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
DVP-MVS99.03 198.83 299.63 399.72 1299.25 298.97 6398.58 14097.62 999.45 799.46 897.42 499.94 398.47 1599.81 1099.69 45
APDe-MVS99.02 298.84 199.55 599.57 3198.96 999.39 598.93 3797.38 2299.41 999.54 196.66 1199.84 5198.86 199.85 399.87 1
DPE-MVS98.92 398.67 599.65 299.58 3099.20 598.42 16298.91 4397.58 1299.54 599.46 897.10 799.94 397.64 5599.84 899.83 5
SteuartSystems-ACMMP98.90 498.75 399.36 2099.22 8798.43 3099.10 4398.87 5597.38 2299.35 1299.40 1297.78 299.87 4397.77 4699.85 399.78 12
Skip Steuart: Steuart Systems R&D Blog.
TSAR-MVS + MP.98.78 598.62 699.24 3899.69 2398.28 4499.14 3698.66 12696.84 4999.56 399.31 3196.34 1799.70 10998.32 2399.73 4199.73 35
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
CNVR-MVS98.78 598.56 899.45 1399.32 6298.87 1298.47 15498.81 7597.72 598.76 4799.16 5797.05 899.78 9098.06 3199.66 5499.69 45
MSP-MVS98.74 798.55 999.29 2999.75 398.23 4599.26 1898.88 4997.52 1399.41 998.78 10696.00 3299.79 8697.79 4599.59 6599.85 2
XVS98.70 898.49 1499.34 2299.70 2198.35 3999.29 1498.88 4997.40 1998.46 6299.20 4895.90 3899.89 3497.85 4199.74 3999.78 12
Regformer-298.69 998.52 1199.19 4199.35 5498.01 5898.37 16698.81 7597.48 1699.21 1999.21 4496.13 2599.80 7498.40 2199.73 4199.75 27
Regformer-198.66 1098.51 1299.12 5399.35 5497.81 6698.37 16698.76 9497.49 1599.20 2099.21 4496.08 2799.79 8698.42 1999.73 4199.75 27
MCST-MVS98.65 1198.37 1999.48 999.60 2998.87 1298.41 16398.68 11597.04 4498.52 6198.80 10496.78 1099.83 5497.93 3599.61 6199.74 32
Regformer-498.64 1298.53 1098.99 5999.43 5197.37 7998.40 16498.79 8897.46 1799.09 2699.31 3195.86 4099.80 7498.64 399.76 3099.79 9
SD-MVS98.64 1298.68 498.53 8799.33 5998.36 3898.90 7298.85 6397.28 2799.72 299.39 1396.63 1397.60 31298.17 2699.85 399.64 64
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
HFP-MVS98.63 1498.40 1699.32 2799.72 1298.29 4299.23 2198.96 3296.10 7798.94 3499.17 5296.06 2899.92 2097.62 5699.78 2199.75 27
ACMMP_NAP98.61 1598.30 3099.55 599.62 2898.95 1098.82 9198.81 7595.80 8599.16 2299.47 795.37 5499.92 2097.89 3999.75 3699.79 9
region2R98.61 1598.38 1899.29 2999.74 798.16 5199.23 2198.93 3796.15 7298.94 3499.17 5295.91 3799.94 397.55 6499.79 1799.78 12
NCCC98.61 1598.35 2299.38 1799.28 7698.61 2198.45 15598.76 9497.82 498.45 6598.93 9196.65 1299.83 5497.38 7199.41 9099.71 42
xxxxxxxxxxxxxcwj98.59 1898.32 2899.41 1599.54 3398.71 1599.04 5098.81 7595.12 11999.32 1399.39 1396.22 1899.84 5197.72 4999.73 4199.67 55
SF-MVS98.59 1898.32 2899.41 1599.54 3398.71 1599.04 5098.81 7595.12 11999.32 1399.39 1396.22 1899.84 5197.72 4999.73 4199.67 55
Regformer-398.59 1898.50 1398.86 6999.43 5197.05 9298.40 16498.68 11597.43 1899.06 2799.31 3195.80 4199.77 9598.62 599.76 3099.78 12
ACMMPR98.59 1898.36 2099.29 2999.74 798.15 5299.23 2198.95 3496.10 7798.93 3899.19 5195.70 4299.94 397.62 5699.79 1799.78 12
SMA-MVS98.58 2298.25 3499.56 499.51 3799.04 898.95 6798.80 8693.67 18999.37 1199.52 396.52 1599.89 3498.06 3199.81 1099.76 25
MTAPA98.58 2298.29 3199.46 1199.76 198.64 1998.90 7298.74 9897.27 3198.02 8499.39 1394.81 7199.96 197.91 3699.79 1799.77 19
HPM-MVS++copyleft98.58 2298.25 3499.55 599.50 3999.08 798.72 11598.66 12697.51 1498.15 7598.83 10195.70 4299.92 2097.53 6699.67 5199.66 59
SR-MVS98.57 2598.35 2299.24 3899.53 3598.18 4999.09 4498.82 6996.58 5999.10 2599.32 2995.39 5299.82 6197.70 5299.63 5899.72 38
CP-MVS98.57 2598.36 2099.19 4199.66 2597.86 6399.34 1198.87 5595.96 8098.60 5899.13 5996.05 3099.94 397.77 4699.86 199.77 19
MSLP-MVS++98.56 2798.57 798.55 8399.26 7996.80 10198.71 11699.05 2497.28 2798.84 4199.28 3696.47 1699.40 14998.52 1399.70 4899.47 92
zzz-MVS98.55 2898.25 3499.46 1199.76 198.64 1998.55 14498.74 9897.27 3198.02 8499.39 1394.81 7199.96 197.91 3699.79 1799.77 19
DeepC-MVS_fast96.70 198.55 2898.34 2499.18 4599.25 8098.04 5698.50 15198.78 9097.72 598.92 3999.28 3695.27 5899.82 6197.55 6499.77 2499.69 45
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
#test#98.54 3098.27 3299.32 2799.72 1298.29 4298.98 6298.96 3295.65 9398.94 3499.17 5296.06 2899.92 2097.21 7599.78 2199.75 27
APD-MVS_3200maxsize98.53 3198.33 2799.15 5099.50 3997.92 6299.15 3598.81 7596.24 6899.20 2099.37 2195.30 5799.80 7497.73 4899.67 5199.72 38
mPP-MVS98.51 3298.26 3399.25 3799.75 398.04 5699.28 1698.81 7596.24 6898.35 7199.23 4195.46 4899.94 397.42 6999.81 1099.77 19
ZNCC-MVS98.49 3398.20 4099.35 2199.73 1198.39 3199.19 3198.86 6095.77 8698.31 7499.10 6495.46 4899.93 1497.57 6399.81 1099.74 32
PGM-MVS98.49 3398.23 3899.27 3699.72 1298.08 5598.99 5999.49 595.43 10299.03 2899.32 2995.56 4499.94 396.80 9999.77 2499.78 12
EI-MVSNet-Vis-set98.47 3598.39 1798.69 7499.46 4796.49 11698.30 17898.69 11297.21 3498.84 4199.36 2595.41 5199.78 9098.62 599.65 5599.80 8
MVS_111021_HR98.47 3598.34 2498.88 6899.22 8797.32 8097.91 22399.58 397.20 3598.33 7299.00 8095.99 3399.64 12098.05 3399.76 3099.69 45
GST-MVS98.43 3798.12 4399.34 2299.72 1298.38 3299.09 4498.82 6995.71 8998.73 5099.06 7395.27 5899.93 1497.07 7999.63 5899.72 38
EI-MVSNet-UG-set98.41 3898.34 2498.61 7999.45 4996.32 12498.28 18198.68 11597.17 3798.74 4899.37 2195.25 6099.79 8698.57 799.54 7799.73 35
DELS-MVS98.40 3998.20 4098.99 5999.00 10297.66 6897.75 23998.89 4697.71 798.33 7298.97 8294.97 6899.88 4298.42 1999.76 3099.42 101
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
TSAR-MVS + GP.98.38 4098.24 3798.81 7099.22 8797.25 8698.11 20598.29 19697.19 3698.99 3399.02 7596.22 1899.67 11698.52 1398.56 12899.51 83
HPM-MVS_fast98.38 4098.13 4299.12 5399.75 397.86 6399.44 498.82 6994.46 15198.94 3499.20 4895.16 6399.74 10197.58 6099.85 399.77 19
HPM-MVScopyleft98.36 4298.10 4499.13 5199.74 797.82 6599.53 198.80 8694.63 14498.61 5798.97 8295.13 6499.77 9597.65 5499.83 999.79 9
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
ETH3D-3000-0.198.35 4398.00 4999.38 1799.47 4498.68 1898.67 12698.84 6494.66 14299.11 2499.25 3995.46 4899.81 6596.80 9999.73 4199.63 67
APD-MVScopyleft98.35 4398.00 4999.42 1499.51 3798.72 1498.80 9898.82 6994.52 14899.23 1899.25 3995.54 4699.80 7496.52 10899.77 2499.74 32
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MVS_111021_LR98.34 4598.23 3898.67 7699.27 7796.90 9897.95 22099.58 397.14 3998.44 6699.01 7995.03 6799.62 12597.91 3699.75 3699.50 85
PHI-MVS98.34 4598.06 4599.18 4599.15 9498.12 5499.04 5099.09 2093.32 20298.83 4399.10 6496.54 1499.83 5497.70 5299.76 3099.59 74
testtj98.33 4797.95 5199.47 1099.49 4398.70 1798.83 8898.86 6095.48 9998.91 4099.17 5295.48 4799.93 1495.80 13199.53 7899.76 25
MP-MVScopyleft98.33 4798.01 4899.28 3399.75 398.18 4999.22 2598.79 8896.13 7497.92 9799.23 4194.54 7899.94 396.74 10299.78 2199.73 35
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
MP-MVS-pluss98.31 4997.92 5399.49 899.72 1298.88 1198.43 16098.78 9094.10 15997.69 10999.42 1195.25 6099.92 2098.09 3099.80 1599.67 55
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
abl_698.30 5098.03 4799.13 5199.56 3297.76 6799.13 3998.82 6996.14 7399.26 1699.37 2193.33 9699.93 1496.96 8499.67 5199.69 45
ACMMPcopyleft98.23 5197.95 5199.09 5599.74 797.62 7199.03 5399.41 695.98 7997.60 11899.36 2594.45 8399.93 1497.14 7698.85 11599.70 44
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
test_prior398.22 5297.90 5499.19 4199.31 6498.22 4697.80 23598.84 6496.12 7597.89 9998.69 11395.96 3499.70 10996.89 8999.60 6299.65 61
CANet98.05 5397.76 5798.90 6798.73 12197.27 8298.35 16898.78 9097.37 2497.72 10798.96 8791.53 13299.92 2098.79 299.65 5599.51 83
train_agg97.97 5497.52 6899.33 2699.31 6498.50 2697.92 22198.73 10292.98 21497.74 10598.68 11596.20 2199.80 7496.59 10599.57 6899.68 51
ETH3D cwj APD-0.1697.96 5597.52 6899.29 2999.05 9898.52 2498.33 17098.68 11593.18 20698.68 5299.13 5994.62 7599.83 5496.45 11099.55 7699.52 79
ETV-MVS97.96 5597.81 5598.40 9998.42 14497.27 8298.73 11198.55 14596.84 4998.38 6997.44 22595.39 5299.35 15397.62 5698.89 11198.58 179
UA-Net97.96 5597.62 6098.98 6198.86 11397.47 7698.89 7699.08 2196.67 5698.72 5199.54 193.15 9999.81 6594.87 15998.83 11699.65 61
agg_prior197.95 5897.51 7099.28 3399.30 6998.38 3297.81 23498.72 10493.16 20897.57 11998.66 11896.14 2499.81 6596.63 10499.56 7399.66 59
CDPH-MVS97.94 5997.49 7199.28 3399.47 4498.44 2897.91 22398.67 12392.57 23098.77 4698.85 9895.93 3699.72 10395.56 14199.69 4999.68 51
DeepPCF-MVS96.37 297.93 6098.48 1596.30 23699.00 10289.54 30197.43 25798.87 5598.16 299.26 1699.38 2096.12 2699.64 12098.30 2499.77 2499.72 38
DeepC-MVS95.98 397.88 6197.58 6398.77 7199.25 8096.93 9698.83 8898.75 9796.96 4796.89 14299.50 490.46 15399.87 4397.84 4399.76 3099.52 79
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DP-MVS Recon97.86 6297.46 7399.06 5799.53 3598.35 3998.33 17098.89 4692.62 22798.05 8098.94 9095.34 5699.65 11896.04 12299.42 8999.19 126
CSCG97.85 6397.74 5898.20 11199.67 2495.16 17499.22 2599.32 793.04 21197.02 13598.92 9395.36 5599.91 2997.43 6899.64 5799.52 79
CS-MVS97.81 6497.61 6198.41 9898.52 14197.15 9099.09 4498.55 14596.18 7197.61 11697.20 24094.59 7799.39 15097.62 5699.10 10498.70 167
MG-MVS97.81 6497.60 6298.44 9499.12 9695.97 13997.75 23998.78 9096.89 4898.46 6299.22 4393.90 9399.68 11594.81 16399.52 8099.67 55
VNet97.79 6697.40 7798.96 6398.88 11197.55 7398.63 13198.93 3796.74 5399.02 2998.84 10090.33 15699.83 5498.53 996.66 18099.50 85
EIA-MVS97.75 6797.58 6398.27 10598.38 14696.44 11899.01 5598.60 13395.88 8297.26 12497.53 21994.97 6899.33 15597.38 7199.20 10099.05 143
PS-MVSNAJ97.73 6897.77 5697.62 15198.68 12995.58 15797.34 26698.51 15497.29 2698.66 5497.88 18894.51 7999.90 3297.87 4099.17 10297.39 212
CPTT-MVS97.72 6997.32 8098.92 6599.64 2697.10 9199.12 4198.81 7592.34 23898.09 7899.08 7193.01 10099.92 2096.06 12199.77 2499.75 27
PVSNet_Blended_VisFu97.70 7097.46 7398.44 9499.27 7795.91 14898.63 13199.16 1794.48 15097.67 11098.88 9692.80 10299.91 2997.11 7799.12 10399.50 85
canonicalmvs97.67 7197.23 8398.98 6198.70 12698.38 3299.34 1198.39 17696.76 5297.67 11097.40 22892.26 11099.49 14098.28 2596.28 19699.08 141
xiu_mvs_v2_base97.66 7297.70 5997.56 15598.61 13595.46 16497.44 25598.46 16497.15 3898.65 5598.15 16894.33 8599.80 7497.84 4398.66 12497.41 210
baseline97.64 7397.44 7598.25 10898.35 14896.20 12899.00 5798.32 18696.33 6798.03 8399.17 5291.35 13599.16 16898.10 2998.29 14299.39 102
casdiffmvs97.63 7497.41 7698.28 10498.33 15396.14 13198.82 9198.32 18696.38 6597.95 9299.21 4491.23 13999.23 16298.12 2898.37 13799.48 90
xiu_mvs_v1_base_debu97.60 7597.56 6597.72 14198.35 14895.98 13497.86 23098.51 15497.13 4099.01 3098.40 14291.56 12899.80 7498.53 998.68 12097.37 214
xiu_mvs_v1_base97.60 7597.56 6597.72 14198.35 14895.98 13497.86 23098.51 15497.13 4099.01 3098.40 14291.56 12899.80 7498.53 998.68 12097.37 214
xiu_mvs_v1_base_debi97.60 7597.56 6597.72 14198.35 14895.98 13497.86 23098.51 15497.13 4099.01 3098.40 14291.56 12899.80 7498.53 998.68 12097.37 214
ETH3 D test640097.59 7897.01 9299.34 2299.40 5398.56 2298.20 18998.81 7591.63 26098.44 6698.85 9893.98 9299.82 6194.11 18699.69 4999.64 64
diffmvs97.58 7997.40 7798.13 11698.32 15595.81 15298.06 21098.37 17996.20 7098.74 4898.89 9591.31 13799.25 15998.16 2798.52 12999.34 105
MVSFormer97.57 8097.49 7197.84 13298.07 17395.76 15399.47 298.40 17494.98 12798.79 4498.83 10192.34 10798.41 25796.91 8699.59 6599.34 105
alignmvs97.56 8197.07 9099.01 5898.66 13098.37 3798.83 8898.06 23696.74 5398.00 9097.65 20890.80 14799.48 14498.37 2296.56 18499.19 126
DPM-MVS97.55 8296.99 9499.23 4099.04 10098.55 2397.17 27998.35 18294.85 13497.93 9698.58 12695.07 6699.71 10892.60 22799.34 9599.43 100
OMC-MVS97.55 8297.34 7998.20 11199.33 5995.92 14698.28 18198.59 13595.52 9897.97 9199.10 6493.28 9899.49 14095.09 15698.88 11299.19 126
PAPM_NR97.46 8497.11 8798.50 8999.50 3996.41 12098.63 13198.60 13395.18 11697.06 13398.06 17494.26 8799.57 12993.80 19598.87 11499.52 79
EPP-MVSNet97.46 8497.28 8197.99 12598.64 13295.38 16699.33 1398.31 18893.61 19297.19 12699.07 7294.05 8999.23 16296.89 8998.43 13699.37 104
3Dnovator94.51 597.46 8496.93 9699.07 5697.78 19097.64 6999.35 1099.06 2297.02 4593.75 23899.16 5789.25 17199.92 2097.22 7499.75 3699.64 64
CNLPA97.45 8797.03 9198.73 7299.05 9897.44 7898.07 20998.53 15095.32 11096.80 14798.53 13093.32 9799.72 10394.31 17999.31 9799.02 145
lupinMVS97.44 8897.22 8498.12 11898.07 17395.76 15397.68 24497.76 25394.50 14998.79 4498.61 12192.34 10799.30 15697.58 6099.59 6599.31 111
3Dnovator+94.38 697.43 8996.78 10399.38 1797.83 18898.52 2499.37 798.71 10897.09 4392.99 26399.13 5989.36 16899.89 3496.97 8299.57 6899.71 42
Vis-MVSNetpermissive97.42 9097.11 8798.34 10298.66 13096.23 12799.22 2599.00 2796.63 5898.04 8299.21 4488.05 20499.35 15396.01 12499.21 9999.45 98
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
API-MVS97.41 9197.25 8297.91 12998.70 12696.80 10198.82 9198.69 11294.53 14698.11 7798.28 15794.50 8299.57 12994.12 18599.49 8197.37 214
sss97.39 9296.98 9598.61 7998.60 13696.61 10998.22 18698.93 3793.97 16898.01 8898.48 13591.98 12099.85 4896.45 11098.15 14599.39 102
PVSNet_Blended97.38 9397.12 8698.14 11499.25 8095.35 16997.28 27199.26 893.13 20997.94 9498.21 16492.74 10399.81 6596.88 9299.40 9299.27 118
112197.37 9496.77 10799.16 4899.34 5697.99 6198.19 19398.68 11590.14 29498.01 8898.97 8294.80 7399.87 4393.36 20799.46 8699.61 69
WTY-MVS97.37 9496.92 9798.72 7398.86 11396.89 10098.31 17698.71 10895.26 11297.67 11098.56 12992.21 11399.78 9095.89 12696.85 17599.48 90
jason97.32 9697.08 8998.06 12297.45 21995.59 15697.87 22997.91 24894.79 13598.55 6098.83 10191.12 14099.23 16297.58 6099.60 6299.34 105
jason: jason.
MVS_Test97.28 9797.00 9398.13 11698.33 15395.97 13998.74 10798.07 23294.27 15598.44 6698.07 17392.48 10599.26 15896.43 11298.19 14499.16 131
EPNet97.28 9796.87 9998.51 8894.98 31796.14 13198.90 7297.02 29998.28 195.99 17699.11 6291.36 13499.89 3496.98 8199.19 10199.50 85
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
test_yl97.22 9996.78 10398.54 8598.73 12196.60 11098.45 15598.31 18894.70 13698.02 8498.42 14090.80 14799.70 10996.81 9796.79 17799.34 105
DCV-MVSNet97.22 9996.78 10398.54 8598.73 12196.60 11098.45 15598.31 18894.70 13698.02 8498.42 14090.80 14799.70 10996.81 9796.79 17799.34 105
IS-MVSNet97.22 9996.88 9898.25 10898.85 11596.36 12299.19 3197.97 24395.39 10497.23 12598.99 8191.11 14198.93 20194.60 16898.59 12699.47 92
PLCcopyleft95.07 497.20 10296.78 10398.44 9499.29 7296.31 12698.14 20098.76 9492.41 23696.39 16698.31 15594.92 7099.78 9094.06 18898.77 11999.23 121
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CHOSEN 280x42097.18 10397.18 8597.20 16798.81 11793.27 24795.78 32299.15 1895.25 11396.79 14898.11 17192.29 10999.07 18498.56 899.85 399.25 120
LS3D97.16 10496.66 11298.68 7598.53 14097.19 8898.93 7098.90 4492.83 22295.99 17699.37 2192.12 11699.87 4393.67 19999.57 6898.97 150
AdaColmapbinary97.15 10596.70 10898.48 9199.16 9296.69 10698.01 21598.89 4694.44 15296.83 14398.68 11590.69 15099.76 9794.36 17699.29 9898.98 149
Effi-MVS+97.12 10696.69 10998.39 10098.19 16496.72 10597.37 26298.43 17193.71 18297.65 11398.02 17692.20 11499.25 15996.87 9597.79 15699.19 126
CHOSEN 1792x268897.12 10696.80 10098.08 12099.30 6994.56 20698.05 21199.71 193.57 19397.09 12998.91 9488.17 19999.89 3496.87 9599.56 7399.81 7
F-COLMAP97.09 10896.80 10097.97 12699.45 4994.95 18798.55 14498.62 13293.02 21296.17 17198.58 12694.01 9099.81 6593.95 19098.90 11099.14 134
TAMVS97.02 10996.79 10297.70 14498.06 17595.31 17198.52 14698.31 18893.95 16997.05 13498.61 12193.49 9598.52 23995.33 14797.81 15599.29 116
CDS-MVSNet96.99 11096.69 10997.90 13098.05 17695.98 13498.20 18998.33 18593.67 18996.95 13698.49 13493.54 9498.42 25095.24 15497.74 15999.31 111
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
CANet_DTU96.96 11196.55 11598.21 11098.17 16896.07 13397.98 21898.21 20497.24 3397.13 12898.93 9186.88 22899.91 2995.00 15899.37 9498.66 173
114514_t96.93 11296.27 12498.92 6599.50 3997.63 7098.85 8498.90 4484.80 32797.77 10299.11 6292.84 10199.66 11794.85 16099.77 2499.47 92
MAR-MVS96.91 11396.40 12098.45 9398.69 12896.90 9898.66 12998.68 11592.40 23797.07 13297.96 18191.54 13199.75 9993.68 19798.92 10998.69 169
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
HyFIR lowres test96.90 11496.49 11898.14 11499.33 5995.56 15997.38 26099.65 292.34 23897.61 11698.20 16589.29 17099.10 18196.97 8297.60 16499.77 19
Vis-MVSNet (Re-imp)96.87 11596.55 11597.83 13398.73 12195.46 16499.20 2998.30 19494.96 12996.60 15498.87 9790.05 15998.59 23493.67 19998.60 12599.46 96
PAPR96.84 11696.24 12698.65 7798.72 12596.92 9797.36 26498.57 14193.33 20196.67 15097.57 21694.30 8699.56 13191.05 26398.59 12699.47 92
HY-MVS93.96 896.82 11796.23 12798.57 8198.46 14397.00 9398.14 20098.21 20493.95 16996.72 14997.99 18091.58 12799.76 9794.51 17396.54 18598.95 154
UGNet96.78 11896.30 12398.19 11398.24 15895.89 15098.88 7998.93 3797.39 2196.81 14697.84 19282.60 28599.90 3296.53 10799.49 8198.79 162
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
PVSNet_BlendedMVS96.73 11996.60 11397.12 17399.25 8095.35 16998.26 18499.26 894.28 15497.94 9497.46 22292.74 10399.81 6596.88 9293.32 24196.20 302
mvs_anonymous96.70 12096.53 11797.18 16998.19 16493.78 22798.31 17698.19 20794.01 16494.47 20098.27 16092.08 11898.46 24497.39 7097.91 15199.31 111
1112_ss96.63 12196.00 13398.50 8998.56 13796.37 12198.18 19798.10 22692.92 21794.84 18998.43 13892.14 11599.58 12894.35 17796.51 18699.56 78
mvs-test196.60 12296.68 11196.37 23197.89 18591.81 26798.56 14298.10 22696.57 6096.52 16197.94 18390.81 14599.45 14795.72 13498.01 14897.86 200
PMMVS96.60 12296.33 12297.41 16097.90 18493.93 22397.35 26598.41 17292.84 22197.76 10397.45 22491.10 14299.20 16596.26 11697.91 15199.11 137
DP-MVS96.59 12495.93 13498.57 8199.34 5696.19 13098.70 12098.39 17689.45 30394.52 19899.35 2791.85 12299.85 4892.89 22398.88 11299.68 51
PatchMatch-RL96.59 12496.03 13298.27 10599.31 6496.51 11597.91 22399.06 2293.72 18196.92 14098.06 17488.50 19499.65 11891.77 25199.00 10798.66 173
XVG-OURS96.55 12696.41 11996.99 17998.75 12093.76 22897.50 25498.52 15295.67 9196.83 14399.30 3488.95 18499.53 13795.88 12796.26 19797.69 206
FIs96.51 12796.12 12997.67 14797.13 24197.54 7499.36 899.22 1495.89 8194.03 22698.35 14891.98 12098.44 24796.40 11392.76 24797.01 222
XVG-OURS-SEG-HR96.51 12796.34 12197.02 17898.77 11993.76 22897.79 23798.50 15995.45 10196.94 13799.09 6987.87 20999.55 13696.76 10195.83 20697.74 203
PS-MVSNAJss96.43 12996.26 12596.92 18895.84 30095.08 17999.16 3498.50 15995.87 8393.84 23498.34 15294.51 7998.61 23196.88 9293.45 23897.06 220
FC-MVSNet-test96.42 13096.05 13097.53 15696.95 24997.27 8299.36 899.23 1295.83 8493.93 22898.37 14692.00 11998.32 26696.02 12392.72 24897.00 223
ab-mvs96.42 13095.71 14298.55 8398.63 13396.75 10497.88 22898.74 9893.84 17496.54 15998.18 16785.34 25399.75 9995.93 12596.35 19099.15 132
PVSNet91.96 1896.35 13296.15 12896.96 18399.17 9192.05 26496.08 31598.68 11593.69 18597.75 10497.80 19888.86 18599.69 11494.26 18199.01 10699.15 132
Test_1112_low_res96.34 13395.66 14698.36 10198.56 13795.94 14297.71 24198.07 23292.10 24794.79 19397.29 23391.75 12499.56 13194.17 18396.50 18799.58 76
Effi-MVS+-dtu96.29 13496.56 11495.51 26497.89 18590.22 29498.80 9898.10 22696.57 6096.45 16596.66 28290.81 14598.91 20395.72 13497.99 14997.40 211
QAPM96.29 13495.40 14998.96 6397.85 18797.60 7299.23 2198.93 3789.76 29893.11 26099.02 7589.11 17699.93 1491.99 24699.62 6099.34 105
Fast-Effi-MVS+96.28 13695.70 14398.03 12398.29 15795.97 13998.58 13798.25 20291.74 25595.29 18397.23 23791.03 14499.15 17192.90 22197.96 15098.97 150
nrg03096.28 13695.72 13997.96 12896.90 25498.15 5299.39 598.31 18895.47 10094.42 20698.35 14892.09 11798.69 22497.50 6789.05 29197.04 221
131496.25 13895.73 13897.79 13597.13 24195.55 16198.19 19398.59 13593.47 19692.03 28897.82 19691.33 13699.49 14094.62 16798.44 13498.32 190
HQP_MVS96.14 13995.90 13596.85 19097.42 22094.60 20498.80 9898.56 14397.28 2795.34 18098.28 15787.09 22399.03 18996.07 11994.27 21496.92 228
tttt051796.07 14095.51 14897.78 13698.41 14594.84 19099.28 1694.33 33694.26 15697.64 11498.64 12084.05 27499.47 14595.34 14697.60 16499.03 144
MVSTER96.06 14195.72 13997.08 17698.23 15995.93 14598.73 11198.27 19794.86 13395.07 18498.09 17288.21 19898.54 23796.59 10593.46 23696.79 246
thisisatest053096.01 14295.36 15497.97 12698.38 14695.52 16298.88 7994.19 33894.04 16197.64 11498.31 15583.82 28199.46 14695.29 15097.70 16198.93 155
test_djsdf96.00 14395.69 14496.93 18695.72 30295.49 16399.47 298.40 17494.98 12794.58 19697.86 18989.16 17498.41 25796.91 8694.12 22296.88 237
EI-MVSNet95.96 14495.83 13796.36 23297.93 18293.70 23498.12 20398.27 19793.70 18495.07 18499.02 7592.23 11298.54 23794.68 16493.46 23696.84 242
BH-untuned95.95 14595.72 13996.65 20198.55 13992.26 26098.23 18597.79 25293.73 18094.62 19598.01 17888.97 18399.00 19293.04 21798.51 13098.68 170
MSDG95.93 14695.30 16097.83 13398.90 10995.36 16796.83 30398.37 17991.32 27194.43 20598.73 11290.27 15799.60 12690.05 27798.82 11798.52 180
BH-RMVSNet95.92 14795.32 15897.69 14598.32 15594.64 19898.19 19397.45 27594.56 14596.03 17498.61 12185.02 25699.12 17490.68 26899.06 10599.30 114
Fast-Effi-MVS+-dtu95.87 14895.85 13695.91 25297.74 19491.74 27198.69 12298.15 21895.56 9694.92 18797.68 20788.98 18298.79 21993.19 21297.78 15797.20 218
LFMVS95.86 14994.98 17498.47 9298.87 11296.32 12498.84 8796.02 31893.40 19998.62 5699.20 4874.99 32599.63 12397.72 4997.20 17099.46 96
baseline195.84 15095.12 16798.01 12498.49 14295.98 13498.73 11197.03 29795.37 10796.22 16998.19 16689.96 16199.16 16894.60 16887.48 30898.90 157
OpenMVScopyleft93.04 1395.83 15195.00 17298.32 10397.18 23897.32 8099.21 2898.97 3089.96 29691.14 29699.05 7486.64 23199.92 2093.38 20599.47 8397.73 204
VDD-MVS95.82 15295.23 16297.61 15298.84 11693.98 22298.68 12397.40 27995.02 12697.95 9299.34 2874.37 32999.78 9098.64 396.80 17699.08 141
UniMVSNet (Re)95.78 15395.19 16497.58 15396.99 24897.47 7698.79 10299.18 1695.60 9493.92 22997.04 25791.68 12598.48 24195.80 13187.66 30796.79 246
VPA-MVSNet95.75 15495.11 16897.69 14597.24 23097.27 8298.94 6999.23 1295.13 11895.51 17997.32 23185.73 24698.91 20397.33 7389.55 28496.89 236
HQP-MVS95.72 15595.40 14996.69 19997.20 23494.25 21798.05 21198.46 16496.43 6294.45 20197.73 20186.75 22998.96 19695.30 14894.18 21896.86 241
UniMVSNet_NR-MVSNet95.71 15695.15 16597.40 16296.84 25796.97 9498.74 10799.24 1095.16 11793.88 23197.72 20391.68 12598.31 26895.81 12987.25 31296.92 228
PatchmatchNetpermissive95.71 15695.52 14796.29 23797.58 20490.72 28796.84 30297.52 26894.06 16097.08 13096.96 26689.24 17298.90 20692.03 24598.37 13799.26 119
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
OPM-MVS95.69 15895.33 15796.76 19496.16 28994.63 19998.43 16098.39 17696.64 5795.02 18698.78 10685.15 25599.05 18595.21 15594.20 21796.60 269
ACMM93.85 995.69 15895.38 15396.61 20697.61 20193.84 22698.91 7198.44 16895.25 11394.28 21298.47 13686.04 24499.12 17495.50 14393.95 22796.87 239
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
tpmrst95.63 16095.69 14495.44 26897.54 20988.54 31596.97 28897.56 26293.50 19597.52 12196.93 27089.49 16499.16 16895.25 15396.42 18998.64 175
LPG-MVS_test95.62 16195.34 15596.47 22397.46 21593.54 23798.99 5998.54 14894.67 14094.36 20898.77 10885.39 25099.11 17895.71 13694.15 22096.76 249
CLD-MVS95.62 16195.34 15596.46 22697.52 21293.75 23097.27 27298.46 16495.53 9794.42 20698.00 17986.21 23998.97 19396.25 11794.37 21296.66 264
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
thisisatest051595.61 16394.89 17897.76 13898.15 16995.15 17696.77 30494.41 33492.95 21697.18 12797.43 22684.78 26199.45 14794.63 16597.73 16098.68 170
thres600view795.49 16494.77 18197.67 14798.98 10595.02 18098.85 8496.90 30595.38 10596.63 15296.90 27184.29 26799.59 12788.65 29796.33 19198.40 185
PatchFormer-LS_test95.47 16595.27 16196.08 24597.59 20390.66 28898.10 20797.34 28193.98 16796.08 17296.15 30287.65 21599.12 17495.27 15295.24 21098.44 184
SCA95.46 16695.13 16696.46 22697.67 19791.29 27897.33 26797.60 26094.68 13996.92 14097.10 24483.97 27698.89 20792.59 22998.32 14199.20 123
IterMVS-LS95.46 16695.21 16396.22 23998.12 17093.72 23398.32 17598.13 22193.71 18294.26 21397.31 23292.24 11198.10 28494.63 16590.12 27596.84 242
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
jajsoiax95.45 16895.03 17196.73 19595.42 31394.63 19999.14 3698.52 15295.74 8793.22 25498.36 14783.87 27998.65 22996.95 8594.04 22396.91 233
CVMVSNet95.43 16996.04 13193.57 30597.93 18283.62 33198.12 20398.59 13595.68 9096.56 15599.02 7587.51 21697.51 31693.56 20397.44 16699.60 72
anonymousdsp95.42 17094.91 17796.94 18595.10 31695.90 14999.14 3698.41 17293.75 17793.16 25697.46 22287.50 21898.41 25795.63 14094.03 22496.50 288
DU-MVS95.42 17094.76 18297.40 16296.53 27296.97 9498.66 12998.99 2995.43 10293.88 23197.69 20488.57 19098.31 26895.81 12987.25 31296.92 228
mvs_tets95.41 17295.00 17296.65 20195.58 30694.42 20999.00 5798.55 14595.73 8893.21 25598.38 14583.45 28398.63 23097.09 7894.00 22596.91 233
thres100view90095.38 17394.70 18597.41 16098.98 10594.92 18898.87 8196.90 30595.38 10596.61 15396.88 27284.29 26799.56 13188.11 29896.29 19397.76 201
thres40095.38 17394.62 18897.65 15098.94 10794.98 18498.68 12396.93 30395.33 10896.55 15796.53 28884.23 27099.56 13188.11 29896.29 19398.40 185
BH-w/o95.38 17395.08 16996.26 23898.34 15291.79 26897.70 24297.43 27792.87 22094.24 21597.22 23888.66 18898.84 21391.55 25597.70 16198.16 193
VDDNet95.36 17694.53 19297.86 13198.10 17295.13 17798.85 8497.75 25490.46 28798.36 7099.39 1373.27 33199.64 12097.98 3496.58 18398.81 161
TAPA-MVS93.98 795.35 17794.56 19197.74 14099.13 9594.83 19298.33 17098.64 13186.62 31696.29 16898.61 12194.00 9199.29 15780.00 32999.41 9099.09 138
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP93.49 1095.34 17894.98 17496.43 22897.67 19793.48 23998.73 11198.44 16894.94 13292.53 27698.53 13084.50 26699.14 17295.48 14494.00 22596.66 264
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
COLMAP_ROBcopyleft93.27 1295.33 17994.87 17996.71 19699.29 7293.24 24998.58 13798.11 22489.92 29793.57 24299.10 6486.37 23799.79 8690.78 26698.10 14797.09 219
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
tfpn200view995.32 18094.62 18897.43 15998.94 10794.98 18498.68 12396.93 30395.33 10896.55 15796.53 28884.23 27099.56 13188.11 29896.29 19397.76 201
Anonymous20240521195.28 18194.49 19497.67 14799.00 10293.75 23098.70 12097.04 29690.66 28496.49 16298.80 10478.13 31099.83 5496.21 11895.36 20999.44 99
thres20095.25 18294.57 19097.28 16598.81 11794.92 18898.20 18997.11 29295.24 11596.54 15996.22 30084.58 26499.53 13787.93 30296.50 18797.39 212
AllTest95.24 18394.65 18796.99 17999.25 8093.21 25098.59 13598.18 21091.36 26793.52 24498.77 10884.67 26299.72 10389.70 28497.87 15398.02 196
LCM-MVSNet-Re95.22 18495.32 15894.91 28298.18 16687.85 32298.75 10495.66 32495.11 12188.96 31196.85 27590.26 15897.65 31095.65 13998.44 13499.22 122
EPNet_dtu95.21 18594.95 17695.99 24796.17 28790.45 29298.16 19997.27 28796.77 5193.14 25998.33 15390.34 15598.42 25085.57 31598.81 11899.09 138
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
XXY-MVS95.20 18694.45 19997.46 15796.75 26296.56 11398.86 8398.65 13093.30 20493.27 25398.27 16084.85 26098.87 21094.82 16291.26 26496.96 225
D2MVS95.18 18795.08 16995.48 26597.10 24392.07 26398.30 17899.13 1994.02 16392.90 26496.73 27989.48 16598.73 22394.48 17493.60 23595.65 314
WR-MVS95.15 18894.46 19797.22 16696.67 26796.45 11798.21 18798.81 7594.15 15793.16 25697.69 20487.51 21698.30 27095.29 15088.62 29796.90 235
TranMVSNet+NR-MVSNet95.14 18994.48 19597.11 17496.45 27796.36 12299.03 5399.03 2595.04 12593.58 24197.93 18488.27 19798.03 29294.13 18486.90 31796.95 227
baseline295.11 19094.52 19396.87 18996.65 26893.56 23698.27 18394.10 34093.45 19792.02 28997.43 22687.45 22099.19 16693.88 19297.41 16897.87 199
miper_enhance_ethall95.10 19194.75 18396.12 24497.53 21193.73 23296.61 31098.08 23092.20 24693.89 23096.65 28492.44 10698.30 27094.21 18291.16 26596.34 296
Anonymous2024052995.10 19194.22 20897.75 13999.01 10194.26 21698.87 8198.83 6885.79 32496.64 15198.97 8278.73 30799.85 4896.27 11594.89 21199.12 136
test-LLR95.10 19194.87 17995.80 25796.77 25989.70 29896.91 29395.21 32695.11 12194.83 19195.72 31287.71 21198.97 19393.06 21598.50 13198.72 165
WR-MVS_H95.05 19494.46 19796.81 19296.86 25695.82 15199.24 2099.24 1093.87 17392.53 27696.84 27690.37 15498.24 27693.24 21087.93 30496.38 295
miper_ehance_all_eth95.01 19594.69 18695.97 24997.70 19693.31 24697.02 28698.07 23292.23 24393.51 24696.96 26691.85 12298.15 28093.68 19791.16 26596.44 293
ADS-MVSNet95.00 19694.45 19996.63 20498.00 17791.91 26696.04 31697.74 25590.15 29296.47 16396.64 28587.89 20798.96 19690.08 27597.06 17199.02 145
VPNet94.99 19794.19 21097.40 16297.16 23996.57 11298.71 11698.97 3095.67 9194.84 18998.24 16380.36 30098.67 22896.46 10987.32 31196.96 225
EPMVS94.99 19794.48 19596.52 21997.22 23291.75 27097.23 27391.66 34494.11 15897.28 12396.81 27785.70 24798.84 21393.04 21797.28 16998.97 150
NR-MVSNet94.98 19994.16 21297.44 15896.53 27297.22 8798.74 10798.95 3494.96 12989.25 31097.69 20489.32 16998.18 27894.59 17087.40 31096.92 228
FMVSNet394.97 20094.26 20797.11 17498.18 16696.62 10798.56 14298.26 20193.67 18994.09 22297.10 24484.25 26998.01 29392.08 24192.14 25196.70 258
CostFormer94.95 20194.73 18495.60 26397.28 22889.06 30897.53 25396.89 30789.66 30096.82 14596.72 28086.05 24298.95 20095.53 14296.13 20298.79 162
PAPM94.95 20194.00 22297.78 13697.04 24595.65 15596.03 31898.25 20291.23 27694.19 21897.80 19891.27 13898.86 21282.61 32497.61 16398.84 160
CP-MVSNet94.94 20394.30 20696.83 19196.72 26495.56 15999.11 4298.95 3493.89 17192.42 28197.90 18687.19 22298.12 28394.32 17888.21 30196.82 245
TR-MVS94.94 20394.20 20997.17 17097.75 19194.14 21997.59 25097.02 29992.28 24295.75 17897.64 21083.88 27898.96 19689.77 28196.15 20198.40 185
RPSCF94.87 20595.40 14993.26 30998.89 11082.06 33798.33 17098.06 23690.30 29196.56 15599.26 3887.09 22399.49 14093.82 19496.32 19298.24 191
DWT-MVSNet_test94.82 20694.36 20496.20 24097.35 22590.79 28598.34 16996.57 31792.91 21895.33 18296.44 29282.00 28799.12 17494.52 17295.78 20798.70 167
GA-MVS94.81 20794.03 21897.14 17197.15 24093.86 22596.76 30597.58 26194.00 16594.76 19497.04 25780.91 29498.48 24191.79 25096.25 19899.09 138
cl_fuxian94.79 20894.43 20195.89 25497.75 19193.12 25397.16 28098.03 24092.23 24393.46 24997.05 25691.39 13398.01 29393.58 20289.21 28996.53 280
V4294.78 20994.14 21496.70 19896.33 28295.22 17398.97 6398.09 22992.32 24094.31 21197.06 25488.39 19598.55 23692.90 22188.87 29596.34 296
CR-MVSNet94.76 21094.15 21396.59 20997.00 24693.43 24094.96 32697.56 26292.46 23196.93 13896.24 29688.15 20097.88 30587.38 30496.65 18198.46 182
DI_MVS_plusplus_test94.74 21193.62 24798.09 11995.34 31495.92 14698.09 20897.34 28194.66 14285.89 32395.91 30780.49 29999.38 15296.66 10398.22 14398.97 150
v2v48294.69 21294.03 21896.65 20196.17 28794.79 19598.67 12698.08 23092.72 22394.00 22797.16 24287.69 21498.45 24592.91 22088.87 29596.72 254
pmmvs494.69 21293.99 22496.81 19295.74 30195.94 14297.40 25897.67 25790.42 28993.37 25097.59 21489.08 17798.20 27792.97 21991.67 25896.30 300
cl-mvsnet294.68 21494.19 21096.13 24398.11 17193.60 23596.94 29098.31 18892.43 23593.32 25296.87 27486.51 23298.28 27494.10 18791.16 26596.51 286
eth_miper_zixun_eth94.68 21494.41 20295.47 26697.64 19991.71 27296.73 30798.07 23292.71 22493.64 23997.21 23990.54 15298.17 27993.38 20589.76 27996.54 278
PCF-MVS93.45 1194.68 21493.43 25598.42 9798.62 13496.77 10395.48 32498.20 20684.63 32893.34 25198.32 15488.55 19299.81 6584.80 32098.96 10898.68 170
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MVS94.67 21793.54 25198.08 12096.88 25596.56 11398.19 19398.50 15978.05 33692.69 27198.02 17691.07 14399.63 12390.09 27498.36 13998.04 195
PS-CasMVS94.67 21793.99 22496.71 19696.68 26695.26 17299.13 3999.03 2593.68 18792.33 28297.95 18285.35 25298.10 28493.59 20188.16 30396.79 246
cascas94.63 21993.86 23296.93 18696.91 25394.27 21596.00 31998.51 15485.55 32594.54 19796.23 29884.20 27298.87 21095.80 13196.98 17497.66 207
tpmvs94.60 22094.36 20495.33 27197.46 21588.60 31496.88 29997.68 25691.29 27393.80 23696.42 29388.58 18999.24 16191.06 26196.04 20498.17 192
LTVRE_ROB92.95 1594.60 22093.90 22996.68 20097.41 22394.42 20998.52 14698.59 13591.69 25891.21 29598.35 14884.87 25999.04 18891.06 26193.44 23996.60 269
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
v114494.59 22293.92 22796.60 20896.21 28494.78 19698.59 13598.14 22091.86 25494.21 21797.02 25987.97 20598.41 25791.72 25289.57 28296.61 268
ADS-MVSNet294.58 22394.40 20395.11 27798.00 17788.74 31296.04 31697.30 28490.15 29296.47 16396.64 28587.89 20797.56 31490.08 27597.06 17199.02 145
ACMH92.88 1694.55 22493.95 22696.34 23497.63 20093.26 24898.81 9798.49 16393.43 19889.74 30698.53 13081.91 28899.08 18393.69 19693.30 24296.70 258
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
XVG-ACMP-BASELINE94.54 22594.14 21495.75 26096.55 27191.65 27398.11 20598.44 16894.96 12994.22 21697.90 18679.18 30699.11 17894.05 18993.85 22996.48 290
cl-mvsnet194.52 22694.03 21895.99 24797.57 20893.38 24497.05 28497.94 24691.74 25592.81 26697.10 24489.12 17598.07 28892.60 22790.30 27396.53 280
cl-mvsnet_94.51 22794.01 22196.02 24697.58 20493.40 24397.05 28497.96 24591.73 25792.76 26897.08 25089.06 17898.13 28292.61 22690.29 27496.52 283
GBi-Net94.49 22893.80 23596.56 21498.21 16195.00 18198.82 9198.18 21092.46 23194.09 22297.07 25181.16 29197.95 29792.08 24192.14 25196.72 254
test194.49 22893.80 23596.56 21498.21 16195.00 18198.82 9198.18 21092.46 23194.09 22297.07 25181.16 29197.95 29792.08 24192.14 25196.72 254
v894.47 23093.77 23896.57 21396.36 28094.83 19299.05 4998.19 20791.92 25193.16 25696.97 26488.82 18798.48 24191.69 25387.79 30596.39 294
FMVSNet294.47 23093.61 24897.04 17798.21 16196.43 11998.79 10298.27 19792.46 23193.50 24797.09 24881.16 29198.00 29591.09 25991.93 25596.70 258
Patchmatch-test94.42 23293.68 24596.63 20497.60 20291.76 26994.83 33097.49 27289.45 30394.14 22097.10 24488.99 17998.83 21585.37 31898.13 14699.29 116
PEN-MVS94.42 23293.73 24296.49 22196.28 28394.84 19099.17 3399.00 2793.51 19492.23 28497.83 19586.10 24197.90 30192.55 23286.92 31696.74 251
v14419294.39 23493.70 24396.48 22296.06 29294.35 21398.58 13798.16 21791.45 26494.33 21097.02 25987.50 21898.45 24591.08 26089.11 29096.63 266
Baseline_NR-MVSNet94.35 23593.81 23495.96 25096.20 28594.05 22198.61 13496.67 31591.44 26593.85 23397.60 21388.57 19098.14 28194.39 17586.93 31595.68 313
miper_lstm_enhance94.33 23694.07 21795.11 27797.75 19190.97 28297.22 27498.03 24091.67 25992.76 26896.97 26490.03 16097.78 30892.51 23489.64 28196.56 275
v119294.32 23793.58 24996.53 21896.10 29094.45 20898.50 15198.17 21591.54 26294.19 21897.06 25486.95 22798.43 24990.14 27389.57 28296.70 258
ACMH+92.99 1494.30 23893.77 23895.88 25597.81 18992.04 26598.71 11698.37 17993.99 16690.60 30298.47 13680.86 29699.05 18592.75 22592.40 25096.55 277
v14894.29 23993.76 24095.91 25296.10 29092.93 25598.58 13797.97 24392.59 22993.47 24896.95 26888.53 19398.32 26692.56 23187.06 31496.49 289
v1094.29 23993.55 25096.51 22096.39 27994.80 19498.99 5998.19 20791.35 26993.02 26296.99 26288.09 20298.41 25790.50 27088.41 29996.33 298
MVP-Stereo94.28 24193.92 22795.35 27094.95 31892.60 25897.97 21997.65 25891.61 26190.68 30197.09 24886.32 23898.42 25089.70 28499.34 9595.02 322
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
UniMVSNet_ETH3D94.24 24293.33 25796.97 18297.19 23793.38 24498.74 10798.57 14191.21 27893.81 23598.58 12672.85 33298.77 22195.05 15793.93 22898.77 164
OurMVSNet-221017-094.21 24394.00 22294.85 28595.60 30589.22 30698.89 7697.43 27795.29 11192.18 28598.52 13382.86 28498.59 23493.46 20491.76 25796.74 251
v192192094.20 24493.47 25496.40 23095.98 29594.08 22098.52 14698.15 21891.33 27094.25 21497.20 24086.41 23698.42 25090.04 27889.39 28796.69 263
v7n94.19 24593.43 25596.47 22395.90 29794.38 21299.26 1898.34 18491.99 24992.76 26897.13 24388.31 19698.52 23989.48 28987.70 30696.52 283
tpm294.19 24593.76 24095.46 26797.23 23189.04 30997.31 26996.85 31087.08 31596.21 17096.79 27883.75 28298.74 22292.43 23796.23 19998.59 177
TESTMET0.1,194.18 24793.69 24495.63 26296.92 25189.12 30796.91 29394.78 33193.17 20794.88 18896.45 29178.52 30898.92 20293.09 21498.50 13198.85 158
dp94.15 24893.90 22994.90 28397.31 22786.82 32796.97 28897.19 29191.22 27796.02 17596.61 28785.51 24999.02 19190.00 27994.30 21398.85 158
ET-MVSNet_ETH3D94.13 24992.98 26397.58 15398.22 16096.20 12897.31 26995.37 32594.53 14679.56 33397.63 21286.51 23297.53 31596.91 8690.74 26999.02 145
tpm94.13 24993.80 23595.12 27696.50 27487.91 32197.44 25595.89 32392.62 22796.37 16796.30 29584.13 27398.30 27093.24 21091.66 25999.14 134
IterMVS-SCA-FT94.11 25193.87 23194.85 28597.98 18190.56 29197.18 27798.11 22493.75 17792.58 27497.48 22183.97 27697.41 31792.48 23691.30 26296.58 271
Anonymous2023121194.10 25293.26 26096.61 20699.11 9794.28 21499.01 5598.88 4986.43 31892.81 26697.57 21681.66 29098.68 22794.83 16189.02 29396.88 237
IterMVS94.09 25393.85 23394.80 28897.99 17990.35 29397.18 27798.12 22293.68 18792.46 28097.34 22984.05 27497.41 31792.51 23491.33 26196.62 267
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test-mter94.08 25493.51 25295.80 25796.77 25989.70 29896.91 29395.21 32692.89 21994.83 19195.72 31277.69 31398.97 19393.06 21598.50 13198.72 165
test0.0.03 194.08 25493.51 25295.80 25795.53 30892.89 25697.38 26095.97 32095.11 12192.51 27896.66 28287.71 21196.94 32387.03 30693.67 23197.57 208
v124094.06 25693.29 25996.34 23496.03 29493.90 22498.44 15898.17 21591.18 27994.13 22197.01 26186.05 24298.42 25089.13 29489.50 28596.70 258
X-MVStestdata94.06 25692.30 27599.34 2299.70 2198.35 3999.29 1498.88 4997.40 1998.46 6243.50 34695.90 3899.89 3497.85 4199.74 3999.78 12
DTE-MVSNet93.98 25893.26 26096.14 24296.06 29294.39 21199.20 2998.86 6093.06 21091.78 29097.81 19785.87 24597.58 31390.53 26986.17 32196.46 292
pm-mvs193.94 25993.06 26296.59 20996.49 27595.16 17498.95 6798.03 24092.32 24091.08 29797.84 19284.54 26598.41 25792.16 23986.13 32396.19 303
MS-PatchMatch93.84 26093.63 24694.46 29796.18 28689.45 30297.76 23898.27 19792.23 24392.13 28697.49 22079.50 30398.69 22489.75 28299.38 9395.25 317
tfpnnormal93.66 26192.70 26996.55 21796.94 25095.94 14298.97 6399.19 1591.04 28191.38 29497.34 22984.94 25898.61 23185.45 31789.02 29395.11 319
EU-MVSNet93.66 26194.14 21492.25 31495.96 29683.38 33298.52 14698.12 22294.69 13892.61 27398.13 17087.36 22196.39 33291.82 24990.00 27796.98 224
our_test_393.65 26393.30 25894.69 29095.45 31189.68 30096.91 29397.65 25891.97 25091.66 29296.88 27289.67 16397.93 30088.02 30191.49 26096.48 290
pmmvs593.65 26392.97 26495.68 26195.49 30992.37 25998.20 18997.28 28689.66 30092.58 27497.26 23482.14 28698.09 28693.18 21390.95 26896.58 271
tpm cat193.36 26592.80 26695.07 27997.58 20487.97 32096.76 30597.86 25082.17 33293.53 24396.04 30586.13 24099.13 17389.24 29295.87 20598.10 194
JIA-IIPM93.35 26692.49 27295.92 25196.48 27690.65 28995.01 32596.96 30185.93 32296.08 17287.33 33687.70 21398.78 22091.35 25895.58 20898.34 188
SixPastTwentyTwo93.34 26792.86 26594.75 28995.67 30389.41 30498.75 10496.67 31593.89 17190.15 30498.25 16280.87 29598.27 27590.90 26490.64 27096.57 273
USDC93.33 26892.71 26895.21 27396.83 25890.83 28496.91 29397.50 27093.84 17490.72 30098.14 16977.69 31398.82 21689.51 28893.21 24495.97 308
IB-MVS91.98 1793.27 26991.97 27997.19 16897.47 21493.41 24297.09 28395.99 31993.32 20292.47 27995.73 31078.06 31199.53 13794.59 17082.98 32698.62 176
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
MIMVSNet93.26 27092.21 27696.41 22997.73 19593.13 25295.65 32397.03 29791.27 27594.04 22596.06 30475.33 32397.19 32086.56 30896.23 19998.92 156
ppachtmachnet_test93.22 27192.63 27094.97 28195.45 31190.84 28396.88 29997.88 24990.60 28592.08 28797.26 23488.08 20397.86 30785.12 31990.33 27296.22 301
Patchmtry93.22 27192.35 27495.84 25696.77 25993.09 25494.66 33197.56 26287.37 31492.90 26496.24 29688.15 20097.90 30187.37 30590.10 27696.53 280
FMVSNet193.19 27392.07 27796.56 21497.54 20995.00 18198.82 9198.18 21090.38 29092.27 28397.07 25173.68 33097.95 29789.36 29191.30 26296.72 254
LF4IMVS93.14 27492.79 26794.20 30095.88 29888.67 31397.66 24697.07 29493.81 17691.71 29197.65 20877.96 31298.81 21791.47 25691.92 25695.12 318
testgi93.06 27592.45 27394.88 28496.43 27889.90 29598.75 10497.54 26795.60 9491.63 29397.91 18574.46 32897.02 32286.10 31193.67 23197.72 205
PatchT93.06 27591.97 27996.35 23396.69 26592.67 25794.48 33297.08 29386.62 31697.08 13092.23 33187.94 20697.90 30178.89 33396.69 17998.49 181
MVS_030492.81 27792.01 27895.23 27297.46 21591.33 27698.17 19898.81 7591.13 28093.80 23695.68 31566.08 33898.06 28990.79 26596.13 20296.32 299
TransMVSNet (Re)92.67 27891.51 28396.15 24196.58 27094.65 19798.90 7296.73 31190.86 28389.46 30997.86 18985.62 24898.09 28686.45 30981.12 33195.71 312
K. test v392.55 27991.91 28194.48 29595.64 30489.24 30599.07 4794.88 33094.04 16186.78 31997.59 21477.64 31697.64 31192.08 24189.43 28696.57 273
DSMNet-mixed92.52 28092.58 27192.33 31394.15 32582.65 33598.30 17894.26 33789.08 30792.65 27295.73 31085.01 25795.76 33386.24 31097.76 15898.59 177
RPMNet92.52 28091.17 28496.59 20997.00 24693.43 24094.96 32697.26 28882.27 33196.93 13892.12 33286.98 22697.88 30576.32 33796.65 18198.46 182
TinyColmap92.31 28291.53 28294.65 29296.92 25189.75 29796.92 29196.68 31490.45 28889.62 30797.85 19176.06 32198.81 21786.74 30792.51 24995.41 316
gg-mvs-nofinetune92.21 28390.58 28997.13 17296.75 26295.09 17895.85 32089.40 34785.43 32694.50 19981.98 33980.80 29798.40 26392.16 23998.33 14097.88 198
FMVSNet591.81 28490.92 28694.49 29497.21 23392.09 26298.00 21797.55 26689.31 30590.86 29995.61 31674.48 32795.32 33585.57 31589.70 28096.07 306
pmmvs691.77 28590.63 28895.17 27594.69 32391.24 27998.67 12697.92 24786.14 32089.62 30797.56 21875.79 32298.34 26490.75 26784.56 32595.94 309
Anonymous2023120691.66 28691.10 28593.33 30794.02 32787.35 32498.58 13797.26 28890.48 28690.16 30396.31 29483.83 28096.53 33079.36 33189.90 27896.12 304
Patchmatch-RL test91.49 28790.85 28793.41 30691.37 33384.40 32992.81 33695.93 32291.87 25387.25 31794.87 32088.99 17996.53 33092.54 23382.00 32899.30 114
test_040291.32 28890.27 29194.48 29596.60 26991.12 28098.50 15197.22 29086.10 32188.30 31496.98 26377.65 31597.99 29678.13 33592.94 24694.34 325
PVSNet_088.72 1991.28 28990.03 29395.00 28097.99 17987.29 32594.84 32998.50 15992.06 24889.86 30595.19 31779.81 30299.39 15092.27 23869.79 33998.33 189
EG-PatchMatch MVS91.13 29090.12 29294.17 30294.73 32289.00 31098.13 20297.81 25189.22 30685.32 32796.46 29067.71 33598.42 25087.89 30393.82 23095.08 320
TDRefinement91.06 29189.68 29595.21 27385.35 34191.49 27498.51 15097.07 29491.47 26388.83 31297.84 19277.31 31799.09 18292.79 22477.98 33495.04 321
UnsupCasMVSNet_eth90.99 29289.92 29494.19 30194.08 32689.83 29697.13 28298.67 12393.69 18585.83 32596.19 30175.15 32496.74 32489.14 29379.41 33396.00 307
test20.0390.89 29390.38 29092.43 31293.48 32888.14 31998.33 17097.56 26293.40 19987.96 31596.71 28180.69 29894.13 33979.15 33286.17 32195.01 323
MDA-MVSNet_test_wron90.71 29489.38 29894.68 29194.83 32090.78 28697.19 27697.46 27387.60 31272.41 33995.72 31286.51 23296.71 32785.92 31386.80 31896.56 275
YYNet190.70 29589.39 29794.62 29394.79 32190.65 28997.20 27597.46 27387.54 31372.54 33895.74 30986.51 23296.66 32886.00 31286.76 31996.54 278
testing_290.61 29688.50 30196.95 18490.08 33795.57 15897.69 24398.06 23693.02 21276.55 33492.48 33061.18 34198.44 24795.45 14591.98 25496.84 242
pmmvs-eth3d90.36 29789.05 29994.32 29991.10 33492.12 26197.63 24996.95 30288.86 30884.91 32893.13 32678.32 30996.74 32488.70 29681.81 33094.09 329
new_pmnet90.06 29889.00 30093.22 31094.18 32488.32 31896.42 31496.89 30786.19 31985.67 32693.62 32477.18 31897.10 32181.61 32689.29 28894.23 326
MDA-MVSNet-bldmvs89.97 29988.35 30394.83 28795.21 31591.34 27597.64 24797.51 26988.36 31071.17 34096.13 30379.22 30596.63 32983.65 32186.27 32096.52 283
CMPMVSbinary66.06 2189.70 30089.67 29689.78 31993.19 32976.56 33997.00 28798.35 18280.97 33381.57 33297.75 20074.75 32698.61 23189.85 28093.63 23394.17 327
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MIMVSNet189.67 30188.28 30493.82 30392.81 33191.08 28198.01 21597.45 27587.95 31187.90 31695.87 30867.63 33694.56 33878.73 33488.18 30295.83 311
MVS-HIRNet89.46 30288.40 30292.64 31197.58 20482.15 33694.16 33593.05 34375.73 33890.90 29882.52 33879.42 30498.33 26583.53 32298.68 12097.43 209
OpenMVS_ROBcopyleft86.42 2089.00 30387.43 30793.69 30493.08 33089.42 30397.91 22396.89 30778.58 33585.86 32494.69 32169.48 33498.29 27377.13 33693.29 24393.36 334
new-patchmatchnet88.50 30487.45 30691.67 31790.31 33685.89 32897.16 28097.33 28389.47 30283.63 33092.77 32776.38 31995.06 33782.70 32377.29 33594.06 330
PM-MVS87.77 30586.55 30891.40 31891.03 33583.36 33396.92 29195.18 32891.28 27486.48 32293.42 32553.27 34296.74 32489.43 29081.97 32994.11 328
UnsupCasMVSNet_bld87.17 30685.12 30993.31 30891.94 33288.77 31194.92 32898.30 19484.30 32982.30 33190.04 33363.96 34097.25 31985.85 31474.47 33893.93 332
N_pmnet87.12 30787.77 30585.17 32495.46 31061.92 34697.37 26270.66 35385.83 32388.73 31396.04 30585.33 25497.76 30980.02 32890.48 27195.84 310
pmmvs386.67 30884.86 31092.11 31688.16 33887.19 32696.63 30994.75 33279.88 33487.22 31892.75 32866.56 33795.20 33681.24 32776.56 33693.96 331
test_normal83.22 30980.23 31192.18 31588.06 33982.87 33469.03 34598.05 23992.70 22563.67 34280.19 34150.72 34398.05 29091.41 25788.24 30095.62 315
LCM-MVSNet78.70 31076.24 31486.08 32277.26 34771.99 34394.34 33396.72 31261.62 34276.53 33589.33 33433.91 35092.78 34181.85 32574.60 33793.46 333
Gipumacopyleft78.40 31176.75 31383.38 32595.54 30780.43 33879.42 34497.40 27964.67 34173.46 33780.82 34045.65 34593.14 34066.32 34087.43 30976.56 342
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMMVS277.95 31275.44 31585.46 32382.54 34274.95 34194.23 33493.08 34272.80 33974.68 33687.38 33536.36 34991.56 34273.95 33863.94 34089.87 336
FPMVS77.62 31377.14 31279.05 32779.25 34560.97 34795.79 32195.94 32165.96 34067.93 34194.40 32237.73 34888.88 34468.83 33988.46 29887.29 337
ANet_high69.08 31465.37 31780.22 32665.99 34971.96 34490.91 34090.09 34682.62 33049.93 34778.39 34229.36 35181.75 34562.49 34138.52 34486.95 339
tmp_tt68.90 31566.97 31674.68 32950.78 35159.95 34887.13 34183.47 35138.80 34762.21 34396.23 29864.70 33976.91 34988.91 29530.49 34587.19 338
PMVScopyleft61.03 2365.95 31663.57 31973.09 33057.90 35051.22 35185.05 34393.93 34154.45 34344.32 34883.57 33713.22 35289.15 34358.68 34281.00 33278.91 341
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
E-PMN64.94 31764.25 31867.02 33182.28 34359.36 34991.83 33985.63 34952.69 34460.22 34477.28 34341.06 34780.12 34746.15 34441.14 34261.57 344
EMVS64.07 31863.26 32066.53 33281.73 34458.81 35091.85 33884.75 35051.93 34659.09 34575.13 34443.32 34679.09 34842.03 34539.47 34361.69 343
MVEpermissive62.14 2263.28 31959.38 32174.99 32874.33 34865.47 34585.55 34280.50 35252.02 34551.10 34675.00 34510.91 35580.50 34651.60 34353.40 34178.99 340
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuyk23d30.17 32030.18 32330.16 33378.61 34643.29 35266.79 34614.21 35417.31 34814.82 35111.93 35111.55 35441.43 35037.08 34619.30 3465.76 347
cdsmvs_eth3d_5k23.98 32131.98 3220.00 3360.00 3540.00 3550.00 34798.59 1350.00 3510.00 35298.61 12190.60 1510.00 3530.00 3490.00 3490.00 348
testmvs21.48 32224.95 32411.09 33514.89 3526.47 35496.56 3119.87 3557.55 34917.93 34939.02 3479.43 3565.90 35216.56 34812.72 34720.91 346
test12320.95 32323.72 32512.64 33413.54 3538.19 35396.55 3126.13 3567.48 35016.74 35037.98 34812.97 3536.05 35116.69 3475.43 34823.68 345
ab-mvs-re8.20 32410.94 3260.00 3360.00 3540.00 3550.00 3470.00 3570.00 3510.00 35298.43 1380.00 3570.00 3530.00 3490.00 3490.00 348
pcd_1.5k_mvsjas7.88 32510.50 3270.00 3360.00 3540.00 3550.00 3470.00 3570.00 3510.00 3520.00 35294.51 790.00 3530.00 3490.00 3490.00 348
uanet_test0.00 3260.00 3280.00 3360.00 3540.00 3550.00 347