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
AdaColmapbinary97.23 12896.80 13798.51 13199.99 195.60 19799.09 30098.84 6493.32 20096.74 20999.72 9286.04 256100.00 198.01 15099.43 12799.94 85
CNVR-MVS99.40 199.26 199.84 699.98 299.51 699.98 2098.69 8098.20 999.93 299.98 296.82 25100.00 199.75 39100.00 199.99 24
MCST-MVS99.32 399.14 499.86 599.97 399.59 599.97 3898.64 8998.47 399.13 10399.92 1696.38 35100.00 199.74 41100.00 1100.00 1
mPP-MVS98.39 5598.20 5398.97 9199.97 396.92 13699.95 7098.38 18295.04 12198.61 13699.80 5793.39 116100.00 198.64 112100.00 199.98 55
CPTT-MVS97.64 10897.32 11298.58 12099.97 395.77 18699.96 5198.35 18889.90 33198.36 15199.79 6191.18 17599.99 3898.37 12899.99 2199.99 24
DP-MVS Recon98.41 5298.02 6799.56 2899.97 398.70 5199.92 9898.44 14692.06 26498.40 15099.84 4795.68 46100.00 198.19 13999.71 9199.97 65
PAPR98.52 4298.16 5799.58 2799.97 398.77 4599.95 7098.43 15495.35 11598.03 16599.75 7894.03 10199.98 4998.11 14499.83 8099.99 24
MED-MVS test99.60 2399.96 898.79 4199.97 3898.88 5496.36 8799.07 10899.93 11100.00 199.98 999.96 4699.99 24
TestfortrainingZip a99.09 998.87 1899.76 1099.96 899.27 1899.97 3898.88 5496.36 8799.07 10899.93 1197.36 17100.00 198.32 13199.96 46100.00 1
HFP-MVS98.56 3898.37 4299.14 7199.96 897.43 11299.95 7098.61 9794.77 13199.31 9199.85 3694.22 94100.00 198.70 10799.98 3299.98 55
region2R98.54 4098.37 4299.05 8199.96 897.18 12299.96 5198.55 11794.87 12899.45 7899.85 3694.07 100100.00 198.67 109100.00 199.98 55
ACMMPR98.50 4398.32 4699.05 8199.96 897.18 12299.95 7098.60 9994.77 13199.31 9199.84 4793.73 110100.00 198.70 10799.98 3299.98 55
NCCC99.37 299.25 299.71 1699.96 899.15 2399.97 3898.62 9698.02 2199.90 699.95 397.33 18100.00 199.54 56100.00 1100.00 1
CP-MVS98.45 4798.32 4698.87 9699.96 896.62 14999.97 3898.39 17894.43 14898.90 11799.87 3094.30 91100.00 199.04 8299.99 2199.99 24
test_one_060199.94 1599.30 1298.41 17196.63 7299.75 3999.93 1197.49 10
test_0728_SECOND99.82 799.94 1599.47 799.95 7098.43 154100.00 199.99 5100.00 1100.00 1
XVS98.70 3198.55 3099.15 6999.94 1597.50 10899.94 8898.42 16696.22 9199.41 8399.78 6594.34 8899.96 7498.92 9299.95 5399.99 24
X-MVStestdata93.83 26792.06 30299.15 6999.94 1597.50 10899.94 8898.42 16696.22 9199.41 8341.37 47694.34 8899.96 7498.92 9299.95 5399.99 24
test_prior99.43 3999.94 1598.49 6498.65 8699.80 14099.99 24
MSLP-MVS++99.13 899.01 1199.49 3599.94 1598.46 6599.98 2098.86 5897.10 5299.80 2599.94 495.92 42100.00 199.51 57100.00 1100.00 1
APDe-MVScopyleft99.06 1398.91 1499.51 3299.94 1598.76 4899.91 10698.39 17897.20 5099.46 7799.85 3695.53 5099.79 14299.86 25100.00 199.99 24
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
MP-MVScopyleft98.23 7097.97 7199.03 8399.94 1597.17 12599.95 7098.39 17894.70 13598.26 15799.81 5691.84 166100.00 198.85 9899.97 4299.93 86
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
CDPH-MVS98.65 3498.36 4499.49 3599.94 1598.73 4999.87 12898.33 19393.97 17399.76 3899.87 3094.99 6699.75 15198.55 116100.00 199.98 55
PAPM_NR98.12 7497.93 7798.70 10799.94 1596.13 17599.82 15798.43 15494.56 13997.52 18299.70 9894.40 8399.98 4997.00 18799.98 3299.99 24
MG-MVS98.91 2198.65 2699.68 1799.94 1599.07 2599.64 21799.44 1997.33 4399.00 11399.72 9294.03 10199.98 4998.73 106100.00 1100.00 1
ME-MVS99.07 1198.89 1699.59 2599.93 2698.79 4199.95 7098.80 7095.89 10099.28 9599.93 1196.28 3699.98 4999.98 999.96 4699.99 24
SED-MVS99.28 599.11 799.77 899.93 2699.30 1299.96 5198.43 15497.27 4699.80 2599.94 496.71 28100.00 1100.00 1100.00 1100.00 1
IU-MVS99.93 2699.31 1098.41 17197.71 3099.84 20100.00 1100.00 1100.00 1
test_241102_ONE99.93 2699.30 1298.43 15497.26 4899.80 2599.88 2796.71 28100.00 1
DVP-MVScopyleft99.30 499.16 399.73 1399.93 2699.29 1599.95 7098.32 19597.28 4499.83 2199.91 1797.22 20100.00 199.99 5100.00 199.89 95
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
test072699.93 2699.29 1599.96 5198.42 16697.28 4499.86 1499.94 497.22 20
MSP-MVS99.09 999.12 598.98 9099.93 2697.24 11999.95 7098.42 16697.50 3799.52 7399.88 2797.43 1699.71 15799.50 5999.98 32100.00 1
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
agg_prior99.93 2698.77 4598.43 15499.63 5699.85 127
FOURS199.92 3497.66 10299.95 7098.36 18695.58 10999.52 73
ZD-MVS99.92 3498.57 5998.52 12692.34 25299.31 9199.83 4995.06 6199.80 14099.70 4799.97 42
GST-MVS98.27 6297.97 7199.17 6499.92 3497.57 10499.93 9598.39 17894.04 17198.80 12299.74 8592.98 132100.00 198.16 14199.76 8899.93 86
TEST999.92 3498.92 3099.96 5198.43 15493.90 17999.71 4699.86 3295.88 4399.85 127
train_agg98.88 2298.65 2699.59 2599.92 3498.92 3099.96 5198.43 15494.35 15399.71 4699.86 3295.94 4099.85 12799.69 4899.98 3299.99 24
test_899.92 3498.88 3399.96 5198.43 15494.35 15399.69 4899.85 3695.94 4099.85 127
PGM-MVS98.34 5798.13 5998.99 8899.92 3497.00 13299.75 18199.50 1793.90 17999.37 8899.76 7093.24 125100.00 197.75 16999.96 4699.98 55
ACMMPcopyleft97.74 10197.44 10598.66 11199.92 3496.13 17599.18 29399.45 1894.84 12996.41 22399.71 9591.40 16999.99 3897.99 15298.03 18799.87 98
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
DVP-MVS++99.26 699.09 999.77 899.91 4299.31 1099.95 7098.43 15496.48 7799.80 2599.93 1197.44 14100.00 199.92 1599.98 32100.00 1
MSC_two_6792asdad99.93 299.91 4299.80 298.41 171100.00 199.96 11100.00 1100.00 1
No_MVS99.93 299.91 4299.80 298.41 171100.00 199.96 11100.00 1100.00 1
HPM-MVS++copyleft99.07 1198.88 1799.63 1899.90 4599.02 2699.95 7098.56 11197.56 3699.44 7999.85 3695.38 54100.00 199.31 6999.99 2199.87 98
APD-MVScopyleft98.62 3598.35 4599.41 4299.90 4598.51 6299.87 12898.36 18694.08 16699.74 4299.73 8994.08 9999.74 15399.42 6599.99 2199.99 24
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
DeepC-MVS_fast96.59 198.81 2598.54 3199.62 2199.90 4598.85 3699.24 28898.47 13898.14 1599.08 10699.91 1793.09 129100.00 199.04 8299.99 21100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OPU-MVS99.93 299.89 4899.80 299.96 5199.80 5797.44 14100.00 1100.00 199.98 32100.00 1
DPE-MVScopyleft99.26 699.10 899.74 1299.89 4899.24 2099.87 12898.44 14697.48 3899.64 5599.94 496.68 3099.99 3899.99 5100.00 199.99 24
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part299.89 4899.25 1999.49 76
CSCG97.10 13497.04 12497.27 22599.89 4891.92 31499.90 11299.07 3788.67 35595.26 25599.82 5293.17 12899.98 4998.15 14299.47 12299.90 94
ZNCC-MVS98.31 5998.03 6699.17 6499.88 5297.59 10399.94 8898.44 14694.31 15698.50 14399.82 5293.06 13099.99 3898.30 13399.99 2199.93 86
SR-MVS98.46 4698.30 4998.93 9499.88 5297.04 13199.84 14798.35 18894.92 12599.32 9099.80 5793.35 11899.78 14499.30 7099.95 5399.96 73
9.1498.38 4099.87 5499.91 10698.33 19393.22 20399.78 3699.89 2594.57 7999.85 12799.84 2799.97 42
SMA-MVScopyleft98.76 2898.48 3499.62 2199.87 5498.87 3499.86 13998.38 18293.19 20499.77 3799.94 495.54 48100.00 199.74 4199.99 21100.00 1
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
NormalMVS97.90 8397.85 8398.04 16399.86 5695.39 20799.61 22497.78 26296.52 7598.61 13699.31 15492.73 14099.67 16596.77 19799.48 11999.06 238
lecture98.67 3298.46 3599.28 5199.86 5697.88 9099.97 3899.25 3096.07 9599.79 3499.70 9892.53 14899.98 4999.51 5799.48 11999.97 65
PHI-MVS98.41 5298.21 5299.03 8399.86 5697.10 12999.98 2098.80 7090.78 31199.62 5999.78 6595.30 55100.00 199.80 3099.93 6499.99 24
MTAPA98.29 6197.96 7499.30 5099.85 5997.93 8899.39 26698.28 20295.76 10397.18 19699.88 2792.74 139100.00 198.67 10999.88 7699.99 24
LS3D95.84 19995.11 21298.02 16499.85 5995.10 22598.74 35098.50 13587.22 37793.66 27699.86 3287.45 23399.95 8390.94 31499.81 8699.02 242
HPM-MVScopyleft97.96 7897.72 8898.68 10899.84 6196.39 16199.90 11298.17 21792.61 23798.62 13599.57 12891.87 16599.67 16598.87 9799.99 2199.99 24
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
EI-MVSNet-Vis-set98.27 6298.11 6198.75 10499.83 6296.59 15399.40 26298.51 12995.29 11798.51 14299.76 7093.60 11499.71 15798.53 11999.52 11299.95 81
save fliter99.82 6398.79 4199.96 5198.40 17597.66 32
PLCcopyleft95.54 397.93 8197.89 8198.05 16299.82 6394.77 23599.92 9898.46 14093.93 17697.20 19499.27 15995.44 5399.97 6297.41 17499.51 11599.41 189
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
APD-MVS_3200maxsize98.25 6798.08 6398.78 10199.81 6596.60 15199.82 15798.30 20093.95 17599.37 8899.77 6892.84 13699.76 15098.95 8899.92 6799.97 65
EI-MVSNet-UG-set98.14 7397.99 6998.60 11699.80 6696.27 16499.36 27298.50 13595.21 11998.30 15499.75 7893.29 12299.73 15698.37 12899.30 13699.81 107
SR-MVS-dyc-post98.31 5998.17 5698.71 10699.79 6796.37 16299.76 17798.31 19794.43 14899.40 8599.75 7893.28 12399.78 14498.90 9599.92 6799.97 65
RE-MVS-def98.13 5999.79 6796.37 16299.76 17798.31 19794.43 14899.40 8599.75 7892.95 13398.90 9599.92 6799.97 65
HPM-MVS_fast97.80 9597.50 10198.68 10899.79 6796.42 15799.88 12598.16 22291.75 27598.94 11599.54 13191.82 16799.65 16997.62 17299.99 2199.99 24
SF-MVS98.67 3298.40 3899.50 3399.77 7098.67 5299.90 11298.21 21293.53 19199.81 2399.89 2594.70 7599.86 12699.84 2799.93 6499.96 73
MGCNet99.06 1398.84 1999.72 1499.76 7199.21 2299.99 599.34 2598.70 299.44 7999.75 7893.24 12599.99 3899.94 1399.41 12999.95 81
旧先验199.76 7197.52 10698.64 8999.85 3695.63 4799.94 5899.99 24
OMC-MVS97.28 12497.23 11697.41 21599.76 7193.36 28199.65 21397.95 24396.03 9697.41 18799.70 9889.61 20199.51 17596.73 19998.25 17799.38 191
新几何199.42 4199.75 7498.27 6998.63 9592.69 23299.55 6899.82 5294.40 83100.00 191.21 30699.94 5899.99 24
MP-MVS-pluss98.07 7797.64 9499.38 4799.74 7598.41 6799.74 18498.18 21693.35 19896.45 22099.85 3692.64 14399.97 6298.91 9499.89 7399.77 114
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
TSAR-MVS + MP.98.93 1998.77 2199.41 4299.74 7598.67 5299.77 17198.38 18296.73 6899.88 1199.74 8594.89 6899.59 17199.80 3099.98 3299.97 65
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
test1299.43 3999.74 7598.56 6098.40 17599.65 5294.76 7199.75 15199.98 3299.99 24
原ACMM198.96 9299.73 7896.99 13398.51 12994.06 16999.62 5999.85 3694.97 6799.96 7495.11 22799.95 5399.92 91
TSAR-MVS + GP.98.60 3698.51 3398.86 9799.73 7896.63 14899.97 3897.92 24898.07 1898.76 12899.55 12995.00 6599.94 9199.91 1897.68 19499.99 24
CANet98.27 6297.82 8599.63 1899.72 8099.10 2499.98 2098.51 12997.00 5898.52 14099.71 9587.80 22599.95 8399.75 3999.38 13199.83 103
reproduce_model98.75 2998.66 2599.03 8399.71 8197.10 12999.73 19198.23 21097.02 5799.18 10199.90 2194.54 8099.99 3899.77 3599.90 7299.99 24
F-COLMAP96.93 14696.95 12796.87 23899.71 8191.74 31999.85 14297.95 24393.11 21095.72 24499.16 17792.35 15499.94 9195.32 22399.35 13498.92 250
reproduce-ours98.78 2698.67 2399.09 7899.70 8397.30 11699.74 18498.25 20697.10 5299.10 10499.90 2194.59 7699.99 3899.77 3599.91 7099.99 24
our_new_method98.78 2698.67 2399.09 7899.70 8397.30 11699.74 18498.25 20697.10 5299.10 10499.90 2194.59 7699.99 3899.77 3599.91 7099.99 24
SD-MVS98.92 2098.70 2299.56 2899.70 8398.73 4999.94 8898.34 19296.38 8399.81 2399.76 7094.59 7699.98 4999.84 2799.96 4699.97 65
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
patch_mono-298.24 6899.12 595.59 27999.67 8686.91 40299.95 7098.89 5297.60 3399.90 699.76 7096.54 3399.98 4999.94 1399.82 8499.88 96
ACMMP_NAP98.49 4498.14 5899.54 3099.66 8798.62 5899.85 14298.37 18594.68 13699.53 7199.83 4992.87 135100.00 198.66 11199.84 7999.99 24
DeepPCF-MVS95.94 297.71 10598.98 1293.92 34599.63 8881.76 43799.96 5198.56 11199.47 199.19 10099.99 194.16 98100.00 199.92 1599.93 64100.00 1
EPNet98.49 4498.40 3898.77 10399.62 8996.80 14299.90 11299.51 1697.60 3399.20 9899.36 14993.71 11199.91 10897.99 15298.71 16299.61 145
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MM98.83 2398.53 3299.76 1099.59 9099.33 899.99 599.76 698.39 499.39 8799.80 5790.49 19099.96 7499.89 2099.43 12799.98 55
PVSNet_BlendedMVS96.05 19095.82 18496.72 24499.59 9096.99 13399.95 7099.10 3494.06 16998.27 15595.80 35089.00 21399.95 8399.12 7687.53 34293.24 404
PVSNet_Blended97.94 8097.64 9498.83 9899.59 9096.99 133100.00 199.10 3495.38 11498.27 15599.08 18189.00 21399.95 8399.12 7699.25 13899.57 156
PatchMatch-RL96.04 19195.40 19997.95 16699.59 9095.22 22099.52 24499.07 3793.96 17496.49 21998.35 26582.28 30299.82 13990.15 33099.22 14198.81 257
dcpmvs_297.42 11998.09 6295.42 28699.58 9487.24 39899.23 28996.95 37794.28 15998.93 11699.73 8994.39 8699.16 20399.89 2099.82 8499.86 100
test22299.55 9597.41 11499.34 27498.55 11791.86 27099.27 9699.83 4993.84 10899.95 5399.99 24
CNLPA97.76 9997.38 10898.92 9599.53 9696.84 13899.87 12898.14 22693.78 18396.55 21799.69 10292.28 15699.98 4997.13 18299.44 12699.93 86
API-MVS97.86 8697.66 9298.47 13399.52 9795.41 20599.47 25498.87 5791.68 27698.84 11999.85 3692.34 15599.99 3898.44 12499.96 46100.00 1
PVSNet91.05 1397.13 13396.69 14398.45 13599.52 9795.81 18499.95 7099.65 1294.73 13399.04 11199.21 17084.48 28599.95 8394.92 23398.74 16199.58 154
114514_t97.41 12096.83 13499.14 7199.51 9997.83 9299.89 12298.27 20488.48 35999.06 11099.66 11390.30 19399.64 17096.32 20899.97 4299.96 73
cl2293.77 27293.25 27695.33 29099.49 10094.43 24399.61 22498.09 22990.38 31989.16 34695.61 35890.56 18897.34 33291.93 29784.45 36394.21 349
testdata98.42 13999.47 10195.33 21198.56 11193.78 18399.79 3499.85 3693.64 11399.94 9194.97 23199.94 58100.00 1
MAR-MVS97.43 11597.19 11898.15 15599.47 10194.79 23499.05 31198.76 7292.65 23598.66 13399.82 5288.52 21999.98 4998.12 14399.63 9799.67 128
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
DP-MVS94.54 24493.42 26697.91 17299.46 10394.04 25898.93 32997.48 29981.15 43190.04 31799.55 12987.02 24199.95 8388.97 34298.11 18399.73 118
MVS_111021_LR98.42 5198.38 4098.53 12899.39 10495.79 18599.87 12899.86 296.70 6998.78 12399.79 6192.03 16299.90 11099.17 7599.86 7899.88 96
CHOSEN 280x42099.01 1699.03 1098.95 9399.38 10598.87 3498.46 36999.42 2197.03 5699.02 11299.09 18099.35 298.21 29499.73 4399.78 8799.77 114
MVS_111021_HR98.72 3098.62 2899.01 8799.36 10697.18 12299.93 9599.90 196.81 6698.67 13299.77 6893.92 10399.89 11599.27 7199.94 5899.96 73
DPM-MVS98.83 2398.46 3599.97 199.33 10799.92 199.96 5198.44 14697.96 2299.55 6899.94 497.18 22100.00 193.81 26499.94 5899.98 55
TAPA-MVS92.12 894.42 25293.60 25896.90 23799.33 10791.78 31899.78 16698.00 23789.89 33294.52 26199.47 13591.97 16399.18 20069.90 44899.52 11299.73 118
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
reproduce_monomvs95.38 21695.07 21496.32 25999.32 10996.60 15199.76 17798.85 6196.65 7187.83 36896.05 34799.52 198.11 29996.58 20381.07 39294.25 344
fmvsm_s_conf0.5_n_998.15 7298.02 6798.55 12299.28 11095.84 18399.99 598.57 10598.17 1299.93 299.74 8587.04 24099.97 6299.86 2599.59 10699.83 103
SPE-MVS-test97.88 8497.94 7697.70 18999.28 11095.20 22199.98 2097.15 34495.53 11199.62 5999.79 6192.08 16198.38 27798.75 10599.28 13799.52 168
test_fmvsm_n_192098.44 4898.61 2997.92 17099.27 11295.18 222100.00 198.90 5098.05 1999.80 2599.73 8992.64 14399.99 3899.58 5599.51 11598.59 267
fmvsm_s_conf0.5_n_1098.24 6897.90 7999.26 5399.24 11397.88 9099.99 598.76 7298.20 999.92 499.74 8585.97 25899.94 9199.72 4499.53 11199.96 73
fmvsm_l_conf0.5_n_a99.00 1798.91 1499.28 5199.21 11497.91 8999.98 2098.85 6198.25 599.92 499.75 7894.72 7399.97 6299.87 2399.64 9599.95 81
fmvsm_s_conf0.5_n_898.38 5698.05 6599.35 4899.20 11598.12 7599.98 2098.81 6698.22 799.80 2599.71 9587.37 23599.97 6299.91 1899.48 11999.97 65
test_yl97.83 9097.37 10999.21 5899.18 11697.98 8499.64 21799.27 2791.43 28597.88 17298.99 19195.84 4499.84 13598.82 9995.32 26999.79 110
DCV-MVSNet97.83 9097.37 10999.21 5899.18 11697.98 8499.64 21799.27 2791.43 28597.88 17298.99 19195.84 4499.84 13598.82 9995.32 26999.79 110
fmvsm_l_conf0.5_n98.94 1898.84 1999.25 5499.17 11897.81 9499.98 2098.86 5898.25 599.90 699.76 7094.21 9699.97 6299.87 2399.52 11299.98 55
DeepC-MVS94.51 496.92 14796.40 15698.45 13599.16 11995.90 18199.66 21298.06 23296.37 8694.37 26799.49 13483.29 29599.90 11097.63 17199.61 10299.55 158
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DELS-MVS98.54 4098.22 5199.50 3399.15 12098.65 56100.00 198.58 10397.70 3198.21 16099.24 16692.58 14699.94 9198.63 11499.94 5899.92 91
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
fmvsm_l_conf0.5_n_398.41 5298.08 6399.39 4499.12 12198.29 6899.98 2098.64 8998.14 1599.86 1499.76 7087.99 22499.97 6299.72 4499.54 10999.91 93
fmvsm_l_conf0.5_n_998.55 3998.23 5099.49 3599.10 12298.50 6399.99 598.70 7898.14 1599.94 199.68 10989.02 21299.98 4999.89 2099.61 10299.99 24
CS-MVS97.79 9797.91 7897.43 21399.10 12294.42 24499.99 597.10 35695.07 12099.68 4999.75 7892.95 13398.34 28198.38 12699.14 14399.54 162
Anonymous20240521193.10 29091.99 30396.40 25599.10 12289.65 36898.88 33597.93 24583.71 41594.00 27398.75 22768.79 40899.88 12195.08 22891.71 30299.68 126
fmvsm_s_conf0.5_n97.80 9597.85 8397.67 19099.06 12594.41 24599.98 2098.97 4397.34 4199.63 5699.69 10287.27 23699.97 6299.62 5399.06 14898.62 266
HyFIR lowres test96.66 16296.43 15497.36 22099.05 12693.91 26399.70 20399.80 390.54 31596.26 22698.08 27892.15 15998.23 29396.84 19695.46 26499.93 86
LFMVS94.75 23893.56 26198.30 14599.03 12795.70 19198.74 35097.98 24087.81 37098.47 14499.39 14667.43 41799.53 17298.01 15095.20 27299.67 128
fmvsm_s_conf0.5_n_497.75 10097.86 8297.42 21499.01 12894.69 23799.97 3898.76 7297.91 2499.87 1299.76 7086.70 24799.93 10199.67 5099.12 14697.64 295
fmvsm_s_conf0.5_n_297.59 11097.28 11398.53 12899.01 12898.15 7099.98 2098.59 10198.17 1299.75 3999.63 11981.83 30899.94 9199.78 3398.79 15997.51 303
AllTest92.48 30591.64 30895.00 29999.01 12888.43 38698.94 32796.82 39186.50 38688.71 35198.47 26074.73 38399.88 12185.39 38296.18 23996.71 309
TestCases95.00 29999.01 12888.43 38696.82 39186.50 38688.71 35198.47 26074.73 38399.88 12185.39 38296.18 23996.71 309
COLMAP_ROBcopyleft90.47 1492.18 31291.49 31494.25 33399.00 13288.04 39298.42 37596.70 39882.30 42688.43 36099.01 18876.97 35899.85 12786.11 37896.50 23194.86 320
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
fmvsm_s_conf0.5_n_397.95 7997.66 9298.81 9998.99 13398.07 7899.98 2098.81 6698.18 1199.89 999.70 9884.15 28899.97 6299.76 3899.50 11798.39 274
test_fmvs195.35 21795.68 19194.36 32998.99 13384.98 41399.96 5196.65 40097.60 3399.73 4498.96 19771.58 39899.93 10198.31 13299.37 13298.17 279
HY-MVS92.50 797.79 9797.17 12099.63 1898.98 13599.32 997.49 40399.52 1495.69 10698.32 15397.41 29893.32 12099.77 14798.08 14795.75 25499.81 107
VNet97.21 12996.57 14899.13 7598.97 13697.82 9399.03 31499.21 3294.31 15699.18 10198.88 20986.26 25499.89 11598.93 9094.32 28299.69 125
thres20096.96 14396.21 16399.22 5798.97 13698.84 3799.85 14299.71 793.17 20596.26 22698.88 20989.87 19899.51 17594.26 25294.91 27499.31 208
tfpn200view996.79 15195.99 17099.19 6098.94 13898.82 3899.78 16699.71 792.86 22096.02 23498.87 21689.33 20599.50 17793.84 26194.57 27899.27 217
thres40096.78 15395.99 17099.16 6798.94 13898.82 3899.78 16699.71 792.86 22096.02 23498.87 21689.33 20599.50 17793.84 26194.57 27899.16 226
sasdasda97.09 13696.32 15799.39 4498.93 14098.95 2899.72 19597.35 31294.45 14497.88 17299.42 13986.71 24599.52 17398.48 12193.97 28899.72 120
Anonymous2023121189.86 36288.44 37094.13 33698.93 14090.68 34698.54 36698.26 20576.28 44386.73 38295.54 36270.60 40497.56 32590.82 31780.27 40194.15 357
canonicalmvs97.09 13696.32 15799.39 4498.93 14098.95 2899.72 19597.35 31294.45 14497.88 17299.42 13986.71 24599.52 17398.48 12193.97 28899.72 120
SDMVSNet94.80 23393.96 24897.33 22398.92 14395.42 20499.59 22998.99 4092.41 24892.55 29197.85 28975.81 37398.93 21897.90 15891.62 30397.64 295
sd_testset93.55 27992.83 28395.74 27798.92 14390.89 34298.24 38298.85 6192.41 24892.55 29197.85 28971.07 40398.68 24693.93 25891.62 30397.64 295
EPNet_dtu95.71 20595.39 20096.66 24698.92 14393.41 27799.57 23498.90 5096.19 9397.52 18298.56 25092.65 14297.36 33077.89 42998.33 17299.20 224
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
WTY-MVS98.10 7597.60 9699.60 2398.92 14399.28 1799.89 12299.52 1495.58 10998.24 15999.39 14693.33 11999.74 15397.98 15495.58 26399.78 113
CHOSEN 1792x268896.81 15096.53 14997.64 19398.91 14793.07 28399.65 21399.80 395.64 10795.39 25198.86 21884.35 28799.90 11096.98 18999.16 14299.95 81
thres100view90096.74 15795.92 18099.18 6198.90 14898.77 4599.74 18499.71 792.59 23995.84 23898.86 21889.25 20799.50 17793.84 26194.57 27899.27 217
thres600view796.69 16095.87 18399.14 7198.90 14898.78 4499.74 18499.71 792.59 23995.84 23898.86 21889.25 20799.50 17793.44 27494.50 28199.16 226
MSDG94.37 25493.36 27397.40 21698.88 15093.95 26299.37 27097.38 30885.75 39790.80 31099.17 17484.11 29099.88 12186.35 37498.43 17098.36 276
MGCFI-Net97.00 14196.22 16299.34 4998.86 15198.80 4099.67 21197.30 32194.31 15697.77 17899.41 14386.36 25299.50 17798.38 12693.90 29099.72 120
h-mvs3394.92 23094.36 23496.59 24898.85 15291.29 33498.93 32998.94 4495.90 9898.77 12598.42 26390.89 18399.77 14797.80 16270.76 44098.72 263
Anonymous2024052992.10 31390.65 32596.47 25098.82 15390.61 34898.72 35298.67 8575.54 44793.90 27598.58 24866.23 42199.90 11094.70 24290.67 30698.90 253
PVSNet_Blended_VisFu97.27 12596.81 13698.66 11198.81 15496.67 14799.92 9898.64 8994.51 14196.38 22498.49 25689.05 21199.88 12197.10 18498.34 17199.43 186
PS-MVSNAJ98.44 4898.20 5399.16 6798.80 15598.92 3099.54 24298.17 21797.34 4199.85 1799.85 3691.20 17299.89 11599.41 6699.67 9398.69 264
CANet_DTU96.76 15496.15 16598.60 11698.78 15697.53 10599.84 14797.63 27797.25 4999.20 9899.64 11681.36 31499.98 4992.77 28598.89 15398.28 278
mvsany_test197.82 9397.90 7997.55 20298.77 15793.04 28699.80 16397.93 24596.95 6099.61 6699.68 10990.92 18099.83 13799.18 7498.29 17699.80 109
alignmvs97.81 9497.33 11199.25 5498.77 15798.66 5499.99 598.44 14694.40 15298.41 14899.47 13593.65 11299.42 18798.57 11594.26 28499.67 128
SymmetryMVS97.64 10897.46 10298.17 15198.74 15995.39 20799.61 22499.26 2996.52 7598.61 13699.31 15492.73 14099.67 16596.77 19795.63 26199.45 182
SteuartSystems-ACMMP99.02 1598.97 1399.18 6198.72 16097.71 9799.98 2098.44 14696.85 6199.80 2599.91 1797.57 899.85 12799.44 6499.99 2199.99 24
Skip Steuart: Steuart Systems R&D Blog.
xiu_mvs_v2_base98.23 7097.97 7199.02 8698.69 16198.66 5499.52 24498.08 23197.05 5599.86 1499.86 3290.65 18599.71 15799.39 6898.63 16398.69 264
miper_enhance_ethall94.36 25693.98 24795.49 28098.68 16295.24 21899.73 19197.29 32493.28 20289.86 32295.97 34894.37 8797.05 35392.20 28984.45 36394.19 350
fmvsm_s_conf0.5_n_598.08 7697.71 9099.17 6498.67 16397.69 10199.99 598.57 10597.40 3999.89 999.69 10285.99 25799.96 7499.80 3099.40 13099.85 101
ETVMVS97.03 14096.64 14498.20 15098.67 16397.12 12699.89 12298.57 10591.10 29798.17 16198.59 24593.86 10798.19 29595.64 22095.24 27199.28 215
test250697.53 11297.19 11898.58 12098.66 16596.90 13798.81 34499.77 594.93 12397.95 16798.96 19792.51 14999.20 19894.93 23298.15 18099.64 134
ECVR-MVScopyleft95.66 20895.05 21597.51 20798.66 16593.71 26798.85 34198.45 14194.93 12396.86 20598.96 19775.22 37999.20 19895.34 22298.15 18099.64 134
mamv495.24 22096.90 12990.25 40798.65 16772.11 45598.28 38097.64 27689.99 33095.93 23698.25 27394.74 7299.11 20499.01 8799.64 9599.53 166
balanced_conf0398.27 6297.99 6999.11 7698.64 16898.43 6699.47 25497.79 26094.56 13999.74 4298.35 26594.33 9099.25 19299.12 7699.96 4699.64 134
fmvsm_s_conf0.5_n_a97.73 10397.72 8897.77 18498.63 16994.26 25299.96 5198.92 4997.18 5199.75 3999.69 10287.00 24299.97 6299.46 6298.89 15399.08 236
MVSMamba_PlusPlus97.83 9097.45 10498.99 8898.60 17098.15 7099.58 23197.74 26790.34 32299.26 9798.32 26894.29 9299.23 19399.03 8599.89 7399.58 154
testing22297.08 13996.75 13998.06 16198.56 17196.82 13999.85 14298.61 9792.53 24398.84 11998.84 22293.36 11798.30 28595.84 21694.30 28399.05 240
test111195.57 21194.98 21897.37 21898.56 17193.37 28098.86 33998.45 14194.95 12296.63 21198.95 20275.21 38099.11 20495.02 22998.14 18299.64 134
MVSTER95.53 21295.22 20796.45 25398.56 17197.72 9699.91 10697.67 27292.38 25191.39 30197.14 30597.24 1997.30 33794.80 23887.85 33594.34 339
testing3-297.72 10497.43 10798.60 11698.55 17497.11 128100.00 199.23 3193.78 18397.90 16998.73 22995.50 5199.69 16198.53 11994.63 27698.99 244
VDD-MVS93.77 27292.94 28196.27 26098.55 17490.22 35798.77 34997.79 26090.85 30396.82 20799.42 13961.18 44199.77 14798.95 8894.13 28598.82 256
tpmvs94.28 25893.57 26096.40 25598.55 17491.50 33295.70 44098.55 11787.47 37292.15 29494.26 41391.42 16898.95 21788.15 35395.85 25098.76 259
UGNet95.33 21894.57 23097.62 19798.55 17494.85 23098.67 35899.32 2695.75 10496.80 20896.27 33772.18 39599.96 7494.58 24599.05 14998.04 284
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
PCF-MVS94.20 595.18 22294.10 24198.43 13798.55 17495.99 17997.91 39697.31 32090.35 32189.48 33599.22 16785.19 27199.89 11590.40 32798.47 16999.41 189
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
UWE-MVS-2895.95 19396.49 15094.34 33098.51 17989.99 36299.39 26698.57 10593.14 20797.33 19098.31 27093.44 11594.68 43093.69 27195.98 24498.34 277
UWE-MVS96.79 15196.72 14197.00 23298.51 17993.70 26899.71 19898.60 9992.96 21597.09 19798.34 26796.67 3298.85 22492.11 29596.50 23198.44 272
myMVS_eth3d2897.86 8697.59 9898.68 10898.50 18197.26 11899.92 9898.55 11793.79 18298.26 15798.75 22795.20 5699.48 18398.93 9096.40 23499.29 213
test_vis1_n_192095.44 21495.31 20395.82 27498.50 18188.74 38099.98 2097.30 32197.84 2799.85 1799.19 17266.82 41999.97 6298.82 9999.46 12498.76 259
BH-w/o95.71 20595.38 20196.68 24598.49 18392.28 30599.84 14797.50 29792.12 26192.06 29798.79 22584.69 28198.67 24895.29 22499.66 9499.09 234
baseline195.78 20194.86 22198.54 12698.47 18498.07 7899.06 30797.99 23892.68 23394.13 27298.62 24293.28 12398.69 24593.79 26685.76 35098.84 255
fmvsm_s_conf0.5_n_797.70 10697.74 8797.59 20098.44 18595.16 22499.97 3898.65 8697.95 2399.62 5999.78 6586.09 25599.94 9199.69 4899.50 11797.66 294
EPMVS96.53 16996.01 16998.09 15998.43 18696.12 17796.36 42799.43 2093.53 19197.64 18095.04 39094.41 8298.38 27791.13 30898.11 18399.75 116
kuosan93.17 28792.60 28994.86 30698.40 18789.54 37098.44 37198.53 12484.46 41088.49 35697.92 28690.57 18797.05 35383.10 39993.49 29397.99 285
WBMVS94.52 24794.03 24595.98 26698.38 18896.68 14699.92 9897.63 27790.75 31289.64 33095.25 38396.77 2696.90 36594.35 25083.57 37094.35 337
UBG97.84 8997.69 9198.29 14698.38 18896.59 15399.90 11298.53 12493.91 17898.52 14098.42 26396.77 2699.17 20198.54 11796.20 23899.11 233
sss97.57 11197.03 12599.18 6198.37 19098.04 8199.73 19199.38 2293.46 19498.76 12899.06 18391.21 17199.89 11596.33 20797.01 22299.62 141
testing1197.48 11497.27 11498.10 15898.36 19196.02 17899.92 9898.45 14193.45 19698.15 16298.70 23295.48 5299.22 19497.85 16095.05 27399.07 237
BH-untuned95.18 22294.83 22296.22 26198.36 19191.22 33599.80 16397.32 31990.91 30191.08 30498.67 23483.51 29298.54 25994.23 25399.61 10298.92 250
testing9197.16 13196.90 12997.97 16598.35 19395.67 19499.91 10698.42 16692.91 21897.33 19098.72 23094.81 7099.21 19596.98 18994.63 27699.03 241
testing9997.17 13096.91 12897.95 16698.35 19395.70 19199.91 10698.43 15492.94 21697.36 18898.72 23094.83 6999.21 19597.00 18794.64 27598.95 246
ET-MVSNet_ETH3D94.37 25493.28 27597.64 19398.30 19597.99 8399.99 597.61 28394.35 15371.57 45399.45 13896.23 3795.34 42096.91 19485.14 35799.59 148
AUN-MVS93.28 28492.60 28995.34 28998.29 19690.09 36099.31 27898.56 11191.80 27496.35 22598.00 28189.38 20498.28 28892.46 28669.22 44597.64 295
FMVSNet392.69 30091.58 31095.99 26598.29 19697.42 11399.26 28797.62 28089.80 33389.68 32695.32 37781.62 31296.27 39687.01 37085.65 35194.29 341
PMMVS96.76 15496.76 13896.76 24298.28 19892.10 30999.91 10697.98 24094.12 16499.53 7199.39 14686.93 24398.73 23896.95 19297.73 19199.45 182
hse-mvs294.38 25394.08 24495.31 29198.27 19990.02 36199.29 28398.56 11195.90 9898.77 12598.00 28190.89 18398.26 29297.80 16269.20 44697.64 295
PVSNet_088.03 1991.80 32090.27 33496.38 25798.27 19990.46 35299.94 8899.61 1393.99 17286.26 39297.39 30071.13 40299.89 11598.77 10367.05 45298.79 258
UA-Net96.54 16895.96 17698.27 14798.23 20195.71 19098.00 39498.45 14193.72 18798.41 14899.27 15988.71 21899.66 16891.19 30797.69 19299.44 185
test_cas_vis1_n_192096.59 16596.23 16097.65 19298.22 20294.23 25399.99 597.25 32997.77 2899.58 6799.08 18177.10 35399.97 6297.64 17099.45 12598.74 261
FE-MVS95.70 20795.01 21797.79 18098.21 20394.57 23995.03 44198.69 8088.90 34997.50 18496.19 33992.60 14599.49 18289.99 33297.94 18999.31 208
GG-mvs-BLEND98.54 12698.21 20398.01 8293.87 44698.52 12697.92 16897.92 28699.02 397.94 31298.17 14099.58 10799.67 128
mvs_anonymous95.65 20995.03 21697.53 20498.19 20595.74 18899.33 27597.49 29890.87 30290.47 31397.10 30788.23 22197.16 34495.92 21497.66 19599.68 126
MVS_Test96.46 17195.74 18798.61 11598.18 20697.23 12099.31 27897.15 34491.07 29898.84 11997.05 31188.17 22298.97 21494.39 24797.50 19799.61 145
BH-RMVSNet95.18 22294.31 23797.80 17898.17 20795.23 21999.76 17797.53 29392.52 24494.27 27099.25 16576.84 36098.80 22890.89 31699.54 10999.35 199
dongtai91.55 32691.13 31992.82 37598.16 20886.35 40399.47 25498.51 12983.24 41885.07 40297.56 29490.33 19294.94 42676.09 43791.73 30197.18 306
RPSCF91.80 32092.79 28588.83 41898.15 20969.87 45798.11 39096.60 40283.93 41394.33 26899.27 15979.60 33699.46 18691.99 29693.16 29897.18 306
ETV-MVS97.92 8297.80 8698.25 14898.14 21096.48 15599.98 2097.63 27795.61 10899.29 9499.46 13792.55 14798.82 22699.02 8698.54 16799.46 179
IS-MVSNet96.29 18295.90 18197.45 21098.13 21194.80 23399.08 30297.61 28392.02 26695.54 24998.96 19790.64 18698.08 30193.73 26997.41 20199.47 177
test_fmvsmconf_n98.43 5098.32 4698.78 10198.12 21296.41 15899.99 598.83 6598.22 799.67 5099.64 11691.11 17699.94 9199.67 5099.62 9899.98 55
fmvsm_s_conf0.1_n_297.25 12696.85 13398.43 13798.08 21398.08 7799.92 9897.76 26698.05 1999.65 5299.58 12580.88 32199.93 10199.59 5498.17 17897.29 304
ab-mvs94.69 23993.42 26698.51 13198.07 21496.26 16596.49 42598.68 8290.31 32394.54 26097.00 31376.30 36899.71 15795.98 21393.38 29699.56 157
XVG-OURS-SEG-HR94.79 23494.70 22995.08 29698.05 21589.19 37299.08 30297.54 29193.66 18894.87 25899.58 12578.78 34499.79 14297.31 17793.40 29596.25 313
EIA-MVS97.53 11297.46 10297.76 18698.04 21694.84 23199.98 2097.61 28394.41 15197.90 16999.59 12292.40 15398.87 22298.04 14999.13 14499.59 148
XVG-OURS94.82 23194.74 22895.06 29798.00 21789.19 37299.08 30297.55 28994.10 16594.71 25999.62 12080.51 32799.74 15396.04 21293.06 30096.25 313
mvsmamba96.94 14496.73 14097.55 20297.99 21894.37 24999.62 22097.70 26993.13 20898.42 14797.92 28688.02 22398.75 23698.78 10299.01 15099.52 168
dp95.05 22594.43 23296.91 23597.99 21892.73 29496.29 43097.98 24089.70 33495.93 23694.67 40393.83 10998.45 26586.91 37396.53 23099.54 162
tpmrst96.27 18495.98 17297.13 22797.96 22093.15 28296.34 42898.17 21792.07 26298.71 13195.12 38793.91 10498.73 23894.91 23596.62 22899.50 174
TR-MVS94.54 24493.56 26197.49 20997.96 22094.34 25098.71 35397.51 29690.30 32494.51 26298.69 23375.56 37498.77 23292.82 28495.99 24399.35 199
Vis-MVSNet (Re-imp)96.32 17995.98 17297.35 22297.93 22294.82 23299.47 25498.15 22591.83 27195.09 25699.11 17991.37 17097.47 32893.47 27397.43 19899.74 117
MDTV_nov1_ep1395.69 18997.90 22394.15 25595.98 43698.44 14693.12 20997.98 16695.74 35295.10 5998.58 25590.02 33196.92 224
Fast-Effi-MVS+95.02 22794.19 23997.52 20697.88 22494.55 24099.97 3897.08 36088.85 35194.47 26397.96 28584.59 28298.41 26989.84 33497.10 21599.59 148
ADS-MVSNet293.80 27193.88 25193.55 35897.87 22585.94 40794.24 44296.84 38890.07 32796.43 22194.48 40890.29 19495.37 41987.44 36097.23 20899.36 195
ADS-MVSNet94.79 23494.02 24697.11 22997.87 22593.79 26494.24 44298.16 22290.07 32796.43 22194.48 40890.29 19498.19 29587.44 36097.23 20899.36 195
Effi-MVS+96.30 18195.69 18998.16 15297.85 22796.26 16597.41 40597.21 33690.37 32098.65 13498.58 24886.61 24998.70 24497.11 18397.37 20299.52 168
PatchmatchNetpermissive95.94 19495.45 19697.39 21797.83 22894.41 24596.05 43498.40 17592.86 22097.09 19795.28 38294.21 9698.07 30389.26 34098.11 18399.70 123
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
cascas94.64 24293.61 25697.74 18897.82 22996.26 16599.96 5197.78 26285.76 39594.00 27397.54 29576.95 35999.21 19597.23 18095.43 26697.76 293
1112_ss96.01 19295.20 20898.42 13997.80 23096.41 15899.65 21396.66 39992.71 23092.88 28799.40 14492.16 15899.30 19091.92 29893.66 29199.55 158
Test_1112_low_res95.72 20394.83 22298.42 13997.79 23196.41 15899.65 21396.65 40092.70 23192.86 28896.13 34392.15 15999.30 19091.88 29993.64 29299.55 158
Effi-MVS+-dtu94.53 24695.30 20492.22 38397.77 23282.54 43099.59 22997.06 36494.92 12595.29 25395.37 37585.81 25997.89 31394.80 23897.07 21696.23 315
tpm cat193.51 28092.52 29596.47 25097.77 23291.47 33396.13 43298.06 23280.98 43292.91 28693.78 41789.66 19998.87 22287.03 36996.39 23599.09 234
FA-MVS(test-final)95.86 19795.09 21398.15 15597.74 23495.62 19696.31 42998.17 21791.42 28796.26 22696.13 34390.56 18899.47 18592.18 29097.07 21699.35 199
xiu_mvs_v1_base_debu97.43 11597.06 12198.55 12297.74 23498.14 7299.31 27897.86 25496.43 8099.62 5999.69 10285.56 26699.68 16299.05 7998.31 17397.83 289
xiu_mvs_v1_base97.43 11597.06 12198.55 12297.74 23498.14 7299.31 27897.86 25496.43 8099.62 5999.69 10285.56 26699.68 16299.05 7998.31 17397.83 289
xiu_mvs_v1_base_debi97.43 11597.06 12198.55 12297.74 23498.14 7299.31 27897.86 25496.43 8099.62 5999.69 10285.56 26699.68 16299.05 7998.31 17397.83 289
EPP-MVSNet96.69 16096.60 14696.96 23497.74 23493.05 28599.37 27098.56 11188.75 35395.83 24099.01 18896.01 3898.56 25796.92 19397.20 21099.25 219
gg-mvs-nofinetune93.51 28091.86 30798.47 13397.72 23997.96 8792.62 45298.51 12974.70 45097.33 19069.59 46798.91 497.79 31697.77 16799.56 10899.67 128
IB-MVS92.85 694.99 22893.94 24998.16 15297.72 23995.69 19399.99 598.81 6694.28 15992.70 28996.90 31595.08 6099.17 20196.07 21173.88 43399.60 147
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
thisisatest051597.41 12097.02 12698.59 11997.71 24197.52 10699.97 3898.54 12191.83 27197.45 18599.04 18597.50 999.10 20694.75 24096.37 23699.16 226
VortexMVS94.11 26093.50 26395.94 26897.70 24296.61 15099.35 27397.18 33993.52 19389.57 33395.74 35287.55 23096.97 36195.76 21985.13 35894.23 346
viewdifsd2359ckpt0996.21 18695.77 18597.53 20497.69 24394.50 24199.78 16697.23 33492.88 21996.58 21499.26 16384.85 27698.66 25196.61 20197.02 22199.43 186
Syy-MVS90.00 36090.63 32688.11 42597.68 24474.66 45399.71 19898.35 18890.79 30992.10 29598.67 23479.10 34293.09 44563.35 46095.95 24796.59 311
myMVS_eth3d94.46 25194.76 22793.55 35897.68 24490.97 33799.71 19898.35 18890.79 30992.10 29598.67 23492.46 15293.09 44587.13 36695.95 24796.59 311
test_fmvs1_n94.25 25994.36 23493.92 34597.68 24483.70 42099.90 11296.57 40397.40 3999.67 5098.88 20961.82 43899.92 10798.23 13899.13 14498.14 282
fmvsm_s_conf0.5_n_698.27 6297.96 7499.23 5697.66 24798.11 7699.98 2098.64 8997.85 2699.87 1299.72 9288.86 21599.93 10199.64 5299.36 13399.63 140
RRT-MVS96.24 18595.68 19197.94 16997.65 24894.92 22999.27 28697.10 35692.79 22697.43 18697.99 28381.85 30799.37 18998.46 12398.57 16499.53 166
diffmvspermissive97.00 14196.64 14498.09 15997.64 24996.17 17499.81 15997.19 33794.67 13798.95 11499.28 15686.43 25098.76 23498.37 12897.42 20099.33 202
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
viewcassd2359sk1196.59 16596.23 16097.66 19197.63 25094.70 23699.77 17197.33 31693.41 19797.34 18999.17 17486.72 24498.83 22597.40 17597.32 20599.46 179
viewdifsd2359ckpt1396.19 18795.77 18597.45 21097.62 25194.40 24799.70 20397.23 33492.76 22896.63 21199.05 18484.96 27598.64 25296.65 20097.35 20399.31 208
Vis-MVSNetpermissive95.72 20395.15 21197.45 21097.62 25194.28 25199.28 28498.24 20894.27 16196.84 20698.94 20479.39 33798.76 23493.25 27598.49 16899.30 211
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
thisisatest053097.10 13496.72 14198.22 14997.60 25396.70 14399.92 9898.54 12191.11 29697.07 19998.97 19597.47 1299.03 20993.73 26996.09 24198.92 250
GDP-MVS97.88 8497.59 9898.75 10497.59 25497.81 9499.95 7097.37 31194.44 14799.08 10699.58 12597.13 2499.08 20794.99 23098.17 17899.37 193
miper_ehance_all_eth93.16 28892.60 28994.82 30797.57 25593.56 27299.50 24897.07 36388.75 35388.85 35095.52 36490.97 17996.74 37590.77 31884.45 36394.17 351
guyue97.15 13296.82 13598.15 15597.56 25696.25 16999.71 19897.84 25795.75 10498.13 16398.65 23787.58 22998.82 22698.29 13497.91 19099.36 195
viewmanbaseed2359cas96.45 17296.07 16697.59 20097.55 25794.59 23899.70 20397.33 31693.62 19097.00 20199.32 15185.57 26598.71 24197.26 17997.33 20499.47 177
testing393.92 26594.23 23892.99 37297.54 25890.23 35699.99 599.16 3390.57 31491.33 30398.63 24192.99 13192.52 44982.46 40395.39 26796.22 316
SSM_040495.75 20295.16 21097.50 20897.53 25995.39 20799.11 29897.25 32990.81 30595.27 25498.83 22384.74 27898.67 24895.24 22597.69 19298.45 271
LCM-MVSNet-Re92.31 30992.60 28991.43 39297.53 25979.27 44799.02 31691.83 46292.07 26280.31 42694.38 41183.50 29395.48 41697.22 18197.58 19699.54 162
GBi-Net90.88 33789.82 34394.08 33797.53 25991.97 31098.43 37296.95 37787.05 37889.68 32694.72 39971.34 39996.11 40287.01 37085.65 35194.17 351
test190.88 33789.82 34394.08 33797.53 25991.97 31098.43 37296.95 37787.05 37889.68 32694.72 39971.34 39996.11 40287.01 37085.65 35194.17 351
FMVSNet291.02 33489.56 34895.41 28797.53 25995.74 18898.98 31997.41 30687.05 37888.43 36095.00 39371.34 39996.24 39885.12 38585.21 35694.25 344
tttt051796.85 14896.49 15097.92 17097.48 26495.89 18299.85 14298.54 12190.72 31396.63 21198.93 20797.47 1299.02 21093.03 28295.76 25398.85 254
BP-MVS198.33 5898.18 5598.81 9997.44 26597.98 8499.96 5198.17 21794.88 12798.77 12599.59 12297.59 799.08 20798.24 13798.93 15299.36 195
casdiffmvs_mvgpermissive96.43 17395.94 17897.89 17497.44 26595.47 20099.86 13997.29 32493.35 19896.03 23399.19 17285.39 26998.72 24097.89 15997.04 21899.49 176
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
EC-MVSNet97.38 12297.24 11597.80 17897.41 26795.64 19599.99 597.06 36494.59 13899.63 5699.32 15189.20 21098.14 29798.76 10499.23 14099.62 141
viewdifsd2359ckpt0795.83 20095.42 19897.07 23097.40 26893.04 28699.60 22797.24 33292.39 25096.09 23299.14 17883.07 29898.93 21897.02 18696.87 22599.23 222
c3_l92.53 30491.87 30694.52 31997.40 26892.99 28899.40 26296.93 38287.86 36888.69 35395.44 36989.95 19796.44 38890.45 32480.69 39794.14 360
viewmambaseed2359dif95.92 19695.55 19597.04 23197.38 27093.41 27799.78 16696.97 37591.14 29596.58 21499.27 15984.85 27698.75 23696.87 19597.12 21498.97 245
fmvsm_s_conf0.1_n97.30 12397.21 11797.60 19997.38 27094.40 24799.90 11298.64 8996.47 7999.51 7599.65 11584.99 27499.93 10199.22 7399.09 14798.46 270
CDS-MVSNet96.34 17896.07 16697.13 22797.37 27294.96 22799.53 24397.91 24991.55 27995.37 25298.32 26895.05 6297.13 34793.80 26595.75 25499.30 211
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
TESTMET0.1,196.74 15796.26 15998.16 15297.36 27396.48 15599.96 5198.29 20191.93 26795.77 24198.07 27995.54 4898.29 28690.55 32298.89 15399.70 123
miper_lstm_enhance91.81 31791.39 31693.06 37197.34 27489.18 37499.38 26896.79 39386.70 38587.47 37495.22 38490.00 19695.86 41188.26 35181.37 38694.15 357
baseline96.43 17395.98 17297.76 18697.34 27495.17 22399.51 24697.17 34193.92 17796.90 20499.28 15685.37 27098.64 25297.50 17396.86 22799.46 179
cl____92.31 30991.58 31094.52 31997.33 27692.77 29099.57 23496.78 39486.97 38287.56 37295.51 36589.43 20396.62 38088.60 34582.44 37894.16 356
SD_040392.63 30393.38 27090.40 40697.32 27777.91 44997.75 40198.03 23691.89 26890.83 30998.29 27282.00 30493.79 43988.51 34995.75 25499.52 168
DIV-MVS_self_test92.32 30891.60 30994.47 32397.31 27892.74 29299.58 23196.75 39586.99 38187.64 37095.54 36289.55 20296.50 38588.58 34682.44 37894.17 351
casdiffmvspermissive96.42 17595.97 17597.77 18497.30 27994.98 22699.84 14797.09 35993.75 18696.58 21499.26 16385.07 27298.78 23197.77 16797.04 21899.54 162
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
GeoE94.36 25693.48 26496.99 23397.29 28093.54 27399.96 5196.72 39788.35 36293.43 27798.94 20482.05 30398.05 30488.12 35596.48 23399.37 193
eth_miper_zixun_eth92.41 30791.93 30493.84 34997.28 28190.68 34698.83 34296.97 37588.57 35889.19 34595.73 35589.24 20996.69 37889.97 33381.55 38494.15 357
MVSFormer96.94 14496.60 14697.95 16697.28 28197.70 9999.55 24097.27 32691.17 29299.43 8199.54 13190.92 18096.89 36694.67 24399.62 9899.25 219
lupinMVS97.85 8897.60 9698.62 11497.28 28197.70 9999.99 597.55 28995.50 11399.43 8199.67 11190.92 18098.71 24198.40 12599.62 9899.45 182
diffmvs_AUTHOR96.75 15696.41 15597.79 18097.20 28495.46 20199.69 20697.15 34494.46 14398.78 12399.21 17085.64 26398.77 23298.27 13597.31 20699.13 230
mamba_040894.98 22994.09 24297.64 19397.14 28595.31 21293.48 44997.08 36090.48 31694.40 26498.62 24284.49 28398.67 24893.99 25697.18 21198.93 247
SSM_0407294.77 23694.09 24296.82 23997.14 28595.31 21293.48 44997.08 36090.48 31694.40 26498.62 24284.49 28396.21 39993.99 25697.18 21198.93 247
SSM_040795.62 21094.95 21997.61 19897.14 28595.31 21299.00 31797.25 32990.81 30594.40 26498.83 22384.74 27898.58 25595.24 22597.18 21198.93 247
SCA94.69 23993.81 25397.33 22397.10 28894.44 24298.86 33998.32 19593.30 20196.17 23195.59 36076.48 36697.95 31091.06 31097.43 19899.59 148
viewmacassd2359aftdt95.93 19595.45 19697.36 22097.09 28994.12 25799.57 23497.26 32893.05 21396.50 21899.17 17482.76 29998.68 24696.61 20197.04 21899.28 215
KinetiMVS96.10 18895.29 20598.53 12897.08 29097.12 12699.56 23798.12 22894.78 13098.44 14598.94 20480.30 33199.39 18891.56 30398.79 15999.06 238
TAMVS95.85 19895.58 19396.65 24797.07 29193.50 27499.17 29497.82 25991.39 28995.02 25798.01 28092.20 15797.30 33793.75 26895.83 25199.14 229
Fast-Effi-MVS+-dtu93.72 27593.86 25293.29 36397.06 29286.16 40499.80 16396.83 38992.66 23492.58 29097.83 29181.39 31397.67 32189.75 33596.87 22596.05 318
CostFormer96.10 18895.88 18296.78 24197.03 29392.55 30097.08 41497.83 25890.04 32998.72 13094.89 39795.01 6498.29 28696.54 20495.77 25299.50 174
test_fmvsmvis_n_192097.67 10797.59 9897.91 17297.02 29495.34 21099.95 7098.45 14197.87 2597.02 20099.59 12289.64 20099.98 4999.41 6699.34 13598.42 273
test-LLR96.47 17096.04 16897.78 18297.02 29495.44 20299.96 5198.21 21294.07 16795.55 24796.38 33293.90 10598.27 29090.42 32598.83 15799.64 134
test-mter96.39 17695.93 17997.78 18297.02 29495.44 20299.96 5198.21 21291.81 27395.55 24796.38 33295.17 5798.27 29090.42 32598.83 15799.64 134
icg_test_0407_295.04 22694.78 22695.84 27396.97 29791.64 32598.63 36197.12 34992.33 25395.60 24598.88 20985.65 26196.56 38392.12 29195.70 25799.32 204
IMVS_040795.21 22194.80 22596.46 25296.97 29791.64 32598.81 34497.12 34992.33 25395.60 24598.88 20985.65 26198.42 26792.12 29195.70 25799.32 204
IMVS_040493.83 26793.17 27795.80 27596.97 29791.64 32597.78 40097.12 34992.33 25390.87 30898.88 20976.78 36196.43 38992.12 29195.70 25799.32 204
IMVS_040395.25 21994.81 22496.58 24996.97 29791.64 32598.97 32497.12 34992.33 25395.43 25098.88 20985.78 26098.79 22992.12 29195.70 25799.32 204
gm-plane-assit96.97 29793.76 26691.47 28398.96 19798.79 22994.92 233
WB-MVSnew92.90 29492.77 28693.26 36596.95 30293.63 27099.71 19898.16 22291.49 28094.28 26998.14 27681.33 31596.48 38679.47 42095.46 26489.68 446
QAPM95.40 21594.17 24099.10 7796.92 30397.71 9799.40 26298.68 8289.31 33788.94 34998.89 20882.48 30199.96 7493.12 28199.83 8099.62 141
KD-MVS_2432*160088.00 38286.10 38693.70 35496.91 30494.04 25897.17 41197.12 34984.93 40581.96 41692.41 43092.48 15094.51 43279.23 42152.68 46692.56 416
miper_refine_blended88.00 38286.10 38693.70 35496.91 30494.04 25897.17 41197.12 34984.93 40581.96 41692.41 43092.48 15094.51 43279.23 42152.68 46692.56 416
tpm295.47 21395.18 20996.35 25896.91 30491.70 32396.96 41797.93 24588.04 36698.44 14595.40 37193.32 12097.97 30794.00 25595.61 26299.38 191
FMVSNet588.32 37887.47 38090.88 39596.90 30788.39 38897.28 40895.68 42482.60 42584.67 40492.40 43279.83 33491.16 45476.39 43681.51 38593.09 407
3Dnovator+91.53 1196.31 18095.24 20699.52 3196.88 30898.64 5799.72 19598.24 20895.27 11888.42 36298.98 19382.76 29999.94 9197.10 18499.83 8099.96 73
Patchmatch-test92.65 30291.50 31396.10 26496.85 30990.49 35191.50 45797.19 33782.76 42490.23 31495.59 36095.02 6398.00 30677.41 43196.98 22399.82 105
MVS96.60 16495.56 19499.72 1496.85 30999.22 2198.31 37898.94 4491.57 27890.90 30799.61 12186.66 24899.96 7497.36 17699.88 7699.99 24
3Dnovator91.47 1296.28 18395.34 20299.08 8096.82 31197.47 11199.45 25998.81 6695.52 11289.39 33699.00 19081.97 30599.95 8397.27 17899.83 8099.84 102
EI-MVSNet93.73 27493.40 26994.74 30896.80 31292.69 29599.06 30797.67 27288.96 34691.39 30199.02 18688.75 21797.30 33791.07 30987.85 33594.22 347
CVMVSNet94.68 24194.94 22093.89 34896.80 31286.92 40199.06 30798.98 4194.45 14494.23 27199.02 18685.60 26495.31 42190.91 31595.39 26799.43 186
IterMVS-LS92.69 30092.11 30094.43 32796.80 31292.74 29299.45 25996.89 38588.98 34489.65 32995.38 37488.77 21696.34 39390.98 31382.04 38194.22 347
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
AstraMVS96.57 16796.46 15396.91 23596.79 31592.50 30199.90 11297.38 30896.02 9797.79 17799.32 15186.36 25298.99 21198.26 13696.33 23799.23 222
IterMVS90.91 33690.17 33893.12 36896.78 31690.42 35498.89 33397.05 36789.03 34186.49 38795.42 37076.59 36495.02 42387.22 36584.09 36693.93 378
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
131496.84 14995.96 17699.48 3896.74 31798.52 6198.31 37898.86 5895.82 10189.91 32098.98 19387.49 23299.96 7497.80 16299.73 9099.96 73
IterMVS-SCA-FT90.85 33990.16 33992.93 37396.72 31889.96 36398.89 33396.99 37188.95 34786.63 38495.67 35676.48 36695.00 42487.04 36884.04 36993.84 385
MVS-HIRNet86.22 38983.19 40295.31 29196.71 31990.29 35592.12 45497.33 31662.85 46186.82 38170.37 46669.37 40797.49 32775.12 43997.99 18898.15 280
viewdifsd2359ckpt1194.09 26293.63 25595.46 28496.68 32088.92 37799.62 22097.12 34993.07 21195.73 24299.22 16777.05 35498.88 22196.52 20587.69 34098.58 268
viewmsd2359difaftdt94.09 26293.64 25495.46 28496.68 32088.92 37799.62 22097.13 34893.07 21195.73 24299.22 16777.05 35498.89 22096.52 20587.70 33998.58 268
VDDNet93.12 28991.91 30596.76 24296.67 32292.65 29898.69 35698.21 21282.81 42397.75 17999.28 15661.57 43999.48 18398.09 14694.09 28698.15 280
dmvs_re93.20 28693.15 27893.34 36196.54 32383.81 41998.71 35398.51 12991.39 28992.37 29398.56 25078.66 34697.83 31593.89 25989.74 30798.38 275
Elysia94.50 24893.38 27097.85 17696.49 32496.70 14398.98 31997.78 26290.81 30596.19 22998.55 25273.63 39098.98 21289.41 33698.56 16597.88 287
StellarMVS94.50 24893.38 27097.85 17696.49 32496.70 14398.98 31997.78 26290.81 30596.19 22998.55 25273.63 39098.98 21289.41 33698.56 16597.88 287
MIMVSNet90.30 35288.67 36695.17 29596.45 32691.64 32592.39 45397.15 34485.99 39290.50 31293.19 42566.95 41894.86 42882.01 40793.43 29499.01 243
CR-MVSNet93.45 28392.62 28895.94 26896.29 32792.66 29692.01 45596.23 41192.62 23696.94 20293.31 42391.04 17796.03 40779.23 42195.96 24599.13 230
RPMNet89.76 36487.28 38197.19 22696.29 32792.66 29692.01 45598.31 19770.19 45796.94 20285.87 45987.25 23799.78 14462.69 46195.96 24599.13 230
tt080591.28 32990.18 33794.60 31496.26 32987.55 39498.39 37698.72 7689.00 34389.22 34298.47 26062.98 43498.96 21690.57 32188.00 33497.28 305
Patchmtry89.70 36588.49 36993.33 36296.24 33089.94 36691.37 45896.23 41178.22 44087.69 36993.31 42391.04 17796.03 40780.18 41982.10 38094.02 368
test_vis1_rt86.87 38786.05 38989.34 41496.12 33178.07 44899.87 12883.54 47492.03 26578.21 43789.51 44445.80 45999.91 10896.25 20993.11 29990.03 443
JIA-IIPM91.76 32390.70 32494.94 30196.11 33287.51 39593.16 45198.13 22775.79 44697.58 18177.68 46492.84 13697.97 30788.47 35096.54 22999.33 202
OpenMVScopyleft90.15 1594.77 23693.59 25998.33 14396.07 33397.48 11099.56 23798.57 10590.46 31886.51 38698.95 20278.57 34799.94 9193.86 26099.74 8997.57 300
PAPM98.60 3698.42 3799.14 7196.05 33498.96 2799.90 11299.35 2496.68 7098.35 15299.66 11396.45 3498.51 26099.45 6399.89 7399.96 73
CLD-MVS94.06 26493.90 25094.55 31896.02 33590.69 34599.98 2097.72 26896.62 7491.05 30698.85 22177.21 35298.47 26198.11 14489.51 31394.48 325
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
PatchT90.38 34988.75 36595.25 29395.99 33690.16 35891.22 45997.54 29176.80 44297.26 19386.01 45891.88 16496.07 40666.16 45695.91 24999.51 172
ACMH+89.98 1690.35 35089.54 34992.78 37795.99 33686.12 40598.81 34497.18 33989.38 33683.14 41297.76 29268.42 41298.43 26689.11 34186.05 34993.78 388
DeepMVS_CXcopyleft82.92 43695.98 33858.66 46796.01 41692.72 22978.34 43695.51 36558.29 44598.08 30182.57 40285.29 35492.03 424
ACMP92.05 992.74 29892.42 29793.73 35095.91 33988.72 38199.81 15997.53 29394.13 16387.00 38098.23 27474.07 38798.47 26196.22 21088.86 32093.99 373
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
test_vis1_n93.61 27893.03 28095.35 28895.86 34086.94 40099.87 12896.36 40996.85 6199.54 7098.79 22552.41 45399.83 13798.64 11298.97 15199.29 213
HQP-NCC95.78 34199.87 12896.82 6393.37 278
ACMP_Plane95.78 34199.87 12896.82 6393.37 278
HQP-MVS94.61 24394.50 23194.92 30295.78 34191.85 31599.87 12897.89 25096.82 6393.37 27898.65 23780.65 32598.39 27397.92 15689.60 30894.53 321
NP-MVS95.77 34491.79 31798.65 237
test_fmvsmconf0.1_n97.74 10197.44 10598.64 11395.76 34596.20 17199.94 8898.05 23498.17 1298.89 11899.42 13987.65 22799.90 11099.50 5999.60 10599.82 105
plane_prior695.76 34591.72 32280.47 329
ACMM91.95 1092.88 29592.52 29593.98 34495.75 34789.08 37699.77 17197.52 29593.00 21489.95 31997.99 28376.17 37098.46 26493.63 27288.87 31994.39 333
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
GA-MVS93.83 26792.84 28296.80 24095.73 34893.57 27199.88 12597.24 33292.57 24192.92 28596.66 32478.73 34597.67 32187.75 35894.06 28799.17 225
plane_prior195.73 348
jason97.24 12796.86 13298.38 14295.73 34897.32 11599.97 3897.40 30795.34 11698.60 13999.54 13187.70 22698.56 25797.94 15599.47 12299.25 219
jason: jason.
mmtdpeth88.52 37687.75 37890.85 39795.71 35183.47 42598.94 32794.85 43988.78 35297.19 19589.58 44363.29 43298.97 21498.54 11762.86 46090.10 442
HQP_MVS94.49 25094.36 23494.87 30395.71 35191.74 31999.84 14797.87 25296.38 8393.01 28398.59 24580.47 32998.37 27997.79 16589.55 31194.52 323
plane_prior795.71 35191.59 331
ITE_SJBPF92.38 38095.69 35485.14 41195.71 42392.81 22389.33 33998.11 27770.23 40598.42 26785.91 38088.16 33293.59 396
fmvsm_s_conf0.1_n_a97.09 13696.90 12997.63 19695.65 35594.21 25499.83 15498.50 13596.27 9099.65 5299.64 11684.72 28099.93 10199.04 8298.84 15698.74 261
ACMH89.72 1790.64 34389.63 34693.66 35695.64 35688.64 38498.55 36497.45 30089.03 34181.62 41997.61 29369.75 40698.41 26989.37 33887.62 34193.92 379
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
baseline296.71 15996.49 15097.37 21895.63 35795.96 18099.74 18498.88 5492.94 21691.61 29998.97 19597.72 698.62 25494.83 23798.08 18697.53 302
FMVSNet188.50 37786.64 38494.08 33795.62 35891.97 31098.43 37296.95 37783.00 42186.08 39494.72 39959.09 44496.11 40281.82 40984.07 36794.17 351
LuminaMVS96.63 16396.21 16397.87 17595.58 35996.82 13999.12 29697.67 27294.47 14297.88 17298.31 27087.50 23198.71 24198.07 14897.29 20798.10 283
LPG-MVS_test92.96 29292.71 28793.71 35295.43 36088.67 38299.75 18197.62 28092.81 22390.05 31598.49 25675.24 37798.40 27195.84 21689.12 31594.07 365
LGP-MVS_train93.71 35295.43 36088.67 38297.62 28092.81 22390.05 31598.49 25675.24 37798.40 27195.84 21689.12 31594.07 365
tpm93.70 27693.41 26894.58 31695.36 36287.41 39697.01 41596.90 38490.85 30396.72 21094.14 41490.40 19196.84 37090.75 31988.54 32799.51 172
D2MVS92.76 29792.59 29393.27 36495.13 36389.54 37099.69 20699.38 2292.26 25887.59 37194.61 40585.05 27397.79 31691.59 30288.01 33392.47 419
VPA-MVSNet92.70 29991.55 31296.16 26295.09 36496.20 17198.88 33599.00 3991.02 30091.82 29895.29 38176.05 37297.96 30995.62 22181.19 38794.30 340
LTVRE_ROB88.28 1890.29 35389.05 36094.02 34095.08 36590.15 35997.19 41097.43 30284.91 40783.99 40897.06 31074.00 38898.28 28884.08 39187.71 33793.62 395
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
TinyColmap87.87 38486.51 38591.94 38695.05 36685.57 40997.65 40294.08 44984.40 41181.82 41896.85 31962.14 43798.33 28280.25 41886.37 34891.91 426
test0.0.03 193.86 26693.61 25694.64 31295.02 36792.18 30899.93 9598.58 10394.07 16787.96 36698.50 25593.90 10594.96 42581.33 41093.17 29796.78 308
UniMVSNet (Re)93.07 29192.13 29995.88 27094.84 36896.24 17099.88 12598.98 4192.49 24689.25 34095.40 37187.09 23997.14 34693.13 28078.16 41194.26 342
USDC90.00 36088.96 36193.10 37094.81 36988.16 39098.71 35395.54 42893.66 18883.75 41097.20 30465.58 42398.31 28483.96 39487.49 34392.85 413
VPNet91.81 31790.46 32895.85 27294.74 37095.54 19998.98 31998.59 10192.14 26090.77 31197.44 29768.73 41097.54 32694.89 23677.89 41394.46 326
FIs94.10 26193.43 26596.11 26394.70 37196.82 13999.58 23198.93 4892.54 24289.34 33897.31 30187.62 22897.10 35094.22 25486.58 34694.40 332
UniMVSNet_ETH3D90.06 35988.58 36894.49 32294.67 37288.09 39197.81 39997.57 28883.91 41488.44 35897.41 29857.44 44697.62 32391.41 30488.59 32697.77 292
UniMVSNet_NR-MVSNet92.95 29392.11 30095.49 28094.61 37395.28 21699.83 15499.08 3691.49 28089.21 34396.86 31887.14 23896.73 37693.20 27677.52 41694.46 326
test_fmvs289.47 36989.70 34588.77 42194.54 37475.74 45099.83 15494.70 44594.71 13491.08 30496.82 32354.46 44997.78 31892.87 28388.27 33092.80 414
MonoMVSNet94.82 23194.43 23295.98 26694.54 37490.73 34499.03 31497.06 36493.16 20693.15 28295.47 36888.29 22097.57 32497.85 16091.33 30599.62 141
WR-MVS92.31 30991.25 31795.48 28394.45 37695.29 21599.60 22798.68 8290.10 32688.07 36596.89 31680.68 32496.80 37493.14 27979.67 40494.36 334
nrg03093.51 28092.53 29496.45 25394.36 37797.20 12199.81 15997.16 34391.60 27789.86 32297.46 29686.37 25197.68 32095.88 21580.31 40094.46 326
tfpnnormal89.29 37287.61 37994.34 33094.35 37894.13 25698.95 32698.94 4483.94 41284.47 40595.51 36574.84 38297.39 32977.05 43480.41 39891.48 429
FC-MVSNet-test93.81 27093.15 27895.80 27594.30 37996.20 17199.42 26198.89 5292.33 25389.03 34897.27 30387.39 23496.83 37293.20 27686.48 34794.36 334
SSC-MVS3.289.59 36788.66 36792.38 38094.29 38086.12 40599.49 25097.66 27590.28 32588.63 35595.18 38564.46 42896.88 36885.30 38482.66 37594.14 360
MS-PatchMatch90.65 34290.30 33391.71 39194.22 38185.50 41098.24 38297.70 26988.67 35586.42 38996.37 33467.82 41598.03 30583.62 39699.62 9891.60 427
WR-MVS_H91.30 32790.35 33194.15 33494.17 38292.62 29999.17 29498.94 4488.87 35086.48 38894.46 41084.36 28696.61 38188.19 35278.51 40993.21 405
DU-MVS92.46 30691.45 31595.49 28094.05 38395.28 21699.81 15998.74 7592.25 25989.21 34396.64 32681.66 31096.73 37693.20 27677.52 41694.46 326
NR-MVSNet91.56 32590.22 33595.60 27894.05 38395.76 18798.25 38198.70 7891.16 29480.78 42596.64 32683.23 29696.57 38291.41 30477.73 41594.46 326
CP-MVSNet91.23 33190.22 33594.26 33293.96 38592.39 30499.09 30098.57 10588.95 34786.42 38996.57 32979.19 34096.37 39190.29 32878.95 40694.02 368
XXY-MVS91.82 31690.46 32895.88 27093.91 38695.40 20698.87 33897.69 27188.63 35787.87 36797.08 30874.38 38697.89 31391.66 30184.07 36794.35 337
PS-CasMVS90.63 34489.51 35193.99 34393.83 38791.70 32398.98 31998.52 12688.48 35986.15 39396.53 33175.46 37596.31 39588.83 34378.86 40893.95 376
test_040285.58 39183.94 39690.50 40393.81 38885.04 41298.55 36495.20 43676.01 44479.72 43195.13 38664.15 43096.26 39766.04 45786.88 34590.21 440
XVG-ACMP-BASELINE91.22 33290.75 32392.63 37993.73 38985.61 40898.52 36897.44 30192.77 22789.90 32196.85 31966.64 42098.39 27392.29 28888.61 32493.89 381
TranMVSNet+NR-MVSNet91.68 32490.61 32794.87 30393.69 39093.98 26199.69 20698.65 8691.03 29988.44 35896.83 32280.05 33396.18 40090.26 32976.89 42494.45 331
TransMVSNet (Re)87.25 38585.28 39293.16 36793.56 39191.03 33698.54 36694.05 45183.69 41681.09 42396.16 34075.32 37696.40 39076.69 43568.41 44892.06 423
v1090.25 35488.82 36394.57 31793.53 39293.43 27699.08 30296.87 38785.00 40487.34 37894.51 40680.93 32097.02 36082.85 40179.23 40593.26 403
testgi89.01 37488.04 37591.90 38793.49 39384.89 41499.73 19195.66 42593.89 18185.14 40098.17 27559.68 44394.66 43177.73 43088.88 31896.16 317
v890.54 34689.17 35694.66 31193.43 39493.40 27999.20 29196.94 38185.76 39587.56 37294.51 40681.96 30697.19 34384.94 38778.25 41093.38 401
V4291.28 32990.12 34094.74 30893.42 39593.46 27599.68 20997.02 36887.36 37489.85 32495.05 38981.31 31697.34 33287.34 36380.07 40293.40 399
pm-mvs189.36 37187.81 37794.01 34193.40 39691.93 31398.62 36296.48 40786.25 39083.86 40996.14 34273.68 38997.04 35686.16 37775.73 42993.04 409
v114491.09 33389.83 34294.87 30393.25 39793.69 26999.62 22096.98 37386.83 38489.64 33094.99 39480.94 31997.05 35385.08 38681.16 38893.87 383
v119290.62 34589.25 35594.72 31093.13 39893.07 28399.50 24897.02 36886.33 38989.56 33495.01 39179.22 33997.09 35282.34 40581.16 38894.01 370
v2v48291.30 32790.07 34195.01 29893.13 39893.79 26499.77 17197.02 36888.05 36589.25 34095.37 37580.73 32397.15 34587.28 36480.04 40394.09 364
OPM-MVS93.21 28592.80 28494.44 32593.12 40090.85 34399.77 17197.61 28396.19 9391.56 30098.65 23775.16 38198.47 26193.78 26789.39 31493.99 373
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
v14419290.79 34089.52 35094.59 31593.11 40192.77 29099.56 23796.99 37186.38 38889.82 32594.95 39680.50 32897.10 35083.98 39380.41 39893.90 380
PEN-MVS90.19 35689.06 35993.57 35793.06 40290.90 34199.06 30798.47 13888.11 36485.91 39596.30 33676.67 36295.94 41087.07 36776.91 42393.89 381
v124090.20 35588.79 36494.44 32593.05 40392.27 30699.38 26896.92 38385.89 39389.36 33794.87 39877.89 35197.03 35880.66 41481.08 39194.01 370
v14890.70 34189.63 34693.92 34592.97 40490.97 33799.75 18196.89 38587.51 37188.27 36395.01 39181.67 30997.04 35687.40 36277.17 42193.75 389
v192192090.46 34789.12 35794.50 32192.96 40592.46 30299.49 25096.98 37386.10 39189.61 33295.30 37878.55 34897.03 35882.17 40680.89 39694.01 370
MVStest185.03 39782.76 40691.83 38892.95 40689.16 37598.57 36394.82 44071.68 45568.54 45895.11 38883.17 29795.66 41474.69 44065.32 45590.65 436
tt0320-xc82.94 41180.35 41890.72 40192.90 40783.54 42396.85 42094.73 44363.12 46079.85 43093.77 41849.43 45795.46 41780.98 41371.54 43893.16 406
Baseline_NR-MVSNet90.33 35189.51 35192.81 37692.84 40889.95 36499.77 17193.94 45284.69 40989.04 34795.66 35781.66 31096.52 38490.99 31276.98 42291.97 425
test_method80.79 41779.70 42084.08 43392.83 40967.06 45999.51 24695.42 43054.34 46581.07 42493.53 42044.48 46092.22 45178.90 42577.23 42092.94 411
pmmvs492.10 31391.07 32195.18 29492.82 41094.96 22799.48 25396.83 38987.45 37388.66 35496.56 33083.78 29196.83 37289.29 33984.77 36193.75 389
LF4IMVS89.25 37388.85 36290.45 40592.81 41181.19 44098.12 38994.79 44191.44 28486.29 39197.11 30665.30 42698.11 29988.53 34885.25 35592.07 422
tt032083.56 41081.15 41390.77 39992.77 41283.58 42296.83 42195.52 42963.26 45981.36 42192.54 42853.26 45195.77 41280.45 41574.38 43292.96 410
DTE-MVSNet89.40 37088.24 37392.88 37492.66 41389.95 36499.10 29998.22 21187.29 37585.12 40196.22 33876.27 36995.30 42283.56 39775.74 42893.41 398
EU-MVSNet90.14 35890.34 33289.54 41392.55 41481.06 44198.69 35698.04 23591.41 28886.59 38596.84 32180.83 32293.31 44486.20 37681.91 38294.26 342
APD_test181.15 41580.92 41581.86 43792.45 41559.76 46696.04 43593.61 45573.29 45377.06 44096.64 32644.28 46196.16 40172.35 44482.52 37689.67 447
sc_t185.01 39882.46 40892.67 37892.44 41683.09 42697.39 40695.72 42265.06 45885.64 39896.16 34049.50 45697.34 33284.86 38875.39 43097.57 300
our_test_390.39 34889.48 35393.12 36892.40 41789.57 36999.33 27596.35 41087.84 36985.30 39994.99 39484.14 28996.09 40580.38 41684.56 36293.71 394
ppachtmachnet_test89.58 36888.35 37193.25 36692.40 41790.44 35399.33 27596.73 39685.49 40085.90 39695.77 35181.09 31896.00 40976.00 43882.49 37793.30 402
v7n89.65 36688.29 37293.72 35192.22 41990.56 35099.07 30697.10 35685.42 40286.73 38294.72 39980.06 33297.13 34781.14 41178.12 41293.49 397
dmvs_testset83.79 40786.07 38876.94 44192.14 42048.60 47696.75 42290.27 46689.48 33578.65 43498.55 25279.25 33886.65 46466.85 45482.69 37495.57 319
PS-MVSNAJss93.64 27793.31 27494.61 31392.11 42192.19 30799.12 29697.38 30892.51 24588.45 35796.99 31491.20 17297.29 34094.36 24887.71 33794.36 334
pmmvs590.17 35789.09 35893.40 36092.10 42289.77 36799.74 18495.58 42785.88 39487.24 37995.74 35273.41 39296.48 38688.54 34783.56 37193.95 376
N_pmnet80.06 42080.78 41677.89 44091.94 42345.28 47898.80 34756.82 48078.10 44180.08 42893.33 42177.03 35695.76 41368.14 45282.81 37392.64 415
test_djsdf92.83 29692.29 29894.47 32391.90 42492.46 30299.55 24097.27 32691.17 29289.96 31896.07 34681.10 31796.89 36694.67 24388.91 31794.05 367
SixPastTwentyTwo88.73 37588.01 37690.88 39591.85 42582.24 43298.22 38695.18 43788.97 34582.26 41596.89 31671.75 39796.67 37984.00 39282.98 37293.72 393
K. test v388.05 38187.24 38290.47 40491.82 42682.23 43398.96 32597.42 30489.05 34076.93 44295.60 35968.49 41195.42 41885.87 38181.01 39493.75 389
OurMVSNet-221017-089.81 36389.48 35390.83 39891.64 42781.21 43998.17 38895.38 43291.48 28285.65 39797.31 30172.66 39397.29 34088.15 35384.83 36093.97 375
mvs_tets91.81 31791.08 32094.00 34291.63 42890.58 34998.67 35897.43 30292.43 24787.37 37797.05 31171.76 39697.32 33594.75 24088.68 32394.11 363
Gipumacopyleft66.95 43365.00 43372.79 44691.52 42967.96 45866.16 47095.15 43847.89 46758.54 46467.99 46929.74 46587.54 46350.20 46877.83 41462.87 469
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
test_fmvsmconf0.01_n96.39 17695.74 18798.32 14491.47 43095.56 19899.84 14797.30 32197.74 2997.89 17199.35 15079.62 33599.85 12799.25 7299.24 13999.55 158
jajsoiax91.92 31591.18 31894.15 33491.35 43190.95 34099.00 31797.42 30492.61 23787.38 37697.08 30872.46 39497.36 33094.53 24688.77 32194.13 362
MDA-MVSNet-bldmvs84.09 40581.52 41291.81 38991.32 43288.00 39398.67 35895.92 41880.22 43555.60 46793.32 42268.29 41393.60 44273.76 44176.61 42593.82 387
MVP-Stereo90.93 33590.45 33092.37 38291.25 43388.76 37998.05 39396.17 41387.27 37684.04 40695.30 37878.46 34997.27 34283.78 39599.70 9291.09 430
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MDA-MVSNet_test_wron85.51 39383.32 40192.10 38490.96 43488.58 38599.20 29196.52 40579.70 43757.12 46692.69 42779.11 34193.86 43877.10 43377.46 41893.86 384
YYNet185.50 39483.33 40092.00 38590.89 43588.38 38999.22 29096.55 40479.60 43857.26 46592.72 42679.09 34393.78 44077.25 43277.37 41993.84 385
anonymousdsp91.79 32290.92 32294.41 32890.76 43692.93 28998.93 32997.17 34189.08 33987.46 37595.30 37878.43 35096.92 36492.38 28788.73 32293.39 400
lessismore_v090.53 40290.58 43780.90 44295.80 41977.01 44195.84 34966.15 42296.95 36283.03 40075.05 43193.74 392
EG-PatchMatch MVS85.35 39583.81 39889.99 41190.39 43881.89 43598.21 38796.09 41581.78 42874.73 44893.72 41951.56 45597.12 34979.16 42488.61 32490.96 433
EGC-MVSNET69.38 42663.76 43686.26 43090.32 43981.66 43896.24 43193.85 4530.99 4773.22 47892.33 43352.44 45292.92 44759.53 46484.90 35984.21 458
CMPMVSbinary61.59 2184.75 40185.14 39383.57 43490.32 43962.54 46296.98 41697.59 28774.33 45169.95 45596.66 32464.17 42998.32 28387.88 35788.41 32989.84 445
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
new_pmnet84.49 40482.92 40489.21 41590.03 44182.60 42996.89 41995.62 42680.59 43375.77 44789.17 44565.04 42794.79 42972.12 44581.02 39390.23 439
pmmvs685.69 39083.84 39791.26 39490.00 44284.41 41797.82 39896.15 41475.86 44581.29 42295.39 37361.21 44096.87 36983.52 39873.29 43492.50 418
ttmdpeth88.23 38087.06 38391.75 39089.91 44387.35 39798.92 33295.73 42187.92 36784.02 40796.31 33568.23 41496.84 37086.33 37576.12 42691.06 431
DSMNet-mixed88.28 37988.24 37388.42 42389.64 44475.38 45298.06 39289.86 46785.59 39988.20 36492.14 43476.15 37191.95 45278.46 42796.05 24297.92 286
UnsupCasMVSNet_eth85.52 39283.99 39490.10 40989.36 44583.51 42496.65 42397.99 23889.14 33875.89 44693.83 41663.25 43393.92 43681.92 40867.90 45192.88 412
Anonymous2023120686.32 38885.42 39189.02 41789.11 44680.53 44599.05 31195.28 43385.43 40182.82 41393.92 41574.40 38593.44 44366.99 45381.83 38393.08 408
Anonymous2024052185.15 39683.81 39889.16 41688.32 44782.69 42898.80 34795.74 42079.72 43681.53 42090.99 43765.38 42594.16 43472.69 44381.11 39090.63 437
OpenMVS_ROBcopyleft79.82 2083.77 40881.68 41190.03 41088.30 44882.82 42798.46 36995.22 43573.92 45276.00 44591.29 43655.00 44896.94 36368.40 45188.51 32890.34 438
test20.0384.72 40283.99 39486.91 42888.19 44980.62 44498.88 33595.94 41788.36 36178.87 43294.62 40468.75 40989.11 45966.52 45575.82 42791.00 432
KD-MVS_self_test83.59 40982.06 40988.20 42486.93 45080.70 44397.21 40996.38 40882.87 42282.49 41488.97 44667.63 41692.32 45073.75 44262.30 46291.58 428
MIMVSNet182.58 41280.51 41788.78 41986.68 45184.20 41896.65 42395.41 43178.75 43978.59 43592.44 42951.88 45489.76 45865.26 45878.95 40692.38 421
CL-MVSNet_self_test84.50 40383.15 40388.53 42286.00 45281.79 43698.82 34397.35 31285.12 40383.62 41190.91 43976.66 36391.40 45369.53 44960.36 46392.40 420
UnsupCasMVSNet_bld79.97 42277.03 42788.78 41985.62 45381.98 43493.66 44797.35 31275.51 44870.79 45483.05 46148.70 45894.91 42778.31 42860.29 46489.46 450
mvs5depth84.87 39982.90 40590.77 39985.59 45484.84 41591.10 46093.29 45783.14 41985.07 40294.33 41262.17 43697.32 33578.83 42672.59 43790.14 441
Patchmatch-RL test86.90 38685.98 39089.67 41284.45 45575.59 45189.71 46392.43 45986.89 38377.83 43990.94 43894.22 9493.63 44187.75 35869.61 44299.79 110
pmmvs-eth3d84.03 40681.97 41090.20 40884.15 45687.09 39998.10 39194.73 44383.05 42074.10 45187.77 45265.56 42494.01 43581.08 41269.24 44489.49 449
test_fmvs379.99 42180.17 41979.45 43984.02 45762.83 46099.05 31193.49 45688.29 36380.06 42986.65 45628.09 46788.00 46088.63 34473.27 43587.54 456
PM-MVS80.47 41878.88 42285.26 43183.79 45872.22 45495.89 43891.08 46485.71 39876.56 44488.30 44836.64 46393.90 43782.39 40469.57 44389.66 448
new-patchmatchnet81.19 41479.34 42186.76 42982.86 45980.36 44697.92 39595.27 43482.09 42772.02 45286.87 45562.81 43590.74 45671.10 44663.08 45989.19 452
FE-MVSNET81.05 41678.81 42387.79 42681.98 46083.70 42098.23 38491.78 46381.27 43074.29 45087.44 45360.92 44290.67 45764.92 45968.43 44789.01 453
mvsany_test382.12 41381.14 41485.06 43281.87 46170.41 45697.09 41392.14 46091.27 29177.84 43888.73 44739.31 46295.49 41590.75 31971.24 43989.29 451
WB-MVS76.28 42477.28 42673.29 44581.18 46254.68 47097.87 39794.19 44881.30 42969.43 45690.70 44077.02 35782.06 46835.71 47368.11 45083.13 459
test_f78.40 42377.59 42580.81 43880.82 46362.48 46396.96 41793.08 45883.44 41774.57 44984.57 46027.95 46892.63 44884.15 39072.79 43687.32 457
SSC-MVS75.42 42576.40 42872.49 44980.68 46453.62 47197.42 40494.06 45080.42 43468.75 45790.14 44276.54 36581.66 46933.25 47466.34 45482.19 460
pmmvs380.27 41977.77 42487.76 42780.32 46582.43 43198.23 38491.97 46172.74 45478.75 43387.97 45157.30 44790.99 45570.31 44762.37 46189.87 444
testf168.38 42966.92 43072.78 44778.80 46650.36 47390.95 46187.35 47255.47 46358.95 46288.14 44920.64 47287.60 46157.28 46564.69 45680.39 462
APD_test268.38 42966.92 43072.78 44778.80 46650.36 47390.95 46187.35 47255.47 46358.95 46288.14 44920.64 47287.60 46157.28 46564.69 45680.39 462
ambc83.23 43577.17 46862.61 46187.38 46594.55 44776.72 44386.65 45630.16 46496.36 39284.85 38969.86 44190.73 435
test_vis3_rt68.82 42766.69 43275.21 44476.24 46960.41 46596.44 42668.71 47975.13 44950.54 47069.52 46816.42 47796.32 39480.27 41766.92 45368.89 466
TDRefinement84.76 40082.56 40791.38 39374.58 47084.80 41697.36 40794.56 44684.73 40880.21 42796.12 34563.56 43198.39 27387.92 35663.97 45890.95 434
E-PMN52.30 43752.18 43952.67 45571.51 47145.40 47793.62 44876.60 47736.01 47143.50 47264.13 47127.11 46967.31 47431.06 47526.06 47045.30 473
EMVS51.44 43951.22 44152.11 45670.71 47244.97 47994.04 44475.66 47835.34 47342.40 47361.56 47428.93 46665.87 47527.64 47624.73 47145.49 472
PMMVS267.15 43264.15 43576.14 44370.56 47362.07 46493.89 44587.52 47158.09 46260.02 46178.32 46322.38 47184.54 46659.56 46347.03 46881.80 461
FPMVS68.72 42868.72 42968.71 45165.95 47444.27 48095.97 43794.74 44251.13 46653.26 46890.50 44125.11 47083.00 46760.80 46280.97 39578.87 464
wuyk23d20.37 44320.84 44618.99 45965.34 47527.73 48250.43 4717.67 4839.50 4768.01 4776.34 4776.13 48026.24 47623.40 47710.69 4752.99 474
LCM-MVSNet67.77 43164.73 43476.87 44262.95 47656.25 46989.37 46493.74 45444.53 46861.99 46080.74 46220.42 47486.53 46569.37 45059.50 46587.84 454
MVEpermissive53.74 2251.54 43847.86 44262.60 45359.56 47750.93 47279.41 46877.69 47635.69 47236.27 47461.76 4735.79 48169.63 47237.97 47236.61 46967.24 467
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ANet_high56.10 43552.24 43867.66 45249.27 47856.82 46883.94 46682.02 47570.47 45633.28 47564.54 47017.23 47669.16 47345.59 47023.85 47277.02 465
tmp_tt65.23 43462.94 43772.13 45044.90 47950.03 47581.05 46789.42 47038.45 46948.51 47199.90 2154.09 45078.70 47191.84 30018.26 47387.64 455
PMVScopyleft49.05 2353.75 43651.34 44060.97 45440.80 48034.68 48174.82 46989.62 46937.55 47028.67 47672.12 4657.09 47981.63 47043.17 47168.21 44966.59 468
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
test12337.68 44139.14 44433.31 45719.94 48124.83 48398.36 3779.75 48215.53 47551.31 46987.14 45419.62 47517.74 47747.10 4693.47 47657.36 470
testmvs40.60 44044.45 44329.05 45819.49 48214.11 48499.68 20918.47 48120.74 47464.59 45998.48 25910.95 47817.09 47856.66 46711.01 47455.94 471
mmdepth0.00 4460.00 4490.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 4790.00 4790.00 4820.00 4790.00 4780.00 4770.00 475
monomultidepth0.00 4460.00 4490.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 4790.00 4790.00 4820.00 4790.00 4780.00 4770.00 475
test_blank0.00 4460.00 4490.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 4790.02 4780.00 4820.00 4790.00 4780.00 4770.00 475
eth-test20.00 483
eth-test0.00 483
uanet_test0.00 4460.00 4490.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 4790.00 4790.00 4820.00 4790.00 4780.00 4770.00 475
DCPMVS0.00 4460.00 4490.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 4790.00 4790.00 4820.00 4790.00 4780.00 4770.00 475
cdsmvs_eth3d_5k23.43 44231.24 4450.00 4600.00 4830.00 4850.00 47298.09 2290.00 4780.00 47999.67 11183.37 2940.00 4790.00 4780.00 4770.00 475
pcd_1.5k_mvsjas7.60 44510.13 4480.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 4790.00 47991.20 1720.00 4790.00 4780.00 4770.00 475
sosnet-low-res0.00 4460.00 4490.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 4790.00 4790.00 4820.00 4790.00 4780.00 4770.00 475
sosnet0.00 4460.00 4490.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 4790.00 4790.00 4820.00 4790.00 4780.00 4770.00 475
uncertanet0.00 4460.00 4490.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 4790.00 4790.00 4820.00 4790.00 4780.00 4770.00 475
Regformer0.00 4460.00 4490.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 4790.00 4790.00 4820.00 4790.00 4780.00 4770.00 475
ab-mvs-re8.28 44411.04 4470.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 47999.40 1440.00 4820.00 4790.00 4780.00 4770.00 475
uanet0.00 4460.00 4490.00 4600.00 4830.00 4850.00 4720.00 4840.00 4780.00 4790.00 4790.00 4820.00 4790.00 4780.00 4770.00 475
TestfortrainingZip99.97 38
WAC-MVS90.97 33786.10 379
PC_three_145296.96 5999.80 2599.79 6197.49 10100.00 199.99 599.98 32100.00 1
test_241102_TWO98.43 15497.27 4699.80 2599.94 497.18 22100.00 1100.00 1100.00 1100.00 1
test_0728_THIRD96.48 7799.83 2199.91 1797.87 5100.00 199.92 15100.00 1100.00 1
GSMVS99.59 148
sam_mvs194.72 7399.59 148
sam_mvs94.25 93
MTGPAbinary98.28 202
test_post195.78 43959.23 47593.20 12797.74 31991.06 310
test_post63.35 47294.43 8198.13 298
patchmatchnet-post91.70 43595.12 5897.95 310
MTMP99.87 12896.49 406
test9_res99.71 4699.99 21100.00 1
agg_prior299.48 61100.00 1100.00 1
test_prior498.05 8099.94 88
test_prior299.95 7095.78 10299.73 4499.76 7096.00 3999.78 33100.00 1
旧先验299.46 25894.21 16299.85 1799.95 8396.96 191
新几何299.40 262
无先验99.49 25098.71 7793.46 194100.00 194.36 24899.99 24
原ACMM299.90 112
testdata299.99 3890.54 323
segment_acmp96.68 30
testdata199.28 28496.35 89
plane_prior597.87 25298.37 27997.79 16589.55 31194.52 323
plane_prior498.59 245
plane_prior391.64 32596.63 7293.01 283
plane_prior299.84 14796.38 83
plane_prior91.74 31999.86 13996.76 6789.59 310
n20.00 484
nn0.00 484
door-mid89.69 468
test1198.44 146
door90.31 465
HQP5-MVS91.85 315
BP-MVS97.92 156
HQP4-MVS93.37 27898.39 27394.53 321
HQP3-MVS97.89 25089.60 308
HQP2-MVS80.65 325
MDTV_nov1_ep13_2view96.26 16596.11 43391.89 26898.06 16494.40 8394.30 25199.67 128
ACMMP++_ref87.04 344
ACMMP++88.23 331
Test By Simon92.82 138