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.
sort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
APDe-MVS99.66 199.57 199.92 199.77 2999.89 199.75 3399.56 4399.02 999.88 399.85 2499.18 499.96 1199.22 2299.92 899.90 1
Regformer-499.59 299.54 499.73 3799.76 3299.41 6299.58 7699.49 9299.02 999.88 399.80 5899.00 1699.94 2799.45 799.92 899.84 10
EI-MVSNet-UG-set99.58 399.57 199.64 5299.78 2599.14 8499.60 7199.45 12799.01 1299.90 199.83 3498.98 1799.93 4099.59 199.95 499.86 4
EI-MVSNet-Vis-set99.58 399.56 399.64 5299.78 2599.15 8399.61 7099.45 12799.01 1299.89 299.82 4299.01 1099.92 4799.56 399.95 499.85 6
Regformer-399.57 599.53 599.68 4299.76 3299.29 7199.58 7699.44 13399.01 1299.87 699.80 5898.97 1899.91 5699.44 899.92 899.83 20
Regformer-299.54 699.47 799.75 3099.71 5499.52 5099.49 11299.49 9298.94 2499.83 899.76 7599.01 1099.94 2799.15 2999.87 2899.80 31
SteuartSystems-ACMMP99.54 699.42 1099.87 299.82 2099.81 799.59 7399.51 7998.62 3699.79 1499.83 3499.28 299.97 698.48 9099.90 1899.84 10
Skip Steuart: Steuart Systems R&D Blog.
Regformer-199.53 899.47 799.72 3999.71 5499.44 5999.49 11299.46 11698.95 2399.83 899.76 7599.01 1099.93 4099.17 2799.87 2899.80 31
XVS99.53 899.42 1099.87 299.85 1599.83 399.69 4399.68 1698.98 1899.37 8099.74 8298.81 3099.94 2798.79 5899.86 3899.84 10
HPM-MVS_fast99.51 1099.40 1399.85 1399.91 199.79 1199.76 2699.56 4397.72 10599.76 2099.75 7999.13 599.92 4799.07 3599.92 899.85 6
HFP-MVS99.49 1199.37 1599.86 899.87 899.80 899.66 5299.67 1998.15 6499.68 2699.69 9799.06 799.96 1198.69 6699.87 2899.84 10
ACMMPR99.49 1199.36 1799.86 899.87 899.79 1199.66 5299.67 1998.15 6499.67 3099.69 9798.95 2299.96 1198.69 6699.87 2899.84 10
DeepC-MVS_fast98.69 199.49 1199.39 1499.77 2899.63 7799.59 3899.36 15899.46 11699.07 899.79 1499.82 4298.85 2899.92 4798.68 6899.87 2899.82 24
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
region2R99.48 1499.35 1999.87 299.88 499.80 899.65 6099.66 2298.13 6699.66 3599.68 10298.96 1999.96 1198.62 7399.87 2899.84 10
APD-MVS_3200maxsize99.48 1499.35 1999.85 1399.76 3299.83 399.63 6399.54 5798.36 4999.79 1499.82 4298.86 2799.95 2498.62 7399.81 5699.78 39
DELS-MVS99.48 1499.42 1099.65 4899.72 5299.40 6499.05 21899.66 2299.14 599.57 4999.80 5898.46 5399.94 2799.57 299.84 4799.60 92
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023
MSLP-MVS99.46 1799.47 799.44 8499.60 8499.16 8199.41 14299.71 1198.98 1899.45 6699.78 6999.19 399.54 15999.28 1899.84 4799.63 88
PGM-MVS99.45 1899.31 2799.86 899.87 899.78 1599.58 7699.65 2797.84 9399.71 2299.80 5899.12 699.97 698.33 10199.87 2899.83 20
CP-MVS99.45 1899.32 2299.85 1399.83 1999.75 1699.69 4399.52 7198.07 7599.53 5499.63 12398.93 2399.97 698.74 6199.91 1399.83 20
ACMMPcopyleft99.45 1899.32 2299.82 1899.89 399.67 2699.62 6499.69 1598.12 6799.63 4099.84 3298.73 4199.96 1198.55 8599.83 5199.81 27
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
mPP-MVS99.44 2199.30 2899.86 899.88 499.79 1199.69 4399.48 9998.12 6799.50 5899.75 7998.78 3299.97 698.57 8099.89 2499.83 20
#test#99.43 2299.29 3199.86 899.87 899.80 899.55 9399.67 1997.83 9499.68 2699.69 9799.06 799.96 1198.39 9499.87 2899.84 10
MCST-MVS99.43 2299.30 2899.82 1899.79 2499.74 1899.29 17299.40 15198.79 3199.52 5699.62 12898.91 2499.90 6798.64 7099.75 6699.82 24
UA-Net99.42 2499.29 3199.80 2299.62 7899.55 4399.50 10799.70 1298.79 3199.77 1899.96 197.45 7999.96 1198.92 4699.90 1899.89 2
HPM-MVS99.42 2499.28 3399.83 1799.90 299.72 1999.81 1599.54 5797.59 11299.68 2699.63 12398.91 2499.94 2798.58 7899.91 1399.84 10
CNVR-MVS99.42 2499.30 2899.78 2699.62 7899.71 2099.26 18399.52 7198.82 2899.39 7799.71 8998.96 1999.85 8698.59 7799.80 5899.77 41
SD-MVS99.41 2799.52 699.05 11799.74 4499.68 2499.46 12399.52 7199.11 699.88 399.91 599.43 197.70 26998.72 6399.93 799.77 41
MVS_111021_LR99.41 2799.33 2199.65 4899.77 2999.51 5298.94 24399.85 498.82 2899.65 3899.74 8298.51 5099.80 10998.83 5699.89 2499.64 85
MVS_111021_HR99.41 2799.32 2299.66 4599.72 5299.47 5698.95 24199.85 498.82 2899.54 5399.73 8598.51 5099.74 12098.91 4799.88 2699.77 41
HPM-MVS++99.39 3099.23 3599.87 299.75 3899.84 299.43 13299.51 7998.68 3499.27 10699.53 14998.64 4799.96 1198.44 9399.80 5899.79 35
TSAR-MVS99.36 3199.36 1799.36 9199.67 6498.61 15499.07 21399.33 18599.00 1699.82 1199.81 5199.06 799.84 9199.09 3299.42 9499.65 80
PVSNet_Blended_VisFu99.36 3199.28 3399.61 5699.86 1299.07 8999.47 12199.93 197.66 11099.71 2299.86 2197.73 7499.96 1199.47 699.82 5599.79 35
NCCC99.34 3399.19 3699.79 2599.61 8299.65 3099.30 16999.48 9998.86 2799.21 11899.63 12398.72 4299.90 6798.25 10599.63 8999.80 31
MP-MVScopyleft99.33 3499.15 3999.87 299.88 499.82 699.66 5299.46 11698.09 7199.48 6299.74 8298.29 6299.96 1197.93 12699.87 2899.82 24
PS-MVSNAJ99.32 3599.32 2299.30 9799.57 8998.94 10798.97 23599.46 11698.92 2699.71 2299.24 21699.01 1099.98 299.35 1099.66 8498.97 157
CSCG99.32 3599.32 2299.32 9399.85 1598.29 17099.71 4099.66 2298.11 6999.41 7399.80 5898.37 5999.96 1198.99 4199.96 399.72 62
PHI-MVS99.30 3799.17 3899.70 4199.56 9199.52 5099.58 7699.80 697.12 15099.62 4399.73 8598.58 4999.90 6798.61 7599.91 1399.68 74
DeepC-MVS98.35 299.30 3799.19 3699.64 5299.82 2099.23 7799.62 6499.55 5098.94 2499.63 4099.95 295.82 11699.94 2799.37 999.97 299.73 56
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
APD-MVScopyleft99.27 3999.08 4299.84 1699.75 3899.79 1199.50 10799.50 8997.16 14699.77 1899.82 4298.78 3299.94 2797.56 15799.86 3899.80 31
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
LS3D99.27 3999.12 4099.74 3599.18 15599.75 1699.56 8899.57 4098.45 4399.49 6199.85 2497.77 7399.94 2798.33 10199.84 4799.52 108
3Dnovator97.25 999.24 4199.05 4499.81 2199.12 16799.66 2899.84 999.74 899.09 798.92 16099.90 795.94 11399.98 298.95 4499.92 899.79 35
test_prior399.21 4299.05 4499.68 4299.67 6499.48 5498.96 23799.56 4398.34 5099.01 14799.52 15298.68 4499.83 9797.96 12499.74 6899.74 50
F-COLMAP99.19 4399.04 4799.64 5299.78 2599.27 7399.42 13899.54 5797.29 13799.41 7399.59 13498.42 5699.93 4098.19 10799.69 7999.73 56
3Dnovator+97.12 1399.18 4498.97 5799.82 1899.17 15999.68 2499.81 1599.51 7999.20 498.72 18099.89 1095.68 12099.97 698.86 5399.86 3899.81 27
MVSFormer99.17 4599.12 4099.29 10099.51 9598.94 10799.88 199.46 11697.55 11699.80 1299.65 11397.39 8099.28 19899.03 3799.85 4299.65 80
sss99.17 4599.05 4499.53 6899.62 7898.97 10399.36 15899.62 2897.83 9499.67 3099.65 11397.37 8399.95 2499.19 2499.19 10299.68 74
DP-MVS99.16 4798.95 6299.78 2699.77 2999.53 4799.41 14299.50 8997.03 15899.04 14499.88 1397.39 8099.92 4798.66 6999.90 1899.87 3
CNLPA99.14 4898.99 5499.59 5899.58 8799.41 6299.16 19799.44 13398.45 4399.19 12599.49 16098.08 6599.89 7597.73 14399.75 6699.48 113
CDPH-MVS99.13 4998.91 6599.80 2299.75 3899.71 2099.15 20099.41 14596.60 18299.60 4599.55 14598.83 2999.90 6797.48 16299.83 5199.78 39
jason99.13 4999.03 4999.45 8199.46 10598.87 11499.12 20699.26 20898.03 8299.79 1499.65 11397.02 9099.85 8699.02 3999.90 1899.65 80
jason: jason.
lupinMVS99.13 4999.01 5399.46 8099.51 9598.94 10799.05 21899.16 21897.86 8999.80 1299.56 14297.39 8099.86 8398.94 4599.85 4299.58 98
EPP-MVSNet99.13 4998.99 5499.53 6899.65 7499.06 9099.81 1599.33 18597.43 12599.60 4599.88 1397.14 8799.84 9199.13 3098.94 11899.69 70
MG-MVS99.13 4999.02 5299.45 8199.57 8998.63 15099.07 21399.34 17798.99 1799.61 4499.82 4297.98 6899.87 8097.00 18799.80 5899.85 6
DP-MVS Recon99.12 5498.95 6299.65 4899.74 4499.70 2299.27 17699.57 4096.40 19999.42 7199.68 10298.75 3999.80 10997.98 12399.72 7299.44 123
Vis-MVSNetpermissive99.12 5498.97 5799.56 6399.78 2599.10 8699.68 4899.66 2298.49 4299.86 799.87 1894.77 15899.84 9199.19 2499.41 9599.74 50
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
TAMVS99.12 5499.08 4299.24 10399.46 10598.55 15699.51 10299.46 11698.09 7199.45 6699.82 4298.34 6099.51 16098.70 6498.93 11999.67 77
VNet99.11 5798.90 6699.73 3799.52 9399.56 4199.41 14299.39 15499.01 1299.74 2199.78 6995.56 12199.92 4799.52 498.18 15199.72 62
CPTT-MVS99.11 5798.90 6699.74 3599.80 2399.46 5799.59 7399.49 9297.03 15899.63 4099.69 9797.27 8599.96 1197.82 13399.84 4799.81 27
MVS_Test99.10 5998.97 5799.48 7699.49 10099.14 8499.67 5099.34 17797.31 13599.58 4799.76 7597.65 7699.82 10298.87 5099.07 11099.46 120
liao99.09 6098.87 6999.75 3099.74 4499.60 3699.27 17699.48 9996.82 16999.25 11099.65 11398.38 5799.93 4097.53 15899.67 8399.73 56
HyFIR99.09 6098.97 5799.45 8199.68 6298.78 13899.14 20599.62 2897.97 8599.20 12199.83 3496.26 10799.82 10299.08 3399.98 199.74 50
CDS-MVSNet99.09 6099.03 4999.25 10299.42 11098.73 14199.45 12499.46 11698.11 6999.46 6599.77 7398.01 6799.37 17798.70 6498.92 12299.66 78
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PVSNet_Blended99.08 6398.97 5799.42 8899.76 3298.79 13698.78 25399.91 296.74 17199.67 3099.49 16097.53 7799.88 7898.98 4299.85 4299.60 92
OMC-MVS99.08 6399.04 4799.20 10799.67 6498.22 17399.28 17499.52 7198.07 7599.66 3599.81 5197.79 7299.78 11397.79 13599.81 5699.60 92
WTY-MVS99.06 6598.88 6899.61 5699.62 7899.16 8199.37 15599.56 4398.04 8099.53 5499.62 12896.84 9399.94 2798.85 5498.49 14399.72 62
IS-MVSNet99.05 6698.87 6999.57 6199.73 4999.32 6799.75 3399.20 21498.02 8399.56 5099.86 2196.54 10099.67 14298.09 11499.13 10599.73 56
PAPM_NR99.04 6798.84 7399.66 4599.74 4499.44 5999.39 14999.38 15997.70 10899.28 10299.28 21298.34 6099.85 8696.96 19199.45 9399.69 70
API-MVS99.04 6799.03 4999.06 11599.40 11699.31 7099.55 9399.56 4398.54 3999.33 9199.39 18598.76 3799.78 11396.98 18999.78 6298.07 254
mvs_anonymous99.03 6998.99 5499.16 10999.38 11998.52 16199.51 10299.38 15997.79 9799.38 7999.81 5197.30 8499.45 16499.35 1098.99 11399.51 110
canonicalmvs99.02 7098.86 7199.51 7499.42 11099.32 6799.80 1999.48 9998.63 3599.31 9398.81 24497.09 8899.75 11999.27 2097.90 16199.47 117
PLCcopyleft97.94 499.02 7098.85 7299.53 6899.66 7399.01 9699.24 18699.52 7196.85 16799.27 10699.48 16498.25 6499.91 5697.76 13999.62 9099.65 80
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
agg_prior199.01 7298.76 7999.76 2999.67 6499.62 3298.99 22999.40 15196.26 20598.87 16699.49 16098.77 3599.91 5697.69 14999.72 7299.75 45
AdaColmapbinary99.01 7298.80 7599.66 4599.56 9199.54 4499.18 19699.70 1298.18 6399.35 8799.63 12396.32 10399.90 6797.48 16299.77 6499.55 100
1112_ss98.98 7498.77 7899.59 5899.68 6299.02 9499.25 18499.48 9997.23 14399.13 12999.58 13796.93 9299.90 6798.87 5098.78 13199.84 10
MSDG98.98 7498.80 7599.53 6899.76 3299.19 7898.75 25699.55 5097.25 14099.47 6399.77 7397.82 7199.87 8096.93 19499.90 1899.54 102
agg_prior398.97 7698.71 8399.75 3099.67 6499.60 3699.04 22299.41 14595.93 22098.87 16699.48 16498.61 4899.91 5697.63 15299.72 7299.75 45
114514_t98.93 7798.67 8799.72 3999.85 1599.53 4799.62 6499.59 3592.65 26399.71 2299.78 6998.06 6699.90 6798.84 5599.91 1399.74 50
PS-MVSNAJss98.92 7898.92 6498.90 14298.78 23398.53 15899.78 2299.54 5798.07 7599.00 15399.76 7599.01 1099.37 17799.13 3097.23 19198.81 163
Test_1112_low_res98.89 7998.66 9099.57 6199.69 6198.95 10499.03 22399.47 11296.98 16099.15 12899.23 21796.77 9599.89 7598.83 5698.78 13199.86 4
AllTest98.87 8098.72 8199.31 9499.86 1298.48 16599.56 8899.61 3097.85 9199.36 8499.85 2495.95 11199.85 8696.66 20799.83 5199.59 96
UGNet98.87 8098.69 8599.40 8999.22 14898.72 14299.44 12899.68 1699.24 399.18 12799.42 17592.74 20899.96 1199.34 1499.94 699.53 106
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 8098.72 8199.31 9499.71 5498.88 11399.80 1999.44 13397.91 8799.36 8499.78 6995.49 12399.43 17297.91 12799.11 10699.62 90
EPNet98.86 8398.71 8399.30 9797.20 27398.18 17499.62 6498.91 24399.28 298.63 19799.81 5195.96 11099.99 199.24 2199.72 7299.73 56
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PVSNet_BlendedMVS98.86 8398.80 7599.03 11899.76 3298.79 13699.28 17499.91 297.42 12799.67 3099.37 18997.53 7799.88 7898.98 4297.29 19098.42 245
ab-mvs98.86 8398.63 9299.54 6499.64 7599.19 7899.44 12899.54 5797.77 9999.30 9499.81 5194.20 17899.93 4099.17 2798.82 12999.49 111
MAR-MVS98.86 8398.63 9299.54 6499.37 12199.66 2899.45 12499.54 5796.61 18099.01 14799.40 18197.09 8899.86 8397.68 15199.53 9299.10 143
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
COLMAP_ROBcopyleft97.56 698.86 8398.75 8099.17 10899.88 498.53 15899.34 16299.59 3597.55 11698.70 18699.89 1095.83 11599.90 6798.10 11399.90 1899.08 148
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
HY-MVS97.30 798.85 8898.64 9199.47 7899.42 11099.08 8899.62 6499.36 16597.39 13099.28 10299.68 10296.44 10199.92 4798.37 9798.22 15099.40 128
PVSNet96.02 1798.85 8898.84 7398.89 14499.73 4997.28 19198.32 27499.60 3297.86 8999.50 5899.57 14196.75 9699.86 8398.56 8399.70 7899.54 102
PatchMatch-RL98.84 9098.62 9599.52 7299.71 5499.28 7299.06 21699.77 797.74 10399.50 5899.53 14995.41 12499.84 9197.17 17999.64 8799.44 123
alignmvs98.81 9198.56 10199.58 6099.43 10999.42 6199.51 10298.96 23698.61 3799.35 8798.92 23994.78 15599.77 11599.35 1098.11 15599.54 102
DeepPCF-MVS98.18 398.81 9199.37 1597.12 24899.60 8491.75 27398.61 26599.44 13399.35 199.83 899.85 2498.70 4399.81 10799.02 3999.91 1399.81 27
PMMVS98.80 9398.62 9599.34 9299.27 14198.70 14398.76 25599.31 19297.34 13299.21 11899.07 22897.20 8699.82 10298.56 8398.87 12699.52 108
FIs98.78 9498.63 9299.23 10599.18 15599.54 4499.83 1299.59 3598.28 5498.79 17599.81 5196.75 9699.37 17799.08 3396.38 20698.78 166
FC-MVSNet-test98.75 9598.62 9599.15 11199.08 17699.45 5899.86 899.60 3298.23 5998.70 18699.82 4296.80 9499.22 21299.07 3596.38 20698.79 165
XVG-OURS98.73 9698.68 8698.88 14699.70 5997.73 18698.92 24499.55 5098.52 4199.45 6699.84 3295.27 12899.91 5698.08 11898.84 12899.00 154
diffmvs98.72 9798.49 10399.43 8799.48 10399.19 7899.62 6499.42 14295.58 22799.37 8099.67 10696.14 10899.74 12098.14 11198.96 11699.37 129
XVG-OURS-SEG-HR98.69 9898.62 9598.89 14499.71 5497.74 18599.12 20699.54 5798.44 4699.42 7199.71 8994.20 17899.92 4798.54 8798.90 12499.00 154
liao198.68 9998.54 10299.11 11398.89 21798.65 14899.27 17699.49 9296.89 16597.99 22899.56 14297.72 7599.83 9797.74 14299.27 10098.84 162
EI-MVSNet98.67 10098.67 8798.68 16799.35 12497.97 18099.50 10799.38 15996.93 16499.20 12199.83 3497.87 6999.36 18198.38 9697.56 17298.71 178
test_djsdf98.67 10098.57 10098.98 12498.70 24498.91 11299.88 199.46 11697.55 11699.22 11799.88 1395.73 11999.28 19899.03 3797.62 16898.75 172
QAPM98.67 10098.30 11399.80 2299.20 15199.67 2699.77 2499.72 994.74 23598.73 17999.90 795.78 11799.98 296.96 19199.88 2699.76 44
nrg03098.64 10398.42 10599.28 10199.05 18199.69 2399.81 1599.46 11698.04 8099.01 14799.82 4296.69 9899.38 17499.34 1494.59 24098.78 166
PAPR98.63 10498.34 10999.51 7499.40 11699.03 9398.80 25299.36 16596.33 20199.00 15399.12 22698.46 5399.84 9195.23 23499.37 9999.66 78
CVMVSNet98.57 10598.67 8798.30 19799.35 12495.59 23999.50 10799.55 5098.60 3899.39 7799.83 3494.48 16999.45 16498.75 6098.56 14099.85 6
MVSTER98.49 10698.32 11199.00 12299.35 12499.02 9499.54 9699.38 15997.41 12899.20 12199.73 8593.86 19099.36 18198.87 5097.56 17298.62 223
OpenMVScopyleft96.50 1698.47 10798.12 11999.52 7299.04 18299.53 4799.82 1399.72 994.56 24098.08 22399.88 1394.73 16099.98 297.47 16499.76 6599.06 150
IterMVS-LS98.46 10898.42 10598.58 17299.59 8698.00 17899.37 15599.43 14196.94 16399.07 13999.59 13497.87 6999.03 22998.32 10395.62 21698.71 178
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
jajsoiax98.43 10998.28 11498.88 14698.60 25198.43 16799.82 1399.53 6798.19 6098.63 19799.80 5893.22 19899.44 16999.22 2297.50 17698.77 169
BH-untuned98.42 11098.36 10798.59 17199.49 10096.70 21799.27 17699.13 22197.24 14298.80 17499.38 18695.75 11899.74 12097.07 18499.16 10399.33 132
BH-RMVSNet98.41 11198.08 12299.40 8999.41 11398.83 12099.30 16998.77 25197.70 10898.94 15899.65 11392.91 20499.74 12096.52 21199.55 9199.64 85
mvs_tets98.40 11298.23 11598.91 13898.67 24798.51 16299.66 5299.53 6798.19 6098.65 19599.81 5192.75 20699.44 16999.31 1697.48 18098.77 169
XXY-MVS98.38 11398.09 12199.24 10399.26 14399.32 6799.56 8899.55 5097.45 12498.71 18199.83 3493.23 19799.63 15198.88 4896.32 20898.76 171
ACMM97.58 598.37 11498.34 10998.48 18399.41 11397.10 19999.56 8899.45 12798.53 4099.04 14499.85 2493.00 20099.71 13398.74 6197.45 18198.64 216
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
tpmrst98.33 11598.48 10497.90 22799.16 16194.78 25399.31 16799.11 22297.27 13899.45 6699.59 13495.33 12599.84 9198.48 9098.61 13499.09 147
PatchmatchNetpermissive98.31 11698.36 10798.19 21299.16 16195.32 24599.27 17698.92 24097.37 13199.37 8099.58 13794.90 14999.70 13897.43 16799.21 10199.54 102
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
VPA-MVSNet98.29 11797.95 13299.30 9799.16 16199.54 4499.50 10799.58 3998.27 5599.35 8799.37 18992.53 21599.65 14599.35 1094.46 24198.72 176
UniMVSNet (Re)98.29 11798.00 12899.13 11299.00 18899.36 6599.49 11299.51 7997.95 8698.97 15699.13 22396.30 10499.38 17498.36 9993.34 25698.66 212
HQP_MVS98.27 11998.22 11698.44 18799.29 13696.97 20999.39 14999.47 11298.97 2199.11 13399.61 13192.71 20999.69 14097.78 13697.63 16698.67 203
UniMVSNet_NR-MVSNet98.22 12097.97 13098.96 12698.92 21198.98 10099.48 11799.53 6797.76 10098.71 18199.46 16996.43 10299.22 21298.57 8092.87 26298.69 187
LPG-MVS_test98.22 12098.13 11898.49 18199.33 12897.05 20399.58 7699.55 5097.46 12199.24 11199.83 3492.58 21399.72 12898.09 11497.51 17498.68 192
RPSCF98.22 12098.62 9596.99 24999.82 2091.58 27499.72 3899.44 13396.61 18099.66 3599.89 1095.92 11499.82 10297.46 16599.10 10799.57 99
ADS-MVSNet98.20 12398.08 12298.56 17599.33 12896.48 22599.23 18799.15 21996.24 20799.10 13599.67 10694.11 18299.71 13396.81 19799.05 11199.48 113
CR-MVSNet98.17 12497.93 13498.87 14999.18 15598.49 16399.22 19099.33 18596.96 16199.56 5099.38 18694.33 17499.00 23294.83 24098.58 13799.14 140
CLD-MVS98.16 12598.10 12098.33 19499.29 13696.82 21598.75 25699.44 13397.83 9499.13 12999.55 14592.92 20299.67 14298.32 10397.69 16598.48 243
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
WR-MVS_H98.13 12697.87 13998.90 14299.02 18698.84 11799.70 4199.59 3597.27 13898.40 21099.19 22095.53 12299.23 20998.34 10093.78 25498.61 232
v1neww98.12 12797.84 14098.93 13198.97 19698.81 12999.66 5299.35 16996.49 18799.29 9899.37 18995.02 13999.32 18997.73 14394.73 23298.67 203
v7new98.12 12797.84 14098.93 13198.97 19698.81 12999.66 5299.35 16996.49 18799.29 9899.37 18995.02 13999.32 18997.73 14394.73 23298.67 203
v698.12 12797.84 14098.94 12998.94 20498.83 12099.66 5299.34 17796.49 18799.30 9499.37 18994.95 14399.34 18697.77 13894.74 23198.67 203
ACMH97.28 898.10 13097.99 12998.44 18799.41 11396.96 21199.60 7199.56 4398.09 7198.15 22099.91 590.87 23299.70 13898.88 4897.45 18198.67 203
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
CP-MVSNet98.09 13197.78 14699.01 12098.97 19699.24 7699.67 5099.46 11697.25 14098.48 20799.64 11993.79 19199.06 22498.63 7194.10 24898.74 175
DU-MVS98.08 13297.79 14498.96 12698.87 22098.98 10099.41 14299.45 12797.87 8898.71 18199.50 15794.82 15399.22 21298.57 8092.87 26298.68 192
divwei89l23v2f11298.06 13397.78 14698.91 13898.90 21498.77 14099.57 8299.35 16996.45 19499.24 11199.37 18994.92 14799.27 20097.50 16094.71 23698.68 192
v2v48298.06 13397.77 15098.92 13698.90 21498.82 12799.57 8299.36 16596.65 17799.19 12599.35 20094.20 17899.25 20697.72 14794.97 22898.69 187
V4298.06 13397.79 14498.86 15398.98 19398.84 11799.69 4399.34 17796.53 18699.30 9499.37 18994.67 16299.32 18997.57 15694.66 23798.42 245
test-LLR98.06 13397.90 13598.55 17798.79 22997.10 19998.67 26197.75 28197.34 13298.61 20098.85 24094.45 17099.45 16497.25 17399.38 9699.10 143
WR-MVS98.06 13397.73 15799.06 11598.86 22399.25 7599.19 19599.35 16997.30 13698.66 18999.43 17493.94 18799.21 21598.58 7894.28 24498.71 178
ACMP97.20 1198.06 13397.94 13398.45 18699.37 12197.01 20699.44 12899.49 9297.54 11998.45 20899.79 6691.95 22299.72 12897.91 12797.49 17998.62 223
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
v114198.05 13997.76 15398.91 13898.91 21398.78 13899.57 8299.35 16996.41 19899.23 11599.36 19694.93 14699.27 20097.38 16994.72 23498.68 192
v798.05 13997.78 14698.87 14998.99 18998.67 14599.64 6299.34 17796.31 20299.29 9899.51 15594.78 15599.27 20097.03 18595.15 22598.66 212
v198.05 13997.76 15398.93 13198.92 21198.80 13499.57 8299.35 16996.39 20099.28 10299.36 19694.86 15299.32 18997.38 16994.72 23498.68 192
EPNet_dtu98.03 14297.96 13198.23 20898.27 25895.54 24199.23 18798.75 25299.02 997.82 23299.71 8996.11 10999.48 16193.04 25899.65 8699.69 70
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
FMVSNet398.03 14297.76 15398.84 15799.39 11898.98 10099.40 14899.38 15996.67 17699.07 13999.28 21292.93 20198.98 23597.10 18196.65 19998.56 238
ADS-MVSNet298.02 14498.07 12497.87 22899.33 12895.19 24899.23 18799.08 22496.24 20799.10 13599.67 10694.11 18298.93 24396.81 19799.05 11199.48 113
HQP-MVS98.02 14497.90 13598.37 19299.19 15296.83 21398.98 23299.39 15498.24 5698.66 18999.40 18192.47 21799.64 14797.19 17797.58 17098.64 216
LTVRE_ROB97.16 1298.02 14497.90 13598.40 19099.23 14696.80 21699.70 4199.60 3297.12 15098.18 21999.70 9291.73 22499.72 12898.39 9497.45 18198.68 192
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 14798.05 12597.87 22899.15 16494.76 25499.42 13898.93 23897.12 15098.84 17198.59 25193.74 19599.80 10998.55 8598.17 15299.06 150
BH-w/o98.00 14897.89 13898.32 19599.35 12496.20 23399.01 22798.90 24596.42 19698.38 21199.00 23395.26 12999.72 12896.06 21898.61 13499.03 152
v114497.98 14997.69 16098.85 15698.87 22098.66 14799.54 9699.35 16996.27 20499.23 11599.35 20094.67 16299.23 20996.73 20295.16 22498.68 192
EU-MVSNet97.98 14998.03 12697.81 23398.72 24196.65 22099.66 5299.66 2298.09 7198.35 21399.82 4295.25 13098.01 26497.41 16895.30 22198.78 166
tpmvs97.98 14998.02 12797.84 23199.04 18294.73 25599.31 16799.20 21496.10 21898.76 17899.42 17594.94 14499.81 10796.97 19098.45 14498.97 157
NR-MVSNet97.97 15297.61 16499.02 11998.87 22099.26 7499.47 12199.42 14297.63 11197.08 24299.50 15795.07 13799.13 21997.86 13093.59 25598.68 192
v897.95 15397.63 16398.93 13198.95 20198.81 12999.80 1999.41 14596.03 21999.10 13599.42 17594.92 14799.30 19596.94 19394.08 24998.66 212
PS-CasMVS97.93 15497.59 16698.95 12898.99 18999.06 9099.68 4899.52 7197.13 14898.31 21599.68 10292.44 22099.05 22598.51 8894.08 24998.75 172
TranMVSNet+NR-MVSNet97.93 15497.66 16198.76 16498.78 23398.62 15299.65 6099.49 9297.76 10098.49 20699.60 13394.23 17798.97 24298.00 12292.90 26098.70 182
v14419297.92 15697.60 16598.87 14998.83 22698.65 14899.55 9399.34 17796.20 21099.32 9299.40 18194.36 17399.26 20596.37 21595.03 22798.70 182
ACMH+97.24 1097.92 15697.78 14698.32 19599.46 10596.68 21999.56 8899.54 5798.41 4797.79 23499.87 1890.18 23999.66 14498.05 12197.18 19498.62 223
LFMVS97.90 15897.35 19299.54 6499.52 9399.01 9699.39 14998.24 27297.10 15499.65 3899.79 6684.79 27199.91 5699.28 1898.38 14799.69 70
OurMVSNet-221017-097.88 15997.77 15098.19 21298.71 24396.53 22399.88 199.00 23297.79 9798.78 17699.94 391.68 22599.35 18497.21 17596.99 19798.69 187
v7n97.87 16097.52 17098.92 13698.76 23798.58 15599.84 999.46 11696.20 21098.91 16199.70 9294.89 15099.44 16996.03 21993.89 25398.75 172
v1097.85 16197.52 17098.86 15398.99 18998.67 14599.75 3399.41 14595.70 22598.98 15599.41 17894.75 15999.23 20996.01 22094.63 23998.67 203
GA-MVS97.85 16197.47 17799.00 12299.38 11997.99 17998.57 26799.15 21997.04 15798.90 16399.30 20989.83 24199.38 17496.70 20498.33 14899.62 90
VPNet97.84 16397.44 18299.01 12099.21 14998.94 10799.48 11799.57 4098.38 4899.28 10299.73 8588.89 24899.39 17399.19 2493.27 25798.71 178
LCM-MVSNet-Re97.83 16498.15 11796.87 25399.30 13492.25 27299.59 7398.26 27197.43 12596.20 25099.13 22396.27 10598.73 24898.17 10998.99 11399.64 85
XVG-ACMP-BASELINE97.83 16497.71 15998.20 21199.11 16996.33 22999.41 14299.52 7198.06 7999.05 14399.50 15789.64 24399.73 12697.73 14397.38 18798.53 240
IterMVS97.83 16497.77 15098.02 21899.58 8796.27 23199.02 22599.48 9997.22 14498.71 18199.70 9292.75 20699.13 21997.46 16596.00 21298.67 203
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
EPMVS97.82 16797.65 16298.35 19398.88 21895.98 23599.49 11294.71 29297.57 11599.26 10999.48 16492.46 21999.71 13397.87 12999.08 10999.35 130
MV-PatchMatch97.81 16897.75 15697.99 22197.53 26796.60 22198.96 23798.85 24797.22 14497.23 24099.36 19695.28 12799.46 16395.51 22999.78 6297.92 262
v119297.81 16897.44 18298.91 13898.88 21898.68 14499.51 10299.34 17796.18 21299.20 12199.34 20394.03 18599.36 18195.32 23395.18 22398.69 187
v192192097.80 17097.45 17998.84 15798.80 22798.53 15899.52 10099.34 17796.15 21499.24 11199.47 16893.98 18699.29 19795.40 23195.13 22698.69 187
V497.80 17097.51 17298.67 16998.79 22998.63 15099.87 499.44 13395.87 22199.01 14799.46 16994.52 16799.33 18796.64 21093.97 25198.05 255
v14897.79 17297.55 16798.50 17998.74 23897.72 18799.54 9699.33 18596.26 20598.90 16399.51 15594.68 16199.14 21897.83 13293.15 25998.63 222
v5297.79 17297.50 17398.66 17098.80 22798.62 15299.87 499.44 13395.87 22199.01 14799.46 16994.44 17299.33 18796.65 20993.96 25298.05 255
pm-mvs197.77 17497.53 16998.50 17998.46 25497.92 18199.15 20099.31 19295.87 22198.58 20299.58 13794.51 16899.04 22696.74 20195.59 21798.56 238
PEN-MVS97.76 17597.44 18298.72 16698.77 23698.54 15799.78 2299.51 7997.06 15698.29 21799.64 11992.63 21298.89 24498.09 11493.16 25898.72 176
Baseline_NR-MVSNet97.76 17597.45 17998.68 16799.09 17498.29 17099.41 14298.85 24795.65 22698.63 19799.67 10694.82 15399.10 22398.07 11992.89 26198.64 216
TR-MVS97.76 17597.41 18798.82 15999.06 17997.87 18298.87 24998.56 26596.63 17998.68 18899.22 21892.49 21699.65 14595.40 23197.79 16398.95 159
Patchmtry97.75 17897.40 18898.81 16099.10 17298.87 11499.11 20999.33 18594.83 23398.81 17399.38 18694.33 17499.02 23096.10 21795.57 21898.53 240
dp97.75 17897.80 14397.59 24099.10 17293.71 26499.32 16498.88 24696.48 19399.08 13899.55 14592.67 21199.82 10296.52 21198.58 13799.24 137
TAPA-MVS97.07 1597.74 18097.34 19598.94 12999.70 5997.53 18899.25 18499.51 7991.90 26799.30 9499.63 12398.78 3299.64 14788.09 27399.87 2899.65 80
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
VDD-MVS97.73 18197.35 19298.88 14699.47 10497.12 19899.34 16298.85 24798.19 6099.67 3099.85 2482.98 27599.92 4799.49 598.32 14999.60 92
MIMVSNet97.73 18197.45 17998.57 17399.45 10897.50 18999.02 22598.98 23496.11 21699.41 7399.14 22290.28 23598.74 24795.74 22498.93 11999.47 117
CostFormer97.72 18397.73 15797.71 23899.15 16494.02 26099.54 9699.02 23194.67 23699.04 14499.35 20092.35 22199.77 11598.50 8997.94 16099.34 131
FMVSNet297.72 18397.36 19098.80 16199.51 9598.84 11799.45 12499.42 14296.49 18798.86 17099.29 21190.26 23698.98 23596.44 21396.56 20298.58 237
test0.0.03 197.71 18597.42 18698.56 17598.41 25697.82 18398.78 25398.63 26197.34 13298.05 22798.98 23694.45 17098.98 23595.04 23797.15 19598.89 160
v124097.69 18697.32 19898.79 16298.85 22498.43 16799.48 11799.36 16596.11 21699.27 10699.36 19693.76 19399.24 20894.46 24595.23 22298.70 182
cascas97.69 18697.43 18598.48 18398.60 25197.30 19098.18 27999.39 15492.96 26098.41 20998.78 24793.77 19299.27 20098.16 11098.61 13498.86 161
GBi-Net97.68 18897.48 17598.29 19899.51 9597.26 19399.43 13299.48 9996.49 18799.07 13999.32 20690.26 23698.98 23597.10 18196.65 19998.62 223
test197.68 18897.48 17598.29 19899.51 9597.26 19399.43 13299.48 9996.49 18799.07 13999.32 20690.26 23698.98 23597.10 18196.65 19998.62 223
tpm97.67 19097.55 16798.03 21699.02 18695.01 25199.43 13298.54 26696.44 19599.12 13199.34 20391.83 22399.60 15497.75 14196.46 20499.48 113
PCF-MVS97.08 1497.66 19197.06 20799.47 7899.61 8299.09 8798.04 28099.25 21091.24 27098.51 20499.70 9294.55 16599.91 5692.76 26099.85 4299.42 126
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
testgi97.65 19297.50 17398.13 21499.36 12396.45 22699.42 13899.48 9997.76 10097.87 23199.45 17291.09 22998.81 24694.53 24398.52 14199.13 142
PAPM97.59 19397.09 20699.07 11499.06 17998.26 17298.30 27599.10 22394.88 23298.08 22399.34 20396.27 10599.64 14789.87 26898.92 12299.31 133
VDDNet97.55 19497.02 20899.16 10999.49 10098.12 17799.38 15399.30 19595.35 22999.68 2699.90 782.62 27799.93 4099.31 1698.13 15499.42 126
TESTMET0.1,197.55 19497.27 20198.40 19098.93 20996.53 22398.67 26197.61 28596.96 16198.64 19699.28 21288.63 25499.45 16497.30 17299.38 9699.21 138
DWT-MVSNet_test97.53 19697.40 18897.93 22499.03 18494.86 25299.57 8298.63 26196.59 18498.36 21298.79 24589.32 24599.74 12098.14 11198.16 15399.20 139
v74897.52 19797.23 20298.41 18998.69 24597.23 19699.87 499.45 12795.72 22498.51 20499.53 14994.13 18199.30 19596.78 19992.39 26598.70 182
LF4IMVS97.52 19797.46 17897.70 23998.98 19395.55 24099.29 17298.82 25098.07 7598.66 18999.64 11989.97 24099.61 15397.01 18696.68 19897.94 260
DTE-MVSNet97.51 19997.19 20498.46 18598.63 25098.13 17699.84 999.48 9996.68 17597.97 22999.67 10692.92 20298.56 25096.88 19692.60 26498.70 182
SixPastTwentyTwo97.50 20097.33 19798.03 21698.65 24896.23 23299.77 2498.68 25997.14 14797.90 23099.93 490.45 23499.18 21797.00 18796.43 20598.67 203
JIA-IIPM97.50 20097.02 20898.93 13198.73 23997.80 18499.30 16998.97 23591.73 26898.91 16194.86 28395.10 13699.71 13397.58 15597.98 15999.28 135
test-mter97.49 20297.13 20598.55 17798.79 22997.10 19998.67 26197.75 28196.65 17798.61 20098.85 24088.23 25999.45 16497.25 17399.38 9699.10 143
DI_MVS_test_dynamic97.45 20396.79 21299.44 8497.76 26599.04 9299.21 19298.61 26397.74 10394.01 26698.83 24287.38 26399.83 9798.63 7198.90 12499.44 123
DI_MVS_test_normal97.44 20496.77 21499.44 8497.75 26699.00 9899.10 21198.64 26097.71 10693.93 26998.82 24387.39 26299.83 9798.61 7598.97 11599.49 111
tpm297.44 20497.34 19597.74 23799.15 16494.36 25899.45 12498.94 23793.45 25898.90 16399.44 17391.35 22799.59 15597.31 17198.07 15699.29 134
tpm cat197.39 20697.36 19097.50 24399.17 15993.73 26299.43 13299.31 19291.27 26998.71 18199.08 22794.31 17699.77 11596.41 21498.50 14299.00 154
tpmp4_e2397.34 20797.29 20097.52 24199.25 14593.73 26299.58 7699.19 21794.00 25098.20 21899.41 17890.74 23399.74 12097.13 18098.07 15699.07 149
USDC97.34 20797.20 20397.75 23699.07 17795.20 24798.51 27099.04 22997.99 8498.31 21599.86 2189.02 24699.55 15895.67 22797.36 18898.49 242
HC-MVS97.28 20996.55 21699.48 7698.78 23398.95 10499.27 17699.39 15483.53 28498.08 22399.54 14896.97 9199.87 8094.23 25299.16 10399.63 88
DSMNet-mixed97.25 21097.35 19296.95 25197.84 26393.61 26699.57 8296.63 28896.13 21598.87 16698.61 25094.59 16497.70 26995.08 23698.86 12799.55 100
MS-PatchMatch97.24 21197.32 19896.99 24998.45 25593.51 26798.82 25199.32 19197.41 12898.13 22199.30 20988.99 24799.56 15695.68 22699.80 5897.90 263
TransMVSNet (Re)97.15 21296.58 21598.86 15399.12 16798.85 11699.49 11298.91 24395.48 22897.16 24199.80 5893.38 19699.11 22294.16 25491.73 26698.62 223
TinyColmap97.12 21396.89 21097.83 23299.07 17795.52 24298.57 26798.74 25597.58 11497.81 23399.79 6688.16 26099.56 15695.10 23597.21 19298.39 248
K. test v397.10 21496.79 21298.01 21998.72 24196.33 22999.87 497.05 28797.59 11296.16 25199.80 5888.71 25099.04 22696.69 20596.55 20398.65 215
LP97.04 21596.80 21197.77 23598.90 21495.23 24698.97 23599.06 22794.02 24998.09 22299.41 17893.88 18898.82 24590.46 26598.42 14699.26 136
PatchT97.03 21696.44 21798.79 16298.99 18998.34 16999.16 19799.07 22692.13 26499.52 5697.31 27594.54 16698.98 23588.54 27198.73 13399.03 152
FMVSNet196.84 21796.36 21898.29 19899.32 13297.26 19399.43 13299.48 9995.11 23098.55 20399.32 20683.95 27498.98 23595.81 22396.26 20998.62 223
test_040296.64 21896.24 21997.85 23098.85 22496.43 22799.44 12899.26 20893.52 25696.98 24499.52 15288.52 25599.20 21692.58 26297.50 17697.93 261
RPMNet96.61 21995.85 22598.87 14999.18 15598.49 16399.22 19099.08 22488.72 28099.56 5097.38 27494.08 18499.00 23286.87 27798.58 13799.14 140
X-MVStestdata96.55 22095.45 23899.87 299.85 1599.83 399.69 4399.68 1698.98 1899.37 8064.01 29698.81 3099.94 2798.79 5899.86 3899.84 10
UnsupCasMVSNet_eth96.44 22196.12 22197.40 24598.65 24895.65 23799.36 15899.51 7997.13 14896.04 25498.99 23488.40 25798.17 25396.71 20390.27 26898.40 247
FMVSNet596.43 22296.19 22097.15 24799.11 16995.89 23699.32 16499.52 7194.47 24398.34 21499.07 22887.54 26197.07 27292.61 26195.72 21498.47 244
v1896.42 22395.80 22898.26 20198.95 20198.82 12799.76 2699.28 20394.58 23794.12 26197.70 26395.22 13298.16 25494.83 24087.80 27497.79 271
v1796.42 22395.81 22798.25 20598.94 20498.80 13499.76 2699.28 20394.57 23894.18 26097.71 26295.23 13198.16 25494.86 23887.73 27697.80 266
v1696.39 22595.76 22998.26 20198.96 19998.81 12999.76 2699.28 20394.57 23894.10 26297.70 26395.04 13898.16 25494.70 24287.77 27597.80 266
new_pmnet96.38 22696.03 22297.41 24498.13 26195.16 25099.05 21899.20 21493.94 25197.39 23898.79 24591.61 22699.04 22690.43 26695.77 21398.05 255
v1596.28 22795.62 23198.25 20598.94 20498.83 12099.76 2699.29 19694.52 24194.02 26597.61 27095.02 13998.13 25894.53 24386.92 27997.80 266
V1496.26 22895.60 23298.26 20198.94 20498.83 12099.76 2699.29 19694.49 24293.96 26797.66 26794.99 14298.13 25894.41 24686.90 28097.80 266
V996.25 22995.58 23398.26 20198.94 20498.83 12099.75 3399.29 19694.45 24493.96 26797.62 26994.94 14498.14 25794.40 24786.87 28197.81 264
v1396.24 23095.58 23398.25 20598.98 19398.83 12099.75 3399.29 19694.35 24693.89 27097.60 27195.17 13498.11 26094.27 25186.86 28297.81 264
v1296.24 23095.58 23398.23 20898.96 19998.81 12999.76 2699.29 19694.42 24593.85 27197.60 27195.12 13598.09 26194.32 24886.85 28397.80 266
v1196.23 23295.57 23698.21 21098.93 20998.83 12099.72 3899.29 19694.29 24794.05 26497.64 26894.88 15198.04 26292.89 25988.43 27397.77 272
IB-MVS95.67 1896.22 23395.44 23998.57 17399.21 14996.70 21798.65 26497.74 28396.71 17397.27 23998.54 25386.03 26599.92 4798.47 9286.30 28499.10 143
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
gg-mvs-nofinetune96.17 23495.32 24098.73 16598.79 22998.14 17599.38 15394.09 29391.07 27298.07 22691.04 28989.62 24499.35 18496.75 20099.09 10898.68 192
test20.0396.12 23595.96 22496.63 25597.44 26895.45 24399.51 10299.38 15996.55 18596.16 25199.25 21593.76 19396.17 27687.35 27694.22 24698.27 250
PVSNet_094.43 1996.09 23695.47 23797.94 22399.31 13394.34 25997.81 28199.70 1297.12 15097.46 23798.75 24889.71 24299.79 11297.69 14981.69 28799.68 74
EG-PatchMatch MVS95.97 23795.69 23096.81 25497.78 26492.79 27099.16 19798.93 23896.16 21394.08 26399.22 21882.72 27699.47 16295.67 22797.50 17698.17 252
MVS-HIRNet95.75 23895.16 24297.51 24299.30 13493.69 26598.88 24895.78 28985.09 28398.78 17692.65 28591.29 22899.37 17794.85 23999.85 4299.46 120
testpf95.66 23996.02 22394.58 26198.35 25792.32 27197.25 28697.91 27992.83 26197.03 24398.99 23488.69 25198.61 24995.72 22597.40 18592.80 285
MIMVSNet195.51 24095.04 24396.92 25297.38 26995.60 23899.52 10099.50 8993.65 25496.97 24599.17 22185.28 26996.56 27588.36 27295.55 21998.60 233
MDA-MVSNet_test_wron95.45 24194.60 24598.01 21998.16 26097.21 19799.11 20999.24 21193.49 25780.73 28898.98 23693.02 19998.18 25294.22 25394.45 24298.64 216
TDRefinement95.42 24294.57 24697.97 22289.83 28996.11 23499.48 11798.75 25296.74 17196.68 24699.88 1388.65 25399.71 13398.37 9782.74 28698.09 253
YYNet195.36 24394.51 24797.92 22597.89 26297.10 19999.10 21199.23 21293.26 25980.77 28799.04 23192.81 20598.02 26394.30 24994.18 24798.64 216
Test495.05 24493.67 25199.22 10696.07 27598.94 10799.20 19499.27 20797.71 10689.96 28197.59 27366.18 28599.25 20698.06 12098.96 11699.47 117
MDA-MVSNet-bldmvs94.96 24593.98 24997.92 22598.24 25997.27 19299.15 20099.33 18593.80 25380.09 28999.03 23288.31 25897.86 26793.49 25794.36 24398.62 223
N_pmnet94.95 24695.83 22692.31 26798.47 25379.33 29099.12 20692.81 29793.87 25297.68 23699.13 22393.87 18999.01 23191.38 26396.19 21098.59 234
testus94.61 24795.30 24192.54 26696.44 27484.18 28398.36 27199.03 23094.18 24896.49 24798.57 25288.74 24995.09 28087.41 27598.45 14498.36 249
testing_294.44 24892.93 25498.98 12494.16 28199.00 9899.42 13899.28 20396.60 18284.86 28396.84 27670.91 28099.27 20098.23 10696.08 21198.68 192
OpenMVS_ROBcopyleft92.34 2094.38 24993.70 25096.41 25897.38 26993.17 26999.06 21698.75 25286.58 28194.84 25998.26 25681.53 27899.32 18989.01 27097.87 16296.76 276
CMPMVSbinary69.68 2394.13 25094.90 24491.84 26897.24 27280.01 28998.52 26999.48 9989.01 27891.99 27599.67 10685.67 26799.13 21995.44 23097.03 19696.39 278
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs394.09 25193.25 25396.60 25694.76 28094.49 25698.92 24498.18 27589.66 27596.48 24898.06 25786.28 26497.33 27189.68 26987.20 27897.97 259
test235694.07 25294.46 24892.89 26495.18 27986.13 28197.60 28499.06 22793.61 25596.15 25398.28 25485.60 26893.95 28286.68 27898.00 15898.59 234
HyFIR lowres test93.82 25392.65 25697.33 24699.03 18493.48 26898.72 26097.91 27990.29 27497.72 23598.28 25462.59 28898.99 23490.37 26798.93 11999.53 106
UnsupCasMVSNet_bld93.53 25492.51 25796.58 25797.38 26993.82 26198.24 27699.48 9991.10 27193.10 27296.66 27774.89 27998.37 25194.03 25587.71 27797.56 274
Patchmatch-RL test93.33 25592.66 25595.32 25995.61 27690.57 27698.24 27698.39 26895.10 23195.20 25697.70 26367.41 28497.77 26896.28 21690.02 27097.62 273
PM-MVS92.96 25692.23 25895.14 26095.61 27689.98 27899.37 15598.21 27394.80 23495.04 25897.69 26665.06 28697.90 26694.30 24989.98 27197.54 275
test123567892.91 25793.30 25291.71 27093.14 28483.01 28598.75 25698.58 26492.80 26292.45 27397.91 25988.51 25693.54 28382.26 28295.35 22098.59 234
111192.30 25892.21 25992.55 26593.30 28286.27 27999.15 20098.74 25591.94 26590.85 27897.82 26084.18 27295.21 27879.65 28494.27 24596.19 279
test1235691.74 25992.19 26090.37 27391.22 28582.41 28698.61 26598.28 27090.66 27391.82 27697.92 25884.90 27092.61 28481.64 28394.66 23796.09 280
Gipumacopyleft90.99 26090.15 26193.51 26298.73 23990.12 27793.98 29099.45 12779.32 28692.28 27494.91 28269.61 28197.98 26587.42 27495.67 21592.45 287
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
testmv87.91 26187.80 26288.24 27487.68 29277.50 29299.07 21397.66 28489.27 27686.47 28296.22 28068.35 28292.49 28676.63 28888.82 27294.72 283
PMMVS286.87 26285.37 26591.35 27290.21 28883.80 28498.89 24797.45 28683.13 28591.67 27795.03 28148.49 29194.70 28185.86 27977.62 28895.54 281
LCM-MVSNet86.80 26385.22 26691.53 27187.81 29180.96 28898.23 27898.99 23371.05 28990.13 28096.51 27848.45 29296.88 27390.51 26485.30 28596.76 276
FPMVS84.93 26485.65 26482.75 28186.77 29363.39 29998.35 27398.92 24074.11 28883.39 28598.98 23650.85 29092.40 28784.54 28094.97 22892.46 286
.test124583.42 26586.17 26375.15 28493.30 28286.27 27999.15 20098.74 25591.94 26590.85 27897.82 26084.18 27295.21 27879.65 28439.90 29743.98 296
no-one83.04 26680.12 26891.79 26989.44 29085.65 28299.32 16498.32 26989.06 27779.79 29189.16 29144.86 29396.67 27484.33 28146.78 29593.05 284
DUST3R82.80 26781.52 26786.66 27566.61 30068.44 29892.79 29297.92 27768.96 29180.04 29099.85 2485.77 26696.15 27797.86 13043.89 29695.39 282
E-PMN80.61 26879.88 26982.81 28090.75 28776.38 29497.69 28295.76 29066.44 29383.52 28492.25 28662.54 28987.16 29168.53 29261.40 29184.89 294
EMVS80.02 26979.22 27082.43 28291.19 28676.40 29397.55 28592.49 29966.36 29483.01 28691.27 28764.63 28785.79 29265.82 29360.65 29285.08 293
PNet_i23d79.43 27077.68 27184.67 27786.18 29471.69 29796.50 28893.68 29475.17 28771.33 29291.18 28832.18 29690.62 28878.57 28774.34 28991.71 289
ANet_high77.30 27174.86 27384.62 27875.88 29877.61 29197.63 28393.15 29688.81 27964.27 29489.29 29036.51 29483.93 29375.89 28952.31 29492.33 288
MVEpermissive76.82 2176.91 27274.31 27484.70 27685.38 29676.05 29596.88 28793.17 29567.39 29271.28 29389.01 29221.66 30187.69 29071.74 29172.29 29090.35 290
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVScopyleft70.75 2275.98 27374.97 27279.01 28370.98 29955.18 30093.37 29198.21 27365.08 29561.78 29693.83 28421.74 30092.53 28578.59 28691.12 26789.34 291
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
wuykxyi23d74.42 27471.19 27584.14 27976.16 29774.29 29696.00 28992.57 29869.57 29063.84 29587.49 29321.98 29888.86 28975.56 29057.50 29389.26 292
pcd1.5k->3k40.85 27543.49 27732.93 28698.95 2010.00 3040.00 29599.53 670.00 2990.00 3000.27 29895.32 1260.00 2970.00 29797.30 18998.80 164
wuyk23d40.18 27641.29 27936.84 28586.18 29449.12 30179.73 29422.81 30127.64 29625.46 29928.45 29721.98 29848.89 29455.80 29423.56 30012.51 298
testmvs39.17 27743.78 27625.37 28836.04 30216.84 30398.36 27126.56 30020.06 29738.51 29867.32 29429.64 29715.30 29637.59 29539.90 29743.98 296
test12339.01 27842.50 27828.53 28739.17 30120.91 30298.75 25619.17 30219.83 29838.57 29766.67 29533.16 29515.42 29537.50 29629.66 29949.26 295
cdsmvs_eth3d_5k24.64 27932.85 2800.00 2890.00 3030.00 3040.00 29599.51 790.00 2990.00 30099.56 14296.58 990.00 2970.00 2970.00 3010.00 299
ab-mvs-re8.30 28011.06 2810.00 2890.00 3030.00 3040.00 2950.00 3030.00 2990.00 30099.58 1370.00 3020.00 2970.00 2970.00 3010.00 299
pcd_1.5k_mvsjas8.27 28111.03 2820.00 2890.00 3030.00 3040.00 2950.00 3030.00 2990.00 3000.27 29899.01 100.00 2970.00 2970.00 3010.00 299
sosnet-low-res0.02 2820.03 2830.00 2890.00 3030.00 3040.00 2950.00 3030.00 2990.00 3000.27 2980.00 3020.00 2970.00 2970.00 3010.00 299
sosnet0.02 2820.03 2830.00 2890.00 3030.00 3040.00 2950.00 3030.00 2990.00 3000.27 2980.00 3020.00 2970.00 2970.00 3010.00 299
uncertanet0.02 2820.03 2830.00 2890.00 3030.00 3040.00 2950.00 3030.00 2990.00 3000.27 2980.00 3020.00 2970.00 2970.00 3010.00 299
Regformer0.02 2820.03 2830.00 2890.00 3030.00 3040.00 2950.00 3030.00 2990.00 3000.27 2980.00 3020.00 2970.00 2970.00 3010.00 299
uanet0.02 2820.03 2830.00 2890.00 3030.00 3040.00 2950.00 3030.00 2990.00 3000.27 2980.00 3020.00 2970.00 2970.00 3010.00 299
test9_res97.49 16199.72 7299.75 45
TEST999.67 6499.65 3099.05 21899.41 14596.22 20998.95 15799.49 16098.77 3599.91 56
train_agg97.63 15299.72 7299.75 45
Patchmatch-test195.52 27890.87 27590.46 29398.41 26795.19 25796.45 27967.48 28390.26 269
Patchmatch-test99.09 17496.59 22298.70 249
test_899.67 6499.61 3499.03 22399.41 14596.28 20398.93 15999.48 16498.76 3799.91 56
agg_prior297.21 17599.73 7199.75 45
agg_prior99.67 6499.62 3299.40 15198.87 16699.91 56
TestCases99.31 9499.86 1298.48 16599.61 3097.85 9199.36 8499.85 2495.95 11199.85 8696.66 20799.83 5199.59 96
test_prior499.56 4198.99 229
test_prior298.96 23798.34 5099.01 14799.52 15298.68 4497.96 12499.74 68
test_prior99.68 4299.67 6499.48 5499.56 4399.83 9799.74 50
旧先验298.96 23796.70 17499.47 6399.94 2798.19 107
新几何299.01 227
新几何199.75 3099.75 3899.59 3899.54 5796.76 17099.29 9899.64 11998.43 5599.94 2796.92 19599.66 8499.72 62
旧先验199.74 4499.59 3899.54 5799.69 9798.47 5299.68 8299.73 56
无先验98.99 22999.51 7996.89 16599.93 4097.53 15899.72 62
原ACMM298.95 241
原ACMM199.65 4899.73 4999.33 6699.47 11297.46 12199.12 13199.66 11298.67 4699.91 5697.70 14899.69 7999.71 69
test22299.75 3899.49 5398.91 24699.49 9296.42 19699.34 9099.65 11398.28 6399.69 7999.72 62
testdata299.95 2496.67 206
segment_acmp98.96 19
testdata99.54 6499.75 3898.95 10499.51 7997.07 15599.43 7099.70 9298.87 2699.94 2797.76 13999.64 8799.72 62
testdata198.85 25098.32 53
test1299.75 3099.64 7599.61 3499.29 19699.21 11898.38 5799.89 7599.74 6899.74 50
plane_prior799.29 13697.03 205
plane_prior699.27 14196.98 20892.71 209
plane_prior599.47 11299.69 14097.78 13697.63 16698.67 203
plane_prior499.61 131
plane_prior397.00 20798.69 3399.11 133
plane_prior299.39 14998.97 21
plane_prior199.26 143
plane_prior96.97 20999.21 19298.45 4397.60 169
abl_699.79 35
n20.00 303
nn0.00 303
door-mid98.05 276
lessismore_v097.79 23498.69 24595.44 24494.75 29195.71 25599.87 1888.69 25199.32 18995.89 22194.93 23098.62 223
LGP-MVS_train98.49 18199.33 12897.05 20399.55 5097.46 12199.24 11199.83 3492.58 21399.72 12898.09 11497.51 17498.68 192
test1199.35 169
door97.92 277
HQP5-MVS96.83 213
HQP-NCC99.19 15298.98 23298.24 5698.66 189
ACMP_Plane99.19 15298.98 23298.24 5698.66 189
BP-MVS97.19 177
HQP4-MVS98.66 18999.64 14798.64 216
HQP3-MVS99.39 15497.58 170
HQP2-MVS92.47 217
NP-MVS99.23 14696.92 21299.40 181
MDTV_nov1_ep13_2view95.18 24999.35 161