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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
LCM-MVSNet99.86 199.86 199.87 199.99 199.77 199.77 199.80 199.97 199.97 199.95 199.74 199.98 199.56 1100.00 199.85 3
UA-Net98.88 798.76 1399.22 299.11 8497.89 1499.47 399.32 1099.08 1097.87 14199.67 296.47 8899.92 497.88 2399.98 299.85 3
abl_698.42 2398.19 3299.09 399.16 7198.10 697.73 7299.11 2997.76 5098.62 5298.27 10397.88 1999.80 3895.67 10899.50 11599.38 88
zzz-MVS98.01 4497.66 6799.06 499.44 3297.90 1295.66 18498.73 12997.69 5797.90 13597.96 14095.81 11299.82 2996.13 8199.61 7599.45 69
MTAPA98.14 3497.84 5199.06 499.44 3297.90 1297.25 9898.73 12997.69 5797.90 13597.96 14095.81 11299.82 2996.13 8199.61 7599.45 69
test117298.08 3997.76 5999.05 698.78 11498.07 797.41 9398.85 9497.57 6198.15 10697.96 14096.60 8099.76 5895.30 13499.18 19799.33 100
mPP-MVS97.91 5997.53 8399.04 799.22 5997.87 1597.74 7098.78 12096.04 12397.10 18097.73 16996.53 8399.78 4395.16 14499.50 11599.46 64
MSP-MVS97.45 9596.92 12399.03 899.26 5097.70 1997.66 7398.89 7995.65 14598.51 6296.46 26292.15 21599.81 3295.14 14798.58 26499.58 28
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
SR-MVS-dyc-post98.14 3497.84 5199.02 998.81 10998.05 997.55 8198.86 9097.77 4798.20 9998.07 12596.60 8099.76 5895.49 11899.20 19299.26 120
TDRefinement98.90 598.86 899.02 999.54 2198.06 899.34 499.44 898.85 2099.00 3699.20 2397.42 3299.59 16097.21 4899.76 4299.40 84
SR-MVS98.00 4597.66 6799.01 1198.77 11697.93 1197.38 9498.83 10697.32 7598.06 11897.85 15596.65 7599.77 5395.00 15699.11 20899.32 101
MP-MVScopyleft97.64 8097.18 10799.00 1299.32 4797.77 1897.49 8798.73 12996.27 10995.59 25797.75 16696.30 9699.78 4393.70 21099.48 12399.45 69
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
Effi-MVS+-dtu96.81 13396.09 16698.99 1396.90 30098.69 296.42 13898.09 22195.86 13695.15 26595.54 30194.26 16699.81 3294.06 19498.51 26798.47 236
anonymousdsp98.72 1498.63 1998.99 1399.62 1397.29 3998.65 1699.19 1895.62 14799.35 1999.37 1297.38 3399.90 1398.59 1199.91 1799.77 8
CP-MVS97.92 5697.56 8298.99 1398.99 9797.82 1697.93 5798.96 7196.11 11896.89 19997.45 19296.85 6899.78 4395.19 14099.63 6899.38 88
PGM-MVS97.88 6297.52 8498.96 1699.20 6797.62 2297.09 10999.06 4195.45 15597.55 15197.94 14597.11 4499.78 4394.77 16699.46 12899.48 59
RPSCF97.87 6397.51 8598.95 1799.15 7498.43 397.56 8099.06 4196.19 11598.48 6698.70 6294.72 14999.24 25994.37 18199.33 17499.17 136
XVS97.96 4697.63 7498.94 1899.15 7497.66 2097.77 6698.83 10697.42 6996.32 22597.64 17696.49 8699.72 8695.66 11099.37 15699.45 69
X-MVStestdata92.86 28090.83 30598.94 1899.15 7497.66 2097.77 6698.83 10697.42 6996.32 22536.50 37296.49 8699.72 8695.66 11099.37 15699.45 69
ACMMPR97.95 5097.62 7698.94 1899.20 6797.56 2697.59 7898.83 10696.05 12197.46 16397.63 17796.77 7199.76 5895.61 11499.46 12899.49 53
ACMMPcopyleft98.05 4197.75 6198.93 2199.23 5697.60 2398.09 5098.96 7195.75 14397.91 13498.06 13096.89 6499.76 5895.32 13399.57 8699.43 80
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
region2R97.92 5697.59 7998.92 2299.22 5997.55 2797.60 7798.84 9996.00 12697.22 17097.62 17896.87 6799.76 5895.48 12199.43 14199.46 64
HPM-MVScopyleft98.11 3897.83 5398.92 2299.42 3697.46 3398.57 1799.05 4395.43 15797.41 16697.50 18897.98 1599.79 3995.58 11799.57 8699.50 45
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
HPM-MVS_fast98.32 2798.13 3398.88 2499.54 2197.48 3298.35 2999.03 5095.88 13497.88 13898.22 11098.15 1299.74 7596.50 7099.62 6999.42 81
ACMM93.33 1198.05 4197.79 5598.85 2599.15 7497.55 2796.68 13198.83 10695.21 16398.36 7998.13 11798.13 1499.62 15196.04 8799.54 9899.39 86
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ZNCC-MVS97.92 5697.62 7698.83 2699.32 4797.24 4197.45 8898.84 9995.76 14196.93 19697.43 19497.26 4099.79 3996.06 8499.53 10199.45 69
HFP-MVS97.94 5297.64 7298.83 2699.15 7497.50 3097.59 7898.84 9996.05 12197.49 15797.54 18397.07 4899.70 10995.61 11499.46 12899.30 107
#test#97.62 8297.22 10598.83 2699.15 7497.50 3096.81 12198.84 9994.25 20097.49 15797.54 18397.07 4899.70 10994.37 18199.46 12899.30 107
GST-MVS97.82 6997.49 8898.81 2999.23 5697.25 4097.16 10398.79 11695.96 12897.53 15297.40 19696.93 6099.77 5395.04 15399.35 16499.42 81
HPM-MVS++copyleft96.99 11796.38 15398.81 2998.64 13097.59 2495.97 16698.20 20495.51 15395.06 26696.53 25894.10 17099.70 10994.29 18599.15 19999.13 146
APD-MVS_3200maxsize98.13 3797.90 4598.79 3198.79 11297.31 3897.55 8198.92 7697.72 5498.25 9498.13 11797.10 4599.75 6595.44 12599.24 19099.32 101
SteuartSystems-ACMMP98.02 4397.76 5998.79 3199.43 3497.21 4397.15 10498.90 7896.58 9698.08 11697.87 15497.02 5399.76 5895.25 13799.59 8199.40 84
Skip Steuart: Steuart Systems R&D Blog.
mvs_tets98.90 598.94 698.75 3399.69 896.48 6198.54 2099.22 1396.23 11299.71 499.48 798.77 699.93 298.89 399.95 599.84 5
WR-MVS_H98.65 1598.62 2198.75 3399.51 2496.61 5798.55 1999.17 1999.05 1399.17 2998.79 5595.47 12799.89 1697.95 2199.91 1799.75 13
jajsoiax98.77 998.79 1298.74 3599.66 1096.48 6198.45 2699.12 2895.83 13999.67 699.37 1298.25 1099.92 498.77 599.94 899.82 6
LPG-MVS_test97.94 5297.67 6698.74 3599.15 7497.02 4497.09 10999.02 5295.15 16798.34 8298.23 10797.91 1799.70 10994.41 17899.73 4899.50 45
LGP-MVS_train98.74 3599.15 7497.02 4499.02 5295.15 16798.34 8298.23 10797.91 1799.70 10994.41 17899.73 4899.50 45
LTVRE_ROB96.88 199.18 299.34 298.72 3899.71 796.99 4699.69 299.57 499.02 1599.62 1099.36 1498.53 799.52 18298.58 1299.95 599.66 22
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
MP-MVS-pluss97.69 7897.36 9498.70 3999.50 2796.84 4995.38 20198.99 6392.45 25298.11 11098.31 9097.25 4199.77 5396.60 6499.62 6999.48 59
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
test_djsdf98.73 1198.74 1698.69 4099.63 1296.30 6798.67 1399.02 5296.50 10099.32 2099.44 1097.43 3199.92 498.73 799.95 599.86 2
ACMMP_NAP97.89 6197.63 7498.67 4199.35 4396.84 4996.36 14298.79 11695.07 17197.88 13898.35 8697.24 4299.72 8696.05 8699.58 8399.45 69
MIMVSNet198.51 2098.45 2698.67 4199.72 696.71 5298.76 1198.89 7998.49 2899.38 1799.14 3395.44 12999.84 2596.47 7199.80 3699.47 62
UniMVSNet_ETH3D99.12 399.28 398.65 4399.77 396.34 6599.18 599.20 1699.67 299.73 399.65 499.15 399.86 2097.22 4699.92 1499.77 8
COLMAP_ROBcopyleft94.48 698.25 3198.11 3498.64 4499.21 6697.35 3797.96 5599.16 2098.34 3298.78 4598.52 7597.32 3599.45 20294.08 19399.67 6199.13 146
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
OurMVSNet-221017-098.61 1698.61 2398.63 4599.77 396.35 6499.17 699.05 4398.05 4199.61 1199.52 593.72 18099.88 1898.72 999.88 2399.65 23
SMA-MVScopyleft97.48 9397.11 11098.60 4698.83 10896.67 5496.74 12598.73 12991.61 26398.48 6698.36 8596.53 8399.68 12595.17 14299.54 9899.45 69
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
DTE-MVSNet98.79 898.86 898.59 4799.55 1996.12 7298.48 2599.10 3199.36 499.29 2399.06 3997.27 3899.93 297.71 3299.91 1799.70 18
LS3D97.77 7397.50 8798.57 4896.24 31397.58 2598.45 2698.85 9498.58 2797.51 15497.94 14595.74 11699.63 14395.19 14098.97 22298.51 233
pmmvs699.07 499.24 498.56 4999.81 296.38 6398.87 999.30 1199.01 1699.63 999.66 399.27 299.68 12597.75 3099.89 2299.62 25
ACMP92.54 1397.47 9497.10 11198.55 5099.04 9496.70 5396.24 15098.89 7993.71 21697.97 12997.75 16697.44 3099.63 14393.22 21999.70 5799.32 101
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
EGC-MVSNET83.08 33877.93 34198.53 5199.57 1697.55 2798.33 3298.57 1614.71 37410.38 37598.90 5095.60 12199.50 18795.69 10699.61 7598.55 231
DPE-MVScopyleft97.64 8097.35 9598.50 5298.85 10796.18 6995.21 21698.99 6395.84 13898.78 4598.08 12396.84 6999.81 3293.98 20099.57 8699.52 42
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
XVG-ACMP-BASELINE97.58 8697.28 10098.49 5399.16 7196.90 4896.39 13998.98 6695.05 17298.06 11898.02 13495.86 10499.56 16994.37 18199.64 6699.00 171
CPTT-MVS96.69 14396.08 16798.49 5398.89 10596.64 5697.25 9898.77 12192.89 24696.01 24197.13 21792.23 21499.67 13092.24 23199.34 16799.17 136
APDe-MVS98.14 3498.03 4098.47 5598.72 12096.04 7598.07 5199.10 3195.96 12898.59 5798.69 6396.94 5899.81 3296.64 6299.58 8399.57 32
PEN-MVS98.75 1098.85 1098.44 5699.58 1595.67 8998.45 2699.15 2499.33 599.30 2199.00 4197.27 3899.92 497.64 3499.92 1499.75 13
TranMVSNet+NR-MVSNet98.33 2698.30 3198.43 5799.07 8895.87 8096.73 12999.05 4398.67 2498.84 4298.45 8097.58 2899.88 1896.45 7299.86 2599.54 38
OPM-MVS97.54 8897.25 10198.41 5899.11 8496.61 5795.24 21498.46 17094.58 19098.10 11398.07 12597.09 4799.39 22495.16 14499.44 13399.21 129
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
APD-MVScopyleft97.00 11696.53 14698.41 5898.55 14496.31 6696.32 14598.77 12192.96 24597.44 16597.58 18295.84 10599.74 7591.96 23499.35 16499.19 133
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
PS-CasMVS98.73 1198.85 1098.39 6099.55 1995.47 10198.49 2399.13 2799.22 899.22 2798.96 4597.35 3499.92 497.79 2899.93 1099.79 7
UniMVSNet_NR-MVSNet97.83 6797.65 6998.37 6198.72 12095.78 8295.66 18499.02 5298.11 4098.31 8997.69 17494.65 15499.85 2297.02 5799.71 5499.48 59
testtj96.69 14396.13 16398.36 6298.46 15896.02 7796.44 13798.70 13994.26 19996.79 20197.13 21794.07 17199.75 6590.53 27598.80 24399.31 106
DU-MVS97.79 7197.60 7898.36 6298.73 11895.78 8295.65 18798.87 8797.57 6198.31 8997.83 15794.69 15099.85 2297.02 5799.71 5499.46 64
UniMVSNet (Re)97.83 6797.65 6998.35 6498.80 11195.86 8195.92 17199.04 4997.51 6698.22 9897.81 16194.68 15299.78 4397.14 5399.75 4699.41 83
mvs-test196.20 16495.50 18998.32 6596.90 30098.16 595.07 22498.09 22195.86 13693.63 30894.32 32794.26 16699.71 10094.06 19497.27 31697.07 312
nrg03098.54 1898.62 2198.32 6599.22 5995.66 9097.90 6099.08 3798.31 3399.02 3498.74 5997.68 2499.61 15897.77 2999.85 2899.70 18
DeepPCF-MVS94.58 596.90 12596.43 15298.31 6797.48 26597.23 4292.56 31198.60 15792.84 24798.54 6097.40 19696.64 7798.78 31094.40 18099.41 15098.93 183
CP-MVSNet98.42 2398.46 2498.30 6899.46 3095.22 11798.27 3898.84 9999.05 1399.01 3598.65 6795.37 13099.90 1397.57 3699.91 1799.77 8
XVG-OURS-SEG-HR97.38 10097.07 11498.30 6899.01 9697.41 3694.66 24499.02 5295.20 16498.15 10697.52 18698.83 498.43 33994.87 15996.41 33199.07 162
h-mvs3396.29 16095.63 18498.26 7098.50 15196.11 7396.90 11797.09 27596.58 9697.21 17298.19 11284.14 29799.78 4395.89 9896.17 33598.89 192
NR-MVSNet97.96 4697.86 5098.26 7098.73 11895.54 9498.14 4798.73 12997.79 4699.42 1597.83 15794.40 16399.78 4395.91 9799.76 4299.46 64
XVG-OURS97.12 11396.74 13298.26 7098.99 9797.45 3493.82 27999.05 4395.19 16598.32 8797.70 17295.22 13698.41 34094.27 18698.13 27998.93 183
test_0728_SECOND98.25 7399.23 5695.49 10096.74 12598.89 7999.75 6595.48 12199.52 10699.53 41
PHI-MVS96.96 12196.53 14698.25 7397.48 26596.50 6096.76 12498.85 9493.52 21996.19 23496.85 23795.94 10299.42 20893.79 20699.43 14198.83 201
MSC_two_6792asdad98.22 7597.75 24395.34 10998.16 21399.75 6595.87 10099.51 11199.57 32
No_MVS98.22 7597.75 24395.34 10998.16 21399.75 6595.87 10099.51 11199.57 32
SF-MVS97.60 8497.39 9298.22 7598.93 10295.69 8697.05 11199.10 3195.32 16097.83 14497.88 15296.44 9099.72 8694.59 17399.39 15399.25 124
PS-MVSNAJss98.53 1998.63 1998.21 7899.68 994.82 12998.10 4999.21 1496.91 8599.75 299.45 995.82 10899.92 498.80 499.96 499.89 1
ETH3D-3000-0.196.89 12796.46 15198.16 7998.62 13595.69 8695.96 16798.98 6693.36 22497.04 18797.31 20994.93 14599.63 14392.60 22699.34 16799.17 136
DVP-MVScopyleft97.78 7297.65 6998.16 7999.24 5495.51 9696.74 12598.23 20095.92 13198.40 7398.28 9997.06 5099.71 10095.48 12199.52 10699.26 120
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
DeepC-MVS95.41 497.82 6997.70 6298.16 7998.78 11495.72 8496.23 15199.02 5293.92 21198.62 5298.99 4297.69 2399.62 15196.18 8099.87 2499.15 140
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
3Dnovator+96.13 397.73 7597.59 7998.15 8298.11 19695.60 9298.04 5298.70 13998.13 3996.93 19698.45 8095.30 13499.62 15195.64 11298.96 22399.24 126
PM-MVS97.36 10397.10 11198.14 8398.91 10496.77 5196.20 15298.63 15593.82 21398.54 6098.33 8893.98 17399.05 28495.99 9299.45 13298.61 226
DVP-MVS++97.96 4697.90 4598.12 8497.75 24395.40 10299.03 798.89 7996.62 9298.62 5298.30 9496.97 5699.75 6595.70 10499.25 18799.21 129
NCCC96.52 15295.99 17198.10 8597.81 22595.68 8895.00 23098.20 20495.39 15895.40 26196.36 26993.81 17799.45 20293.55 21398.42 26999.17 136
ETH3D cwj APD-0.1696.23 16395.61 18698.09 8697.91 21295.65 9194.94 23298.74 12791.31 26996.02 24097.08 22294.05 17299.69 11791.51 24698.94 22798.93 183
SED-MVS97.94 5297.90 4598.07 8799.22 5995.35 10796.79 12298.83 10696.11 11899.08 3198.24 10597.87 2099.72 8695.44 12599.51 11199.14 143
Vis-MVSNetpermissive98.27 2998.34 2898.07 8799.33 4595.21 11998.04 5299.46 797.32 7597.82 14699.11 3496.75 7299.86 2097.84 2599.36 15999.15 140
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
AllTest97.20 11296.92 12398.06 8999.08 8696.16 7097.14 10699.16 2094.35 19697.78 14798.07 12595.84 10599.12 27491.41 24799.42 14498.91 188
TestCases98.06 8999.08 8696.16 7099.16 2094.35 19697.78 14798.07 12595.84 10599.12 27491.41 24799.42 14498.91 188
N_pmnet95.18 20694.23 24098.06 8997.85 21796.55 5992.49 31291.63 34689.34 28798.09 11497.41 19590.33 24399.06 28391.58 24599.31 17898.56 229
F-COLMAP95.30 20294.38 23798.05 9298.64 13096.04 7595.61 19098.66 14989.00 29193.22 32296.40 26692.90 19699.35 23587.45 32297.53 30698.77 210
CNVR-MVS96.92 12396.55 14398.03 9398.00 20695.54 9494.87 23598.17 21094.60 18796.38 22297.05 22595.67 11899.36 23295.12 15099.08 21299.19 133
TSAR-MVS + MP.97.42 9797.23 10498.00 9499.38 4095.00 12497.63 7698.20 20493.00 24098.16 10498.06 13095.89 10399.72 8695.67 10899.10 21099.28 115
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
ACMH+93.58 1098.23 3298.31 2997.98 9599.39 3995.22 11797.55 8199.20 1698.21 3799.25 2598.51 7698.21 1199.40 21994.79 16399.72 5199.32 101
v7n98.73 1198.99 597.95 9699.64 1194.20 15598.67 1399.14 2699.08 1099.42 1599.23 2196.53 8399.91 1299.27 299.93 1099.73 15
Anonymous2023121198.55 1798.76 1397.94 9798.79 11294.37 14798.84 1099.15 2499.37 399.67 699.43 1195.61 12099.72 8698.12 1699.86 2599.73 15
Regformer-297.41 9897.24 10397.93 9897.21 28794.72 13294.85 23798.27 19597.74 5198.11 11097.50 18895.58 12299.69 11796.57 6799.31 17899.37 95
OMC-MVS96.48 15496.00 17097.91 9998.30 16796.01 7894.86 23698.60 15791.88 26097.18 17497.21 21596.11 9999.04 28590.49 27999.34 16798.69 218
GeoE97.75 7497.70 6297.89 10098.88 10694.53 14097.10 10898.98 6695.75 14397.62 14997.59 18097.61 2799.77 5396.34 7699.44 13399.36 96
xxxxxxxxxxxxxcwj97.24 11097.03 11797.89 10098.48 15494.71 13394.53 24999.07 4095.02 17497.83 14497.88 15296.44 9099.72 8694.59 17399.39 15399.25 124
train_agg95.46 19594.66 21997.88 10297.84 22195.23 11493.62 28598.39 18287.04 31193.78 30095.99 28594.58 15799.52 18291.76 24298.90 23198.89 192
pm-mvs198.47 2198.67 1797.86 10399.52 2394.58 13998.28 3699.00 6097.57 6199.27 2499.22 2298.32 999.50 18797.09 5499.75 4699.50 45
ITE_SJBPF97.85 10498.64 13096.66 5598.51 16795.63 14697.22 17097.30 21095.52 12398.55 33390.97 25798.90 23198.34 249
CDPH-MVS95.45 19694.65 22097.84 10598.28 17094.96 12593.73 28398.33 19185.03 33395.44 25996.60 25495.31 13399.44 20590.01 28599.13 20499.11 155
DP-MVS97.87 6397.89 4897.81 10698.62 13594.82 12997.13 10798.79 11698.98 1798.74 4898.49 7795.80 11499.49 18995.04 15399.44 13399.11 155
hse-mvs295.77 18295.09 19897.79 10797.84 22195.51 9695.66 18495.43 31496.58 9697.21 17296.16 27784.14 29799.54 17695.89 9896.92 31898.32 250
DROMVSNet97.90 6097.94 4497.79 10798.66 12995.14 12098.31 3399.66 297.57 6195.95 24297.01 22996.99 5599.82 2997.66 3399.64 6698.39 241
MAR-MVS94.21 25093.03 26797.76 10996.94 29897.44 3596.97 11697.15 27287.89 30592.00 34092.73 34592.14 21699.12 27483.92 34697.51 30796.73 329
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
agg_prior195.39 19894.60 22597.75 11097.80 22994.96 12593.39 29398.36 18687.20 30993.49 31495.97 28894.65 15499.53 17891.69 24498.86 23798.77 210
AUN-MVS93.95 26092.69 27797.74 11197.80 22995.38 10495.57 19195.46 31391.26 27092.64 33396.10 28374.67 34299.55 17393.72 20996.97 31798.30 254
VDD-MVS97.37 10197.25 10197.74 11198.69 12794.50 14397.04 11295.61 30998.59 2698.51 6298.72 6092.54 20899.58 16296.02 8999.49 11999.12 151
Anonymous2024052997.96 4698.04 3997.71 11398.69 12794.28 15297.86 6298.31 19498.79 2299.23 2698.86 5395.76 11599.61 15895.49 11899.36 15999.23 127
Regformer-497.53 9097.47 9097.71 11397.35 27593.91 16395.26 21198.14 21697.97 4398.34 8297.89 15095.49 12499.71 10097.41 4199.42 14499.51 44
VPA-MVSNet98.27 2998.46 2497.70 11599.06 8993.80 16997.76 6899.00 6098.40 3099.07 3398.98 4396.89 6499.75 6597.19 5199.79 3899.55 37
IS-MVSNet96.93 12296.68 13597.70 11599.25 5394.00 16198.57 1796.74 28998.36 3198.14 10897.98 13988.23 26999.71 10093.10 22299.72 5199.38 88
CSCG97.40 9997.30 9797.69 11798.95 9994.83 12897.28 9798.99 6396.35 10898.13 10995.95 29095.99 10199.66 13694.36 18499.73 4898.59 227
HQP_MVS96.66 14696.33 15697.68 11898.70 12594.29 14996.50 13598.75 12596.36 10696.16 23596.77 24491.91 22699.46 19892.59 22899.20 19299.28 115
EPP-MVSNet96.84 12896.58 14097.65 11999.18 7093.78 17198.68 1296.34 29397.91 4597.30 16898.06 13088.46 26699.85 2293.85 20499.40 15199.32 101
OPU-MVS97.64 12098.01 20295.27 11296.79 12297.35 20596.97 5698.51 33691.21 25399.25 18799.14 143
MVS_111021_LR96.82 13296.55 14397.62 12198.27 17295.34 10993.81 28198.33 19194.59 18996.56 21496.63 25396.61 7898.73 31594.80 16299.34 16798.78 207
Regformer-197.27 10797.16 10897.61 12297.21 28793.86 16694.85 23798.04 23097.62 6098.03 12297.50 18895.34 13199.63 14396.52 6899.31 17899.35 98
UGNet96.81 13396.56 14297.58 12396.64 30393.84 16897.75 6997.12 27496.47 10393.62 30998.88 5193.22 18999.53 17895.61 11499.69 5899.36 96
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
FC-MVSNet-test98.16 3398.37 2797.56 12499.49 2893.10 19198.35 2999.21 1498.43 2998.89 3998.83 5494.30 16599.81 3297.87 2499.91 1799.77 8
MCST-MVS96.24 16295.80 17897.56 12498.75 11794.13 15794.66 24498.17 21090.17 28196.21 23396.10 28395.14 13799.43 20794.13 19298.85 23999.13 146
GBi-Net96.99 11796.80 12997.56 12497.96 20893.67 17498.23 3998.66 14995.59 15097.99 12599.19 2489.51 25899.73 8194.60 17099.44 13399.30 107
test196.99 11796.80 12997.56 12497.96 20893.67 17498.23 3998.66 14995.59 15097.99 12599.19 2489.51 25899.73 8194.60 17099.44 13399.30 107
FMVSNet197.95 5098.08 3597.56 12499.14 8293.67 17498.23 3998.66 14997.41 7299.00 3699.19 2495.47 12799.73 8195.83 10299.76 4299.30 107
TransMVSNet (Re)98.38 2598.67 1797.51 12999.51 2493.39 18498.20 4498.87 8798.23 3699.48 1299.27 1998.47 899.55 17396.52 6899.53 10199.60 26
PLCcopyleft91.02 1694.05 25792.90 26997.51 12998.00 20695.12 12294.25 25798.25 19886.17 31791.48 34395.25 30691.01 23499.19 26485.02 34196.69 32698.22 262
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
ACMH93.61 998.44 2298.76 1397.51 12999.43 3493.54 18098.23 3999.05 4397.40 7399.37 1899.08 3798.79 599.47 19597.74 3199.71 5499.50 45
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
alignmvs96.01 17395.52 18897.50 13297.77 24094.71 13396.07 15896.84 28397.48 6796.78 20594.28 32885.50 28999.40 21996.22 7898.73 25298.40 239
Baseline_NR-MVSNet97.72 7697.79 5597.50 13299.56 1793.29 18595.44 19498.86 9098.20 3898.37 7699.24 2094.69 15099.55 17395.98 9399.79 3899.65 23
3Dnovator96.53 297.61 8397.64 7297.50 13297.74 24693.65 17898.49 2398.88 8596.86 8797.11 17998.55 7395.82 10899.73 8195.94 9599.42 14499.13 146
TSAR-MVS + GP.96.47 15596.12 16497.49 13597.74 24695.23 11494.15 26496.90 28293.26 22898.04 12196.70 24994.41 16298.89 30194.77 16699.14 20098.37 243
FIs97.93 5598.07 3697.48 13699.38 4092.95 19498.03 5499.11 2998.04 4298.62 5298.66 6593.75 17999.78 4397.23 4599.84 2999.73 15
ETH3 D test640094.77 22393.87 25497.47 13798.12 19593.73 17294.56 24898.70 13985.45 32894.70 27695.93 29291.77 22899.63 14386.45 32899.14 20099.05 166
test_part196.77 13696.53 14697.47 13798.04 19892.92 19597.93 5798.85 9498.83 2199.30 2199.07 3879.25 31899.79 3997.59 3599.93 1099.69 20
test_040297.84 6697.97 4197.47 13799.19 6994.07 15896.71 13098.73 12998.66 2598.56 5998.41 8296.84 6999.69 11794.82 16199.81 3398.64 221
test_prior395.91 17795.39 19097.46 14097.79 23594.26 15393.33 29698.42 17794.21 20194.02 29596.25 27393.64 18199.34 23791.90 23698.96 22398.79 205
test_prior97.46 14097.79 23594.26 15398.42 17799.34 23798.79 205
test1297.46 14097.61 25794.07 15897.78 24393.57 31293.31 18799.42 20898.78 24598.89 192
DeepC-MVS_fast94.34 796.74 13796.51 14997.44 14397.69 24994.15 15696.02 16298.43 17493.17 23597.30 16897.38 20295.48 12699.28 25393.74 20799.34 16798.88 196
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
Anonymous20240521196.34 15995.98 17297.43 14498.25 17593.85 16796.74 12594.41 32297.72 5498.37 7698.03 13387.15 28099.53 17894.06 19499.07 21498.92 187
pmmvs-eth3d96.49 15396.18 16297.42 14598.25 17594.29 14994.77 24198.07 22789.81 28497.97 12998.33 8893.11 19099.08 28195.46 12499.84 2998.89 192
VDDNet96.98 12096.84 12697.41 14699.40 3893.26 18697.94 5695.31 31599.26 798.39 7599.18 2787.85 27699.62 15195.13 14999.09 21199.35 98
EG-PatchMatch MVS97.69 7897.79 5597.40 14799.06 8993.52 18195.96 16798.97 7094.55 19198.82 4398.76 5897.31 3699.29 25197.20 5099.44 13399.38 88
Fast-Effi-MVS+-dtu96.44 15696.12 16497.39 14897.18 28994.39 14595.46 19398.73 12996.03 12594.72 27494.92 31596.28 9899.69 11793.81 20597.98 28498.09 268
RRT_MVS94.90 21794.07 24697.39 14893.18 36293.21 18895.26 21197.49 26193.94 21098.25 9497.85 15572.96 35399.84 2597.90 2299.78 4199.14 143
LF4IMVS96.07 16995.63 18497.36 15098.19 18195.55 9395.44 19498.82 11492.29 25495.70 25596.55 25692.63 20498.69 31991.75 24399.33 17497.85 288
Gipumacopyleft98.07 4098.31 2997.36 15099.76 596.28 6898.51 2299.10 3198.76 2396.79 20199.34 1796.61 7898.82 30696.38 7499.50 11596.98 315
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
LCM-MVSNet-Re97.33 10497.33 9697.32 15298.13 19493.79 17096.99 11599.65 396.74 9099.47 1398.93 4796.91 6399.84 2590.11 28399.06 21798.32 250
canonicalmvs97.23 11197.21 10697.30 15397.65 25494.39 14597.84 6399.05 4397.42 6996.68 20893.85 33197.63 2699.33 24096.29 7798.47 26898.18 266
112194.26 24693.26 26397.27 15498.26 17494.73 13195.86 17297.71 24777.96 36294.53 28096.71 24891.93 22499.40 21987.71 31498.64 25997.69 296
MVS_111021_HR96.73 13996.54 14597.27 15498.35 16593.66 17793.42 29198.36 18694.74 18296.58 21296.76 24696.54 8298.99 29194.87 15999.27 18599.15 140
SixPastTwentyTwo97.49 9297.57 8197.26 15699.56 1792.33 20498.28 3696.97 28098.30 3499.45 1499.35 1688.43 26799.89 1698.01 2099.76 4299.54 38
KD-MVS_self_test97.86 6598.07 3697.25 15799.22 5992.81 19797.55 8198.94 7497.10 8198.85 4198.88 5195.03 14199.67 13097.39 4399.65 6499.26 120
新几何197.25 15798.29 16894.70 13697.73 24577.98 36194.83 27396.67 25192.08 21999.45 20288.17 31298.65 25897.61 299
WR-MVS96.90 12596.81 12897.16 15998.56 14392.20 21094.33 25398.12 21997.34 7498.20 9997.33 20792.81 19799.75 6594.79 16399.81 3399.54 38
TAMVS95.49 19194.94 20497.16 15998.31 16693.41 18395.07 22496.82 28591.09 27297.51 15497.82 16089.96 25099.42 20888.42 30899.44 13398.64 221
CDS-MVSNet94.88 21994.12 24597.14 16197.64 25593.57 17993.96 27597.06 27790.05 28296.30 22896.55 25686.10 28599.47 19590.10 28499.31 17898.40 239
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
EI-MVSNet-Vis-set97.32 10597.39 9297.11 16297.36 27492.08 21495.34 20497.65 25397.74 5198.29 9298.11 12195.05 13899.68 12597.50 3999.50 11599.56 35
Regformer-397.25 10997.29 9897.11 16297.35 27592.32 20595.26 21197.62 25897.67 5998.17 10397.89 15095.05 13899.56 16997.16 5299.42 14499.46 64
EI-MVSNet-UG-set97.32 10597.40 9197.09 16497.34 27992.01 21695.33 20597.65 25397.74 5198.30 9198.14 11695.04 14099.69 11797.55 3799.52 10699.58 28
XXY-MVS97.54 8897.70 6297.07 16599.46 3092.21 20897.22 10199.00 6094.93 17898.58 5898.92 4897.31 3699.41 21794.44 17699.43 14199.59 27
lessismore_v097.05 16699.36 4292.12 21284.07 37098.77 4798.98 4385.36 29099.74 7597.34 4499.37 15699.30 107
TAPA-MVS93.32 1294.93 21694.23 24097.04 16798.18 18494.51 14195.22 21598.73 12981.22 35096.25 23195.95 29093.80 17898.98 29389.89 28798.87 23597.62 298
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
EPNet93.72 26392.62 28097.03 16887.61 37792.25 20696.27 14691.28 34996.74 9087.65 36397.39 20085.00 29299.64 14192.14 23299.48 12399.20 132
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PatchMatch-RL94.61 23593.81 25597.02 16998.19 18195.72 8493.66 28497.23 26888.17 30194.94 27195.62 29991.43 23098.57 33087.36 32397.68 29996.76 328
K. test v396.44 15696.28 15796.95 17099.41 3791.53 22497.65 7490.31 35898.89 1998.93 3899.36 1484.57 29699.92 497.81 2699.56 8999.39 86
tfpnnormal97.72 7697.97 4196.94 17199.26 5092.23 20797.83 6498.45 17198.25 3599.13 3098.66 6596.65 7599.69 11793.92 20299.62 6998.91 188
MVP-Stereo95.69 18395.28 19296.92 17298.15 19093.03 19295.64 18998.20 20490.39 27896.63 21197.73 16991.63 22999.10 27991.84 24097.31 31498.63 223
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
HQP-MVS95.17 20894.58 22896.92 17297.85 21792.47 20294.26 25498.43 17493.18 23292.86 32795.08 30990.33 24399.23 26190.51 27798.74 24999.05 166
HyFIR lowres test93.72 26392.65 27896.91 17498.93 10291.81 22191.23 33598.52 16582.69 34396.46 21996.52 26080.38 31599.90 1390.36 28198.79 24499.03 168
VNet96.84 12896.83 12796.88 17598.06 19792.02 21596.35 14397.57 26097.70 5697.88 13897.80 16292.40 21299.54 17694.73 16898.96 22399.08 160
FMVSNet296.72 14096.67 13696.87 17697.96 20891.88 21897.15 10498.06 22895.59 15098.50 6498.62 6889.51 25899.65 13894.99 15799.60 7999.07 162
EIA-MVS96.04 17195.77 18096.85 17797.80 22992.98 19396.12 15699.16 2094.65 18593.77 30291.69 35695.68 11799.67 13094.18 18998.85 23997.91 286
MVS_030495.50 19095.05 20296.84 17896.28 31293.12 19097.00 11496.16 29595.03 17389.22 35797.70 17290.16 24999.48 19294.51 17599.34 16797.93 285
ETV-MVS96.13 16895.90 17696.82 17997.76 24193.89 16495.40 19998.95 7395.87 13595.58 25891.00 36296.36 9599.72 8693.36 21498.83 24196.85 322
DP-MVS Recon95.55 18995.13 19696.80 18098.51 14893.99 16294.60 24698.69 14290.20 28095.78 25196.21 27692.73 20098.98 29390.58 27498.86 23797.42 305
QAPM95.88 17995.57 18796.80 18097.90 21491.84 22098.18 4698.73 12988.41 29796.42 22098.13 11794.73 14899.75 6588.72 30398.94 22798.81 203
CMPMVSbinary73.10 2392.74 28291.39 29496.77 18293.57 36194.67 13794.21 26197.67 24980.36 35493.61 31096.60 25482.85 30397.35 36084.86 34298.78 24598.29 257
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
Fast-Effi-MVS+95.49 19195.07 19996.75 18397.67 25392.82 19694.22 26098.60 15791.61 26393.42 31992.90 34196.73 7399.70 10992.60 22697.89 28997.74 293
CNLPA95.04 21294.47 23396.75 18397.81 22595.25 11394.12 26897.89 23594.41 19394.57 27895.69 29590.30 24698.35 34686.72 32798.76 24796.64 331
Effi-MVS+96.19 16596.01 16996.71 18597.43 27192.19 21196.12 15699.10 3195.45 15593.33 32194.71 31897.23 4399.56 16993.21 22097.54 30598.37 243
pmmvs494.82 22194.19 24396.70 18697.42 27292.75 19992.09 32196.76 28786.80 31495.73 25497.22 21489.28 26198.89 30193.28 21799.14 20098.46 238
CS-MVS-test96.62 14896.59 13896.69 18797.88 21693.16 18997.21 10299.53 695.61 14893.72 30495.33 30595.49 12499.69 11795.37 13299.19 19697.22 309
CLD-MVS95.47 19495.07 19996.69 18798.27 17292.53 20191.36 32998.67 14791.22 27195.78 25194.12 32995.65 11998.98 29390.81 26299.72 5198.57 228
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
V4297.04 11597.16 10896.68 18998.59 14091.05 22996.33 14498.36 18694.60 18797.99 12598.30 9493.32 18699.62 15197.40 4299.53 10199.38 88
LFMVS95.32 20194.88 20996.62 19098.03 19991.47 22697.65 7490.72 35599.11 997.89 13798.31 9079.20 31999.48 19293.91 20399.12 20798.93 183
ab-mvs96.59 14996.59 13896.60 19198.64 13092.21 20898.35 2997.67 24994.45 19296.99 19198.79 5594.96 14499.49 18990.39 28099.07 21498.08 269
VPNet97.26 10897.49 8896.59 19299.47 2990.58 23996.27 14698.53 16497.77 4798.46 6998.41 8294.59 15699.68 12594.61 16999.29 18299.52 42
原ACMM196.58 19398.16 18892.12 21298.15 21585.90 32193.49 31496.43 26392.47 21199.38 22787.66 31798.62 26098.23 261
AdaColmapbinary95.11 20994.62 22496.58 19397.33 28194.45 14494.92 23398.08 22393.15 23693.98 29895.53 30294.34 16499.10 27985.69 33398.61 26196.20 339
PCF-MVS89.43 1892.12 29490.64 30896.57 19597.80 22993.48 18289.88 35398.45 17174.46 36796.04 23995.68 29690.71 23999.31 24473.73 36699.01 22196.91 319
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
ambc96.56 19698.23 17891.68 22397.88 6198.13 21898.42 7298.56 7294.22 16899.04 28594.05 19799.35 16498.95 177
casdiffmvs97.50 9197.81 5496.56 19698.51 14891.04 23095.83 17699.09 3697.23 7898.33 8698.30 9497.03 5299.37 23096.58 6699.38 15599.28 115
FMVSNet593.39 27292.35 28396.50 19895.83 32890.81 23697.31 9598.27 19592.74 24896.27 22998.28 9962.23 36999.67 13090.86 26099.36 15999.03 168
CANet95.86 18095.65 18396.49 19996.41 30990.82 23494.36 25298.41 17994.94 17692.62 33596.73 24792.68 20199.71 10095.12 15099.60 7998.94 179
test20.0396.58 15096.61 13796.48 20098.49 15291.72 22295.68 18397.69 24896.81 8898.27 9397.92 14894.18 16998.71 31790.78 26499.66 6399.00 171
UnsupCasMVSNet_eth95.91 17795.73 18196.44 20198.48 15491.52 22595.31 20798.45 17195.76 14197.48 16097.54 18389.53 25798.69 31994.43 17794.61 35099.13 146
baseline97.44 9697.78 5896.43 20298.52 14790.75 23796.84 11999.03 5096.51 9997.86 14298.02 13496.67 7499.36 23297.09 5499.47 12599.19 133
DPM-MVS93.68 26592.77 27696.42 20397.91 21292.54 20091.17 33697.47 26484.99 33493.08 32494.74 31789.90 25199.00 28987.54 32098.09 28197.72 294
PVSNet_Blended_VisFu95.95 17695.80 17896.42 20399.28 4990.62 23895.31 20799.08 3788.40 29896.97 19498.17 11592.11 21799.78 4393.64 21199.21 19198.86 199
ANet_high98.31 2898.94 696.41 20599.33 4589.64 25197.92 5999.56 599.27 699.66 899.50 697.67 2599.83 2897.55 3799.98 299.77 8
SD-MVS97.37 10197.70 6296.35 20698.14 19195.13 12196.54 13498.92 7695.94 13099.19 2898.08 12397.74 2295.06 36895.24 13899.54 9898.87 198
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
Patchmtry95.03 21494.59 22796.33 20794.83 34590.82 23496.38 14197.20 26996.59 9597.49 15798.57 7077.67 32699.38 22792.95 22599.62 6998.80 204
OpenMVScopyleft94.22 895.48 19395.20 19396.32 20897.16 29091.96 21797.74 7098.84 9987.26 30794.36 28598.01 13693.95 17499.67 13090.70 27098.75 24897.35 308
v1097.55 8797.97 4196.31 20998.60 13889.64 25197.44 8999.02 5296.60 9498.72 5099.16 3093.48 18499.72 8698.76 699.92 1499.58 28
PMMVS92.39 28791.08 29996.30 21093.12 36592.81 19790.58 34495.96 30179.17 35891.85 34292.27 34990.29 24798.66 32489.85 28896.68 32797.43 304
bset_n11_16_dypcd94.53 23993.95 25296.25 21197.56 26089.85 24888.52 35991.32 34894.90 17997.51 15496.38 26882.34 30599.78 4397.22 4699.80 3699.12 151
v897.60 8498.06 3896.23 21298.71 12389.44 25597.43 9198.82 11497.29 7798.74 4899.10 3593.86 17599.68 12598.61 1099.94 899.56 35
1112_ss94.12 25393.42 26096.23 21298.59 14090.85 23394.24 25898.85 9485.49 32592.97 32594.94 31386.01 28699.64 14191.78 24197.92 28698.20 264
FMVSNet395.26 20494.94 20496.22 21496.53 30690.06 24395.99 16497.66 25194.11 20597.99 12597.91 14980.22 31699.63 14394.60 17099.44 13398.96 176
114514_t93.96 25893.22 26596.19 21599.06 8990.97 23295.99 16498.94 7473.88 36893.43 31896.93 23392.38 21399.37 23089.09 29899.28 18398.25 260
CHOSEN 1792x268894.10 25493.41 26196.18 21699.16 7190.04 24492.15 31898.68 14479.90 35596.22 23297.83 15787.92 27599.42 20889.18 29799.65 6499.08 160
v119296.83 13197.06 11596.15 21798.28 17089.29 25795.36 20298.77 12193.73 21598.11 11098.34 8793.02 19599.67 13098.35 1499.58 8399.50 45
v114496.84 12897.08 11396.13 21898.42 16089.28 25895.41 19898.67 14794.21 20197.97 12998.31 9093.06 19199.65 13898.06 1999.62 6999.45 69
UnsupCasMVSNet_bld94.72 22894.26 23996.08 21998.62 13590.54 24293.38 29498.05 22990.30 27997.02 18996.80 24389.54 25599.16 27088.44 30796.18 33498.56 229
v14419296.69 14396.90 12596.03 22098.25 17588.92 26295.49 19298.77 12193.05 23898.09 11498.29 9892.51 21099.70 10998.11 1799.56 8999.47 62
v192192096.72 14096.96 12195.99 22198.21 17988.79 26795.42 19698.79 11693.22 23098.19 10298.26 10492.68 20199.70 10998.34 1599.55 9599.49 53
DELS-MVS96.17 16696.23 15995.99 22197.55 26290.04 24492.38 31698.52 16594.13 20496.55 21697.06 22494.99 14399.58 16295.62 11399.28 18398.37 243
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
CANet_DTU94.65 23394.21 24295.96 22395.90 32589.68 25093.92 27697.83 24193.19 23190.12 35295.64 29888.52 26599.57 16893.27 21899.47 12598.62 224
PAPM_NR94.61 23594.17 24495.96 22398.36 16491.23 22795.93 17097.95 23192.98 24193.42 31994.43 32590.53 24098.38 34387.60 31896.29 33398.27 258
v2v48296.78 13597.06 11595.95 22598.57 14288.77 26895.36 20298.26 19795.18 16697.85 14398.23 10792.58 20599.63 14397.80 2799.69 5899.45 69
PMVScopyleft89.60 1796.71 14296.97 11995.95 22599.51 2497.81 1797.42 9297.49 26197.93 4495.95 24298.58 6996.88 6696.91 36289.59 29199.36 15993.12 362
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MSDG95.33 20095.13 19695.94 22797.40 27391.85 21991.02 34098.37 18595.30 16196.31 22795.99 28594.51 16098.38 34389.59 29197.65 30297.60 300
v124096.74 13797.02 11895.91 22898.18 18488.52 27095.39 20098.88 8593.15 23698.46 6998.40 8492.80 19899.71 10098.45 1399.49 11999.49 53
Anonymous2023120695.27 20395.06 20195.88 22998.72 12089.37 25695.70 18097.85 23788.00 30396.98 19397.62 17891.95 22299.34 23789.21 29699.53 10198.94 179
Vis-MVSNet (Re-imp)95.11 20994.85 21095.87 23099.12 8389.17 25997.54 8694.92 31796.50 10096.58 21297.27 21183.64 30199.48 19288.42 30899.67 6198.97 175
CL-MVSNet_self_test95.04 21294.79 21695.82 23197.51 26489.79 24991.14 33796.82 28593.05 23896.72 20696.40 26690.82 23799.16 27091.95 23598.66 25698.50 234
IterMVS-LS96.92 12397.29 9895.79 23298.51 14888.13 28095.10 21998.66 14996.99 8298.46 6998.68 6492.55 20699.74 7596.91 6099.79 3899.50 45
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Anonymous2024052197.07 11497.51 8595.76 23399.35 4388.18 27797.78 6598.40 18197.11 8098.34 8299.04 4089.58 25499.79 3998.09 1899.93 1099.30 107
EI-MVSNet96.63 14796.93 12295.74 23497.26 28488.13 28095.29 20997.65 25396.99 8297.94 13298.19 11292.55 20699.58 16296.91 6099.56 8999.50 45
MDA-MVSNet-bldmvs95.69 18395.67 18295.74 23498.48 15488.76 26992.84 30397.25 26796.00 12697.59 15097.95 14491.38 23199.46 19893.16 22196.35 33298.99 174
sss94.22 24893.72 25695.74 23497.71 24889.95 24693.84 27896.98 27988.38 29993.75 30395.74 29487.94 27198.89 30191.02 25698.10 28098.37 243
testdata95.70 23798.16 18890.58 23997.72 24680.38 35395.62 25697.02 22792.06 22098.98 29389.06 30098.52 26597.54 301
test_yl94.40 24294.00 24995.59 23896.95 29689.52 25394.75 24295.55 31196.18 11696.79 20196.14 28081.09 31199.18 26590.75 26597.77 29098.07 271
DCV-MVSNet94.40 24294.00 24995.59 23896.95 29689.52 25394.75 24295.55 31196.18 11696.79 20196.14 28081.09 31199.18 26590.75 26597.77 29098.07 271
tttt051793.31 27492.56 28195.57 24098.71 12387.86 28497.44 8987.17 36695.79 14097.47 16296.84 23864.12 36799.81 3296.20 7999.32 17699.02 170
MSLP-MVS++96.42 15896.71 13395.57 24097.82 22490.56 24195.71 17998.84 9994.72 18396.71 20797.39 20094.91 14698.10 35495.28 13599.02 21998.05 278
thisisatest053092.71 28391.76 29195.56 24298.42 16088.23 27596.03 16187.35 36594.04 20796.56 21495.47 30364.03 36899.77 5394.78 16599.11 20898.68 220
Test_1112_low_res93.53 27092.86 27095.54 24398.60 13888.86 26592.75 30698.69 14282.66 34492.65 33296.92 23584.75 29499.56 16990.94 25897.76 29298.19 265
pmmvs594.63 23494.34 23895.50 24497.63 25688.34 27494.02 27097.13 27387.15 31095.22 26497.15 21687.50 27799.27 25593.99 19999.26 18698.88 196
MVSFormer96.14 16796.36 15495.49 24597.68 25087.81 28798.67 1399.02 5296.50 10094.48 28396.15 27886.90 28199.92 498.73 799.13 20498.74 212
ET-MVSNet_ETH3D91.12 30489.67 31695.47 24696.41 30989.15 26191.54 32790.23 35989.07 28986.78 36792.84 34269.39 36299.44 20594.16 19096.61 32897.82 290
diffmvs96.04 17196.23 15995.46 24797.35 27588.03 28293.42 29199.08 3794.09 20696.66 20996.93 23393.85 17699.29 25196.01 9198.67 25499.06 164
v14896.58 15096.97 11995.42 24898.63 13487.57 29195.09 22197.90 23495.91 13398.24 9697.96 14093.42 18599.39 22496.04 8799.52 10699.29 114
OpenMVS_ROBcopyleft91.80 1493.64 26793.05 26695.42 24897.31 28391.21 22895.08 22396.68 29181.56 34796.88 20096.41 26490.44 24299.25 25885.39 33797.67 30095.80 344
jason94.39 24494.04 24895.41 25098.29 16887.85 28692.74 30896.75 28885.38 33095.29 26296.15 27888.21 27099.65 13894.24 18799.34 16798.74 212
jason: jason.
API-MVS95.09 21195.01 20395.31 25196.61 30494.02 16096.83 12097.18 27195.60 14995.79 24994.33 32694.54 15998.37 34585.70 33298.52 26593.52 359
PVSNet_BlendedMVS95.02 21594.93 20695.27 25297.79 23587.40 29594.14 26698.68 14488.94 29294.51 28198.01 13693.04 19299.30 24789.77 28999.49 11999.11 155
lupinMVS93.77 26193.28 26295.24 25397.68 25087.81 28792.12 31996.05 29784.52 33794.48 28395.06 31186.90 28199.63 14393.62 21299.13 20498.27 258
D2MVS95.18 20695.17 19595.21 25497.76 24187.76 28994.15 26497.94 23289.77 28596.99 19197.68 17587.45 27899.14 27295.03 15599.81 3398.74 212
CS-MVS95.98 17596.24 15895.20 25597.26 28489.88 24795.84 17599.39 993.89 21294.28 28695.15 30894.81 14799.62 15196.11 8399.40 15196.10 340
Patchmatch-RL test94.66 23294.49 23195.19 25698.54 14588.91 26392.57 31098.74 12791.46 26698.32 8797.75 16677.31 33198.81 30896.06 8499.61 7597.85 288
WTY-MVS93.55 26993.00 26895.19 25697.81 22587.86 28493.89 27796.00 29989.02 29094.07 29395.44 30486.27 28499.33 24087.69 31696.82 32298.39 241
JIA-IIPM91.79 29890.69 30795.11 25893.80 35890.98 23194.16 26391.78 34596.38 10490.30 35199.30 1872.02 35598.90 29988.28 31090.17 36295.45 350
MIMVSNet93.42 27192.86 27095.10 25998.17 18688.19 27698.13 4893.69 32592.07 25595.04 26998.21 11180.95 31399.03 28881.42 35498.06 28298.07 271
PAPR92.22 29191.27 29795.07 26095.73 33288.81 26691.97 32297.87 23685.80 32290.91 34592.73 34591.16 23298.33 34779.48 35795.76 34198.08 269
MVSTER94.21 25093.93 25395.05 26195.83 32886.46 30795.18 21797.65 25392.41 25397.94 13298.00 13872.39 35499.58 16296.36 7599.56 8999.12 151
cl____94.73 22494.64 22195.01 26295.85 32787.00 30191.33 33198.08 22393.34 22597.10 18097.33 20784.01 30099.30 24795.14 14799.56 8998.71 217
DIV-MVS_self_test94.73 22494.64 22195.01 26295.86 32687.00 30191.33 33198.08 22393.34 22597.10 18097.34 20684.02 29999.31 24495.15 14699.55 9598.72 215
TinyColmap96.00 17496.34 15594.96 26497.90 21487.91 28394.13 26798.49 16894.41 19398.16 10497.76 16396.29 9798.68 32290.52 27699.42 14498.30 254
PVSNet_Blended93.96 25893.65 25794.91 26597.79 23587.40 29591.43 32898.68 14484.50 33894.51 28194.48 32493.04 19299.30 24789.77 28998.61 26198.02 281
BH-RMVSNet94.56 23794.44 23694.91 26597.57 25887.44 29493.78 28296.26 29493.69 21796.41 22196.50 26192.10 21899.00 28985.96 33097.71 29698.31 252
RPMNet94.68 23194.60 22594.90 26795.44 33788.15 27896.18 15398.86 9097.43 6894.10 29198.49 7779.40 31799.76 5895.69 10695.81 33796.81 326
HY-MVS91.43 1592.58 28491.81 29094.90 26796.49 30788.87 26497.31 9594.62 31985.92 32090.50 34996.84 23885.05 29199.40 21983.77 34995.78 34096.43 336
GA-MVS92.83 28192.15 28694.87 26996.97 29587.27 29890.03 34896.12 29691.83 26194.05 29494.57 31976.01 33898.97 29792.46 23097.34 31398.36 248
miper_lstm_enhance94.81 22294.80 21594.85 27096.16 31986.45 30891.14 33798.20 20493.49 22097.03 18897.37 20484.97 29399.26 25695.28 13599.56 8998.83 201
IterMVS-SCA-FT95.86 18096.19 16194.85 27097.68 25085.53 31792.42 31497.63 25796.99 8298.36 7998.54 7487.94 27199.75 6597.07 5699.08 21299.27 119
c3_l95.20 20595.32 19194.83 27296.19 31786.43 30991.83 32498.35 19093.47 22197.36 16797.26 21288.69 26499.28 25395.41 13199.36 15998.78 207
testgi96.07 16996.50 15094.80 27399.26 5087.69 29095.96 16798.58 16095.08 17098.02 12496.25 27397.92 1697.60 35988.68 30598.74 24999.11 155
CR-MVSNet93.29 27592.79 27394.78 27495.44 33788.15 27896.18 15397.20 26984.94 33594.10 29198.57 7077.67 32699.39 22495.17 14295.81 33796.81 326
eth_miper_zixun_eth94.89 21894.93 20694.75 27595.99 32486.12 31291.35 33098.49 16893.40 22297.12 17897.25 21386.87 28399.35 23595.08 15298.82 24298.78 207
MVS_Test96.27 16196.79 13194.73 27696.94 29886.63 30696.18 15398.33 19194.94 17696.07 23898.28 9995.25 13599.26 25697.21 4897.90 28898.30 254
miper_ehance_all_eth94.69 22994.70 21894.64 27795.77 33086.22 31191.32 33398.24 19991.67 26297.05 18696.65 25288.39 26899.22 26394.88 15898.34 27198.49 235
Patchmatch-test93.60 26893.25 26494.63 27896.14 32287.47 29396.04 16094.50 32193.57 21896.47 21896.97 23076.50 33498.61 32790.67 27198.41 27097.81 292
baseline193.14 27892.64 27994.62 27997.34 27987.20 29996.67 13293.02 33394.71 18496.51 21795.83 29381.64 30698.60 32990.00 28688.06 36598.07 271
xiu_mvs_v1_base_debu95.62 18695.96 17394.60 28098.01 20288.42 27193.99 27298.21 20192.98 24195.91 24494.53 32196.39 9299.72 8695.43 12898.19 27695.64 346
xiu_mvs_v1_base95.62 18695.96 17394.60 28098.01 20288.42 27193.99 27298.21 20192.98 24195.91 24494.53 32196.39 9299.72 8695.43 12898.19 27695.64 346
xiu_mvs_v1_base_debi95.62 18695.96 17394.60 28098.01 20288.42 27193.99 27298.21 20192.98 24195.91 24494.53 32196.39 9299.72 8695.43 12898.19 27695.64 346
MS-PatchMatch94.83 22094.91 20894.57 28396.81 30287.10 30094.23 25997.34 26688.74 29597.14 17697.11 22091.94 22398.23 35092.99 22397.92 28698.37 243
USDC94.56 23794.57 23094.55 28497.78 23986.43 30992.75 30698.65 15485.96 31996.91 19897.93 14790.82 23798.74 31490.71 26999.59 8198.47 236
BH-untuned94.69 22994.75 21794.52 28597.95 21187.53 29294.07 26997.01 27893.99 20897.10 18095.65 29792.65 20398.95 29887.60 31896.74 32597.09 311
cl2293.25 27692.84 27294.46 28694.30 35186.00 31391.09 33996.64 29290.74 27495.79 24996.31 27178.24 32398.77 31194.15 19198.34 27198.62 224
MDA-MVSNet_test_wron94.73 22494.83 21394.42 28797.48 26585.15 32490.28 34795.87 30392.52 24997.48 16097.76 16391.92 22599.17 26993.32 21596.80 32498.94 179
YYNet194.73 22494.84 21194.41 28897.47 26985.09 32690.29 34695.85 30492.52 24997.53 15297.76 16391.97 22199.18 26593.31 21696.86 32198.95 177
ADS-MVSNet291.47 30290.51 31094.36 28995.51 33585.63 31595.05 22795.70 30583.46 34192.69 33096.84 23879.15 32099.41 21785.66 33490.52 36098.04 279
new_pmnet92.34 28991.69 29294.32 29096.23 31589.16 26092.27 31792.88 33584.39 34095.29 26296.35 27085.66 28896.74 36684.53 34497.56 30497.05 313
MG-MVS94.08 25694.00 24994.32 29097.09 29285.89 31493.19 30095.96 30192.52 24994.93 27297.51 18789.54 25598.77 31187.52 32197.71 29698.31 252
PatchT93.75 26293.57 25894.29 29295.05 34387.32 29796.05 15992.98 33497.54 6594.25 28798.72 6075.79 33999.24 25995.92 9695.81 33796.32 337
miper_enhance_ethall93.14 27892.78 27594.20 29393.65 35985.29 32189.97 34997.85 23785.05 33296.15 23794.56 32085.74 28799.14 27293.74 20798.34 27198.17 267
IterMVS95.42 19795.83 17794.20 29397.52 26383.78 33892.41 31597.47 26495.49 15498.06 11898.49 7787.94 27199.58 16296.02 8999.02 21999.23 127
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
thisisatest051590.43 31089.18 32294.17 29597.07 29385.44 31889.75 35487.58 36488.28 30093.69 30791.72 35565.27 36699.58 16290.59 27398.67 25497.50 303
ECVR-MVScopyleft94.37 24594.48 23294.05 29698.95 9983.10 34098.31 3382.48 37296.20 11398.23 9799.16 3081.18 31099.66 13695.95 9499.83 3199.38 88
thres600view792.03 29591.43 29393.82 29798.19 18184.61 33196.27 14690.39 35696.81 8896.37 22393.11 33473.44 35199.49 18980.32 35697.95 28597.36 306
FPMVS89.92 31788.63 32593.82 29798.37 16396.94 4791.58 32693.34 33188.00 30390.32 35097.10 22170.87 35991.13 37171.91 36996.16 33693.39 361
test111194.53 23994.81 21493.72 29999.06 8981.94 34898.31 3383.87 37196.37 10598.49 6599.17 2981.49 30799.73 8196.64 6299.86 2599.49 53
thres40091.68 30091.00 30093.71 30098.02 20084.35 33495.70 18090.79 35396.26 11095.90 24792.13 35173.62 34899.42 20878.85 36097.74 29397.36 306
IB-MVS85.98 2088.63 32686.95 33593.68 30195.12 34284.82 33090.85 34190.17 36087.55 30688.48 36091.34 35958.01 37199.59 16087.24 32493.80 35496.63 333
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
EU-MVSNet94.25 24794.47 23393.60 30298.14 19182.60 34397.24 10092.72 33885.08 33198.48 6698.94 4682.59 30498.76 31397.47 4099.53 10199.44 79
TR-MVS92.54 28592.20 28593.57 30396.49 30786.66 30593.51 28994.73 31889.96 28394.95 27093.87 33090.24 24898.61 32781.18 35594.88 34795.45 350
cascas91.89 29791.35 29593.51 30494.27 35285.60 31688.86 35898.61 15679.32 35792.16 33991.44 35889.22 26298.12 35390.80 26397.47 31096.82 325
ppachtmachnet_test94.49 24194.84 21193.46 30596.16 31982.10 34590.59 34397.48 26390.53 27797.01 19097.59 18091.01 23499.36 23293.97 20199.18 19798.94 179
pmmvs390.00 31488.90 32493.32 30694.20 35585.34 31991.25 33492.56 34078.59 35993.82 29995.17 30767.36 36598.69 31989.08 29998.03 28395.92 341
EPNet_dtu91.39 30390.75 30693.31 30790.48 37482.61 34294.80 23992.88 33593.39 22381.74 37194.90 31681.36 30999.11 27788.28 31098.87 23598.21 263
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
thres100view90091.76 29991.26 29893.26 30898.21 17984.50 33296.39 13990.39 35696.87 8696.33 22493.08 33873.44 35199.42 20878.85 36097.74 29395.85 342
baseline289.65 32088.44 32793.25 30995.62 33382.71 34193.82 27985.94 36888.89 29387.35 36592.54 34771.23 35799.33 24086.01 32994.60 35197.72 294
DSMNet-mixed92.19 29291.83 28993.25 30996.18 31883.68 33996.27 14693.68 32776.97 36592.54 33699.18 2789.20 26398.55 33383.88 34798.60 26397.51 302
tfpn200view991.55 30191.00 30093.21 31198.02 20084.35 33495.70 18090.79 35396.26 11095.90 24792.13 35173.62 34899.42 20878.85 36097.74 29395.85 342
mvs_anonymous95.36 19996.07 16893.21 31196.29 31181.56 34994.60 24697.66 25193.30 22796.95 19598.91 4993.03 19499.38 22796.60 6497.30 31598.69 218
our_test_394.20 25294.58 22893.07 31396.16 31981.20 35190.42 34596.84 28390.72 27597.14 17697.13 21790.47 24199.11 27794.04 19898.25 27598.91 188
ADS-MVSNet90.95 30890.26 31293.04 31495.51 33582.37 34495.05 22793.41 33083.46 34192.69 33096.84 23879.15 32098.70 31885.66 33490.52 36098.04 279
PAPM87.64 33485.84 33993.04 31496.54 30584.99 32788.42 36095.57 31079.52 35683.82 36893.05 34080.57 31498.41 34062.29 37292.79 35695.71 345
PS-MVSNAJ94.10 25494.47 23393.00 31697.35 27584.88 32891.86 32397.84 23991.96 25894.17 28992.50 34895.82 10899.71 10091.27 25097.48 30894.40 356
xiu_mvs_v2_base94.22 24894.63 22392.99 31797.32 28284.84 32992.12 31997.84 23991.96 25894.17 28993.43 33296.07 10099.71 10091.27 25097.48 30894.42 355
SCA93.38 27393.52 25992.96 31896.24 31381.40 35093.24 29894.00 32491.58 26594.57 27896.97 23087.94 27199.42 20889.47 29397.66 30198.06 275
new-patchmatchnet95.67 18596.58 14092.94 31997.48 26580.21 35492.96 30298.19 20994.83 18098.82 4398.79 5593.31 18799.51 18695.83 10299.04 21899.12 151
test0.0.03 190.11 31289.21 31992.83 32093.89 35786.87 30491.74 32588.74 36392.02 25694.71 27591.14 36173.92 34594.48 36983.75 35092.94 35597.16 310
thres20091.00 30790.42 31192.77 32197.47 26983.98 33794.01 27191.18 35195.12 16995.44 25991.21 36073.93 34499.31 24477.76 36397.63 30395.01 352
BH-w/o92.14 29391.94 28792.73 32297.13 29185.30 32092.46 31395.64 30689.33 28894.21 28892.74 34489.60 25398.24 34981.68 35394.66 34994.66 354
131492.38 28892.30 28492.64 32395.42 33985.15 32495.86 17296.97 28085.40 32990.62 34693.06 33991.12 23397.80 35786.74 32695.49 34494.97 353
KD-MVS_2432*160088.93 32487.74 32992.49 32488.04 37581.99 34689.63 35595.62 30791.35 26795.06 26693.11 33456.58 37498.63 32585.19 33895.07 34596.85 322
miper_refine_blended88.93 32487.74 32992.49 32488.04 37581.99 34689.63 35595.62 30791.35 26795.06 26693.11 33456.58 37498.63 32585.19 33895.07 34596.85 322
MVS90.02 31389.20 32092.47 32694.71 34686.90 30395.86 17296.74 28964.72 37090.62 34692.77 34392.54 20898.39 34279.30 35895.56 34392.12 363
PMMVS293.66 26694.07 24692.45 32797.57 25880.67 35386.46 36296.00 29993.99 20897.10 18097.38 20289.90 25197.82 35688.76 30299.47 12598.86 199
CHOSEN 280x42089.98 31589.19 32192.37 32895.60 33481.13 35286.22 36397.09 27581.44 34987.44 36493.15 33373.99 34399.47 19588.69 30499.07 21496.52 335
PatchmatchNetpermissive91.98 29691.87 28892.30 32994.60 34879.71 35595.12 21893.59 32989.52 28693.61 31097.02 22777.94 32499.18 26590.84 26194.57 35298.01 282
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
RRT_test8_iter0592.46 28692.52 28292.29 33095.33 34077.43 36295.73 17898.55 16394.41 19397.46 16397.72 17157.44 37299.74 7596.92 5999.14 20099.69 20
gg-mvs-nofinetune88.28 32986.96 33492.23 33192.84 36884.44 33398.19 4574.60 37599.08 1087.01 36699.47 856.93 37398.23 35078.91 35995.61 34294.01 357
test250689.86 31889.16 32391.97 33298.95 9976.83 36598.54 2061.07 37996.20 11397.07 18599.16 3055.19 37899.69 11796.43 7399.83 3199.38 88
tpm91.08 30690.85 30491.75 33395.33 34078.09 35895.03 22991.27 35088.75 29493.53 31397.40 19671.24 35699.30 24791.25 25293.87 35397.87 287
PVSNet86.72 1991.10 30590.97 30291.49 33497.56 26078.04 35987.17 36194.60 32084.65 33692.34 33792.20 35087.37 27998.47 33785.17 34097.69 29897.96 283
DWT-MVSNet_test87.92 33286.77 33691.39 33593.18 36278.62 35795.10 21991.42 34785.58 32488.00 36188.73 36760.60 37098.90 29990.60 27287.70 36696.65 330
EPMVS89.26 32288.55 32691.39 33592.36 37079.11 35695.65 18779.86 37388.60 29693.12 32396.53 25870.73 36098.10 35490.75 26589.32 36496.98 315
CostFormer89.75 31989.25 31791.26 33794.69 34778.00 36095.32 20691.98 34381.50 34890.55 34896.96 23271.06 35898.89 30188.59 30692.63 35796.87 320
CVMVSNet92.33 29092.79 27390.95 33897.26 28475.84 36895.29 20992.33 34181.86 34596.27 22998.19 11281.44 30898.46 33894.23 18898.29 27498.55 231
tpm288.47 32787.69 33190.79 33994.98 34477.34 36395.09 22191.83 34477.51 36489.40 35596.41 26467.83 36498.73 31583.58 35192.60 35896.29 338
GG-mvs-BLEND90.60 34091.00 37284.21 33698.23 3972.63 37882.76 36984.11 37056.14 37696.79 36472.20 36892.09 35990.78 367
tpmvs90.79 30990.87 30390.57 34192.75 36976.30 36695.79 17793.64 32891.04 27391.91 34196.26 27277.19 33298.86 30589.38 29589.85 36396.56 334
test-LLR89.97 31689.90 31490.16 34294.24 35374.98 36989.89 35089.06 36192.02 25689.97 35390.77 36373.92 34598.57 33091.88 23897.36 31196.92 317
test-mter87.92 33287.17 33390.16 34294.24 35374.98 36989.89 35089.06 36186.44 31689.97 35390.77 36354.96 37998.57 33091.88 23897.36 31196.92 317
tpm cat188.01 33187.33 33290.05 34494.48 34976.28 36794.47 25194.35 32373.84 36989.26 35695.61 30073.64 34798.30 34884.13 34586.20 36895.57 349
tpmrst90.31 31190.61 30989.41 34594.06 35672.37 37495.06 22693.69 32588.01 30292.32 33896.86 23677.45 32898.82 30691.04 25587.01 36797.04 314
TESTMET0.1,187.20 33586.57 33789.07 34693.62 36072.84 37389.89 35087.01 36785.46 32789.12 35890.20 36556.00 37797.72 35890.91 25996.92 31896.64 331
E-PMN89.52 32189.78 31588.73 34793.14 36477.61 36183.26 36692.02 34294.82 18193.71 30593.11 33475.31 34096.81 36385.81 33196.81 32391.77 365
EMVS89.06 32389.22 31888.61 34893.00 36677.34 36382.91 36790.92 35294.64 18692.63 33491.81 35476.30 33697.02 36183.83 34896.90 32091.48 366
PVSNet_081.89 2184.49 33783.21 34088.34 34995.76 33174.97 37183.49 36592.70 33978.47 36087.94 36286.90 36983.38 30296.63 36773.44 36766.86 37393.40 360
MVEpermissive73.61 2286.48 33685.92 33888.18 35096.23 31585.28 32281.78 36875.79 37486.01 31882.53 37091.88 35392.74 19987.47 37371.42 37094.86 34891.78 364
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
dp88.08 33088.05 32888.16 35192.85 36768.81 37694.17 26292.88 33585.47 32691.38 34496.14 28068.87 36398.81 30886.88 32583.80 37096.87 320
wuyk23d93.25 27695.20 19387.40 35296.07 32395.38 10497.04 11294.97 31695.33 15999.70 598.11 12198.14 1391.94 37077.76 36399.68 6074.89 370
MVS-HIRNet88.40 32890.20 31382.99 35397.01 29460.04 37793.11 30185.61 36984.45 33988.72 35999.09 3684.72 29598.23 35082.52 35296.59 32990.69 368
DeepMVS_CXcopyleft77.17 35490.94 37385.28 32274.08 37752.51 37180.87 37288.03 36875.25 34170.63 37459.23 37384.94 36975.62 369
test_method66.88 33966.13 34269.11 35562.68 37825.73 38049.76 36996.04 29814.32 37364.27 37491.69 35673.45 35088.05 37276.06 36566.94 37293.54 358
tmp_tt57.23 34062.50 34341.44 35634.77 37949.21 37983.93 36460.22 38015.31 37271.11 37379.37 37170.09 36144.86 37564.76 37182.93 37130.25 371
test12312.59 34215.49 3453.87 3576.07 3802.55 38190.75 3422.59 3822.52 3755.20 37713.02 3744.96 3801.85 3775.20 3749.09 3747.23 372
testmvs12.33 34315.23 3463.64 3585.77 3812.23 38288.99 3573.62 3812.30 3765.29 37613.09 3734.52 3811.95 3765.16 3758.32 3756.75 373
test_blank0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uanet_test0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
cdsmvs_eth3d_5k24.22 34132.30 3440.00 3590.00 3820.00 3830.00 37098.10 2200.00 3770.00 37895.06 31197.54 290.00 3780.00 3760.00 3760.00 374
pcd_1.5k_mvsjas7.98 34410.65 3470.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 37795.82 1080.00 3780.00 3760.00 3760.00 374
sosnet-low-res0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
sosnet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
uncertanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
Regformer0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
ab-mvs-re7.91 34510.55 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 37894.94 3130.00 3820.00 3780.00 3760.00 3760.00 374
uanet0.00 3460.00 3490.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 3780.00 3770.00 3820.00 3780.00 3760.00 3760.00 374
FOURS199.59 1498.20 499.03 799.25 1298.96 1898.87 40
PC_three_145287.24 30898.37 7697.44 19397.00 5496.78 36592.01 23399.25 18799.21 129
test_one_060199.05 9395.50 9998.87 8797.21 7998.03 12298.30 9496.93 60
eth-test20.00 382
eth-test0.00 382
ZD-MVS98.43 15995.94 7998.56 16290.72 27596.66 20997.07 22395.02 14299.74 7591.08 25498.93 229
RE-MVS-def97.88 4998.81 10998.05 997.55 8198.86 9097.77 4798.20 9998.07 12596.94 5895.49 11899.20 19299.26 120
IU-MVS99.22 5995.40 10298.14 21685.77 32398.36 7995.23 13999.51 11199.49 53
test_241102_TWO98.83 10696.11 11898.62 5298.24 10596.92 6299.72 8695.44 12599.49 11999.49 53
test_241102_ONE99.22 5995.35 10798.83 10696.04 12399.08 3198.13 11797.87 2099.33 240
9.1496.69 13498.53 14696.02 16298.98 6693.23 22997.18 17497.46 19196.47 8899.62 15192.99 22399.32 176
save fliter98.48 15494.71 13394.53 24998.41 17995.02 174
test_0728_THIRD96.62 9298.40 7398.28 9997.10 4599.71 10095.70 10499.62 6999.58 28
test072699.24 5495.51 9696.89 11898.89 7995.92 13198.64 5198.31 9097.06 50
GSMVS98.06 275
test_part299.03 9596.07 7498.08 116
sam_mvs177.80 32598.06 275
sam_mvs77.38 329
MTGPAbinary98.73 129
test_post194.98 23110.37 37676.21 33799.04 28589.47 293
test_post10.87 37576.83 33399.07 282
patchmatchnet-post96.84 23877.36 33099.42 208
MTMP96.55 13374.60 375
gm-plane-assit91.79 37171.40 37581.67 34690.11 36698.99 29184.86 342
test9_res91.29 24998.89 23499.00 171
TEST997.84 22195.23 11493.62 28598.39 18286.81 31393.78 30095.99 28594.68 15299.52 182
test_897.81 22595.07 12393.54 28898.38 18487.04 31193.71 30595.96 28994.58 15799.52 182
agg_prior290.34 28298.90 23199.10 159
agg_prior97.80 22994.96 12598.36 18693.49 31499.53 178
test_prior495.38 10493.61 287
test_prior293.33 29694.21 20194.02 29596.25 27393.64 18191.90 23698.96 223
旧先验293.35 29577.95 36395.77 25398.67 32390.74 268
新几何293.43 290
旧先验197.80 22993.87 16597.75 24497.04 22693.57 18398.68 25398.72 215
无先验93.20 29997.91 23380.78 35199.40 21987.71 31497.94 284
原ACMM292.82 304
test22298.17 18693.24 18792.74 30897.61 25975.17 36694.65 27796.69 25090.96 23698.66 25697.66 297
testdata299.46 19887.84 313
segment_acmp95.34 131
testdata192.77 30593.78 214
plane_prior798.70 12594.67 137
plane_prior698.38 16294.37 14791.91 226
plane_prior598.75 12599.46 19892.59 22899.20 19299.28 115
plane_prior496.77 244
plane_prior394.51 14195.29 16296.16 235
plane_prior296.50 13596.36 106
plane_prior198.49 152
plane_prior94.29 14995.42 19694.31 19898.93 229
n20.00 383
nn0.00 383
door-mid98.17 210
test1198.08 223
door97.81 242
HQP5-MVS92.47 202
HQP-NCC97.85 21794.26 25493.18 23292.86 327
ACMP_Plane97.85 21794.26 25493.18 23292.86 327
BP-MVS90.51 277
HQP4-MVS92.87 32699.23 26199.06 164
HQP3-MVS98.43 17498.74 249
HQP2-MVS90.33 243
NP-MVS98.14 19193.72 17395.08 309
MDTV_nov1_ep13_2view57.28 37894.89 23480.59 35294.02 29578.66 32285.50 33697.82 290
MDTV_nov1_ep1391.28 29694.31 35073.51 37294.80 23993.16 33286.75 31593.45 31797.40 19676.37 33598.55 33388.85 30196.43 330
ACMMP++_ref99.52 106
ACMMP++99.55 95
Test By Simon94.51 160