DeepPCF-MVS | | 80.84 1 | 88.10 1 | 88.56 1 | 86.73 6 | 92.24 6 | 69.03 12 | 89.57 13 | 93.39 4 | 77.53 2 | 89.79 1 | 94.12 2 | 78.98 1 | 96.58 4 | 85.66 1 | 95.72 1 | 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 9 | 93.94 1 | 77.12 4 | 82.82 4 | 94.23 1 | 72.13 3 | 97.09 1 | 84.83 2 | 95.37 2 | 93.65 4 |
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 3 | 93.04 6 | 76.62 6 | 84.22 2 | 93.36 5 | 71.44 4 | 96.76 2 | 80.82 4 | 95.33 3 | 94.16 3 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
CSCG | | | 86.41 4 | 86.19 4 | 87.07 5 | 92.91 4 | 72.48 4 | 90.81 5 | 93.56 3 | 73.95 11 | 83.16 3 | 91.07 11 | 75.94 2 | 95.19 7 | 79.94 5 | 94.38 4 | 93.55 5 |
|
ACMMwithACMP | | | 85.89 5 | 85.39 5 | 87.38 4 | 93.59 1 | 72.63 3 | 92.74 2 | 93.18 5 | 76.78 5 | 80.73 6 | 93.82 3 | 64.33 9 | 96.29 5 | 82.67 3 | 90.69 12 | 93.23 6 |
|
3Dnovator+ | | 77.84 4 | 85.48 6 | 84.47 6 | 88.51 1 | 91.08 10 | 73.49 1 | 93.18 1 | 93.78 2 | 80.79 1 | 76.66 15 | 93.37 4 | 60.40 16 | 96.75 3 | 77.20 7 | 93.73 5 | 95.29 1 |
|
MG-MVS | | | 83.41 7 | 83.45 7 | 83.28 19 | 92.74 5 | 62.28 28 | 88.17 21 | 89.50 17 | 75.22 8 | 81.49 5 | 92.74 7 | 66.75 5 | 95.11 8 | 72.85 12 | 91.58 8 | 92.45 8 |
|
3Dnovator | | 76.31 5 | 83.38 8 | 82.31 8 | 86.59 7 | 87.94 24 | 72.94 2 | 90.64 7 | 92.14 8 | 77.21 3 | 75.47 17 | 92.83 6 | 58.56 17 | 94.72 12 | 73.24 11 | 92.71 6 | 92.13 10 |
|
OMC-MVS | | | 82.69 9 | 81.97 9 | 84.85 10 | 88.75 19 | 67.42 19 | 87.98 23 | 90.87 15 | 74.92 9 | 79.72 7 | 91.65 9 | 62.19 14 | 93.96 17 | 75.26 9 | 86.42 19 | 93.16 7 |
|
CLD-MVS | | | 82.31 10 | 81.65 10 | 84.29 12 | 88.47 23 | 67.73 18 | 85.81 25 | 92.35 7 | 75.78 7 | 78.33 10 | 86.58 27 | 64.01 11 | 94.35 16 | 76.05 8 | 87.48 15 | 90.79 12 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
PHI-MVS | | | 81.99 11 | 81.23 11 | 84.26 13 | 90.94 11 | 70.18 9 | 91.10 4 | 89.32 19 | 71.51 12 | 78.66 8 | 88.28 21 | 65.26 8 | 95.10 9 | 64.74 14 | 91.23 9 | 87.51 24 |
|
MAR-MVS | | | 81.84 12 | 80.70 12 | 85.27 8 | 91.32 8 | 71.53 7 | 89.82 12 | 90.92 14 | 69.77 18 | 78.50 9 | 86.21 28 | 62.36 13 | 94.52 15 | 65.36 13 | 92.05 7 | 89.77 14 |
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 13 | 80.57 13 | 84.36 11 | 89.42 16 | 68.69 15 | 89.97 11 | 91.50 11 | 74.46 10 | 75.04 18 | 90.41 13 | 53.82 21 | 94.54 13 | 77.56 6 | 82.91 22 | 89.86 13 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
0120 | | | 81.07 14 | 80.32 14 | 83.34 18 | 90.91 12 | 70.11 10 | 90.80 6 | 88.83 24 | 71.17 13 | 78.06 11 | 83.31 33 | 65.55 7 | 94.73 11 | 63.34 15 | 90.88 11 | 85.18 30 |
|
ACMM | | 73.20 8 | 80.78 15 | 79.84 15 | 83.58 16 | 89.31 17 | 68.37 16 | 89.99 10 | 91.60 9 | 70.28 15 | 77.25 13 | 89.66 16 | 53.37 23 | 93.53 21 | 74.24 10 | 82.85 23 | 88.85 16 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
AdaColmap |  | | 80.58 16 | 79.42 16 | 84.06 15 | 93.09 3 | 68.91 14 | 89.36 14 | 88.97 23 | 69.27 19 | 75.70 16 | 89.69 15 | 57.20 19 | 95.77 6 | 63.06 16 | 88.41 13 | 87.50 25 |
|
PCF-MVS | | 73.52 7 | 80.38 17 | 78.84 17 | 85.01 9 | 87.71 25 | 68.99 13 | 83.65 29 | 91.46 12 | 63.00 29 | 77.77 12 | 90.28 14 | 66.10 6 | 95.09 10 | 61.40 19 | 88.22 14 | 90.94 11 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
OpenMVS |  | 72.83 10 | 79.77 18 | 78.33 18 | 84.09 14 | 85.17 29 | 69.91 11 | 90.57 8 | 90.97 13 | 66.70 21 | 72.17 20 | 91.91 8 | 54.70 20 | 93.96 17 | 61.81 18 | 90.95 10 | 88.41 19 |
|
TAPA-MVS | | 73.13 9 | 79.15 19 | 77.94 19 | 82.79 21 | 89.59 15 | 62.99 27 | 88.16 22 | 91.51 10 | 65.77 23 | 77.14 14 | 91.09 10 | 60.91 15 | 93.21 22 | 50.26 33 | 87.05 16 | 92.17 9 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
CNLPA | | | 78.08 20 | 76.79 20 | 81.97 24 | 90.40 14 | 71.07 8 | 87.59 24 | 84.55 29 | 66.03 22 | 72.38 19 | 89.64 17 | 57.56 18 | 86.04 35 | 59.61 20 | 83.35 21 | 88.79 17 |
|
PLC |  | 70.83 11 | 78.05 21 | 76.37 22 | 83.08 20 | 91.88 7 | 67.80 17 | 88.19 20 | 89.46 18 | 64.33 26 | 69.87 24 | 88.38 20 | 53.66 22 | 93.58 20 | 58.86 21 | 82.73 24 | 87.86 21 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
PAPM | | | 77.68 22 | 76.40 21 | 81.51 26 | 87.29 26 | 61.85 29 | 83.78 28 | 89.59 16 | 64.74 25 | 71.23 22 | 88.70 18 | 62.59 12 | 93.66 19 | 52.66 31 | 87.03 17 | 89.01 15 |
|
LS3D | | | 76.95 23 | 74.82 23 | 83.37 17 | 90.45 13 | 67.36 20 | 89.15 15 | 86.94 26 | 61.87 32 | 69.52 26 | 90.61 12 | 51.71 24 | 94.53 14 | 46.38 37 | 86.71 18 | 88.21 20 |
|
F-COLMAP | | | 76.38 24 | 74.33 25 | 82.50 22 | 89.28 18 | 66.95 21 | 88.41 18 | 89.03 21 | 64.05 28 | 66.83 29 | 88.61 19 | 46.78 27 | 92.89 25 | 57.48 23 | 78.55 27 | 87.67 22 |
|
LTVRE_ROB | | 69.57 12 | 76.25 25 | 74.54 24 | 81.41 27 | 88.60 21 | 64.38 26 | 79.24 34 | 89.12 20 | 70.76 14 | 69.79 25 | 87.86 22 | 49.09 26 | 93.20 23 | 56.21 25 | 80.16 26 | 86.65 29 |
Andreas Kuhn, Heiko HirschmĂĽller, 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 26 | 74.01 26 | 82.03 23 | 88.60 21 | 65.31 25 | 88.86 16 | 87.55 25 | 70.25 16 | 67.75 27 | 87.47 24 | 41.27 33 | 93.19 24 | 58.37 22 | 75.94 33 | 87.60 23 |
|
ACMH | | 67.68 14 | 75.89 27 | 73.93 27 | 81.77 25 | 88.71 20 | 66.61 22 | 88.62 17 | 89.01 22 | 69.81 17 | 66.78 30 | 86.70 26 | 41.95 32 | 91.51 27 | 55.64 26 | 78.14 28 | 87.17 27 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
MSDG | | | 73.36 28 | 70.99 29 | 80.49 29 | 84.51 30 | 65.80 23 | 80.71 30 | 86.13 28 | 65.70 24 | 65.46 31 | 83.74 32 | 44.60 28 | 90.91 29 | 51.13 32 | 76.89 29 | 84.74 32 |
|
PatchmatchNet | | | 73.12 29 | 71.33 28 | 78.49 30 | 83.18 31 | 60.85 31 | 79.63 32 | 78.57 39 | 64.13 27 | 71.73 21 | 79.81 38 | 51.20 25 | 85.97 36 | 57.40 24 | 76.36 30 | 88.66 18 |
|
COLMAP_ROB |  | 66.92 15 | 73.01 30 | 70.41 31 | 80.81 28 | 87.13 27 | 65.63 24 | 88.30 19 | 84.19 30 | 62.96 30 | 63.80 33 | 87.69 23 | 38.04 34 | 92.56 26 | 46.66 36 | 74.91 34 | 84.24 33 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
PVSNet | | 64.34 16 | 72.08 31 | 70.87 30 | 75.69 36 | 86.21 28 | 56.44 37 | 74.37 37 | 80.73 37 | 62.06 31 | 70.17 23 | 82.23 36 | 42.86 31 | 83.31 37 | 54.77 27 | 84.45 20 | 87.32 26 |
|
OpenMVS_ROB |  | 64.09 17 | 70.56 32 | 68.19 33 | 77.65 32 | 80.26 35 | 59.41 33 | 85.01 26 | 82.96 34 | 58.76 37 | 65.43 32 | 82.33 35 | 37.63 35 | 91.23 28 | 45.34 39 | 76.03 32 | 82.32 35 |
|
USDC | | | 70.33 33 | 68.37 32 | 76.21 35 | 80.60 34 | 56.23 38 | 79.19 35 | 86.49 27 | 60.89 34 | 61.29 34 | 85.47 29 | 31.78 37 | 89.47 30 | 53.37 29 | 76.21 31 | 82.94 34 |
|
CMPMVS |  | 51.72 19 | 70.19 34 | 68.16 34 | 76.28 34 | 73.15 39 | 57.55 34 | 79.47 33 | 83.92 31 | 48.02 40 | 56.48 38 | 84.81 31 | 43.13 30 | 86.42 34 | 62.67 17 | 81.81 25 | 84.89 31 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
TDRefinement | | | 67.49 35 | 64.34 36 | 76.92 33 | 73.47 38 | 61.07 30 | 84.86 27 | 82.98 33 | 59.77 36 | 58.30 37 | 85.13 30 | 26.06 38 | 87.89 31 | 47.92 34 | 60.59 39 | 81.81 36 |
|
TinyColmap | | | 67.30 36 | 64.81 35 | 74.76 37 | 81.92 32 | 56.68 36 | 80.29 31 | 81.49 35 | 60.33 35 | 56.27 39 | 83.22 34 | 24.77 39 | 87.66 32 | 45.52 38 | 69.47 36 | 79.95 37 |
|
LF4IMVS | | | 64.02 37 | 62.19 37 | 69.50 38 | 70.90 40 | 53.29 39 | 76.13 36 | 77.18 40 | 52.65 39 | 58.59 35 | 80.98 37 | 23.55 40 | 76.52 39 | 53.06 30 | 66.66 37 | 78.68 39 |
|
PVSNet_0 | | 57.27 18 | 61.67 38 | 59.27 38 | 68.85 39 | 79.61 36 | 57.44 35 | 68.01 40 | 73.44 41 | 55.93 38 | 58.54 36 | 70.41 40 | 44.58 29 | 77.55 38 | 47.01 35 | 35.91 42 | 71.55 40 |
|
FPMVS | | | 53.68 39 | 51.64 39 | 59.81 41 | 65.08 41 | 51.03 41 | 69.48 39 | 69.58 42 | 41.46 41 | 40.67 40 | 72.32 39 | 16.46 42 | 70.00 44 | 24.24 43 | 65.42 38 | 58.40 42 |
|
ANet_high | | | 50.57 40 | 46.10 40 | 63.99 40 | 48.67 44 | 39.13 44 | 70.99 38 | 80.85 36 | 61.39 33 | 31.18 41 | 57.70 41 | 17.02 41 | 73.65 42 | 31.22 41 | 15.89 47 | 79.18 38 |
|
Gipuma |  | | 45.18 41 | 41.86 41 | 55.16 44 | 77.03 37 | 51.52 40 | 32.50 45 | 80.52 38 | 32.46 43 | 27.12 42 | 35.02 46 | 9.52 44 | 75.50 41 | 22.31 44 | 60.21 40 | 38.45 46 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
PMVS |  | 37.38 20 | 44.16 42 | 40.28 42 | 55.82 43 | 40.82 47 | 42.54 43 | 65.12 41 | 63.99 44 | 34.43 42 | 24.48 43 | 57.12 42 | 3.92 45 | 76.17 40 | 17.10 46 | 55.52 41 | 48.75 43 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
wuykxyi23d | | | 39.76 43 | 33.18 44 | 59.51 42 | 46.98 45 | 44.01 42 | 57.70 43 | 67.74 43 | 24.13 45 | 13.98 47 | 34.33 47 | 1.27 48 | 71.33 43 | 34.23 40 | 18.23 45 | 63.18 41 |
|
PNet_i23d | | | 38.26 44 | 35.42 43 | 46.79 45 | 58.74 42 | 35.48 45 | 59.65 42 | 51.25 45 | 32.45 44 | 23.44 45 | 47.53 44 | 2.04 47 | 58.96 45 | 25.60 42 | 18.09 46 | 45.92 45 |
|
MVE |  | 26.22 21 | 30.37 45 | 25.89 45 | 43.81 46 | 44.55 46 | 35.46 46 | 28.87 46 | 39.07 46 | 18.20 46 | 18.58 46 | 40.18 45 | 2.68 46 | 47.37 46 | 17.07 47 | 23.78 44 | 48.60 44 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
wuyk23d | | | 16.82 46 | 15.94 46 | 19.46 48 | 58.74 42 | 31.45 47 | 39.22 44 | 3.74 48 | 6.84 48 | 6.04 48 | 2.70 48 | 1.27 48 | 24.29 48 | 10.54 48 | 14.40 48 | 2.63 48 |
|
ITE_SJBPF | | | | | 78.22 31 | 81.77 33 | 60.57 32 | | 83.30 32 | 69.25 20 | 67.54 28 | 87.20 25 | 36.33 36 | 87.28 33 | 54.34 28 | 74.62 35 | 86.80 28 |
|
Test By Simon | | | | | | | | | | | | | 64.33 9 | | | | |
|
DeepMVS_CX |  | | | | 27.40 47 | 40.17 48 | 26.90 48 | | 24.59 47 | 17.44 47 | 23.95 44 | 48.61 43 | 9.77 43 | 26.48 47 | 18.06 45 | 24.47 43 | 28.83 47 |
|