TDRefinement | | | 93.52 1 | 93.39 2 | 93.88 1 | 95.94 2 | 90.26 3 | 95.70 2 | 96.46 1 | 90.58 2 | 92.86 8 | 96.29 4 | 88.16 8 | 94.17 10 | 86.07 3 | 98.48 4 | 97.22 1 |
|
LTVRE_ROB | | 86.10 1 | 93.04 2 | 93.44 1 | 91.82 4 | 93.73 6 | 85.72 6 | 96.79 1 | 95.51 3 | 88.86 5 | 95.63 2 | 96.99 2 | 84.81 12 | 93.16 16 | 91.10 1 | 97.53 11 | 96.58 2 |
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 |
COLMAP_ROB |  | 83.01 3 | 91.97 3 | 91.95 3 | 92.04 2 | 93.68 7 | 86.15 4 | 93.37 4 | 95.10 4 | 90.28 3 | 92.11 10 | 95.03 8 | 89.75 6 | 94.93 7 | 79.95 11 | 98.27 7 | 95.04 7 |
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016 |
ACMMwithACMP | | | 91.91 4 | 91.87 4 | 92.03 3 | 95.53 3 | 85.91 5 | 93.35 5 | 94.16 7 | 82.52 10 | 92.39 9 | 94.14 13 | 89.15 7 | 95.62 3 | 87.35 2 | 98.24 8 | 94.56 9 |
|
ACMH+ | | 77.89 11 | 90.73 5 | 91.50 5 | 88.44 14 | 93.00 9 | 76.26 23 | 89.65 8 | 95.55 2 | 87.72 7 | 93.89 5 | 94.94 9 | 91.62 1 | 93.44 12 | 78.35 14 | 98.76 2 | 95.61 4 |
|
ACMM | | 79.39 9 | 90.65 6 | 90.99 7 | 89.63 11 | 95.03 4 | 83.53 12 | 89.62 9 | 93.35 12 | 79.20 14 | 93.83 6 | 93.60 16 | 90.81 3 | 92.96 17 | 85.02 4 | 98.45 5 | 92.41 16 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
LS3D | | | 90.60 7 | 90.34 10 | 91.38 5 | 89.03 24 | 84.23 10 | 93.58 3 | 94.68 5 | 90.65 1 | 90.33 12 | 93.95 14 | 84.50 13 | 95.37 4 | 80.87 10 | 95.50 21 | 94.53 11 |
|
ACMP | | 79.16 10 | 90.54 8 | 90.60 9 | 90.35 8 | 94.36 5 | 80.98 16 | 89.16 12 | 94.05 9 | 79.03 16 | 92.87 7 | 93.74 15 | 90.60 5 | 95.21 5 | 82.87 8 | 98.76 2 | 94.87 8 |
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020 |
PMVS |  | 80.48 6 | 90.08 9 | 90.66 8 | 88.34 16 | 96.71 1 | 92.97 2 | 90.31 7 | 89.57 26 | 88.51 6 | 90.11 13 | 95.12 7 | 90.98 2 | 88.92 29 | 77.55 17 | 97.07 13 | 83.13 37 |
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010) |
3Dnovator+ | | 83.92 2 | 89.97 10 | 89.66 11 | 90.92 6 | 91.27 15 | 81.66 15 | 91.25 6 | 94.13 8 | 88.89 4 | 88.83 18 | 94.26 12 | 77.55 26 | 95.86 1 | 84.88 5 | 95.87 18 | 95.24 6 |
|
ACMH | | 76.49 14 | 89.34 11 | 91.14 6 | 83.96 27 | 92.50 10 | 70.36 30 | 89.55 10 | 93.84 10 | 81.89 11 | 94.70 4 | 95.44 5 | 90.69 4 | 88.31 31 | 83.33 7 | 98.30 6 | 93.20 15 |
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019 |
DeepC-MVS | | 82.31 4 | 89.15 12 | 89.08 12 | 89.37 13 | 93.64 8 | 79.07 20 | 88.54 16 | 94.20 6 | 73.53 25 | 89.71 15 | 94.82 11 | 85.09 11 | 95.77 2 | 84.17 6 | 98.03 9 | 93.26 13 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
wuykxyi23d | | | 88.46 13 | 88.80 13 | 87.44 19 | 90.96 16 | 93.03 1 | 85.85 25 | 81.96 40 | 74.58 24 | 98.58 1 | 97.29 1 | 87.73 9 | 87.31 32 | 82.84 9 | 99.41 1 | 81.99 40 |
|
OMC-MVS | | | 88.19 14 | 87.52 14 | 90.19 9 | 91.94 12 | 81.68 14 | 87.49 20 | 93.17 13 | 76.02 21 | 88.64 19 | 91.22 22 | 84.24 14 | 93.37 13 | 77.97 16 | 97.03 14 | 95.52 5 |
|
DeepPCF-MVS | | 81.24 5 | 87.28 15 | 86.21 17 | 90.49 7 | 91.48 13 | 84.90 9 | 83.41 29 | 92.38 16 | 70.25 31 | 89.35 17 | 90.68 25 | 82.85 16 | 94.57 8 | 79.55 12 | 95.95 16 | 92.00 18 |
|
CSCG | | | 86.26 16 | 86.47 15 | 85.60 21 | 90.87 17 | 74.26 26 | 87.98 18 | 91.85 19 | 80.35 13 | 89.54 16 | 88.01 30 | 79.09 22 | 92.13 21 | 75.51 19 | 95.06 24 | 90.41 21 |
|
DeepC-MVS_fast | | 80.27 8 | 86.23 17 | 85.65 19 | 87.96 17 | 91.30 14 | 76.92 22 | 87.19 21 | 91.99 17 | 70.56 30 | 84.96 25 | 90.69 24 | 80.01 21 | 95.14 6 | 78.37 13 | 95.78 19 | 91.82 19 |
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020 |
TAPA-MVS | | 77.73 12 | 85.71 18 | 84.83 20 | 88.37 15 | 88.78 25 | 79.72 19 | 87.15 22 | 93.50 11 | 69.17 32 | 85.80 22 | 89.56 27 | 80.76 19 | 92.13 21 | 73.21 22 | 95.51 20 | 93.25 14 |
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019 |
F-COLMAP | | | 84.97 19 | 83.42 23 | 89.63 11 | 92.39 11 | 83.40 13 | 88.83 13 | 91.92 18 | 73.19 26 | 80.18 35 | 89.15 28 | 77.04 28 | 93.28 15 | 65.82 28 | 92.28 31 | 92.21 17 |
|
3Dnovator | | 80.37 7 | 84.80 20 | 84.71 21 | 85.06 23 | 86.36 30 | 74.71 25 | 88.77 14 | 90.00 24 | 75.65 22 | 84.96 25 | 93.17 17 | 74.06 33 | 91.19 24 | 78.28 15 | 91.09 34 | 89.29 24 |
|
Gipuma |  | | 84.44 21 | 86.33 16 | 78.78 34 | 84.20 36 | 73.57 27 | 89.55 10 | 90.44 22 | 84.24 8 | 84.38 27 | 94.89 10 | 76.35 30 | 80.40 40 | 76.14 18 | 96.80 15 | 82.36 39 |
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015 |
AdaColmap |  | | 83.66 22 | 83.69 22 | 83.57 28 | 90.05 20 | 72.26 29 | 86.29 23 | 90.00 24 | 78.19 18 | 81.65 34 | 87.16 35 | 83.40 15 | 94.24 9 | 61.69 34 | 94.76 25 | 84.21 35 |
|
CNLPA | | | 83.55 23 | 83.10 24 | 84.90 24 | 89.34 22 | 83.87 11 | 84.54 28 | 88.77 29 | 79.09 15 | 83.54 29 | 88.66 29 | 74.87 32 | 81.73 39 | 66.84 27 | 92.29 30 | 89.11 25 |
|
CLD-MVS | | | 83.18 24 | 82.64 25 | 84.79 25 | 89.05 23 | 67.82 35 | 77.93 39 | 92.52 15 | 68.33 33 | 85.07 24 | 81.54 42 | 82.06 18 | 92.96 17 | 69.35 25 | 97.91 10 | 93.57 12 |
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020 |
ANet_high | | | 83.17 25 | 85.68 18 | 75.65 40 | 81.24 41 | 45.26 46 | 79.94 37 | 92.91 14 | 83.83 9 | 91.33 11 | 96.88 3 | 80.25 20 | 85.92 37 | 68.89 26 | 95.89 17 | 95.76 3 |
|
LF4IMVS | | | 82.75 26 | 81.93 29 | 85.19 22 | 82.08 39 | 80.15 18 | 85.53 27 | 88.76 30 | 68.01 35 | 85.58 23 | 87.75 31 | 71.80 37 | 86.85 34 | 74.02 20 | 93.87 28 | 88.58 27 |
|
PHI-MVS | | | 82.28 27 | 82.61 26 | 81.30 30 | 86.29 31 | 69.79 31 | 88.71 15 | 87.67 34 | 78.42 17 | 82.15 31 | 84.15 38 | 77.98 24 | 91.59 23 | 65.39 29 | 92.75 29 | 82.51 38 |
|
PCF-MVS | | 74.62 15 | 82.15 28 | 80.92 31 | 85.84 20 | 89.43 21 | 72.30 28 | 80.53 35 | 91.82 20 | 57.36 41 | 87.81 20 | 89.92 26 | 77.67 25 | 93.63 11 | 58.69 39 | 95.08 23 | 91.58 20 |
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019 |
PLC |  | 73.85 16 | 82.09 29 | 80.31 33 | 87.45 18 | 90.86 18 | 80.29 17 | 85.88 24 | 90.65 21 | 68.17 34 | 76.32 41 | 86.33 36 | 73.12 35 | 92.61 19 | 61.40 36 | 90.02 37 | 89.44 23 |
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019 |
OpenMVS |  | 76.72 13 | 81.98 30 | 82.00 28 | 81.93 29 | 84.42 34 | 68.22 33 | 88.50 17 | 89.48 27 | 66.92 37 | 81.80 33 | 91.86 20 | 72.59 36 | 90.16 28 | 71.19 23 | 91.25 33 | 87.40 28 |
|
TinyColmap | | | 81.25 31 | 82.34 27 | 77.99 37 | 85.33 33 | 60.68 38 | 82.32 30 | 88.33 31 | 71.26 29 | 86.97 21 | 92.22 19 | 77.10 27 | 86.98 33 | 62.37 32 | 95.17 22 | 86.31 31 |
|
MG-MVS | | | 80.32 32 | 80.94 30 | 78.47 36 | 88.18 27 | 52.62 43 | 82.29 31 | 85.01 37 | 72.01 27 | 79.24 37 | 92.54 18 | 69.36 38 | 93.36 14 | 70.65 24 | 89.19 38 | 89.45 22 |
|
MAR-MVS | | | 80.24 33 | 78.74 36 | 84.73 26 | 86.87 28 | 78.18 21 | 85.75 26 | 87.81 33 | 65.67 38 | 77.84 38 | 78.50 43 | 73.79 34 | 90.53 27 | 61.59 35 | 90.87 35 | 85.49 32 |
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 |
0120 | | | 80.19 34 | 80.52 32 | 79.23 33 | 85.76 32 | 68.78 32 | 87.50 19 | 86.24 36 | 76.48 20 | 79.57 36 | 81.58 41 | 75.60 31 | 90.81 25 | 60.61 38 | 91.30 32 | 78.11 42 |
|
MSDG | | | 80.06 35 | 79.99 34 | 80.25 31 | 83.91 37 | 68.04 34 | 77.51 40 | 89.19 28 | 77.65 19 | 81.94 32 | 83.45 39 | 76.37 29 | 86.31 36 | 63.31 31 | 86.59 39 | 86.41 29 |
|
OpenMVS_ROB |  | 70.19 17 | 77.77 36 | 77.46 37 | 78.71 35 | 84.39 35 | 61.15 37 | 81.18 33 | 82.52 38 | 62.45 39 | 83.34 30 | 87.37 34 | 66.20 39 | 88.66 30 | 64.69 30 | 85.02 40 | 86.32 30 |
|
USDC | | | 76.63 37 | 76.73 38 | 76.34 39 | 83.46 38 | 57.20 39 | 80.02 36 | 88.04 32 | 52.14 43 | 83.65 28 | 91.25 21 | 63.24 40 | 86.65 35 | 54.66 40 | 94.11 27 | 85.17 33 |
|
wuyk23d | | | 75.13 38 | 79.30 35 | 62.63 44 | 75.56 44 | 75.18 24 | 80.89 34 | 73.10 41 | 75.06 23 | 94.76 3 | 95.32 6 | 87.73 9 | 52.85 46 | 34.16 46 | 97.11 12 | 59.85 44 |
|
CMPMVS |  | 59.41 18 | 75.12 39 | 73.57 39 | 79.77 32 | 75.84 43 | 67.22 36 | 81.21 32 | 82.18 39 | 50.78 45 | 76.50 40 | 87.66 32 | 55.20 43 | 82.99 38 | 62.17 33 | 90.64 36 | 89.09 26 |
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011 |
FPMVS | | | 72.29 40 | 72.00 40 | 73.14 41 | 88.63 26 | 85.00 7 | 74.65 42 | 67.39 44 | 71.94 28 | 77.80 39 | 87.66 32 | 50.48 46 | 75.83 42 | 49.95 41 | 79.51 43 | 58.58 46 |
|
PAPM | | | 71.77 41 | 70.06 41 | 76.92 38 | 86.39 29 | 53.97 40 | 76.62 41 | 86.62 35 | 53.44 42 | 63.97 44 | 84.73 37 | 57.79 41 | 92.34 20 | 39.65 43 | 81.33 42 | 84.45 34 |
|
PatchmatchNet | | | 69.71 42 | 68.83 42 | 72.33 42 | 77.66 42 | 53.60 41 | 79.29 38 | 69.99 43 | 57.66 40 | 72.53 42 | 82.93 40 | 46.45 47 | 80.08 41 | 60.91 37 | 72.09 44 | 83.31 36 |
|
PVSNet | | 58.17 19 | 66.41 43 | 65.63 43 | 68.75 43 | 81.96 40 | 49.88 45 | 62.19 43 | 72.51 42 | 51.03 44 | 68.04 43 | 75.34 44 | 50.84 45 | 74.77 43 | 45.82 42 | 82.96 41 | 81.60 41 |
|
PVSNet_0 | | 51.08 20 | 56.10 44 | 54.97 44 | 59.48 45 | 75.12 46 | 53.28 42 | 55.16 44 | 61.89 45 | 44.30 46 | 59.16 45 | 62.48 47 | 54.22 44 | 65.91 44 | 35.40 45 | 47.01 46 | 59.25 45 |
|
PNet_i23d | | | 52.13 45 | 51.24 45 | 54.79 47 | 75.56 44 | 45.26 46 | 54.54 45 | 52.55 46 | 66.95 36 | 57.19 46 | 65.82 46 | 13.15 49 | 63.40 45 | 36.39 44 | 39.04 47 | 55.71 47 |
|
MVE |  | 40.22 21 | 51.82 46 | 50.47 46 | 55.87 46 | 62.66 47 | 51.91 44 | 31.61 46 | 39.28 47 | 40.65 47 | 50.76 47 | 74.98 45 | 56.24 42 | 44.67 47 | 33.94 47 | 64.11 45 | 71.04 43 |
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014) |
ITE_SJBPF | | | | | 90.11 10 | 90.72 19 | 84.97 8 | | 90.30 23 | 81.56 12 | 90.02 14 | 91.20 23 | 82.40 17 | 90.81 25 | 73.58 21 | 94.66 26 | 94.56 9 |
|
Test By Simon | | | | | | | | | | | | | 79.09 22 | | | | |
|
DeepMVS_CX |  | | | | 24.13 48 | 32.95 48 | 29.49 48 | | 21.63 48 | 12.07 48 | 37.95 48 | 45.07 48 | 30.84 48 | 19.21 48 | 17.94 48 | 33.06 48 | 23.69 48 |
|