APDe-MVS | | | 89.15 1 | 89.63 1 | 87.73 13 | 94.49 6 | 71.69 26 | 93.83 2 | 93.96 2 | 75.70 57 | 91.06 1 | 96.03 1 | 76.84 2 | 97.03 3 | 89.09 1 | 95.65 8 | 94.47 7 |
|
HPM-MVS++ | | | 89.02 2 | 89.15 2 | 88.63 1 | 95.01 1 | 76.03 1 | 92.38 11 | 92.85 25 | 80.26 10 | 87.78 7 | 94.27 10 | 75.89 6 | 96.81 6 | 87.45 5 | 96.44 1 | 93.05 48 |
|
CNVR-MVS | | | 88.93 3 | 89.13 3 | 88.33 3 | 94.77 2 | 73.82 4 | 90.51 33 | 93.00 18 | 80.90 7 | 88.06 6 | 94.06 16 | 76.43 3 | 96.84 5 | 88.48 2 | 95.99 2 | 94.34 10 |
|
SteuartSystems-ACMMP | | | 88.72 4 | 88.86 4 | 88.32 4 | 92.14 37 | 72.96 13 | 93.73 3 | 93.67 6 | 80.19 11 | 88.10 5 | 94.80 2 | 73.76 14 | 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 27 | 92.24 36 | 69.03 53 | 89.57 48 | 93.39 9 | 77.53 32 | 89.79 3 | 94.12 14 | 78.98 1 | 96.58 14 | 85.66 6 | 95.72 7 | 94.58 4 |
|
SD-MVS | | | 88.06 6 | 88.50 6 | 86.71 28 | 92.60 34 | 72.71 15 | 91.81 20 | 93.19 13 | 77.87 26 | 90.32 2 | 94.00 17 | 74.83 7 | 93.78 85 | 87.63 3 | 94.27 28 | 93.65 30 |
|
NCCC | | | 88.06 6 | 88.01 7 | 88.24 5 | 94.41 10 | 73.62 5 | 91.22 26 | 92.83 26 | 81.50 4 | 85.79 13 | 93.47 24 | 73.02 17 | 97.00 4 | 84.90 9 | 94.94 15 | 94.10 15 |
|
MP-MVS |  | | 87.71 8 | 87.64 8 | 87.93 10 | 94.36 12 | 73.88 2 | 92.71 10 | 92.65 30 | 77.57 29 | 83.84 29 | 94.40 9 | 72.24 21 | 96.28 19 | 85.65 7 | 95.30 12 | 93.62 32 |
|
ACMMPR | | | 87.44 9 | 87.23 11 | 88.08 6 | 94.64 3 | 73.59 6 | 93.04 5 | 93.20 12 | 76.78 43 | 84.66 22 | 94.52 3 | 68.81 35 | 96.65 9 | 84.53 12 | 94.90 16 | 94.00 20 |
|
APD-MVS |  | | 87.44 9 | 87.52 9 | 87.19 21 | 94.24 13 | 72.39 22 | 91.86 19 | 92.83 26 | 73.01 89 | 88.58 4 | 94.52 3 | 73.36 15 | 96.49 15 | 84.26 14 | 95.01 14 | 92.70 50 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
MCST-MVS | | | 87.37 11 | 87.25 10 | 87.73 13 | 94.53 5 | 72.46 21 | 89.82 44 | 93.82 4 | 73.07 88 | 84.86 21 | 92.89 31 | 76.22 4 | 96.33 17 | 84.89 10 | 95.13 13 | 94.40 8 |
|
#test# | | | 87.33 12 | 87.13 12 | 87.94 9 | 94.58 4 | 73.54 8 | 92.34 12 | 93.24 11 | 75.23 64 | 84.91 18 | 94.44 7 | 70.78 27 | 96.61 11 | 83.75 17 | 94.89 17 | 93.66 26 |
|
XVS | | | 87.18 13 | 86.91 15 | 88.00 7 | 94.42 8 | 73.33 11 | 92.78 6 | 92.99 19 | 79.14 15 | 83.67 32 | 94.17 13 | 67.45 42 | 96.60 12 | 83.06 22 | 94.50 21 | 94.07 16 |
|
HPM-MVS | | | 87.11 14 | 86.98 13 | 87.50 18 | 93.88 17 | 72.16 25 | 92.19 15 | 93.33 10 | 76.07 54 | 83.81 30 | 93.95 18 | 69.77 31 | 96.01 24 | 85.15 8 | 94.66 19 | 94.32 11 |
|
CP-MVS | | | 87.11 14 | 86.92 14 | 87.68 17 | 94.20 15 | 73.86 3 | 93.98 1 | 92.82 28 | 76.62 45 | 83.68 31 | 94.46 6 | 67.93 38 | 95.95 25 | 84.20 15 | 94.39 24 | 93.23 43 |
|
DeepC-MVS | | 79.81 2 | 87.08 16 | 86.88 16 | 87.69 16 | 91.16 46 | 72.32 24 | 90.31 37 | 93.94 3 | 77.12 37 | 82.82 39 | 94.23 12 | 72.13 22 | 97.09 2 | 84.83 11 | 95.37 10 | 93.65 30 |
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 17 | 86.62 18 | 87.76 12 | 93.52 20 | 72.37 23 | 91.26 23 | 93.04 15 | 76.62 45 | 84.22 25 | 93.36 26 | 71.44 25 | 96.76 7 | 80.82 33 | 95.33 11 | 94.16 13 |
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 18 | 86.86 17 | 86.33 33 | 92.61 32 | 69.59 48 | 88.85 62 | 92.97 22 | 75.41 60 | 84.91 18 | 93.54 20 | 74.28 11 | 95.48 32 | 83.31 18 | 95.86 4 | 93.91 22 |
|
PGM-MVS | | | 86.68 19 | 86.27 22 | 87.90 11 | 94.22 14 | 73.38 10 | 90.22 39 | 93.04 15 | 75.53 59 | 83.86 28 | 94.42 8 | 67.87 40 | 96.64 10 | 82.70 26 | 94.57 20 | 93.66 26 |
|
mPP-MVS | | | 86.67 20 | 86.32 21 | 87.72 15 | 94.41 10 | 73.55 7 | 92.74 8 | 92.22 38 | 76.87 41 | 82.81 40 | 94.25 11 | 66.44 49 | 96.24 20 | 82.88 25 | 94.28 27 | 93.38 39 |
|
Regformer-2 | | | 86.63 21 | 86.53 19 | 86.95 24 | 89.33 70 | 71.24 29 | 88.43 69 | 92.05 43 | 82.50 1 | 86.88 9 | 90.09 71 | 74.45 9 | 95.61 28 | 84.38 13 | 90.63 51 | 94.01 19 |
|
PHI-MVS | | | 86.43 22 | 86.17 24 | 87.24 20 | 90.88 51 | 70.96 32 | 92.27 14 | 94.07 1 | 72.45 100 | 85.22 16 | 91.90 42 | 69.47 32 | 96.42 16 | 83.28 20 | 95.94 3 | 94.35 9 |
|
Regformer-1 | | | 86.41 23 | 86.33 20 | 86.64 29 | 89.33 70 | 70.93 33 | 88.43 69 | 91.39 61 | 82.14 2 | 86.65 10 | 90.09 71 | 74.39 10 | 95.01 48 | 83.97 16 | 90.63 51 | 93.97 21 |
|
CSCG | | | 86.41 23 | 86.19 23 | 87.07 23 | 92.91 28 | 72.48 20 | 90.81 29 | 93.56 7 | 73.95 75 | 83.16 37 | 91.07 55 | 75.94 5 | 95.19 40 | 79.94 39 | 94.38 25 | 93.55 35 |
|
patchmatch test | | | 85.97 25 | 85.88 25 | 86.22 36 | 92.69 30 | 69.53 50 | 91.93 18 | 92.99 19 | 73.54 81 | 85.94 11 | 94.51 5 | 65.80 57 | 95.61 28 | 83.04 24 | 92.51 38 | 93.53 37 |
|
ACMMP |  | | 85.89 26 | 85.39 28 | 87.38 19 | 93.59 19 | 72.63 17 | 92.74 8 | 93.18 14 | 76.78 43 | 80.73 54 | 93.82 19 | 64.33 65 | 96.29 18 | 82.67 27 | 90.69 50 | 93.23 43 |
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 27 | 85.29 31 | 87.17 22 | 93.49 21 | 71.08 30 | 88.58 67 | 92.42 34 | 68.32 143 | 84.61 23 | 93.48 22 | 72.32 20 | 96.15 22 | 79.00 40 | 95.43 9 | 94.28 12 |
|
TSAR-MVS | | | 85.71 28 | 85.33 29 | 86.84 25 | 91.34 44 | 72.50 19 | 89.07 58 | 87.28 143 | 76.41 47 | 85.80 12 | 90.22 69 | 74.15 13 | 95.37 38 | 81.82 29 | 91.88 40 | 92.65 52 |
|
Regformer-4 | | | 85.68 29 | 85.45 27 | 86.35 32 | 88.95 82 | 69.67 47 | 88.29 77 | 91.29 63 | 81.73 3 | 85.36 15 | 90.01 73 | 72.62 18 | 95.35 39 | 83.28 20 | 87.57 75 | 94.03 18 |
|
3Dnovator+ | | 77.84 4 | 85.48 30 | 84.47 35 | 88.51 2 | 91.08 47 | 73.49 9 | 93.18 4 | 93.78 5 | 80.79 8 | 76.66 105 | 93.37 25 | 60.40 128 | 96.75 8 | 77.20 53 | 93.73 31 | 95.29 1 |
|
MSLP-MVS | | | 85.43 31 | 85.76 26 | 84.45 60 | 91.93 39 | 70.24 40 | 90.71 30 | 92.86 24 | 77.46 34 | 84.22 25 | 92.81 35 | 67.16 45 | 92.94 112 | 80.36 35 | 94.35 26 | 90.16 107 |
|
DELS-MVS | | | 85.41 32 | 85.30 30 | 85.77 39 | 88.49 95 | 67.93 76 | 85.52 142 | 93.44 8 | 78.70 22 | 83.63 34 | 89.03 94 | 74.57 8 | 95.71 27 | 80.26 37 | 94.04 29 | 93.66 26 |
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 33 | 84.95 33 | 86.57 31 | 93.69 18 | 70.58 39 | 92.15 16 | 91.62 54 | 73.89 76 | 82.67 42 | 94.09 15 | 62.60 93 | 95.54 31 | 80.93 31 | 92.93 33 | 93.57 34 |
|
Regformer-3 | | | 85.23 34 | 85.07 32 | 85.70 40 | 88.95 82 | 69.01 55 | 88.29 77 | 89.91 96 | 80.95 6 | 85.01 17 | 90.01 73 | 72.45 19 | 94.19 69 | 82.50 28 | 87.57 75 | 93.90 24 |
|
MVS_111021_HR | | | 85.14 35 | 84.75 34 | 86.32 35 | 91.65 42 | 72.70 16 | 85.98 133 | 90.33 82 | 76.11 53 | 82.08 44 | 91.61 48 | 71.36 26 | 94.17 70 | 81.02 30 | 92.58 37 | 92.08 61 |
|
EI-MVSNet-Vis | | | 84.19 36 | 83.81 36 | 85.31 42 | 88.18 102 | 67.85 77 | 87.66 90 | 89.73 100 | 80.05 13 | 82.95 38 | 89.59 80 | 70.74 28 | 94.82 54 | 80.66 34 | 84.72 99 | 93.28 42 |
|
EI-MVSNet-UG | | | 83.81 37 | 83.38 38 | 85.09 46 | 87.87 110 | 67.53 81 | 87.44 100 | 89.66 101 | 79.74 14 | 82.23 43 | 89.41 89 | 70.24 29 | 94.74 56 | 79.95 38 | 83.92 103 | 92.99 49 |
|
CPTT-MVS | | | 83.73 38 | 83.33 39 | 84.92 51 | 93.28 23 | 70.86 35 | 92.09 17 | 90.38 79 | 68.75 140 | 79.57 59 | 92.83 33 | 60.60 124 | 93.04 111 | 80.92 32 | 91.56 44 | 90.86 85 |
|
EPNet | | | 83.72 39 | 82.92 42 | 86.14 38 | 84.22 156 | 69.48 51 | 91.05 28 | 85.27 165 | 81.30 5 | 76.83 102 | 91.65 45 | 66.09 53 | 95.56 30 | 76.00 60 | 93.85 30 | 93.38 39 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
HQP_MVS | | | 83.64 40 | 83.14 40 | 85.14 45 | 90.08 60 | 68.71 64 | 91.25 24 | 92.44 31 | 79.12 17 | 78.92 66 | 91.00 58 | 60.42 126 | 95.38 36 | 78.71 43 | 86.32 88 | 91.33 74 |
|
Vis-MVSNet |  | | 83.46 41 | 82.80 44 | 85.43 41 | 90.25 58 | 68.74 63 | 90.30 38 | 90.13 89 | 76.33 52 | 80.87 53 | 92.89 31 | 61.00 119 | 94.20 68 | 72.45 88 | 90.97 48 | 93.35 41 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MG-MVS | | | 83.41 42 | 83.45 37 | 83.28 84 | 92.74 29 | 62.28 159 | 88.17 80 | 89.50 103 | 75.22 65 | 81.49 47 | 92.74 36 | 66.75 46 | 95.11 42 | 72.85 81 | 91.58 43 | 92.45 53 |
|
EPP-MVSNet | | | 83.40 43 | 83.02 41 | 84.57 56 | 90.13 59 | 64.47 131 | 92.32 13 | 90.73 72 | 74.45 70 | 79.35 62 | 91.10 53 | 69.05 34 | 95.12 41 | 72.78 82 | 87.22 79 | 94.13 14 |
|
3Dnovator | | 76.31 5 | 83.38 44 | 82.31 48 | 86.59 30 | 87.94 109 | 72.94 14 | 90.64 31 | 92.14 42 | 77.21 35 | 75.47 117 | 92.83 33 | 58.56 133 | 94.72 57 | 73.24 80 | 92.71 36 | 92.13 60 |
|
IS-MVSNet | | | 83.15 45 | 82.81 43 | 84.18 68 | 89.94 62 | 63.30 146 | 91.59 21 | 88.46 133 | 79.04 19 | 79.49 60 | 92.16 37 | 65.10 61 | 94.28 64 | 67.71 114 | 91.86 41 | 94.95 2 |
|
DP-MVS Recon | | | 83.11 46 | 82.09 50 | 86.15 37 | 94.44 7 | 70.92 34 | 88.79 64 | 92.20 39 | 70.53 121 | 79.17 63 | 91.03 57 | 64.12 67 | 96.03 23 | 68.39 113 | 90.14 56 | 91.50 72 |
|
PAPM_NR | | | 83.02 47 | 82.41 45 | 84.82 53 | 92.47 35 | 66.37 95 | 87.93 86 | 91.80 50 | 73.82 77 | 77.32 94 | 90.66 62 | 67.90 39 | 94.90 51 | 70.37 101 | 89.48 62 | 93.19 45 |
|
VDD-MVS | | | 83.01 48 | 82.36 47 | 84.96 49 | 91.02 48 | 66.40 94 | 88.91 60 | 88.11 135 | 77.57 29 | 84.39 24 | 93.29 27 | 52.19 167 | 93.91 79 | 77.05 54 | 88.70 69 | 94.57 5 |
|
MVSFormer | | | 82.85 49 | 82.05 51 | 85.24 44 | 87.35 123 | 70.21 41 | 90.50 34 | 90.38 79 | 68.55 141 | 81.32 48 | 89.47 84 | 61.68 107 | 93.46 94 | 78.98 41 | 90.26 54 | 92.05 62 |
|
OMC-MVS | | | 82.69 50 | 81.97 53 | 84.85 52 | 88.75 89 | 67.42 82 | 87.98 83 | 90.87 71 | 74.92 67 | 79.72 58 | 91.65 45 | 62.19 104 | 93.96 76 | 75.26 69 | 86.42 87 | 93.16 46 |
|
PVSNet_Blended_VisFu | | | 82.62 51 | 81.83 54 | 84.96 49 | 90.80 53 | 69.76 46 | 88.74 65 | 91.70 53 | 69.39 132 | 78.96 65 | 88.46 107 | 65.47 58 | 94.87 53 | 74.42 72 | 88.57 70 | 90.24 105 |
|
MVS_111021_LR | | | 82.61 52 | 82.11 49 | 84.11 69 | 88.82 86 | 71.58 27 | 85.15 143 | 86.16 158 | 74.69 68 | 80.47 55 | 91.04 56 | 62.29 101 | 90.55 158 | 80.33 36 | 90.08 57 | 90.20 106 |
|
HQP-MVS | | | 82.61 52 | 82.02 52 | 84.37 61 | 89.33 70 | 66.98 89 | 89.17 53 | 92.19 40 | 76.41 47 | 77.23 97 | 90.23 68 | 60.17 129 | 95.11 42 | 77.47 51 | 85.99 92 | 91.03 79 |
|
CLD-MVS | | | 82.31 54 | 81.65 55 | 84.29 65 | 88.47 96 | 67.73 80 | 85.81 138 | 92.35 36 | 75.78 55 | 78.33 78 | 86.58 147 | 64.01 68 | 94.35 62 | 76.05 59 | 87.48 77 | 90.79 86 |
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 55 | 82.41 45 | 81.62 131 | 90.82 52 | 60.93 164 | 84.47 154 | 89.78 98 | 76.36 51 | 84.07 27 | 91.88 43 | 64.71 64 | 90.26 160 | 70.68 98 | 88.89 66 | 93.66 26 |
|
LPG-MVS_test | | | 82.08 56 | 81.27 58 | 84.50 58 | 89.23 78 | 68.76 61 | 90.22 39 | 91.94 47 | 75.37 62 | 76.64 107 | 91.51 50 | 54.29 154 | 94.91 49 | 78.44 45 | 83.78 104 | 89.83 120 |
|
PS-MVSNAJss | | | 82.07 57 | 81.31 57 | 84.34 64 | 86.51 132 | 67.27 86 | 89.27 51 | 91.51 57 | 71.75 107 | 79.37 61 | 90.22 69 | 63.15 77 | 94.27 65 | 77.69 49 | 82.36 116 | 91.49 73 |
|
API-MVS | | | 81.99 58 | 81.23 59 | 84.26 66 | 90.94 49 | 70.18 43 | 91.10 27 | 89.32 106 | 71.51 113 | 78.66 70 | 88.28 112 | 65.26 59 | 95.10 45 | 64.74 139 | 91.23 47 | 87.51 172 |
|
UniMVSNet_NR-MVSNet | | | 81.88 59 | 81.54 56 | 82.92 100 | 88.46 97 | 63.46 142 | 87.13 110 | 92.37 35 | 80.19 11 | 78.38 76 | 89.14 91 | 71.66 24 | 93.05 109 | 70.05 103 | 76.46 168 | 92.25 56 |
|
MAR-MVS | | | 81.84 60 | 80.70 64 | 85.27 43 | 91.32 45 | 71.53 28 | 89.82 44 | 90.92 70 | 69.77 128 | 78.50 72 | 86.21 154 | 62.36 100 | 94.52 61 | 65.36 133 | 92.05 39 | 89.77 123 |
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 61 | 81.23 59 | 83.57 79 | 91.89 40 | 63.43 144 | 89.84 43 | 81.85 196 | 77.04 39 | 83.21 35 | 93.10 28 | 52.26 166 | 93.43 98 | 71.98 94 | 89.95 59 | 93.85 25 |
|
PS-MVSNAJ | | | 81.69 62 | 81.02 62 | 83.70 77 | 89.51 67 | 68.21 74 | 84.28 160 | 90.09 90 | 70.79 118 | 81.26 50 | 85.62 160 | 63.15 77 | 94.29 63 | 75.62 66 | 88.87 67 | 88.59 150 |
|
PAPR | | | 81.66 63 | 80.89 63 | 83.99 74 | 90.27 57 | 64.00 140 | 86.76 121 | 91.77 52 | 68.84 139 | 77.13 101 | 89.50 81 | 67.63 41 | 94.88 52 | 67.55 115 | 88.52 71 | 93.09 47 |
|
UniMVSNet (Re) | | | 81.60 64 | 81.11 61 | 83.09 91 | 88.38 99 | 64.41 133 | 87.60 91 | 93.02 17 | 78.42 25 | 78.56 71 | 88.16 113 | 69.78 30 | 93.26 100 | 69.58 107 | 76.49 167 | 91.60 68 |
|
VDDNet | | | 81.52 65 | 80.67 65 | 84.05 72 | 90.44 55 | 64.13 137 | 89.73 46 | 85.91 161 | 71.11 115 | 83.18 36 | 93.48 22 | 50.54 176 | 93.49 93 | 73.40 79 | 88.25 73 | 94.54 6 |
|
ACMP | | 74.13 6 | 81.51 66 | 80.57 66 | 84.36 62 | 89.42 68 | 68.69 67 | 89.97 42 | 91.50 59 | 74.46 69 | 75.04 132 | 90.41 65 | 53.82 159 | 94.54 59 | 77.56 50 | 82.91 109 | 89.86 119 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
jason | | | 81.39 67 | 80.29 71 | 84.70 55 | 86.63 131 | 69.90 45 | 85.95 134 | 86.77 148 | 63.24 183 | 81.07 52 | 89.47 84 | 61.08 118 | 92.15 125 | 78.33 48 | 90.07 58 | 92.05 62 |
jason: jason. |
lupinMVS | | | 81.39 67 | 80.27 72 | 84.76 54 | 87.35 123 | 70.21 41 | 85.55 140 | 86.41 153 | 62.85 187 | 81.32 48 | 88.61 103 | 61.68 107 | 92.24 124 | 78.41 47 | 90.26 54 | 91.83 65 |
|
DU-MVS | | | 81.12 69 | 80.52 68 | 82.90 101 | 87.80 113 | 63.46 142 | 87.02 114 | 91.87 49 | 79.01 20 | 78.38 76 | 89.07 92 | 65.02 62 | 93.05 109 | 70.05 103 | 76.46 168 | 92.20 57 |
|
PVSNet_Blended | | | 80.98 70 | 80.34 69 | 82.90 101 | 88.85 84 | 65.40 108 | 84.43 157 | 92.00 44 | 67.62 146 | 78.11 86 | 85.05 165 | 66.02 55 | 94.27 65 | 71.52 96 | 89.50 61 | 89.01 133 |
|
QAPM | | | 80.88 71 | 79.50 83 | 85.03 47 | 88.01 108 | 68.97 57 | 91.59 21 | 92.00 44 | 66.63 156 | 75.15 129 | 92.16 37 | 57.70 135 | 95.45 34 | 63.52 142 | 88.76 68 | 90.66 91 |
|
liao | | | 80.84 72 | 79.77 76 | 84.05 72 | 93.11 25 | 70.78 36 | 84.66 150 | 85.42 164 | 57.37 222 | 81.76 46 | 92.02 39 | 63.41 71 | 94.12 71 | 67.28 118 | 92.93 33 | 87.26 178 |
|
TranMVSNet+NR-MVSNet | | | 80.84 72 | 80.31 70 | 82.42 112 | 87.85 111 | 62.33 157 | 87.74 89 | 91.33 62 | 80.55 9 | 77.99 88 | 89.86 75 | 65.23 60 | 92.62 115 | 67.05 122 | 75.24 183 | 92.30 54 |
|
UGNet | | | 80.83 74 | 79.59 78 | 84.54 57 | 88.04 106 | 68.09 75 | 89.42 49 | 88.16 134 | 76.95 40 | 76.22 111 | 89.46 86 | 49.30 181 | 93.94 78 | 68.48 112 | 90.31 53 | 91.60 68 |
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 75 | 79.76 77 | 83.96 76 | 85.60 141 | 68.78 60 | 83.54 169 | 90.50 76 | 70.66 120 | 76.71 104 | 91.66 44 | 60.69 122 | 91.26 142 | 76.94 55 | 81.58 122 | 91.83 65 |
|
ACMM | | 73.20 8 | 80.78 76 | 79.84 75 | 83.58 78 | 89.31 75 | 68.37 70 | 89.99 41 | 91.60 55 | 70.28 124 | 77.25 95 | 89.66 78 | 53.37 161 | 93.53 92 | 74.24 74 | 82.85 110 | 88.85 137 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
114514_t | | | 80.68 77 | 79.51 82 | 84.20 67 | 94.09 16 | 67.27 86 | 89.64 47 | 91.11 67 | 58.75 213 | 74.08 138 | 90.72 61 | 58.10 134 | 95.04 47 | 69.70 106 | 89.42 63 | 90.30 104 |
|
VPA-MVSNet | | | 80.60 78 | 80.55 67 | 80.76 145 | 88.07 105 | 60.80 167 | 86.86 116 | 91.58 56 | 75.67 58 | 80.24 56 | 89.45 88 | 63.34 72 | 90.25 161 | 70.51 100 | 79.22 142 | 91.23 77 |
|
PVSNet_BlendedMVS | | | 80.60 78 | 80.02 73 | 82.36 114 | 88.85 84 | 65.40 108 | 86.16 131 | 92.00 44 | 69.34 134 | 78.11 86 | 86.09 156 | 66.02 55 | 94.27 65 | 71.52 96 | 82.06 117 | 87.39 174 |
|
AdaColmap |  | | 80.58 80 | 79.42 84 | 84.06 71 | 93.09 26 | 68.91 58 | 89.36 50 | 88.97 121 | 69.27 135 | 75.70 116 | 89.69 77 | 57.20 138 | 95.77 26 | 63.06 146 | 88.41 72 | 87.50 173 |
|
EI-MVSNet | | | 80.52 81 | 79.98 74 | 82.12 115 | 84.28 153 | 63.19 149 | 86.41 127 | 88.95 123 | 74.18 72 | 78.69 68 | 87.54 122 | 66.62 47 | 92.43 120 | 72.57 87 | 80.57 132 | 90.74 88 |
|
XVG-OURS | | | 80.41 82 | 79.23 92 | 83.97 75 | 85.64 140 | 69.02 54 | 83.03 172 | 90.39 78 | 71.09 116 | 77.63 93 | 91.49 52 | 54.62 153 | 91.35 140 | 75.71 64 | 83.47 106 | 91.54 70 |
|
v1neww | | | 80.40 83 | 79.54 79 | 82.98 96 | 84.10 163 | 64.51 127 | 87.57 93 | 90.22 84 | 73.25 82 | 78.47 73 | 86.65 143 | 62.83 84 | 93.86 81 | 75.72 62 | 77.02 158 | 90.58 93 |
|
v7new | | | 80.40 83 | 79.54 79 | 82.98 96 | 84.10 163 | 64.51 127 | 87.57 93 | 90.22 84 | 73.25 82 | 78.47 73 | 86.65 143 | 62.83 84 | 93.86 81 | 75.72 62 | 77.02 158 | 90.58 93 |
|
v6 | | | 80.40 83 | 79.54 79 | 82.98 96 | 84.09 165 | 64.50 129 | 87.57 93 | 90.22 84 | 73.25 82 | 78.47 73 | 86.63 145 | 62.84 83 | 93.86 81 | 75.73 61 | 77.02 158 | 90.58 93 |
|
PCF-MVS | | 73.52 7 | 80.38 86 | 78.84 97 | 85.01 48 | 87.71 116 | 68.99 56 | 83.65 166 | 91.46 60 | 63.00 185 | 77.77 91 | 90.28 66 | 66.10 52 | 95.09 46 | 61.40 161 | 88.22 74 | 90.94 83 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
X-MVStestdata | | | 80.37 87 | 77.83 114 | 88.00 7 | 94.42 8 | 73.33 11 | 92.78 6 | 92.99 19 | 79.14 15 | 83.67 32 | 12.47 261 | 67.45 42 | 96.60 12 | 83.06 22 | 94.50 21 | 94.07 16 |
|
test_djsdf | | | 80.30 88 | 79.32 87 | 83.27 85 | 83.98 171 | 65.37 110 | 90.50 34 | 90.38 79 | 68.55 141 | 76.19 112 | 88.70 99 | 56.44 140 | 93.46 94 | 78.98 41 | 80.14 137 | 90.97 82 |
|
v7 | | | 80.24 89 | 79.26 91 | 83.15 89 | 84.07 169 | 64.94 118 | 87.56 96 | 90.67 73 | 72.26 103 | 78.28 79 | 86.51 150 | 61.45 111 | 94.03 75 | 75.14 70 | 77.41 153 | 90.49 98 |
|
v2v482 | | | 80.23 90 | 79.29 90 | 83.05 93 | 83.62 176 | 64.14 136 | 87.04 113 | 89.97 93 | 73.61 78 | 78.18 85 | 87.22 130 | 61.10 117 | 93.82 84 | 76.11 58 | 76.78 166 | 91.18 78 |
|
NR-MVSNet | | | 80.23 90 | 79.38 85 | 82.78 108 | 87.80 113 | 63.34 145 | 86.31 129 | 91.09 68 | 79.01 20 | 72.17 154 | 89.07 92 | 67.20 44 | 92.81 114 | 66.08 128 | 75.65 176 | 92.20 57 |
|
divwei89l23v2f112 | | | 80.19 92 | 79.31 88 | 82.85 103 | 83.84 173 | 64.11 139 | 87.13 110 | 90.08 91 | 73.13 85 | 78.27 80 | 86.39 152 | 62.69 90 | 93.75 86 | 75.40 68 | 76.82 164 | 90.68 89 |
|
v1 | | | 80.19 92 | 79.31 88 | 82.85 103 | 83.83 174 | 64.12 138 | 87.14 108 | 90.07 92 | 73.13 85 | 78.27 80 | 86.38 153 | 62.72 89 | 93.75 86 | 75.41 67 | 76.82 164 | 90.68 89 |
|
IterMVS-LS | | | 80.06 94 | 79.38 85 | 82.11 116 | 85.89 136 | 63.20 148 | 86.79 118 | 89.34 105 | 74.19 71 | 75.45 119 | 86.72 136 | 66.62 47 | 92.39 122 | 72.58 86 | 76.86 162 | 90.75 87 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
v8 | | | 79.97 95 | 79.02 95 | 82.80 106 | 84.09 165 | 64.50 129 | 87.96 84 | 90.29 83 | 74.13 74 | 75.24 128 | 86.81 135 | 62.88 81 | 93.89 80 | 74.39 73 | 75.40 180 | 90.00 116 |
|
OpenMVS |  | 72.83 10 | 79.77 96 | 78.33 106 | 84.09 70 | 85.17 143 | 69.91 44 | 90.57 32 | 90.97 69 | 66.70 152 | 72.17 154 | 91.91 41 | 54.70 151 | 93.96 76 | 61.81 159 | 90.95 49 | 88.41 158 |
|
v10 | | | 79.74 97 | 78.67 98 | 82.97 99 | 84.06 170 | 64.95 117 | 87.88 88 | 90.62 75 | 73.11 87 | 75.11 130 | 86.56 148 | 61.46 110 | 94.05 74 | 73.68 76 | 75.55 177 | 89.90 117 |
|
BH-RMVSNet | | | 79.61 98 | 78.44 104 | 83.14 90 | 89.38 69 | 65.93 99 | 84.95 146 | 87.15 144 | 73.56 80 | 78.19 84 | 89.79 76 | 56.67 139 | 93.36 99 | 59.53 174 | 86.74 84 | 90.13 109 |
|
ab-mvs | | | 79.51 99 | 78.97 96 | 81.14 141 | 88.46 97 | 60.91 165 | 83.84 164 | 89.24 110 | 70.36 123 | 79.03 64 | 88.87 96 | 63.23 76 | 90.21 162 | 65.12 134 | 82.57 114 | 92.28 55 |
|
WR-MVS | | | 79.49 100 | 79.22 93 | 80.27 152 | 88.79 88 | 58.35 183 | 85.06 144 | 88.61 131 | 78.56 23 | 77.65 92 | 88.34 110 | 63.81 70 | 90.66 157 | 64.98 137 | 77.22 156 | 91.80 67 |
|
BH-untuned | | | 79.47 101 | 78.60 101 | 82.05 117 | 89.19 80 | 65.91 100 | 86.07 132 | 88.52 132 | 72.18 104 | 75.42 120 | 87.69 117 | 61.15 116 | 93.54 91 | 60.38 167 | 86.83 83 | 86.70 190 |
|
mvs_anonymous | | | 79.42 102 | 79.11 94 | 80.34 149 | 84.45 152 | 57.97 189 | 82.59 173 | 87.62 140 | 67.40 150 | 76.17 114 | 88.56 105 | 68.47 36 | 89.59 170 | 70.65 99 | 86.05 91 | 93.47 38 |
|
V42 | | | 79.38 103 | 78.24 109 | 82.83 105 | 81.10 207 | 65.50 107 | 85.55 140 | 89.82 97 | 71.57 112 | 78.21 83 | 86.12 155 | 60.66 123 | 93.18 104 | 75.64 65 | 75.46 179 | 89.81 122 |
|
jajsoiax | | | 79.29 104 | 77.96 111 | 83.27 85 | 84.68 148 | 66.57 93 | 89.25 52 | 90.16 88 | 69.20 137 | 75.46 118 | 89.49 82 | 45.75 197 | 93.13 107 | 76.84 56 | 80.80 128 | 90.11 110 |
|
TAPA-MVS | | 73.13 9 | 79.15 105 | 77.94 112 | 82.79 107 | 89.59 66 | 62.99 153 | 88.16 81 | 91.51 57 | 65.77 163 | 77.14 100 | 91.09 54 | 60.91 120 | 93.21 101 | 50.26 212 | 87.05 81 | 92.17 59 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
mvs_tets | | | 79.13 106 | 77.77 115 | 83.22 87 | 84.70 147 | 66.37 95 | 89.17 53 | 90.19 87 | 69.38 133 | 75.40 121 | 89.46 86 | 44.17 204 | 93.15 105 | 76.78 57 | 80.70 130 | 90.14 108 |
|
CDS-MVSNet | | | 79.07 107 | 77.70 116 | 83.17 88 | 87.60 118 | 68.23 73 | 84.40 158 | 86.20 157 | 67.49 148 | 76.36 109 | 86.54 149 | 61.54 109 | 90.79 155 | 61.86 158 | 87.33 78 | 90.49 98 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
MVSTER | | | 79.01 108 | 77.88 113 | 82.38 113 | 83.07 184 | 64.80 120 | 84.08 163 | 88.95 123 | 69.01 138 | 78.69 68 | 87.17 132 | 54.70 151 | 92.43 120 | 74.69 71 | 80.57 132 | 89.89 118 |
|
TAMVS | | | 78.89 109 | 77.51 118 | 83.03 94 | 87.80 113 | 67.79 79 | 84.72 149 | 85.05 168 | 67.63 145 | 76.75 103 | 87.70 116 | 62.25 102 | 90.82 154 | 58.53 180 | 87.13 80 | 90.49 98 |
|
diffmvs | | | 78.78 110 | 78.64 100 | 79.22 163 | 84.48 151 | 56.11 212 | 82.12 179 | 87.53 142 | 65.53 166 | 76.66 105 | 88.73 98 | 68.25 37 | 87.97 186 | 68.73 110 | 85.70 95 | 93.59 33 |
|
VPNet | | | 78.69 111 | 78.66 99 | 78.76 170 | 88.31 100 | 55.72 214 | 84.45 156 | 86.63 150 | 76.79 42 | 78.26 82 | 90.55 64 | 59.30 131 | 89.70 169 | 66.63 123 | 77.05 157 | 90.88 84 |
|
WR-MVS_H | | | 78.51 112 | 78.49 102 | 78.56 172 | 88.02 107 | 56.38 208 | 88.43 69 | 92.67 29 | 77.14 36 | 73.89 139 | 87.55 121 | 66.25 51 | 89.24 175 | 58.92 176 | 73.55 195 | 90.06 114 |
|
MVS_Test | | | 78.49 113 | 78.26 108 | 79.18 167 | 83.29 180 | 56.48 205 | 82.45 174 | 86.59 151 | 66.73 151 | 76.13 115 | 88.46 107 | 66.33 50 | 89.04 178 | 70.30 102 | 84.06 102 | 92.01 64 |
|
GBi-Net | | | 78.40 114 | 77.40 119 | 81.40 136 | 87.60 118 | 63.01 150 | 88.39 73 | 89.28 107 | 71.63 109 | 75.34 123 | 87.28 126 | 54.80 148 | 91.11 145 | 62.72 147 | 79.57 138 | 90.09 111 |
|
test1 | | | 78.40 114 | 77.40 119 | 81.40 136 | 87.60 118 | 63.01 150 | 88.39 73 | 89.28 107 | 71.63 109 | 75.34 123 | 87.28 126 | 54.80 148 | 91.11 145 | 62.72 147 | 79.57 138 | 90.09 111 |
|
Vis-MVSNet (Re-imp) | | | 78.36 116 | 78.45 103 | 78.07 178 | 88.64 91 | 51.78 227 | 86.70 122 | 79.63 210 | 74.14 73 | 75.11 130 | 90.83 60 | 61.29 114 | 89.75 168 | 58.10 184 | 91.60 42 | 92.69 51 |
|
CP-MVSNet | | | 78.22 117 | 78.34 105 | 77.84 180 | 87.83 112 | 54.54 218 | 87.94 85 | 91.17 66 | 77.65 27 | 73.48 141 | 88.49 106 | 62.24 103 | 88.43 183 | 62.19 153 | 74.07 190 | 90.55 96 |
|
BH-w/o | | | 78.21 118 | 77.33 121 | 80.84 143 | 88.81 87 | 65.13 114 | 84.87 147 | 87.85 137 | 69.75 129 | 74.52 136 | 84.74 170 | 61.34 112 | 93.11 108 | 58.24 183 | 85.84 94 | 84.27 210 |
|
FMVSNet2 | | | 78.20 119 | 77.21 122 | 81.20 139 | 87.60 118 | 62.89 154 | 87.47 99 | 89.02 114 | 71.63 109 | 75.29 127 | 87.28 126 | 54.80 148 | 91.10 148 | 62.38 151 | 79.38 141 | 89.61 125 |
|
HC-MVS | | | 78.19 120 | 76.99 125 | 81.78 121 | 85.66 139 | 66.99 88 | 84.66 150 | 90.47 77 | 55.08 230 | 72.02 158 | 85.27 163 | 63.83 69 | 94.11 73 | 66.10 127 | 89.80 60 | 84.24 211 |
|
Baseline_NR-MVSNet | | | 78.15 121 | 78.33 106 | 77.61 184 | 85.79 137 | 56.21 211 | 86.78 119 | 85.76 162 | 73.60 79 | 77.93 89 | 87.57 120 | 65.02 62 | 88.99 179 | 67.14 121 | 75.33 181 | 87.63 169 |
|
CNLPA | | | 78.08 122 | 76.79 129 | 81.97 119 | 90.40 56 | 71.07 31 | 87.59 92 | 84.55 170 | 66.03 162 | 72.38 153 | 89.64 79 | 57.56 136 | 86.04 198 | 59.61 172 | 83.35 107 | 88.79 139 |
|
PLC |  | 70.83 11 | 78.05 123 | 76.37 132 | 83.08 92 | 91.88 41 | 67.80 78 | 88.19 79 | 89.46 104 | 64.33 176 | 69.87 178 | 88.38 109 | 53.66 160 | 93.58 90 | 58.86 177 | 82.73 112 | 87.86 166 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
PS-CasMVS | | | 78.01 124 | 78.09 110 | 77.77 182 | 87.71 116 | 54.39 219 | 88.02 82 | 91.22 64 | 77.50 33 | 73.26 142 | 88.64 102 | 60.73 121 | 88.41 184 | 61.88 157 | 73.88 194 | 90.53 97 |
|
V4 | | | 77.95 125 | 76.37 132 | 82.67 109 | 79.40 221 | 65.52 105 | 86.43 125 | 89.94 94 | 72.28 101 | 72.14 157 | 84.95 166 | 55.72 143 | 93.44 96 | 73.64 77 | 72.86 198 | 89.05 131 |
|
HY-MVS | | 69.67 12 | 77.95 125 | 77.15 124 | 80.36 148 | 87.57 122 | 60.21 171 | 83.37 171 | 87.78 138 | 66.11 159 | 75.37 122 | 87.06 134 | 63.27 74 | 90.48 159 | 61.38 162 | 82.43 115 | 90.40 103 |
|
v52 | | | 77.94 127 | 76.37 132 | 82.67 109 | 79.39 222 | 65.52 105 | 86.43 125 | 89.94 94 | 72.28 101 | 72.15 156 | 84.94 167 | 55.70 144 | 93.44 96 | 73.64 77 | 72.84 199 | 89.06 130 |
|
FMVSNet3 | | | 77.88 128 | 76.85 127 | 80.97 142 | 86.84 129 | 62.36 156 | 86.52 124 | 88.77 130 | 71.13 114 | 75.34 123 | 86.66 142 | 54.07 157 | 91.10 148 | 62.72 147 | 79.57 138 | 89.45 127 |
|
PEN-MVS | | | 77.73 129 | 77.69 117 | 77.84 180 | 87.07 128 | 53.91 221 | 87.91 87 | 91.18 65 | 77.56 31 | 73.14 144 | 88.82 97 | 61.23 115 | 89.17 176 | 59.95 169 | 72.37 200 | 90.43 101 |
|
v16 | | | 77.69 130 | 76.36 135 | 81.68 128 | 84.15 160 | 64.63 125 | 87.33 102 | 88.99 118 | 72.69 98 | 69.31 185 | 82.08 189 | 62.80 87 | 91.79 129 | 72.70 84 | 67.23 218 | 88.63 144 |
|
v17 | | | 77.68 131 | 76.35 136 | 81.69 127 | 84.15 160 | 64.65 123 | 87.33 102 | 88.99 118 | 72.70 97 | 69.25 186 | 82.07 190 | 62.82 86 | 91.79 129 | 72.69 85 | 67.15 220 | 88.63 144 |
|
PAPM | | | 77.68 131 | 76.40 131 | 81.51 134 | 87.29 125 | 61.85 161 | 83.78 165 | 89.59 102 | 64.74 171 | 71.23 164 | 88.70 99 | 62.59 94 | 93.66 89 | 52.66 206 | 87.03 82 | 89.01 133 |
|
v18 | | | 77.67 133 | 76.35 136 | 81.64 130 | 84.09 165 | 64.47 131 | 87.27 105 | 89.01 116 | 72.59 99 | 69.39 182 | 82.04 191 | 62.85 82 | 91.80 128 | 72.72 83 | 67.20 219 | 88.63 144 |
|
V14 | | | 77.52 134 | 76.12 139 | 81.70 126 | 84.15 160 | 64.77 121 | 87.21 107 | 88.95 123 | 72.80 94 | 68.79 188 | 81.94 197 | 62.69 90 | 91.72 132 | 72.31 90 | 66.27 225 | 88.60 148 |
|
V9 | | | 77.52 134 | 76.11 142 | 81.73 125 | 84.19 159 | 64.89 119 | 87.26 106 | 88.94 126 | 72.87 93 | 68.65 191 | 81.96 196 | 62.65 92 | 91.72 132 | 72.27 91 | 66.24 226 | 88.60 148 |
|
v15 | | | 77.51 136 | 76.12 139 | 81.66 129 | 84.09 165 | 64.65 123 | 87.14 108 | 88.96 122 | 72.76 95 | 68.90 187 | 81.91 198 | 62.74 88 | 91.73 131 | 72.32 89 | 66.29 224 | 88.61 147 |
|
v12 | | | 77.51 136 | 76.09 143 | 81.76 124 | 84.22 156 | 64.99 116 | 87.30 104 | 88.93 127 | 72.92 90 | 68.48 193 | 81.97 194 | 62.54 96 | 91.70 135 | 72.24 92 | 66.21 228 | 88.58 151 |
|
v13 | | | 77.50 138 | 76.07 144 | 81.77 122 | 84.23 155 | 65.07 115 | 87.34 101 | 88.91 128 | 72.92 90 | 68.35 194 | 81.97 194 | 62.53 97 | 91.69 136 | 72.20 93 | 66.22 227 | 88.56 152 |
|
HyFIR | | | 77.49 139 | 77.16 123 | 78.47 175 | 88.18 102 | 58.04 186 | 75.75 218 | 84.17 175 | 60.53 199 | 76.25 110 | 89.49 82 | 62.42 99 | 87.81 189 | 68.64 111 | 89.00 65 | 89.56 126 |
|
v11 | | | 77.45 140 | 76.06 145 | 81.59 133 | 84.22 156 | 64.52 126 | 87.11 112 | 89.02 114 | 72.76 95 | 68.76 189 | 81.90 199 | 62.09 105 | 91.71 134 | 71.98 94 | 66.73 221 | 88.56 152 |
|
FMVSNet1 | | | 77.44 141 | 76.12 139 | 81.40 136 | 86.81 130 | 63.01 150 | 88.39 73 | 89.28 107 | 70.49 122 | 74.39 137 | 87.28 126 | 49.06 183 | 91.11 145 | 60.91 164 | 78.52 144 | 90.09 111 |
|
TR-MVS | | | 77.44 141 | 76.18 138 | 81.20 139 | 88.24 101 | 63.24 147 | 84.61 153 | 86.40 154 | 67.55 147 | 77.81 90 | 86.48 151 | 54.10 156 | 93.15 105 | 57.75 185 | 82.72 113 | 87.20 179 |
|
1112_ss | | | 77.40 143 | 76.43 130 | 80.32 150 | 89.11 81 | 60.41 170 | 83.65 166 | 87.72 139 | 62.13 192 | 73.05 145 | 86.72 136 | 62.58 95 | 89.97 166 | 62.11 155 | 80.80 128 | 90.59 92 |
|
LCM-MVSNet-Re | | | 77.05 144 | 76.94 126 | 77.36 186 | 87.20 126 | 51.60 228 | 80.06 193 | 80.46 204 | 75.20 66 | 67.69 198 | 86.72 136 | 62.48 98 | 88.98 180 | 63.44 143 | 89.25 64 | 91.51 71 |
|
DTE-MVSNet | | | 76.99 145 | 76.80 128 | 77.54 185 | 86.24 134 | 53.06 224 | 87.52 97 | 90.66 74 | 77.08 38 | 72.50 151 | 88.67 101 | 60.48 125 | 89.52 171 | 57.33 189 | 70.74 208 | 90.05 115 |
|
LS3D | | | 76.95 146 | 74.82 152 | 83.37 82 | 90.45 54 | 67.36 85 | 89.15 57 | 86.94 147 | 61.87 194 | 69.52 180 | 90.61 63 | 51.71 171 | 94.53 60 | 46.38 226 | 86.71 85 | 88.21 161 |
|
GA-MVS | | | 76.87 147 | 75.17 150 | 81.97 119 | 82.75 191 | 62.58 155 | 81.44 184 | 86.35 156 | 72.16 106 | 74.74 134 | 82.89 180 | 46.20 192 | 92.02 127 | 68.85 109 | 81.09 125 | 91.30 76 |
|
DP-MVS | | | 76.78 148 | 74.57 154 | 83.42 80 | 93.29 22 | 69.46 52 | 88.55 68 | 83.70 178 | 63.98 180 | 70.20 170 | 88.89 95 | 54.01 158 | 94.80 55 | 46.66 223 | 81.88 120 | 86.01 198 |
|
cascas | | | 76.72 149 | 74.64 153 | 82.99 95 | 85.78 138 | 65.88 101 | 82.33 177 | 89.21 111 | 60.85 198 | 72.74 147 | 81.02 205 | 47.28 188 | 93.75 86 | 67.48 116 | 85.02 96 | 89.34 128 |
|
liao1 | | | 76.53 150 | 75.30 149 | 80.21 153 | 83.93 172 | 62.32 158 | 84.66 150 | 88.81 129 | 60.23 203 | 70.16 172 | 84.07 171 | 55.30 147 | 90.73 156 | 67.37 117 | 83.21 108 | 87.59 171 |
|
Test_1112_low_res | | | 76.40 151 | 75.44 148 | 79.27 161 | 89.28 76 | 58.09 185 | 81.69 181 | 87.07 145 | 59.53 209 | 72.48 152 | 86.67 141 | 61.30 113 | 89.33 173 | 60.81 166 | 80.15 136 | 90.41 102 |
|
F-COLMAP | | | 76.38 152 | 74.33 157 | 82.50 111 | 89.28 76 | 66.95 91 | 88.41 72 | 89.03 113 | 64.05 178 | 66.83 204 | 88.61 103 | 46.78 191 | 92.89 113 | 57.48 186 | 78.55 143 | 87.67 168 |
|
LTVRE_ROB | | 69.57 13 | 76.25 153 | 74.54 156 | 81.41 135 | 88.60 92 | 64.38 134 | 79.24 199 | 89.12 112 | 70.76 119 | 69.79 179 | 87.86 114 | 49.09 182 | 93.20 102 | 56.21 194 | 80.16 135 | 86.65 191 |
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 |
XVG-ACMP-BASELINE | | | 76.11 154 | 74.27 158 | 81.62 131 | 83.20 181 | 64.67 122 | 83.60 168 | 89.75 99 | 69.75 129 | 71.85 159 | 87.09 133 | 32.78 235 | 92.11 126 | 69.99 105 | 80.43 134 | 88.09 163 |
|
ACMH+ | | 68.96 14 | 76.01 155 | 74.01 159 | 82.03 118 | 88.60 92 | 65.31 111 | 88.86 61 | 87.55 141 | 70.25 125 | 67.75 197 | 87.47 124 | 41.27 215 | 93.19 103 | 58.37 181 | 75.94 173 | 87.60 170 |
|
ACMH | | 67.68 16 | 75.89 156 | 73.93 160 | 81.77 122 | 88.71 90 | 66.61 92 | 88.62 66 | 89.01 116 | 69.81 127 | 66.78 205 | 86.70 140 | 41.95 214 | 91.51 139 | 55.64 195 | 78.14 149 | 87.17 180 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
IB-MVS | | 68.01 15 | 75.85 157 | 73.36 164 | 83.31 83 | 84.76 146 | 66.03 97 | 83.38 170 | 85.06 167 | 70.21 126 | 69.40 181 | 81.05 204 | 45.76 196 | 94.66 58 | 65.10 135 | 75.49 178 | 89.25 129 |
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 |
WTY-MVS | | | 75.65 158 | 75.68 146 | 75.57 198 | 86.40 133 | 56.82 199 | 77.92 208 | 82.40 189 | 65.10 170 | 76.18 113 | 87.72 115 | 63.13 79 | 80.90 216 | 60.31 168 | 81.96 118 | 89.00 135 |
|
EPNet_dtu | | | 75.46 159 | 74.86 151 | 77.23 188 | 82.57 194 | 54.60 217 | 86.89 115 | 83.09 183 | 71.64 108 | 66.25 209 | 85.86 158 | 55.99 142 | 88.04 185 | 54.92 196 | 86.55 86 | 89.05 131 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
XXY-MVS | | | 75.41 160 | 75.56 147 | 74.96 200 | 83.59 177 | 57.82 192 | 80.59 191 | 83.87 177 | 66.54 157 | 74.93 133 | 88.31 111 | 63.24 75 | 80.09 220 | 62.16 154 | 76.85 163 | 86.97 185 |
|
TransMVSNet (Re) | | | 75.39 161 | 74.56 155 | 77.86 179 | 85.50 142 | 57.10 197 | 86.78 119 | 86.09 160 | 72.17 105 | 71.53 163 | 87.34 125 | 63.01 80 | 89.31 174 | 56.84 191 | 61.83 236 | 87.17 180 |
|
CostFormer | | | 75.24 162 | 73.90 161 | 79.27 161 | 82.65 193 | 58.27 184 | 80.80 186 | 82.73 187 | 61.57 195 | 75.33 126 | 83.13 179 | 55.52 145 | 91.07 151 | 64.98 137 | 78.34 148 | 88.45 156 |
|
PT_06_test | | | 75.20 163 | 73.77 162 | 79.49 160 | 82.69 192 | 60.19 172 | 82.34 175 | 86.99 146 | 69.71 131 | 72.52 150 | 78.31 218 | 56.27 141 | 90.07 165 | 62.03 156 | 73.11 197 | 88.23 159 |
|
PatchFormer-LS_test | | | 74.50 164 | 73.05 165 | 78.86 169 | 82.95 187 | 59.55 176 | 81.65 182 | 82.30 191 | 67.44 149 | 71.62 162 | 78.15 221 | 52.34 164 | 88.92 182 | 65.05 136 | 75.90 174 | 88.12 162 |
|
IterMVS | | | 74.29 165 | 72.94 166 | 78.35 176 | 81.53 202 | 63.49 141 | 81.58 183 | 82.49 188 | 68.06 144 | 69.99 175 | 83.69 175 | 51.66 172 | 85.54 201 | 65.85 130 | 71.64 205 | 86.01 198 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
OurMVSNet-221017-0 | | | 74.26 166 | 72.42 169 | 79.80 156 | 83.76 175 | 59.59 174 | 85.92 136 | 86.64 149 | 66.39 158 | 66.96 203 | 87.58 119 | 39.46 220 | 91.60 138 | 65.76 131 | 69.27 211 | 88.22 160 |
|
EG-PatchMatch MVS | | | 74.04 167 | 71.82 173 | 80.71 146 | 84.92 145 | 67.42 82 | 85.86 137 | 88.08 136 | 66.04 161 | 64.22 218 | 83.85 172 | 35.10 234 | 92.56 118 | 57.44 187 | 80.83 127 | 82.16 225 |
|
Test4 | | | 73.95 168 | 72.20 170 | 79.21 164 | 82.91 188 | 58.94 178 | 81.25 185 | 82.17 192 | 65.21 167 | 71.05 166 | 82.44 183 | 44.21 202 | 90.17 163 | 63.29 144 | 77.28 154 | 88.53 154 |
|
DWT-MVSNet_test | | | 73.70 169 | 71.86 172 | 79.21 164 | 82.91 188 | 58.94 178 | 82.34 175 | 82.17 192 | 65.21 167 | 71.05 166 | 78.31 218 | 44.21 202 | 90.17 163 | 63.29 144 | 77.28 154 | 88.53 154 |
|
sss | | | 73.60 170 | 73.64 163 | 73.51 210 | 82.80 190 | 55.01 216 | 76.12 213 | 81.69 197 | 62.47 191 | 74.68 135 | 85.85 159 | 57.32 137 | 78.11 227 | 60.86 165 | 80.93 126 | 87.39 174 |
|
tpmp4_e23 | | | 73.45 171 | 71.17 180 | 80.31 151 | 83.55 178 | 59.56 175 | 81.88 180 | 82.33 190 | 57.94 218 | 70.51 169 | 81.62 200 | 51.19 175 | 91.63 137 | 53.96 200 | 77.51 152 | 89.75 124 |
|
SixPastTwentyTwo | | | 73.37 172 | 71.26 179 | 79.70 157 | 85.08 144 | 57.89 191 | 85.57 139 | 83.56 179 | 71.03 117 | 65.66 210 | 85.88 157 | 42.10 212 | 92.57 117 | 59.11 175 | 63.34 233 | 88.65 143 |
|
CR-MVSNet | | | 73.37 172 | 71.27 178 | 79.67 158 | 81.32 205 | 65.19 112 | 75.92 215 | 80.30 206 | 59.92 206 | 72.73 148 | 81.19 202 | 52.50 162 | 86.69 193 | 59.84 170 | 77.71 150 | 87.11 183 |
|
MSDG | | | 73.36 174 | 70.99 181 | 80.49 147 | 84.51 150 | 65.80 102 | 80.71 188 | 86.13 159 | 65.70 164 | 65.46 211 | 83.74 174 | 44.60 200 | 90.91 153 | 51.13 210 | 76.89 161 | 84.74 209 |
|
tpm2 | | | 73.26 175 | 71.46 175 | 78.63 171 | 83.34 179 | 56.71 202 | 80.65 189 | 80.40 205 | 56.63 225 | 73.55 140 | 82.02 192 | 51.80 170 | 91.24 143 | 56.35 193 | 78.42 147 | 87.95 164 |
|
RPSCF | | | 73.23 176 | 71.46 175 | 78.54 173 | 82.50 195 | 59.85 173 | 82.18 178 | 82.84 186 | 58.96 211 | 71.15 165 | 89.41 89 | 45.48 199 | 84.77 204 | 58.82 178 | 71.83 204 | 91.02 81 |
|
PatchmatchNet |  | | 73.12 177 | 71.33 177 | 78.49 174 | 83.18 182 | 60.85 166 | 79.63 196 | 78.57 214 | 64.13 177 | 71.73 160 | 79.81 213 | 51.20 174 | 85.97 199 | 57.40 188 | 76.36 170 | 88.66 142 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
COLMAP_ROB |  | 66.92 17 | 73.01 178 | 70.41 185 | 80.81 144 | 87.13 127 | 65.63 104 | 88.30 76 | 84.19 174 | 62.96 186 | 63.80 220 | 87.69 117 | 38.04 225 | 92.56 118 | 46.66 223 | 74.91 184 | 84.24 211 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
CVMVSNet | | | 72.99 179 | 72.58 167 | 74.25 207 | 84.28 153 | 50.85 233 | 86.41 127 | 83.45 180 | 44.56 248 | 73.23 143 | 87.54 122 | 49.38 179 | 85.70 200 | 65.90 129 | 78.44 146 | 86.19 195 |
|
test-LLR | | | 72.94 180 | 72.43 168 | 74.48 204 | 81.35 203 | 58.04 186 | 78.38 204 | 77.46 218 | 66.66 153 | 69.95 176 | 79.00 216 | 48.06 186 | 79.24 222 | 66.13 125 | 84.83 97 | 86.15 196 |
|
test_0402 | | | 72.79 181 | 70.44 184 | 79.84 155 | 88.13 104 | 65.99 98 | 85.93 135 | 84.29 172 | 65.57 165 | 67.40 200 | 85.49 161 | 46.92 190 | 92.61 116 | 35.88 242 | 74.38 189 | 80.94 227 |
|
tpmrst | | | 72.39 182 | 72.13 171 | 73.18 212 | 80.54 212 | 49.91 235 | 79.91 195 | 79.08 212 | 63.11 184 | 71.69 161 | 79.95 210 | 55.32 146 | 82.77 211 | 65.66 132 | 73.89 193 | 86.87 186 |
|
PatchMatch-RL | | | 72.38 183 | 70.90 182 | 76.80 191 | 88.60 92 | 67.38 84 | 79.53 197 | 76.17 224 | 62.75 189 | 69.36 183 | 82.00 193 | 45.51 198 | 84.89 203 | 53.62 201 | 80.58 131 | 78.12 235 |
|
tpm | | | 72.37 184 | 71.71 174 | 74.35 206 | 82.19 197 | 52.00 225 | 79.22 200 | 77.29 220 | 64.56 173 | 72.95 146 | 83.68 176 | 51.35 173 | 83.26 210 | 58.33 182 | 75.80 175 | 87.81 167 |
|
PVSNet | | 64.34 18 | 72.08 185 | 70.87 183 | 75.69 197 | 86.21 135 | 56.44 207 | 74.37 226 | 80.73 202 | 62.06 193 | 70.17 171 | 82.23 187 | 42.86 208 | 83.31 209 | 54.77 197 | 84.45 100 | 87.32 176 |
|
RPMNet | | | 71.62 186 | 68.94 193 | 79.67 158 | 81.32 205 | 65.19 112 | 75.92 215 | 78.30 216 | 57.60 220 | 72.73 148 | 76.45 228 | 52.30 165 | 86.69 193 | 48.14 220 | 77.71 150 | 87.11 183 |
|
test-mter | | | 71.41 187 | 70.39 186 | 74.48 204 | 81.35 203 | 58.04 186 | 78.38 204 | 77.46 218 | 60.32 202 | 69.95 176 | 79.00 216 | 36.08 232 | 79.24 222 | 66.13 125 | 84.83 97 | 86.15 196 |
|
K. test v3 | | | 71.19 188 | 68.51 195 | 79.21 164 | 83.04 185 | 57.78 193 | 84.35 159 | 76.91 222 | 72.90 92 | 62.99 223 | 82.86 181 | 39.27 221 | 91.09 150 | 61.65 160 | 52.66 248 | 88.75 140 |
|
tpmvs | | | 71.09 189 | 69.29 189 | 76.49 192 | 82.04 198 | 56.04 213 | 78.92 203 | 81.37 199 | 64.05 178 | 67.18 201 | 78.28 220 | 49.74 178 | 89.77 167 | 49.67 215 | 72.37 200 | 83.67 214 |
|
pm-mvs1 | | | 70.87 190 | 69.03 191 | 76.39 193 | 79.41 220 | 58.92 180 | 80.64 190 | 78.89 213 | 55.71 227 | 67.14 202 | 83.58 177 | 48.48 185 | 85.25 202 | 52.94 205 | 74.48 188 | 84.99 206 |
|
Patchmtry | | | 70.74 191 | 69.16 190 | 75.49 199 | 80.72 209 | 54.07 220 | 74.94 225 | 80.30 206 | 58.34 214 | 70.01 173 | 81.19 202 | 52.50 162 | 86.54 195 | 53.37 202 | 71.09 206 | 85.87 200 |
|
MIMVSNet | | | 70.69 192 | 69.30 188 | 74.88 201 | 84.52 149 | 56.35 209 | 75.87 217 | 79.42 211 | 64.59 172 | 67.76 196 | 82.41 184 | 41.10 216 | 81.54 215 | 46.64 225 | 81.34 123 | 86.75 189 |
|
tpm cat1 | | | 70.57 193 | 68.31 197 | 77.35 187 | 82.41 196 | 57.95 190 | 78.08 207 | 80.22 208 | 52.04 240 | 68.54 192 | 77.66 224 | 52.00 169 | 87.84 188 | 51.77 207 | 72.07 203 | 86.25 194 |
|
OpenMVS_ROB |  | 64.09 19 | 70.56 194 | 68.19 198 | 77.65 183 | 80.26 213 | 59.41 177 | 85.01 145 | 82.96 185 | 58.76 212 | 65.43 212 | 82.33 185 | 37.63 228 | 91.23 144 | 45.34 230 | 76.03 172 | 82.32 223 |
|
USDC | | | 70.33 195 | 68.37 196 | 76.21 195 | 80.60 211 | 56.23 210 | 79.19 201 | 86.49 152 | 60.89 197 | 61.29 224 | 85.47 162 | 31.78 236 | 89.47 172 | 53.37 202 | 76.21 171 | 82.94 222 |
|
CMPMVS |  | 51.72 21 | 70.19 196 | 68.16 199 | 76.28 194 | 73.15 240 | 57.55 194 | 79.47 198 | 83.92 176 | 48.02 246 | 56.48 236 | 84.81 168 | 43.13 206 | 86.42 197 | 62.67 150 | 81.81 121 | 84.89 207 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
TESTMET0.1,1 | | | 69.89 197 | 69.00 192 | 72.55 213 | 79.27 224 | 56.85 198 | 78.38 204 | 74.71 234 | 57.64 219 | 68.09 195 | 77.19 226 | 37.75 226 | 76.70 232 | 63.92 141 | 84.09 101 | 84.10 213 |
|
FMVSNet5 | | | 69.50 198 | 67.96 201 | 74.15 208 | 82.97 186 | 55.35 215 | 80.01 194 | 82.12 194 | 62.56 190 | 63.02 221 | 81.53 201 | 36.92 229 | 81.92 213 | 48.42 218 | 74.06 191 | 85.17 205 |
|
PMMVS | | | 69.34 199 | 68.67 194 | 71.35 219 | 75.67 232 | 62.03 160 | 75.17 220 | 73.46 239 | 50.00 244 | 68.68 190 | 79.05 214 | 52.07 168 | 78.13 226 | 61.16 163 | 82.77 111 | 73.90 243 |
|
EPMVS | | | 69.02 200 | 68.16 199 | 71.59 215 | 79.61 218 | 49.80 236 | 77.40 210 | 66.93 250 | 62.82 188 | 70.01 173 | 79.05 214 | 45.79 195 | 77.86 229 | 56.58 192 | 75.26 182 | 87.13 182 |
|
MIMVSNet1 | | | 68.58 201 | 66.78 206 | 73.98 209 | 80.07 214 | 51.82 226 | 80.77 187 | 84.37 171 | 64.40 175 | 59.75 227 | 82.16 188 | 36.47 230 | 83.63 207 | 42.73 233 | 70.33 209 | 86.48 193 |
|
EU-MVSNet | | | 68.53 202 | 67.61 204 | 71.31 220 | 78.51 226 | 47.01 241 | 84.47 154 | 84.27 173 | 42.27 249 | 66.44 208 | 84.79 169 | 40.44 218 | 83.76 205 | 58.76 179 | 68.54 217 | 83.17 217 |
|
PatchT | | | 68.46 203 | 67.85 202 | 70.29 222 | 80.70 210 | 43.93 245 | 72.47 229 | 74.88 230 | 60.15 204 | 70.55 168 | 76.57 227 | 49.94 177 | 81.59 214 | 50.58 211 | 74.83 185 | 85.34 202 |
|
test0.0.03 1 | | | 68.00 204 | 67.69 203 | 68.90 226 | 77.55 227 | 47.43 239 | 75.70 219 | 72.95 241 | 66.66 153 | 66.56 206 | 82.29 186 | 48.06 186 | 75.87 235 | 44.97 231 | 74.51 187 | 83.41 216 |
|
TDRefinement | | | 67.49 205 | 64.34 211 | 76.92 189 | 73.47 239 | 61.07 163 | 84.86 148 | 82.98 184 | 59.77 207 | 58.30 230 | 85.13 164 | 26.06 239 | 87.89 187 | 47.92 221 | 60.59 240 | 81.81 226 |
|
test20.03 | | | 67.45 206 | 66.95 205 | 68.94 225 | 75.48 235 | 44.84 243 | 77.50 209 | 77.67 217 | 66.66 153 | 63.01 222 | 83.80 173 | 47.02 189 | 78.40 225 | 42.53 234 | 68.86 215 | 83.58 215 |
|
UnsupCasMVSNet_eth | | | 67.33 207 | 65.99 208 | 71.37 217 | 73.48 238 | 51.47 230 | 75.16 221 | 85.19 166 | 65.20 169 | 60.78 226 | 80.93 207 | 42.35 209 | 77.20 231 | 57.12 190 | 53.69 247 | 85.44 201 |
|
TinyColmap | | | 67.30 208 | 64.81 210 | 74.76 203 | 81.92 199 | 56.68 203 | 80.29 192 | 81.49 198 | 60.33 201 | 56.27 237 | 83.22 178 | 24.77 241 | 87.66 190 | 45.52 228 | 69.47 210 | 79.95 231 |
|
dp | | | 66.80 209 | 65.43 209 | 70.90 221 | 79.74 217 | 48.82 238 | 75.12 223 | 74.77 232 | 59.61 208 | 64.08 219 | 77.23 225 | 42.89 207 | 80.72 217 | 48.86 217 | 66.58 223 | 83.16 218 |
|
MDA-MVSNet-bldmvs | | | 66.68 210 | 63.66 213 | 75.75 196 | 79.28 223 | 60.56 169 | 73.92 227 | 78.35 215 | 64.43 174 | 50.13 247 | 79.87 212 | 44.02 205 | 83.67 206 | 46.10 227 | 56.86 242 | 83.03 220 |
|
testgi | | | 66.67 211 | 66.53 207 | 67.08 231 | 75.62 233 | 41.69 250 | 75.93 214 | 76.50 223 | 66.11 159 | 65.20 215 | 86.59 146 | 35.72 233 | 74.71 238 | 43.71 232 | 73.38 196 | 84.84 208 |
|
PM-MVS | | | 66.41 212 | 64.14 212 | 73.20 211 | 73.92 236 | 56.45 206 | 78.97 202 | 64.96 254 | 63.88 182 | 64.72 216 | 80.24 209 | 19.84 248 | 83.44 208 | 66.24 124 | 64.52 231 | 79.71 232 |
|
JIA-IIPM | | | 66.32 213 | 62.82 218 | 76.82 190 | 77.09 228 | 61.72 162 | 65.34 250 | 75.38 226 | 58.04 217 | 64.51 217 | 62.32 247 | 42.05 213 | 86.51 196 | 51.45 209 | 69.22 212 | 82.21 224 |
|
ADS-MVSNet2 | | | 66.20 214 | 63.33 214 | 74.82 202 | 79.92 215 | 58.75 181 | 67.55 246 | 75.19 228 | 53.37 236 | 65.25 213 | 75.86 229 | 42.32 210 | 80.53 218 | 41.57 235 | 68.91 213 | 85.18 203 |
|
YYNet1 | | | 65.03 215 | 62.91 216 | 71.38 216 | 75.85 231 | 56.60 204 | 69.12 240 | 74.66 236 | 57.28 223 | 54.12 239 | 77.87 223 | 45.85 194 | 74.48 239 | 49.95 213 | 61.52 238 | 83.05 219 |
|
MDA-MVSNet_test_wron | | | 65.03 215 | 62.92 215 | 71.37 217 | 75.93 230 | 56.73 200 | 69.09 241 | 74.73 233 | 57.28 223 | 54.03 240 | 77.89 222 | 45.88 193 | 74.39 240 | 49.89 214 | 61.55 237 | 82.99 221 |
|
ADS-MVSNet | | | 64.36 217 | 62.88 217 | 68.78 228 | 79.92 215 | 47.17 240 | 67.55 246 | 71.18 244 | 53.37 236 | 65.25 213 | 75.86 229 | 42.32 210 | 73.99 242 | 41.57 235 | 68.91 213 | 85.18 203 |
|
LF4IMVS | | | 64.02 218 | 62.19 219 | 69.50 224 | 70.90 244 | 53.29 223 | 76.13 212 | 77.18 221 | 52.65 239 | 58.59 228 | 80.98 206 | 23.55 242 | 76.52 233 | 53.06 204 | 66.66 222 | 78.68 234 |
|
UnsupCasMVSNet_bld | | | 63.70 219 | 61.53 220 | 70.21 223 | 73.69 237 | 51.39 231 | 72.82 228 | 81.89 195 | 55.63 228 | 57.81 231 | 71.80 236 | 38.67 223 | 78.61 224 | 49.26 216 | 52.21 249 | 80.63 228 |
|
PVSNet_0 | | 57.27 20 | 61.67 220 | 59.27 221 | 68.85 227 | 79.61 218 | 57.44 195 | 68.01 244 | 73.44 240 | 55.93 226 | 58.54 229 | 70.41 239 | 44.58 201 | 77.55 230 | 47.01 222 | 35.91 254 | 71.55 245 |
|
LP | | | 61.36 221 | 57.78 224 | 72.09 214 | 75.54 234 | 58.53 182 | 67.16 248 | 75.22 227 | 51.90 241 | 54.13 238 | 69.97 240 | 37.73 227 | 80.45 219 | 32.74 246 | 55.63 244 | 77.29 238 |
|
test2356 | | | 59.50 222 | 58.08 222 | 63.74 235 | 71.23 243 | 41.88 248 | 67.59 245 | 72.42 243 | 53.72 235 | 57.65 232 | 70.74 238 | 26.31 238 | 72.40 245 | 32.03 249 | 71.06 207 | 76.93 240 |
|
MVS-HIRNet | | | 59.14 223 | 57.67 225 | 63.57 236 | 81.65 201 | 43.50 246 | 71.73 230 | 65.06 253 | 39.59 253 | 51.43 245 | 57.73 250 | 38.34 224 | 82.58 212 | 39.53 238 | 73.95 192 | 64.62 250 |
|
testus | | | 59.00 224 | 57.91 223 | 62.25 238 | 72.25 241 | 39.09 253 | 69.74 235 | 75.02 229 | 53.04 238 | 57.21 234 | 73.72 234 | 18.76 250 | 70.33 249 | 32.86 245 | 68.57 216 | 77.35 237 |
|
test1235678 | | | 58.74 225 | 56.89 228 | 64.30 233 | 69.70 245 | 41.87 249 | 71.05 231 | 74.87 231 | 54.06 232 | 50.63 246 | 71.53 237 | 25.30 240 | 74.10 241 | 31.80 250 | 63.10 234 | 76.93 240 |
|
pmmvs3 | | | 57.79 226 | 54.26 230 | 68.37 229 | 64.02 252 | 56.72 201 | 75.12 223 | 65.17 252 | 40.20 251 | 52.93 243 | 69.86 241 | 20.36 246 | 75.48 237 | 45.45 229 | 55.25 246 | 72.90 244 |
|
DSMNet-mixed | | | 57.77 227 | 56.90 227 | 60.38 239 | 67.70 250 | 35.61 256 | 69.18 239 | 53.97 257 | 32.30 260 | 57.49 233 | 79.88 211 | 40.39 219 | 68.57 252 | 38.78 239 | 72.37 200 | 76.97 239 |
|
1111 | | | 57.11 228 | 56.82 229 | 57.97 242 | 69.10 246 | 28.28 261 | 68.90 242 | 74.54 237 | 54.01 233 | 53.71 241 | 74.51 232 | 23.09 243 | 67.90 253 | 32.28 247 | 61.26 239 | 77.73 236 |
|
testpf | | | 56.51 229 | 57.58 226 | 53.30 246 | 71.99 242 | 41.19 251 | 46.89 261 | 69.32 248 | 58.06 216 | 52.87 244 | 69.45 242 | 27.99 237 | 72.73 244 | 59.59 173 | 62.07 235 | 45.98 256 |
|
LCM-MVSNet | | | 54.25 230 | 49.68 237 | 67.97 230 | 53.73 259 | 45.28 242 | 66.85 249 | 80.78 201 | 35.96 255 | 39.45 253 | 62.23 248 | 8.70 259 | 78.06 228 | 48.24 219 | 51.20 250 | 80.57 229 |
|
testmv | | | 53.85 231 | 51.03 233 | 62.31 237 | 61.46 254 | 38.88 254 | 70.95 234 | 74.69 235 | 51.11 243 | 41.26 250 | 66.85 243 | 14.28 253 | 72.13 246 | 29.19 252 | 49.51 251 | 75.93 242 |
|
FPMVS | | | 53.68 232 | 51.64 232 | 59.81 240 | 65.08 251 | 51.03 232 | 69.48 238 | 69.58 246 | 41.46 250 | 40.67 251 | 72.32 235 | 16.46 252 | 70.00 250 | 24.24 256 | 65.42 229 | 58.40 252 |
|
N_pmnet | | | 52.79 233 | 53.26 231 | 51.40 249 | 78.99 225 | 7.68 268 | 69.52 237 | 3.89 265 | 51.63 242 | 57.01 235 | 74.98 231 | 40.83 217 | 65.96 255 | 37.78 240 | 64.67 230 | 80.56 230 |
|
HyFIR lowres test | | | 51.79 234 | 50.01 236 | 57.11 243 | 68.82 248 | 49.21 237 | 60.50 253 | 53.26 258 | 34.52 256 | 43.77 249 | 64.94 246 | 20.34 247 | 71.75 247 | 39.87 237 | 64.06 232 | 50.39 253 |
|
no-one | | | 51.08 235 | 45.79 240 | 66.95 232 | 57.92 257 | 50.49 234 | 59.63 256 | 76.04 225 | 48.04 245 | 31.85 254 | 56.10 253 | 19.12 249 | 80.08 221 | 36.89 241 | 26.52 256 | 70.29 246 |
|
new_pmnet | | | 50.91 236 | 50.29 234 | 52.78 247 | 68.58 249 | 34.94 259 | 63.71 252 | 56.63 256 | 39.73 252 | 44.95 248 | 65.47 245 | 21.93 245 | 58.48 257 | 34.98 243 | 56.62 243 | 64.92 249 |
|
ANet_high | | | 50.57 237 | 46.10 239 | 63.99 234 | 48.67 262 | 39.13 252 | 70.99 233 | 80.85 200 | 61.39 196 | 31.18 256 | 57.70 251 | 17.02 251 | 73.65 243 | 31.22 251 | 15.89 263 | 79.18 233 |
|
test12356 | | | 49.28 238 | 48.51 238 | 51.59 248 | 62.06 253 | 19.11 266 | 60.40 254 | 72.45 242 | 47.60 247 | 40.64 252 | 65.68 244 | 13.84 254 | 68.72 251 | 27.29 254 | 46.67 253 | 66.94 248 |
|
.test1245 | | | 45.55 239 | 50.02 235 | 32.14 255 | 69.10 246 | 28.28 261 | 68.90 242 | 74.54 237 | 54.01 233 | 53.71 241 | 74.51 232 | 23.09 243 | 67.90 253 | 32.28 247 | 0.02 265 | 0.25 264 |
|
Gipuma |  | | 45.18 240 | 41.86 241 | 55.16 245 | 77.03 229 | 51.52 229 | 32.50 263 | 80.52 203 | 32.46 258 | 27.12 257 | 35.02 257 | 9.52 258 | 75.50 236 | 22.31 257 | 60.21 241 | 38.45 258 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMVS |  | 37.38 22 | 44.16 241 | 40.28 242 | 55.82 244 | 40.82 265 | 42.54 247 | 65.12 251 | 63.99 255 | 34.43 257 | 24.48 258 | 57.12 252 | 3.92 261 | 76.17 234 | 17.10 259 | 55.52 245 | 48.75 254 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
PMMVS2 | | | 40.82 242 | 38.86 243 | 46.69 251 | 53.84 258 | 16.45 267 | 48.61 260 | 49.92 260 | 37.49 254 | 31.67 255 | 60.97 249 | 8.14 260 | 56.42 258 | 28.42 253 | 30.72 255 | 67.19 247 |
|
wuykxyi23d | | | 39.76 243 | 33.18 245 | 59.51 241 | 46.98 263 | 44.01 244 | 57.70 257 | 67.74 249 | 24.13 262 | 13.98 264 | 34.33 258 | 1.27 264 | 71.33 248 | 34.23 244 | 18.23 259 | 63.18 251 |
|
PNet_i23d | | | 38.26 244 | 35.42 244 | 46.79 250 | 58.74 255 | 35.48 257 | 59.65 255 | 51.25 259 | 32.45 259 | 23.44 260 | 47.53 255 | 2.04 263 | 58.96 256 | 25.60 255 | 18.09 261 | 45.92 257 |
|
E-PMN | | | 31.77 245 | 30.64 246 | 35.15 253 | 52.87 260 | 27.67 263 | 57.09 258 | 47.86 261 | 24.64 261 | 16.40 262 | 33.05 259 | 11.23 256 | 54.90 259 | 14.46 261 | 18.15 260 | 22.87 260 |
|
EMVS | | | 30.81 246 | 29.65 247 | 34.27 254 | 50.96 261 | 25.95 265 | 56.58 259 | 46.80 262 | 24.01 263 | 15.53 263 | 30.68 260 | 12.47 255 | 54.43 260 | 12.81 262 | 17.05 262 | 22.43 261 |
|
MVE |  | 26.22 23 | 30.37 247 | 25.89 248 | 43.81 252 | 44.55 264 | 35.46 258 | 28.87 264 | 39.07 263 | 18.20 264 | 18.58 261 | 40.18 256 | 2.68 262 | 47.37 261 | 17.07 260 | 23.78 258 | 48.60 255 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
wuyk23d | | | 16.82 248 | 15.94 249 | 19.46 257 | 58.74 255 | 31.45 260 | 39.22 262 | 3.74 266 | 6.84 266 | 6.04 265 | 2.70 262 | 1.27 264 | 24.29 263 | 10.54 263 | 14.40 264 | 2.63 262 |
|
ab-mvs-re | | | 7.23 249 | 9.64 250 | 0.00 260 | 0.00 269 | 0.00 271 | 0.00 265 | 0.00 269 | 0.00 269 | 0.00 268 | 86.72 136 | 0.00 268 | 0.00 266 | 0.00 266 | 0.00 268 | 0.00 266 |
|
test123 | | | 6.12 250 | 8.11 251 | 0.14 258 | 0.06 268 | 0.09 269 | 71.05 231 | 0.03 268 | 0.04 268 | 0.25 267 | 1.30 264 | 0.05 266 | 0.03 265 | 0.21 265 | 0.01 267 | 0.29 263 |
|
testmvs | | | 6.04 251 | 8.02 252 | 0.10 259 | 0.08 267 | 0.03 270 | 69.74 235 | 0.04 267 | 0.05 267 | 0.31 266 | 1.68 263 | 0.02 267 | 0.04 264 | 0.24 264 | 0.02 265 | 0.25 264 |
|
Regformer | | | 0.00 252 | 0.00 253 | 0.00 260 | 0.00 269 | 0.00 271 | 0.00 265 | 0.00 269 | 0.00 269 | 0.00 268 | 0.00 265 | 0.00 268 | 0.00 266 | 0.00 266 | 0.00 268 | 0.00 266 |
|
test_prior4 | | | | | | | 72.60 18 | 89.01 59 | | | | | | | | | |
|
test_prior2 | | | | | | | | 88.85 62 | | 75.41 60 | 84.91 18 | 93.54 20 | 74.28 11 | | 83.31 18 | 95.86 4 | |
|
test_prior | | | | | 86.33 33 | 92.61 32 | 69.59 48 | | 92.97 22 | | | | | 95.48 32 | | | 93.91 22 |
|
旧先验2 | | | | | | | | 86.56 123 | | 58.10 215 | 87.04 8 | | | 88.98 180 | 74.07 75 | | |
|
æ–°å‡ ä½•2 | | | | | | | | 86.29 130 | | | | | | | | | |
|
æ–°å‡ ä½•1 | | | | | 83.42 80 | 93.13 24 | 70.71 37 | | 85.48 163 | 57.43 221 | 81.80 45 | 91.98 40 | 63.28 73 | 92.27 123 | 64.60 140 | 92.99 32 | 87.27 177 |
|
旧先验1 | | | | | | 91.96 38 | 65.79 103 | | 86.37 155 | | | 93.08 29 | 69.31 33 | | | 92.74 35 | 88.74 141 |
|
æ— å…ˆéªŒ | | | | | | | | 87.48 98 | 88.98 120 | 60.00 205 | | | | 94.12 71 | 67.28 118 | | 88.97 136 |
|
原ACMM2 | | | | | | | | 86.86 116 | | | | | | | | | |
|
原ACMM1 | | | | | 84.35 63 | 93.01 27 | 68.79 59 | | 92.44 31 | 63.96 181 | 81.09 51 | 91.57 49 | 66.06 54 | 95.45 34 | 67.19 120 | 94.82 18 | 88.81 138 |
|
test222 | | | | | | 91.50 43 | 68.26 72 | 84.16 161 | 83.20 182 | 54.63 231 | 79.74 57 | 91.63 47 | 58.97 132 | | | 91.42 45 | 86.77 188 |
|
testdata2 | | | | | | | | | | | | | | 91.01 152 | 62.37 152 | | |
|
segment_acmp | | | | | | | | | | | | | 73.08 16 | | | | |
|
testdata | | | | | 79.97 154 | 90.90 50 | 64.21 135 | | 84.71 169 | 59.27 210 | 85.40 14 | 92.91 30 | 62.02 106 | 89.08 177 | 68.95 108 | 91.37 46 | 86.63 192 |
|
testdata1 | | | | | | | | 84.14 162 | | 75.71 56 | | | | | | | |
|
test12 | | | | | 86.80 26 | 92.63 31 | 70.70 38 | | 91.79 51 | | 82.71 41 | | 71.67 23 | 96.16 21 | | 94.50 21 | 93.54 36 |
|
plane_prior7 | | | | | | 90.08 60 | 68.51 69 | | | | | | | | | | |
|
plane_prior6 | | | | | | 89.84 64 | 68.70 66 | | | | | | 60.42 126 | | | | |
|
plane_prior5 | | | | | | | | | 92.44 31 | | | | | 95.38 36 | 78.71 43 | 86.32 88 | 91.33 74 |
|
plane_prior4 | | | | | | | | | | | | 91.00 58 | | | | | |
|
plane_prior3 | | | | | | | 68.60 68 | | | 78.44 24 | 78.92 66 | | | | | | |
|
plane_prior2 | | | | | | | | 91.25 24 | | 79.12 17 | | | | | | | |
|
plane_prior1 | | | | | | 89.90 63 | | | | | | | | | | | |
|
plane_prior | | | | | | | 68.71 64 | 90.38 36 | | 77.62 28 | | | | | | 86.16 90 | |
|
n2 | | | | | | | | | 0.00 269 | | | | | | | | |
|
nn | | | | | | | | | 0.00 269 | | | | | | | | |
|
door-mid | | | | | | | | | 69.98 245 | | | | | | | | |
|
lessismore_v0 | | | | | 78.97 168 | 81.01 208 | 57.15 196 | | 65.99 251 | | 61.16 225 | 82.82 182 | 39.12 222 | 91.34 141 | 59.67 171 | 46.92 252 | 88.43 157 |
|
LGP-MVS_train | | | | | 84.50 58 | 89.23 78 | 68.76 61 | | 91.94 47 | 75.37 62 | 76.64 107 | 91.51 50 | 54.29 154 | 94.91 49 | 78.44 45 | 83.78 104 | 89.83 120 |
|
test11 | | | | | | | | | 92.23 37 | | | | | | | | |
|
door | | | | | | | | | 69.44 247 | | | | | | | | |
|
HQP5-MVS | | | | | | | 66.98 89 | | | | | | | | | | |
|
HQP-NCC | | | | | | 89.33 70 | | 89.17 53 | | 76.41 47 | 77.23 97 | | | | | | |
|
ACMP_Plane | | | | | | 89.33 70 | | 89.17 53 | | 76.41 47 | 77.23 97 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.47 51 | | |
|
HQP4-MVS | | | | | | | | | | | 77.24 96 | | | 95.11 42 | | | 91.03 79 |
|
HQP3-MVS | | | | | | | | | 92.19 40 | | | | | | | 85.99 92 | |
|
HQP2-MVS | | | | | | | | | | | | | 60.17 129 | | | | |
|
NP-MVS | | | | | | 89.62 65 | 68.32 71 | | | | | 90.24 67 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 37.79 255 | 75.16 221 | | 55.10 229 | 66.53 207 | | 49.34 180 | | 53.98 199 | | 87.94 165 |
|
MDTV_nov1_ep13 | | | | 69.97 187 | | 83.18 182 | 53.48 222 | 77.10 211 | 80.18 209 | 60.45 200 | 69.33 184 | 80.44 208 | 48.89 184 | 86.90 192 | 51.60 208 | 78.51 145 | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 81.95 119 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 81.25 124 | |
|
Test By Simon | | | | | | | | | | | | | 64.33 65 | | | | |
|
ITE_SJBPF | | | | | 78.22 177 | 81.77 200 | 60.57 168 | | 83.30 181 | 69.25 136 | 67.54 199 | 87.20 131 | 36.33 231 | 87.28 191 | 54.34 198 | 74.62 186 | 86.80 187 |
|
DeepMVS_CX |  | | | | 27.40 256 | 40.17 266 | 26.90 264 | | 24.59 264 | 17.44 265 | 23.95 259 | 48.61 254 | 9.77 257 | 26.48 262 | 18.06 258 | 24.47 257 | 28.83 259 |
|