DVP-MVS | | | 88.67 1 | 91.62 1 | 85.22 2 | 90.47 14 | 92.36 1 | 90.69 6 | 76.15 2 | 93.08 1 | 82.75 3 | 92.19 4 | 90.71 2 | 80.45 4 | 89.27 4 | 87.91 7 | 90.82 8 | 95.84 1 |
|
DPE-MVS | | | 88.63 2 | 91.29 2 | 85.53 1 | 90.87 6 | 92.20 2 | 91.98 2 | 76.00 4 | 90.55 6 | 82.09 5 | 93.85 1 | 90.75 1 | 81.25 1 | 88.62 6 | 87.59 12 | 90.96 6 | 95.48 2 |
|
CSCG | | | 85.28 19 | 87.68 16 | 82.49 22 | 89.95 21 | 91.99 3 | 88.82 22 | 71.20 35 | 86.41 19 | 79.63 14 | 79.26 26 | 88.36 7 | 73.94 37 | 86.64 29 | 86.67 24 | 91.40 2 | 94.41 7 |
|
MSP-MVS | | | 88.09 3 | 90.84 3 | 84.88 5 | 90.00 20 | 91.80 4 | 91.63 3 | 75.80 5 | 91.99 2 | 81.23 6 | 92.54 2 | 89.18 4 | 80.89 2 | 87.99 13 | 87.91 7 | 89.70 40 | 94.51 6 |
|
APDe-MVS | | | 88.00 4 | 90.50 4 | 85.08 3 | 90.95 5 | 91.58 5 | 92.03 1 | 75.53 9 | 91.15 3 | 80.10 12 | 92.27 3 | 88.34 8 | 80.80 3 | 88.00 12 | 86.99 17 | 91.09 4 | 95.16 5 |
|
SMA-MVS | | | 87.56 5 | 90.17 5 | 84.52 6 | 91.71 2 | 90.57 6 | 90.77 5 | 75.19 10 | 90.67 5 | 80.50 11 | 86.59 14 | 88.86 5 | 78.09 13 | 89.92 1 | 89.41 1 | 90.84 7 | 95.19 4 |
|
DeepPCF-MVS | | 79.04 1 | 85.30 18 | 88.93 9 | 81.06 29 | 88.77 33 | 90.48 7 | 85.46 43 | 73.08 26 | 90.97 4 | 73.77 34 | 84.81 19 | 85.95 17 | 77.43 20 | 88.22 9 | 87.73 9 | 87.85 74 | 94.34 8 |
|
DeepC-MVS | | 78.47 2 | 84.81 23 | 86.03 26 | 83.37 16 | 89.29 29 | 90.38 8 | 88.61 24 | 76.50 1 | 86.25 20 | 77.22 21 | 75.12 36 | 80.28 42 | 77.59 19 | 88.39 8 | 88.17 6 | 91.02 5 | 93.66 16 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
APD-MVS | | | 86.84 9 | 88.91 11 | 84.41 7 | 90.66 9 | 90.10 9 | 90.78 4 | 75.64 6 | 87.38 14 | 78.72 16 | 90.68 7 | 86.82 13 | 80.15 5 | 87.13 22 | 86.45 27 | 90.51 17 | 93.83 12 |
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023 |
ACMMP_NAP | | | 86.52 10 | 89.01 8 | 83.62 14 | 90.28 16 | 90.09 10 | 90.32 10 | 74.05 17 | 88.32 11 | 79.74 13 | 87.04 12 | 85.59 20 | 76.97 26 | 89.35 2 | 88.44 4 | 90.35 26 | 94.27 10 |
|
CNVR-MVS | | | 86.36 11 | 88.19 14 | 84.23 9 | 91.33 4 | 89.84 11 | 90.34 8 | 75.56 7 | 87.36 15 | 78.97 15 | 81.19 25 | 86.76 14 | 78.74 8 | 89.30 3 | 88.58 2 | 90.45 23 | 94.33 9 |
|
SteuartSystems-ACMMP | | | 85.99 13 | 88.31 13 | 83.27 18 | 90.73 8 | 89.84 11 | 90.27 11 | 74.31 12 | 84.56 27 | 75.88 27 | 87.32 11 | 85.04 21 | 77.31 21 | 89.01 5 | 88.46 3 | 91.14 3 | 93.96 11 |
Skip Steuart: Steuart Systems R&D Blog. |
MCST-MVS | | | 85.13 20 | 86.62 21 | 83.39 15 | 90.55 12 | 89.82 13 | 89.29 19 | 73.89 20 | 84.38 28 | 76.03 26 | 79.01 28 | 85.90 18 | 78.47 9 | 87.81 14 | 86.11 31 | 92.11 1 | 93.29 20 |
|
3Dnovator+ | | 75.73 4 | 82.40 32 | 82.76 37 | 81.97 26 | 88.02 35 | 89.67 14 | 86.60 34 | 71.48 34 | 81.28 40 | 78.18 18 | 64.78 80 | 77.96 48 | 77.13 24 | 87.32 20 | 86.83 20 | 90.41 24 | 91.48 34 |
|
PHI-MVS | | | 82.36 33 | 85.89 27 | 78.24 46 | 86.40 45 | 89.52 15 | 85.52 41 | 69.52 46 | 82.38 37 | 65.67 65 | 81.35 24 | 82.36 31 | 73.07 42 | 87.31 21 | 86.76 22 | 89.24 47 | 91.56 33 |
|
MP-MVS | | | 85.50 16 | 87.40 18 | 83.28 17 | 90.65 10 | 89.51 16 | 89.16 21 | 74.11 16 | 83.70 31 | 78.06 19 | 85.54 17 | 84.89 24 | 77.31 21 | 87.40 19 | 87.14 16 | 90.41 24 | 93.65 17 |
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo. |
ACMMPR | | | 85.52 15 | 87.53 17 | 83.17 19 | 90.13 17 | 89.27 17 | 89.30 18 | 73.97 18 | 86.89 17 | 77.14 22 | 86.09 15 | 83.18 29 | 77.74 17 | 87.42 18 | 87.20 14 | 90.77 10 | 92.63 23 |
|
DeepC-MVS_fast | | 78.24 3 | 84.27 26 | 85.50 28 | 82.85 20 | 90.46 15 | 89.24 18 | 87.83 30 | 74.24 14 | 84.88 23 | 76.23 25 | 75.26 35 | 81.05 40 | 77.62 18 | 88.02 11 | 87.62 11 | 90.69 13 | 92.41 26 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
SD-MVS | | | 86.96 7 | 89.45 6 | 84.05 12 | 90.13 17 | 89.23 19 | 89.77 15 | 74.59 11 | 89.17 7 | 80.70 8 | 89.93 8 | 89.67 3 | 78.47 9 | 87.57 17 | 86.79 21 | 90.67 14 | 93.76 14 |
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024 |
HFP-MVS | | | 86.15 12 | 87.95 15 | 84.06 11 | 90.80 7 | 89.20 20 | 89.62 17 | 74.26 13 | 87.52 12 | 80.63 9 | 86.82 13 | 84.19 26 | 78.22 11 | 87.58 16 | 87.19 15 | 90.81 9 | 93.13 22 |
|
MVS_0304 | | | 81.73 36 | 83.86 33 | 79.26 39 | 86.22 47 | 89.18 21 | 86.41 35 | 67.15 60 | 75.28 52 | 70.75 50 | 74.59 38 | 83.49 28 | 74.42 33 | 87.05 25 | 86.34 28 | 90.58 16 | 91.08 38 |
|
NCCC | | | 85.34 17 | 86.59 22 | 83.88 13 | 91.48 3 | 88.88 22 | 89.79 14 | 75.54 8 | 86.67 18 | 77.94 20 | 76.55 32 | 84.99 22 | 78.07 14 | 88.04 10 | 87.68 10 | 90.46 22 | 93.31 19 |
|
abl_6 | | | | | 79.05 40 | 87.27 39 | 88.85 23 | 83.62 52 | 68.25 52 | 81.68 38 | 72.94 37 | 73.79 42 | 84.45 25 | 72.55 47 | | | 89.66 42 | 90.64 41 |
|
PGM-MVS | | | 84.42 25 | 86.29 25 | 82.23 23 | 90.04 19 | 88.82 24 | 89.23 20 | 71.74 33 | 82.82 34 | 74.61 30 | 84.41 20 | 82.09 32 | 77.03 25 | 87.13 22 | 86.73 23 | 90.73 12 | 92.06 30 |
|
XVS | | | | | | 86.63 43 | 88.68 25 | 85.00 44 | | | 71.81 43 | | 81.92 34 | | | | 90.47 19 | |
|
X-MVStestdata | | | | | | 86.63 43 | 88.68 25 | 85.00 44 | | | 71.81 43 | | 81.92 34 | | | | 90.47 19 | |
|
X-MVS | | | 83.23 30 | 85.20 30 | 80.92 31 | 89.71 24 | 88.68 25 | 88.21 29 | 73.60 21 | 82.57 35 | 71.81 43 | 77.07 30 | 81.92 34 | 71.72 55 | 86.98 26 | 86.86 19 | 90.47 19 | 92.36 27 |
|
TSAR-MVS + MP. | | | 86.88 8 | 89.23 7 | 84.14 10 | 89.78 23 | 88.67 28 | 90.59 7 | 73.46 24 | 88.99 8 | 80.52 10 | 91.26 5 | 88.65 6 | 79.91 6 | 86.96 27 | 86.22 29 | 90.59 15 | 93.83 12 |
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition |
CANet | | | 81.62 37 | 83.41 34 | 79.53 38 | 87.06 40 | 88.59 29 | 85.47 42 | 67.96 56 | 76.59 50 | 74.05 31 | 74.69 37 | 81.98 33 | 72.98 45 | 86.14 36 | 85.47 35 | 89.68 41 | 90.42 44 |
|
TSAR-MVS + ACMM | | | 85.10 21 | 88.81 12 | 80.77 32 | 89.55 26 | 88.53 30 | 88.59 25 | 72.55 28 | 87.39 13 | 71.90 40 | 90.95 6 | 87.55 10 | 74.57 31 | 87.08 24 | 86.54 25 | 87.47 81 | 93.67 15 |
|
DPM-MVS | | | 83.30 29 | 84.33 32 | 82.11 24 | 89.56 25 | 88.49 31 | 90.33 9 | 73.24 25 | 83.85 30 | 76.46 24 | 72.43 45 | 82.65 30 | 73.02 44 | 86.37 33 | 86.91 18 | 90.03 33 | 89.62 49 |
|
ACMMP | | | 83.42 28 | 85.27 29 | 81.26 28 | 88.47 34 | 88.49 31 | 88.31 28 | 72.09 30 | 83.42 32 | 72.77 38 | 82.65 21 | 78.22 46 | 75.18 30 | 86.24 35 | 85.76 33 | 90.74 11 | 92.13 29 |
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 | | | 82.64 31 | 85.03 31 | 79.86 36 | 89.41 28 | 88.31 33 | 88.32 27 | 71.84 32 | 80.11 42 | 67.47 58 | 82.09 22 | 81.44 38 | 71.85 53 | 85.89 37 | 86.15 30 | 90.24 29 | 91.25 36 |
|
PCF-MVS | | 73.28 6 | 79.42 46 | 80.41 49 | 78.26 45 | 84.88 58 | 88.17 34 | 86.08 36 | 69.85 41 | 75.23 54 | 68.43 53 | 68.03 67 | 78.38 45 | 71.76 54 | 81.26 79 | 80.65 79 | 88.56 61 | 91.18 37 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
MAR-MVS | | | 79.21 48 | 80.32 50 | 77.92 48 | 87.46 37 | 88.15 35 | 83.95 50 | 67.48 59 | 74.28 56 | 68.25 54 | 64.70 81 | 77.04 49 | 72.17 49 | 85.42 40 | 85.00 40 | 88.22 62 | 87.62 61 |
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 |
CP-MVS | | | 84.74 24 | 86.43 24 | 82.77 21 | 89.48 27 | 88.13 36 | 88.64 23 | 73.93 19 | 84.92 22 | 76.77 23 | 81.94 23 | 83.50 27 | 77.29 23 | 86.92 28 | 86.49 26 | 90.49 18 | 93.14 21 |
|
HPM-MVS++ | | | 87.09 6 | 88.92 10 | 84.95 4 | 92.61 1 | 87.91 37 | 90.23 12 | 76.06 3 | 88.85 9 | 81.20 7 | 87.33 10 | 87.93 9 | 79.47 7 | 88.59 7 | 88.23 5 | 90.15 31 | 93.60 18 |
|
3Dnovator | | 73.76 5 | 79.75 43 | 80.52 48 | 78.84 42 | 84.94 57 | 87.35 38 | 84.43 49 | 65.54 71 | 78.29 46 | 73.97 32 | 63.00 88 | 75.62 54 | 74.07 36 | 85.00 44 | 85.34 37 | 90.11 32 | 89.04 51 |
|
DELS-MVS | | | 79.15 50 | 81.07 45 | 76.91 52 | 83.54 59 | 87.31 39 | 84.45 48 | 64.92 76 | 69.98 65 | 69.34 52 | 71.62 50 | 76.26 51 | 69.84 64 | 86.57 30 | 85.90 32 | 89.39 45 | 89.88 46 |
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 |
MSLP-MVS++ | | | 82.09 34 | 82.66 38 | 81.42 27 | 87.03 41 | 87.22 40 | 85.82 39 | 70.04 40 | 80.30 41 | 78.66 17 | 68.67 64 | 81.04 41 | 77.81 16 | 85.19 43 | 84.88 41 | 89.19 50 | 91.31 35 |
|
zzz-MVS | | | 85.71 14 | 86.88 20 | 84.34 8 | 90.54 13 | 87.11 41 | 89.77 15 | 74.17 15 | 88.54 10 | 83.08 2 | 78.60 29 | 86.10 16 | 78.11 12 | 87.80 15 | 87.46 13 | 90.35 26 | 92.56 24 |
|
TSAR-MVS + GP. | | | 83.69 27 | 86.58 23 | 80.32 33 | 85.14 52 | 86.96 42 | 84.91 47 | 70.25 39 | 84.71 26 | 73.91 33 | 85.16 18 | 85.63 19 | 77.92 15 | 85.44 39 | 85.71 34 | 89.77 37 | 92.45 25 |
|
CLD-MVS | | | 79.35 47 | 81.23 43 | 77.16 51 | 85.01 55 | 86.92 43 | 85.87 38 | 60.89 122 | 80.07 44 | 75.35 29 | 72.96 43 | 73.21 62 | 68.43 73 | 85.41 41 | 84.63 42 | 87.41 82 | 85.44 82 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
OPM-MVS | | | 79.68 45 | 79.28 54 | 80.15 35 | 87.99 36 | 86.77 44 | 88.52 26 | 72.72 27 | 64.55 89 | 67.65 57 | 67.87 68 | 74.33 58 | 74.31 34 | 86.37 33 | 85.25 38 | 89.73 39 | 89.81 47 |
|
QAPM | | | 78.47 53 | 80.22 51 | 76.43 54 | 85.03 54 | 86.75 45 | 80.62 62 | 66.00 68 | 73.77 59 | 65.35 66 | 65.54 76 | 78.02 47 | 72.69 46 | 83.71 52 | 83.36 51 | 88.87 56 | 90.41 45 |
|
PVSNet_Blended_VisFu | | | 76.57 61 | 77.90 60 | 75.02 61 | 80.56 77 | 86.58 46 | 79.24 73 | 66.18 65 | 64.81 86 | 68.18 55 | 65.61 74 | 71.45 67 | 67.05 75 | 84.16 48 | 81.80 58 | 88.90 54 | 90.92 39 |
|
CPTT-MVS | | | 81.77 35 | 83.10 36 | 80.21 34 | 85.93 48 | 86.45 47 | 87.72 31 | 70.98 36 | 82.54 36 | 71.53 46 | 74.23 41 | 81.49 37 | 76.31 28 | 82.85 61 | 81.87 57 | 88.79 58 | 92.26 28 |
|
canonicalmvs | | | 79.16 49 | 82.37 40 | 75.41 59 | 82.33 66 | 86.38 48 | 80.80 59 | 63.18 89 | 82.90 33 | 67.34 59 | 72.79 44 | 76.07 52 | 69.62 65 | 83.46 57 | 84.41 43 | 89.20 49 | 90.60 42 |
|
AdaColmap | | | 79.74 44 | 78.62 56 | 81.05 30 | 89.23 30 | 86.06 49 | 84.95 46 | 71.96 31 | 79.39 45 | 75.51 28 | 63.16 86 | 68.84 89 | 76.51 27 | 83.55 54 | 82.85 52 | 88.13 66 | 86.46 71 |
|
ACMP | | 73.23 7 | 79.79 42 | 80.53 47 | 78.94 41 | 85.61 50 | 85.68 50 | 85.61 40 | 69.59 44 | 77.33 48 | 71.00 49 | 74.45 39 | 69.16 83 | 71.88 51 | 83.15 58 | 83.37 50 | 89.92 34 | 90.57 43 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
OMC-MVS | | | 80.26 39 | 82.59 39 | 77.54 49 | 83.04 60 | 85.54 51 | 83.25 54 | 65.05 75 | 87.32 16 | 72.42 39 | 72.04 48 | 78.97 44 | 73.30 40 | 83.86 50 | 81.60 61 | 88.15 65 | 88.83 53 |
|
train_agg | | | 84.86 22 | 87.21 19 | 82.11 24 | 90.59 11 | 85.47 52 | 89.81 13 | 73.55 23 | 83.95 29 | 73.30 35 | 89.84 9 | 87.23 12 | 75.61 29 | 86.47 31 | 85.46 36 | 89.78 36 | 92.06 30 |
|
HQP-MVS | | | 81.19 38 | 83.27 35 | 78.76 43 | 87.40 38 | 85.45 53 | 86.95 32 | 70.47 38 | 81.31 39 | 66.91 61 | 79.24 27 | 76.63 50 | 71.67 56 | 84.43 47 | 83.78 47 | 89.19 50 | 92.05 32 |
|
UA-Net | | | 74.47 71 | 77.80 61 | 70.59 85 | 85.33 51 | 85.40 54 | 73.54 133 | 65.98 69 | 60.65 121 | 56.00 103 | 72.11 46 | 79.15 43 | 54.63 158 | 83.13 59 | 82.25 55 | 88.04 68 | 81.92 119 |
|
LGP-MVS_train | | | 79.83 41 | 81.22 44 | 78.22 47 | 86.28 46 | 85.36 55 | 86.76 33 | 69.59 44 | 77.34 47 | 65.14 67 | 75.68 34 | 70.79 72 | 71.37 59 | 84.60 45 | 84.01 44 | 90.18 30 | 90.74 40 |
|
MVS_111021_HR | | | 80.13 40 | 81.46 42 | 78.58 44 | 85.77 49 | 85.17 56 | 83.45 53 | 69.28 47 | 74.08 58 | 70.31 51 | 74.31 40 | 75.26 55 | 73.13 41 | 86.46 32 | 85.15 39 | 89.53 43 | 89.81 47 |
|
TSAR-MVS + COLMAP | | | 78.34 54 | 81.64 41 | 74.48 68 | 80.13 83 | 85.01 57 | 81.73 55 | 65.93 70 | 84.75 25 | 61.68 77 | 85.79 16 | 66.27 97 | 71.39 58 | 82.91 60 | 80.78 70 | 86.01 122 | 85.98 73 |
|
OpenMVS | | 70.44 10 | 76.15 64 | 76.82 72 | 75.37 60 | 85.01 55 | 84.79 58 | 78.99 77 | 62.07 112 | 71.27 63 | 67.88 56 | 57.91 115 | 72.36 65 | 70.15 63 | 82.23 66 | 81.41 62 | 88.12 67 | 87.78 60 |
|
TAPA-MVS | | 71.42 9 | 77.69 56 | 80.05 52 | 74.94 62 | 80.68 76 | 84.52 59 | 81.36 56 | 63.14 90 | 84.77 24 | 64.82 69 | 68.72 62 | 75.91 53 | 71.86 52 | 81.62 68 | 79.55 95 | 87.80 76 | 85.24 85 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
CNLPA | | | 77.20 58 | 77.54 63 | 76.80 53 | 82.63 62 | 84.31 60 | 79.77 68 | 64.64 77 | 85.17 21 | 73.18 36 | 56.37 122 | 69.81 79 | 74.53 32 | 81.12 82 | 78.69 105 | 86.04 121 | 87.29 65 |
|
Vis-MVSNet | | | 72.77 79 | 77.20 69 | 67.59 118 | 74.19 131 | 84.01 61 | 76.61 100 | 61.69 117 | 60.62 122 | 50.61 134 | 70.25 56 | 71.31 70 | 55.57 154 | 83.85 51 | 82.28 54 | 86.90 94 | 88.08 57 |
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020 |
EPP-MVSNet | | | 74.00 73 | 77.41 66 | 70.02 91 | 80.53 78 | 83.91 62 | 74.99 110 | 62.68 103 | 65.06 84 | 49.77 138 | 68.68 63 | 72.09 66 | 63.06 100 | 82.49 65 | 80.73 71 | 89.12 52 | 88.91 52 |
|
EIA-MVS | | | 75.64 66 | 76.60 73 | 74.53 67 | 82.43 65 | 83.84 63 | 78.32 83 | 62.28 111 | 65.96 79 | 63.28 75 | 68.95 60 | 67.54 93 | 71.61 57 | 82.55 63 | 81.63 60 | 89.24 47 | 85.72 76 |
|
PVSNet_BlendedMVS | | | 76.21 62 | 77.52 64 | 74.69 65 | 79.46 86 | 83.79 64 | 77.50 90 | 64.34 81 | 69.88 66 | 71.88 41 | 68.54 65 | 70.42 75 | 67.05 75 | 83.48 55 | 79.63 91 | 87.89 72 | 86.87 67 |
|
PVSNet_Blended | | | 76.21 62 | 77.52 64 | 74.69 65 | 79.46 86 | 83.79 64 | 77.50 90 | 64.34 81 | 69.88 66 | 71.88 41 | 68.54 65 | 70.42 75 | 67.05 75 | 83.48 55 | 79.63 91 | 87.89 72 | 86.87 67 |
|
casdiffmvs | | | 76.76 60 | 78.46 57 | 74.77 64 | 80.32 80 | 83.73 66 | 80.65 61 | 63.24 88 | 73.58 60 | 66.11 63 | 69.39 59 | 74.09 59 | 69.49 67 | 82.52 64 | 79.35 99 | 88.84 57 | 86.52 70 |
|
CS-MVS | | | 76.92 59 | 78.01 59 | 75.64 57 | 81.47 69 | 83.59 67 | 80.68 60 | 62.47 108 | 68.39 70 | 65.83 64 | 67.84 69 | 70.74 73 | 73.07 42 | 85.31 42 | 82.79 53 | 90.33 28 | 87.42 62 |
|
IS_MVSNet | | | 73.33 75 | 77.34 68 | 68.65 106 | 81.29 70 | 83.47 68 | 74.45 114 | 63.58 85 | 65.75 81 | 48.49 142 | 67.11 73 | 70.61 74 | 54.63 158 | 84.51 46 | 83.58 49 | 89.48 44 | 86.34 72 |
|
ACMM | | 72.26 8 | 78.86 52 | 78.13 58 | 79.71 37 | 86.89 42 | 83.40 69 | 86.02 37 | 70.50 37 | 75.28 52 | 71.49 47 | 63.01 87 | 69.26 82 | 73.57 39 | 84.11 49 | 83.98 45 | 89.76 38 | 87.84 59 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
Effi-MVS+ | | | 75.28 68 | 76.20 74 | 74.20 69 | 81.15 71 | 83.24 70 | 81.11 57 | 63.13 91 | 66.37 75 | 60.27 82 | 64.30 84 | 68.88 87 | 70.93 62 | 81.56 70 | 81.69 59 | 88.61 59 | 87.35 63 |
|
UGNet | | | 72.78 78 | 77.67 62 | 67.07 128 | 71.65 155 | 83.24 70 | 75.20 104 | 63.62 84 | 64.93 85 | 56.72 99 | 71.82 49 | 73.30 60 | 49.02 171 | 81.02 83 | 80.70 77 | 86.22 113 | 88.67 54 |
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 |
EPNet | | | 79.08 51 | 80.62 46 | 77.28 50 | 88.90 32 | 83.17 72 | 83.65 51 | 72.41 29 | 74.41 55 | 67.15 60 | 76.78 31 | 74.37 57 | 64.43 92 | 83.70 53 | 83.69 48 | 87.15 85 | 88.19 56 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
ETV-MVS | | | 77.41 57 | 78.94 55 | 75.62 58 | 81.86 68 | 83.04 73 | 80.59 63 | 63.41 86 | 70.65 64 | 63.89 72 | 72.11 46 | 68.87 88 | 74.10 35 | 85.61 38 | 83.89 46 | 89.88 35 | 88.38 55 |
|
HyFIR lowres test | | | 69.47 108 | 68.94 122 | 70.09 90 | 76.77 108 | 82.93 74 | 76.63 99 | 60.17 131 | 59.00 129 | 54.03 112 | 40.54 190 | 65.23 100 | 67.89 74 | 76.54 138 | 78.30 110 | 85.03 139 | 80.07 134 |
|
IB-MVS | | 66.94 12 | 71.21 90 | 71.66 98 | 70.68 82 | 79.18 88 | 82.83 75 | 72.61 139 | 61.77 116 | 59.66 126 | 63.44 74 | 53.26 144 | 59.65 118 | 59.16 127 | 76.78 135 | 82.11 56 | 87.90 71 | 87.33 64 |
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 |
LS3D | | | 74.08 72 | 73.39 84 | 74.88 63 | 85.05 53 | 82.62 76 | 79.71 69 | 68.66 50 | 72.82 61 | 58.80 86 | 57.61 116 | 61.31 111 | 71.07 61 | 80.32 92 | 78.87 104 | 86.00 123 | 80.18 133 |
|
ACMH | | 65.37 14 | 70.71 93 | 70.00 108 | 71.54 77 | 82.51 64 | 82.47 77 | 77.78 87 | 68.13 53 | 56.19 148 | 46.06 157 | 54.30 132 | 51.20 172 | 68.68 71 | 80.66 87 | 80.72 72 | 86.07 117 | 84.45 98 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
CANet_DTU | | | 73.29 76 | 76.96 71 | 69.00 102 | 77.04 106 | 82.06 78 | 79.49 71 | 56.30 159 | 67.85 72 | 53.29 119 | 71.12 53 | 70.37 77 | 61.81 114 | 81.59 69 | 80.96 68 | 86.09 116 | 84.73 93 |
|
Anonymous202405211 | | | | 72.16 95 | | 80.85 75 | 81.85 79 | 76.88 97 | 65.40 72 | 62.89 104 | | 46.35 177 | 67.99 92 | 62.05 107 | 81.15 81 | 80.38 83 | 85.97 124 | 84.50 96 |
|
DI_MVS_plusplus_trai | | | 75.13 69 | 76.12 75 | 73.96 70 | 78.18 94 | 81.55 80 | 80.97 58 | 62.54 105 | 68.59 69 | 65.13 68 | 61.43 90 | 74.81 56 | 69.32 68 | 81.01 84 | 79.59 93 | 87.64 79 | 85.89 74 |
|
Anonymous20231211 | | | 71.90 83 | 72.48 92 | 71.21 78 | 80.14 82 | 81.53 81 | 76.92 95 | 62.89 94 | 64.46 91 | 58.94 84 | 43.80 181 | 70.98 71 | 62.22 104 | 80.70 86 | 80.19 86 | 86.18 114 | 85.73 75 |
|
MVS_111021_LR | | | 78.13 55 | 79.85 53 | 76.13 55 | 81.12 72 | 81.50 82 | 80.28 64 | 65.25 73 | 76.09 51 | 71.32 48 | 76.49 33 | 72.87 64 | 72.21 48 | 82.79 62 | 81.29 63 | 86.59 107 | 87.91 58 |
|
EG-PatchMatch MVS | | | 67.24 136 | 66.94 143 | 67.60 117 | 78.73 91 | 81.35 83 | 73.28 137 | 59.49 138 | 46.89 189 | 51.42 130 | 43.65 182 | 53.49 153 | 55.50 155 | 81.38 74 | 80.66 78 | 87.15 85 | 81.17 125 |
|
MVS_Test | | | 75.37 67 | 77.13 70 | 73.31 72 | 79.07 89 | 81.32 84 | 79.98 65 | 60.12 133 | 69.72 68 | 64.11 71 | 70.53 54 | 73.22 61 | 68.90 69 | 80.14 97 | 79.48 97 | 87.67 78 | 85.50 80 |
|
PLC | | 68.99 11 | 75.68 65 | 75.31 77 | 76.12 56 | 82.94 61 | 81.26 85 | 79.94 66 | 66.10 66 | 77.15 49 | 66.86 62 | 59.13 104 | 68.53 90 | 73.73 38 | 80.38 91 | 79.04 100 | 87.13 89 | 81.68 121 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
ET-MVSNet_ETH3D | | | 72.46 81 | 74.19 80 | 70.44 86 | 62.50 189 | 81.17 86 | 79.90 67 | 62.46 109 | 64.52 90 | 57.52 95 | 71.49 52 | 59.15 120 | 72.08 50 | 78.61 115 | 81.11 65 | 88.16 64 | 83.29 107 |
|
ACMH+ | | 66.54 13 | 71.36 89 | 70.09 107 | 72.85 73 | 82.59 63 | 81.13 87 | 78.56 79 | 68.04 54 | 61.55 114 | 52.52 125 | 51.50 161 | 54.14 145 | 68.56 72 | 78.85 112 | 79.50 96 | 86.82 97 | 83.94 101 |
|
v1144 | | | 69.93 103 | 69.36 117 | 70.61 84 | 74.89 124 | 80.93 88 | 79.11 75 | 60.64 124 | 55.97 150 | 55.31 106 | 53.85 139 | 54.14 145 | 66.54 84 | 78.10 120 | 77.44 123 | 87.14 88 | 85.09 87 |
|
UniMVSNet (Re) | | | 69.53 106 | 71.90 96 | 66.76 133 | 76.42 109 | 80.93 88 | 72.59 140 | 68.03 55 | 61.75 113 | 41.68 171 | 58.34 112 | 57.23 129 | 53.27 163 | 79.53 104 | 80.62 80 | 88.57 60 | 84.90 91 |
|
v1192 | | | 69.50 107 | 68.83 123 | 70.29 88 | 74.49 128 | 80.92 90 | 78.55 80 | 60.54 126 | 55.04 156 | 54.21 109 | 52.79 153 | 52.33 165 | 66.92 79 | 77.88 122 | 77.35 126 | 87.04 92 | 85.51 79 |
|
Fast-Effi-MVS+ | | | 73.11 77 | 73.66 82 | 72.48 74 | 77.72 100 | 80.88 91 | 78.55 80 | 58.83 148 | 65.19 83 | 60.36 81 | 59.98 99 | 62.42 109 | 71.22 60 | 81.66 67 | 80.61 81 | 88.20 63 | 84.88 92 |
|
UniMVSNet_NR-MVSNet | | | 70.59 94 | 72.19 93 | 68.72 104 | 77.72 100 | 80.72 92 | 73.81 130 | 69.65 43 | 61.99 109 | 43.23 166 | 60.54 95 | 57.50 127 | 58.57 128 | 79.56 103 | 81.07 66 | 89.34 46 | 83.97 99 |
|
v144192 | | | 69.34 109 | 68.68 127 | 70.12 89 | 74.06 132 | 80.54 93 | 78.08 86 | 60.54 126 | 54.99 158 | 54.13 111 | 52.92 151 | 52.80 163 | 66.73 82 | 77.13 130 | 76.72 133 | 87.15 85 | 85.63 77 |
|
Effi-MVS+-dtu | | | 71.82 84 | 71.86 97 | 71.78 76 | 78.77 90 | 80.47 94 | 78.55 80 | 61.67 119 | 60.68 120 | 55.49 104 | 58.48 108 | 65.48 99 | 68.85 70 | 76.92 132 | 75.55 144 | 87.35 83 | 85.46 81 |
|
v1921920 | | | 69.03 112 | 68.32 131 | 69.86 92 | 74.03 133 | 80.37 95 | 77.55 88 | 60.25 130 | 54.62 160 | 53.59 117 | 52.36 157 | 51.50 171 | 66.75 81 | 77.17 129 | 76.69 135 | 86.96 93 | 85.56 78 |
|
diffmvs | | | 74.86 70 | 77.37 67 | 71.93 75 | 75.62 117 | 80.35 96 | 79.42 72 | 60.15 132 | 72.81 62 | 64.63 70 | 71.51 51 | 73.11 63 | 66.53 85 | 79.02 110 | 77.98 113 | 85.25 136 | 86.83 69 |
|
v2v482 | | | 70.05 102 | 69.46 116 | 70.74 80 | 74.62 127 | 80.32 97 | 79.00 76 | 60.62 125 | 57.41 139 | 56.89 98 | 55.43 128 | 55.14 140 | 66.39 86 | 77.25 128 | 77.14 128 | 86.90 94 | 83.57 106 |
|
v10 | | | 70.22 99 | 69.76 112 | 70.74 80 | 74.79 125 | 80.30 98 | 79.22 74 | 59.81 136 | 57.71 137 | 56.58 101 | 54.22 137 | 55.31 138 | 66.95 78 | 78.28 118 | 77.47 122 | 87.12 91 | 85.07 88 |
|
v1240 | | | 68.64 117 | 67.89 136 | 69.51 97 | 73.89 135 | 80.26 99 | 76.73 98 | 59.97 135 | 53.43 167 | 53.08 120 | 51.82 160 | 50.84 174 | 66.62 83 | 76.79 134 | 76.77 132 | 86.78 99 | 85.34 83 |
|
v8 | | | 70.23 98 | 69.86 110 | 70.67 83 | 74.69 126 | 79.82 100 | 78.79 78 | 59.18 141 | 58.80 130 | 58.20 92 | 55.00 129 | 57.33 128 | 66.31 87 | 77.51 125 | 76.71 134 | 86.82 97 | 83.88 102 |
|
DU-MVS | | | 69.63 105 | 70.91 101 | 68.13 110 | 75.99 112 | 79.54 101 | 73.81 130 | 69.20 48 | 61.20 118 | 43.23 166 | 58.52 106 | 53.50 152 | 58.57 128 | 79.22 107 | 80.45 82 | 87.97 69 | 83.97 99 |
|
NR-MVSNet | | | 68.79 115 | 70.56 103 | 66.71 135 | 77.48 103 | 79.54 101 | 73.52 134 | 69.20 48 | 61.20 118 | 39.76 173 | 58.52 106 | 50.11 178 | 51.37 167 | 80.26 95 | 80.71 76 | 88.97 53 | 83.59 105 |
|
TranMVSNet+NR-MVSNet | | | 69.25 110 | 70.81 102 | 67.43 119 | 77.23 105 | 79.46 103 | 73.48 135 | 69.66 42 | 60.43 123 | 39.56 174 | 58.82 105 | 53.48 154 | 55.74 152 | 79.59 101 | 81.21 64 | 88.89 55 | 82.70 109 |
|
MSDG | | | 71.52 86 | 69.87 109 | 73.44 71 | 82.21 67 | 79.35 104 | 79.52 70 | 64.59 78 | 66.15 77 | 61.87 76 | 53.21 146 | 56.09 135 | 65.85 89 | 78.94 111 | 78.50 107 | 86.60 106 | 76.85 156 |
|
DCV-MVSNet | | | 73.65 74 | 75.78 76 | 71.16 79 | 80.19 81 | 79.27 105 | 77.45 92 | 61.68 118 | 66.73 74 | 58.72 87 | 65.31 77 | 69.96 78 | 62.19 105 | 81.29 78 | 80.97 67 | 86.74 100 | 86.91 66 |
|
v7n | | | 67.05 139 | 66.94 143 | 67.17 125 | 72.35 148 | 78.97 106 | 73.26 138 | 58.88 147 | 51.16 178 | 50.90 132 | 48.21 173 | 50.11 178 | 60.96 119 | 77.70 123 | 77.38 124 | 86.68 104 | 85.05 89 |
|
tfpn200view9 | | | 68.11 120 | 68.72 126 | 67.40 120 | 77.83 98 | 78.93 107 | 74.28 120 | 62.81 95 | 56.64 143 | 46.82 152 | 52.65 154 | 53.47 155 | 56.59 144 | 80.41 88 | 78.43 108 | 86.11 115 | 80.52 130 |
|
CHOSEN 1792x2688 | | | 69.20 111 | 69.26 118 | 69.13 99 | 76.86 107 | 78.93 107 | 77.27 93 | 60.12 133 | 61.86 111 | 54.42 108 | 42.54 185 | 61.61 110 | 66.91 80 | 78.55 116 | 78.14 112 | 79.23 167 | 83.23 108 |
|
thres600view7 | | | 67.68 128 | 68.43 130 | 66.80 132 | 77.90 95 | 78.86 109 | 73.84 128 | 62.75 96 | 56.07 149 | 44.70 164 | 52.85 152 | 52.81 162 | 55.58 153 | 80.41 88 | 77.77 116 | 86.05 119 | 80.28 132 |
|
thres200 | | | 67.98 122 | 68.55 129 | 67.30 123 | 77.89 97 | 78.86 109 | 74.18 124 | 62.75 96 | 56.35 146 | 46.48 155 | 52.98 150 | 53.54 151 | 56.46 145 | 80.41 88 | 77.97 114 | 86.05 119 | 79.78 137 |
|
FC-MVSNet-train | | | 72.60 80 | 75.07 78 | 69.71 94 | 81.10 73 | 78.79 111 | 73.74 132 | 65.23 74 | 66.10 78 | 53.34 118 | 70.36 55 | 63.40 106 | 56.92 143 | 81.44 72 | 80.96 68 | 87.93 70 | 84.46 97 |
|
tttt0517 | | | 71.41 88 | 72.95 88 | 69.60 96 | 73.70 138 | 78.70 112 | 74.42 117 | 59.12 142 | 63.89 96 | 58.35 91 | 64.56 83 | 58.39 124 | 64.27 93 | 80.29 93 | 80.17 87 | 87.74 77 | 84.69 94 |
|
thisisatest0530 | | | 71.48 87 | 73.01 87 | 69.70 95 | 73.83 136 | 78.62 113 | 74.53 113 | 59.12 142 | 64.13 92 | 58.63 88 | 64.60 82 | 58.63 122 | 64.27 93 | 80.28 94 | 80.17 87 | 87.82 75 | 84.64 95 |
|
thres400 | | | 67.95 123 | 68.62 128 | 67.17 125 | 77.90 95 | 78.59 114 | 74.27 121 | 62.72 98 | 56.34 147 | 45.77 159 | 53.00 149 | 53.35 158 | 56.46 145 | 80.21 96 | 78.43 108 | 85.91 126 | 80.43 131 |
|
GA-MVS | | | 68.14 119 | 69.17 120 | 66.93 131 | 73.77 137 | 78.50 115 | 74.45 114 | 58.28 150 | 55.11 155 | 48.44 143 | 60.08 97 | 53.99 148 | 61.50 116 | 78.43 117 | 77.57 120 | 85.13 137 | 80.54 129 |
|
UniMVSNet_ETH3D | | | 67.18 138 | 67.03 142 | 67.36 121 | 74.44 129 | 78.12 116 | 74.07 125 | 66.38 63 | 52.22 172 | 46.87 151 | 48.64 171 | 51.84 169 | 56.96 141 | 77.29 127 | 78.53 106 | 85.42 133 | 82.59 110 |
|
V42 | | | 68.76 116 | 69.63 113 | 67.74 113 | 64.93 186 | 78.01 117 | 78.30 84 | 56.48 158 | 58.65 131 | 56.30 102 | 54.26 135 | 57.03 131 | 64.85 91 | 77.47 126 | 77.01 130 | 85.60 130 | 84.96 90 |
|
GBi-Net | | | 70.78 91 | 73.37 85 | 67.76 111 | 72.95 143 | 78.00 118 | 75.15 105 | 62.72 98 | 64.13 92 | 51.44 127 | 58.37 109 | 69.02 84 | 57.59 135 | 81.33 75 | 80.72 72 | 86.70 101 | 82.02 113 |
|
test1 | | | 70.78 91 | 73.37 85 | 67.76 111 | 72.95 143 | 78.00 118 | 75.15 105 | 62.72 98 | 64.13 92 | 51.44 127 | 58.37 109 | 69.02 84 | 57.59 135 | 81.33 75 | 80.72 72 | 86.70 101 | 82.02 113 |
|
FMVSNet2 | | | 70.39 97 | 72.67 91 | 67.72 114 | 72.95 143 | 78.00 118 | 75.15 105 | 62.69 102 | 63.29 100 | 51.25 131 | 55.64 124 | 68.49 91 | 57.59 135 | 80.91 85 | 80.35 84 | 86.70 101 | 82.02 113 |
|
FMVSNet3 | | | 70.49 95 | 72.90 89 | 67.67 116 | 72.88 146 | 77.98 121 | 74.96 111 | 62.72 98 | 64.13 92 | 51.44 127 | 58.37 109 | 69.02 84 | 57.43 138 | 79.43 105 | 79.57 94 | 86.59 107 | 81.81 120 |
|
COLMAP_ROB | | 62.73 15 | 67.66 129 | 66.76 145 | 68.70 105 | 80.49 79 | 77.98 121 | 75.29 103 | 62.95 93 | 63.62 98 | 49.96 136 | 47.32 176 | 50.72 175 | 58.57 128 | 76.87 133 | 75.50 145 | 84.94 141 | 75.33 167 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
Fast-Effi-MVS+-dtu | | | 68.34 118 | 69.47 115 | 67.01 129 | 75.15 120 | 77.97 123 | 77.12 94 | 55.40 161 | 57.87 132 | 46.68 154 | 56.17 123 | 60.39 112 | 62.36 103 | 76.32 139 | 76.25 140 | 85.35 135 | 81.34 123 |
|
MS-PatchMatch | | | 70.17 100 | 70.49 104 | 69.79 93 | 80.98 74 | 77.97 123 | 77.51 89 | 58.95 145 | 62.33 107 | 55.22 107 | 53.14 147 | 65.90 98 | 62.03 108 | 79.08 109 | 77.11 129 | 84.08 146 | 77.91 147 |
|
thres100view900 | | | 67.60 132 | 68.02 133 | 67.12 127 | 77.83 98 | 77.75 125 | 73.90 127 | 62.52 106 | 56.64 143 | 46.82 152 | 52.65 154 | 53.47 155 | 55.92 149 | 78.77 113 | 77.62 119 | 85.72 127 | 79.23 140 |
|
FMVSNet1 | | | 68.84 114 | 70.47 105 | 66.94 130 | 71.35 160 | 77.68 126 | 74.71 112 | 62.35 110 | 56.93 141 | 49.94 137 | 50.01 167 | 64.59 101 | 57.07 140 | 81.33 75 | 80.72 72 | 86.25 112 | 82.00 116 |
|
gg-mvs-nofinetune | | | 62.55 160 | 65.05 158 | 59.62 169 | 78.72 92 | 77.61 127 | 70.83 147 | 53.63 162 | 39.71 201 | 22.04 201 | 36.36 194 | 64.32 102 | 47.53 173 | 81.16 80 | 79.03 101 | 85.00 140 | 77.17 152 |
|
WR-MVS | | | 63.03 156 | 67.40 140 | 57.92 175 | 75.14 121 | 77.60 128 | 60.56 188 | 66.10 66 | 54.11 165 | 23.88 195 | 53.94 138 | 53.58 150 | 34.50 192 | 73.93 151 | 77.71 117 | 87.35 83 | 80.94 126 |
|
v148 | | | 67.85 125 | 67.53 137 | 68.23 108 | 73.25 141 | 77.57 129 | 74.26 122 | 57.36 155 | 55.70 151 | 57.45 96 | 53.53 140 | 55.42 137 | 61.96 110 | 75.23 143 | 73.92 152 | 85.08 138 | 81.32 124 |
|
LTVRE_ROB | | 59.44 16 | 61.82 172 | 62.64 174 | 60.87 162 | 72.83 147 | 77.19 130 | 64.37 177 | 58.97 144 | 33.56 205 | 28.00 191 | 52.59 156 | 42.21 196 | 63.93 96 | 74.52 147 | 76.28 138 | 77.15 174 | 82.13 112 |
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 |
baseline2 | | | 69.69 104 | 70.27 106 | 69.01 101 | 75.72 116 | 77.13 131 | 73.82 129 | 58.94 146 | 61.35 116 | 57.09 97 | 61.68 89 | 57.17 130 | 61.99 109 | 78.10 120 | 76.58 136 | 86.48 110 | 79.85 135 |
|
WR-MVS_H | | | 61.83 171 | 65.87 150 | 57.12 178 | 71.72 153 | 76.87 132 | 61.45 186 | 66.19 64 | 51.97 175 | 22.92 199 | 53.13 148 | 52.30 167 | 33.80 193 | 71.03 170 | 75.00 147 | 86.65 105 | 80.78 127 |
|
baseline1 | | | 70.10 101 | 72.17 94 | 67.69 115 | 79.74 84 | 76.80 133 | 73.91 126 | 64.38 80 | 62.74 105 | 48.30 144 | 64.94 78 | 64.08 103 | 54.17 160 | 81.46 71 | 78.92 102 | 85.66 129 | 76.22 158 |
|
TDRefinement | | | 66.09 142 | 65.03 159 | 67.31 122 | 69.73 170 | 76.75 134 | 75.33 101 | 64.55 79 | 60.28 124 | 49.72 139 | 45.63 179 | 42.83 195 | 60.46 124 | 75.75 140 | 75.95 141 | 84.08 146 | 78.04 146 |
|
Vis-MVSNet (Re-imp) | | | 67.83 126 | 73.52 83 | 61.19 160 | 78.37 93 | 76.72 135 | 66.80 165 | 62.96 92 | 65.50 82 | 34.17 184 | 67.19 72 | 69.68 80 | 39.20 188 | 79.39 106 | 79.44 98 | 85.68 128 | 76.73 157 |
|
CDS-MVSNet | | | 67.65 130 | 69.83 111 | 65.09 140 | 75.39 119 | 76.55 136 | 74.42 117 | 63.75 83 | 53.55 166 | 49.37 140 | 59.41 102 | 62.45 108 | 44.44 178 | 79.71 100 | 79.82 89 | 83.17 152 | 77.36 151 |
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022 |
pm-mvs1 | | | 65.62 143 | 67.42 139 | 63.53 152 | 73.66 139 | 76.39 137 | 69.66 149 | 60.87 123 | 49.73 182 | 43.97 165 | 51.24 163 | 57.00 132 | 48.16 172 | 79.89 98 | 77.84 115 | 84.85 143 | 79.82 136 |
|
IterMVS-LS | | | 71.69 85 | 72.82 90 | 70.37 87 | 77.54 102 | 76.34 138 | 75.13 108 | 60.46 128 | 61.53 115 | 57.57 94 | 64.89 79 | 67.33 94 | 66.04 88 | 77.09 131 | 77.37 125 | 85.48 132 | 85.18 86 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
GG-mvs-BLEND | | | 46.86 198 | 67.51 138 | 22.75 204 | 0.05 214 | 76.21 139 | 64.69 175 | 0.04 211 | 61.90 110 | 0.09 214 | 55.57 125 | 71.32 69 | 0.08 210 | 70.54 174 | 67.19 184 | 71.58 194 | 69.86 182 |
|
CostFormer | | | 68.92 113 | 69.58 114 | 68.15 109 | 75.98 114 | 76.17 140 | 78.22 85 | 51.86 175 | 65.80 80 | 61.56 78 | 63.57 85 | 62.83 107 | 61.85 112 | 70.40 178 | 68.67 176 | 79.42 165 | 79.62 138 |
|
MVSTER | | | 72.06 82 | 74.24 79 | 69.51 97 | 70.39 166 | 75.97 141 | 76.91 96 | 57.36 155 | 64.64 88 | 61.39 79 | 68.86 61 | 63.76 104 | 63.46 97 | 81.44 72 | 79.70 90 | 87.56 80 | 85.31 84 |
|
baseline | | | 70.45 96 | 74.09 81 | 66.20 136 | 70.95 163 | 75.67 142 | 74.26 122 | 53.57 163 | 68.33 71 | 58.42 89 | 69.87 57 | 71.45 67 | 61.55 115 | 74.84 146 | 74.76 149 | 78.42 169 | 83.72 104 |
|
IterMVS-SCA-FT | | | 66.89 140 | 69.22 119 | 64.17 146 | 71.30 161 | 75.64 143 | 71.33 144 | 53.17 167 | 57.63 138 | 49.08 141 | 60.72 93 | 60.05 116 | 63.09 99 | 74.99 145 | 73.92 152 | 77.07 175 | 81.57 122 |
|
tfpnnormal | | | 64.27 152 | 63.64 168 | 65.02 141 | 75.84 115 | 75.61 144 | 71.24 146 | 62.52 106 | 47.79 186 | 42.97 168 | 42.65 184 | 44.49 193 | 52.66 165 | 78.77 113 | 76.86 131 | 84.88 142 | 79.29 139 |
|
PEN-MVS | | | 62.96 157 | 65.77 151 | 59.70 168 | 73.98 134 | 75.45 145 | 63.39 181 | 67.61 58 | 52.49 170 | 25.49 194 | 53.39 141 | 49.12 182 | 40.85 186 | 71.94 163 | 77.26 127 | 86.86 96 | 80.72 128 |
|
CP-MVSNet | | | 62.68 159 | 65.49 154 | 59.40 171 | 71.84 151 | 75.34 146 | 62.87 183 | 67.04 61 | 52.64 169 | 27.19 192 | 53.38 142 | 48.15 184 | 41.40 184 | 71.26 166 | 75.68 142 | 86.07 117 | 82.00 116 |
|
TransMVSNet (Re) | | | 64.74 149 | 65.66 152 | 63.66 151 | 77.40 104 | 75.33 147 | 69.86 148 | 62.67 104 | 47.63 187 | 41.21 172 | 50.01 167 | 52.33 165 | 45.31 177 | 79.57 102 | 77.69 118 | 85.49 131 | 77.07 155 |
|
thisisatest0515 | | | 67.40 134 | 68.78 124 | 65.80 138 | 70.02 168 | 75.24 148 | 69.36 152 | 57.37 154 | 54.94 159 | 53.67 116 | 55.53 127 | 54.85 141 | 58.00 133 | 78.19 119 | 78.91 103 | 86.39 111 | 83.78 103 |
|
USDC | | | 67.36 135 | 67.90 135 | 66.74 134 | 71.72 153 | 75.23 149 | 71.58 143 | 60.28 129 | 67.45 73 | 50.54 135 | 60.93 91 | 45.20 192 | 62.08 106 | 76.56 137 | 74.50 150 | 84.25 145 | 75.38 166 |
|
PS-CasMVS | | | 62.38 165 | 65.06 157 | 59.25 172 | 71.73 152 | 75.21 150 | 62.77 184 | 66.99 62 | 51.94 176 | 26.96 193 | 52.00 159 | 47.52 187 | 41.06 185 | 71.16 169 | 75.60 143 | 85.97 124 | 81.97 118 |
|
pmmvs6 | | | 62.41 163 | 62.88 171 | 61.87 157 | 71.38 159 | 75.18 151 | 67.76 158 | 59.45 140 | 41.64 197 | 42.52 170 | 37.33 192 | 52.91 161 | 46.87 174 | 77.67 124 | 76.26 139 | 83.23 151 | 79.18 141 |
|
Baseline_NR-MVSNet | | | 67.53 133 | 68.77 125 | 66.09 137 | 75.99 112 | 74.75 152 | 72.43 141 | 68.41 51 | 61.33 117 | 38.33 177 | 51.31 162 | 54.13 147 | 56.03 148 | 79.22 107 | 78.19 111 | 85.37 134 | 82.45 111 |
|
IterMVS | | | 66.36 141 | 68.30 132 | 64.10 147 | 69.48 173 | 74.61 153 | 73.41 136 | 50.79 181 | 57.30 140 | 48.28 145 | 60.64 94 | 59.92 117 | 60.85 123 | 74.14 150 | 72.66 159 | 81.80 155 | 78.82 143 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo. |
DTE-MVSNet | | | 61.85 169 | 64.96 160 | 58.22 174 | 74.32 130 | 74.39 154 | 61.01 187 | 67.85 57 | 51.76 177 | 21.91 202 | 53.28 143 | 48.17 183 | 37.74 189 | 72.22 160 | 76.44 137 | 86.52 109 | 78.49 144 |
|
DWT-MVSNet_training | | | 67.24 136 | 65.96 148 | 68.74 103 | 76.15 110 | 74.36 155 | 74.37 119 | 56.66 157 | 61.82 112 | 60.51 80 | 58.23 114 | 49.76 180 | 65.07 90 | 70.04 179 | 70.39 167 | 79.70 164 | 77.11 154 |
|
anonymousdsp | | | 65.28 146 | 67.98 134 | 62.13 156 | 58.73 197 | 73.98 156 | 67.10 162 | 50.69 182 | 48.41 185 | 47.66 150 | 54.27 133 | 52.75 164 | 61.45 118 | 76.71 136 | 80.20 85 | 87.13 89 | 89.53 50 |
|
pmmvs4 | | | 67.89 124 | 67.39 141 | 68.48 107 | 71.60 157 | 73.57 157 | 74.45 114 | 60.98 121 | 64.65 87 | 57.97 93 | 54.95 130 | 51.73 170 | 61.88 111 | 73.78 152 | 75.11 146 | 83.99 148 | 77.91 147 |
|
SCA | | | 65.40 145 | 66.58 147 | 64.02 148 | 70.65 164 | 73.37 158 | 67.35 159 | 53.46 165 | 63.66 97 | 54.14 110 | 60.84 92 | 60.20 115 | 61.50 116 | 69.96 180 | 68.14 181 | 77.01 176 | 69.91 181 |
|
tpm cat1 | | | 65.41 144 | 63.81 167 | 67.28 124 | 75.61 118 | 72.88 159 | 75.32 102 | 52.85 169 | 62.97 102 | 63.66 73 | 53.24 145 | 53.29 160 | 61.83 113 | 65.54 190 | 64.14 192 | 74.43 187 | 74.60 169 |
|
PatchMatch-RL | | | 67.78 127 | 66.65 146 | 69.10 100 | 73.01 142 | 72.69 160 | 68.49 155 | 61.85 115 | 62.93 103 | 60.20 83 | 56.83 121 | 50.42 176 | 69.52 66 | 75.62 141 | 74.46 151 | 81.51 156 | 73.62 175 |
|
SixPastTwentyTwo | | | 61.84 170 | 62.45 176 | 61.12 161 | 69.20 174 | 72.20 161 | 62.03 185 | 57.40 153 | 46.54 190 | 38.03 179 | 57.14 120 | 41.72 197 | 58.12 132 | 69.67 181 | 71.58 163 | 81.94 154 | 78.30 145 |
|
dps | | | 64.00 154 | 62.99 170 | 65.18 139 | 73.29 140 | 72.07 162 | 68.98 154 | 53.07 168 | 57.74 136 | 58.41 90 | 55.55 126 | 47.74 186 | 60.89 122 | 69.53 182 | 67.14 185 | 76.44 179 | 71.19 179 |
|
TinyColmap | | | 62.84 158 | 61.03 183 | 64.96 142 | 69.61 171 | 71.69 163 | 68.48 156 | 59.76 137 | 55.41 152 | 47.69 149 | 47.33 175 | 34.20 203 | 62.76 102 | 74.52 147 | 72.59 160 | 81.44 157 | 71.47 178 |
|
pmmvs5 | | | 62.37 166 | 64.04 165 | 60.42 163 | 65.03 184 | 71.67 164 | 67.17 161 | 52.70 172 | 50.30 179 | 44.80 162 | 54.23 136 | 51.19 173 | 49.37 170 | 72.88 155 | 73.48 156 | 83.45 149 | 74.55 170 |
|
our_test_3 | | | | | | 67.93 177 | 70.99 165 | 66.89 163 | | | | | | | | | | |
|
MDTV_nov1_ep13 | | | 64.37 151 | 65.24 155 | 63.37 154 | 68.94 175 | 70.81 166 | 72.40 142 | 50.29 184 | 60.10 125 | 53.91 114 | 60.07 98 | 59.15 120 | 57.21 139 | 69.43 183 | 67.30 183 | 77.47 172 | 69.78 183 |
|
RPSCF | | | 67.64 131 | 71.25 99 | 63.43 153 | 61.86 191 | 70.73 167 | 67.26 160 | 50.86 180 | 74.20 57 | 58.91 85 | 67.49 70 | 69.33 81 | 64.10 95 | 71.41 165 | 68.45 180 | 77.61 171 | 77.17 152 |
|
CMPMVS | | 47.78 17 | 62.49 162 | 62.52 175 | 62.46 155 | 70.01 169 | 70.66 168 | 62.97 182 | 51.84 176 | 51.98 174 | 56.71 100 | 42.87 183 | 53.62 149 | 57.80 134 | 72.23 159 | 70.37 168 | 75.45 184 | 75.91 160 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
pmmvs-eth3d | | | 63.52 155 | 62.44 177 | 64.77 143 | 66.82 181 | 70.12 169 | 69.41 151 | 59.48 139 | 54.34 164 | 52.71 121 | 46.24 178 | 44.35 194 | 56.93 142 | 72.37 156 | 73.77 154 | 83.30 150 | 75.91 160 |
|
CR-MVSNet | | | 64.83 148 | 65.54 153 | 64.01 149 | 70.64 165 | 69.41 170 | 65.97 170 | 52.74 170 | 57.81 134 | 52.65 122 | 54.27 133 | 56.31 134 | 60.92 120 | 72.20 161 | 73.09 157 | 81.12 159 | 75.69 163 |
|
RPMNet | | | 61.71 173 | 62.88 171 | 60.34 164 | 69.51 172 | 69.41 170 | 63.48 180 | 49.23 185 | 57.81 134 | 45.64 160 | 50.51 165 | 50.12 177 | 53.13 164 | 68.17 188 | 68.49 179 | 81.07 160 | 75.62 165 |
|
CVMVSNet | | | 62.55 160 | 65.89 149 | 58.64 173 | 66.95 179 | 69.15 172 | 66.49 169 | 56.29 160 | 52.46 171 | 32.70 185 | 59.27 103 | 58.21 126 | 50.09 169 | 71.77 164 | 71.39 164 | 79.31 166 | 78.99 142 |
|
MDTV_nov1_ep13_2view | | | 60.16 177 | 60.51 185 | 59.75 167 | 65.39 183 | 69.05 173 | 68.00 157 | 48.29 191 | 51.99 173 | 45.95 158 | 48.01 174 | 49.64 181 | 53.39 162 | 68.83 185 | 66.52 187 | 77.47 172 | 69.55 184 |
|
PatchmatchNet | | | 64.21 153 | 64.65 161 | 63.69 150 | 71.29 162 | 68.66 174 | 69.63 150 | 51.70 177 | 63.04 101 | 53.77 115 | 59.83 101 | 58.34 125 | 60.23 125 | 68.54 186 | 66.06 188 | 75.56 182 | 68.08 187 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
EPNet_dtu | | | 68.08 121 | 71.00 100 | 64.67 144 | 79.64 85 | 68.62 175 | 75.05 109 | 63.30 87 | 66.36 76 | 45.27 161 | 67.40 71 | 66.84 96 | 43.64 180 | 75.37 142 | 74.98 148 | 81.15 158 | 77.44 150 |
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023 |
test0.0.03 1 | | | 58.80 180 | 61.58 181 | 55.56 183 | 75.02 122 | 68.45 176 | 59.58 192 | 61.96 113 | 52.74 168 | 29.57 188 | 49.75 170 | 54.56 143 | 31.46 195 | 71.19 167 | 69.77 169 | 75.75 180 | 64.57 191 |
|
MDA-MVSNet-bldmvs | | | 53.37 192 | 53.01 195 | 53.79 189 | 43.67 207 | 67.95 177 | 59.69 191 | 57.92 151 | 43.69 193 | 32.41 186 | 41.47 186 | 27.89 208 | 52.38 166 | 56.97 202 | 65.99 189 | 76.68 177 | 67.13 188 |
|
PatchT | | | 61.97 168 | 64.04 165 | 59.55 170 | 60.49 193 | 67.40 178 | 56.54 194 | 48.65 189 | 56.69 142 | 52.65 122 | 51.10 164 | 52.14 168 | 60.92 120 | 72.20 161 | 73.09 157 | 78.03 170 | 75.69 163 |
|
testgi | | | 54.39 190 | 57.86 189 | 50.35 192 | 71.59 158 | 67.24 179 | 54.95 196 | 53.25 166 | 43.36 194 | 23.78 196 | 44.64 180 | 47.87 185 | 24.96 200 | 70.45 175 | 68.66 177 | 73.60 190 | 62.78 196 |
|
MIMVSNet | | | 58.52 182 | 61.34 182 | 55.22 184 | 60.76 192 | 67.01 180 | 66.81 164 | 49.02 187 | 56.43 145 | 38.90 176 | 40.59 189 | 54.54 144 | 40.57 187 | 73.16 154 | 71.65 162 | 75.30 185 | 66.00 190 |
|
PM-MVS | | | 60.48 176 | 60.94 184 | 59.94 166 | 58.85 196 | 66.83 181 | 64.27 178 | 51.39 178 | 55.03 157 | 48.03 146 | 50.00 169 | 40.79 199 | 58.26 131 | 69.20 184 | 67.13 186 | 78.84 168 | 77.60 149 |
|
Anonymous20231206 | | | 56.36 186 | 57.80 190 | 54.67 186 | 70.08 167 | 66.39 182 | 60.46 189 | 57.54 152 | 49.50 184 | 29.30 189 | 33.86 197 | 46.64 188 | 35.18 191 | 70.44 176 | 68.88 175 | 75.47 183 | 68.88 186 |
|
test20.03 | | | 53.93 191 | 56.28 192 | 51.19 191 | 72.19 150 | 65.83 183 | 53.20 198 | 61.08 120 | 42.74 195 | 22.08 200 | 37.07 193 | 45.76 191 | 24.29 203 | 70.44 176 | 69.04 173 | 74.31 188 | 63.05 195 |
|
Patchmtry | | | | | | | 65.80 184 | 65.97 170 | 52.74 170 | | 52.65 122 | | | | | | | |
|
TAMVS | | | 59.58 179 | 62.81 173 | 55.81 182 | 66.03 182 | 65.64 185 | 63.86 179 | 48.74 188 | 49.95 181 | 37.07 181 | 54.77 131 | 58.54 123 | 44.44 178 | 72.29 158 | 71.79 161 | 74.70 186 | 66.66 189 |
|
test-mter | | | 60.84 175 | 64.62 162 | 56.42 180 | 55.99 201 | 64.18 186 | 65.39 172 | 34.23 204 | 54.39 163 | 46.21 156 | 57.40 119 | 59.49 119 | 55.86 150 | 71.02 171 | 69.65 170 | 80.87 161 | 76.20 159 |
|
tpmrst | | | 62.00 167 | 62.35 178 | 61.58 158 | 71.62 156 | 64.14 187 | 69.07 153 | 48.22 193 | 62.21 108 | 53.93 113 | 58.26 113 | 55.30 139 | 55.81 151 | 63.22 194 | 62.62 194 | 70.85 196 | 70.70 180 |
|
test-LLR | | | 64.42 150 | 64.36 163 | 64.49 145 | 75.02 122 | 63.93 188 | 66.61 167 | 61.96 113 | 54.41 161 | 47.77 147 | 57.46 117 | 60.25 113 | 55.20 156 | 70.80 172 | 69.33 171 | 80.40 162 | 74.38 171 |
|
TESTMET0.1,1 | | | 61.10 174 | 64.36 163 | 57.29 177 | 57.53 198 | 63.93 188 | 66.61 167 | 36.22 203 | 54.41 161 | 47.77 147 | 57.46 117 | 60.25 113 | 55.20 156 | 70.80 172 | 69.33 171 | 80.40 162 | 74.38 171 |
|
tpm | | | 62.41 163 | 63.15 169 | 61.55 159 | 72.24 149 | 63.79 190 | 71.31 145 | 46.12 197 | 57.82 133 | 55.33 105 | 59.90 100 | 54.74 142 | 53.63 161 | 67.24 189 | 64.29 191 | 70.65 197 | 74.25 173 |
|
PMMVS | | | 65.06 147 | 69.17 120 | 60.26 165 | 55.25 203 | 63.43 191 | 66.71 166 | 43.01 199 | 62.41 106 | 50.64 133 | 69.44 58 | 67.04 95 | 63.29 98 | 74.36 149 | 73.54 155 | 82.68 153 | 73.99 174 |
|
ambc | | | | 53.42 193 | | 64.99 185 | 63.36 192 | 49.96 201 | | 47.07 188 | 37.12 180 | 28.97 201 | 16.36 211 | 41.82 182 | 75.10 144 | 67.34 182 | 71.55 195 | 75.72 162 |
|
FC-MVSNet-test | | | 56.90 185 | 65.20 156 | 47.21 195 | 66.98 178 | 63.20 193 | 49.11 203 | 58.60 149 | 59.38 128 | 11.50 208 | 65.60 75 | 56.68 133 | 24.66 202 | 71.17 168 | 71.36 165 | 72.38 193 | 69.02 185 |
|
EPMVS | | | 60.00 178 | 61.97 179 | 57.71 176 | 68.46 176 | 63.17 194 | 64.54 176 | 48.23 192 | 63.30 99 | 44.72 163 | 60.19 96 | 56.05 136 | 50.85 168 | 65.27 192 | 62.02 195 | 69.44 199 | 63.81 193 |
|
FMVSNet5 | | | 57.24 183 | 60.02 186 | 53.99 188 | 56.45 200 | 62.74 195 | 65.27 173 | 47.03 194 | 55.14 154 | 39.55 175 | 40.88 187 | 53.42 157 | 41.83 181 | 72.35 157 | 71.10 166 | 73.79 189 | 64.50 192 |
|
EU-MVSNet | | | 54.63 188 | 58.69 187 | 49.90 193 | 56.99 199 | 62.70 196 | 56.41 195 | 50.64 183 | 45.95 192 | 23.14 198 | 50.42 166 | 46.51 189 | 36.63 190 | 65.51 191 | 64.85 190 | 75.57 181 | 74.91 168 |
|
gm-plane-assit | | | 57.00 184 | 57.62 191 | 56.28 181 | 76.10 111 | 62.43 197 | 47.62 204 | 46.57 195 | 33.84 204 | 23.24 197 | 37.52 191 | 40.19 200 | 59.61 126 | 79.81 99 | 77.55 121 | 84.55 144 | 72.03 177 |
|
MIMVSNet1 | | | 49.27 194 | 53.25 194 | 44.62 197 | 44.61 205 | 61.52 198 | 53.61 197 | 52.18 173 | 41.62 198 | 18.68 204 | 28.14 203 | 41.58 198 | 25.50 198 | 68.46 187 | 69.04 173 | 73.15 191 | 62.37 197 |
|
ADS-MVSNet | | | 55.94 187 | 58.01 188 | 53.54 190 | 62.48 190 | 58.48 199 | 59.12 193 | 46.20 196 | 59.65 127 | 42.88 169 | 52.34 158 | 53.31 159 | 46.31 175 | 62.00 196 | 60.02 197 | 64.23 203 | 60.24 200 |
|
FPMVS | | | 51.87 193 | 50.00 198 | 54.07 187 | 66.83 180 | 57.25 200 | 60.25 190 | 50.91 179 | 50.25 180 | 34.36 183 | 36.04 195 | 32.02 205 | 41.49 183 | 58.98 200 | 56.07 199 | 70.56 198 | 59.36 201 |
|
new-patchmatchnet | | | 46.97 197 | 49.47 199 | 44.05 199 | 62.82 188 | 56.55 201 | 45.35 205 | 52.01 174 | 42.47 196 | 17.04 206 | 35.73 196 | 35.21 202 | 21.84 206 | 61.27 197 | 54.83 201 | 65.26 202 | 60.26 198 |
|
MVS-HIRNet | | | 54.41 189 | 52.10 196 | 57.11 179 | 58.99 195 | 56.10 202 | 49.68 202 | 49.10 186 | 46.18 191 | 52.15 126 | 33.18 198 | 46.11 190 | 56.10 147 | 63.19 195 | 59.70 198 | 76.64 178 | 60.25 199 |
|
pmmvs3 | | | 47.65 195 | 49.08 200 | 45.99 196 | 44.61 205 | 54.79 203 | 50.04 200 | 31.95 207 | 33.91 203 | 29.90 187 | 30.37 199 | 33.53 204 | 46.31 175 | 63.50 193 | 63.67 193 | 73.14 192 | 63.77 194 |
|
N_pmnet | | | 47.35 196 | 50.13 197 | 44.11 198 | 59.98 194 | 51.64 204 | 51.86 199 | 44.80 198 | 49.58 183 | 20.76 203 | 40.65 188 | 40.05 201 | 29.64 196 | 59.84 198 | 55.15 200 | 57.63 204 | 54.00 203 |
|
CHOSEN 280x420 | | | 58.70 181 | 61.88 180 | 54.98 185 | 55.45 202 | 50.55 205 | 64.92 174 | 40.36 200 | 55.21 153 | 38.13 178 | 48.31 172 | 63.76 104 | 63.03 101 | 73.73 153 | 68.58 178 | 68.00 201 | 73.04 176 |
|
new_pmnet | | | 38.40 200 | 42.64 202 | 33.44 201 | 37.54 210 | 45.00 206 | 36.60 207 | 32.72 206 | 40.27 199 | 12.72 207 | 29.89 200 | 28.90 207 | 24.78 201 | 53.17 203 | 52.90 203 | 56.31 205 | 48.34 204 |
|
PMVS | | 39.38 18 | 46.06 199 | 43.30 201 | 49.28 194 | 62.93 187 | 38.75 207 | 41.88 206 | 53.50 164 | 33.33 206 | 35.46 182 | 28.90 202 | 31.01 206 | 33.04 194 | 58.61 201 | 54.63 202 | 68.86 200 | 57.88 202 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
Gipuma | | | 36.38 201 | 35.80 203 | 37.07 200 | 45.76 204 | 33.90 208 | 29.81 208 | 48.47 190 | 39.91 200 | 18.02 205 | 8.00 210 | 8.14 213 | 25.14 199 | 59.29 199 | 61.02 196 | 55.19 206 | 40.31 205 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMMVS2 | | | 25.60 202 | 29.75 204 | 20.76 205 | 28.00 211 | 30.93 209 | 23.10 209 | 29.18 208 | 23.14 208 | 1.46 213 | 18.23 206 | 16.54 210 | 5.08 208 | 40.22 204 | 41.40 205 | 37.76 207 | 37.79 207 |
|
MVE | | 19.12 19 | 20.47 205 | 23.27 205 | 17.20 206 | 12.66 213 | 25.41 210 | 10.52 213 | 34.14 205 | 14.79 211 | 6.53 212 | 8.79 209 | 4.68 214 | 16.64 207 | 29.49 206 | 41.63 204 | 22.73 211 | 38.11 206 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
E-PMN | | | 21.77 203 | 18.24 206 | 25.89 202 | 40.22 208 | 19.58 211 | 12.46 212 | 39.87 201 | 18.68 210 | 6.71 210 | 9.57 207 | 4.31 216 | 22.36 205 | 19.89 208 | 27.28 207 | 33.73 208 | 28.34 209 |
|
EMVS | | | 20.98 204 | 17.15 207 | 25.44 203 | 39.51 209 | 19.37 212 | 12.66 211 | 39.59 202 | 19.10 209 | 6.62 211 | 9.27 208 | 4.40 215 | 22.43 204 | 17.99 209 | 24.40 208 | 31.81 209 | 25.53 210 |
|
DeepMVS_CX | | | | | | | 18.74 213 | 18.55 210 | 8.02 209 | 26.96 207 | 7.33 209 | 23.81 205 | 13.05 212 | 25.99 197 | 25.17 207 | | 22.45 212 | 36.25 208 |
|
tmp_tt | | | | | 14.50 207 | 14.68 212 | 7.17 214 | 10.46 214 | 2.21 210 | 37.73 202 | 28.71 190 | 25.26 204 | 16.98 209 | 4.37 209 | 31.49 205 | 29.77 206 | 26.56 210 | |
|
testmvs | | | 0.09 206 | 0.15 208 | 0.02 208 | 0.01 215 | 0.02 215 | 0.05 216 | 0.01 212 | 0.11 212 | 0.01 215 | 0.26 212 | 0.01 217 | 0.06 212 | 0.10 210 | 0.10 209 | 0.01 213 | 0.43 212 |
|
test123 | | | 0.09 206 | 0.14 209 | 0.02 208 | 0.00 216 | 0.02 215 | 0.02 217 | 0.01 212 | 0.09 213 | 0.00 216 | 0.30 211 | 0.00 218 | 0.08 210 | 0.03 211 | 0.09 210 | 0.01 213 | 0.45 211 |
|
sosnet-low-res | | | 0.00 208 | 0.00 210 | 0.00 210 | 0.00 216 | 0.00 217 | 0.00 218 | 0.00 214 | 0.00 214 | 0.00 216 | 0.00 213 | 0.00 218 | 0.00 213 | 0.00 212 | 0.00 211 | 0.00 215 | 0.00 213 |
|
sosnet | | | 0.00 208 | 0.00 210 | 0.00 210 | 0.00 216 | 0.00 217 | 0.00 218 | 0.00 214 | 0.00 214 | 0.00 216 | 0.00 213 | 0.00 218 | 0.00 213 | 0.00 212 | 0.00 211 | 0.00 215 | 0.00 213 |
|
SR-MVS | | | | | | 88.99 31 | | | 73.57 22 | | | | 87.54 11 | | | | | |
|
test_part1 | | | | | | | | | | | | | | | | | | 95.35 3 |
|
MTAPA | | | | | | | | | | | 83.48 1 | | 86.45 15 | | | | | |
|
MTMP | | | | | | | | | | | 82.66 4 | | 84.91 23 | | | | | |
|
Patchmatch-RL test | | | | | | | | 2.85 215 | | | | | | | | | | |
|
mPP-MVS | | | | | | 89.90 22 | | | | | | | 81.29 39 | | | | | |
|
NP-MVS | | | | | | | | | | 80.10 43 | | | | | | | | |
|