62 180 | 91.35 171 | 75.71 79 | 83.47 123 | 91.54 87 |
|
v1neww | | | 80.40 95 | 79.54 91 | 82.98 113 | 84.10 182 | 64.51 150 | 87.57 107 | 90.22 110 | 73.25 94 | 78.47 87 | 86.65 160 | 62.83 98 | 93.86 93 | 75.72 77 | 77.02 180 | 90.58 118 |
|
v7new | | | 80.40 95 | 79.54 91 | 82.98 113 | 84.10 182 | 64.51 150 | 87.57 107 | 90.22 110 | 73.25 94 | 78.47 87 | 86.65 160 | 62.83 98 | 93.86 93 | 75.72 77 | 77.02 180 | 90.58 118 |
|
v6 | | | 80.40 95 | 79.54 91 | 82.98 113 | 84.09 184 | 64.50 153 | 87.57 107 | 90.22 110 | 73.25 94 | 78.47 87 | 86.63 162 | 62.84 97 | 93.86 93 | 75.73 76 | 77.02 180 | 90.58 118 |
|
PCF-MVS | | 73.52 7 | 80.38 98 | 78.84 111 | 85.01 56 | 87.71 130 | 68.99 69 | 83.65 196 | 91.46 76 | 63.00 211 | 77.77 109 | 90.28 80 | 66.10 64 | 95.09 53 | 61.40 187 | 88.22 87 | 90.94 101 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
X-MVStestdata | | | 80.37 99 | 77.83 132 | 88.00 8 | 94.42 10 | 73.33 13 | 92.78 8 | 92.99 24 | 79.14 16 | 83.67 44 | 12.47 299 | 67.45 55 | 96.60 14 | 83.06 28 | 94.50 28 | 94.07 18 |
|
test_djsdf | | | 80.30 100 | 79.32 99 | 83.27 99 | 83.98 190 | 65.37 129 | 90.50 36 | 90.38 101 | 68.55 165 | 76.19 132 | 88.70 112 | 56.44 167 | 93.46 114 | 78.98 51 | 80.14 157 | 90.97 100 |
|
v7 | | | 80.24 101 | 79.26 104 | 83.15 103 | 84.07 188 | 64.94 140 | 87.56 110 | 90.67 91 | 72.26 116 | 78.28 94 | 86.51 167 | 61.45 128 | 94.03 84 | 75.14 86 | 77.41 174 | 90.49 123 |
|
v2v482 | | | 80.23 102 | 79.29 103 | 83.05 109 | 83.62 198 | 64.14 160 | 87.04 130 | 89.97 120 | 73.61 88 | 78.18 101 | 87.22 144 | 61.10 135 | 93.82 96 | 76.11 72 | 76.78 191 | 91.18 96 |
|
NR-MVSNet | | | 80.23 102 | 79.38 97 | 82.78 128 | 87.80 127 | 63.34 175 | 86.31 150 | 91.09 85 | 79.01 21 | 72.17 176 | 89.07 106 | 67.20 57 | 92.81 138 | 66.08 154 | 75.65 203 | 92.20 74 |
|
v1141 | | | 80.19 104 | 79.31 100 | 82.85 121 | 83.84 193 | 64.12 162 | 87.14 123 | 90.08 117 | 73.13 97 | 78.27 95 | 86.39 169 | 62.67 107 | 93.75 103 | 75.40 83 | 76.83 188 | 90.68 109 |
|
divwei89l23v2f112 | | | 80.19 104 | 79.31 100 | 82.85 121 | 83.84 193 | 64.11 164 | 87.13 126 | 90.08 117 | 73.13 97 | 78.27 95 | 86.39 169 | 62.69 105 | 93.75 103 | 75.40 83 | 76.82 189 | 90.68 109 |
|
v1 | | | 80.19 104 | 79.31 100 | 82.85 121 | 83.83 195 | 64.12 162 | 87.14 123 | 90.07 119 | 73.13 97 | 78.27 95 | 86.38 171 | 62.72 104 | 93.75 103 | 75.41 82 | 76.82 189 | 90.68 109 |
|
IterMVS-LS | | | 80.06 107 | 79.38 97 | 82.11 139 | 85.89 153 | 63.20 180 | 86.79 138 | 89.34 134 | 74.19 80 | 75.45 141 | 86.72 153 | 66.62 60 | 92.39 147 | 72.58 107 | 76.86 185 | 90.75 106 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
v1144 | | | 80.03 108 | 79.03 108 | 83.01 111 | 83.78 196 | 64.51 150 | 87.11 128 | 90.57 96 | 71.96 120 | 78.08 104 | 86.20 174 | 61.41 129 | 93.94 87 | 74.93 87 | 77.23 176 | 90.60 115 |
|
v8 | | | 79.97 109 | 79.02 109 | 82.80 125 | 84.09 184 | 64.50 153 | 87.96 97 | 90.29 109 | 74.13 83 | 75.24 150 | 86.81 150 | 62.88 95 | 93.89 92 | 74.39 90 | 75.40 208 | 90.00 144 |
|
DI_MVS_test_dynamic | | | 79.89 110 | 78.58 116 | 83.85 87 | 82.89 217 | 65.32 130 | 86.12 154 | 89.55 130 | 69.64 149 | 70.55 190 | 85.82 181 | 57.24 162 | 93.81 97 | 76.85 68 | 88.55 82 | 92.41 69 |
|
DI_MVS_test_normal | | | 79.81 111 | 78.45 118 | 83.89 86 | 82.70 221 | 65.40 126 | 85.82 162 | 89.48 132 | 69.39 150 | 70.12 197 | 85.66 184 | 57.15 164 | 93.71 108 | 77.08 65 | 88.62 80 | 92.56 65 |
|
OpenMVS |  | 72.83 10 | 79.77 112 | 78.33 124 | 84.09 79 | 85.17 161 | 69.91 53 | 90.57 34 | 90.97 86 | 66.70 178 | 72.17 176 | 91.91 50 | 54.70 178 | 93.96 85 | 61.81 184 | 90.95 56 | 88.41 185 |
|
v10 | | | 79.74 113 | 78.67 112 | 82.97 116 | 84.06 189 | 64.95 139 | 87.88 102 | 90.62 94 | 73.11 100 | 75.11 152 | 86.56 165 | 61.46 127 | 94.05 83 | 73.68 95 | 75.55 205 | 89.90 145 |
|
BH-RMVSNet | | | 79.61 114 | 78.44 120 | 83.14 104 | 89.38 82 | 65.93 116 | 84.95 172 | 87.15 177 | 73.56 90 | 78.19 100 | 89.79 90 | 56.67 166 | 93.36 119 | 59.53 200 | 86.74 98 | 90.13 135 |
|
v1192 | | | 79.59 115 | 78.43 121 | 83.07 108 | 83.55 200 | 64.52 148 | 86.93 133 | 90.58 95 | 70.83 132 | 77.78 108 | 85.90 177 | 59.15 151 | 93.94 87 | 73.96 94 | 77.19 178 | 90.76 105 |
|
diffmvs | | | 79.51 116 | 78.59 115 | 82.25 137 | 83.31 205 | 62.66 187 | 84.17 189 | 88.11 165 | 67.64 171 | 76.09 136 | 87.47 137 | 64.01 80 | 91.15 176 | 71.71 118 | 84.82 114 | 92.94 58 |
|
ab-mvs | | | 79.51 116 | 78.97 110 | 81.14 166 | 88.46 111 | 60.91 199 | 83.84 194 | 89.24 140 | 70.36 138 | 79.03 78 | 88.87 110 | 63.23 89 | 90.21 194 | 65.12 160 | 82.57 133 | 92.28 72 |
|
WR-MVS | | | 79.49 118 | 79.22 106 | 80.27 179 | 88.79 102 | 58.35 217 | 85.06 170 | 88.61 161 | 78.56 24 | 77.65 110 | 88.34 123 | 63.81 83 | 90.66 189 | 64.98 163 | 77.22 177 | 91.80 84 |
|
v144192 | | | 79.47 119 | 78.37 122 | 82.78 128 | 83.35 203 | 63.96 166 | 86.96 132 | 90.36 104 | 69.99 142 | 77.50 112 | 85.67 183 | 60.66 141 | 93.77 101 | 74.27 91 | 76.58 192 | 90.62 113 |
|
BH-untuned | | | 79.47 119 | 78.60 114 | 82.05 140 | 89.19 93 | 65.91 117 | 86.07 156 | 88.52 162 | 72.18 117 | 75.42 142 | 87.69 130 | 61.15 134 | 93.54 111 | 60.38 193 | 86.83 97 | 86.70 216 |
|
mvs_anonymous | | | 79.42 121 | 79.11 107 | 80.34 176 | 84.45 171 | 57.97 223 | 82.59 203 | 87.62 173 | 67.40 177 | 76.17 135 | 88.56 119 | 68.47 50 | 89.59 200 | 70.65 123 | 86.05 105 | 93.47 42 |
|
V42 | | | 79.38 122 | 78.24 126 | 82.83 124 | 81.10 238 | 65.50 125 | 85.55 165 | 89.82 124 | 71.57 126 | 78.21 99 | 86.12 175 | 60.66 141 | 93.18 125 | 75.64 80 | 75.46 207 | 89.81 150 |
|
jajsoiax | | | 79.29 123 | 77.96 129 | 83.27 99 | 84.68 168 | 66.57 108 | 89.25 58 | 90.16 114 | 69.20 156 | 75.46 140 | 89.49 96 | 45.75 227 | 93.13 128 | 76.84 69 | 80.80 147 | 90.11 136 |
|
v1921920 | | | 79.22 124 | 78.03 128 | 82.80 125 | 83.30 206 | 63.94 167 | 86.80 137 | 90.33 106 | 69.91 143 | 77.48 113 | 85.53 187 | 58.44 155 | 93.75 103 | 73.60 98 | 76.85 186 | 90.71 108 |
|
TAPA-MVS | | 73.13 9 | 79.15 125 | 77.94 130 | 82.79 127 | 89.59 78 | 62.99 185 | 88.16 94 | 91.51 73 | 65.77 189 | 77.14 122 | 91.09 66 | 60.91 138 | 93.21 121 | 50.26 244 | 87.05 95 | 92.17 76 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
mvs_tets | | | 79.13 126 | 77.77 135 | 83.22 101 | 84.70 167 | 66.37 110 | 89.17 59 | 90.19 113 | 69.38 152 | 75.40 143 | 89.46 99 | 44.17 233 | 93.15 126 | 76.78 70 | 80.70 149 | 90.14 134 |
|
CDS-MVSNet | | | 79.07 127 | 77.70 136 | 83.17 102 | 87.60 132 | 68.23 87 | 84.40 186 | 86.20 188 | 67.49 175 | 76.36 130 | 86.54 166 | 61.54 126 | 90.79 187 | 61.86 183 | 87.33 92 | 90.49 123 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
MVSTER | | | 79.01 128 | 77.88 131 | 82.38 135 | 83.07 211 | 64.80 142 | 84.08 193 | 88.95 153 | 69.01 159 | 78.69 82 | 87.17 146 | 54.70 178 | 92.43 145 | 74.69 88 | 80.57 151 | 89.89 146 |
|
v1240 | | | 78.99 129 | 77.78 134 | 82.64 132 | 83.21 207 | 63.54 170 | 86.62 143 | 90.30 108 | 69.74 148 | 77.33 115 | 85.68 182 | 57.04 165 | 93.76 102 | 73.13 101 | 76.92 183 | 90.62 113 |
|
v7n | | | 78.97 130 | 77.58 138 | 83.14 104 | 83.45 202 | 65.51 124 | 88.32 87 | 91.21 81 | 73.69 87 | 72.41 174 | 86.32 172 | 57.93 158 | 93.81 97 | 69.18 133 | 75.65 203 | 90.11 136 |
|
TAMVS | | | 78.89 131 | 77.51 139 | 83.03 110 | 87.80 127 | 67.79 94 | 84.72 175 | 85.05 199 | 67.63 172 | 76.75 125 | 87.70 129 | 62.25 118 | 90.82 186 | 58.53 208 | 87.13 94 | 90.49 123 |
|
v148 | | | 78.72 132 | 77.80 133 | 81.47 159 | 82.73 220 | 61.96 194 | 86.30 151 | 88.08 167 | 73.26 93 | 76.18 133 | 85.47 189 | 62.46 115 | 92.36 149 | 71.92 117 | 73.82 223 | 90.09 138 |
|
VPNet | | | 78.69 133 | 78.66 113 | 78.76 196 | 88.31 115 | 55.72 247 | 84.45 183 | 86.63 182 | 76.79 45 | 78.26 98 | 90.55 78 | 59.30 150 | 89.70 199 | 66.63 149 | 77.05 179 | 90.88 102 |
|
WR-MVS_H | | | 78.51 134 | 78.49 117 | 78.56 198 | 88.02 121 | 56.38 241 | 88.43 80 | 92.67 34 | 77.14 37 | 73.89 161 | 87.55 134 | 66.25 63 | 89.24 205 | 58.92 203 | 73.55 224 | 90.06 142 |
|
GBi-Net | | | 78.40 135 | 77.40 140 | 81.40 161 | 87.60 132 | 63.01 182 | 88.39 84 | 89.28 136 | 71.63 123 | 75.34 145 | 87.28 140 | 54.80 175 | 91.11 177 | 62.72 173 | 79.57 158 | 90.09 138 |
|
test1 | | | 78.40 135 | 77.40 140 | 81.40 161 | 87.60 132 | 63.01 182 | 88.39 84 | 89.28 136 | 71.63 123 | 75.34 145 | 87.28 140 | 54.80 175 | 91.11 177 | 62.72 173 | 79.57 158 | 90.09 138 |
|
Vis-MVSNet (Re-imp) | | | 78.36 137 | 78.45 118 | 78.07 204 | 88.64 105 | 51.78 262 | 86.70 142 | 79.63 244 | 74.14 82 | 75.11 152 | 90.83 74 | 61.29 132 | 89.75 198 | 58.10 212 | 91.60 49 | 92.69 62 |
|
CP-MVSNet | | | 78.22 138 | 78.34 123 | 77.84 206 | 87.83 126 | 54.54 251 | 87.94 99 | 91.17 83 | 77.65 28 | 73.48 163 | 88.49 120 | 62.24 119 | 88.43 215 | 62.19 179 | 74.07 218 | 90.55 121 |
|
BH-w/o | | | 78.21 139 | 77.33 142 | 80.84 170 | 88.81 100 | 65.13 136 | 84.87 173 | 87.85 170 | 69.75 146 | 74.52 158 | 84.74 199 | 61.34 130 | 93.11 129 | 58.24 211 | 85.84 108 | 84.27 239 |
|
FMVSNet2 | | | 78.20 140 | 77.21 143 | 81.20 164 | 87.60 132 | 62.89 186 | 87.47 114 | 89.02 144 | 71.63 123 | 75.29 149 | 87.28 140 | 54.80 175 | 91.10 180 | 62.38 177 | 79.38 161 | 89.61 154 |
|
HC-MVS | | | 78.19 141 | 76.99 145 | 81.78 145 | 85.66 156 | 66.99 103 | 84.66 176 | 90.47 99 | 55.08 263 | 72.02 180 | 85.27 192 | 63.83 82 | 94.11 82 | 66.10 153 | 89.80 68 | 84.24 240 |
|
Baseline_NR-MVSNet | | | 78.15 142 | 78.33 124 | 77.61 210 | 85.79 154 | 56.21 244 | 86.78 139 | 85.76 193 | 73.60 89 | 77.93 106 | 87.57 133 | 65.02 74 | 88.99 208 | 67.14 147 | 75.33 209 | 87.63 195 |
|
CNLPA | | | 78.08 143 | 76.79 149 | 81.97 142 | 90.40 66 | 71.07 39 | 87.59 106 | 84.55 202 | 66.03 188 | 72.38 175 | 89.64 93 | 57.56 160 | 86.04 230 | 59.61 198 | 83.35 124 | 88.79 167 |
|
PLC |  | 70.83 11 | 78.05 144 | 76.37 153 | 83.08 107 | 91.88 51 | 67.80 93 | 88.19 92 | 89.46 133 | 64.33 201 | 69.87 204 | 88.38 122 | 53.66 187 | 93.58 110 | 58.86 204 | 82.73 130 | 87.86 192 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
PS-CasMVS | | | 78.01 145 | 78.09 127 | 77.77 208 | 87.71 130 | 54.39 253 | 88.02 95 | 91.22 80 | 77.50 34 | 73.26 164 | 88.64 115 | 60.73 139 | 88.41 216 | 61.88 182 | 73.88 222 | 90.53 122 |
|
v748 | | | 77.97 146 | 76.65 150 | 81.92 144 | 82.29 226 | 63.28 177 | 87.53 111 | 90.35 105 | 73.50 92 | 70.76 189 | 85.55 186 | 58.28 156 | 92.81 138 | 68.81 136 | 72.76 228 | 89.67 153 |
|
V4 | | | 77.95 147 | 76.37 153 | 82.67 130 | 79.40 254 | 65.52 122 | 86.43 146 | 89.94 121 | 72.28 114 | 72.14 179 | 84.95 195 | 55.72 170 | 93.44 116 | 73.64 96 | 72.86 226 | 89.05 159 |
|
HY-MVS | | 69.67 12 | 77.95 147 | 77.15 144 | 80.36 175 | 87.57 136 | 60.21 205 | 83.37 201 | 87.78 171 | 66.11 185 | 75.37 144 | 87.06 148 | 63.27 87 | 90.48 191 | 61.38 188 | 82.43 134 | 90.40 128 |
|
v52 | | | 77.94 149 | 76.37 153 | 82.67 130 | 79.39 255 | 65.52 122 | 86.43 146 | 89.94 121 | 72.28 114 | 72.15 178 | 84.94 196 | 55.70 171 | 93.44 116 | 73.64 96 | 72.84 227 | 89.06 158 |
|
FMVSNet3 | | | 77.88 150 | 76.85 147 | 80.97 169 | 86.84 145 | 62.36 189 | 86.52 145 | 88.77 160 | 71.13 128 | 75.34 145 | 86.66 159 | 54.07 184 | 91.10 180 | 62.72 173 | 79.57 158 | 89.45 155 |
|
Test4 | | | 77.83 151 | 75.90 167 | 83.62 89 | 80.24 245 | 65.25 132 | 85.27 168 | 90.67 91 | 69.03 158 | 66.48 237 | 83.75 203 | 43.07 237 | 93.00 134 | 75.93 75 | 88.66 79 | 92.62 64 |
|
PEN-MVS | | | 77.73 152 | 77.69 137 | 77.84 206 | 87.07 142 | 53.91 255 | 87.91 101 | 91.18 82 | 77.56 32 | 73.14 166 | 88.82 111 | 61.23 133 | 89.17 206 | 59.95 195 | 72.37 229 | 90.43 126 |
|
v16 | | | 77.69 153 | 76.36 156 | 81.68 152 | 84.15 179 | 64.63 147 | 87.33 117 | 88.99 148 | 72.69 111 | 69.31 211 | 82.08 220 | 62.80 101 | 91.79 157 | 72.70 105 | 67.23 249 | 88.63 172 |
|
v17 | | | 77.68 154 | 76.35 157 | 81.69 151 | 84.15 179 | 64.65 145 | 87.33 117 | 88.99 148 | 72.70 110 | 69.25 212 | 82.07 221 | 62.82 100 | 91.79 157 | 72.69 106 | 67.15 251 | 88.63 172 |
|
PAPM | | | 77.68 154 | 76.40 152 | 81.51 158 | 87.29 139 | 61.85 195 | 83.78 195 | 89.59 129 | 64.74 196 | 71.23 186 | 88.70 112 | 62.59 110 | 93.66 109 | 52.66 236 | 87.03 96 | 89.01 161 |
|
v18 | | | 77.67 156 | 76.35 157 | 81.64 154 | 84.09 184 | 64.47 155 | 87.27 120 | 89.01 146 | 72.59 112 | 69.39 208 | 82.04 222 | 62.85 96 | 91.80 156 | 72.72 104 | 67.20 250 | 88.63 172 |
|
HyFIR | | | 77.63 157 | 75.69 168 | 83.44 92 | 89.98 72 | 68.58 82 | 78.70 232 | 87.50 175 | 56.38 258 | 75.80 137 | 86.84 149 | 58.67 153 | 91.40 170 | 61.58 186 | 85.75 109 | 90.34 129 |
|
V14 | | | 77.52 158 | 76.12 160 | 81.70 150 | 84.15 179 | 64.77 143 | 87.21 122 | 88.95 153 | 72.80 107 | 68.79 214 | 81.94 228 | 62.69 105 | 91.72 162 | 72.31 111 | 66.27 257 | 88.60 176 |
|
V9 | | | 77.52 158 | 76.11 163 | 81.73 149 | 84.19 178 | 64.89 141 | 87.26 121 | 88.94 156 | 72.87 106 | 68.65 217 | 81.96 227 | 62.65 108 | 91.72 162 | 72.27 112 | 66.24 258 | 88.60 176 |
|
v15 | | | 77.51 160 | 76.12 160 | 81.66 153 | 84.09 184 | 64.65 145 | 87.14 123 | 88.96 152 | 72.76 108 | 68.90 213 | 81.91 229 | 62.74 103 | 91.73 160 | 72.32 110 | 66.29 256 | 88.61 175 |
|
v12 | | | 77.51 160 | 76.09 164 | 81.76 148 | 84.22 175 | 64.99 138 | 87.30 119 | 88.93 157 | 72.92 103 | 68.48 221 | 81.97 225 | 62.54 112 | 91.70 165 | 72.24 113 | 66.21 260 | 88.58 179 |
|
v13 | | | 77.50 162 | 76.07 165 | 81.77 146 | 84.23 174 | 65.07 137 | 87.34 116 | 88.91 158 | 72.92 103 | 68.35 222 | 81.97 225 | 62.53 113 | 91.69 166 | 72.20 114 | 66.22 259 | 88.56 180 |
|
v11 | | | 77.45 163 | 76.06 166 | 81.59 157 | 84.22 175 | 64.52 148 | 87.11 128 | 89.02 144 | 72.76 108 | 68.76 215 | 81.90 230 | 62.09 121 | 91.71 164 | 71.98 115 | 66.73 252 | 88.56 180 |
|
FMVSNet1 | | | 77.44 164 | 76.12 160 | 81.40 161 | 86.81 146 | 63.01 182 | 88.39 84 | 89.28 136 | 70.49 137 | 74.39 159 | 87.28 140 | 49.06 211 | 91.11 177 | 60.91 190 | 78.52 165 | 90.09 138 |
|
TR-MVS | | | 77.44 164 | 76.18 159 | 81.20 164 | 88.24 116 | 63.24 178 | 84.61 179 | 86.40 185 | 67.55 174 | 77.81 107 | 86.48 168 | 54.10 183 | 93.15 126 | 57.75 214 | 82.72 131 | 87.20 205 |
|
1112_ss | | | 77.40 166 | 76.43 151 | 80.32 177 | 89.11 94 | 60.41 204 | 83.65 196 | 87.72 172 | 62.13 222 | 73.05 167 | 86.72 153 | 62.58 111 | 89.97 196 | 62.11 181 | 80.80 147 | 90.59 117 |
|
LCM-MVSNet-Re | | | 77.05 167 | 76.94 146 | 77.36 212 | 87.20 140 | 51.60 263 | 80.06 221 | 80.46 236 | 75.20 73 | 67.69 226 | 86.72 153 | 62.48 114 | 88.98 209 | 63.44 169 | 89.25 72 | 91.51 88 |
|
DTE-MVSNet | | | 76.99 168 | 76.80 148 | 77.54 211 | 86.24 151 | 53.06 259 | 87.52 112 | 90.66 93 | 77.08 40 | 72.50 172 | 88.67 114 | 60.48 144 | 89.52 201 | 57.33 218 | 70.74 239 | 90.05 143 |
|
LS3D | | | 76.95 169 | 74.82 175 | 83.37 96 | 90.45 64 | 67.36 100 | 89.15 63 | 86.94 179 | 61.87 224 | 69.52 206 | 90.61 77 | 51.71 199 | 94.53 69 | 46.38 258 | 86.71 99 | 88.21 187 |
|
GA-MVS | | | 76.87 170 | 75.17 173 | 81.97 142 | 82.75 219 | 62.58 188 | 81.44 213 | 86.35 187 | 72.16 119 | 74.74 156 | 82.89 210 | 46.20 222 | 92.02 155 | 68.85 135 | 81.09 144 | 91.30 94 |
|
DP-MVS | | | 76.78 171 | 74.57 177 | 83.42 93 | 93.29 25 | 69.46 63 | 88.55 79 | 83.70 209 | 63.98 205 | 70.20 194 | 88.89 109 | 54.01 185 | 94.80 64 | 46.66 255 | 81.88 139 | 86.01 226 |
|
cascas | | | 76.72 172 | 74.64 176 | 82.99 112 | 85.78 155 | 65.88 118 | 82.33 205 | 89.21 141 | 60.85 229 | 72.74 169 | 81.02 238 | 47.28 217 | 93.75 103 | 67.48 142 | 85.02 110 | 89.34 156 |
|
liao1 | | | 76.53 173 | 75.30 172 | 80.21 180 | 83.93 191 | 62.32 191 | 84.66 176 | 88.81 159 | 60.23 233 | 70.16 196 | 84.07 200 | 55.30 174 | 90.73 188 | 67.37 143 | 83.21 126 | 87.59 197 |
|
Test_1112_low_res | | | 76.40 174 | 75.44 171 | 79.27 190 | 89.28 89 | 58.09 220 | 81.69 210 | 87.07 178 | 59.53 239 | 72.48 173 | 86.67 158 | 61.30 131 | 89.33 203 | 60.81 192 | 80.15 156 | 90.41 127 |
|
F-COLMAP | | | 76.38 175 | 74.33 181 | 82.50 133 | 89.28 89 | 66.95 106 | 88.41 83 | 89.03 143 | 64.05 203 | 66.83 233 | 88.61 116 | 46.78 220 | 92.89 136 | 57.48 215 | 78.55 164 | 87.67 194 |
|
LTVRE_ROB | | 69.57 13 | 76.25 176 | 74.54 179 | 81.41 160 | 88.60 106 | 64.38 158 | 79.24 227 | 89.12 142 | 70.76 134 | 69.79 205 | 87.86 127 | 49.09 210 | 93.20 123 | 56.21 223 | 80.16 155 | 86.65 217 |
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-PatchMatch | | | 76.12 177 | 74.46 180 | 81.13 167 | 85.37 160 | 69.79 55 | 84.42 185 | 87.95 169 | 65.03 195 | 67.46 228 | 85.33 191 | 53.28 189 | 91.73 160 | 58.01 213 | 83.27 125 | 81.85 257 |
|
XVG-ACMP-BASELINE | | | 76.11 178 | 74.27 182 | 81.62 155 | 83.20 208 | 64.67 144 | 83.60 198 | 89.75 126 | 69.75 146 | 71.85 181 | 87.09 147 | 32.78 269 | 92.11 154 | 69.99 128 | 80.43 154 | 88.09 189 |
|
ACMH+ | | 68.96 14 | 76.01 179 | 74.01 183 | 82.03 141 | 88.60 106 | 65.31 131 | 88.86 67 | 87.55 174 | 70.25 140 | 67.75 225 | 87.47 137 | 41.27 247 | 93.19 124 | 58.37 209 | 75.94 199 | 87.60 196 |
|
ACMH | | 67.68 16 | 75.89 180 | 73.93 184 | 81.77 146 | 88.71 104 | 66.61 107 | 88.62 76 | 89.01 146 | 69.81 144 | 66.78 234 | 86.70 157 | 41.95 246 | 91.51 169 | 55.64 224 | 78.14 170 | 87.17 206 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
IB-MVS | | 68.01 15 | 75.85 181 | 73.36 187 | 83.31 97 | 84.76 166 | 66.03 113 | 83.38 200 | 85.06 198 | 70.21 141 | 69.40 207 | 81.05 237 | 45.76 226 | 94.66 67 | 65.10 161 | 75.49 206 | 89.25 157 |
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021 |
testing_2 | | | 75.73 182 | 73.34 188 | 82.89 120 | 77.37 263 | 65.22 133 | 84.10 192 | 90.54 97 | 69.09 157 | 60.46 259 | 81.15 236 | 40.48 250 | 92.84 137 | 76.36 71 | 80.54 153 | 90.60 115 |
|
WTY-MVS | | | 75.65 183 | 75.68 169 | 75.57 226 | 86.40 150 | 56.82 233 | 77.92 238 | 82.40 220 | 65.10 194 | 76.18 133 | 87.72 128 | 63.13 93 | 80.90 249 | 60.31 194 | 81.96 137 | 89.00 163 |
|
EPNet_dtu | | | 75.46 184 | 74.86 174 | 77.23 215 | 82.57 223 | 54.60 250 | 86.89 134 | 83.09 214 | 71.64 122 | 66.25 239 | 85.86 179 | 55.99 169 | 88.04 218 | 54.92 225 | 86.55 100 | 89.05 159 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
XXY-MVS | | | 75.41 185 | 75.56 170 | 74.96 229 | 83.59 199 | 57.82 226 | 80.59 219 | 83.87 208 | 66.54 183 | 74.93 155 | 88.31 124 | 63.24 88 | 80.09 253 | 62.16 180 | 76.85 186 | 86.97 211 |
|
TransMVSNet (Re) | | | 75.39 186 | 74.56 178 | 77.86 205 | 85.50 159 | 57.10 231 | 86.78 139 | 86.09 191 | 72.17 118 | 71.53 185 | 87.34 139 | 63.01 94 | 89.31 204 | 56.84 220 | 61.83 270 | 87.17 206 |
|
CostFormer | | | 75.24 187 | 73.90 185 | 79.27 190 | 82.65 222 | 58.27 219 | 80.80 214 | 82.73 218 | 61.57 225 | 75.33 148 | 83.13 209 | 55.52 172 | 91.07 183 | 64.98 163 | 78.34 169 | 88.45 183 |
|
PatchFormer-LS_test | | | 74.50 188 | 73.05 189 | 78.86 195 | 82.95 215 | 59.55 210 | 81.65 211 | 82.30 222 | 67.44 176 | 71.62 184 | 78.15 256 | 52.34 192 | 88.92 213 | 65.05 162 | 75.90 200 | 88.12 188 |
|
IterMVS | | | 74.29 189 | 72.94 190 | 78.35 202 | 81.53 232 | 63.49 171 | 81.58 212 | 82.49 219 | 68.06 170 | 69.99 201 | 83.69 205 | 51.66 200 | 85.54 233 | 65.85 156 | 71.64 234 | 86.01 226 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
OurMVSNet-221017-0 | | | 74.26 190 | 72.42 194 | 79.80 184 | 83.76 197 | 59.59 207 | 85.92 160 | 86.64 181 | 66.39 184 | 66.96 232 | 87.58 132 | 39.46 253 | 91.60 168 | 65.76 157 | 69.27 242 | 88.22 186 |
|
EG-PatchMatch MVS | | | 74.04 191 | 71.82 197 | 80.71 173 | 84.92 165 | 67.42 97 | 85.86 161 | 88.08 167 | 66.04 187 | 64.22 249 | 83.85 201 | 35.10 267 | 92.56 143 | 57.44 216 | 80.83 146 | 82.16 256 |
|
MS-PatchMatch | | | 73.83 192 | 72.67 191 | 77.30 214 | 83.87 192 | 66.02 114 | 81.82 208 | 84.66 201 | 61.37 227 | 68.61 219 | 82.82 212 | 47.29 216 | 88.21 217 | 59.27 201 | 84.32 118 | 77.68 270 |
|
DWT-MVSNet_test | | | 73.70 193 | 71.86 196 | 79.21 192 | 82.91 216 | 58.94 212 | 82.34 204 | 82.17 223 | 65.21 192 | 71.05 188 | 78.31 254 | 44.21 232 | 90.17 195 | 63.29 171 | 77.28 175 | 88.53 182 |
|
sss | | | 73.60 194 | 73.64 186 | 73.51 239 | 82.80 218 | 55.01 249 | 76.12 244 | 81.69 227 | 62.47 219 | 74.68 157 | 85.85 180 | 57.32 161 | 78.11 261 | 60.86 191 | 80.93 145 | 87.39 200 |
|
tpmp4_e23 | | | 73.45 195 | 71.17 204 | 80.31 178 | 83.55 200 | 59.56 209 | 81.88 207 | 82.33 221 | 57.94 249 | 70.51 192 | 81.62 232 | 51.19 203 | 91.63 167 | 53.96 229 | 77.51 173 | 89.75 152 |
|
SixPastTwentyTwo | | | 73.37 196 | 71.26 203 | 79.70 185 | 85.08 164 | 57.89 225 | 85.57 164 | 83.56 210 | 71.03 131 | 65.66 241 | 85.88 178 | 42.10 244 | 92.57 142 | 59.11 202 | 63.34 267 | 88.65 171 |
|
CR-MVSNet | | | 73.37 196 | 71.27 202 | 79.67 186 | 81.32 236 | 65.19 134 | 75.92 246 | 80.30 238 | 59.92 236 | 72.73 170 | 81.19 234 | 52.50 190 | 86.69 224 | 59.84 196 | 77.71 171 | 87.11 209 |
|
MSDG | | | 73.36 198 | 70.99 205 | 80.49 174 | 84.51 170 | 65.80 119 | 80.71 216 | 86.13 190 | 65.70 190 | 65.46 242 | 83.74 204 | 44.60 230 | 90.91 185 | 51.13 240 | 76.89 184 | 84.74 237 |
|
tpm2 | | | 73.26 199 | 71.46 199 | 78.63 197 | 83.34 204 | 56.71 236 | 80.65 217 | 80.40 237 | 56.63 257 | 73.55 162 | 82.02 223 | 51.80 198 | 91.24 174 | 56.35 222 | 78.42 168 | 87.95 190 |
|
RPSCF | | | 73.23 200 | 71.46 199 | 78.54 199 | 82.50 224 | 59.85 206 | 82.18 206 | 82.84 217 | 58.96 241 | 71.15 187 | 89.41 103 | 45.48 229 | 84.77 237 | 58.82 205 | 71.83 233 | 91.02 99 |
|
PatchmatchNet |  | | 73.12 201 | 71.33 201 | 78.49 201 | 83.18 209 | 60.85 200 | 79.63 224 | 78.57 248 | 64.13 202 | 71.73 182 | 79.81 249 | 51.20 202 | 85.97 231 | 57.40 217 | 76.36 196 | 88.66 170 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
COLMAP_ROB |  | 66.92 17 | 73.01 202 | 70.41 209 | 80.81 171 | 87.13 141 | 65.63 121 | 88.30 88 | 84.19 206 | 62.96 212 | 63.80 252 | 87.69 130 | 38.04 258 | 92.56 143 | 46.66 255 | 74.91 212 | 84.24 240 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
CVMVSNet | | | 72.99 203 | 72.58 192 | 74.25 236 | 84.28 172 | 50.85 268 | 86.41 148 | 83.45 211 | 44.56 281 | 73.23 165 | 87.54 135 | 49.38 207 | 85.70 232 | 65.90 155 | 78.44 167 | 86.19 221 |
|
test-LLR | | | 72.94 204 | 72.43 193 | 74.48 233 | 81.35 234 | 58.04 221 | 78.38 233 | 77.46 252 | 66.66 179 | 69.95 202 | 79.00 252 | 48.06 214 | 79.24 255 | 66.13 151 | 84.83 112 | 86.15 222 |
|
test_0402 | | | 72.79 205 | 70.44 208 | 79.84 183 | 88.13 118 | 65.99 115 | 85.93 159 | 84.29 204 | 65.57 191 | 67.40 229 | 85.49 188 | 46.92 219 | 92.61 141 | 35.88 275 | 74.38 217 | 80.94 260 |
|
tpmrst | | | 72.39 206 | 72.13 195 | 73.18 241 | 80.54 243 | 49.91 271 | 79.91 223 | 79.08 246 | 63.11 209 | 71.69 183 | 79.95 246 | 55.32 173 | 82.77 244 | 65.66 158 | 73.89 221 | 86.87 212 |
|
PatchMatch-RL | | | 72.38 207 | 70.90 206 | 76.80 218 | 88.60 106 | 67.38 99 | 79.53 225 | 76.17 258 | 62.75 216 | 69.36 209 | 82.00 224 | 45.51 228 | 84.89 236 | 53.62 231 | 80.58 150 | 78.12 268 |
|
tpm | | | 72.37 208 | 71.71 198 | 74.35 235 | 82.19 227 | 52.00 260 | 79.22 228 | 77.29 254 | 64.56 198 | 72.95 168 | 83.68 206 | 51.35 201 | 83.26 243 | 58.33 210 | 75.80 201 | 87.81 193 |
|
PVSNet | | 64.34 18 | 72.08 209 | 70.87 207 | 75.69 225 | 86.21 152 | 56.44 240 | 74.37 256 | 80.73 233 | 62.06 223 | 70.17 195 | 82.23 218 | 42.86 239 | 83.31 242 | 54.77 226 | 84.45 117 | 87.32 202 |
|
RPMNet | | | 71.62 210 | 68.94 217 | 79.67 186 | 81.32 236 | 65.19 134 | 75.92 246 | 78.30 250 | 57.60 251 | 72.73 170 | 76.45 263 | 52.30 193 | 86.69 224 | 48.14 252 | 77.71 171 | 87.11 209 |
|
test-mter | | | 71.41 211 | 70.39 210 | 74.48 233 | 81.35 234 | 58.04 221 | 78.38 233 | 77.46 252 | 60.32 232 | 69.95 202 | 79.00 252 | 36.08 265 | 79.24 255 | 66.13 151 | 84.83 112 | 86.15 222 |
|
K. test v3 | | | 71.19 212 | 68.51 219 | 79.21 192 | 83.04 213 | 57.78 227 | 84.35 187 | 76.91 256 | 72.90 105 | 62.99 255 | 82.86 211 | 39.27 254 | 91.09 182 | 61.65 185 | 52.66 282 | 88.75 168 |
|
tpmvs | | | 71.09 213 | 69.29 213 | 76.49 219 | 82.04 228 | 56.04 245 | 78.92 231 | 81.37 230 | 64.05 203 | 67.18 230 | 78.28 255 | 49.74 206 | 89.77 197 | 49.67 247 | 72.37 229 | 83.67 243 |
|
AllTest | | | 70.96 214 | 68.09 225 | 79.58 188 | 85.15 162 | 63.62 168 | 84.58 180 | 79.83 242 | 62.31 220 | 60.32 260 | 86.73 151 | 32.02 270 | 88.96 211 | 50.28 242 | 71.57 235 | 86.15 222 |
|
pm-mvs1 | | | 70.87 215 | 69.03 215 | 76.39 220 | 79.41 253 | 58.92 213 | 80.64 218 | 78.89 247 | 55.71 260 | 67.14 231 | 83.58 207 | 48.48 213 | 85.25 235 | 52.94 235 | 74.48 216 | 84.99 234 |
|
Patchmtry | | | 70.74 216 | 69.16 214 | 75.49 227 | 80.72 240 | 54.07 254 | 74.94 255 | 80.30 238 | 58.34 245 | 70.01 198 | 81.19 234 | 52.50 190 | 86.54 226 | 53.37 232 | 71.09 237 | 85.87 228 |
|
MIMVSNet | | | 70.69 217 | 69.30 212 | 74.88 230 | 84.52 169 | 56.35 242 | 75.87 248 | 79.42 245 | 64.59 197 | 67.76 224 | 82.41 215 | 41.10 248 | 81.54 248 | 46.64 257 | 81.34 142 | 86.75 215 |
|
tpm cat1 | | | 70.57 218 | 68.31 221 | 77.35 213 | 82.41 225 | 57.95 224 | 78.08 237 | 80.22 240 | 52.04 273 | 68.54 220 | 77.66 259 | 52.00 197 | 87.84 220 | 51.77 237 | 72.07 232 | 86.25 220 |
|
OpenMVS_ROB |  | 64.09 19 | 70.56 219 | 68.19 222 | 77.65 209 | 80.26 244 | 59.41 211 | 85.01 171 | 82.96 216 | 58.76 243 | 65.43 243 | 82.33 216 | 37.63 261 | 91.23 175 | 45.34 262 | 76.03 198 | 82.32 254 |
|
pmmvs-eth3d | | | 70.50 220 | 67.83 229 | 78.52 200 | 77.37 263 | 66.18 112 | 81.82 208 | 81.51 228 | 58.90 242 | 63.90 251 | 80.42 243 | 42.69 240 | 86.28 229 | 58.56 207 | 65.30 263 | 83.11 249 |
|
USDC | | | 70.33 221 | 68.37 220 | 76.21 222 | 80.60 242 | 56.23 243 | 79.19 229 | 86.49 183 | 60.89 228 | 61.29 256 | 85.47 189 | 31.78 272 | 89.47 202 | 53.37 232 | 76.21 197 | 82.94 253 |
|
CMPMVS |  | 51.72 21 | 70.19 222 | 68.16 223 | 76.28 221 | 73.15 278 | 57.55 228 | 79.47 226 | 83.92 207 | 48.02 279 | 56.48 271 | 84.81 197 | 43.13 236 | 86.42 228 | 62.67 176 | 81.81 140 | 84.89 235 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
gg-mvs-nofinetune | | | 69.95 223 | 67.96 226 | 75.94 223 | 83.07 211 | 54.51 252 | 77.23 241 | 70.29 281 | 63.11 209 | 70.32 193 | 62.33 283 | 43.62 235 | 88.69 214 | 53.88 230 | 87.76 88 | 84.62 238 |
|
TESTMET0.1,1 | | | 69.89 224 | 69.00 216 | 72.55 242 | 79.27 257 | 56.85 232 | 78.38 233 | 74.71 268 | 57.64 250 | 68.09 223 | 77.19 261 | 37.75 259 | 76.70 266 | 63.92 167 | 84.09 119 | 84.10 242 |
|
FMVSNet5 | | | 69.50 225 | 67.96 226 | 74.15 237 | 82.97 214 | 55.35 248 | 80.01 222 | 82.12 224 | 62.56 218 | 63.02 253 | 81.53 233 | 36.92 262 | 81.92 246 | 48.42 250 | 74.06 219 | 85.17 233 |
|
PMMVS | | | 69.34 226 | 68.67 218 | 71.35 248 | 75.67 270 | 62.03 193 | 75.17 250 | 73.46 274 | 50.00 277 | 68.68 216 | 79.05 250 | 52.07 196 | 78.13 260 | 61.16 189 | 82.77 129 | 73.90 277 |
|
EPMVS | | | 69.02 227 | 68.16 223 | 71.59 244 | 79.61 251 | 49.80 272 | 77.40 240 | 66.93 287 | 62.82 215 | 70.01 198 | 79.05 250 | 45.79 225 | 77.86 263 | 56.58 221 | 75.26 210 | 87.13 208 |
|
Patchmatch-RL test | | | 68.82 228 | 66.60 235 | 75.47 228 | 77.43 262 | 59.57 208 | 71.16 261 | 70.33 280 | 62.94 213 | 68.65 217 | 81.66 231 | 31.06 273 | 85.49 234 | 69.58 131 | 66.58 254 | 81.34 259 |
|
Anonymous20231206 | | | 68.60 229 | 67.80 230 | 71.02 250 | 80.23 246 | 50.75 269 | 78.30 236 | 80.47 235 | 56.79 256 | 66.11 240 | 82.63 214 | 46.35 221 | 78.95 257 | 43.62 265 | 75.70 202 | 83.36 246 |
|
MIMVSNet1 | | | 68.58 230 | 66.78 234 | 73.98 238 | 80.07 247 | 51.82 261 | 80.77 215 | 84.37 203 | 64.40 200 | 59.75 262 | 82.16 219 | 36.47 263 | 83.63 240 | 42.73 266 | 70.33 240 | 86.48 219 |
|
EU-MVSNet | | | 68.53 231 | 67.61 232 | 71.31 249 | 78.51 260 | 47.01 277 | 84.47 181 | 84.27 205 | 42.27 282 | 66.44 238 | 84.79 198 | 40.44 251 | 83.76 238 | 58.76 206 | 68.54 248 | 83.17 247 |
|
PatchT | | | 68.46 232 | 67.85 228 | 70.29 252 | 80.70 241 | 43.93 281 | 72.47 259 | 74.88 264 | 60.15 234 | 70.55 190 | 76.57 262 | 49.94 205 | 81.59 247 | 50.58 241 | 74.83 213 | 85.34 230 |
|
test0.0.03 1 | | | 68.00 233 | 67.69 231 | 68.90 256 | 77.55 261 | 47.43 275 | 75.70 249 | 72.95 276 | 66.66 179 | 66.56 235 | 82.29 217 | 48.06 214 | 75.87 269 | 44.97 263 | 74.51 215 | 83.41 245 |
|
TDRefinement | | | 67.49 234 | 64.34 240 | 76.92 216 | 73.47 277 | 61.07 197 | 84.86 174 | 82.98 215 | 59.77 237 | 58.30 265 | 85.13 193 | 26.06 277 | 87.89 219 | 47.92 253 | 60.59 274 | 81.81 258 |
|
test20.03 | | | 67.45 235 | 66.95 233 | 68.94 255 | 75.48 273 | 44.84 279 | 77.50 239 | 77.67 251 | 66.66 179 | 63.01 254 | 83.80 202 | 47.02 218 | 78.40 259 | 42.53 267 | 68.86 246 | 83.58 244 |
|
UnsupCasMVSNet_eth | | | 67.33 236 | 65.99 237 | 71.37 246 | 73.48 276 | 51.47 265 | 75.16 251 | 85.19 197 | 65.20 193 | 60.78 258 | 80.93 241 | 42.35 241 | 77.20 265 | 57.12 219 | 53.69 281 | 85.44 229 |
|
TinyColmap | | | 67.30 237 | 64.81 239 | 74.76 232 | 81.92 229 | 56.68 237 | 80.29 220 | 81.49 229 | 60.33 231 | 56.27 272 | 83.22 208 | 24.77 279 | 87.66 221 | 45.52 260 | 69.47 241 | 79.95 264 |
|
dp | | | 66.80 238 | 65.43 238 | 70.90 251 | 79.74 250 | 48.82 274 | 75.12 253 | 74.77 266 | 59.61 238 | 64.08 250 | 77.23 260 | 42.89 238 | 80.72 250 | 48.86 249 | 66.58 254 | 83.16 248 |
|
MDA-MVSNet-bldmvs | | | 66.68 239 | 63.66 242 | 75.75 224 | 79.28 256 | 60.56 203 | 73.92 257 | 78.35 249 | 64.43 199 | 50.13 282 | 79.87 248 | 44.02 234 | 83.67 239 | 46.10 259 | 56.86 276 | 83.03 251 |
|
testgi | | | 66.67 240 | 66.53 236 | 67.08 261 | 75.62 271 | 41.69 286 | 75.93 245 | 76.50 257 | 66.11 185 | 65.20 246 | 86.59 163 | 35.72 266 | 74.71 272 | 43.71 264 | 73.38 225 | 84.84 236 |
|
PM-MVS | | | 66.41 241 | 64.14 241 | 73.20 240 | 73.92 274 | 56.45 239 | 78.97 230 | 64.96 291 | 63.88 207 | 64.72 247 | 80.24 244 | 19.84 286 | 83.44 241 | 66.24 150 | 64.52 265 | 79.71 265 |
|
JIA-IIPM | | | 66.32 242 | 62.82 247 | 76.82 217 | 77.09 265 | 61.72 196 | 65.34 281 | 75.38 260 | 58.04 248 | 64.51 248 | 62.32 284 | 42.05 245 | 86.51 227 | 51.45 239 | 69.22 243 | 82.21 255 |
|
ADS-MVSNet2 | | | 66.20 243 | 63.33 243 | 74.82 231 | 79.92 248 | 58.75 214 | 67.55 277 | 75.19 262 | 53.37 269 | 65.25 244 | 75.86 264 | 42.32 242 | 80.53 251 | 41.57 268 | 68.91 244 | 85.18 231 |
|
YYNet1 | | | 65.03 244 | 62.91 245 | 71.38 245 | 75.85 268 | 56.60 238 | 69.12 271 | 74.66 270 | 57.28 254 | 54.12 274 | 77.87 258 | 45.85 224 | 74.48 273 | 49.95 245 | 61.52 272 | 83.05 250 |
|
MDA-MVSNet_test_wron | | | 65.03 244 | 62.92 244 | 71.37 246 | 75.93 267 | 56.73 234 | 69.09 272 | 74.73 267 | 57.28 254 | 54.03 275 | 77.89 257 | 45.88 223 | 74.39 274 | 49.89 246 | 61.55 271 | 82.99 252 |
|
ADS-MVSNet | | | 64.36 246 | 62.88 246 | 68.78 258 | 79.92 248 | 47.17 276 | 67.55 277 | 71.18 279 | 53.37 269 | 65.25 244 | 75.86 264 | 42.32 242 | 73.99 276 | 41.57 268 | 68.91 244 | 85.18 231 |
|
LF4IMVS | | | 64.02 247 | 62.19 248 | 69.50 254 | 70.90 282 | 53.29 258 | 76.13 243 | 77.18 255 | 52.65 272 | 58.59 263 | 80.98 239 | 23.55 280 | 76.52 267 | 53.06 234 | 66.66 253 | 78.68 267 |
|
UnsupCasMVSNet_bld | | | 63.70 248 | 61.53 249 | 70.21 253 | 73.69 275 | 51.39 266 | 72.82 258 | 81.89 225 | 55.63 261 | 57.81 266 | 71.80 272 | 38.67 256 | 78.61 258 | 49.26 248 | 52.21 283 | 80.63 261 |
|
PVSNet_0 | | 57.27 20 | 61.67 249 | 59.27 250 | 68.85 257 | 79.61 251 | 57.44 229 | 68.01 275 | 73.44 275 | 55.93 259 | 58.54 264 | 70.41 275 | 44.58 231 | 77.55 264 | 47.01 254 | 35.91 288 | 71.55 279 |
|
LP | | | 61.36 250 | 57.78 253 | 72.09 243 | 75.54 272 | 58.53 216 | 67.16 279 | 75.22 261 | 51.90 274 | 54.13 273 | 69.97 276 | 37.73 260 | 80.45 252 | 32.74 279 | 55.63 278 | 77.29 272 |
|
test2356 | | | 59.50 251 | 58.08 251 | 63.74 265 | 71.23 281 | 41.88 284 | 67.59 276 | 72.42 278 | 53.72 268 | 57.65 267 | 70.74 274 | 26.31 276 | 72.40 279 | 32.03 282 | 71.06 238 | 76.93 274 |
|
MVS-HIRNet | | | 59.14 252 | 57.67 254 | 63.57 266 | 81.65 231 | 43.50 282 | 71.73 260 | 65.06 290 | 39.59 286 | 51.43 280 | 57.73 287 | 38.34 257 | 82.58 245 | 39.53 271 | 73.95 220 | 64.62 284 |
|
testus | | | 59.00 253 | 57.91 252 | 62.25 268 | 72.25 279 | 39.09 289 | 69.74 266 | 75.02 263 | 53.04 271 | 57.21 269 | 73.72 269 | 18.76 288 | 70.33 283 | 32.86 278 | 68.57 247 | 77.35 271 |
|
test1235678 | | | 58.74 254 | 56.89 257 | 64.30 263 | 69.70 283 | 41.87 285 | 71.05 262 | 74.87 265 | 54.06 265 | 50.63 281 | 71.53 273 | 25.30 278 | 74.10 275 | 31.80 283 | 63.10 268 | 76.93 274 |
|
pmmvs3 | | | 57.79 255 | 54.26 259 | 68.37 259 | 64.02 290 | 56.72 235 | 75.12 253 | 65.17 289 | 40.20 284 | 52.93 278 | 69.86 277 | 20.36 284 | 75.48 271 | 45.45 261 | 55.25 280 | 72.90 278 |
|
DSMNet-mixed | | | 57.77 256 | 56.90 256 | 60.38 269 | 67.70 288 | 35.61 293 | 69.18 270 | 53.97 294 | 32.30 293 | 57.49 268 | 79.88 247 | 40.39 252 | 68.57 286 | 38.78 272 | 72.37 229 | 76.97 273 |
|
1111 | | | 57.11 257 | 56.82 258 | 57.97 272 | 69.10 284 | 28.28 298 | 68.90 273 | 74.54 271 | 54.01 266 | 53.71 276 | 74.51 267 | 23.09 281 | 67.90 287 | 32.28 280 | 61.26 273 | 77.73 269 |
|
testpf | | | 56.51 258 | 57.58 255 | 53.30 276 | 71.99 280 | 41.19 287 | 46.89 293 | 69.32 285 | 58.06 247 | 52.87 279 | 69.45 278 | 27.99 275 | 72.73 278 | 59.59 199 | 62.07 269 | 45.98 290 |
|
LCM-MVSNet | | | 54.25 259 | 49.68 266 | 67.97 260 | 53.73 297 | 45.28 278 | 66.85 280 | 80.78 232 | 35.96 288 | 39.45 288 | 62.23 285 | 8.70 297 | 78.06 262 | 48.24 251 | 51.20 284 | 80.57 262 |
|
testmv | | | 53.85 260 | 51.03 262 | 62.31 267 | 61.46 292 | 38.88 290 | 70.95 265 | 74.69 269 | 51.11 276 | 41.26 285 | 66.85 279 | 14.28 291 | 72.13 280 | 29.19 285 | 49.51 285 | 75.93 276 |
|
FPMVS | | | 53.68 261 | 51.64 261 | 59.81 270 | 65.08 289 | 51.03 267 | 69.48 269 | 69.58 283 | 41.46 283 | 40.67 286 | 72.32 271 | 16.46 290 | 70.00 284 | 24.24 290 | 65.42 262 | 58.40 286 |
|
N_pmnet | | | 52.79 262 | 53.26 260 | 51.40 279 | 78.99 258 | 7.68 306 | 69.52 268 | 3.89 303 | 51.63 275 | 57.01 270 | 74.98 266 | 40.83 249 | 65.96 289 | 37.78 273 | 64.67 264 | 80.56 263 |
|
HyFIR lowres test | | | 51.79 263 | 50.01 265 | 57.11 273 | 68.82 286 | 49.21 273 | 60.50 285 | 53.26 295 | 34.52 289 | 43.77 284 | 64.94 282 | 20.34 285 | 71.75 281 | 39.87 270 | 64.06 266 | 50.39 287 |
|
no-one | | | 51.08 264 | 45.79 269 | 66.95 262 | 57.92 295 | 50.49 270 | 59.63 288 | 76.04 259 | 48.04 278 | 31.85 289 | 56.10 290 | 19.12 287 | 80.08 254 | 36.89 274 | 26.52 290 | 70.29 280 |
|
new_pmnet | | | 50.91 265 | 50.29 263 | 52.78 277 | 68.58 287 | 34.94 296 | 63.71 284 | 56.63 293 | 39.73 285 | 44.95 283 | 65.47 281 | 21.93 283 | 58.48 291 | 34.98 276 | 56.62 277 | 64.92 283 |
|
ANet_high | | | 50.57 266 | 46.10 268 | 63.99 264 | 48.67 301 | 39.13 288 | 70.99 264 | 80.85 231 | 61.39 226 | 31.18 291 | 57.70 288 | 17.02 289 | 73.65 277 | 31.22 284 | 15.89 297 | 79.18 266 |
|
test12356 | | | 49.28 267 | 48.51 267 | 51.59 278 | 62.06 291 | 19.11 303 | 60.40 286 | 72.45 277 | 47.60 280 | 40.64 287 | 65.68 280 | 13.84 292 | 68.72 285 | 27.29 287 | 46.67 287 | 66.94 282 |
|
.test1245 | | | 45.55 268 | 50.02 264 | 32.14 285 | 69.10 284 | 28.28 298 | 68.90 273 | 74.54 271 | 54.01 266 | 53.71 276 | 74.51 267 | 23.09 281 | 67.90 287 | 32.28 280 | 0.02 300 | 0.25 299 |
|
Gipuma |  | | 45.18 269 | 41.86 270 | 55.16 275 | 77.03 266 | 51.52 264 | 32.50 296 | 80.52 234 | 32.46 291 | 27.12 292 | 35.02 294 | 9.52 296 | 75.50 270 | 22.31 291 | 60.21 275 | 38.45 292 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMVS |  | 37.38 22 | 44.16 270 | 40.28 271 | 55.82 274 | 40.82 304 | 42.54 283 | 65.12 282 | 63.99 292 | 34.43 290 | 24.48 293 | 57.12 289 | 3.92 299 | 76.17 268 | 17.10 293 | 55.52 279 | 48.75 288 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
PMMVS2 | | | 40.82 271 | 38.86 272 | 46.69 281 | 53.84 296 | 16.45 304 | 48.61 292 | 49.92 297 | 37.49 287 | 31.67 290 | 60.97 286 | 8.14 298 | 56.42 292 | 28.42 286 | 30.72 289 | 67.19 281 |
|
wuykxyi23d | | | 39.76 272 | 33.18 275 | 59.51 271 | 46.98 302 | 44.01 280 | 57.70 289 | 67.74 286 | 24.13 295 | 13.98 300 | 34.33 295 | 1.27 302 | 71.33 282 | 34.23 277 | 18.23 293 | 63.18 285 |
|
PNet_i23d | | | 38.26 273 | 35.42 273 | 46.79 280 | 58.74 293 | 35.48 294 | 59.65 287 | 51.25 296 | 32.45 292 | 23.44 296 | 47.53 292 | 2.04 301 | 58.96 290 | 25.60 289 | 18.09 295 | 45.92 291 |
|
pcd1.5k->3k | | | 34.07 274 | 35.26 274 | 30.50 286 | 86.92 143 | 0.00 309 | 0.00 298 | 91.58 71 | 0.00 303 | 0.00 304 | 0.00 303 | 56.23 168 | 0.00 301 | 0.00 300 | 82.60 132 | 91.49 90 |
|
E-PMN | | | 31.77 275 | 30.64 276 | 35.15 283 | 52.87 298 | 27.67 300 | 57.09 290 | 47.86 298 | 24.64 294 | 16.40 298 | 33.05 296 | 11.23 294 | 54.90 293 | 14.46 295 | 18.15 294 | 22.87 294 |
|
EMVS | | | 30.81 276 | 29.65 277 | 34.27 284 | 50.96 300 | 25.95 302 | 56.58 291 | 46.80 299 | 24.01 296 | 15.53 299 | 30.68 297 | 12.47 293 | 54.43 294 | 12.81 296 | 17.05 296 | 22.43 295 |
|
MVE |  | 26.22 23 | 30.37 277 | 25.89 279 | 43.81 282 | 44.55 303 | 35.46 295 | 28.87 297 | 39.07 300 | 18.20 297 | 18.58 297 | 40.18 293 | 2.68 300 | 47.37 295 | 17.07 294 | 23.78 292 | 48.60 289 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
cdsmvs_eth3d_5k | | | 19.96 278 | 26.61 278 | 0.00 292 | 0.00 309 | 0.00 309 | 0.00 298 | 89.26 139 | 0.00 303 | 0.00 304 | 88.61 116 | 61.62 125 | 0.00 301 | 0.00 300 | 0.00 303 | 0.00 301 |
|
DUST3R | | | 18.61 279 | 21.40 280 | 10.23 289 | 4.82 306 | 10.11 305 | 34.70 295 | 30.74 301 | 1.48 300 | 23.91 295 | 26.07 298 | 28.42 274 | 13.41 298 | 27.12 288 | 15.35 298 | 7.17 296 |
|
wuyk23d | | | 16.82 280 | 15.94 281 | 19.46 288 | 58.74 293 | 31.45 297 | 39.22 294 | 3.74 304 | 6.84 299 | 6.04 301 | 2.70 300 | 1.27 302 | 24.29 297 | 10.54 297 | 14.40 299 | 2.63 297 |
|
ab-mvs-re | | | 7.23 281 | 9.64 282 | 0.00 292 | 0.00 309 | 0.00 309 | 0.00 298 | 0.00 307 | 0.00 303 | 0.00 304 | 86.72 153 | 0.00 306 | 0.00 301 | 0.00 300 | 0.00 303 | 0.00 301 |
|
test123 | | | 6.12 282 | 8.11 283 | 0.14 290 | 0.06 308 | 0.09 307 | 71.05 262 | 0.03 306 | 0.04 302 | 0.25 303 | 1.30 302 | 0.05 304 | 0.03 300 | 0.21 299 | 0.01 302 | 0.29 298 |
|
testmvs | | | 6.04 283 | 8.02 284 | 0.10 291 | 0.08 307 | 0.03 308 | 69.74 266 | 0.04 305 | 0.05 301 | 0.31 302 | 1.68 301 | 0.02 305 | 0.04 299 | 0.24 298 | 0.02 300 | 0.25 299 |
|
pcd_1.5k_mvsjas | | | 5.26 284 | 7.02 285 | 0.00 292 | 0.00 309 | 0.00 309 | 0.00 298 | 0.00 307 | 0.00 303 | 0.00 304 | 0.00 303 | 63.15 90 | 0.00 301 | 0.00 300 | 0.00 303 | 0.00 301 |
|
sosnet-low-res | | | 0.00 285 | 0.00 286 | 0.00 292 | 0.00 309 | 0.00 309 | 0.00 298 | 0.00 307 | 0.00 303 | 0.00 304 | 0.00 303 | 0.00 306 | 0.00 301 | 0.00 300 | 0.00 303 | 0.00 301 |
|
sosnet | | | 0.00 285 | 0.00 286 | 0.00 292 | 0.00 309 | 0.00 309 | 0.00 298 | 0.00 307 | 0.00 303 | 0.00 304 | 0.00 303 | 0.00 306 | 0.00 301 | 0.00 300 | 0.00 303 | 0.00 301 |
|
uncertanet | | | 0.00 285 | 0.00 286 | 0.00 292 | 0.00 309 | 0.00 309 | 0.00 298 | 0.00 307 | 0.00 303 | 0.00 304 | 0.00 303 | 0.00 306 | 0.00 301 | 0.00 300 | 0.00 303 | 0.00 301 |
|
Regformer | | | 0.00 285 | 0.00 286 | 0.00 292 | 0.00 309 | 0.00 309 | 0.00 298 | 0.00 307 | 0.00 303 | 0.00 304 | 0.00 303 | 0.00 306 | 0.00 301 | 0.00 300 | 0.00 303 | 0.00 301 |
|
uanet | | | 0.00 285 | 0.00 286 | 0.00 292 | 0.00 309 | 0.00 309 | 0.00 298 | 0.00 307 | 0.00 303 | 0.00 304 | 0.00 303 | 0.00 306 | 0.00 301 | 0.00 300 | 0.00 303 | 0.00 301 |
|
MTAPA | | | | | | 52.35 299 | | | | | | | | | | | |
|
gm-plane-assit | | | | | | 81.40 233 | 53.83 256 | | | 62.72 217 | | 80.94 240 | | 92.39 147 | 63.40 170 | | |
|
test9_res | | | | | | | | | | | | | | | 84.90 11 | 95.70 10 | 92.87 59 |
|
TEST9 | | | | | | 93.26 27 | 72.96 15 | 88.75 72 | 91.89 58 | 68.44 167 | 85.00 21 | 93.10 33 | 74.36 14 | 95.41 39 | | | |
|
Patchmatch-test1 | | | | | | 78.56 259 | 58.71 215 | 64.97 283 | 73.71 273 | | 70.00 200 | 80.13 245 | 33.36 268 | | | 65.60 261 | |
|
Patchmatch-test | | | | | | 75.77 269 | 36.09 292 | | | | | 72.41 270 | | | | | |
|
test_8 | | | | | | 93.13 29 | 72.57 24 | 88.68 75 | 91.84 61 | 68.69 163 | 84.87 27 | 93.10 33 | 74.43 11 | 95.16 47 | | | |
|
agg_prior2 | | | | | | | | | | | | | | | 82.91 31 | 95.45 12 | 92.70 60 |
|
agg_prior | | | | | | 92.85 35 | 71.94 32 | | 91.78 64 | | 84.41 33 | | | 94.93 56 | | | |
|
TestCases | | | | | 79.58 188 | 85.15 162 | 63.62 168 | | 79.83 242 | 62.31 220 | 60.32 260 | 86.73 151 | 32.02 270 | 88.96 211 | 50.28 242 | 71.57 235 | 86.15 222 |
|
test_prior4 | | | | | | | 72.60 23 | 89.01 65 | | | | | | | | | |
|
test_prior2 | | | | | | | | 88.85 68 | | 75.41 67 | 84.91 23 | 93.54 23 | 74.28 15 | | 83.31 24 | 95.86 4 | |
|
test_prior | | | | | 86.33 38 | 92.61 40 | 69.59 58 | | 92.97 27 | | | | | 95.48 34 | | | 93.91 25 |
|
旧先验2 | | | | | | | | 86.56 144 | | 58.10 246 | 87.04 10 | | | 88.98 209 | 74.07 93 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 86.29 152 | | | | | | | | | |
|
æ–°å‡ ä½•1 | | | | | 83.42 93 | 93.13 29 | 70.71 45 | | 85.48 194 | 57.43 252 | 81.80 59 | 91.98 49 | 63.28 86 | 92.27 151 | 64.60 166 | 92.99 39 | 87.27 203 |
|
旧先验1 | | | | | | 91.96 48 | 65.79 120 | | 86.37 186 | | | 93.08 37 | 69.31 46 | | | 92.74 42 | 88.74 169 |
|
æ— å…ˆéªŒ | | | | | | | | 87.48 113 | 88.98 150 | 60.00 235 | | | | 94.12 80 | 67.28 144 | | 88.97 164 |
|
原ACMM2 | | | | | | | | 86.86 135 | | | | | | | | | |
|
原ACMM1 | | | | | 84.35 72 | 93.01 33 | 68.79 72 | | 92.44 38 | 63.96 206 | 81.09 65 | 91.57 58 | 66.06 66 | 95.45 36 | 67.19 146 | 94.82 25 | 88.81 166 |
|
test222 | | | | | | 91.50 53 | 68.26 86 | 84.16 190 | 83.20 213 | 54.63 264 | 79.74 71 | 91.63 56 | 58.97 152 | | | 91.42 52 | 86.77 214 |
|
testdata2 | | | | | | | | | | | | | | 91.01 184 | 62.37 178 | | |
|
segment_acmp | | | | | | | | | | | | | 73.08 21 | | | | |
|
testdata | | | | | 79.97 182 | 90.90 60 | 64.21 159 | | 84.71 200 | 59.27 240 | 85.40 16 | 92.91 38 | 62.02 122 | 89.08 207 | 68.95 134 | 91.37 53 | 86.63 218 |
|
testdata1 | | | | | | | | 84.14 191 | | 75.71 63 | | | | | | | |
|
test12 | | | | | 86.80 30 | 92.63 39 | 70.70 46 | | 91.79 63 | | 82.71 55 | | 71.67 30 | 96.16 23 | | 94.50 28 | 93.54 40 |
|
plane_prior7 | | | | | | 90.08 70 | 68.51 83 | | | | | | | | | | |
|
plane_prior6 | | | | | | 89.84 75 | 68.70 79 | | | | | | 60.42 145 | | | | |
|
plane_prior5 | | | | | | | | | 92.44 38 | | | | | 95.38 41 | 78.71 53 | 86.32 102 | 91.33 92 |
|
plane_prior4 | | | | | | | | | | | | 91.00 71 | | | | | |
|
plane_prior3 | | | | | | | 68.60 81 | | | 78.44 25 | 78.92 80 | | | | | | |
|
plane_prior2 | | | | | | | | 91.25 26 | | 79.12 18 | | | | | | | |
|
plane_prior1 | | | | | | 89.90 74 | | | | | | | | | | | |
|
plane_prior | | | | | | | 68.71 77 | 90.38 40 | | 77.62 29 | | | | | | 86.16 104 | |
|
abl_6 | | | | | | 92.23 45 | 70.48 48 | | 92.08 50 | | 85.26 18 | 94.16 16 | 62.75 102 | | | | 91.81 83 |
|
n2 | | | | | | | | | 0.00 307 | | | | | | | | |
|
nn | | | | | | | | | 0.00 307 | | | | | | | | |
|
door-mid | | | | | | | | | 69.98 282 | | | | | | | | |
|
lessismore_v0 | | | | | 78.97 194 | 81.01 239 | 57.15 230 | | 65.99 288 | | 61.16 257 | 82.82 212 | 39.12 255 | 91.34 172 | 59.67 197 | 46.92 286 | 88.43 184 |
|
LGP-MVS_train | | | | | 84.50 67 | 89.23 91 | 68.76 74 | | 91.94 56 | 75.37 69 | 76.64 128 | 91.51 59 | 54.29 181 | 94.91 58 | 78.44 55 | 83.78 121 | 89.83 148 |
|
test11 | | | | | | | | | 92.23 44 | | | | | | | | |
|
door | | | | | | | | | 69.44 284 | | | | | | | | |
|
HQP5-MVS | | | | | | | 66.98 104 | | | | | | | | | | |
|
HQP-NCC | | | | | | 89.33 83 | | 89.17 59 | | 76.41 53 | 77.23 119 | | | | | | |
|
ACMP_Plane | | | | | | 89.33 83 | | 89.17 59 | | 76.41 53 | 77.23 119 | | | | | | |
|
BP-MVS | | | | | | | | |