DeepPCF-MVS | | 79.04 1 | 62.76 1 | 66.22 1 | 60.45 2 | 53.69 1 | 65.50 3 | 68.81 4 | 47.05 3 | 78.76 1 |
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DeepC-MVS_fast | | 78.24 3 | 62.57 2 | 64.27 3 | 61.43 1 | 53.65 2 | 65.83 1 | 70.22 2 | 48.24 1 | 74.89 3 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
DeepC-MVS | | 78.47 2 | 61.99 3 | 64.34 2 | 60.43 3 | 53.21 3 | 65.62 2 | 68.07 5 | 47.59 2 | 75.48 2 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
3Dnovator+ | | 75.73 4 | 58.40 4 | 59.88 5 | 57.41 4 | 46.92 7 | 62.89 4 | 70.54 1 | 38.80 13 | 72.84 6 |
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3Dnovator | | 73.76 5 | 58.20 5 | 60.10 4 | 56.93 5 | 45.58 9 | 62.04 5 | 70.17 3 | 38.57 14 | 74.61 5 |
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PCF-MVS | | 73.28 6 | 57.32 6 | 59.66 6 | 55.76 6 | 48.61 4 | 56.36 12 | 67.24 7 | 43.68 5 | 70.70 11 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
ACMP | | 73.23 7 | 56.18 7 | 59.37 7 | 54.05 9 | 47.31 5 | 61.10 7 | 58.60 19 | 42.44 7 | 71.44 9 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
TAPA-MVS(SR) | | | 56.09 8 | 56.78 13 | 55.62 7 | 43.28 13 | 58.11 9 | 65.17 10 | 43.60 6 | 70.29 12 |
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OpenMVS |  | 70.44 10 | 55.58 9 | 58.77 8 | 53.44 11 | 44.82 10 | 58.83 8 | 65.59 9 | 35.91 17 | 72.72 7 |
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TAPA-MVS | | 71.42 9 | 55.13 10 | 58.21 10 | 53.07 12 | 41.62 16 | 56.79 11 | 62.68 14 | 39.75 12 | 74.79 4 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
ACMM | | 72.26 8 | 55.12 11 | 54.88 18 | 55.28 8 | 38.65 19 | 61.75 6 | 60.21 18 | 43.87 4 | 71.11 10 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
COLMAP(SR) | | | 54.99 12 | 57.09 11 | 53.58 10 | 46.78 8 | 55.24 14 | 63.74 12 | 41.76 9 | 67.41 19 |
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ACMH+ | | 66.54 12 | 53.99 13 | 56.90 12 | 52.05 13 | 44.66 11 | 57.37 10 | 56.79 22 | 41.98 8 | 69.14 14 |
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COLMAP(base) | | | 53.42 14 | 56.15 14 | 51.59 14 | 44.02 12 | 53.93 15 | 60.80 17 | 40.05 11 | 68.28 17 |
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LTVRE_ROB | | 59.44 15 | 53.25 15 | 56.08 15 | 51.36 15 | 39.82 18 | 53.93 15 | 62.24 15 | 37.92 16 | 72.34 8 |
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 |
PLC |  | 68.99 11 | 51.58 16 | 55.07 17 | 49.25 19 | 41.73 15 | 52.26 20 | 56.95 21 | 38.53 15 | 68.41 16 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
ACMH | | 65.37 13 | 51.50 17 | 53.46 20 | 50.20 17 | 38.46 20 | 52.73 18 | 57.24 20 | 40.63 10 | 68.46 15 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
GSE | | | 51.31 18 | 58.55 9 | 46.48 24 | 47.08 6 | 49.58 23 | 54.32 26 | 35.53 19 | 70.02 13 |
|
BP-MVSNet | | | 50.87 19 | 53.66 19 | 49.01 20 | 40.10 17 | 49.76 22 | 63.03 13 | 34.23 20 | 67.21 20 |
Christian Sormann, Patrick Knöbelreiter, Andreas Kuhn, Mattia Rossi, Thomas Pock, Friedrich Fraundorfer: BP-MVSNet: Belief-Propagation-Layers for Multi-View-Stereo. 3DV 2020 |
LPCS | | | 50.41 20 | 55.27 16 | 47.16 23 | 43.12 14 | 51.06 21 | 54.57 25 | 35.86 18 | 67.43 18 |
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COLMAP_ROB |  | 62.73 14 | 49.91 21 | 51.76 21 | 48.68 21 | 37.30 21 | 52.31 19 | 61.83 16 | 31.91 23 | 66.23 21 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
CasMVSNet(SR_B) | | | 49.66 22 | 48.09 22 | 50.71 16 | 33.02 23 | 55.30 13 | 67.43 6 | 29.40 24 | 63.15 23 |
|
CasMVSNet(base) | | | 49.00 23 | 48.08 24 | 49.61 18 | 34.83 22 | 53.10 17 | 66.82 8 | 28.93 26 | 61.32 25 |
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A-TVSNet + Gipuma |  | | 45.36 24 | 47.40 25 | 44.00 25 | 29.86 25 | 43.85 25 | 55.31 23 | 32.84 22 | 64.94 22 |
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CIDER | | | 45.22 25 | 41.50 26 | 47.70 22 | 28.55 26 | 46.16 24 | 64.03 11 | 32.90 21 | 54.46 27 |
Qingshan Xu and Wenbing Tao: Learning Inverse Depth Regression for Multi-View Stereo with Correlation Cost Volume. AAAI 2020 |
CasMVSNet(SR_A) | | | 41.59 26 | 48.09 22 | 37.27 26 | 33.02 23 | 27.16 26 | 55.24 24 | 29.40 24 | 63.15 23 |
|
PMVS |  | 39.38 17 | 22.01 27 | 32.82 27 | 14.80 27 | 5.84 30 | 11.38 28 | 26.05 27 | 6.98 29 | 59.80 26 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
example | | | 18.45 28 | 28.74 28 | 11.60 28 | 6.01 29 | 5.21 31 | 22.21 28 | 7.37 28 | 51.47 28 |
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MVE |  | 19.12 18 | 15.60 29 | 22.59 32 | 10.94 29 | 5.22 31 | 14.12 27 | 8.87 31 | 9.84 27 | 39.95 32 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
hgnet | | | 15.22 30 | 24.38 29 | 9.11 30 | 6.26 27 | 5.91 29 | 17.93 29 | 3.49 30 | 42.51 30 |
|
DPSNet | | | 15.22 30 | 24.38 29 | 9.11 30 | 6.26 27 | 5.91 29 | 17.93 29 | 3.49 30 | 42.51 30 |
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CMPMVS |  | 47.78 16 | 9.53 32 | 23.73 31 | 0.07 32 | 0.00 32 | 0.00 32 | 0.20 32 | 0.00 32 | 47.47 29 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
dnet | | | 0.00 33 | 0.00 33 | 0.00 33 | 0.00 32 | 0.00 32 | 0.00 33 | 0.00 32 | 0.00 33 |
|