DeepPCF-MVS | | 80.84 1 | 88.10 1 | 88.56 1 | 86.73 7 | 92.24 6 | 69.03 12 | 89.57 14 | 93.39 5 | 77.53 2 | 89.79 1 | 94.12 2 | 78.98 1 | 96.58 4 | 85.66 1 | 95.72 2 | 94.58 2 |
|
DeepC-MVS | | 79.81 2 | 87.08 2 | 86.88 2 | 87.69 3 | 91.16 9 | 72.32 6 | 90.31 10 | 93.94 2 | 77.12 4 | 82.82 5 | 94.23 1 | 72.13 3 | 97.09 1 | 84.83 2 | 95.37 3 | 93.65 6 |
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 3 | 86.62 3 | 87.76 2 | 93.52 2 | 72.37 5 | 91.26 5 | 93.04 7 | 76.62 6 | 84.22 3 | 93.36 5 | 71.44 4 | 96.76 2 | 80.82 5 | 95.33 4 | 94.16 4 |
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 4 | 86.17 5 | 87.24 5 | 90.88 12 | 70.96 9 | 92.27 4 | 94.07 1 | 72.45 13 | 85.22 2 | 91.90 9 | 69.47 5 | 96.42 5 | 83.28 3 | 95.94 1 | 94.35 3 |
|
CSCG | | | 86.41 5 | 86.19 4 | 87.07 6 | 92.91 4 | 72.48 4 | 90.81 7 | 93.56 4 | 73.95 12 | 83.16 4 | 91.07 13 | 75.94 2 | 95.19 8 | 79.94 6 | 94.38 5 | 93.55 7 |
|
ACMMwithACMP | | | 85.89 6 | 85.39 6 | 87.38 4 | 93.59 1 | 72.63 3 | 92.74 2 | 93.18 6 | 76.78 5 | 80.73 7 | 93.82 3 | 64.33 10 | 96.29 6 | 82.67 4 | 90.69 12 | 93.23 8 |
|
3Dnovator+ | | 77.84 4 | 85.48 7 | 84.47 7 | 88.51 1 | 91.08 10 | 73.49 1 | 93.18 1 | 93.78 3 | 80.79 1 | 76.66 16 | 93.37 4 | 60.40 17 | 96.75 3 | 77.20 8 | 93.73 6 | 95.29 1 |
|
MG-MVS | | | 83.41 8 | 83.45 8 | 83.28 20 | 92.74 5 | 62.28 31 | 88.17 22 | 89.50 19 | 75.22 8 | 81.49 6 | 92.74 7 | 66.75 7 | 95.11 10 | 72.85 13 | 91.58 9 | 92.45 10 |
|
EPP-MVSNet | | | 83.40 9 | 83.02 9 | 84.57 12 | 90.13 15 | 64.47 28 | 92.32 3 | 90.73 17 | 74.45 11 | 79.35 9 | 91.10 11 | 69.05 6 | 95.12 9 | 72.78 14 | 87.22 16 | 94.13 5 |
|
3Dnovator | | 76.31 5 | 83.38 10 | 82.31 10 | 86.59 8 | 87.94 27 | 72.94 2 | 90.64 8 | 92.14 9 | 77.21 3 | 75.47 18 | 92.83 6 | 58.56 18 | 94.72 13 | 73.24 12 | 92.71 7 | 92.13 12 |
|
OMC-MVS | | | 82.69 11 | 81.97 11 | 84.85 11 | 88.75 20 | 67.42 19 | 87.98 24 | 90.87 16 | 74.92 9 | 79.72 8 | 91.65 10 | 62.19 15 | 93.96 18 | 75.26 10 | 86.42 20 | 93.16 9 |
|
CLD-MVS | | | 82.31 12 | 81.65 12 | 84.29 14 | 88.47 25 | 67.73 18 | 85.81 27 | 92.35 8 | 75.78 7 | 78.33 12 | 86.58 29 | 64.01 12 | 94.35 17 | 76.05 9 | 87.48 15 | 90.79 14 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
test0121 | | | 81.99 13 | 81.23 13 | 84.26 15 | 90.94 11 | 70.18 10 | 91.10 6 | 89.32 21 | 71.51 14 | 78.66 10 | 88.28 23 | 65.26 9 | 95.10 11 | 64.74 16 | 91.23 10 | 87.51 26 |
|
MAR-MVS | | | 81.84 14 | 80.70 14 | 85.27 9 | 91.32 8 | 71.53 7 | 89.82 13 | 90.92 15 | 69.77 19 | 78.50 11 | 86.21 30 | 62.36 14 | 94.52 16 | 65.36 15 | 92.05 8 | 89.77 16 |
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 |
ACMP | | 74.13 6 | 81.51 15 | 80.57 15 | 84.36 13 | 89.42 17 | 68.69 15 | 89.97 12 | 91.50 12 | 74.46 10 | 75.04 19 | 90.41 15 | 53.82 22 | 94.54 14 | 77.56 7 | 82.91 23 | 89.86 15 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
ACMM | | 73.20 8 | 80.78 16 | 79.84 16 | 83.58 18 | 89.31 18 | 68.37 16 | 89.99 11 | 91.60 10 | 70.28 16 | 77.25 14 | 89.66 18 | 53.37 24 | 93.53 22 | 74.24 11 | 82.85 24 | 88.85 18 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
AdaColmap |  | | 80.58 17 | 79.42 17 | 84.06 17 | 93.09 3 | 68.91 14 | 89.36 15 | 88.97 25 | 69.27 20 | 75.70 17 | 89.69 17 | 57.20 20 | 95.77 7 | 63.06 17 | 88.41 13 | 87.50 27 |
|
PCF-MVS | | 73.52 7 | 80.38 18 | 78.84 18 | 85.01 10 | 87.71 28 | 68.99 13 | 83.65 31 | 91.46 13 | 63.00 31 | 77.77 13 | 90.28 16 | 66.10 8 | 95.09 12 | 61.40 20 | 88.22 14 | 90.94 13 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
OpenMVS |  | 72.83 10 | 79.77 19 | 78.33 19 | 84.09 16 | 85.17 32 | 69.91 11 | 90.57 9 | 90.97 14 | 66.70 22 | 72.17 21 | 91.91 8 | 54.70 21 | 93.96 18 | 61.81 19 | 90.95 11 | 88.41 21 |
|
TAPA-MVS | | 73.13 9 | 79.15 20 | 77.94 20 | 82.79 22 | 89.59 16 | 62.99 30 | 88.16 23 | 91.51 11 | 65.77 24 | 77.14 15 | 91.09 12 | 60.91 16 | 93.21 23 | 50.26 36 | 87.05 17 | 92.17 11 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
CNLPA | | | 78.08 21 | 76.79 21 | 81.97 25 | 90.40 14 | 71.07 8 | 87.59 25 | 84.55 30 | 66.03 23 | 72.38 20 | 89.64 19 | 57.56 19 | 86.04 37 | 59.61 22 | 83.35 22 | 88.79 19 |
|
PLC |  | 70.83 11 | 78.05 22 | 76.37 23 | 83.08 21 | 91.88 7 | 67.80 17 | 88.19 21 | 89.46 20 | 64.33 28 | 69.87 25 | 88.38 22 | 53.66 23 | 93.58 21 | 58.86 23 | 82.73 26 | 87.86 23 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
PAPM | | | 77.68 23 | 76.40 22 | 81.51 27 | 87.29 29 | 61.85 33 | 83.78 30 | 89.59 18 | 64.74 27 | 71.23 23 | 88.70 20 | 62.59 13 | 93.66 20 | 52.66 34 | 87.03 18 | 89.01 17 |
|
LS3D | | | 76.95 24 | 74.82 24 | 83.37 19 | 90.45 13 | 67.36 21 | 89.15 16 | 86.94 27 | 61.87 35 | 69.52 27 | 90.61 14 | 51.71 26 | 94.53 15 | 46.38 40 | 86.71 19 | 88.21 22 |
|
F-COLMAP | | | 76.38 25 | 74.33 26 | 82.50 23 | 89.28 19 | 66.95 22 | 88.41 19 | 89.03 23 | 64.05 30 | 66.83 33 | 88.61 21 | 46.78 30 | 92.89 26 | 57.48 25 | 78.55 30 | 87.67 24 |
|
LTVRE_ROB | | 69.57 12 | 76.25 26 | 74.54 25 | 81.41 28 | 88.60 22 | 64.38 29 | 79.24 37 | 89.12 22 | 70.76 15 | 69.79 26 | 87.86 24 | 49.09 28 | 93.20 24 | 56.21 27 | 80.16 29 | 86.65 31 |
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 |
ACMH+ | | 68.96 13 | 76.01 27 | 74.01 27 | 82.03 24 | 88.60 22 | 65.31 27 | 88.86 17 | 87.55 26 | 70.25 17 | 67.75 30 | 87.47 26 | 41.27 37 | 93.19 25 | 58.37 24 | 75.94 36 | 87.60 25 |
|
ACMH | | 67.68 14 | 75.89 28 | 73.93 28 | 81.77 26 | 88.71 21 | 66.61 23 | 88.62 18 | 89.01 24 | 69.81 18 | 66.78 34 | 86.70 28 | 41.95 36 | 91.51 29 | 55.64 28 | 78.14 31 | 87.17 29 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
MSDG | | | 73.36 29 | 70.99 30 | 80.49 30 | 84.51 33 | 65.80 25 | 80.71 32 | 86.13 29 | 65.70 25 | 65.46 35 | 83.74 35 | 44.60 32 | 90.91 31 | 51.13 35 | 76.89 32 | 84.74 33 |
|
PatchmatchNet |  | | 73.12 30 | 71.33 29 | 78.49 32 | 83.18 34 | 60.85 35 | 79.63 34 | 78.57 41 | 64.13 29 | 71.73 22 | 79.81 41 | 51.20 27 | 85.97 38 | 57.40 26 | 76.36 33 | 88.66 20 |
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo. |
COLMAP_ROB |  | 66.92 15 | 73.01 31 | 70.41 34 | 80.81 29 | 87.13 30 | 65.63 26 | 88.30 20 | 84.19 32 | 62.96 32 | 63.80 37 | 87.69 25 | 38.04 38 | 92.56 28 | 46.66 39 | 74.91 37 | 84.24 34 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
test_0402 | | | 72.79 32 | 70.44 33 | 79.84 31 | 88.13 26 | 65.99 24 | 85.93 26 | 84.29 31 | 65.57 26 | 67.40 32 | 85.49 31 | 46.92 29 | 92.61 27 | 35.88 43 | 74.38 39 | 80.94 38 |
|
PatchMatch-RL | | | 72.38 33 | 70.90 31 | 76.80 36 | 88.60 22 | 67.38 20 | 79.53 35 | 76.17 43 | 62.75 33 | 69.36 28 | 82.00 39 | 45.51 31 | 84.89 39 | 53.62 31 | 80.58 28 | 78.12 42 |
|
PVSNet | | 64.34 16 | 72.08 34 | 70.87 32 | 75.69 39 | 86.21 31 | 56.44 41 | 74.37 41 | 80.73 39 | 62.06 34 | 70.17 24 | 82.23 38 | 42.86 35 | 83.31 40 | 54.77 29 | 84.45 21 | 87.32 28 |
|
OpenMVS_ROB |  | 64.09 17 | 70.56 35 | 68.19 37 | 77.65 34 | 80.26 38 | 59.41 37 | 85.01 28 | 82.96 36 | 58.76 40 | 65.43 36 | 82.33 37 | 37.63 39 | 91.23 30 | 45.34 42 | 76.03 35 | 82.32 36 |
|
USDC | | | 70.33 36 | 68.37 36 | 76.21 38 | 80.60 37 | 56.23 42 | 79.19 38 | 86.49 28 | 60.89 37 | 61.29 38 | 85.47 32 | 31.78 41 | 89.47 32 | 53.37 32 | 76.21 34 | 82.94 35 |
|
CMPMVS |  | 51.72 19 | 70.19 37 | 68.16 38 | 76.28 37 | 73.15 43 | 57.55 38 | 79.47 36 | 83.92 33 | 48.02 44 | 56.48 42 | 84.81 34 | 43.13 34 | 86.42 36 | 62.67 18 | 81.81 27 | 84.89 32 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
PMMVS | | | 69.34 38 | 68.67 35 | 71.35 41 | 75.67 41 | 62.03 32 | 75.17 40 | 73.46 44 | 50.00 43 | 68.68 29 | 79.05 42 | 52.07 25 | 78.13 41 | 61.16 21 | 82.77 25 | 73.90 43 |
|
TDRefinement | | | 67.49 39 | 64.34 40 | 76.92 35 | 73.47 42 | 61.07 34 | 84.86 29 | 82.98 35 | 59.77 39 | 58.30 41 | 85.13 33 | 26.06 42 | 87.89 33 | 47.92 37 | 60.59 43 | 81.81 37 |
|
TinyColmap | | | 67.30 40 | 64.81 39 | 74.76 40 | 81.92 35 | 56.68 40 | 80.29 33 | 81.49 37 | 60.33 38 | 56.27 43 | 83.22 36 | 24.77 43 | 87.66 34 | 45.52 41 | 69.47 40 | 79.95 39 |
|
LF4IMVS | | | 64.02 41 | 62.19 41 | 69.50 42 | 70.90 44 | 53.29 43 | 76.13 39 | 77.18 42 | 52.65 42 | 58.59 39 | 80.98 40 | 23.55 44 | 76.52 43 | 53.06 33 | 66.66 41 | 78.68 41 |
|
PVSNet_0 | | 57.27 18 | 61.67 42 | 59.27 42 | 68.85 43 | 79.61 39 | 57.44 39 | 68.01 44 | 73.44 45 | 55.93 41 | 58.54 40 | 70.41 44 | 44.58 33 | 77.55 42 | 47.01 38 | 35.91 46 | 71.55 44 |
|
FPMVS | | | 53.68 43 | 51.64 43 | 59.81 45 | 65.08 45 | 51.03 45 | 69.48 43 | 69.58 46 | 41.46 45 | 40.67 44 | 72.32 43 | 16.46 46 | 70.00 48 | 24.24 47 | 65.42 42 | 58.40 46 |
|
ANet_high | | | 50.57 44 | 46.10 44 | 63.99 44 | 48.67 48 | 39.13 48 | 70.99 42 | 80.85 38 | 61.39 36 | 31.18 45 | 57.70 45 | 17.02 45 | 73.65 46 | 31.22 45 | 15.89 51 | 79.18 40 |
|
Gipuma |  | | 45.18 45 | 41.86 45 | 55.16 48 | 77.03 40 | 51.52 44 | 32.50 49 | 80.52 40 | 32.46 47 | 27.12 46 | 35.02 50 | 9.52 48 | 75.50 45 | 22.31 48 | 60.21 44 | 38.45 50 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMVS |  | 37.38 20 | 44.16 46 | 40.28 46 | 55.82 47 | 40.82 51 | 42.54 47 | 65.12 45 | 63.99 48 | 34.43 46 | 24.48 47 | 57.12 46 | 3.92 49 | 76.17 44 | 17.10 50 | 55.52 45 | 48.75 47 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
wuykxyi23d | | | 39.76 47 | 33.18 48 | 59.51 46 | 46.98 49 | 44.01 46 | 57.70 47 | 67.74 47 | 24.13 49 | 13.98 51 | 34.33 51 | 1.27 52 | 71.33 47 | 34.23 44 | 18.23 49 | 63.18 45 |
|
PNet_i23d | | | 38.26 48 | 35.42 47 | 46.79 49 | 58.74 46 | 35.48 49 | 59.65 46 | 51.25 49 | 32.45 48 | 23.44 49 | 47.53 48 | 2.04 51 | 58.96 49 | 25.60 46 | 18.09 50 | 45.92 49 |
|
MVE |  | 26.22 21 | 30.37 49 | 25.89 49 | 43.81 50 | 44.55 50 | 35.46 50 | 28.87 50 | 39.07 50 | 18.20 50 | 18.58 50 | 40.18 49 | 2.68 50 | 47.37 50 | 17.07 51 | 23.78 48 | 48.60 48 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
wuyk23d | | | 16.82 50 | 15.94 50 | 19.46 52 | 58.74 46 | 31.45 51 | 39.22 48 | 3.74 52 | 6.84 52 | 6.04 52 | 2.70 52 | 1.27 52 | 24.29 52 | 10.54 52 | 14.40 52 | 2.63 52 |
|
DeepMVS_CX |  | | | | 27.40 51 | 40.17 52 | 26.90 52 | | 24.59 51 | 17.44 51 | 23.95 48 | 48.61 47 | 9.77 47 | 26.48 51 | 18.06 49 | 24.47 47 | 28.83 51 |
|
Test By Simon | | | | | | | | | | | | | 64.33 10 | | | | |
|
ITE_SJBPF | | | | | 78.22 33 | 81.77 36 | 60.57 36 | | 83.30 34 | 69.25 21 | 67.54 31 | 87.20 27 | 36.33 40 | 87.28 35 | 54.34 30 | 74.62 38 | 86.80 30 |
|