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 bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
LCM-MVSNet99.93 199.92 199.94 199.99 199.97 199.90 199.89 299.98 199.99 199.96 199.77 1100.00 199.81 1100.00 199.85 7
FOURS199.73 2499.67 299.43 1099.54 5099.43 3099.26 78
Effi-MVS+-dtu98.26 14497.90 16899.35 7098.02 31499.49 398.02 14699.16 19198.29 11697.64 25397.99 27296.44 17999.95 1596.66 17998.93 28598.60 292
abl_698.99 4098.78 5499.61 999.45 9999.46 498.60 8299.50 6098.59 9899.24 8399.04 11198.54 3599.89 5996.45 19899.62 15499.50 102
RPSCF98.62 9798.36 11799.42 5899.65 4499.42 598.55 8899.57 3597.72 15698.90 14099.26 6996.12 19099.52 30595.72 23699.71 11899.32 184
SR-MVS-dyc-post98.81 6398.55 8499.57 1899.20 14399.38 698.48 10099.30 14498.64 9298.95 13098.96 13697.49 11799.86 9496.56 18899.39 21899.45 130
RE-MVS-def98.58 8299.20 14399.38 698.48 10099.30 14498.64 9298.95 13098.96 13697.75 9096.56 18899.39 21899.45 130
LS3D98.63 9598.38 11599.36 6597.25 34699.38 699.12 4699.32 12899.21 4698.44 20198.88 15797.31 12799.80 17296.58 18399.34 22798.92 257
test117298.76 7198.49 9499.57 1899.18 15399.37 998.39 10899.31 13498.43 10698.90 14098.88 15797.49 11799.86 9496.43 20099.37 22299.48 116
zzz-MVS98.79 6598.52 8799.61 999.67 4199.36 1097.33 21499.20 17398.83 8798.89 14398.90 14896.98 14899.92 3597.16 13199.70 12399.56 73
MTAPA98.88 5698.64 7399.61 999.67 4199.36 1098.43 10599.20 17398.83 8798.89 14398.90 14896.98 14899.92 3597.16 13199.70 12399.56 73
SR-MVS98.71 7898.43 10699.57 1899.18 15399.35 1298.36 11199.29 15198.29 11698.88 14798.85 16497.53 11099.87 8796.14 21899.31 23199.48 116
MP-MVS-pluss98.57 10498.23 13499.60 1399.69 3999.35 1297.16 23199.38 10194.87 28498.97 12798.99 12798.01 7199.88 7097.29 12599.70 12399.58 63
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HPM-MVS_fast99.01 3898.82 5099.57 1899.71 3199.35 1299.00 5599.50 6097.33 19498.94 13698.86 16198.75 2499.82 15097.53 11599.71 11899.56 73
UniMVSNet_ETH3D99.69 299.69 499.69 399.84 1499.34 1599.69 499.58 2899.90 299.86 799.78 599.58 399.95 1599.00 3499.95 1699.78 14
TDRefinement99.42 1699.38 1599.55 2699.76 2299.33 1699.68 599.71 1199.38 3499.53 3399.61 2398.64 2999.80 17298.24 7599.84 5699.52 95
DTE-MVSNet99.43 1599.35 1799.66 499.71 3199.30 1799.31 2099.51 5899.64 1299.56 2899.46 4398.23 5299.97 398.78 4599.93 2599.72 25
ACMMP_NAP98.75 7398.48 9699.57 1899.58 5299.29 1897.82 16799.25 16296.94 22398.78 16199.12 9498.02 7099.84 12597.13 13799.67 14099.59 57
UA-Net99.47 1199.40 1499.70 299.49 8599.29 1899.80 399.72 1099.82 399.04 11499.81 398.05 6999.96 898.85 4299.99 599.86 6
HPM-MVScopyleft98.79 6598.53 8699.59 1799.65 4499.29 1899.16 4199.43 9096.74 23198.61 18198.38 24098.62 3099.87 8796.47 19699.67 14099.59 57
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
pmmvs699.67 399.70 399.60 1399.90 499.27 2199.53 799.76 899.64 1299.84 899.83 299.50 599.87 8799.36 1499.92 3499.64 41
APD-MVS_3200maxsize98.84 6098.61 7899.53 3699.19 14699.27 2198.49 9799.33 12698.64 9299.03 11798.98 13197.89 7999.85 10896.54 19299.42 21499.46 126
MSP-MVS98.40 12998.00 16099.61 999.57 5699.25 2398.57 8699.35 11597.55 17099.31 7197.71 28994.61 24199.88 7096.14 21899.19 25299.70 31
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
WR-MVS_H99.33 2399.22 2799.65 599.71 3199.24 2499.32 1799.55 4699.46 2799.50 3999.34 6097.30 12899.93 2898.90 3899.93 2599.77 16
test_0728_SECOND99.60 1399.50 7899.23 2598.02 14699.32 12899.88 7096.99 14699.63 15199.68 33
MP-MVScopyleft98.46 12198.09 15199.54 2999.57 5699.22 2698.50 9699.19 17897.61 16497.58 25898.66 20097.40 12399.88 7094.72 26399.60 16399.54 85
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
ZNCC-MVS98.68 8798.40 11099.54 2999.57 5699.21 2798.46 10299.29 15197.28 20098.11 22498.39 23898.00 7299.87 8796.86 16299.64 14899.55 81
DVP-MVScopyleft98.77 7098.52 8799.52 4199.50 7899.21 2798.02 14698.84 25397.97 13999.08 10499.02 11597.61 10399.88 7096.99 14699.63 15199.48 116
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
test072699.50 7899.21 2798.17 12799.35 11597.97 13999.26 7899.06 10197.61 103
SMA-MVScopyleft98.40 12998.03 15899.51 4599.16 15799.21 2798.05 14199.22 17094.16 30098.98 12499.10 9897.52 11299.79 18696.45 19899.64 14899.53 91
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
XVS98.72 7798.45 10299.53 3699.46 9699.21 2798.65 7799.34 12198.62 9697.54 26298.63 20997.50 11499.83 13996.79 16599.53 18999.56 73
X-MVStestdata94.32 30692.59 32499.53 3699.46 9699.21 2798.65 7799.34 12198.62 9697.54 26245.85 36897.50 11499.83 13996.79 16599.53 18999.56 73
test_one_060199.39 10999.20 3399.31 13498.49 10498.66 17499.02 11597.64 100
GST-MVS98.61 9898.30 12599.52 4199.51 7599.20 3398.26 11799.25 16297.44 18598.67 17298.39 23897.68 9499.85 10896.00 22199.51 19599.52 95
mvs-test197.83 18597.48 19898.89 14598.02 31499.20 3397.20 22599.16 19198.29 11696.46 31797.17 31896.44 17999.92 3596.66 17997.90 32497.54 339
MIMVSNet199.38 2099.32 2199.55 2699.86 1199.19 3699.41 1299.59 2699.59 2099.71 1499.57 2797.12 13999.90 4999.21 2399.87 5299.54 85
PGM-MVS98.66 9098.37 11699.55 2699.53 7199.18 3798.23 11999.49 6897.01 22198.69 17098.88 15798.00 7299.89 5995.87 22999.59 16799.58 63
SED-MVS98.91 5298.72 6099.49 4999.49 8599.17 3898.10 13399.31 13498.03 13599.66 2099.02 11598.36 4499.88 7096.91 15299.62 15499.41 145
test_241102_ONE99.49 8599.17 3899.31 13497.98 13799.66 2098.90 14898.36 4499.48 314
region2R98.69 8398.40 11099.54 2999.53 7199.17 3898.52 9199.31 13497.46 18198.44 20198.51 22497.83 8399.88 7096.46 19799.58 17399.58 63
mPP-MVS98.64 9398.34 12099.54 2999.54 6999.17 3898.63 7999.24 16797.47 17698.09 22698.68 19597.62 10299.89 5996.22 21299.62 15499.57 68
HFP-MVS98.71 7898.44 10499.51 4599.49 8599.16 4298.52 9199.31 13497.47 17698.58 18798.50 22797.97 7699.85 10896.57 18599.59 16799.53 91
#test#98.50 11798.16 14499.51 4599.49 8599.16 4298.03 14499.31 13496.30 24898.58 18798.50 22797.97 7699.85 10895.68 23999.59 16799.53 91
SteuartSystems-ACMMP98.79 6598.54 8599.54 2999.73 2499.16 4298.23 11999.31 13497.92 14398.90 14098.90 14898.00 7299.88 7096.15 21799.72 11499.58 63
Skip Steuart: Steuart Systems R&D Blog.
ACMMPcopyleft98.75 7398.50 9199.52 4199.56 6399.16 4298.87 6499.37 10597.16 21498.82 15899.01 12497.71 9399.87 8796.29 20999.69 12999.54 85
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
PHI-MVS98.29 14197.95 16399.34 7398.44 28899.16 4298.12 13099.38 10196.01 25798.06 22898.43 23497.80 8799.67 25395.69 23899.58 17399.20 211
DVP-MVS++.98.90 5498.70 6599.51 4598.43 28999.15 4799.43 1099.32 12898.17 12899.26 7899.02 11598.18 5999.88 7097.07 14099.45 21099.49 106
IU-MVS99.49 8599.15 4798.87 24492.97 31599.41 4996.76 16999.62 15499.66 36
DPE-MVScopyleft98.59 10398.26 13099.57 1899.27 12799.15 4797.01 23699.39 9997.67 15899.44 4698.99 12797.53 11099.89 5995.40 24999.68 13499.66 36
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
APDe-MVS98.99 4098.79 5399.60 1399.21 13999.15 4798.87 6499.48 7097.57 16799.35 6099.24 7297.83 8399.89 5997.88 9799.70 12399.75 22
ACMMPR98.70 8198.42 10899.54 2999.52 7399.14 5198.52 9199.31 13497.47 17698.56 19198.54 22097.75 9099.88 7096.57 18599.59 16799.58 63
PEN-MVS99.41 1799.34 1999.62 699.73 2499.14 5199.29 2599.54 5099.62 1799.56 2899.42 4998.16 6299.96 898.78 4599.93 2599.77 16
ACMM96.08 1298.91 5298.73 5899.48 5199.55 6699.14 5198.07 13799.37 10597.62 16299.04 11498.96 13698.84 2099.79 18697.43 11999.65 14699.49 106
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
nrg03099.40 1899.35 1799.54 2999.58 5299.13 5498.98 5899.48 7099.68 999.46 4399.26 6998.62 3099.73 22699.17 2699.92 3499.76 20
HPM-MVS++copyleft98.10 15797.64 18699.48 5199.09 17299.13 5497.52 19998.75 26997.46 18196.90 29697.83 28396.01 19499.84 12595.82 23399.35 22599.46 126
CP-MVS98.70 8198.42 10899.52 4199.36 11399.12 5698.72 7399.36 10997.54 17198.30 21198.40 23697.86 8199.89 5996.53 19399.72 11499.56 73
MAR-MVS96.47 26795.70 27498.79 15997.92 31999.12 5698.28 11598.60 28092.16 32795.54 33896.17 33794.77 23999.52 30589.62 34798.23 30997.72 332
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
LTVRE_ROB98.40 199.67 399.71 299.56 2499.85 1399.11 5899.90 199.78 699.63 1499.78 1099.67 1699.48 699.81 16399.30 1799.97 1199.77 16
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
test_part299.36 11399.10 5999.05 112
PS-CasMVS99.40 1899.33 2099.62 699.71 3199.10 5999.29 2599.53 5499.53 2399.46 4399.41 5198.23 5299.95 1598.89 4099.95 1699.81 11
COLMAP_ROBcopyleft96.50 1098.99 4098.85 4899.41 6199.58 5299.10 5998.74 7099.56 4299.09 6699.33 6399.19 7898.40 4299.72 23495.98 22399.76 10099.42 142
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
anonymousdsp99.51 1099.47 1299.62 699.88 799.08 6299.34 1599.69 1598.93 8199.65 2299.72 1198.93 1999.95 1599.11 27100.00 199.82 9
DIV-MVS_2432*160099.25 2799.18 2899.44 5799.63 4999.06 6398.69 7699.54 5099.31 4099.62 2799.53 3397.36 12699.86 9499.24 2299.71 11899.39 154
OurMVSNet-221017-099.37 2199.31 2299.53 3699.91 398.98 6499.63 699.58 2899.44 2999.78 1099.76 696.39 18199.92 3599.44 1399.92 3499.68 33
LPG-MVS_test98.71 7898.46 10099.47 5499.57 5698.97 6598.23 11999.48 7096.60 23699.10 10199.06 10198.71 2799.83 13995.58 24599.78 8699.62 46
LGP-MVS_train99.47 5499.57 5698.97 6599.48 7096.60 23699.10 10199.06 10198.71 2799.83 13995.58 24599.78 8699.62 46
DeepPCF-MVS96.93 598.32 13698.01 15999.23 9398.39 29498.97 6595.03 32499.18 18296.88 22699.33 6398.78 17998.16 6299.28 34096.74 17199.62 15499.44 135
CP-MVSNet99.21 2999.09 3499.56 2499.65 4498.96 6899.13 4499.34 12199.42 3199.33 6399.26 6997.01 14699.94 2398.74 5099.93 2599.79 13
APD-MVScopyleft98.10 15797.67 18199.42 5899.11 16598.93 6997.76 17499.28 15394.97 28198.72 16998.77 18197.04 14299.85 10893.79 29499.54 18599.49 106
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
DROMVSNet99.09 3499.05 3799.20 9599.28 12598.93 6999.24 3399.84 399.08 6898.12 22298.37 24298.72 2699.90 4999.05 3199.77 9098.77 279
TranMVSNet+NR-MVSNet99.17 3099.07 3699.46 5699.37 11298.87 7198.39 10899.42 9399.42 3199.36 5999.06 10198.38 4399.95 1598.34 7299.90 4499.57 68
testtj97.79 18797.25 21199.42 5899.03 18698.85 7297.78 16999.18 18295.83 26398.12 22298.50 22795.50 21799.86 9492.23 32499.07 26899.54 85
ZD-MVS99.01 19098.84 7399.07 20794.10 30198.05 23098.12 26396.36 18599.86 9492.70 31899.19 252
XVG-OURS-SEG-HR98.49 11898.28 12899.14 10499.49 8598.83 7496.54 26399.48 7097.32 19699.11 9898.61 21499.33 899.30 33796.23 21198.38 30699.28 196
ACMH+96.62 999.08 3599.00 4099.33 7599.71 3198.83 7498.60 8299.58 2899.11 5799.53 3399.18 8098.81 2299.67 25396.71 17699.77 9099.50 102
XVG-OURS98.53 11498.34 12099.11 10899.50 7898.82 7695.97 28999.50 6097.30 19899.05 11298.98 13199.35 799.32 33495.72 23699.68 13499.18 218
ETH3D-3000-0.198.03 16197.62 18899.29 8099.11 16598.80 7797.47 20599.32 12895.54 26898.43 20498.62 21196.61 17199.77 20493.95 28899.49 20399.30 191
ACMP95.32 1598.41 12698.09 15199.36 6599.51 7598.79 7897.68 18199.38 10195.76 26598.81 16098.82 17398.36 4499.82 15094.75 26099.77 9099.48 116
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
SF-MVS98.53 11498.27 12999.32 7799.31 12098.75 7998.19 12399.41 9496.77 23098.83 15498.90 14897.80 8799.82 15095.68 23999.52 19299.38 161
UniMVSNet_NR-MVSNet98.86 5998.68 6899.40 6399.17 15598.74 8097.68 18199.40 9799.14 5599.06 10798.59 21696.71 16799.93 2898.57 5899.77 9099.53 91
DU-MVS98.82 6198.63 7499.39 6499.16 15798.74 8097.54 19799.25 16298.84 8699.06 10798.76 18396.76 16399.93 2898.57 5899.77 9099.50 102
test_djsdf99.52 999.51 999.53 3699.86 1198.74 8099.39 1399.56 4299.11 5799.70 1599.73 1099.00 1599.97 399.26 1899.98 999.89 2
OPM-MVS98.56 10598.32 12499.25 9099.41 10798.73 8397.13 23399.18 18297.10 21798.75 16698.92 14498.18 5999.65 26696.68 17899.56 18299.37 164
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
UniMVSNet (Re)98.87 5798.71 6299.35 7099.24 13298.73 8397.73 17799.38 10198.93 8199.12 9698.73 18696.77 16199.86 9498.63 5599.80 7799.46 126
NR-MVSNet98.95 4898.82 5099.36 6599.16 15798.72 8599.22 3499.20 17399.10 6399.72 1398.76 18396.38 18399.86 9498.00 9199.82 6599.50 102
CMPMVSbinary75.91 2396.29 27195.44 28498.84 15196.25 36298.69 8697.02 23599.12 20088.90 35197.83 24198.86 16189.51 29698.90 35791.92 32599.51 19598.92 257
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
ETH3D cwj APD-0.1697.55 20197.00 22599.19 9798.51 28298.64 8796.85 24899.13 19894.19 29997.65 25298.40 23695.78 20799.81 16393.37 30599.16 25599.12 227
pm-mvs199.44 1399.48 1199.33 7599.80 1798.63 8899.29 2599.63 2199.30 4299.65 2299.60 2599.16 1499.82 15099.07 2999.83 6299.56 73
CSCG98.68 8798.50 9199.20 9599.45 9998.63 8898.56 8799.57 3597.87 14798.85 15198.04 27097.66 9699.84 12596.72 17499.81 6999.13 226
OMC-MVS97.88 17597.49 19599.04 12698.89 21798.63 8896.94 24099.25 16295.02 27998.53 19698.51 22497.27 13199.47 31693.50 30299.51 19599.01 241
jajsoiax99.58 699.61 799.48 5199.87 1098.61 9199.28 2999.66 1999.09 6699.89 699.68 1499.53 499.97 399.50 1099.99 599.87 4
mvs_tets99.63 599.67 599.49 4999.88 798.61 9199.34 1599.71 1199.27 4499.90 499.74 899.68 299.97 399.55 899.99 599.88 3
XVG-ACMP-BASELINE98.56 10598.34 12099.22 9499.54 6998.59 9397.71 17899.46 7897.25 20398.98 12498.99 12797.54 10899.84 12595.88 22699.74 10499.23 206
TransMVSNet (Re)99.44 1399.47 1299.36 6599.80 1798.58 9499.27 3199.57 3599.39 3399.75 1299.62 2199.17 1299.83 13999.06 3099.62 15499.66 36
wuyk23d96.06 27697.62 18891.38 34998.65 26798.57 9598.85 6796.95 32996.86 22799.90 499.16 8699.18 1198.40 36289.23 34899.77 9077.18 367
AllTest98.44 12398.20 13799.16 10199.50 7898.55 9698.25 11899.58 2896.80 22898.88 14799.06 10197.65 9799.57 29094.45 27099.61 16199.37 164
TestCases99.16 10199.50 7898.55 9699.58 2896.80 22898.88 14799.06 10197.65 9799.57 29094.45 27099.61 16199.37 164
Baseline_NR-MVSNet98.98 4498.86 4799.36 6599.82 1698.55 9697.47 20599.57 3599.37 3599.21 8799.61 2396.76 16399.83 13998.06 8699.83 6299.71 26
v7n99.53 899.57 899.41 6199.88 798.54 9999.45 999.61 2499.66 1199.68 1999.66 1798.44 4099.95 1599.73 299.96 1499.75 22
PM-MVS98.82 6198.72 6099.12 10699.64 4798.54 9997.98 15299.68 1697.62 16299.34 6299.18 8097.54 10899.77 20497.79 10199.74 10499.04 237
LCM-MVSNet-Re98.64 9398.48 9699.11 10898.85 22398.51 10198.49 9799.83 498.37 10899.69 1799.46 4398.21 5799.92 3594.13 28399.30 23498.91 260
Gipumacopyleft99.03 3799.16 3098.64 17599.94 298.51 10199.32 1799.75 999.58 2298.60 18399.62 2198.22 5599.51 30997.70 10999.73 10797.89 320
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
ITE_SJBPF98.87 14799.22 13798.48 10399.35 11597.50 17398.28 21398.60 21597.64 10099.35 33093.86 29299.27 23898.79 277
CPTT-MVS97.84 18397.36 20599.27 8599.31 12098.46 10498.29 11499.27 15694.90 28397.83 24198.37 24294.90 23099.84 12593.85 29399.54 18599.51 98
DP-MVS98.93 5098.81 5299.28 8299.21 13998.45 10598.46 10299.33 12699.63 1499.48 4099.15 9097.23 13699.75 21897.17 13099.66 14599.63 45
3Dnovator+97.89 398.69 8398.51 8999.24 9298.81 23498.40 10699.02 5299.19 17898.99 7398.07 22799.28 6597.11 14199.84 12596.84 16399.32 22999.47 124
CS-MVS-test98.41 12698.30 12598.73 17198.84 22698.39 10798.71 7599.79 597.98 13796.86 29997.38 31097.86 8199.83 13997.81 10099.46 20797.97 318
F-COLMAP97.30 22096.68 24599.14 10499.19 14698.39 10797.27 22099.30 14492.93 31696.62 30898.00 27195.73 20999.68 25092.62 31998.46 30599.35 174
ACMH96.65 799.25 2799.24 2699.26 8899.72 3098.38 10999.07 4999.55 4698.30 11399.65 2299.45 4799.22 999.76 21198.44 6599.77 9099.64 41
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MSC_two_6792asdad99.32 7798.43 28998.37 11098.86 24999.89 5997.14 13599.60 16399.71 26
No_MVS99.32 7798.43 28998.37 11098.86 24999.89 5997.14 13599.60 16399.71 26
FC-MVSNet-test99.27 2599.25 2599.34 7399.77 2098.37 11099.30 2499.57 3599.61 1999.40 5299.50 3697.12 13999.85 10899.02 3399.94 2199.80 12
VPA-MVSNet99.30 2499.30 2399.28 8299.49 8598.36 11399.00 5599.45 8199.63 1499.52 3599.44 4898.25 5099.88 7099.09 2899.84 5699.62 46
GeoE99.05 3698.99 4299.25 9099.44 10198.35 11498.73 7299.56 4298.42 10798.91 13998.81 17598.94 1899.91 4598.35 7199.73 10799.49 106
OPU-MVS98.82 15398.59 27298.30 11598.10 13398.52 22398.18 5998.75 36094.62 26499.48 20599.41 145
FIs99.14 3299.09 3499.29 8099.70 3798.28 11699.13 4499.52 5799.48 2499.24 8399.41 5196.79 16099.82 15098.69 5399.88 4999.76 20
Vis-MVSNetpermissive99.34 2299.36 1699.27 8599.73 2498.26 11799.17 4099.78 699.11 5799.27 7499.48 4198.82 2199.95 1598.94 3699.93 2599.59 57
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
Anonymous20240521197.90 17197.50 19499.08 11498.90 21298.25 11898.53 9096.16 33998.87 8399.11 9898.86 16190.40 29199.78 19897.36 12299.31 23199.19 216
CNVR-MVS98.17 15497.87 17099.07 11798.67 26198.24 11997.01 23698.93 23397.25 20397.62 25498.34 24697.27 13199.57 29096.42 20199.33 22899.39 154
GBi-Net98.65 9198.47 9899.17 9898.90 21298.24 11999.20 3599.44 8498.59 9898.95 13099.55 2994.14 25199.86 9497.77 10399.69 12999.41 145
test198.65 9198.47 9899.17 9898.90 21298.24 11999.20 3599.44 8498.59 9898.95 13099.55 2994.14 25199.86 9497.77 10399.69 12999.41 145
FMVSNet199.17 3099.17 2999.17 9899.55 6698.24 11999.20 3599.44 8499.21 4699.43 4799.55 2997.82 8699.86 9498.42 6799.89 4899.41 145
API-MVS97.04 24296.91 23297.42 27497.88 32198.23 12398.18 12498.50 28597.57 16797.39 27496.75 32696.77 16199.15 34990.16 34599.02 27694.88 363
Anonymous2024052998.93 5098.87 4599.12 10699.19 14698.22 12499.01 5398.99 22899.25 4599.54 3099.37 5497.04 14299.80 17297.89 9499.52 19299.35 174
ETH3 D test640096.46 26895.59 27999.08 11498.88 21898.21 12596.53 26499.18 18288.87 35297.08 28497.79 28493.64 26399.77 20488.92 34999.40 21799.28 196
test_part197.91 17097.46 20099.27 8598.80 23698.18 12699.07 4999.36 10999.75 599.63 2599.49 3982.20 34599.89 5998.87 4199.95 1699.74 24
Anonymous2023121199.27 2599.27 2499.26 8899.29 12498.18 12699.49 899.51 5899.70 899.80 999.68 1496.84 15499.83 13999.21 2399.91 4099.77 16
MCST-MVS98.00 16597.63 18799.10 11099.24 13298.17 12896.89 24798.73 27295.66 26697.92 23497.70 29197.17 13899.66 26196.18 21699.23 24499.47 124
PS-MVSNAJss99.46 1299.49 1099.35 7099.90 498.15 12999.20 3599.65 2099.48 2499.92 399.71 1298.07 6699.96 899.53 9100.00 199.93 1
CDPH-MVS97.26 22396.66 24899.07 11799.00 19198.15 12996.03 28799.01 22491.21 33897.79 24497.85 28296.89 15299.69 24192.75 31699.38 22199.39 154
test_040298.76 7198.71 6298.93 13999.56 6398.14 13198.45 10499.34 12199.28 4398.95 13098.91 14598.34 4899.79 18695.63 24299.91 4098.86 265
Fast-Effi-MVS+-dtu98.27 14298.09 15198.81 15598.43 28998.11 13297.61 18999.50 6098.64 9297.39 27497.52 30198.12 6599.95 1596.90 15798.71 29598.38 303
EIA-MVS98.00 16597.74 17798.80 15798.72 24598.09 13398.05 14199.60 2597.39 18996.63 30795.55 34697.68 9499.80 17296.73 17399.27 23898.52 295
alignmvs97.35 21696.88 23398.78 16298.54 27998.09 13397.71 17897.69 31399.20 4997.59 25795.90 34188.12 30799.55 29698.18 7998.96 28398.70 287
ANet_high99.57 799.67 599.28 8299.89 698.09 13399.14 4399.93 199.82 399.93 299.81 399.17 1299.94 2399.31 16100.00 199.82 9
TAPA-MVS96.21 1196.63 26195.95 26998.65 17498.93 20498.09 13396.93 24299.28 15383.58 36398.13 22197.78 28596.13 18999.40 32493.52 30099.29 23698.45 299
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
TEST998.71 24898.08 13795.96 29199.03 21791.40 33595.85 32897.53 29996.52 17499.76 211
train_agg97.10 23596.45 25899.07 11798.71 24898.08 13795.96 29199.03 21791.64 33095.85 32897.53 29996.47 17799.76 21193.67 29699.16 25599.36 170
ETV-MVS98.03 16197.86 17198.56 19298.69 25698.07 13997.51 20199.50 6098.10 13297.50 26695.51 34798.41 4199.88 7096.27 21099.24 24397.71 333
VDD-MVS98.56 10598.39 11399.07 11799.13 16498.07 13998.59 8497.01 32799.59 2099.11 9899.27 6794.82 23499.79 18698.34 7299.63 15199.34 176
NCCC97.86 17797.47 19999.05 12498.61 26898.07 13996.98 23898.90 23997.63 16197.04 28797.93 27895.99 19899.66 26195.31 25098.82 28999.43 139
CNLPA97.17 23296.71 24398.55 19398.56 27698.05 14296.33 27698.93 23396.91 22597.06 28697.39 30994.38 24799.45 32091.66 32899.18 25498.14 311
MVS_111021_LR98.30 13898.12 14998.83 15299.16 15798.03 14396.09 28699.30 14497.58 16698.10 22598.24 25398.25 5099.34 33196.69 17799.65 14699.12 227
test_898.67 26198.01 14495.91 29699.02 22191.64 33095.79 33097.50 30296.47 17799.76 211
agg_prior197.06 23996.40 25999.03 12798.68 25997.99 14595.76 30199.01 22491.73 32995.59 33197.50 30296.49 17699.77 20493.71 29599.14 25999.34 176
agg_prior98.68 25997.99 14599.01 22495.59 33199.77 204
SD-MVS98.40 12998.68 6897.54 26798.96 19997.99 14597.88 16099.36 10998.20 12599.63 2599.04 11198.76 2395.33 36996.56 18899.74 10499.31 188
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
DP-MVS Recon97.33 21896.92 23098.57 18899.09 17297.99 14596.79 25199.35 11593.18 31397.71 24898.07 26995.00 22999.31 33593.97 28699.13 26298.42 302
DeepC-MVS97.60 498.97 4598.93 4399.10 11099.35 11797.98 14998.01 14999.46 7897.56 16999.54 3099.50 3698.97 1699.84 12598.06 8699.92 3499.49 106
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
xxxxxxxxxxxxxcwj98.44 12398.24 13299.06 12299.11 16597.97 15096.53 26499.54 5098.24 11998.83 15498.90 14897.80 8799.82 15095.68 23999.52 19299.38 161
save fliter99.11 16597.97 15096.53 26499.02 22198.24 119
test_prior497.97 15095.86 297
IS-MVSNet98.19 15197.90 16899.08 11499.57 5697.97 15099.31 2098.32 29299.01 7298.98 12499.03 11491.59 28599.79 18695.49 24799.80 7799.48 116
SixPastTwentyTwo98.75 7398.62 7599.16 10199.83 1597.96 15499.28 2998.20 29799.37 3599.70 1599.65 1992.65 27799.93 2899.04 3299.84 5699.60 51
test_prior397.48 20797.00 22598.95 13698.69 25697.95 15595.74 30399.03 21796.48 24096.11 32297.63 29595.92 20399.59 28494.16 27899.20 24899.30 191
test_prior98.95 13698.69 25697.95 15599.03 21799.59 28499.30 191
PMVScopyleft91.26 2097.86 17797.94 16597.65 25699.71 3197.94 15798.52 9198.68 27598.99 7397.52 26499.35 5897.41 12298.18 36391.59 33199.67 14096.82 349
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PLCcopyleft94.65 1696.51 26495.73 27398.85 15098.75 24197.91 15896.42 27299.06 20890.94 34195.59 33197.38 31094.41 24599.59 28490.93 34098.04 32299.05 233
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
TSAR-MVS + MP.98.63 9598.49 9499.06 12299.64 4797.90 15998.51 9598.94 23196.96 22299.24 8398.89 15697.83 8399.81 16396.88 15999.49 20399.48 116
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
TSAR-MVS + GP.98.18 15297.98 16198.77 16498.71 24897.88 16096.32 27798.66 27696.33 24599.23 8698.51 22497.48 11999.40 32497.16 13199.46 20799.02 240
plane_prior799.19 14697.87 161
N_pmnet97.63 19797.17 21698.99 13399.27 12797.86 16295.98 28893.41 35895.25 27799.47 4298.90 14895.63 21199.85 10896.91 15299.73 10799.27 198
FPMVS93.44 32192.23 32697.08 28699.25 13197.86 16295.61 30797.16 32592.90 31793.76 35798.65 20275.94 36295.66 36779.30 36797.49 32897.73 331
hse-mvs397.77 18897.33 20999.10 11099.21 13997.84 16498.35 11298.57 28199.11 5798.58 18799.02 11588.65 30499.96 898.11 8196.34 34899.49 106
test1298.93 13998.58 27397.83 16598.66 27696.53 31195.51 21699.69 24199.13 26299.27 198
PatchMatch-RL97.24 22696.78 23998.61 18299.03 18697.83 16596.36 27599.06 20893.49 31197.36 27697.78 28595.75 20899.49 31193.44 30398.77 29098.52 295
EPP-MVSNet98.30 13898.04 15799.07 11799.56 6397.83 16599.29 2598.07 30399.03 7098.59 18599.13 9392.16 28199.90 4996.87 16099.68 13499.49 106
tfpnnormal98.90 5498.90 4498.91 14299.67 4197.82 16899.00 5599.44 8499.45 2899.51 3899.24 7298.20 5899.86 9495.92 22599.69 12999.04 237
canonicalmvs98.34 13598.26 13098.58 18598.46 28697.82 16898.96 5999.46 7899.19 5397.46 26995.46 34998.59 3299.46 31898.08 8598.71 29598.46 297
3Dnovator98.27 298.81 6398.73 5899.05 12498.76 23997.81 17099.25 3299.30 14498.57 10298.55 19399.33 6297.95 7899.90 4997.16 13199.67 14099.44 135
AdaColmapbinary97.14 23496.71 24398.46 20498.34 29697.80 17196.95 23998.93 23395.58 26796.92 29197.66 29295.87 20599.53 30190.97 33999.14 25998.04 314
plane_prior397.78 17297.41 18797.79 244
pmmvs-eth3d98.47 12098.34 12098.86 14999.30 12397.76 17397.16 23199.28 15395.54 26899.42 4899.19 7897.27 13199.63 27197.89 9499.97 1199.20 211
新几何198.91 14298.94 20297.76 17398.76 26687.58 35796.75 30498.10 26594.80 23799.78 19892.73 31799.00 27999.20 211
112196.73 25696.00 26798.91 14298.95 20197.76 17398.07 13798.73 27287.65 35696.54 31098.13 26094.52 24399.73 22692.38 32299.02 27699.24 205
VDDNet98.21 14997.95 16399.01 13199.58 5297.74 17699.01 5397.29 32399.67 1098.97 12799.50 3690.45 29099.80 17297.88 9799.20 24899.48 116
XXY-MVS99.14 3299.15 3299.10 11099.76 2297.74 17698.85 6799.62 2298.48 10599.37 5799.49 3998.75 2499.86 9498.20 7899.80 7799.71 26
Regformer-298.60 10098.46 10099.02 13098.85 22397.71 17896.91 24599.09 20498.98 7599.01 11898.64 20597.37 12599.84 12597.75 10899.57 17799.52 95
plane_prior698.99 19597.70 17994.90 230
LF4IMVS97.90 17197.69 18098.52 19799.17 15597.66 18097.19 22899.47 7696.31 24797.85 24098.20 25796.71 16799.52 30594.62 26499.72 11498.38 303
HQP_MVS97.99 16897.67 18198.93 13999.19 14697.65 18197.77 17299.27 15698.20 12597.79 24497.98 27394.90 23099.70 23794.42 27299.51 19599.45 130
plane_prior97.65 18197.07 23496.72 23299.36 223
WR-MVS98.40 12998.19 13999.03 12799.00 19197.65 18196.85 24898.94 23198.57 10298.89 14398.50 22795.60 21299.85 10897.54 11499.85 5499.59 57
VPNet98.87 5798.83 4999.01 13199.70 3797.62 18498.43 10599.35 11599.47 2699.28 7299.05 10896.72 16699.82 15098.09 8499.36 22399.59 57
K. test v398.00 16597.66 18499.03 12799.79 1997.56 18599.19 3992.47 36199.62 1799.52 3599.66 1789.61 29599.96 899.25 2099.81 6999.56 73
PCF-MVS92.86 1894.36 30593.00 32298.42 20798.70 25297.56 18593.16 35699.11 20279.59 36697.55 26197.43 30792.19 28099.73 22679.85 36699.45 21097.97 318
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
lessismore_v098.97 13499.73 2497.53 18786.71 37199.37 5799.52 3589.93 29399.92 3598.99 3599.72 11499.44 135
QAPM97.31 21996.81 23898.82 15398.80 23697.49 18899.06 5199.19 17890.22 34497.69 25099.16 8696.91 15199.90 4990.89 34299.41 21599.07 231
EG-PatchMatch MVS98.99 4099.01 3998.94 13899.50 7897.47 18998.04 14399.59 2698.15 13199.40 5299.36 5798.58 3399.76 21198.78 4599.68 13499.59 57
MVS_111021_HR98.25 14698.08 15498.75 16799.09 17297.46 19095.97 28999.27 15697.60 16597.99 23398.25 25298.15 6499.38 32896.87 16099.57 17799.42 142
旧先验198.82 23297.45 19198.76 26698.34 24695.50 21799.01 27899.23 206
Fast-Effi-MVS+97.67 19397.38 20398.57 18898.71 24897.43 19297.23 22199.45 8194.82 28596.13 32196.51 32998.52 3699.91 4596.19 21498.83 28898.37 305
114514_t96.50 26695.77 27198.69 17299.48 9397.43 19297.84 16599.55 4681.42 36596.51 31398.58 21795.53 21499.67 25393.41 30499.58 17398.98 246
NP-MVS98.84 22697.39 19496.84 324
hse-mvs297.46 20897.07 22198.64 17598.73 24397.33 19597.45 20797.64 31699.11 5798.58 18797.98 27388.65 30499.79 18698.11 8197.39 33298.81 271
casdiffmvs98.95 4899.00 4098.81 15599.38 11097.33 19597.82 16799.57 3599.17 5499.35 6099.17 8498.35 4799.69 24198.46 6499.73 10799.41 145
Regformer-198.55 10998.44 10498.87 14798.85 22397.29 19796.91 24598.99 22898.97 7698.99 12298.64 20597.26 13499.81 16397.79 10199.57 17799.51 98
VNet98.42 12598.30 12598.79 15998.79 23897.29 19798.23 11998.66 27699.31 4098.85 15198.80 17694.80 23799.78 19898.13 8099.13 26299.31 188
HyFIR lowres test97.19 23096.60 25198.96 13599.62 5197.28 19995.17 32099.50 6094.21 29899.01 11898.32 24986.61 31199.99 297.10 13999.84 5699.60 51
baseline98.96 4799.02 3898.76 16599.38 11097.26 20098.49 9799.50 6098.86 8499.19 8999.06 10198.23 5299.69 24198.71 5299.76 10099.33 182
ab-mvs98.41 12698.36 11798.59 18499.19 14697.23 20199.32 1798.81 25997.66 15998.62 17999.40 5396.82 15799.80 17295.88 22699.51 19598.75 282
DeepC-MVS_fast96.85 698.30 13898.15 14698.75 16798.61 26897.23 20197.76 17499.09 20497.31 19798.75 16698.66 20097.56 10799.64 26896.10 22099.55 18499.39 154
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
AUN-MVS96.24 27495.45 28398.60 18398.70 25297.22 20397.38 21097.65 31495.95 25995.53 33997.96 27782.11 34699.79 18696.31 20797.44 33098.80 276
Regformer-498.73 7698.68 6898.89 14599.02 18897.22 20397.17 22999.06 20899.21 4699.17 9498.85 16497.45 12099.86 9498.48 6399.70 12399.60 51
DPM-MVS96.32 27095.59 27998.51 19998.76 23997.21 20594.54 34098.26 29491.94 32896.37 31897.25 31593.06 27099.43 32291.42 33498.74 29198.89 261
test20.0398.78 6898.77 5698.78 16299.46 9697.20 20697.78 16999.24 16799.04 6999.41 4998.90 14897.65 9799.76 21197.70 10999.79 8299.39 154
Effi-MVS+98.02 16397.82 17398.62 18098.53 28197.19 20797.33 21499.68 1697.30 19896.68 30597.46 30698.56 3499.80 17296.63 18198.20 31198.86 265
TAMVS98.24 14798.05 15698.80 15799.07 17697.18 20897.88 16098.81 25996.66 23599.17 9499.21 7594.81 23699.77 20496.96 15099.88 4999.44 135
UnsupCasMVSNet_eth97.89 17397.60 19098.75 16799.31 12097.17 20997.62 18799.35 11598.72 9198.76 16598.68 19592.57 27899.74 22297.76 10795.60 35599.34 176
OpenMVScopyleft96.65 797.09 23696.68 24598.32 21598.32 29797.16 21098.86 6699.37 10589.48 34896.29 32099.15 9096.56 17299.90 4992.90 31099.20 24897.89 320
OpenMVS_ROBcopyleft95.38 1495.84 28295.18 29397.81 24798.41 29397.15 21197.37 21198.62 27983.86 36298.65 17598.37 24294.29 24999.68 25088.41 35098.62 30196.60 352
FMVSNet298.49 11898.40 11098.75 16798.90 21297.14 21298.61 8199.13 19898.59 9899.19 8999.28 6594.14 25199.82 15097.97 9299.80 7799.29 195
V4298.78 6898.78 5498.76 16599.44 10197.04 21398.27 11699.19 17897.87 14799.25 8299.16 8696.84 15499.78 19899.21 2399.84 5699.46 126
CLD-MVS97.49 20597.16 21798.48 20299.07 17697.03 21494.71 33199.21 17194.46 29198.06 22897.16 31997.57 10699.48 31494.46 26999.78 8698.95 251
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
CDS-MVSNet97.69 19197.35 20698.69 17298.73 24397.02 21596.92 24498.75 26995.89 26198.59 18598.67 19792.08 28399.74 22296.72 17499.81 6999.32 184
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
CS-MVS98.16 15698.22 13597.97 24198.56 27697.01 21698.10 13399.70 1497.45 18397.29 27797.19 31697.72 9299.80 17298.37 6999.62 15497.11 345
UGNet98.53 11498.45 10298.79 15997.94 31896.96 21799.08 4798.54 28299.10 6396.82 30299.47 4296.55 17399.84 12598.56 6199.94 2199.55 81
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
LFMVS97.20 22996.72 24298.64 17598.72 24596.95 21898.93 6194.14 35599.74 798.78 16199.01 12484.45 32999.73 22697.44 11899.27 23899.25 202
test22298.92 20896.93 21995.54 30998.78 26485.72 36096.86 29998.11 26494.43 24499.10 26799.23 206
pmmvs497.58 20097.28 21098.51 19998.84 22696.93 21995.40 31698.52 28493.60 30898.61 18198.65 20295.10 22799.60 28096.97 14999.79 8298.99 245
MSDG97.71 19097.52 19398.28 22098.91 21196.82 22194.42 34199.37 10597.65 16098.37 21098.29 25197.40 12399.33 33394.09 28499.22 24598.68 291
MVP-Stereo98.08 15997.92 16698.57 18898.96 19996.79 22297.90 15999.18 18296.41 24398.46 19998.95 14095.93 20299.60 28096.51 19498.98 28299.31 188
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
HQP5-MVS96.79 222
HQP-MVS97.00 24696.49 25798.55 19398.67 26196.79 22296.29 27899.04 21596.05 25495.55 33596.84 32493.84 25699.54 29992.82 31399.26 24199.32 184
UnsupCasMVSNet_bld97.30 22096.92 23098.45 20599.28 12596.78 22596.20 28399.27 15695.42 27398.28 21398.30 25093.16 26699.71 23594.99 25597.37 33398.87 264
DELS-MVS98.27 14298.20 13798.48 20298.86 22196.70 22695.60 30899.20 17397.73 15598.45 20098.71 18997.50 11499.82 15098.21 7799.59 16798.93 256
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
MVS_030497.64 19597.35 20698.52 19797.87 32296.69 22798.59 8498.05 30597.44 18593.74 35898.85 16493.69 26299.88 7098.11 8199.81 6998.98 246
PAPM_NR96.82 25496.32 26298.30 21899.07 17696.69 22797.48 20398.76 26695.81 26496.61 30996.47 33294.12 25499.17 34790.82 34397.78 32599.06 232
Regformer-398.61 9898.61 7898.63 17899.02 18896.53 22997.17 22998.84 25399.13 5699.10 10198.85 16497.24 13599.79 18698.41 6899.70 12399.57 68
Patchmtry97.35 21696.97 22798.50 20197.31 34596.47 23098.18 12498.92 23698.95 8098.78 16199.37 5485.44 32399.85 10895.96 22499.83 6299.17 222
EI-MVSNet-Vis-set98.68 8798.70 6598.63 17899.09 17296.40 23197.23 22198.86 24999.20 4999.18 9398.97 13397.29 13099.85 10898.72 5199.78 8699.64 41
EI-MVSNet-UG-set98.69 8398.71 6298.62 18099.10 16996.37 23297.23 22198.87 24499.20 4999.19 8998.99 12797.30 12899.85 10898.77 4899.79 8299.65 40
RRT_MVS97.07 23896.57 25398.58 18595.89 36696.33 23397.36 21298.77 26597.85 14999.08 10499.12 9482.30 34299.96 898.82 4499.90 4499.45 130
1112_ss97.29 22296.86 23498.58 18599.34 11996.32 23496.75 25599.58 2893.14 31496.89 29797.48 30492.11 28299.86 9496.91 15299.54 18599.57 68
v899.01 3899.16 3098.57 18899.47 9596.31 23598.90 6299.47 7699.03 7099.52 3599.57 2796.93 15099.81 16399.60 499.98 999.60 51
原ACMM198.35 21398.90 21296.25 23698.83 25892.48 32296.07 32598.10 26595.39 22199.71 23592.61 32098.99 28099.08 230
v1098.97 4599.11 3398.55 19399.44 10196.21 23798.90 6299.55 4698.73 9099.48 4099.60 2596.63 17099.83 13999.70 399.99 599.61 50
FMVSNet596.01 27795.20 29298.41 20897.53 33696.10 23898.74 7099.50 6097.22 21298.03 23299.04 11169.80 36799.88 7097.27 12699.71 11899.25 202
Vis-MVSNet (Re-imp)97.46 20897.16 21798.34 21499.55 6696.10 23898.94 6098.44 28798.32 11298.16 21898.62 21188.76 30199.73 22693.88 29199.79 8299.18 218
CHOSEN 1792x268897.49 20597.14 22098.54 19699.68 4096.09 24096.50 26799.62 2291.58 33298.84 15398.97 13392.36 27999.88 7096.76 16999.95 1699.67 35
v14419298.54 11298.57 8398.45 20599.21 13995.98 24197.63 18699.36 10997.15 21699.32 6999.18 8095.84 20699.84 12599.50 1099.91 4099.54 85
ambc98.24 22398.82 23295.97 24298.62 8099.00 22799.27 7499.21 7596.99 14799.50 31096.55 19199.50 20299.26 201
v114498.60 10098.66 7198.41 20899.36 11395.90 24397.58 19399.34 12197.51 17299.27 7499.15 9096.34 18699.80 17299.47 1299.93 2599.51 98
v119298.60 10098.66 7198.41 20899.27 12795.88 24497.52 19999.36 10997.41 18799.33 6399.20 7796.37 18499.82 15099.57 699.92 3499.55 81
PMMVS96.51 26495.98 26898.09 23097.53 33695.84 24594.92 32798.84 25391.58 33296.05 32695.58 34595.68 21099.66 26195.59 24498.09 31898.76 281
FMVSNet397.50 20397.24 21398.29 21998.08 31295.83 24697.86 16398.91 23897.89 14698.95 13098.95 14087.06 30899.81 16397.77 10399.69 12999.23 206
v2v48298.56 10598.62 7598.37 21299.42 10695.81 24797.58 19399.16 19197.90 14599.28 7299.01 12495.98 19999.79 18699.33 1599.90 4499.51 98
CL-MVSNet_2432*160097.44 21197.22 21498.08 23398.57 27595.78 24894.30 34498.79 26296.58 23898.60 18398.19 25894.74 24099.64 26896.41 20298.84 28798.82 268
v192192098.54 11298.60 8098.38 21199.20 14395.76 24997.56 19599.36 10997.23 20999.38 5599.17 8496.02 19399.84 12599.57 699.90 4499.54 85
v124098.55 10998.62 7598.32 21599.22 13795.58 25097.51 20199.45 8197.16 21499.45 4599.24 7296.12 19099.85 10899.60 499.88 4999.55 81
testgi98.32 13698.39 11398.13 22999.57 5695.54 25197.78 16999.49 6897.37 19199.19 8997.65 29398.96 1799.49 31196.50 19598.99 28099.34 176
Patchmatch-RL test97.26 22397.02 22497.99 24099.52 7395.53 25296.13 28599.71 1197.47 17699.27 7499.16 8684.30 33299.62 27397.89 9499.77 9098.81 271
CANet97.87 17697.76 17598.19 22697.75 32695.51 25396.76 25499.05 21297.74 15496.93 29098.21 25695.59 21399.89 5997.86 9999.93 2599.19 216
EPNet96.14 27595.44 28498.25 22290.76 37395.50 25497.92 15694.65 34898.97 7692.98 35998.85 16489.12 29999.87 8795.99 22299.68 13499.39 154
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test_1112_low_res96.99 24796.55 25598.31 21799.35 11795.47 25595.84 30099.53 5491.51 33496.80 30398.48 23291.36 28699.83 13996.58 18399.53 18999.62 46
diffmvs98.22 14898.24 13298.17 22799.00 19195.44 25696.38 27499.58 2897.79 15398.53 19698.50 22796.76 16399.74 22297.95 9399.64 14899.34 176
Anonymous2023120698.21 14998.21 13698.20 22599.51 7595.43 25798.13 12899.32 12896.16 25198.93 13798.82 17396.00 19599.83 13997.32 12499.73 10799.36 170
testdata98.09 23098.93 20495.40 25898.80 26190.08 34697.45 27098.37 24295.26 22399.70 23793.58 29998.95 28499.17 222
PatchT96.65 26096.35 26097.54 26797.40 34195.32 25997.98 15296.64 33599.33 3996.89 29799.42 4984.32 33199.81 16397.69 11197.49 32897.48 340
bset_n11_16_dypcd96.99 24796.56 25498.27 22199.00 19195.25 26092.18 36194.05 35698.75 8999.01 11898.38 24088.98 30099.93 2898.77 4899.92 3499.64 41
test_yl96.69 25796.29 26397.90 24298.28 29995.24 26197.29 21797.36 31998.21 12298.17 21697.86 28086.27 31399.55 29694.87 25898.32 30798.89 261
DCV-MVSNet96.69 25796.29 26397.90 24298.28 29995.24 26197.29 21797.36 31998.21 12298.17 21697.86 28086.27 31399.55 29694.87 25898.32 30798.89 261
sss97.21 22896.93 22898.06 23598.83 22995.22 26396.75 25598.48 28694.49 28997.27 27897.90 27992.77 27599.80 17296.57 18599.32 22999.16 225
MSLP-MVS++98.02 16398.14 14897.64 25898.58 27395.19 26497.48 20399.23 16997.47 17697.90 23698.62 21197.04 14298.81 35997.55 11299.41 21598.94 255
PVSNet_Blended_VisFu98.17 15498.15 14698.22 22499.73 2495.15 26597.36 21299.68 1694.45 29398.99 12299.27 6796.87 15399.94 2397.13 13799.91 4099.57 68
PAPR95.29 29294.47 30297.75 25197.50 34095.14 26694.89 32898.71 27491.39 33695.35 34295.48 34894.57 24299.14 35084.95 35797.37 33398.97 250
pmmvs597.64 19597.49 19598.08 23399.14 16295.12 26796.70 25899.05 21293.77 30698.62 17998.83 17093.23 26499.75 21898.33 7499.76 10099.36 170
Anonymous2024052198.69 8398.87 4598.16 22899.77 2095.11 26899.08 4799.44 8499.34 3899.33 6399.55 2994.10 25599.94 2399.25 2099.96 1499.42 142
v14898.45 12298.60 8098.00 23999.44 10194.98 26997.44 20899.06 20898.30 11399.32 6998.97 13396.65 16999.62 27398.37 6999.85 5499.39 154
MDA-MVSNet-bldmvs97.94 16997.91 16798.06 23599.44 10194.96 27096.63 26199.15 19798.35 10998.83 15499.11 9694.31 24899.85 10896.60 18298.72 29399.37 164
new_pmnet96.99 24796.76 24097.67 25498.72 24594.89 27195.95 29398.20 29792.62 32198.55 19398.54 22094.88 23399.52 30593.96 28799.44 21398.59 294
HY-MVS95.94 1395.90 28095.35 28897.55 26697.95 31794.79 27298.81 6996.94 33092.28 32595.17 34398.57 21889.90 29499.75 21891.20 33797.33 33798.10 312
D2MVS97.84 18397.84 17297.83 24699.14 16294.74 27396.94 24098.88 24295.84 26298.89 14398.96 13694.40 24699.69 24197.55 11299.95 1699.05 233
EI-MVSNet98.40 12998.51 8998.04 23799.10 16994.73 27497.20 22598.87 24498.97 7699.06 10799.02 11596.00 19599.80 17298.58 5699.82 6599.60 51
MVS_Test98.18 15298.36 11797.67 25498.48 28494.73 27498.18 12499.02 22197.69 15798.04 23199.11 9697.22 13799.56 29398.57 5898.90 28698.71 285
IterMVS-LS98.55 10998.70 6598.09 23099.48 9394.73 27497.22 22499.39 9998.97 7699.38 5599.31 6496.00 19599.93 2898.58 5699.97 1199.60 51
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MIMVSNet96.62 26296.25 26697.71 25399.04 18394.66 27799.16 4196.92 33197.23 20997.87 23899.10 9886.11 31799.65 26691.65 32999.21 24798.82 268
CANet_DTU97.26 22397.06 22297.84 24597.57 33394.65 27896.19 28498.79 26297.23 20995.14 34498.24 25393.22 26599.84 12597.34 12399.84 5699.04 237
WTY-MVS96.67 25996.27 26597.87 24498.81 23494.61 27996.77 25397.92 30894.94 28297.12 28197.74 28891.11 28799.82 15093.89 29098.15 31599.18 218
PMMVS298.07 16098.08 15498.04 23799.41 10794.59 28094.59 33899.40 9797.50 17398.82 15898.83 17096.83 15699.84 12597.50 11799.81 6999.71 26
ET-MVSNet_ETH3D94.30 30893.21 31897.58 26298.14 30894.47 28194.78 33093.24 36094.72 28689.56 36695.87 34278.57 35899.81 16396.91 15297.11 34098.46 297
thisisatest053095.27 29394.45 30397.74 25299.19 14694.37 28297.86 16390.20 36897.17 21398.22 21597.65 29373.53 36599.90 4996.90 15799.35 22598.95 251
TinyColmap97.89 17397.98 16197.60 26098.86 22194.35 28396.21 28299.44 8497.45 18399.06 10798.88 15797.99 7599.28 34094.38 27699.58 17399.18 218
CR-MVSNet96.28 27295.95 26997.28 27997.71 32894.22 28498.11 13198.92 23692.31 32496.91 29399.37 5485.44 32399.81 16397.39 12197.36 33597.81 326
RPMNet97.02 24396.93 22897.30 27897.71 32894.22 28498.11 13199.30 14499.37 3596.91 29399.34 6086.72 31099.87 8797.53 11597.36 33597.81 326
MVSTER96.86 25196.55 25597.79 24897.91 32094.21 28697.56 19598.87 24497.49 17599.06 10799.05 10880.72 34799.80 17298.44 6599.82 6599.37 164
DeepMVS_CXcopyleft93.44 34598.24 30294.21 28694.34 35064.28 36891.34 36494.87 35989.45 29892.77 37077.54 36893.14 36493.35 365
GA-MVS95.86 28195.32 28997.49 27098.60 27094.15 28893.83 35197.93 30795.49 27196.68 30597.42 30883.21 33799.30 33796.22 21298.55 30499.01 241
BH-RMVSNet96.83 25296.58 25297.58 26298.47 28594.05 28996.67 25997.36 31996.70 23497.87 23897.98 27395.14 22699.44 32190.47 34498.58 30399.25 202
cl-mvsnet____97.02 24396.83 23797.58 26297.82 32494.04 29094.66 33499.16 19197.04 21998.63 17798.71 18988.68 30399.69 24197.00 14499.81 6999.00 244
cl-mvsnet197.02 24396.84 23697.58 26297.82 32494.03 29194.66 33499.16 19197.04 21998.63 17798.71 18988.69 30299.69 24197.00 14499.81 6999.01 241
MVS93.19 32392.09 32796.50 30596.91 35094.03 29198.07 13798.06 30468.01 36794.56 34996.48 33195.96 20199.30 33783.84 35996.89 34396.17 355
JIA-IIPM95.52 28995.03 29697.00 28896.85 35294.03 29196.93 24295.82 34399.20 4994.63 34899.71 1283.09 33899.60 28094.42 27294.64 35997.36 342
baseline195.96 27995.44 28497.52 26998.51 28293.99 29498.39 10896.09 34198.21 12298.40 20997.76 28786.88 30999.63 27195.42 24889.27 36798.95 251
TR-MVS95.55 28895.12 29596.86 29997.54 33593.94 29596.49 26896.53 33694.36 29697.03 28896.61 32894.26 25099.16 34886.91 35496.31 34997.47 341
jason97.45 21097.35 20697.76 25099.24 13293.93 29695.86 29798.42 28894.24 29798.50 19898.13 26094.82 23499.91 4597.22 12899.73 10799.43 139
jason: jason.
xiu_mvs_v1_base_debu97.86 17798.17 14196.92 29398.98 19693.91 29796.45 26999.17 18897.85 14998.41 20597.14 32198.47 3799.92 3598.02 8899.05 26996.92 346
xiu_mvs_v1_base97.86 17798.17 14196.92 29398.98 19693.91 29796.45 26999.17 18897.85 14998.41 20597.14 32198.47 3799.92 3598.02 8899.05 26996.92 346
xiu_mvs_v1_base_debi97.86 17798.17 14196.92 29398.98 19693.91 29796.45 26999.17 18897.85 14998.41 20597.14 32198.47 3799.92 3598.02 8899.05 26996.92 346
MVSFormer98.26 14498.43 10697.77 24998.88 21893.89 30099.39 1399.56 4299.11 5798.16 21898.13 26093.81 25899.97 399.26 1899.57 17799.43 139
lupinMVS97.06 23996.86 23497.65 25698.88 21893.89 30095.48 31397.97 30693.53 30998.16 21897.58 29793.81 25899.91 4596.77 16899.57 17799.17 222
tttt051795.64 28694.98 29797.64 25899.36 11393.81 30298.72 7390.47 36798.08 13398.67 17298.34 24673.88 36499.92 3597.77 10399.51 19599.20 211
MS-PatchMatch97.68 19297.75 17697.45 27298.23 30493.78 30397.29 21798.84 25396.10 25398.64 17698.65 20296.04 19299.36 32996.84 16399.14 25999.20 211
PVSNet_BlendedMVS97.55 20197.53 19297.60 26098.92 20893.77 30496.64 26099.43 9094.49 28997.62 25499.18 8096.82 15799.67 25394.73 26199.93 2599.36 170
PVSNet_Blended96.88 25096.68 24597.47 27198.92 20893.77 30494.71 33199.43 9090.98 34097.62 25497.36 31396.82 15799.67 25394.73 26199.56 18298.98 246
USDC97.41 21397.40 20197.44 27398.94 20293.67 30695.17 32099.53 5494.03 30398.97 12799.10 9895.29 22299.34 33195.84 23299.73 10799.30 191
test0.0.03 194.51 30393.69 31296.99 28996.05 36393.61 30794.97 32693.49 35796.17 24997.57 26094.88 35782.30 34299.01 35493.60 29894.17 36398.37 305
BH-untuned96.83 25296.75 24197.08 28698.74 24293.33 30896.71 25798.26 29496.72 23298.44 20197.37 31295.20 22499.47 31691.89 32697.43 33198.44 300
cl_fuxian97.36 21597.37 20497.31 27798.09 31193.25 30995.01 32599.16 19197.05 21898.77 16498.72 18892.88 27399.64 26896.93 15199.76 10099.05 233
MDA-MVSNet_test_wron97.60 19897.66 18497.41 27599.04 18393.09 31095.27 31798.42 28897.26 20298.88 14798.95 14095.43 22099.73 22697.02 14398.72 29399.41 145
miper_ehance_all_eth97.06 23997.03 22397.16 28597.83 32393.06 31194.66 33499.09 20495.99 25898.69 17098.45 23392.73 27699.61 27996.79 16599.03 27398.82 268
Patchmatch-test96.55 26396.34 26197.17 28398.35 29593.06 31198.40 10797.79 30997.33 19498.41 20598.67 19783.68 33699.69 24195.16 25299.31 23198.77 279
MG-MVS96.77 25596.61 25097.26 28098.31 29893.06 31195.93 29498.12 30296.45 24297.92 23498.73 18693.77 26099.39 32691.19 33899.04 27299.33 182
YYNet197.60 19897.67 18197.39 27699.04 18393.04 31495.27 31798.38 29197.25 20398.92 13898.95 14095.48 21999.73 22696.99 14698.74 29199.41 145
thisisatest051594.12 31293.16 31996.97 29198.60 27092.90 31593.77 35290.61 36694.10 30196.91 29395.87 34274.99 36399.80 17294.52 26799.12 26598.20 308
miper_lstm_enhance97.18 23197.16 21797.25 28198.16 30792.85 31695.15 32299.31 13497.25 20398.74 16898.78 17990.07 29299.78 19897.19 12999.80 7799.11 229
cl-mvsnet295.79 28395.39 28796.98 29096.77 35492.79 31794.40 34298.53 28394.59 28897.89 23798.17 25982.82 34199.24 34296.37 20399.03 27398.92 257
eth_miper_zixun_eth97.23 22797.25 21197.17 28398.00 31692.77 31894.71 33199.18 18297.27 20198.56 19198.74 18591.89 28499.69 24197.06 14299.81 6999.05 233
131495.74 28495.60 27896.17 31297.53 33692.75 31998.07 13798.31 29391.22 33794.25 35096.68 32795.53 21499.03 35191.64 33097.18 33896.74 350
PAPM91.88 33390.34 33696.51 30498.06 31392.56 32092.44 35997.17 32486.35 35890.38 36596.01 33886.61 31199.21 34570.65 36995.43 35697.75 330
pmmvs395.03 29894.40 30496.93 29297.70 33092.53 32195.08 32397.71 31288.57 35397.71 24898.08 26879.39 35499.82 15096.19 21499.11 26698.43 301
xiu_mvs_v2_base97.16 23397.49 19596.17 31298.54 27992.46 32295.45 31498.84 25397.25 20397.48 26896.49 33098.31 4999.90 4996.34 20698.68 29796.15 357
PS-MVSNAJ97.08 23797.39 20296.16 31498.56 27692.46 32295.24 31998.85 25297.25 20397.49 26795.99 33998.07 6699.90 4996.37 20398.67 29896.12 358
gg-mvs-nofinetune92.37 32991.20 33495.85 31795.80 36792.38 32499.31 2081.84 37499.75 591.83 36399.74 868.29 36899.02 35287.15 35397.12 33996.16 356
cascas94.79 30194.33 30796.15 31596.02 36592.36 32592.34 36099.26 16185.34 36195.08 34594.96 35692.96 27298.53 36194.41 27598.59 30297.56 338
miper_enhance_ethall96.01 27795.74 27296.81 30096.41 36092.27 32693.69 35398.89 24191.14 33998.30 21197.35 31490.58 28999.58 28996.31 20799.03 27398.60 292
new-patchmatchnet98.35 13498.74 5797.18 28299.24 13292.23 32796.42 27299.48 7098.30 11399.69 1799.53 3397.44 12199.82 15098.84 4399.77 9099.49 106
GG-mvs-BLEND94.76 33394.54 36992.13 32899.31 2080.47 37588.73 36891.01 36767.59 37198.16 36482.30 36494.53 36193.98 364
mvs_anonymous97.83 18598.16 14496.87 29698.18 30691.89 32997.31 21698.90 23997.37 19198.83 15499.46 4396.28 18799.79 18698.90 3898.16 31498.95 251
ADS-MVSNet295.43 29194.98 29796.76 30298.14 30891.74 33097.92 15697.76 31090.23 34296.51 31398.91 14585.61 32099.85 10892.88 31196.90 34198.69 288
MVEpermissive83.40 2292.50 32891.92 33194.25 33798.83 22991.64 33192.71 35783.52 37395.92 26086.46 37095.46 34995.20 22495.40 36880.51 36598.64 29995.73 361
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
thres600view794.45 30493.83 31096.29 30899.06 18091.53 33297.99 15094.24 35398.34 11097.44 27195.01 35379.84 35099.67 25384.33 35898.23 30997.66 334
DSMNet-mixed97.42 21297.60 19096.87 29699.15 16191.46 33398.54 8999.12 20092.87 31897.58 25899.63 2096.21 18899.90 4995.74 23599.54 18599.27 198
tfpn200view994.03 31393.44 31595.78 31898.93 20491.44 33497.60 19094.29 35197.94 14197.10 28294.31 36179.67 35299.62 27383.05 36098.08 31996.29 353
thres40094.14 31193.44 31596.24 31098.93 20491.44 33497.60 19094.29 35197.94 14197.10 28294.31 36179.67 35299.62 27383.05 36098.08 31997.66 334
thres100view90094.19 30993.67 31395.75 31999.06 18091.35 33698.03 14494.24 35398.33 11197.40 27394.98 35579.84 35099.62 27383.05 36098.08 31996.29 353
BH-w/o95.13 29694.89 30095.86 31698.20 30591.31 33795.65 30697.37 31893.64 30796.52 31295.70 34493.04 27199.02 35288.10 35195.82 35497.24 343
thres20093.72 31893.14 32095.46 32798.66 26691.29 33896.61 26294.63 34997.39 18996.83 30193.71 36479.88 34999.56 29382.40 36398.13 31695.54 362
baseline293.73 31792.83 32396.42 30697.70 33091.28 33996.84 25089.77 36993.96 30592.44 36195.93 34079.14 35599.77 20492.94 30996.76 34598.21 307
IB-MVS91.63 1992.24 33190.90 33596.27 30997.22 34791.24 34094.36 34393.33 35992.37 32392.24 36294.58 36066.20 37499.89 5993.16 30894.63 36097.66 334
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
ppachtmachnet_test97.50 20397.74 17796.78 30198.70 25291.23 34194.55 33999.05 21296.36 24499.21 8798.79 17896.39 18199.78 19896.74 17199.82 6599.34 176
IterMVS-SCA-FT97.85 18298.18 14096.87 29699.27 12791.16 34295.53 31099.25 16299.10 6399.41 4999.35 5893.10 26899.96 898.65 5499.94 2199.49 106
IterMVS97.73 18998.11 15096.57 30399.24 13290.28 34395.52 31299.21 17198.86 8499.33 6399.33 6293.11 26799.94 2398.49 6299.94 2199.48 116
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ADS-MVSNet95.24 29494.93 29996.18 31198.14 30890.10 34497.92 15697.32 32290.23 34296.51 31398.91 14585.61 32099.74 22292.88 31196.90 34198.69 288
our_test_397.39 21497.73 17996.34 30798.70 25289.78 34594.61 33798.97 23096.50 23999.04 11498.85 16495.98 19999.84 12597.26 12799.67 14099.41 145
KD-MVS_2432*160092.87 32591.99 32995.51 32591.37 37189.27 34694.07 34698.14 30095.42 27397.25 27996.44 33367.86 36999.24 34291.28 33596.08 35298.02 315
miper_refine_blended92.87 32591.99 32995.51 32591.37 37189.27 34694.07 34698.14 30095.42 27397.25 27996.44 33367.86 36999.24 34291.28 33596.08 35298.02 315
PVSNet93.40 1795.67 28595.70 27495.57 32398.83 22988.57 34892.50 35897.72 31192.69 32096.49 31696.44 33393.72 26199.43 32293.61 29799.28 23798.71 285
tpm94.67 30294.34 30695.66 32197.68 33288.42 34997.88 16094.90 34794.46 29196.03 32798.56 21978.66 35699.79 18695.88 22695.01 35898.78 278
SCA96.41 26996.66 24895.67 32098.24 30288.35 35095.85 29996.88 33296.11 25297.67 25198.67 19793.10 26899.85 10894.16 27899.22 24598.81 271
CHOSEN 280x42095.51 29095.47 28195.65 32298.25 30188.27 35193.25 35598.88 24293.53 30994.65 34797.15 32086.17 31599.93 2897.41 12099.93 2598.73 284
EPMVS93.72 31893.27 31795.09 33196.04 36487.76 35298.13 12885.01 37294.69 28796.92 29198.64 20578.47 36099.31 33595.04 25396.46 34798.20 308
EPNet_dtu94.93 30094.78 30195.38 32893.58 37087.68 35396.78 25295.69 34597.35 19389.14 36798.09 26788.15 30699.49 31194.95 25799.30 23498.98 246
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PatchmatchNetpermissive95.58 28795.67 27695.30 32997.34 34387.32 35497.65 18596.65 33495.30 27697.07 28598.69 19384.77 32699.75 21894.97 25698.64 29998.83 267
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
DWT-MVSNet_test92.75 32792.05 32894.85 33296.48 35887.21 35597.83 16694.99 34692.22 32692.72 36094.11 36370.75 36699.46 31895.01 25494.33 36297.87 322
RRT_test8_iter0595.24 29495.13 29495.57 32397.32 34487.02 35697.99 15099.41 9498.06 13499.12 9699.05 10866.85 37299.85 10898.93 3799.47 20699.84 8
tpm293.09 32492.58 32594.62 33497.56 33486.53 35797.66 18395.79 34486.15 35994.07 35498.23 25575.95 36199.53 30190.91 34196.86 34497.81 326
tpmvs95.02 29995.25 29094.33 33696.39 36185.87 35898.08 13696.83 33395.46 27295.51 34098.69 19385.91 31899.53 30194.16 27896.23 35097.58 337
EU-MVSNet97.66 19498.50 9195.13 33099.63 4985.84 35998.35 11298.21 29698.23 12199.54 3099.46 4395.02 22899.68 25098.24 7599.87 5299.87 4
CostFormer93.97 31493.78 31194.51 33597.53 33685.83 36097.98 15295.96 34289.29 35094.99 34698.63 20978.63 35799.62 27394.54 26696.50 34698.09 313
E-PMN94.17 31094.37 30593.58 34396.86 35185.71 36190.11 36397.07 32698.17 12897.82 24397.19 31684.62 32898.94 35589.77 34697.68 32796.09 359
EMVS93.83 31694.02 30893.23 34796.83 35384.96 36289.77 36496.32 33897.92 14397.43 27296.36 33686.17 31598.93 35687.68 35297.73 32695.81 360
tpm cat193.29 32293.13 32193.75 34197.39 34284.74 36397.39 20997.65 31483.39 36494.16 35198.41 23582.86 34099.39 32691.56 33295.35 35797.14 344
test-LLR93.90 31593.85 30994.04 33896.53 35684.62 36494.05 34892.39 36296.17 24994.12 35295.07 35182.30 34299.67 25395.87 22998.18 31297.82 324
test-mter92.33 33091.76 33394.04 33896.53 35684.62 36494.05 34892.39 36294.00 30494.12 35295.07 35165.63 37599.67 25395.87 22998.18 31297.82 324
tpmrst95.07 29795.46 28293.91 34097.11 34884.36 36697.62 18796.96 32894.98 28096.35 31998.80 17685.46 32299.59 28495.60 24396.23 35097.79 329
PVSNet_089.98 2191.15 33490.30 33793.70 34297.72 32784.34 36790.24 36297.42 31790.20 34593.79 35693.09 36590.90 28898.89 35886.57 35572.76 36997.87 322
MDTV_nov1_ep1395.22 29197.06 34983.20 36897.74 17696.16 33994.37 29596.99 28998.83 17083.95 33499.53 30193.90 28997.95 323
TESTMET0.1,192.19 33291.77 33293.46 34496.48 35882.80 36994.05 34891.52 36594.45 29394.00 35594.88 35766.65 37399.56 29395.78 23498.11 31798.02 315
gm-plane-assit94.83 36881.97 37088.07 35594.99 35499.60 28091.76 327
dp93.47 32093.59 31493.13 34896.64 35581.62 37197.66 18396.42 33792.80 31996.11 32298.64 20578.55 35999.59 28493.31 30692.18 36698.16 310
CVMVSNet96.25 27397.21 21593.38 34699.10 16980.56 37297.20 22598.19 29996.94 22399.00 12199.02 11589.50 29799.80 17296.36 20599.59 16799.78 14
MVS-HIRNet94.32 30695.62 27790.42 35098.46 28675.36 37396.29 27889.13 37095.25 27795.38 34199.75 792.88 27399.19 34694.07 28599.39 21896.72 351
MDTV_nov1_ep13_2view74.92 37497.69 18090.06 34797.75 24785.78 31993.52 30098.69 288
tmp_tt78.77 33678.73 33978.90 35258.45 37574.76 37594.20 34578.26 37639.16 36986.71 36992.82 36680.50 34875.19 37186.16 35692.29 36586.74 366
test_method79.78 33579.50 33880.62 35180.21 37445.76 37670.82 36598.41 29031.08 37080.89 37197.71 28984.85 32597.37 36591.51 33380.03 36898.75 282
test12317.04 33920.11 3427.82 35310.25 3774.91 37794.80 3294.47 3784.93 37110.00 37324.28 3709.69 3763.64 37210.14 37012.43 37114.92 368
testmvs17.12 33820.53 3416.87 35412.05 3764.20 37893.62 3546.73 3774.62 37210.41 37224.33 3698.28 3773.56 3739.69 37115.07 37012.86 369
uanet_test0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
cdsmvs_eth3d_5k24.66 33732.88 3400.00 3550.00 3780.00 3790.00 36699.10 2030.00 3730.00 37497.58 29799.21 100.00 3740.00 3720.00 3720.00 370
pcd_1.5k_mvsjas8.17 34010.90 3430.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 37398.07 660.00 3740.00 3720.00 3720.00 370
sosnet-low-res0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
sosnet0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
uncertanet0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
Regformer0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
ab-mvs-re8.12 34110.83 3440.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 37497.48 3040.00 3780.00 3740.00 3720.00 3720.00 370
uanet0.00 3420.00 3450.00 3550.00 3780.00 3790.00 3660.00 3790.00 3730.00 3740.00 3730.00 3780.00 3740.00 3720.00 3720.00 370
PC_three_145293.27 31299.40 5298.54 22098.22 5597.00 36695.17 25199.45 21099.49 106
eth-test20.00 378
eth-test0.00 378
test_241102_TWO99.30 14498.03 13599.26 7899.02 11597.51 11399.88 7096.91 15299.60 16399.66 36
9.1497.78 17499.07 17697.53 19899.32 12895.53 27098.54 19598.70 19297.58 10599.76 21194.32 27799.46 207
test_0728_THIRD98.17 12899.08 10499.02 11597.89 7999.88 7097.07 14099.71 11899.70 31
GSMVS98.81 271
sam_mvs184.74 32798.81 271
sam_mvs84.29 333
MTGPAbinary99.20 173
test_post197.59 19220.48 37283.07 33999.66 26194.16 278
test_post21.25 37183.86 33599.70 237
patchmatchnet-post98.77 18184.37 33099.85 108
MTMP97.93 15591.91 364
test9_res93.28 30799.15 25899.38 161
agg_prior292.50 32199.16 25599.37 164
test_prior295.74 30396.48 24096.11 32297.63 29595.92 20394.16 27899.20 248
旧先验295.76 30188.56 35497.52 26499.66 26194.48 268
新几何295.93 294
无先验95.74 30398.74 27189.38 34999.73 22692.38 32299.22 210
原ACMM295.53 310
testdata299.79 18692.80 315
segment_acmp97.02 145
testdata195.44 31596.32 246
plane_prior599.27 15699.70 23794.42 27299.51 19599.45 130
plane_prior497.98 273
plane_prior297.77 17298.20 125
plane_prior199.05 182
n20.00 379
nn0.00 379
door-mid99.57 35
test1198.87 244
door99.41 94
HQP-NCC98.67 26196.29 27896.05 25495.55 335
ACMP_Plane98.67 26196.29 27896.05 25495.55 335
BP-MVS92.82 313
HQP4-MVS95.56 33499.54 29999.32 184
HQP3-MVS99.04 21599.26 241
HQP2-MVS93.84 256
ACMMP++_ref99.77 90
ACMMP++99.68 134
Test By Simon96.52 174