CNVR-MVS-fine | | | 88.93 1 | 89.13 1 | 88.33 2 | 94.77 1 | 73.82 2 | 90.51 22 | 93.00 13 | 80.90 3 | 88.06 4 | 94.06 7 | 76.43 2 | 96.84 4 | 88.48 1 | 95.99 1 | 94.34 6 |
|
SteuartSystems-ACMMP | | | 88.72 2 | 88.86 2 | 88.32 3 | 92.14 20 | 72.96 5 | 93.73 2 | 93.67 4 | 80.19 6 | 88.10 3 | 94.80 1 | 73.76 6 | 97.11 1 | 87.51 2 | 95.82 3 | 94.90 3 |
Skip Steuart: Steuart Systems R&D Blog. |
DeepPCF-MVS | | 80.84 1 | 88.10 3 | 88.56 3 | 86.73 16 | 92.24 19 | 69.03 32 | 89.57 33 | 93.39 8 | 77.53 21 | 89.79 1 | 94.12 5 | 78.98 1 | 96.58 7 | 85.66 3 | 95.72 4 | 94.58 4 |
|
NCCC | | | 88.06 4 | 88.01 4 | 88.24 4 | 94.41 3 | 73.62 3 | 91.22 16 | 92.83 14 | 81.50 1 | 85.79 6 | 93.47 11 | 73.02 8 | 97.00 3 | 84.90 5 | 94.94 9 | 94.10 11 |
|
APD-MVS | | | 87.44 5 | 87.52 5 | 87.19 11 | 94.24 4 | 72.39 11 | 91.86 10 | 92.83 14 | 73.01 51 | 88.58 2 | 94.52 2 | 73.36 7 | 96.49 8 | 84.26 7 | 95.01 8 | 92.70 26 |
|
HPM-MVS | | | 87.11 6 | 86.98 6 | 87.50 8 | 93.88 7 | 72.16 14 | 92.19 7 | 93.33 9 | 76.07 34 | 83.81 10 | 93.95 8 | 69.77 18 | 96.01 14 | 85.15 4 | 94.66 10 | 94.32 7 |
|
CP-MVS | | | 87.11 6 | 86.92 7 | 87.68 7 | 94.20 5 | 73.86 1 | 93.98 1 | 92.82 16 | 76.62 26 | 83.68 11 | 94.46 3 | 67.93 23 | 95.95 15 | 84.20 8 | 94.39 12 | 93.23 21 |
|
DeepC-MVS | | 79.81 2 | 87.08 8 | 86.88 8 | 87.69 6 | 91.16 25 | 72.32 13 | 90.31 26 | 93.94 2 | 77.12 23 | 82.82 14 | 94.23 4 | 72.13 10 | 97.09 2 | 84.83 6 | 95.37 6 | 93.65 13 |
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 9 | 86.62 9 | 87.76 5 | 93.52 10 | 72.37 12 | 91.26 13 | 93.04 11 | 76.62 26 | 84.22 9 | 93.36 13 | 71.44 14 | 96.76 5 | 80.82 15 | 95.33 7 | 94.16 9 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
PHI-MVS | | | 86.43 10 | 86.17 11 | 87.24 10 | 90.88 28 | 70.96 19 | 92.27 6 | 94.07 1 | 72.45 53 | 85.22 7 | 91.90 21 | 69.47 19 | 96.42 9 | 83.28 9 | 95.94 2 | 94.35 5 |
|
CSCG | | | 86.41 11 | 86.19 10 | 87.07 13 | 92.91 15 | 72.48 10 | 90.81 19 | 93.56 5 | 73.95 45 | 83.16 13 | 91.07 31 | 75.94 3 | 95.19 24 | 79.94 18 | 94.38 13 | 93.55 16 |
|
ACMMP |  | | 85.89 12 | 85.39 12 | 87.38 9 | 93.59 9 | 72.63 8 | 92.74 4 | 93.18 10 | 76.78 25 | 80.73 23 | 93.82 9 | 64.33 42 | 96.29 10 | 82.67 10 | 90.69 29 | 93.23 21 |
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 13 | 85.29 15 | 87.17 12 | 93.49 11 | 71.08 17 | 88.58 46 | 92.42 20 | 68.32 86 | 84.61 8 | 93.48 10 | 72.32 9 | 96.15 12 | 79.00 19 | 95.43 5 | 94.28 8 |
|
TSAR-MVS | | | 85.71 14 | 85.33 13 | 86.84 14 | 91.34 23 | 72.50 9 | 89.07 40 | 87.28 87 | 76.41 28 | 85.80 5 | 90.22 44 | 74.15 5 | 95.37 23 | 81.82 11 | 91.88 21 | 92.65 28 |
|
3Dnovator+ | | 77.84 4 | 85.48 15 | 84.47 18 | 88.51 1 | 91.08 26 | 73.49 4 | 93.18 3 | 93.78 3 | 80.79 4 | 76.66 63 | 93.37 12 | 60.40 73 | 96.75 6 | 77.20 31 | 93.73 16 | 95.29 1 |
|
DELS-MVS | | | 85.41 16 | 85.30 14 | 85.77 22 | 88.49 64 | 67.93 51 | 85.52 86 | 93.44 6 | 78.70 15 | 83.63 12 | 89.03 59 | 74.57 4 | 95.71 17 | 80.26 17 | 94.04 14 | 93.66 12 |
|
HPM-MVS_fast | | | 85.35 17 | 84.95 16 | 86.57 18 | 93.69 8 | 70.58 23 | 92.15 8 | 91.62 39 | 73.89 46 | 82.67 16 | 94.09 6 | 62.60 51 | 95.54 19 | 80.93 13 | 92.93 17 | 93.57 15 |
|
MVS_111021_HR | | | 85.14 18 | 84.75 17 | 86.32 19 | 91.65 22 | 72.70 7 | 85.98 78 | 90.33 57 | 76.11 33 | 82.08 17 | 91.61 25 | 71.36 15 | 94.17 48 | 81.02 12 | 92.58 19 | 92.08 38 |
|
CPTT-MVS | | | 83.73 19 | 83.33 20 | 84.92 30 | 93.28 13 | 70.86 21 | 92.09 9 | 90.38 54 | 68.75 83 | 79.57 26 | 92.83 15 | 60.60 70 | 93.04 68 | 80.92 14 | 91.56 25 | 90.86 58 |
|
EPNet | | | 83.72 20 | 82.92 23 | 86.14 21 | 84.22 112 | 69.48 30 | 91.05 18 | 85.27 104 | 81.30 2 | 76.83 60 | 91.65 23 | 66.09 33 | 95.56 18 | 76.00 34 | 93.85 15 | 93.38 19 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
HQP_MVS | | | 83.64 21 | 83.14 21 | 85.14 26 | 90.08 35 | 68.71 41 | 91.25 14 | 92.44 18 | 79.12 9 | 78.92 32 | 91.00 34 | 60.42 71 | 95.38 21 | 78.71 22 | 86.32 56 | 91.33 50 |
|
Vis-MVSNet |  | | 83.46 22 | 82.80 25 | 85.43 23 | 90.25 33 | 68.74 40 | 90.30 27 | 90.13 58 | 76.33 32 | 80.87 22 | 92.89 14 | 61.00 67 | 94.20 47 | 72.45 44 | 90.97 27 | 93.35 20 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
MG-MVS | | | 83.41 23 | 83.45 19 | 83.28 55 | 92.74 16 | 62.28 102 | 88.17 54 | 89.50 61 | 75.22 38 | 81.49 18 | 92.74 17 | 66.75 29 | 95.11 26 | 72.85 41 | 91.58 24 | 92.45 29 |
|
EPP-MVSNet | | | 83.40 24 | 83.02 22 | 84.57 35 | 90.13 34 | 64.47 81 | 92.32 5 | 90.73 51 | 74.45 42 | 79.35 28 | 91.10 29 | 69.05 20 | 95.12 25 | 72.78 42 | 87.22 46 | 94.13 10 |
|
3Dnovator | | 76.31 5 | 83.38 25 | 82.31 27 | 86.59 17 | 87.94 75 | 72.94 6 | 90.64 20 | 92.14 28 | 77.21 22 | 75.47 74 | 92.83 15 | 58.56 76 | 94.72 38 | 73.24 40 | 92.71 18 | 92.13 37 |
|
IS-MVSNet | | | 83.15 26 | 82.81 24 | 84.18 44 | 89.94 37 | 63.30 91 | 91.59 11 | 88.46 78 | 79.04 11 | 79.49 27 | 92.16 18 | 65.10 39 | 94.28 44 | 67.71 59 | 91.86 22 | 94.95 2 |
|
DP-MVS Recon | | | 83.11 27 | 82.09 29 | 86.15 20 | 94.44 2 | 70.92 20 | 88.79 43 | 92.20 25 | 70.53 66 | 79.17 29 | 91.03 33 | 64.12 44 | 96.03 13 | 68.39 57 | 90.14 33 | 91.50 49 |
|
PAPM_NR | | | 83.02 28 | 82.41 26 | 84.82 32 | 92.47 18 | 66.37 64 | 87.93 57 | 91.80 35 | 73.82 47 | 77.32 52 | 90.66 38 | 67.90 24 | 94.90 34 | 70.37 48 | 89.48 37 | 93.19 23 |
|
MVSFormer | | | 82.85 29 | 82.05 30 | 85.24 25 | 87.35 88 | 70.21 24 | 90.50 23 | 90.38 54 | 68.55 84 | 81.32 19 | 89.47 51 | 61.68 58 | 93.46 57 | 78.98 20 | 90.26 31 | 92.05 39 |
|
OMC-MVS | | | 82.69 30 | 81.97 32 | 84.85 31 | 88.75 58 | 67.42 55 | 87.98 56 | 90.87 50 | 74.92 39 | 79.72 25 | 91.65 23 | 62.19 57 | 93.96 49 | 75.26 36 | 86.42 55 | 93.16 24 |
|
PVSNet_Blended_VisFu | | | 82.62 31 | 81.83 33 | 84.96 29 | 90.80 29 | 69.76 29 | 88.74 44 | 91.70 38 | 69.39 77 | 78.96 31 | 88.46 69 | 65.47 36 | 94.87 36 | 74.42 38 | 88.57 40 | 90.24 68 |
|
MVS_111021_LR | | | 82.61 32 | 82.11 28 | 84.11 45 | 88.82 56 | 71.58 15 | 85.15 87 | 86.16 99 | 74.69 40 | 80.47 24 | 91.04 32 | 62.29 55 | 90.55 103 | 80.33 16 | 90.08 34 | 90.20 69 |
|
HQP-MVS | | | 82.61 32 | 82.02 31 | 84.37 39 | 89.33 44 | 66.98 60 | 89.17 36 | 92.19 26 | 76.41 28 | 77.23 55 | 90.23 43 | 60.17 74 | 95.11 26 | 77.47 29 | 85.99 60 | 91.03 52 |
|
CLD-MVS | | | 82.31 34 | 81.65 34 | 84.29 41 | 88.47 65 | 67.73 54 | 85.81 83 | 92.35 23 | 75.78 35 | 78.33 40 | 86.58 101 | 64.01 45 | 94.35 43 | 76.05 33 | 87.48 44 | 90.79 59 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
LPG-MVS_test | | | 82.08 35 | 81.27 36 | 84.50 37 | 89.23 50 | 68.76 38 | 90.22 28 | 91.94 32 | 75.37 36 | 76.64 65 | 91.51 26 | 54.29 94 | 94.91 32 | 78.44 24 | 83.78 67 | 89.83 76 |
|
API-MVS | | | 81.99 36 | 81.23 37 | 84.26 42 | 90.94 27 | 70.18 26 | 91.10 17 | 89.32 64 | 71.51 60 | 78.66 35 | 88.28 73 | 65.26 37 | 95.10 29 | 64.74 76 | 91.23 26 | 87.51 111 |
|
UniMVSNet_NR-MVSNet | | | 81.88 37 | 81.54 35 | 82.92 63 | 88.46 66 | 63.46 86 | 87.13 63 | 92.37 21 | 80.19 6 | 78.38 38 | 89.14 55 | 71.66 12 | 93.05 66 | 70.05 50 | 76.46 114 | 92.25 32 |
|
MAR-MVS | | | 81.84 38 | 80.70 40 | 85.27 24 | 91.32 24 | 71.53 16 | 89.82 31 | 90.92 49 | 69.77 73 | 78.50 37 | 86.21 104 | 62.36 54 | 94.52 42 | 65.36 71 | 92.05 20 | 89.77 78 |
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020 |
PAPR | | | 81.66 39 | 80.89 39 | 83.99 48 | 90.27 32 | 64.00 84 | 86.76 71 | 91.77 37 | 68.84 82 | 77.13 59 | 89.50 50 | 67.63 25 | 94.88 35 | 67.55 60 | 88.52 41 | 93.09 25 |
|
UniMVSNet (Re) | | | 81.60 40 | 81.11 38 | 83.09 59 | 88.38 69 | 64.41 82 | 87.60 59 | 93.02 12 | 78.42 18 | 78.56 36 | 88.16 74 | 69.78 17 | 93.26 60 | 69.58 54 | 76.49 113 | 91.60 46 |
|
ACMP | | 74.13 6 | 81.51 41 | 80.57 43 | 84.36 40 | 89.42 42 | 68.69 44 | 89.97 30 | 91.50 42 | 74.46 41 | 75.04 85 | 90.41 40 | 53.82 99 | 94.54 40 | 77.56 28 | 82.91 71 | 89.86 75 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
jason | | | 81.39 42 | 80.29 47 | 84.70 34 | 86.63 94 | 69.90 28 | 85.95 79 | 86.77 92 | 63.24 122 | 81.07 21 | 89.47 51 | 61.08 66 | 92.15 83 | 78.33 27 | 90.07 35 | 92.05 39 |
jason: jason. |
lupinMVS | | | 81.39 42 | 80.27 48 | 84.76 33 | 87.35 88 | 70.21 24 | 85.55 85 | 86.41 96 | 62.85 126 | 81.32 19 | 88.61 66 | 61.68 58 | 92.24 82 | 78.41 26 | 90.26 31 | 91.83 42 |
|
CP-MVSNet | | | 81.18 44 | 80.70 40 | 82.64 69 | 88.46 66 | 63.34 88 | 87.13 63 | 92.37 21 | 79.01 12 | 77.93 45 | 87.97 76 | 71.66 12 | 92.81 71 | 66.08 66 | 75.65 123 | 91.77 44 |
|
WR-MVS_H | | | 81.16 45 | 80.66 42 | 82.66 68 | 88.05 72 | 63.32 90 | 87.38 62 | 92.62 17 | 78.53 16 | 77.54 51 | 88.08 75 | 70.13 16 | 93.00 69 | 67.79 58 | 75.81 121 | 91.65 45 |
|
DU-MVS | | | 81.12 46 | 80.52 44 | 82.90 64 | 87.80 77 | 63.46 86 | 87.02 65 | 91.87 34 | 79.01 12 | 78.38 38 | 89.07 57 | 65.02 40 | 93.05 66 | 70.05 50 | 76.46 114 | 92.20 34 |
|
PVSNet_Blended | | | 80.98 47 | 80.34 45 | 82.90 64 | 88.85 54 | 65.40 72 | 84.43 94 | 92.00 29 | 67.62 89 | 78.11 42 | 85.05 112 | 66.02 34 | 94.27 45 | 71.52 45 | 89.50 36 | 89.01 85 |
|
QAPM | | | 80.88 48 | 79.50 55 | 85.03 27 | 88.01 74 | 68.97 35 | 91.59 11 | 92.00 29 | 66.63 96 | 75.15 83 | 92.16 18 | 57.70 78 | 95.45 20 | 63.52 77 | 88.76 39 | 90.66 61 |
|
TranMVSNet+NR-MVSNet | | | 80.84 49 | 80.31 46 | 82.42 71 | 87.85 76 | 62.33 101 | 87.74 58 | 91.33 44 | 80.55 5 | 77.99 44 | 89.86 45 | 65.23 38 | 92.62 73 | 67.05 64 | 75.24 129 | 92.30 30 |
|
UGNet | | | 80.83 50 | 79.59 53 | 84.54 36 | 88.04 73 | 68.09 50 | 89.42 34 | 88.16 79 | 76.95 24 | 76.22 68 | 89.46 53 | 49.30 118 | 93.94 51 | 68.48 56 | 90.31 30 | 91.60 46 |
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 51 | 79.76 52 | 83.96 50 | 85.60 102 | 68.78 37 | 83.54 103 | 90.50 52 | 70.66 65 | 76.71 62 | 91.66 22 | 60.69 69 | 91.26 90 | 76.94 32 | 81.58 83 | 91.83 42 |
|
DTE-MVSNet | | | 80.80 52 | 80.26 49 | 82.41 72 | 87.68 81 | 62.36 99 | 86.78 68 | 91.09 46 | 80.19 6 | 77.82 47 | 89.14 55 | 67.20 27 | 92.61 74 | 67.14 62 | 75.33 126 | 92.25 32 |
|
ACMM | | 73.20 8 | 80.78 53 | 79.84 51 | 83.58 51 | 89.31 47 | 68.37 47 | 89.99 29 | 91.60 40 | 70.28 69 | 77.25 53 | 89.66 48 | 53.37 102 | 93.53 56 | 74.24 39 | 82.85 72 | 88.85 88 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
114514_t | | | 80.68 54 | 79.51 54 | 84.20 43 | 94.09 6 | 67.27 59 | 89.64 32 | 91.11 45 | 58.75 147 | 74.08 90 | 90.72 37 | 58.10 77 | 95.04 31 | 69.70 53 | 89.42 38 | 90.30 67 |
|
PVSNet_BlendedMVS | | | 80.60 55 | 80.02 50 | 82.36 74 | 88.85 54 | 65.40 72 | 86.16 76 | 92.00 29 | 69.34 78 | 78.11 42 | 86.09 105 | 66.02 34 | 94.27 45 | 71.52 45 | 82.06 78 | 87.39 113 |
|
AdaColmap |  | | 80.58 56 | 79.42 56 | 84.06 47 | 93.09 14 | 68.91 36 | 89.36 35 | 88.97 74 | 69.27 79 | 75.70 73 | 89.69 47 | 57.20 81 | 95.77 16 | 63.06 80 | 88.41 42 | 87.50 112 |
|
XVG-OURS | | | 80.41 57 | 79.23 60 | 83.97 49 | 85.64 101 | 69.02 33 | 83.03 106 | 90.39 53 | 71.09 62 | 77.63 50 | 91.49 28 | 54.62 93 | 91.35 88 | 75.71 35 | 83.47 69 | 91.54 48 |
|
PCF-MVS | | 73.52 7 | 80.38 58 | 78.84 64 | 85.01 28 | 87.71 80 | 68.99 34 | 83.65 100 | 91.46 43 | 63.00 124 | 77.77 49 | 90.28 41 | 66.10 32 | 95.09 30 | 61.40 92 | 88.22 43 | 90.94 57 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
test_djsdf | | | 80.30 59 | 79.32 59 | 83.27 56 | 83.98 113 | 65.37 74 | 90.50 23 | 90.38 54 | 68.55 84 | 76.19 69 | 88.70 64 | 56.44 83 | 93.46 57 | 78.98 20 | 80.14 94 | 90.97 56 |
|
NR-MVSNet | | | 80.23 60 | 79.38 57 | 82.78 67 | 87.80 77 | 63.34 88 | 86.31 74 | 91.09 46 | 79.01 12 | 72.17 101 | 89.07 57 | 67.20 27 | 92.81 71 | 66.08 66 | 75.65 123 | 92.20 34 |
|
IterMVS-LS | | | 80.06 61 | 79.38 57 | 82.11 75 | 85.89 97 | 63.20 93 | 86.79 67 | 89.34 63 | 74.19 43 | 75.45 75 | 86.72 95 | 66.62 30 | 92.39 80 | 72.58 43 | 76.86 111 | 90.75 60 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
OpenMVS |  | 72.83 10 | 79.77 62 | 78.33 69 | 84.09 46 | 85.17 104 | 69.91 27 | 90.57 21 | 90.97 48 | 66.70 95 | 72.17 101 | 91.91 20 | 54.70 91 | 93.96 49 | 61.81 90 | 90.95 28 | 88.41 97 |
|
BH-RMVSNet | | | 79.61 63 | 78.44 68 | 83.14 58 | 89.38 43 | 65.93 67 | 84.95 89 | 87.15 88 | 73.56 50 | 78.19 41 | 89.79 46 | 56.67 82 | 93.36 59 | 59.53 106 | 86.74 52 | 90.13 70 |
|
WR-MVS | | | 79.51 64 | 79.04 62 | 80.90 90 | 87.47 87 | 59.41 119 | 88.85 42 | 93.40 7 | 77.81 19 | 73.66 91 | 88.97 60 | 67.25 26 | 92.27 81 | 60.28 101 | 73.71 137 | 91.01 55 |
|
ab-mvs | | | 79.51 64 | 78.97 63 | 81.14 88 | 88.46 66 | 60.91 107 | 83.84 98 | 89.24 68 | 70.36 68 | 79.03 30 | 88.87 62 | 63.23 48 | 90.21 105 | 65.12 72 | 82.57 76 | 92.28 31 |
|
BH-untuned | | | 79.47 66 | 78.60 66 | 82.05 76 | 89.19 52 | 65.91 68 | 86.07 77 | 88.52 77 | 72.18 54 | 75.42 76 | 87.69 80 | 61.15 65 | 93.54 55 | 60.38 99 | 86.83 51 | 86.70 126 |
|
mvs_anonymous | | | 79.42 67 | 79.11 61 | 80.34 96 | 84.45 111 | 57.97 126 | 82.59 107 | 87.62 84 | 67.40 93 | 76.17 71 | 88.56 68 | 68.47 21 | 89.59 112 | 70.65 47 | 86.05 59 | 93.47 18 |
|
TAPA-MVS | | 73.13 9 | 79.15 68 | 77.94 72 | 82.79 66 | 89.59 41 | 62.99 97 | 88.16 55 | 91.51 41 | 65.77 102 | 77.14 58 | 91.09 30 | 60.91 68 | 93.21 61 | 50.26 141 | 87.05 49 | 92.17 36 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
CDS-MVSNet | | | 79.07 69 | 77.70 74 | 83.17 57 | 87.60 82 | 68.23 49 | 84.40 95 | 86.20 98 | 67.49 91 | 76.36 67 | 86.54 102 | 61.54 60 | 90.79 102 | 61.86 89 | 87.33 45 | 90.49 63 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
MVSTER | | | 79.01 70 | 77.88 73 | 82.38 73 | 83.07 122 | 64.80 79 | 84.08 97 | 88.95 75 | 69.01 81 | 78.69 34 | 87.17 92 | 54.70 91 | 92.43 79 | 74.69 37 | 80.57 90 | 89.89 74 |
|
TAMVS | | | 78.89 71 | 77.51 75 | 83.03 61 | 87.80 77 | 67.79 53 | 84.72 92 | 85.05 107 | 67.63 88 | 76.75 61 | 87.70 79 | 62.25 56 | 90.82 101 | 58.53 111 | 87.13 48 | 90.49 63 |
|
diffmvs | | | 78.78 72 | 78.64 65 | 79.22 107 | 84.48 110 | 56.11 147 | 82.12 113 | 87.53 86 | 65.53 105 | 76.66 63 | 88.73 63 | 68.25 22 | 87.97 121 | 68.73 55 | 85.70 63 | 93.59 14 |
|
MVS_Test | | | 78.49 73 | 78.26 71 | 79.18 111 | 83.29 118 | 56.48 140 | 82.45 108 | 86.59 94 | 66.73 94 | 76.13 72 | 88.46 69 | 66.33 31 | 89.04 116 | 70.30 49 | 84.06 66 | 92.01 41 |
|
GBi-Net | | | 78.40 74 | 77.40 76 | 81.40 83 | 87.60 82 | 63.01 94 | 88.39 49 | 89.28 65 | 71.63 57 | 75.34 78 | 87.28 87 | 54.80 88 | 91.11 93 | 62.72 81 | 79.57 95 | 90.09 71 |
|
test1 | | | 78.40 74 | 77.40 76 | 81.40 83 | 87.60 82 | 63.01 94 | 88.39 49 | 89.28 65 | 71.63 57 | 75.34 78 | 87.28 87 | 54.80 88 | 91.11 93 | 62.72 81 | 79.57 95 | 90.09 71 |
|
Vis-MVSNet (Re-imp) | | | 78.36 76 | 78.45 67 | 78.07 119 | 88.64 60 | 51.78 157 | 86.70 72 | 79.63 142 | 74.14 44 | 75.11 84 | 90.83 36 | 61.29 64 | 89.75 111 | 58.10 115 | 91.60 23 | 92.69 27 |
|
BH-w/o | | | 78.21 77 | 77.33 78 | 80.84 91 | 88.81 57 | 65.13 78 | 84.87 90 | 87.85 81 | 69.75 74 | 74.52 88 | 84.74 114 | 61.34 62 | 93.11 65 | 58.24 114 | 85.84 62 | 84.27 139 |
|
FMVSNet2 | | | 78.20 78 | 77.21 79 | 81.20 86 | 87.60 82 | 62.89 98 | 87.47 61 | 89.02 72 | 71.63 57 | 75.29 82 | 87.28 87 | 54.80 88 | 91.10 96 | 62.38 85 | 79.38 98 | 89.61 80 |
|
Baseline_NR-MVSNet | | | 78.15 79 | 78.33 69 | 77.61 122 | 85.79 98 | 56.21 145 | 86.78 68 | 85.76 102 | 73.60 48 | 77.93 45 | 87.57 83 | 65.02 40 | 88.99 117 | 67.14 62 | 75.33 126 | 87.63 108 |
|
CNLPA | | | 78.08 80 | 76.79 82 | 81.97 78 | 90.40 31 | 71.07 18 | 87.59 60 | 84.55 108 | 66.03 101 | 72.38 100 | 89.64 49 | 57.56 79 | 86.04 132 | 59.61 104 | 83.35 70 | 88.79 89 |
|
PLC |  | 70.83 11 | 78.05 81 | 76.37 85 | 83.08 60 | 91.88 21 | 67.80 52 | 88.19 53 | 89.46 62 | 64.33 116 | 69.87 120 | 88.38 71 | 53.66 101 | 93.58 54 | 58.86 109 | 82.73 74 | 87.86 105 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
HY-MVS | | 69.67 12 | 77.95 82 | 77.15 80 | 80.36 95 | 87.57 86 | 60.21 112 | 83.37 105 | 87.78 82 | 66.11 99 | 75.37 77 | 87.06 94 | 63.27 46 | 90.48 104 | 61.38 93 | 82.43 77 | 90.40 66 |
|
FMVSNet3 | | | 77.88 83 | 76.85 81 | 80.97 89 | 86.84 92 | 62.36 99 | 86.52 73 | 88.77 76 | 71.13 61 | 75.34 78 | 86.66 100 | 54.07 97 | 91.10 96 | 62.72 81 | 79.57 95 | 89.45 81 |
|
PAPM | | | 77.68 84 | 76.40 84 | 81.51 81 | 87.29 90 | 61.85 104 | 83.78 99 | 89.59 60 | 64.74 111 | 71.23 109 | 88.70 64 | 62.59 52 | 93.66 53 | 52.66 135 | 87.03 50 | 89.01 85 |
|
FMVSNet1 | | | 77.44 85 | 76.12 87 | 81.40 83 | 86.81 93 | 63.01 94 | 88.39 49 | 89.28 65 | 70.49 67 | 74.39 89 | 87.28 87 | 49.06 120 | 91.11 93 | 60.91 96 | 78.52 100 | 90.09 71 |
|
TR-MVS | | | 77.44 85 | 76.18 86 | 81.20 86 | 88.24 70 | 63.24 92 | 84.61 93 | 86.40 97 | 67.55 90 | 77.81 48 | 86.48 103 | 54.10 96 | 93.15 64 | 57.75 116 | 82.72 75 | 87.20 116 |
|
1112_ss | | | 77.40 87 | 76.43 83 | 80.32 97 | 89.11 53 | 60.41 111 | 83.65 100 | 87.72 83 | 62.13 131 | 73.05 93 | 86.72 95 | 62.58 53 | 89.97 109 | 62.11 87 | 80.80 88 | 90.59 62 |
|
LS3D | | | 76.95 88 | 74.82 92 | 83.37 53 | 90.45 30 | 67.36 58 | 89.15 39 | 86.94 91 | 61.87 133 | 69.52 122 | 90.61 39 | 51.71 110 | 94.53 41 | 46.38 154 | 86.71 53 | 88.21 100 |
|
DP-MVS | | | 76.78 89 | 74.57 94 | 83.42 52 | 93.29 12 | 69.46 31 | 88.55 47 | 83.70 114 | 63.98 120 | 70.20 115 | 88.89 61 | 54.01 98 | 94.80 37 | 46.66 151 | 81.88 81 | 86.01 130 |
|
cascas | | | 76.72 90 | 74.64 93 | 82.99 62 | 85.78 100 | 65.88 69 | 82.33 111 | 89.21 69 | 60.85 137 | 72.74 95 | 81.02 136 | 47.28 122 | 93.75 52 | 67.48 61 | 85.02 64 | 89.34 82 |
|
Test_1112_low_res | | | 76.40 91 | 75.44 90 | 79.27 105 | 89.28 48 | 58.09 125 | 81.69 115 | 87.07 89 | 59.53 144 | 72.48 99 | 86.67 99 | 61.30 63 | 89.33 114 | 60.81 98 | 80.15 93 | 90.41 65 |
|
F-COLMAP | | | 76.38 92 | 74.33 97 | 82.50 70 | 89.28 48 | 66.95 62 | 88.41 48 | 89.03 71 | 64.05 118 | 66.83 134 | 88.61 66 | 46.78 124 | 92.89 70 | 57.48 117 | 78.55 99 | 87.67 107 |
|
LTVRE_ROB | | 69.57 13 | 76.25 93 | 74.54 96 | 81.41 82 | 88.60 61 | 64.38 83 | 79.24 130 | 89.12 70 | 70.76 64 | 69.79 121 | 87.86 77 | 49.09 119 | 93.20 62 | 56.21 124 | 80.16 92 | 86.65 127 |
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 94 | 74.27 98 | 81.62 80 | 83.20 119 | 64.67 80 | 83.60 102 | 89.75 59 | 69.75 74 | 71.85 104 | 87.09 93 | 32.78 160 | 92.11 84 | 69.99 52 | 80.43 91 | 88.09 102 |
|
ACMH+ | | 68.96 14 | 76.01 95 | 74.01 99 | 82.03 77 | 88.60 61 | 65.31 75 | 88.86 41 | 87.55 85 | 70.25 70 | 67.75 129 | 87.47 85 | 41.27 144 | 93.19 63 | 58.37 112 | 75.94 119 | 87.60 110 |
|
ACMH | | 67.68 16 | 75.89 96 | 73.93 100 | 81.77 79 | 88.71 59 | 66.61 63 | 88.62 45 | 89.01 73 | 69.81 72 | 66.78 135 | 86.70 98 | 41.95 143 | 91.51 87 | 55.64 125 | 78.14 104 | 87.17 117 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
IB-MVS | | 68.01 15 | 75.85 97 | 73.36 105 | 83.31 54 | 84.76 107 | 66.03 65 | 83.38 104 | 85.06 106 | 70.21 71 | 69.40 123 | 81.05 135 | 45.76 129 | 94.66 39 | 65.10 73 | 75.49 125 | 89.25 83 |
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 98 | 75.68 88 | 75.57 134 | 86.40 95 | 56.82 135 | 77.92 136 | 82.40 124 | 65.10 110 | 76.18 70 | 87.72 78 | 63.13 49 | 80.90 149 | 60.31 100 | 81.96 79 | 89.00 87 |
|
EPNet_dtu | | | 75.46 99 | 74.86 91 | 77.23 125 | 82.57 131 | 54.60 151 | 86.89 66 | 83.09 117 | 71.64 56 | 66.25 137 | 85.86 107 | 55.99 85 | 88.04 120 | 54.92 126 | 86.55 54 | 89.05 84 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
XXY-MVS | | | 75.41 100 | 75.56 89 | 74.96 136 | 83.59 115 | 57.82 129 | 80.59 123 | 83.87 113 | 66.54 97 | 74.93 86 | 88.31 72 | 63.24 47 | 80.09 152 | 62.16 86 | 76.85 112 | 86.97 122 |
|
TransMVSNet (Re) | | | 75.39 101 | 74.56 95 | 77.86 120 | 85.50 103 | 57.10 134 | 86.78 68 | 86.09 101 | 72.17 55 | 71.53 108 | 87.34 86 | 63.01 50 | 89.31 115 | 56.84 121 | 61.83 157 | 87.17 117 |
|
CostFormer | | | 75.24 102 | 73.90 101 | 79.27 105 | 82.65 130 | 58.27 124 | 80.80 119 | 82.73 121 | 61.57 134 | 75.33 81 | 83.13 120 | 55.52 86 | 91.07 99 | 64.98 75 | 78.34 103 | 88.45 95 |
|
PT_06_test | | | 75.20 103 | 73.77 103 | 79.49 104 | 82.69 129 | 60.19 113 | 82.34 109 | 86.99 90 | 69.71 76 | 72.52 98 | 78.31 147 | 56.27 84 | 90.07 108 | 62.03 88 | 73.11 138 | 88.23 98 |
|
PEN-MVS | | | 74.79 104 | 73.85 102 | 77.61 122 | 85.79 98 | 56.21 145 | 86.31 74 | 85.76 102 | 73.60 48 | 72.17 101 | 87.57 83 | 61.36 61 | 88.99 117 | 58.98 108 | 53.14 167 | 87.63 108 |
|
PatchFormer-LS_test | | | 74.50 105 | 73.05 106 | 78.86 113 | 82.95 125 | 59.55 118 | 81.65 116 | 82.30 126 | 67.44 92 | 71.62 107 | 78.15 150 | 52.34 105 | 88.92 119 | 65.05 74 | 75.90 120 | 88.12 101 |
|
IterMVS | | | 74.29 106 | 72.94 107 | 78.35 117 | 81.53 139 | 63.49 85 | 81.58 117 | 82.49 122 | 68.06 87 | 69.99 119 | 83.69 117 | 51.66 111 | 85.54 134 | 65.85 68 | 71.64 143 | 86.01 130 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
OurMVSNet-221017-0 | | | 74.26 107 | 72.42 108 | 79.80 100 | 83.76 114 | 59.59 116 | 85.92 81 | 86.64 93 | 66.39 98 | 66.96 133 | 87.58 82 | 39.46 148 | 91.60 86 | 65.76 69 | 69.27 147 | 88.22 99 |
|
EG-PatchMatch MVS | | | 74.04 108 | 71.82 112 | 80.71 93 | 84.92 106 | 67.42 55 | 85.86 82 | 88.08 80 | 66.04 100 | 64.22 145 | 83.85 115 | 35.10 159 | 92.56 77 | 57.44 118 | 80.83 87 | 82.16 149 |
|
Test4 | | | 73.95 109 | 72.20 109 | 79.21 108 | 82.91 126 | 58.94 121 | 81.25 118 | 82.17 127 | 65.21 107 | 71.05 111 | 82.44 124 | 44.21 134 | 90.17 106 | 63.29 78 | 77.28 108 | 88.53 93 |
|
PatchFormer_test | | | 73.70 110 | 71.86 111 | 79.21 108 | 82.91 126 | 58.94 121 | 82.34 109 | 82.17 127 | 65.21 107 | 71.05 111 | 78.31 147 | 44.21 134 | 90.17 106 | 63.29 78 | 77.28 108 | 88.53 93 |
|
sss | | | 73.60 111 | 73.64 104 | 73.51 143 | 82.80 128 | 55.01 150 | 76.12 140 | 81.69 131 | 62.47 130 | 74.68 87 | 85.85 108 | 57.32 80 | 78.11 156 | 60.86 97 | 80.93 86 | 87.39 113 |
|
tpmp4_e23 | | | 73.45 112 | 71.17 119 | 80.31 98 | 83.55 116 | 59.56 117 | 81.88 114 | 82.33 125 | 57.94 151 | 70.51 114 | 81.62 131 | 51.19 114 | 91.63 85 | 53.96 130 | 77.51 107 | 89.75 79 |
|
SixPastTwentyTwo | | | 73.37 113 | 71.26 118 | 79.70 101 | 85.08 105 | 57.89 128 | 85.57 84 | 83.56 115 | 71.03 63 | 65.66 139 | 85.88 106 | 42.10 141 | 92.57 76 | 59.11 107 | 63.34 155 | 88.65 92 |
|
CR-MVSNet | | | 73.37 113 | 71.27 117 | 79.67 102 | 81.32 140 | 65.19 76 | 75.92 141 | 80.30 138 | 59.92 141 | 72.73 96 | 81.19 133 | 52.50 103 | 86.69 127 | 59.84 102 | 77.71 105 | 87.11 120 |
|
MSDG | | | 73.36 115 | 70.99 120 | 80.49 94 | 84.51 109 | 65.80 70 | 80.71 121 | 86.13 100 | 65.70 103 | 65.46 140 | 83.74 116 | 44.60 132 | 90.91 100 | 51.13 139 | 76.89 110 | 84.74 137 |
|
tpm2 | | | 73.26 116 | 71.46 114 | 78.63 114 | 83.34 117 | 56.71 137 | 80.65 122 | 80.40 137 | 56.63 155 | 73.55 92 | 82.02 129 | 51.80 109 | 91.24 91 | 56.35 123 | 78.42 102 | 87.95 103 |
|
RPSCF | | | 73.23 117 | 71.46 114 | 78.54 115 | 82.50 132 | 59.85 115 | 82.18 112 | 82.84 120 | 58.96 145 | 71.15 110 | 89.41 54 | 45.48 131 | 84.77 136 | 58.82 110 | 71.83 142 | 91.02 54 |
|
PatchmatchNet |  | | 73.12 118 | 71.33 116 | 78.49 116 | 83.18 120 | 60.85 108 | 79.63 127 | 78.57 145 | 64.13 117 | 71.73 105 | 79.81 144 | 51.20 113 | 85.97 133 | 57.40 119 | 76.36 116 | 88.66 91 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
COLMAP_ROB |  | 66.92 17 | 73.01 119 | 70.41 125 | 80.81 92 | 87.13 91 | 65.63 71 | 88.30 52 | 84.19 111 | 62.96 125 | 63.80 147 | 87.69 80 | 38.04 153 | 92.56 77 | 46.66 151 | 74.91 130 | 84.24 140 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
test_0402 | | | 72.79 120 | 70.44 124 | 79.84 99 | 88.13 71 | 65.99 66 | 85.93 80 | 84.29 110 | 65.57 104 | 67.40 131 | 85.49 109 | 46.92 123 | 92.61 74 | 35.88 165 | 74.38 133 | 80.94 151 |
|
tpmrst | | | 72.39 121 | 72.13 110 | 73.18 145 | 80.54 146 | 49.91 163 | 79.91 126 | 79.08 144 | 63.11 123 | 71.69 106 | 79.95 141 | 55.32 87 | 82.77 144 | 65.66 70 | 73.89 136 | 86.87 123 |
|
PatchMatch-RL | | | 72.38 122 | 70.90 121 | 76.80 128 | 88.60 61 | 67.38 57 | 79.53 128 | 76.17 152 | 62.75 128 | 69.36 124 | 82.00 130 | 45.51 130 | 84.89 135 | 53.62 131 | 80.58 89 | 78.12 159 |
|
tpm | | | 72.37 123 | 71.71 113 | 74.35 139 | 82.19 134 | 52.00 155 | 79.22 131 | 77.29 149 | 64.56 113 | 72.95 94 | 83.68 118 | 51.35 112 | 83.26 141 | 58.33 113 | 75.80 122 | 87.81 106 |
|
PVSNet | | 64.34 18 | 72.08 124 | 70.87 122 | 75.69 133 | 86.21 96 | 56.44 142 | 74.37 149 | 80.73 135 | 62.06 132 | 70.17 116 | 82.23 127 | 42.86 139 | 83.31 140 | 54.77 127 | 84.45 65 | 87.32 115 |
|
RPMNet | | | 71.62 125 | 68.94 130 | 79.67 102 | 81.32 140 | 65.19 76 | 75.92 141 | 78.30 148 | 57.60 152 | 72.73 96 | 76.45 157 | 52.30 106 | 86.69 127 | 48.14 148 | 77.71 105 | 87.11 120 |
|
HyFIR | | | 71.37 126 | 70.50 123 | 73.97 142 | 80.52 147 | 59.87 114 | 70.92 155 | 82.42 123 | 56.28 156 | 65.84 138 | 76.50 156 | 53.72 100 | 83.21 143 | 61.07 95 | 87.21 47 | 78.84 157 |
|
K. test v3 | | | 71.19 127 | 68.51 132 | 79.21 108 | 83.04 123 | 57.78 130 | 84.35 96 | 76.91 151 | 72.90 52 | 62.99 149 | 82.86 121 | 39.27 149 | 91.09 98 | 61.65 91 | 52.66 168 | 88.75 90 |
|
tpmvs | | | 71.09 128 | 69.29 128 | 76.49 129 | 82.04 135 | 56.04 148 | 78.92 134 | 81.37 133 | 64.05 118 | 67.18 132 | 78.28 149 | 49.74 116 | 89.77 110 | 49.67 144 | 72.37 139 | 83.67 141 |
|
Patchmtry | | | 70.74 129 | 69.16 129 | 75.49 135 | 80.72 143 | 54.07 152 | 74.94 148 | 80.30 138 | 58.34 148 | 70.01 117 | 81.19 133 | 52.50 103 | 86.54 129 | 53.37 132 | 71.09 144 | 85.87 132 |
|
MIMVSNet | | | 70.69 130 | 69.30 127 | 74.88 137 | 84.52 108 | 56.35 143 | 75.87 143 | 79.42 143 | 64.59 112 | 67.76 128 | 82.41 125 | 41.10 145 | 81.54 148 | 46.64 153 | 81.34 84 | 86.75 125 |
|
tpm cat1 | | | 70.57 131 | 68.31 134 | 77.35 124 | 82.41 133 | 57.95 127 | 78.08 135 | 80.22 140 | 52.04 161 | 68.54 127 | 77.66 153 | 52.00 108 | 87.84 123 | 51.77 136 | 72.07 141 | 86.25 129 |
|
OpenMVS_ROB |  | 64.09 19 | 70.56 132 | 68.19 135 | 77.65 121 | 80.26 148 | 59.41 119 | 85.01 88 | 82.96 119 | 58.76 146 | 65.43 141 | 82.33 126 | 37.63 155 | 91.23 92 | 45.34 157 | 76.03 118 | 82.32 147 |
|
USDC | | | 70.33 133 | 68.37 133 | 76.21 131 | 80.60 145 | 56.23 144 | 79.19 132 | 86.49 95 | 60.89 136 | 61.29 150 | 85.47 110 | 31.78 161 | 89.47 113 | 53.37 132 | 76.21 117 | 82.94 146 |
|
CMPMVS |  | 51.72 21 | 70.19 134 | 68.16 136 | 76.28 130 | 73.15 166 | 57.55 131 | 79.47 129 | 83.92 112 | 48.02 166 | 56.48 160 | 84.81 113 | 43.13 137 | 86.42 131 | 62.67 84 | 81.81 82 | 84.89 136 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
FMVSNet5 | | | 69.50 135 | 67.96 138 | 74.15 140 | 82.97 124 | 55.35 149 | 80.01 125 | 82.12 129 | 62.56 129 | 63.02 148 | 81.53 132 | 36.92 156 | 81.92 146 | 48.42 147 | 74.06 134 | 85.17 135 |
|
PMMVS | | | 69.34 136 | 68.67 131 | 71.35 152 | 75.67 160 | 62.03 103 | 75.17 144 | 73.46 160 | 50.00 164 | 68.68 126 | 79.05 145 | 52.07 107 | 78.13 155 | 61.16 94 | 82.77 73 | 73.90 162 |
|
EPMVS | | | 69.02 137 | 68.16 136 | 71.59 148 | 79.61 152 | 49.80 164 | 77.40 137 | 66.93 167 | 62.82 127 | 70.01 117 | 79.05 145 | 45.79 128 | 77.86 157 | 56.58 122 | 75.26 128 | 87.13 119 |
|
MIMVSNet1 | | | 68.58 138 | 66.78 140 | 73.98 141 | 80.07 149 | 51.82 156 | 80.77 120 | 84.37 109 | 64.40 115 | 59.75 153 | 82.16 128 | 36.47 157 | 83.63 138 | 42.73 159 | 70.33 145 | 86.48 128 |
|
PatchT | | | 68.46 139 | 67.85 139 | 70.29 154 | 80.70 144 | 43.93 169 | 72.47 152 | 74.88 156 | 60.15 140 | 70.55 113 | 76.57 155 | 49.94 115 | 81.59 147 | 50.58 140 | 74.83 131 | 85.34 134 |
|
TDRefinement | | | 67.49 140 | 64.34 144 | 76.92 126 | 73.47 165 | 61.07 106 | 84.86 91 | 82.98 118 | 59.77 142 | 58.30 156 | 85.13 111 | 26.06 163 | 87.89 122 | 47.92 149 | 60.59 160 | 81.81 150 |
|
UnsupCasMVSNet_eth | | | 67.33 141 | 65.99 141 | 71.37 150 | 73.48 164 | 51.47 159 | 75.16 145 | 85.19 105 | 65.20 109 | 60.78 152 | 80.93 138 | 42.35 140 | 77.20 159 | 57.12 120 | 53.69 166 | 85.44 133 |
|
TinyColmap | | | 67.30 142 | 64.81 143 | 74.76 138 | 81.92 136 | 56.68 138 | 80.29 124 | 81.49 132 | 60.33 139 | 56.27 161 | 83.22 119 | 24.77 164 | 87.66 124 | 45.52 156 | 69.47 146 | 79.95 154 |
|
dp | | | 66.80 143 | 65.43 142 | 70.90 153 | 79.74 150 | 48.82 167 | 75.12 147 | 74.77 157 | 59.61 143 | 64.08 146 | 77.23 154 | 42.89 138 | 80.72 150 | 48.86 146 | 66.58 150 | 83.16 142 |
|
MDA-MVSNet-bldmvs | | | 66.68 144 | 63.66 146 | 75.75 132 | 79.28 154 | 60.56 110 | 73.92 150 | 78.35 147 | 64.43 114 | 50.13 167 | 79.87 143 | 44.02 136 | 83.67 137 | 46.10 155 | 56.86 162 | 83.03 144 |
|
PM-MVS | | | 66.41 145 | 64.14 145 | 73.20 144 | 73.92 162 | 56.45 141 | 78.97 133 | 64.96 170 | 63.88 121 | 64.72 143 | 80.24 140 | 19.84 168 | 83.44 139 | 66.24 65 | 64.52 153 | 79.71 155 |
|
JIA-IIPM | | | 66.32 146 | 62.82 150 | 76.82 127 | 77.09 156 | 61.72 105 | 65.34 163 | 75.38 154 | 58.04 150 | 64.51 144 | 62.32 166 | 42.05 142 | 86.51 130 | 51.45 138 | 69.22 148 | 82.21 148 |
|
PS-CasMVS | | | 65.34 147 | 63.02 147 | 72.29 146 | 79.74 150 | 49.05 166 | 64.60 165 | 78.57 145 | 65.26 106 | 65.05 142 | 82.68 123 | 45.86 126 | 83.22 142 | 43.19 158 | 42.23 171 | 84.61 138 |
|
YYNet1 | | | 65.03 148 | 62.91 149 | 71.38 149 | 75.85 159 | 56.60 139 | 69.12 159 | 74.66 159 | 57.28 153 | 54.12 163 | 77.87 152 | 45.85 127 | 74.48 163 | 49.95 142 | 61.52 159 | 83.05 143 |
|
MDA-MVSNet_test_wron | | | 65.03 148 | 62.92 148 | 71.37 150 | 75.93 158 | 56.73 136 | 69.09 160 | 74.73 158 | 57.28 153 | 54.03 164 | 77.89 151 | 45.88 125 | 74.39 164 | 49.89 143 | 61.55 158 | 82.99 145 |
|
LF4IMVS | | | 64.02 150 | 62.19 151 | 69.50 156 | 70.90 168 | 53.29 154 | 76.13 139 | 77.18 150 | 52.65 160 | 58.59 154 | 80.98 137 | 23.55 165 | 76.52 160 | 53.06 134 | 66.66 149 | 78.68 158 |
|
UnsupCasMVSNet_bld | | | 63.70 151 | 61.53 152 | 70.21 155 | 73.69 163 | 51.39 160 | 72.82 151 | 81.89 130 | 55.63 158 | 57.81 157 | 71.80 160 | 38.67 151 | 78.61 154 | 49.26 145 | 52.21 169 | 80.63 152 |
|
PVSNet_0 | | 57.27 20 | 61.67 152 | 59.27 153 | 68.85 157 | 79.61 152 | 57.44 132 | 68.01 161 | 73.44 161 | 55.93 157 | 58.54 155 | 70.41 161 | 44.58 133 | 77.55 158 | 47.01 150 | 35.91 172 | 71.55 163 |
|
LP | | | 61.36 153 | 57.78 154 | 72.09 147 | 75.54 161 | 58.53 123 | 67.16 162 | 75.22 155 | 51.90 162 | 54.13 162 | 69.97 162 | 37.73 154 | 80.45 151 | 32.74 168 | 55.63 164 | 77.29 160 |
|
MVS-HIRNet | | | 59.14 154 | 57.67 155 | 63.57 160 | 81.65 138 | 43.50 170 | 71.73 153 | 65.06 169 | 39.59 169 | 51.43 166 | 57.73 168 | 38.34 152 | 82.58 145 | 39.53 161 | 73.95 135 | 64.62 167 |
|
DSMNet-mixed | | | 57.77 155 | 56.90 157 | 60.38 161 | 67.70 171 | 35.61 175 | 69.18 158 | 53.97 173 | 32.30 175 | 57.49 158 | 79.88 142 | 40.39 147 | 68.57 170 | 38.78 162 | 72.37 139 | 76.97 161 |
|
testpf | | | 56.51 156 | 57.58 156 | 53.30 167 | 71.99 167 | 41.19 172 | 46.89 172 | 69.32 165 | 58.06 149 | 52.87 165 | 69.45 163 | 27.99 162 | 72.73 166 | 59.59 105 | 62.07 156 | 45.98 173 |
|
FPMVS | | | 53.68 157 | 51.64 159 | 59.81 162 | 65.08 172 | 51.03 161 | 69.48 157 | 69.58 163 | 41.46 167 | 40.67 170 | 72.32 159 | 16.46 171 | 70.00 169 | 24.24 172 | 65.42 151 | 58.40 169 |
|
N_pmnet | | | 52.79 158 | 53.26 158 | 51.40 169 | 78.99 155 | 7.68 182 | 69.52 156 | 3.89 179 | 51.63 163 | 57.01 159 | 74.98 158 | 40.83 146 | 65.96 171 | 37.78 163 | 64.67 152 | 80.56 153 |
|
HyFIR lowres test | | | 51.79 159 | 50.01 161 | 57.11 164 | 68.82 169 | 49.21 165 | 60.50 167 | 53.26 174 | 34.52 171 | 43.77 169 | 64.94 165 | 20.34 167 | 71.75 167 | 39.87 160 | 64.06 154 | 50.39 170 |
|
no-one | | | 51.08 160 | 45.79 163 | 66.95 158 | 57.92 175 | 50.49 162 | 59.63 169 | 76.04 153 | 48.04 165 | 31.85 171 | 56.10 171 | 19.12 169 | 80.08 153 | 36.89 164 | 26.52 174 | 70.29 164 |
|
new_pmnet | | | 50.91 161 | 50.29 160 | 52.78 168 | 68.58 170 | 34.94 178 | 63.71 166 | 56.63 172 | 39.73 168 | 44.95 168 | 65.47 164 | 21.93 166 | 58.48 173 | 34.98 166 | 56.62 163 | 64.92 166 |
|
ANet_high | | | 50.57 162 | 46.10 162 | 63.99 159 | 48.67 177 | 39.13 173 | 70.99 154 | 80.85 134 | 61.39 135 | 31.18 173 | 57.70 169 | 17.02 170 | 73.65 165 | 31.22 169 | 15.89 179 | 79.18 156 |
|
Gipuma |  | | 45.18 163 | 41.86 164 | 55.16 166 | 77.03 157 | 51.52 158 | 32.50 174 | 80.52 136 | 32.46 173 | 27.12 174 | 35.02 175 | 9.52 173 | 75.50 162 | 22.31 173 | 60.21 161 | 38.45 175 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMVS |  | 37.38 22 | 44.16 164 | 40.28 165 | 55.82 165 | 40.82 180 | 42.54 171 | 65.12 164 | 63.99 171 | 34.43 172 | 24.48 175 | 57.12 170 | 3.92 175 | 76.17 161 | 17.10 175 | 55.52 165 | 48.75 171 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
PMMVS2 | | | 40.82 165 | 38.86 166 | 46.69 171 | 53.84 176 | 16.45 181 | 48.61 171 | 49.92 176 | 37.49 170 | 31.67 172 | 60.97 167 | 8.14 174 | 56.42 174 | 28.42 170 | 30.72 173 | 67.19 165 |
|
wuykxyi23d | | | 39.76 166 | 33.18 168 | 59.51 163 | 46.98 178 | 44.01 168 | 57.70 170 | 67.74 166 | 24.13 176 | 13.98 179 | 34.33 176 | 1.27 178 | 71.33 168 | 34.23 167 | 18.23 177 | 63.18 168 |
|
PNet_i23d | | | 38.26 167 | 35.42 167 | 46.79 170 | 58.74 173 | 35.48 176 | 59.65 168 | 51.25 175 | 32.45 174 | 23.44 177 | 47.53 173 | 2.04 177 | 58.96 172 | 25.60 171 | 18.09 178 | 45.92 174 |
|
MVE |  | 26.22 23 | 30.37 168 | 25.89 169 | 43.81 172 | 44.55 179 | 35.46 177 | 28.87 175 | 39.07 177 | 18.20 177 | 18.58 178 | 40.18 174 | 2.68 176 | 47.37 175 | 17.07 176 | 23.78 176 | 48.60 172 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
wuyk23d | | | 16.82 169 | 15.94 170 | 19.46 174 | 58.74 173 | 31.45 179 | 39.22 173 | 3.74 180 | 6.84 179 | 6.04 180 | 2.70 177 | 1.27 178 | 24.29 177 | 10.54 177 | 14.40 180 | 2.63 177 |
|
ab-mvs-re | | | 7.23 170 | 9.64 171 | 0.00 175 | 0.00 182 | 0.00 183 | 0.00 176 | 0.00 181 | 0.00 180 | 0.00 181 | 86.72 95 | 0.00 180 | 0.00 178 | 0.00 178 | 0.00 181 | 0.00 178 |
|
test12 | | | | | 86.80 15 | 92.63 17 | 70.70 22 | | 91.79 36 | | 82.71 15 | | 71.67 11 | 96.16 11 | | 94.50 11 | 93.54 17 |
|
plane_prior7 | | | | | | 90.08 35 | 68.51 46 | | | | | | | | | | |
|
plane_prior6 | | | | | | 89.84 39 | 68.70 43 | | | | | | 60.42 71 | | | | |
|
plane_prior5 | | | | | | | | | 92.44 18 | | | | | 95.38 21 | 78.71 22 | 86.32 56 | 91.33 50 |
|
plane_prior4 | | | | | | | | | | | | 91.00 34 | | | | | |
|
plane_prior3 | | | | | | | 68.60 45 | | | 78.44 17 | 78.92 32 | | | | | | |
|
plane_prior2 | | | | | | | | 91.25 14 | | 79.12 9 | | | | | | | |
|
plane_prior1 | | | | | | 89.90 38 | | | | | | | | | | | |
|
plane_prior | | | | | | | 68.71 41 | 90.38 25 | | 77.62 20 | | | | | | 86.16 58 | |
|
n2 | | | | | | | | | 0.00 181 | | | | | | | | |
|
nn | | | | | | | | | 0.00 181 | | | | | | | | |
|
door-mid | | | | | | | | | 69.98 162 | | | | | | | | |
|
lessismore_v0 | | | | | 78.97 112 | 81.01 142 | 57.15 133 | | 65.99 168 | | 61.16 151 | 82.82 122 | 39.12 150 | 91.34 89 | 59.67 103 | 46.92 170 | 88.43 96 |
|
LGP-MVS_train | | | | | 84.50 37 | 89.23 50 | 68.76 38 | | 91.94 32 | 75.37 36 | 76.64 65 | 91.51 26 | 54.29 94 | 94.91 32 | 78.44 24 | 83.78 67 | 89.83 76 |
|
test11 | | | | | | | | | 92.23 24 | | | | | | | | |
|
door | | | | | | | | | 69.44 164 | | | | | | | | |
|
HQP5-MVS | | | | | | | 66.98 60 | | | | | | | | | | |
|
HQP-NCC | | | | | | 89.33 44 | | 89.17 36 | | 76.41 28 | 77.23 55 | | | | | | |
|
ACMP_Plane | | | | | | 89.33 44 | | 89.17 36 | | 76.41 28 | 77.23 55 | | | | | | |
|
BP-MVS | | | | | | | | | | | | | | | 77.47 29 | | |
|
HQP4-MVS | | | | | | | | | | | 77.24 54 | | | 95.11 26 | | | 91.03 52 |
|
HQP3-MVS | | | | | | | | | 92.19 26 | | | | | | | 85.99 60 | |
|
HQP2-MVS | | | | | | | | | | | | | 60.17 74 | | | | |
|
NP-MVS | | | | | | 89.62 40 | 68.32 48 | | | | | 90.24 42 | | | | | |
|
MDTV_nov1_ep13_2view | | | | | | | 37.79 174 | 75.16 145 | | 55.10 159 | 66.53 136 | | 49.34 117 | | 53.98 129 | | 87.94 104 |
|
MDTV_nov1_ep13 | | | | 69.97 126 | | 83.18 120 | 53.48 153 | 77.10 138 | 80.18 141 | 60.45 138 | 69.33 125 | 80.44 139 | 48.89 121 | 86.90 126 | 51.60 137 | 78.51 101 | |
|
ACMMP++_ref | | | | | | | | | | | | | | | | 81.95 80 | |
|
ACMMP++ | | | | | | | | | | | | | | | | 81.25 85 | |
|
Test By Simon | | | | | | | | | | | | | 64.33 42 | | | | |
|
ITE_SJBPF | | | | | 78.22 118 | 81.77 137 | 60.57 109 | | 83.30 116 | 69.25 80 | 67.54 130 | 87.20 91 | 36.33 158 | 87.28 125 | 54.34 128 | 74.62 132 | 86.80 124 |
|
DeepMVS_CX |  | | | | 27.40 173 | 40.17 181 | 26.90 180 | | 24.59 178 | 17.44 178 | 23.95 176 | 48.61 172 | 9.77 172 | 26.48 176 | 18.06 174 | 24.47 175 | 28.83 176 |
|