This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
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SteuartSystems-ACMMP99.54 199.42 199.87 199.82 999.81 199.59 2799.51 4798.62 1499.79 599.83 2699.28 199.97 598.48 4499.90 1299.84 5
Skip Steuart: Steuart Systems R&D Blog.
HPM-MVS_fast99.51 299.40 399.85 299.91 199.79 299.76 1399.56 2697.72 4899.76 999.75 4699.13 299.92 2299.07 1099.92 499.85 3
DeepC-MVS_fast98.69 199.49 399.39 499.77 1299.63 3899.59 1499.36 6999.46 6699.07 799.79 599.82 3098.85 599.92 2298.68 3499.87 2099.82 9
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DELS-MVS99.48 499.42 199.65 2099.72 2599.40 2599.05 10599.66 1599.14 599.57 2699.80 3798.46 1799.94 1499.57 199.84 2999.60 45
ACMMPcopyleft99.45 599.32 799.82 699.89 399.67 999.62 2199.69 1398.12 2799.63 1999.84 2498.73 1199.96 898.55 4099.83 3299.81 10
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
CP-MVS99.45 599.32 799.85 299.83 899.75 499.69 1999.52 4298.07 3299.53 3199.63 6698.93 399.97 598.74 3099.91 699.83 8
HPM-MVS99.42 799.28 1199.83 599.90 299.72 699.81 799.54 3697.59 5299.68 1299.63 6698.91 499.94 1498.58 3799.91 699.84 5
MVS_111021_LR99.41 899.33 699.65 2099.77 1599.51 2098.94 11699.85 498.82 1299.65 1899.74 4898.51 1599.80 5798.83 2899.89 1799.64 42
MVS_111021_HR99.41 899.32 799.66 1799.72 2599.47 2198.95 11599.85 498.82 1299.54 3099.73 4998.51 1599.74 6698.91 2099.88 1899.77 18
PVSNet_Blended_VisFu99.36 1099.28 1199.61 2599.86 599.07 3899.47 4799.93 197.66 5199.71 1099.86 1897.73 3299.96 899.47 299.82 3399.79 16
NCCC99.34 1199.19 1399.79 1099.61 4199.65 1399.30 7899.48 5698.86 1199.21 6199.63 6698.72 1299.90 3198.25 5399.63 4699.80 14
CSCG99.32 1299.32 799.32 5099.85 698.29 6699.71 1799.66 1598.11 2899.41 4499.80 3798.37 2099.96 898.99 1599.96 299.72 26
DeepC-MVS98.35 299.30 1399.19 1399.64 2399.82 999.23 3199.62 2199.55 3098.94 1099.63 1999.95 195.82 5999.94 1499.37 399.97 199.73 22
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PHI-MVS99.30 1399.17 1599.70 1699.56 4899.52 1999.58 2999.80 697.12 7999.62 2299.73 4998.58 1499.90 3198.61 3699.91 699.68 32
LS3D99.27 1599.12 1699.74 1399.18 9099.75 499.56 3599.57 2498.45 1999.49 3699.85 2197.77 3199.94 1498.33 5099.84 2999.52 57
APD-MVS99.27 1599.08 1899.84 499.75 2099.79 299.50 4499.50 5197.16 7699.77 899.82 3098.78 699.94 1497.56 8099.86 2299.80 14
3Dnovator97.25 999.24 1799.05 2099.81 899.12 10099.66 1199.84 599.74 899.09 698.92 8399.90 595.94 5599.98 298.95 1899.92 499.79 16
F-COLMAP99.19 1899.04 2299.64 2399.78 1399.27 3099.42 6199.54 3697.29 7099.41 4499.59 7398.42 1999.93 2098.19 5499.69 4399.73 22
3Dnovator+97.12 1399.18 1998.97 3199.82 699.17 9399.68 899.81 799.51 4799.20 498.72 9699.89 795.68 6399.97 598.86 2599.86 2299.81 10
MVSFormer99.17 2099.12 1699.29 5399.51 5098.94 4799.88 199.46 6697.55 5699.80 399.65 6197.39 3599.28 10999.03 1199.85 2499.65 38
sss99.17 2099.05 2099.53 3499.62 3998.97 4599.36 6999.62 1897.83 4399.67 1399.65 6197.37 3899.95 1399.19 699.19 5499.68 32
DP-MVS99.16 2298.95 3499.78 1199.77 1599.53 1699.41 6399.50 5197.03 8399.04 7699.88 1097.39 3599.92 2298.66 3599.90 1299.87 1
CNLPA99.14 2398.99 2999.59 2799.58 4599.41 2499.16 9599.44 7398.45 1999.19 6499.49 8798.08 2499.89 3797.73 7499.75 3999.48 60
MG-MVS99.13 2499.02 2799.45 4499.57 4798.63 6099.07 10299.34 8798.99 999.61 2399.82 3097.98 2799.87 4197.00 9699.80 3599.85 3
EPP-MVSNet99.13 2498.99 2999.53 3499.65 3699.06 3999.81 799.33 8897.43 6499.60 2499.88 1097.14 4199.84 4899.13 998.94 6099.69 29
jason99.13 2499.03 2499.45 4499.46 5698.87 5199.12 9899.26 9398.03 3799.79 599.65 6197.02 4499.85 4699.02 1399.90 1299.65 38
jason: jason.
lupinMVS99.13 2499.01 2899.46 4399.51 5098.94 4799.05 10599.16 10097.86 4199.80 399.56 8197.39 3599.86 4398.94 1999.85 2499.58 48
Vis-MVSNetpermissive99.12 2898.97 3199.56 3199.78 1399.10 3599.68 2099.66 1598.49 1899.86 199.87 1594.77 7399.84 4899.19 699.41 5199.74 20
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
TAMVS99.12 2899.08 1899.24 5599.46 5698.55 6199.51 4399.46 6698.09 3099.45 3999.82 3098.34 2199.51 9998.70 3298.93 6199.67 35
DP-MVS Recon99.12 2898.95 3499.65 2099.74 2199.70 799.27 8499.57 2496.40 10799.42 4299.68 5898.75 999.80 5797.98 6599.72 4099.44 65
CPTT-MVS99.11 3198.90 3699.74 1399.80 1299.46 2299.59 2799.49 5497.03 8399.63 1999.69 5797.27 3999.96 897.82 6999.84 2999.81 10
CDS-MVSNet99.09 3299.03 2499.25 5499.42 6098.73 5799.45 4899.46 6698.11 2899.46 3899.77 4498.01 2699.37 10398.70 3298.92 6499.66 36
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PVSNet_Blended99.08 3398.97 3199.42 4699.76 1798.79 5598.78 12199.91 296.74 9199.67 1399.49 8797.53 3399.88 3998.98 1699.85 2499.60 45
OMC-MVS99.08 3399.04 2299.20 5799.67 3498.22 6899.28 8299.52 4298.07 3299.66 1699.81 3497.79 3099.78 6197.79 7199.81 3499.60 45
WTY-MVS99.06 3598.88 3799.61 2599.62 3999.16 3499.37 6799.56 2698.04 3699.53 3199.62 7196.84 4699.94 1498.85 2698.49 8299.72 26
IS-MVSNet99.05 3698.87 3899.57 2999.73 2399.32 2699.75 1499.20 9798.02 3899.56 2799.86 1896.54 4999.67 8598.09 6099.13 5699.73 22
API-MVS99.04 3799.03 2499.06 6099.40 6599.31 2899.55 3999.56 2698.54 1599.33 5199.39 9798.76 899.78 6196.98 9899.78 3698.07 131
PAPM_NR99.04 3798.84 4099.66 1799.74 2199.44 2399.39 6699.38 8297.70 4999.28 5499.28 10998.34 2199.85 4696.96 9999.45 5099.69 29
PLCcopyleft97.94 499.02 3998.85 3999.53 3499.66 3599.01 4399.24 9099.52 4296.85 8899.27 5699.48 8998.25 2399.91 2897.76 7299.62 4799.65 38
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
AdaColmapbinary99.01 4098.80 4299.66 1799.56 4899.54 1599.18 9499.70 1198.18 2699.35 5099.63 6696.32 5199.90 3197.48 8199.77 3799.55 50
1112_ss98.98 4198.77 4599.59 2799.68 3399.02 4199.25 8899.48 5697.23 7499.13 6799.58 7696.93 4599.90 3198.87 2398.78 7299.84 5
MSDG98.98 4198.80 4299.53 3499.76 1799.19 3298.75 12499.55 3097.25 7299.47 3799.77 4497.82 2999.87 4196.93 10199.90 1299.54 52
114514_t98.93 4398.67 5199.72 1599.85 699.53 1699.62 2199.59 2192.65 12899.71 1099.78 4298.06 2599.90 3198.84 2799.91 699.74 20
Test_1112_low_res98.89 4498.66 5299.57 2999.69 3298.95 4699.03 10899.47 6596.98 8599.15 6699.23 11196.77 4799.89 3798.83 2898.78 7299.86 2
UGNet98.87 4598.69 4999.40 4799.22 8598.72 5899.44 5299.68 1499.24 399.18 6599.42 9292.74 9599.96 899.34 499.94 399.53 55
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
Vis-MVSNet (Re-imp)98.87 4598.72 4799.31 5199.71 2798.88 5099.80 1099.44 7397.91 4099.36 4999.78 4295.49 6499.43 10297.91 6699.11 5799.62 44
COLMAP_ROBcopyleft97.56 698.86 4798.75 4699.17 5899.88 498.53 6299.34 7399.59 2197.55 5698.70 10099.89 795.83 5899.90 3198.10 5999.90 1299.08 84
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
MAR-MVS98.86 4798.63 5499.54 3299.37 6899.66 1199.45 4899.54 3696.61 9699.01 8099.40 9597.09 4299.86 4397.68 7799.53 4999.10 81
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
EPNet98.86 4798.71 4899.30 5297.20 14098.18 6999.62 2198.91 11899.28 298.63 10699.81 3495.96 5499.99 199.24 599.72 4099.73 22
ab-mvs98.86 4798.63 5499.54 3299.64 3799.19 3299.44 5299.54 3697.77 4699.30 5299.81 3494.20 8199.93 2099.17 898.82 7099.49 59
PVSNet_BlendedMVS98.86 4798.80 4299.03 6199.76 1798.79 5599.28 8299.91 297.42 6599.67 1399.37 10197.53 3399.88 3998.98 1697.29 11298.42 125
HY-MVS97.30 798.85 5298.64 5399.47 4199.42 6099.08 3799.62 2199.36 8597.39 6799.28 5499.68 5896.44 5099.92 2298.37 4898.22 8499.40 68
PVSNet96.02 1798.85 5298.84 4098.89 6699.73 2397.28 7998.32 13399.60 1997.86 4199.50 3499.57 7996.75 4899.86 4398.56 3899.70 4299.54 52
PatchMatch-RL98.84 5498.62 5699.52 3899.71 2799.28 2999.06 10399.77 797.74 4799.50 3499.53 8495.41 6599.84 4897.17 8999.64 4599.44 65
DeepPCF-MVS98.18 398.81 5599.37 597.12 12799.60 4391.75 13698.61 12899.44 7399.35 199.83 299.85 2198.70 1399.81 5699.02 1399.91 699.81 10
PMMVS98.80 5698.62 5699.34 4999.27 8198.70 5998.76 12399.31 9197.34 6999.21 6199.07 11997.20 4099.82 5398.56 3898.87 6799.52 57
XVG-OURS98.73 5798.68 5098.88 6899.70 3097.73 7498.92 11799.55 3098.52 1799.45 3999.84 2495.27 6799.91 2898.08 6398.84 6999.00 90
XVG-OURS-SEG-HR98.69 5898.62 5698.89 6699.71 2797.74 7399.12 9899.54 3698.44 2199.42 4299.71 5294.20 8199.92 2298.54 4298.90 6699.00 90
QAPM98.67 5998.30 6999.80 999.20 8799.67 999.77 1199.72 994.74 11598.73 9599.90 595.78 6099.98 296.96 9999.88 1899.76 19
test_djsdf98.67 5998.57 6098.98 6398.70 12598.91 4999.88 199.46 6697.55 5699.22 6099.88 1095.73 6299.28 10999.03 1197.62 9698.75 96
PAPR98.63 6198.34 6599.51 4099.40 6599.03 4098.80 12099.36 8596.33 10899.00 8199.12 11798.46 1799.84 4895.23 12099.37 5299.66 36
MVSTER98.49 6298.32 6799.00 6299.35 7199.02 4199.54 4099.38 8297.41 6699.20 6399.73 4993.86 8699.36 10598.87 2397.56 9898.62 109
OpenMVScopyleft96.50 1698.47 6398.12 7299.52 3899.04 11099.53 1699.82 699.72 994.56 11798.08 12099.88 1094.73 7499.98 297.47 8299.76 3899.06 86
IterMVS-LS98.46 6498.42 6298.58 7899.59 4498.00 7099.37 6799.43 7896.94 8799.07 7199.59 7397.87 2899.03 11998.32 5195.62 13498.71 97
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
BH-untuned98.42 6598.36 6398.59 7799.49 5596.70 9199.27 8499.13 10197.24 7398.80 9299.38 9895.75 6199.74 6697.07 9499.16 5599.33 71
BH-RMVSNet98.41 6698.08 7599.40 4799.41 6298.83 5499.30 7898.77 12297.70 4998.94 8299.65 6192.91 9399.74 6696.52 10499.55 4899.64 42
XXY-MVS98.38 6798.09 7499.24 5599.26 8299.32 2699.56 3599.55 3097.45 6398.71 9799.83 2693.23 8999.63 9298.88 2196.32 12698.76 95
ACMM97.58 598.37 6898.34 6598.48 8399.41 6297.10 8399.56 3599.45 7198.53 1699.04 7699.85 2193.00 9099.71 7998.74 3097.45 10498.64 107
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
tpmrst98.33 6998.48 6197.90 10899.16 9594.78 12099.31 7799.11 10297.27 7199.45 3999.59 7395.33 6699.84 4898.48 4498.61 7599.09 83
HyFIR98.32 7098.20 7098.70 7699.37 6897.58 7598.78 12199.59 2196.59 9899.03 7997.85 13697.08 4398.80 13295.59 11799.91 699.72 26
PatchmatchNetpermissive98.31 7198.36 6398.19 9799.16 9595.32 11299.27 8498.92 11597.37 6899.37 4899.58 7694.90 7199.70 8397.43 8599.21 5399.54 52
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
LPG-MVS_test98.22 7298.13 7198.49 8199.33 7397.05 8499.58 2999.55 3097.46 6199.24 5899.83 2692.58 9799.72 7498.09 6097.51 9998.68 99
RPSCF98.22 7298.62 5696.99 12899.82 991.58 13799.72 1599.44 7396.61 9699.66 1699.89 795.92 5699.82 5397.46 8399.10 5899.57 49
CR-MVSNet98.17 7497.93 8198.87 6999.18 9098.49 6399.22 9299.33 8896.96 8699.56 2799.38 9894.33 7899.00 12294.83 12498.58 7899.14 79
CLD-MVS98.16 7598.10 7398.33 8999.29 7896.82 8998.75 12499.44 7397.83 4399.13 6799.55 8292.92 9299.67 8598.32 5197.69 9598.48 123
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
ACMH97.28 898.10 7697.99 7898.44 8699.41 6296.96 8799.60 2699.56 2698.09 3098.15 11899.91 490.87 11299.70 8398.88 2197.45 10498.67 102
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMP97.20 1198.06 7797.94 8098.45 8599.37 6897.01 8699.44 5299.49 5497.54 5998.45 10999.79 4091.95 10399.72 7497.91 6697.49 10398.62 109
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
EPNet_dtu98.03 7897.96 7998.23 9598.27 13295.54 10899.23 9198.75 12399.02 897.82 12399.71 5296.11 5399.48 10093.04 12799.65 4499.69 29
FMVSNet398.03 7897.76 8898.84 7199.39 6798.98 4499.40 6599.38 8296.67 9499.07 7199.28 10992.93 9198.98 12597.10 9196.65 11998.56 119
LTVRE_ROB97.16 1298.02 8097.90 8298.40 8799.23 8496.80 9099.70 1899.60 1997.12 7998.18 11799.70 5491.73 10599.72 7498.39 4797.45 10498.68 99
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
PatchFormer-LS_test98.01 8198.05 7797.87 10999.15 9794.76 12199.42 6198.93 11397.12 7998.84 8998.59 13293.74 8899.80 5798.55 4098.17 8599.06 86
BH-w/o98.00 8297.89 8398.32 9099.35 7196.20 10199.01 11198.90 11996.42 10698.38 11199.00 12295.26 6899.72 7496.06 10998.61 7599.03 88
PT_06_test97.99 8398.08 7597.75 11498.82 12095.43 11199.57 3299.48 5696.83 9098.87 8698.79 12695.88 5799.15 11498.17 5596.29 12798.66 105
ACMH+97.24 1097.92 8497.78 8598.32 9099.46 5696.68 9399.56 3599.54 3698.41 2297.79 12599.87 1590.18 11999.66 8798.05 6497.18 11598.62 109
OurMVSNet-221017-097.88 8597.77 8698.19 9798.71 12496.53 9499.88 199.00 10997.79 4598.78 9399.94 291.68 10699.35 10697.21 8796.99 11798.69 98
XVG-ACMP-BASELINE97.83 8697.71 9098.20 9699.11 10196.33 9799.41 6399.52 4298.06 3599.05 7599.50 8689.64 12299.73 7297.73 7497.38 11098.53 120
IterMVS97.83 8697.77 8698.02 10299.58 4596.27 9999.02 10999.48 5697.22 7598.71 9799.70 5492.75 9499.13 11597.46 8396.00 13098.67 102
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
EPMVS97.82 8897.65 9198.35 8898.88 11895.98 10399.49 4594.71 14497.57 5599.26 5799.48 8992.46 10199.71 7997.87 6899.08 5999.35 69
TR-MVS97.76 8997.41 9998.82 7299.06 10897.87 7198.87 11998.56 13196.63 9598.68 10199.22 11292.49 9999.65 8895.40 11997.79 9398.95 93
dp97.75 9097.80 8497.59 11999.10 10493.71 12999.32 7498.88 12096.48 10499.08 7099.55 8292.67 9699.82 5396.52 10498.58 7899.24 76
Patchmtry97.75 9097.40 10098.81 7399.10 10498.87 5199.11 10199.33 8894.83 11498.81 9199.38 9894.33 7899.02 12096.10 10895.57 13598.53 120
TAPA-MVS97.07 1597.74 9297.34 10598.94 6499.70 3097.53 7699.25 8899.51 4791.90 13099.30 5299.63 6698.78 699.64 8988.09 13999.87 2099.65 38
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
MIMVSNet97.73 9397.45 9798.57 7999.45 5997.50 7799.02 10998.98 11096.11 11199.41 4499.14 11590.28 11598.74 13395.74 11398.93 6199.47 62
FMVSNet297.72 9497.36 10298.80 7499.51 5098.84 5399.45 4899.42 7996.49 10198.86 8899.29 10890.26 11698.98 12596.44 10696.56 12298.58 118
CostFormer97.72 9497.73 8997.71 11799.15 9794.02 12599.54 4099.02 10894.67 11699.04 7699.35 10292.35 10299.77 6398.50 4397.94 9199.34 70
cascas97.69 9697.43 9898.48 8398.60 12997.30 7898.18 13699.39 8092.96 12698.41 11098.78 12993.77 8799.27 11198.16 5698.61 7598.86 94
GBi-Net97.68 9797.48 9498.29 9299.51 5097.26 8099.43 5699.48 5696.49 10199.07 7199.32 10590.26 11698.98 12597.10 9196.65 11998.62 109
test197.68 9797.48 9498.29 9299.51 5097.26 8099.43 5699.48 5696.49 10199.07 7199.32 10590.26 11698.98 12597.10 9196.65 11998.62 109
tpm97.67 9997.55 9298.03 10099.02 11495.01 11799.43 5698.54 13296.44 10599.12 6999.34 10391.83 10499.60 9597.75 7396.46 12499.48 60
PCF-MVS97.08 1497.66 10097.06 11199.47 4199.61 4199.09 3698.04 13799.25 9591.24 13398.51 10899.70 5494.55 7699.91 2892.76 12899.85 2499.42 67
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
Test497.61 10197.50 9397.93 10699.03 11194.86 11899.72 1598.63 12996.59 9898.36 11299.57 7989.32 12399.74 6698.14 5798.16 8699.20 77
PAPM97.59 10297.09 11099.07 5999.06 10898.26 6798.30 13499.10 10394.88 11398.08 12099.34 10396.27 5299.64 8989.87 13598.92 6499.31 72
PatchFormer_test97.53 10397.40 10097.93 10699.03 11194.86 11899.57 3298.63 12996.59 9898.36 11298.79 12689.32 12399.74 6698.14 5798.16 8699.20 77
LF4IMVS97.52 10497.46 9697.70 11898.98 11695.55 10799.29 8198.82 12198.07 3298.66 10299.64 6589.97 12099.61 9497.01 9596.68 11897.94 134
JIA-IIPM97.50 10597.02 11298.93 6598.73 12197.80 7299.30 7898.97 11191.73 13198.91 8494.86 14195.10 7099.71 7997.58 7997.98 9099.28 74
SixPastTwentyTwo97.50 10597.33 10798.03 10098.65 12796.23 10099.77 1198.68 12897.14 7797.90 12299.93 390.45 11499.18 11397.00 9696.43 12598.67 102
tpm297.44 10797.34 10597.74 11699.15 9794.36 12399.45 4898.94 11293.45 12598.90 8599.44 9191.35 10899.59 9697.31 8698.07 8899.29 73
tpm cat197.39 10897.36 10297.50 12299.17 9393.73 12799.43 5699.31 9191.27 13298.71 9799.08 11894.31 8099.77 6396.41 10798.50 8199.00 90
tpmp4_e2397.34 10997.29 10897.52 12099.25 8393.73 12799.58 2999.19 9994.00 12098.20 11699.41 9390.74 11399.74 6697.13 9098.07 8899.07 85
USDC97.34 10997.20 10997.75 11499.07 10695.20 11498.51 13199.04 10797.99 3998.31 11599.86 1889.02 12599.55 9895.67 11597.36 11198.49 122
DSMNet-mixed97.25 11197.35 10496.95 12997.84 13493.61 13199.57 3296.63 14196.13 11098.87 8698.61 13194.59 7597.70 13895.08 12298.86 6899.55 50
TinyColmap97.12 11296.89 11397.83 11199.07 10695.52 10998.57 12998.74 12697.58 5497.81 12499.79 4088.16 13299.56 9795.10 12197.21 11398.39 127
K. test v397.10 11396.79 11598.01 10398.72 12396.33 9799.87 497.05 14097.59 5296.16 13699.80 3788.71 12699.04 11796.69 10396.55 12398.65 106
LP97.04 11496.80 11497.77 11398.90 11795.23 11398.97 11499.06 10694.02 11998.09 11999.41 9393.88 8498.82 13190.46 13298.42 8399.26 75
PatchT97.03 11596.44 11698.79 7598.99 11598.34 6599.16 9599.07 10592.13 12999.52 3397.31 13894.54 7798.98 12588.54 13798.73 7499.03 88
FMVSNet196.84 11696.36 11798.29 9299.32 7597.26 8099.43 5699.48 5695.11 11298.55 10799.32 10583.95 13898.98 12595.81 11296.26 12898.62 109
test_040296.64 11796.24 11897.85 11098.85 11996.43 9599.44 5299.26 9393.52 12496.98 13299.52 8588.52 13099.20 11292.58 13097.50 10197.93 135
RPMNet96.61 11895.85 12398.87 6999.18 9098.49 6399.22 9299.08 10488.72 13999.56 2797.38 13794.08 8399.00 12286.87 14198.58 7899.14 79
UnsupCasMVSNet_eth96.44 11996.12 12097.40 12498.65 12795.65 10599.36 6999.51 4797.13 7896.04 13798.99 12388.40 13198.17 13696.71 10290.27 14098.40 126
FMVSNet596.43 12096.19 11997.15 12699.11 10195.89 10499.32 7499.52 4294.47 11898.34 11499.07 11987.54 13397.07 13992.61 12995.72 13298.47 124
new_pmnet96.38 12196.03 12197.41 12398.13 13395.16 11699.05 10599.20 9793.94 12197.39 12998.79 12691.61 10799.04 11790.43 13395.77 13198.05 132
IB-MVS95.67 1896.22 12295.44 12798.57 7999.21 8696.70 9198.65 12797.74 13996.71 9397.27 13098.54 13386.03 13499.92 2298.47 4686.30 14299.10 81
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
PVSNet_094.43 1996.09 12395.47 12697.94 10599.31 7694.34 12497.81 13899.70 1197.12 7997.46 12898.75 13089.71 12199.79 6097.69 7681.69 14499.68 32
EG-PatchMatch MVS95.97 12495.69 12596.81 13197.78 13592.79 13499.16 9598.93 11396.16 10994.08 14099.22 11282.72 13999.47 10195.67 11597.50 10198.17 129
MVS-HIRNet95.75 12595.16 12897.51 12199.30 7793.69 13098.88 11895.78 14285.09 14298.78 9392.65 14391.29 10999.37 10394.85 12399.85 2499.46 63
testpf95.66 12696.02 12294.58 13498.35 13192.32 13597.25 14097.91 13792.83 12797.03 13198.99 12388.69 12798.61 13495.72 11497.40 10892.80 140
MIMVSNet195.51 12795.04 12996.92 13097.38 13695.60 10699.52 4299.50 5193.65 12396.97 13399.17 11485.28 13696.56 14188.36 13895.55 13698.60 116
TDRefinement95.42 12894.57 13197.97 10489.83 14196.11 10299.48 4698.75 12396.74 9196.68 13499.88 1088.65 12999.71 7998.37 4882.74 14398.09 130
N_pmnet94.95 12995.83 12492.31 13798.47 13079.33 14299.12 9892.81 14893.87 12297.68 12799.13 11693.87 8599.01 12191.38 13196.19 12998.59 117
OpenMVS_ROBcopyleft92.34 2094.38 13093.70 13296.41 13397.38 13693.17 13399.06 10398.75 12386.58 14094.84 13998.26 13581.53 14099.32 10789.01 13697.87 9296.76 137
CMPMVSbinary69.68 2394.13 13194.90 13091.84 13897.24 13980.01 14198.52 13099.48 5689.01 13791.99 14399.67 6085.67 13599.13 11595.44 11897.03 11696.39 138
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
HyFIR lowres test93.82 13292.65 13397.33 12599.03 11193.48 13298.72 12697.91 13790.29 13597.72 12698.28 13462.59 14398.99 12490.37 13498.93 6199.53 55
UnsupCasMVSNet_bld93.53 13392.51 13496.58 13297.38 13693.82 12698.24 13599.48 5691.10 13493.10 14196.66 13974.89 14198.37 13594.03 12587.71 14197.56 136
Gipumacopyleft90.99 13490.15 13593.51 13598.73 12190.12 13893.98 14499.45 7179.32 14392.28 14294.91 14069.61 14297.98 13787.42 14095.67 13392.45 142
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
FPMVS84.93 13585.65 13682.75 14486.77 14363.39 14798.35 13298.92 11574.11 14583.39 14498.98 12550.85 14492.40 14384.54 14294.97 13792.46 141
no-one83.04 13680.12 13791.79 13989.44 14285.65 13999.32 7498.32 13389.06 13679.79 14589.16 14644.86 14596.67 14084.33 14346.78 14993.05 139
PNet_i23d79.43 13777.68 13884.67 14186.18 14471.69 14696.50 14293.68 14575.17 14471.33 14691.18 14432.18 14790.62 14478.57 14574.34 14591.71 144
ANet_high77.30 13874.86 14084.62 14275.88 14877.61 14397.63 13993.15 14788.81 13864.27 14889.29 14536.51 14683.93 14775.89 14652.31 14892.33 143
MVEpermissive76.82 2176.91 13974.31 14184.70 14085.38 14676.05 14496.88 14193.17 14667.39 14771.28 14789.01 14721.66 15187.69 14671.74 14872.29 14690.35 145
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVScopyleft70.75 2275.98 14074.97 13979.01 14570.98 14955.18 14893.37 14598.21 13465.08 14861.78 15093.83 14221.74 15092.53 14278.59 14491.12 13989.34 146
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
wuykxyi23d74.42 14171.19 14284.14 14376.16 14774.29 14596.00 14392.57 14969.57 14663.84 14987.49 14821.98 14888.86 14575.56 14757.50 14789.26 147
wuyk23d40.18 14241.29 14336.84 14686.18 14449.12 14979.73 14622.81 15027.64 14925.46 15128.45 14921.98 14848.89 14855.80 14923.56 15012.51 148
ab-mvs-re8.30 14311.06 1440.00 1470.00 1500.00 1500.00 1470.00 1510.00 1500.00 15299.58 760.00 1520.00 1490.00 1500.00 1510.00 149
DeepMVS_CXcopyleft93.34 13699.29 7882.27 14099.22 9685.15 14196.33 13599.05 12190.97 11199.73 7293.57 12697.77 9498.01 133
HQP4-MVS98.66 10299.64 8998.64 107
lessismore_v097.79 11298.69 12695.44 11094.75 14395.71 13899.87 1588.69 12799.32 10795.89 11094.93 13898.62 109
LGP-MVS_train98.49 8199.33 7397.05 8499.55 3097.46 6199.24 5899.83 2692.58 9799.72 7498.09 6097.51 9998.68 99
door97.92 136
HQP5-MVS96.83 88
HQP-NCC99.19 8898.98 11298.24 2498.66 102
ACMP_Plane99.19 8898.98 11298.24 2498.66 102
BP-MVS97.19 88
HQP3-MVS99.39 8097.58 97
ITE_SJBPF98.08 9999.29 7896.37 9698.92 11598.34 2398.83 9099.75 4691.09 11099.62 9395.82 11197.40 10898.25 128
HQP2-MVS92.47 100
NP-MVS99.40 95
MDTV_nov1_ep13_2view95.18 11599.35 7296.84 8999.58 2595.19 6997.82 6999.46 63
MDTV_nov1_ep1398.32 6799.11 10194.44 12299.27 8498.74 12697.51 6099.40 4799.62 7194.78 7299.76 6597.59 7898.81 71
ACMMP++_ref97.19 114
ACMMP++97.43 107
HQP-MVS85.22 137
Test By Simon98.75 9
door-mid98.05 135