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
SED-MVS99.09 198.91 199.63 499.71 2199.24 599.02 7398.87 5897.65 1099.73 199.48 897.53 799.94 498.43 2699.81 1299.70 54
DVP-MVS++99.08 298.89 299.64 399.17 10399.23 799.69 198.88 5197.32 3399.53 999.47 1097.81 399.94 498.47 2299.72 5499.74 37
DVP-MVScopyleft99.03 398.83 599.63 499.72 1399.25 298.97 8398.58 15397.62 1299.45 1199.46 1397.42 999.94 498.47 2299.81 1299.69 57
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
APDe-MVS99.02 498.84 499.55 999.57 3598.96 1699.39 1398.93 3997.38 3099.41 1399.54 196.66 1799.84 5798.86 499.85 599.87 1
DPE-MVScopyleft98.92 598.67 899.65 299.58 3499.20 998.42 18698.91 4597.58 1599.54 899.46 1397.10 1299.94 497.64 7399.84 1099.83 7
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
SteuartSystems-ACMMP98.90 698.75 699.36 2499.22 9898.43 3899.10 5798.87 5897.38 3099.35 1799.40 1797.78 599.87 4897.77 6299.85 599.78 16
Skip Steuart: Steuart Systems R&D Blog.
TSAR-MVS + MP.98.78 798.62 999.24 4399.69 2698.28 5399.14 4798.66 13696.84 6299.56 699.31 3996.34 2399.70 11998.32 3399.73 4799.73 42
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
CNVR-MVS98.78 798.56 1299.45 1799.32 7298.87 1998.47 17898.81 8097.72 798.76 6199.16 6897.05 1399.78 10098.06 4199.66 6399.69 57
MSP-MVS98.74 998.55 1399.29 3499.75 498.23 5499.26 2798.88 5197.52 1799.41 1398.78 12496.00 3899.79 9697.79 6199.59 7799.85 4
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
xxxxxxxxxxxxxcwj98.70 1098.50 1799.30 3399.46 5598.38 4098.21 21298.52 16497.95 399.32 1899.39 1896.22 2499.84 5797.72 6599.73 4799.67 67
XVS98.70 1098.49 2099.34 2699.70 2498.35 4899.29 2398.88 5197.40 2798.46 7999.20 5995.90 4499.89 3997.85 5699.74 4599.78 16
Regformer-298.69 1298.52 1599.19 4699.35 6498.01 6798.37 19098.81 8097.48 2099.21 2599.21 5596.13 3199.80 8498.40 3099.73 4799.75 32
Regformer-198.66 1398.51 1699.12 6099.35 6497.81 7998.37 19098.76 10397.49 1999.20 2699.21 5596.08 3399.79 9698.42 2899.73 4799.75 32
MCST-MVS98.65 1498.37 2699.48 1399.60 3398.87 1998.41 18798.68 12597.04 5498.52 7898.80 12296.78 1699.83 6097.93 4899.61 7399.74 37
Regformer-498.64 1598.53 1498.99 6699.43 6197.37 9298.40 18898.79 9697.46 2399.09 3699.31 3995.86 4699.80 8498.64 899.76 3699.79 13
SD-MVS98.64 1598.68 798.53 9499.33 6998.36 4798.90 9398.85 6897.28 3699.72 399.39 1896.63 1997.60 33598.17 3699.85 599.64 76
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 1798.40 2399.32 3199.72 1398.29 5199.23 3098.96 3396.10 9698.94 4599.17 6396.06 3499.92 2597.62 7499.78 2799.75 32
ACMMP_NAP98.61 1898.30 3999.55 999.62 3298.95 1798.82 11398.81 8095.80 10899.16 3299.47 1095.37 6399.92 2597.89 5299.75 4299.79 13
region2R98.61 1898.38 2599.29 3499.74 898.16 6099.23 3098.93 3996.15 9198.94 4599.17 6395.91 4399.94 497.55 8299.79 2399.78 16
NCCC98.61 1898.35 2999.38 2099.28 8698.61 2998.45 17998.76 10397.82 698.45 8298.93 10796.65 1899.83 6097.38 9099.41 10699.71 50
SF-MVS98.59 2198.32 3899.41 1999.54 3898.71 2299.04 6698.81 8095.12 14499.32 1899.39 1896.22 2499.84 5797.72 6599.73 4799.67 67
Regformer-398.59 2198.50 1798.86 7699.43 6197.05 10598.40 18898.68 12597.43 2699.06 3799.31 3995.80 4799.77 10598.62 1099.76 3699.78 16
ACMMPR98.59 2198.36 2799.29 3499.74 898.15 6199.23 3098.95 3596.10 9698.93 5099.19 6295.70 5099.94 497.62 7499.79 2399.78 16
SMA-MVScopyleft98.58 2498.25 4399.56 899.51 4399.04 1598.95 8798.80 9193.67 21399.37 1699.52 396.52 2199.89 3998.06 4199.81 1299.76 30
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
MTAPA98.58 2498.29 4099.46 1599.76 298.64 2798.90 9398.74 10897.27 4098.02 10499.39 1894.81 8499.96 297.91 4999.79 2399.77 23
HPM-MVS++copyleft98.58 2498.25 4399.55 999.50 4599.08 1198.72 13798.66 13697.51 1898.15 9398.83 11995.70 5099.92 2597.53 8499.67 6099.66 71
SR-MVS98.57 2798.35 2999.24 4399.53 3998.18 5899.09 5898.82 7496.58 7499.10 3599.32 3795.39 6199.82 6897.70 7099.63 7099.72 46
CP-MVS98.57 2798.36 2799.19 4699.66 2897.86 7399.34 1998.87 5895.96 10198.60 7599.13 7396.05 3699.94 497.77 6299.86 199.77 23
test117298.56 2998.35 2999.16 5399.53 3997.94 7199.09 5898.83 7296.52 7799.05 3899.34 3595.34 6599.82 6897.86 5599.64 6899.73 42
MSLP-MVS++98.56 2998.57 1198.55 9099.26 8996.80 11598.71 13899.05 2597.28 3698.84 5599.28 4496.47 2299.40 16398.52 2099.70 5799.47 107
zzz-MVS98.55 3198.25 4399.46 1599.76 298.64 2798.55 16898.74 10897.27 4098.02 10499.39 1894.81 8499.96 297.91 4999.79 2399.77 23
DeepC-MVS_fast96.70 198.55 3198.34 3399.18 5099.25 9098.04 6598.50 17598.78 9997.72 798.92 5199.28 4495.27 7099.82 6897.55 8299.77 3099.69 57
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
SR-MVS-dyc-post98.54 3398.35 2999.13 5799.49 4997.86 7399.11 5498.80 9196.49 7899.17 3099.35 3295.34 6599.82 6897.72 6599.65 6499.71 50
#test#98.54 3398.27 4199.32 3199.72 1398.29 5198.98 8298.96 3395.65 11798.94 4599.17 6396.06 3499.92 2597.21 9699.78 2799.75 32
APD-MVS_3200maxsize98.53 3598.33 3799.15 5699.50 4597.92 7299.15 4598.81 8096.24 8899.20 2699.37 2695.30 6899.80 8497.73 6499.67 6099.72 46
mPP-MVS98.51 3698.26 4299.25 4299.75 498.04 6599.28 2598.81 8096.24 8898.35 8999.23 5295.46 5799.94 497.42 8899.81 1299.77 23
ZNCC-MVS98.49 3798.20 4999.35 2599.73 1298.39 3999.19 4198.86 6495.77 10998.31 9299.10 7895.46 5799.93 1997.57 8099.81 1299.74 37
CS-MVS-test98.49 3798.50 1798.46 10199.20 10197.05 10599.64 498.50 17297.45 2598.88 5399.14 7295.25 7299.15 18498.83 599.56 8699.20 139
PGM-MVS98.49 3798.23 4799.27 4199.72 1398.08 6498.99 7999.49 595.43 12699.03 3999.32 3795.56 5399.94 496.80 12299.77 3099.78 16
EI-MVSNet-Vis-set98.47 4098.39 2498.69 8199.46 5596.49 13298.30 20398.69 12297.21 4398.84 5599.36 3095.41 6099.78 10098.62 1099.65 6499.80 12
MVS_111021_HR98.47 4098.34 3398.88 7599.22 9897.32 9397.91 24899.58 397.20 4498.33 9099.00 9595.99 3999.64 13098.05 4399.76 3699.69 57
CS-MVS98.44 4298.49 2098.31 11299.08 11396.73 11999.67 398.47 17897.17 4698.94 4599.10 7895.73 4999.13 18798.71 799.49 9699.09 157
GST-MVS98.43 4398.12 5299.34 2699.72 1398.38 4099.09 5898.82 7495.71 11298.73 6499.06 8895.27 7099.93 1997.07 10099.63 7099.72 46
EI-MVSNet-UG-set98.41 4498.34 3398.61 8699.45 5996.32 14198.28 20698.68 12597.17 4698.74 6299.37 2695.25 7299.79 9698.57 1299.54 9199.73 42
DELS-MVS98.40 4598.20 4998.99 6699.00 12197.66 8197.75 26498.89 4897.71 998.33 9098.97 9794.97 8199.88 4798.42 2899.76 3699.42 117
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 4698.24 4698.81 7799.22 9897.25 10098.11 23198.29 21397.19 4598.99 4499.02 9096.22 2499.67 12698.52 2098.56 14699.51 98
HPM-MVS_fast98.38 4698.13 5199.12 6099.75 497.86 7399.44 1298.82 7494.46 17598.94 4599.20 5995.16 7699.74 11197.58 7799.85 599.77 23
patch_mono-298.36 4898.87 396.82 21099.53 3990.68 31498.64 15399.29 897.88 599.19 2999.52 396.80 1599.97 199.11 199.86 199.82 10
HPM-MVScopyleft98.36 4898.10 5499.13 5799.74 897.82 7799.53 898.80 9194.63 16898.61 7498.97 9795.13 7799.77 10597.65 7299.83 1199.79 13
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
ETH3D-3000-0.198.35 5098.00 5999.38 2099.47 5298.68 2598.67 14898.84 6994.66 16799.11 3499.25 5095.46 5799.81 7596.80 12299.73 4799.63 79
APD-MVScopyleft98.35 5098.00 5999.42 1899.51 4398.72 2198.80 12098.82 7494.52 17299.23 2499.25 5095.54 5599.80 8496.52 13299.77 3099.74 37
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MVS_111021_LR98.34 5298.23 4798.67 8399.27 8796.90 11297.95 24499.58 397.14 4998.44 8399.01 9495.03 8099.62 13597.91 4999.75 4299.50 100
PHI-MVS98.34 5298.06 5599.18 5099.15 10998.12 6399.04 6699.09 2193.32 22698.83 5799.10 7896.54 2099.83 6097.70 7099.76 3699.59 87
testtj98.33 5497.95 6199.47 1499.49 4998.70 2398.83 11098.86 6495.48 12398.91 5299.17 6395.48 5699.93 1995.80 15799.53 9299.76 30
MP-MVScopyleft98.33 5498.01 5899.28 3899.75 498.18 5899.22 3498.79 9696.13 9397.92 11799.23 5294.54 9099.94 496.74 12699.78 2799.73 42
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
MP-MVS-pluss98.31 5697.92 6399.49 1299.72 1398.88 1898.43 18498.78 9994.10 18397.69 12999.42 1695.25 7299.92 2598.09 4099.80 1999.67 67
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
abl_698.30 5798.03 5799.13 5799.56 3797.76 8099.13 5098.82 7496.14 9299.26 2299.37 2693.33 10999.93 1996.96 10599.67 6099.69 57
ACMMPcopyleft98.23 5897.95 6199.09 6299.74 897.62 8499.03 6999.41 695.98 9997.60 13799.36 3094.45 9599.93 1997.14 9798.85 13399.70 54
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 5997.90 6499.19 4699.31 7498.22 5597.80 26098.84 6996.12 9497.89 11998.69 13495.96 4099.70 11996.89 11199.60 7499.65 73
DROMVSNet98.21 6098.11 5398.49 9898.34 17697.26 9999.61 598.43 18696.78 6598.87 5498.84 11793.72 10699.01 20798.91 399.50 9599.19 143
dcpmvs_298.08 6198.59 1096.56 23499.57 3590.34 32099.15 4598.38 19596.82 6499.29 2099.49 795.78 4899.57 13998.94 299.86 199.77 23
CANet98.05 6297.76 6798.90 7498.73 14297.27 9598.35 19398.78 9997.37 3297.72 12798.96 10391.53 14599.92 2598.79 699.65 6499.51 98
train_agg97.97 6397.52 7799.33 3099.31 7498.50 3497.92 24698.73 11292.98 23997.74 12598.68 13696.20 2799.80 8496.59 12899.57 8199.68 63
ETH3D cwj APD-0.1697.96 6497.52 7799.29 3499.05 11498.52 3298.33 19598.68 12593.18 23198.68 6699.13 7394.62 8899.83 6096.45 13499.55 9099.52 94
ETV-MVS97.96 6497.81 6598.40 10798.42 16797.27 9598.73 13398.55 15896.84 6298.38 8697.44 25495.39 6199.35 16697.62 7498.89 12998.58 196
UA-Net97.96 6497.62 7098.98 6898.86 13397.47 8998.89 9799.08 2296.67 7198.72 6599.54 193.15 11299.81 7594.87 18398.83 13499.65 73
agg_prior197.95 6797.51 7999.28 3899.30 7998.38 4097.81 25998.72 11493.16 23397.57 13898.66 13996.14 3099.81 7596.63 12799.56 8699.66 71
CDPH-MVS97.94 6897.49 8099.28 3899.47 5298.44 3697.91 24898.67 13392.57 25398.77 6098.85 11595.93 4299.72 11395.56 16799.69 5899.68 63
DeepPCF-MVS96.37 297.93 6998.48 2296.30 25999.00 12189.54 33097.43 28298.87 5898.16 299.26 2299.38 2596.12 3299.64 13098.30 3499.77 3099.72 46
DeepC-MVS95.98 397.88 7097.58 7298.77 7899.25 9096.93 11098.83 11098.75 10696.96 5896.89 16199.50 590.46 16799.87 4897.84 5899.76 3699.52 94
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 7197.46 8299.06 6499.53 3998.35 4898.33 19598.89 4892.62 25098.05 9998.94 10695.34 6599.65 12896.04 14899.42 10599.19 143
CSCG97.85 7297.74 6898.20 12099.67 2795.16 19399.22 3499.32 793.04 23797.02 15498.92 10995.36 6499.91 3497.43 8799.64 6899.52 94
MG-MVS97.81 7397.60 7198.44 10399.12 11195.97 15797.75 26498.78 9996.89 6198.46 7999.22 5493.90 10599.68 12594.81 18799.52 9499.67 67
VNet97.79 7497.40 8698.96 7098.88 13197.55 8698.63 15598.93 3996.74 6899.02 4098.84 11790.33 17099.83 6098.53 1496.66 19899.50 100
EIA-MVS97.75 7597.58 7298.27 11498.38 16996.44 13499.01 7598.60 14695.88 10597.26 14397.53 24894.97 8199.33 16897.38 9099.20 11699.05 163
PS-MVSNAJ97.73 7697.77 6697.62 16298.68 15095.58 17697.34 29198.51 16797.29 3598.66 7197.88 21794.51 9199.90 3797.87 5499.17 11897.39 230
CPTT-MVS97.72 7797.32 8998.92 7299.64 3097.10 10499.12 5298.81 8092.34 26198.09 9799.08 8693.01 11399.92 2596.06 14799.77 3099.75 32
PVSNet_Blended_VisFu97.70 7897.46 8298.44 10399.27 8795.91 16598.63 15599.16 1894.48 17497.67 13098.88 11292.80 11599.91 3497.11 9899.12 11999.50 100
canonicalmvs97.67 7997.23 9298.98 6898.70 14798.38 4099.34 1998.39 19296.76 6797.67 13097.40 25792.26 12399.49 15398.28 3596.28 21499.08 161
xiu_mvs_v2_base97.66 8097.70 6997.56 16698.61 15695.46 18297.44 28098.46 17997.15 4898.65 7298.15 19494.33 9799.80 8497.84 5898.66 14297.41 228
baseline97.64 8197.44 8498.25 11798.35 17196.20 14599.00 7798.32 20396.33 8798.03 10299.17 6391.35 14899.16 18198.10 3998.29 16099.39 118
casdiffmvs97.63 8297.41 8598.28 11398.33 17896.14 14898.82 11398.32 20396.38 8597.95 11299.21 5591.23 15299.23 17598.12 3898.37 15599.48 105
xiu_mvs_v1_base_debu97.60 8397.56 7497.72 15298.35 17195.98 15297.86 25598.51 16797.13 5099.01 4198.40 16891.56 14199.80 8498.53 1498.68 13897.37 232
xiu_mvs_v1_base97.60 8397.56 7497.72 15298.35 17195.98 15297.86 25598.51 16797.13 5099.01 4198.40 16891.56 14199.80 8498.53 1498.68 13897.37 232
xiu_mvs_v1_base_debi97.60 8397.56 7497.72 15298.35 17195.98 15297.86 25598.51 16797.13 5099.01 4198.40 16891.56 14199.80 8498.53 1498.68 13897.37 232
ETH3 D test640097.59 8697.01 10199.34 2699.40 6398.56 3098.20 21598.81 8091.63 28498.44 8398.85 11593.98 10499.82 6894.11 21199.69 5899.64 76
diffmvs97.58 8797.40 8698.13 12598.32 18095.81 17098.06 23498.37 19696.20 9098.74 6298.89 11191.31 15099.25 17298.16 3798.52 14799.34 121
MVSFormer97.57 8897.49 8097.84 14198.07 19995.76 17199.47 998.40 19094.98 15298.79 5898.83 11992.34 12098.41 28296.91 10799.59 7799.34 121
alignmvs97.56 8997.07 9999.01 6598.66 15198.37 4698.83 11098.06 25896.74 6898.00 11097.65 23790.80 16199.48 15798.37 3196.56 20299.19 143
DPM-MVS97.55 9096.99 10399.23 4599.04 11698.55 3197.17 30498.35 19994.85 15997.93 11698.58 14995.07 7999.71 11892.60 25399.34 11199.43 115
OMC-MVS97.55 9097.34 8898.20 12099.33 6995.92 16498.28 20698.59 14895.52 12297.97 11199.10 7893.28 11199.49 15395.09 18098.88 13099.19 143
PAPM_NR97.46 9297.11 9698.50 9699.50 4596.41 13798.63 15598.60 14695.18 14197.06 15298.06 20094.26 9999.57 13993.80 22098.87 13299.52 94
EPP-MVSNet97.46 9297.28 9097.99 13498.64 15395.38 18599.33 2298.31 20593.61 21697.19 14599.07 8794.05 10199.23 17596.89 11198.43 15499.37 120
3Dnovator94.51 597.46 9296.93 10599.07 6397.78 21697.64 8299.35 1899.06 2397.02 5593.75 26499.16 6889.25 18999.92 2597.22 9599.75 4299.64 76
CNLPA97.45 9597.03 10098.73 7999.05 11497.44 9198.07 23398.53 16295.32 13496.80 16698.53 15393.32 11099.72 11394.31 20499.31 11399.02 165
lupinMVS97.44 9697.22 9398.12 12798.07 19995.76 17197.68 26897.76 27894.50 17398.79 5898.61 14492.34 12099.30 16997.58 7799.59 7799.31 127
3Dnovator+94.38 697.43 9796.78 11299.38 2097.83 21498.52 3299.37 1598.71 11897.09 5392.99 28999.13 7389.36 18599.89 3996.97 10399.57 8199.71 50
Vis-MVSNetpermissive97.42 9897.11 9698.34 11098.66 15196.23 14499.22 3499.00 2896.63 7398.04 10199.21 5588.05 22399.35 16696.01 15099.21 11599.45 113
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
API-MVS97.41 9997.25 9197.91 13898.70 14796.80 11598.82 11398.69 12294.53 17098.11 9598.28 18394.50 9499.57 13994.12 21099.49 9697.37 232
sss97.39 10096.98 10498.61 8698.60 15796.61 12498.22 21198.93 3993.97 19198.01 10898.48 15891.98 13399.85 5496.45 13498.15 16299.39 118
PVSNet_Blended97.38 10197.12 9598.14 12399.25 9095.35 18897.28 29699.26 993.13 23497.94 11498.21 19092.74 11699.81 7596.88 11499.40 10899.27 134
112197.37 10296.77 11699.16 5399.34 6697.99 7098.19 21998.68 12590.14 32098.01 10898.97 9794.80 8699.87 4893.36 23299.46 10299.61 82
WTY-MVS97.37 10296.92 10698.72 8098.86 13396.89 11498.31 20198.71 11895.26 13797.67 13098.56 15292.21 12699.78 10095.89 15296.85 19399.48 105
jason97.32 10497.08 9898.06 13197.45 24495.59 17597.87 25497.91 27394.79 16098.55 7798.83 11991.12 15399.23 17597.58 7799.60 7499.34 121
jason: jason.
MVS_Test97.28 10597.00 10298.13 12598.33 17895.97 15798.74 12998.07 25394.27 17998.44 8398.07 19992.48 11899.26 17196.43 13698.19 16199.16 149
EPNet97.28 10596.87 10898.51 9594.98 34596.14 14898.90 9397.02 32698.28 195.99 19599.11 7691.36 14799.89 3996.98 10299.19 11799.50 100
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
test_yl97.22 10796.78 11298.54 9298.73 14296.60 12598.45 17998.31 20594.70 16198.02 10498.42 16690.80 16199.70 11996.81 12096.79 19599.34 121
DCV-MVSNet97.22 10796.78 11298.54 9298.73 14296.60 12598.45 17998.31 20594.70 16198.02 10498.42 16690.80 16199.70 11996.81 12096.79 19599.34 121
IS-MVSNet97.22 10796.88 10798.25 11798.85 13596.36 13999.19 4197.97 26695.39 12897.23 14498.99 9691.11 15498.93 21894.60 19398.59 14499.47 107
PLCcopyleft95.07 497.20 11096.78 11298.44 10399.29 8296.31 14398.14 22698.76 10392.41 25996.39 18598.31 18194.92 8399.78 10094.06 21398.77 13799.23 137
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CHOSEN 280x42097.18 11197.18 9497.20 18198.81 13893.27 27195.78 34899.15 1995.25 13896.79 16798.11 19792.29 12299.07 19798.56 1399.85 599.25 136
LS3D97.16 11296.66 12198.68 8298.53 16197.19 10298.93 9198.90 4692.83 24695.99 19599.37 2692.12 12999.87 4893.67 22499.57 8198.97 170
AdaColmapbinary97.15 11396.70 11798.48 9999.16 10796.69 12198.01 23998.89 4894.44 17696.83 16298.68 13690.69 16499.76 10794.36 20099.29 11498.98 169
Effi-MVS+97.12 11496.69 11898.39 10898.19 18996.72 12097.37 28798.43 18693.71 20697.65 13398.02 20292.20 12799.25 17296.87 11797.79 17499.19 143
CHOSEN 1792x268897.12 11496.80 10998.08 12999.30 7994.56 22698.05 23599.71 193.57 21797.09 14898.91 11088.17 21899.89 3996.87 11799.56 8699.81 11
F-COLMAP97.09 11696.80 10997.97 13599.45 5994.95 20698.55 16898.62 14593.02 23896.17 19098.58 14994.01 10299.81 7593.95 21598.90 12899.14 152
TAMVS97.02 11796.79 11197.70 15598.06 20195.31 19098.52 17098.31 20593.95 19297.05 15398.61 14493.49 10898.52 26195.33 17297.81 17399.29 132
CDS-MVSNet96.99 11896.69 11897.90 13998.05 20295.98 15298.20 21598.33 20293.67 21396.95 15598.49 15793.54 10798.42 27495.24 17897.74 17799.31 127
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
CANet_DTU96.96 11996.55 12498.21 11998.17 19396.07 15097.98 24298.21 22297.24 4297.13 14798.93 10786.88 24799.91 3495.00 18299.37 11098.66 190
114514_t96.93 12096.27 13498.92 7299.50 4597.63 8398.85 10698.90 4684.80 35697.77 12299.11 7692.84 11499.66 12794.85 18499.77 3099.47 107
MAR-MVS96.91 12196.40 12998.45 10298.69 14996.90 11298.66 15198.68 12592.40 26097.07 15197.96 20991.54 14499.75 10993.68 22298.92 12798.69 186
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 12296.49 12798.14 12399.33 6995.56 17797.38 28599.65 292.34 26197.61 13698.20 19189.29 18799.10 19496.97 10397.60 18299.77 23
Vis-MVSNet (Re-imp)96.87 12396.55 12497.83 14298.73 14295.46 18299.20 3998.30 21194.96 15496.60 17398.87 11390.05 17398.59 25293.67 22498.60 14399.46 111
PAPR96.84 12496.24 13698.65 8498.72 14696.92 11197.36 28998.57 15493.33 22596.67 16997.57 24594.30 9899.56 14291.05 28898.59 14499.47 107
HY-MVS93.96 896.82 12596.23 13798.57 8898.46 16597.00 10798.14 22698.21 22293.95 19296.72 16897.99 20691.58 14099.76 10794.51 19796.54 20398.95 173
UGNet96.78 12696.30 13398.19 12298.24 18395.89 16798.88 10098.93 3997.39 2996.81 16597.84 22182.60 30999.90 3796.53 13199.49 9698.79 181
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 12796.60 12297.12 18899.25 9095.35 18898.26 20999.26 994.28 17897.94 11497.46 25192.74 11699.81 7596.88 11493.32 26396.20 327
mvs_anonymous96.70 12896.53 12697.18 18398.19 18993.78 24998.31 20198.19 22594.01 18894.47 22498.27 18692.08 13198.46 26997.39 8997.91 16999.31 127
1112_ss96.63 12996.00 14598.50 9698.56 15896.37 13898.18 22398.10 24592.92 24294.84 21298.43 16492.14 12899.58 13894.35 20196.51 20499.56 93
mvs-test196.60 13096.68 12096.37 25497.89 21191.81 29198.56 16698.10 24596.57 7596.52 18097.94 21190.81 15999.45 16195.72 16098.01 16697.86 218
PMMVS96.60 13096.33 13197.41 17197.90 21093.93 24597.35 29098.41 18892.84 24597.76 12397.45 25391.10 15599.20 17896.26 14197.91 16999.11 155
DP-MVS96.59 13295.93 14698.57 8899.34 6696.19 14798.70 14298.39 19289.45 33194.52 22299.35 3291.85 13599.85 5492.89 24998.88 13099.68 63
PatchMatch-RL96.59 13296.03 14498.27 11499.31 7496.51 13197.91 24899.06 2393.72 20596.92 15998.06 20088.50 21399.65 12891.77 27799.00 12598.66 190
GeoE96.58 13496.07 14198.10 12898.35 17195.89 16799.34 1998.12 24093.12 23596.09 19198.87 11389.71 17998.97 20992.95 24598.08 16599.43 115
mvsmamba96.57 13596.32 13297.32 17796.60 29396.43 13599.54 797.98 26496.49 7895.20 20698.64 14190.82 15898.55 25697.97 4593.65 25196.98 244
XVG-OURS96.55 13696.41 12896.99 19598.75 14193.76 25097.50 27998.52 16495.67 11596.83 16299.30 4288.95 20299.53 14895.88 15396.26 21597.69 224
FIs96.51 13796.12 13997.67 15897.13 26597.54 8799.36 1699.22 1595.89 10394.03 25198.35 17491.98 13398.44 27296.40 13892.76 27097.01 242
XVG-OURS-SEG-HR96.51 13796.34 13097.02 19498.77 14093.76 25097.79 26298.50 17295.45 12596.94 15699.09 8487.87 22899.55 14796.76 12595.83 22497.74 221
PS-MVSNAJss96.43 13996.26 13596.92 20595.84 32995.08 19899.16 4498.50 17295.87 10693.84 26098.34 17894.51 9198.61 24996.88 11493.45 26097.06 238
iter_conf_final96.42 14096.12 13997.34 17698.46 16596.55 13099.08 6198.06 25896.03 9895.63 19998.46 16287.72 23098.59 25297.84 5893.80 24796.87 262
FC-MVSNet-test96.42 14096.05 14297.53 16796.95 27397.27 9599.36 1699.23 1395.83 10793.93 25498.37 17292.00 13298.32 29196.02 14992.72 27197.00 243
ab-mvs96.42 14095.71 15898.55 9098.63 15496.75 11897.88 25398.74 10893.84 19796.54 17898.18 19385.34 27699.75 10995.93 15196.35 20899.15 150
PVSNet91.96 1896.35 14396.15 13896.96 20099.17 10392.05 28896.08 34198.68 12593.69 20997.75 12497.80 22788.86 20499.69 12494.26 20699.01 12499.15 150
Test_1112_low_res96.34 14495.66 16398.36 10998.56 15895.94 16097.71 26698.07 25392.10 27194.79 21697.29 26291.75 13799.56 14294.17 20896.50 20599.58 91
Effi-MVS+-dtu96.29 14596.56 12395.51 28697.89 21190.22 32198.80 12098.10 24596.57 7596.45 18496.66 31090.81 15998.91 22095.72 16097.99 16797.40 229
QAPM96.29 14595.40 16898.96 7097.85 21397.60 8599.23 3098.93 3989.76 32693.11 28699.02 9089.11 19499.93 1991.99 27299.62 7299.34 121
Fast-Effi-MVS+96.28 14795.70 16098.03 13298.29 18295.97 15798.58 16198.25 22091.74 27995.29 20497.23 26691.03 15799.15 18492.90 24797.96 16898.97 170
nrg03096.28 14795.72 15597.96 13796.90 27898.15 6199.39 1398.31 20595.47 12494.42 23098.35 17492.09 13098.69 24197.50 8689.05 31597.04 239
131496.25 14995.73 15497.79 14697.13 26595.55 17998.19 21998.59 14893.47 22092.03 31597.82 22591.33 14999.49 15394.62 19298.44 15298.32 206
h-mvs3396.17 15095.62 16497.81 14599.03 11794.45 22898.64 15398.75 10697.48 2098.67 6798.72 13289.76 17799.86 5397.95 4681.59 35599.11 155
HQP_MVS96.14 15195.90 14796.85 20897.42 24594.60 22398.80 12098.56 15697.28 3695.34 20298.28 18387.09 24299.03 20296.07 14494.27 23096.92 251
iter_conf0596.13 15295.79 15197.15 18598.16 19495.99 15198.88 10097.98 26495.91 10295.58 20098.46 16285.53 27198.59 25297.88 5393.75 24896.86 265
tttt051796.07 15395.51 16797.78 14798.41 16894.84 20999.28 2594.33 36494.26 18097.64 13498.64 14184.05 29899.47 15995.34 17197.60 18299.03 164
test_low_dy_conf_00196.06 15495.86 14896.69 21896.39 30694.58 22599.47 998.26 21895.68 11395.23 20598.73 13088.90 20398.47 26796.43 13693.62 25397.02 241
MVSTER96.06 15495.72 15597.08 19198.23 18495.93 16398.73 13398.27 21494.86 15895.07 20798.09 19888.21 21798.54 25896.59 12893.46 25896.79 271
thisisatest053096.01 15695.36 17397.97 13598.38 16995.52 18098.88 10094.19 36694.04 18597.64 13498.31 18183.82 30599.46 16095.29 17597.70 17998.93 174
test_djsdf96.00 15795.69 16196.93 20295.72 33195.49 18199.47 998.40 19094.98 15294.58 22097.86 21889.16 19298.41 28296.91 10794.12 23896.88 260
RRT_MVS95.98 15895.78 15296.56 23496.48 30294.22 24099.57 697.92 27195.89 10393.95 25398.70 13389.27 18898.42 27497.23 9493.02 26797.04 239
EI-MVSNet95.96 15995.83 15096.36 25597.93 20893.70 25698.12 22998.27 21493.70 20895.07 20799.02 9092.23 12598.54 25894.68 18993.46 25896.84 267
ECVR-MVScopyleft95.95 16095.71 15896.65 22199.02 11890.86 30999.03 6991.80 37396.96 5898.10 9699.26 4781.31 31699.51 15296.90 11099.04 12199.59 87
BH-untuned95.95 16095.72 15596.65 22198.55 16092.26 28498.23 21097.79 27793.73 20494.62 21998.01 20488.97 20199.00 20893.04 24298.51 14898.68 187
test111195.94 16295.78 15296.41 25198.99 12490.12 32299.04 6692.45 37296.99 5798.03 10299.27 4681.40 31599.48 15796.87 11799.04 12199.63 79
MSDG95.93 16395.30 18097.83 14298.90 12995.36 18696.83 32898.37 19691.32 29594.43 22998.73 13090.27 17199.60 13690.05 30298.82 13598.52 197
BH-RMVSNet95.92 16495.32 17797.69 15698.32 18094.64 21798.19 21997.45 30394.56 16996.03 19398.61 14485.02 27999.12 18990.68 29399.06 12099.30 130
bld_raw_conf00595.91 16595.56 16596.99 19596.51 29995.46 18299.21 3797.42 30796.41 8494.10 24698.63 14386.59 25198.54 25897.56 8193.59 25696.96 247
Fast-Effi-MVS+-dtu95.87 16695.85 14995.91 27497.74 22091.74 29598.69 14498.15 23695.56 12094.92 21097.68 23688.98 20098.79 23693.19 23797.78 17597.20 236
LFMVS95.86 16794.98 19498.47 10098.87 13296.32 14198.84 10996.02 34693.40 22398.62 7399.20 5974.99 35599.63 13397.72 6597.20 18899.46 111
baseline195.84 16895.12 18798.01 13398.49 16495.98 15298.73 13397.03 32495.37 13196.22 18898.19 19289.96 17599.16 18194.60 19387.48 33298.90 176
OpenMVScopyleft93.04 1395.83 16995.00 19298.32 11197.18 26297.32 9399.21 3798.97 3189.96 32291.14 32399.05 8986.64 25099.92 2593.38 23099.47 9997.73 222
VDD-MVS95.82 17095.23 18297.61 16398.84 13693.98 24498.68 14597.40 30895.02 15197.95 11299.34 3574.37 35999.78 10098.64 896.80 19499.08 161
UniMVSNet (Re)95.78 17195.19 18497.58 16496.99 27297.47 8998.79 12499.18 1795.60 11893.92 25597.04 28591.68 13898.48 26495.80 15787.66 33196.79 271
VPA-MVSNet95.75 17295.11 18897.69 15697.24 25497.27 9598.94 8999.23 1395.13 14395.51 20197.32 26085.73 26798.91 22097.33 9289.55 30796.89 259
bld_raw_dy_0_6495.74 17395.31 17997.03 19396.35 30995.76 17199.12 5297.37 31095.97 10094.70 21898.48 15885.80 26698.49 26396.55 13093.48 25796.84 267
HQP-MVS95.72 17495.40 16896.69 21897.20 25894.25 23898.05 23598.46 17996.43 8194.45 22597.73 23086.75 24898.96 21395.30 17394.18 23496.86 265
hse-mvs295.71 17595.30 18096.93 20298.50 16293.53 26198.36 19298.10 24597.48 2098.67 6797.99 20689.76 17799.02 20597.95 4680.91 35998.22 208
UniMVSNet_NR-MVSNet95.71 17595.15 18597.40 17396.84 28196.97 10898.74 12999.24 1195.16 14293.88 25797.72 23291.68 13898.31 29395.81 15587.25 33696.92 251
PatchmatchNetpermissive95.71 17595.52 16696.29 26097.58 22990.72 31396.84 32797.52 29694.06 18497.08 14996.96 29489.24 19098.90 22392.03 27198.37 15599.26 135
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
OPM-MVS95.69 17895.33 17696.76 21396.16 31894.63 21898.43 18498.39 19296.64 7295.02 20998.78 12485.15 27899.05 19895.21 17994.20 23396.60 294
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMM93.85 995.69 17895.38 17296.61 22797.61 22793.84 24898.91 9298.44 18395.25 13894.28 23698.47 16086.04 26499.12 18995.50 16993.95 24396.87 262
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
tpmrst95.63 18095.69 16195.44 29097.54 23488.54 34696.97 31397.56 28993.50 21997.52 14096.93 29889.49 18199.16 18195.25 17796.42 20798.64 192
LPG-MVS_test95.62 18195.34 17496.47 24597.46 24093.54 25998.99 7998.54 16094.67 16594.36 23298.77 12685.39 27399.11 19195.71 16294.15 23696.76 274
CLD-MVS95.62 18195.34 17496.46 24897.52 23793.75 25297.27 29798.46 17995.53 12194.42 23098.00 20586.21 25998.97 20996.25 14294.37 22896.66 289
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
thisisatest051595.61 18394.89 19897.76 14998.15 19595.15 19596.77 32994.41 36292.95 24197.18 14697.43 25584.78 28499.45 16194.63 19097.73 17898.68 187
thres600view795.49 18494.77 20197.67 15898.98 12595.02 19998.85 10696.90 33295.38 12996.63 17196.90 29984.29 29199.59 13788.65 32296.33 20998.40 201
SCA95.46 18595.13 18696.46 24897.67 22391.29 30497.33 29297.60 28794.68 16496.92 15997.10 27283.97 30098.89 22492.59 25598.32 15999.20 139
IterMVS-LS95.46 18595.21 18396.22 26298.12 19693.72 25598.32 20098.13 23993.71 20694.26 23797.31 26192.24 12498.10 30994.63 19090.12 29896.84 267
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
jajsoiax95.45 18795.03 19196.73 21495.42 34294.63 21899.14 4798.52 16495.74 11093.22 28098.36 17383.87 30398.65 24796.95 10694.04 23996.91 256
CVMVSNet95.43 18896.04 14393.57 32997.93 20883.62 36498.12 22998.59 14895.68 11396.56 17499.02 9087.51 23597.51 33993.56 22897.44 18499.60 85
anonymousdsp95.42 18994.91 19796.94 20195.10 34495.90 16699.14 4798.41 18893.75 20193.16 28297.46 25187.50 23798.41 28295.63 16694.03 24096.50 313
DU-MVS95.42 18994.76 20297.40 17396.53 29796.97 10898.66 15198.99 3095.43 12693.88 25797.69 23388.57 20998.31 29395.81 15587.25 33696.92 251
mvs_tets95.41 19195.00 19296.65 22195.58 33594.42 23099.00 7798.55 15895.73 11193.21 28198.38 17183.45 30798.63 24897.09 9994.00 24196.91 256
thres100view90095.38 19294.70 20597.41 17198.98 12594.92 20798.87 10396.90 33295.38 12996.61 17296.88 30084.29 29199.56 14288.11 32396.29 21197.76 219
thres40095.38 19294.62 20897.65 16198.94 12794.98 20398.68 14596.93 33095.33 13296.55 17696.53 31684.23 29499.56 14288.11 32396.29 21198.40 201
BH-w/o95.38 19295.08 18996.26 26198.34 17691.79 29297.70 26797.43 30592.87 24494.24 23997.22 26788.66 20798.84 23091.55 28197.70 17998.16 211
VDDNet95.36 19594.53 21297.86 14098.10 19895.13 19698.85 10697.75 27990.46 31298.36 8799.39 1873.27 36199.64 13097.98 4496.58 20198.81 180
TAPA-MVS93.98 795.35 19694.56 21197.74 15199.13 11094.83 21198.33 19598.64 14186.62 34596.29 18798.61 14494.00 10399.29 17080.00 36099.41 10699.09 157
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP93.49 1095.34 19794.98 19496.43 25097.67 22393.48 26398.73 13398.44 18394.94 15792.53 30298.53 15384.50 29099.14 18695.48 17094.00 24196.66 289
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
COLMAP_ROBcopyleft93.27 1295.33 19894.87 19996.71 21599.29 8293.24 27398.58 16198.11 24389.92 32393.57 26899.10 7886.37 25799.79 9690.78 29198.10 16497.09 237
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
tfpn200view995.32 19994.62 20897.43 17098.94 12794.98 20398.68 14596.93 33095.33 13296.55 17696.53 31684.23 29499.56 14288.11 32396.29 21197.76 219
Anonymous20240521195.28 20094.49 21497.67 15899.00 12193.75 25298.70 14297.04 32390.66 30896.49 18198.80 12278.13 33899.83 6096.21 14395.36 22699.44 114
thres20095.25 20194.57 21097.28 17898.81 13894.92 20798.20 21597.11 31995.24 14096.54 17896.22 32784.58 28899.53 14887.93 32796.50 20597.39 230
AllTest95.24 20294.65 20796.99 19599.25 9093.21 27498.59 15998.18 22891.36 29193.52 27098.77 12684.67 28699.72 11389.70 30997.87 17198.02 214
LCM-MVSNet-Re95.22 20395.32 17794.91 30498.18 19187.85 35598.75 12695.66 35295.11 14588.96 34196.85 30390.26 17297.65 33395.65 16598.44 15299.22 138
EPNet_dtu95.21 20494.95 19695.99 26996.17 31690.45 31898.16 22597.27 31596.77 6693.14 28598.33 17990.34 16998.42 27485.57 34098.81 13699.09 157
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
XXY-MVS95.20 20594.45 21997.46 16896.75 28696.56 12898.86 10598.65 14093.30 22893.27 27998.27 18684.85 28398.87 22794.82 18691.26 28796.96 247
D2MVS95.18 20695.08 18995.48 28797.10 26792.07 28798.30 20399.13 2094.02 18792.90 29096.73 30789.48 18298.73 24094.48 19893.60 25595.65 340
WR-MVS95.15 20794.46 21797.22 18096.67 29196.45 13398.21 21298.81 8094.15 18193.16 28297.69 23387.51 23598.30 29595.29 17588.62 32196.90 258
TranMVSNet+NR-MVSNet95.14 20894.48 21597.11 18996.45 30496.36 13999.03 6999.03 2695.04 15093.58 26797.93 21288.27 21698.03 31694.13 20986.90 34196.95 250
baseline295.11 20994.52 21396.87 20796.65 29293.56 25898.27 20894.10 36893.45 22192.02 31697.43 25587.45 23999.19 17993.88 21797.41 18697.87 217
miper_enhance_ethall95.10 21094.75 20396.12 26697.53 23693.73 25496.61 33598.08 25192.20 27093.89 25696.65 31292.44 11998.30 29594.21 20791.16 28896.34 321
Anonymous2024052995.10 21094.22 22797.75 15099.01 12094.26 23798.87 10398.83 7285.79 35396.64 17098.97 9778.73 33399.85 5496.27 14094.89 22799.12 154
test-LLR95.10 21094.87 19995.80 27996.77 28389.70 32696.91 31895.21 35495.11 14594.83 21495.72 33887.71 23198.97 20993.06 24098.50 14998.72 184
WR-MVS_H95.05 21394.46 21796.81 21196.86 28095.82 16999.24 2999.24 1193.87 19692.53 30296.84 30490.37 16898.24 30193.24 23587.93 32896.38 320
miper_ehance_all_eth95.01 21494.69 20695.97 27197.70 22293.31 27097.02 31198.07 25392.23 26793.51 27296.96 29491.85 13598.15 30593.68 22291.16 28896.44 318
ADS-MVSNet95.00 21594.45 21996.63 22598.00 20391.91 29096.04 34297.74 28090.15 31896.47 18296.64 31387.89 22698.96 21390.08 30097.06 18999.02 165
VPNet94.99 21694.19 22997.40 17397.16 26396.57 12798.71 13898.97 3195.67 11594.84 21298.24 18980.36 32598.67 24596.46 13387.32 33596.96 247
EPMVS94.99 21694.48 21596.52 24197.22 25691.75 29497.23 29891.66 37494.11 18297.28 14296.81 30585.70 26898.84 23093.04 24297.28 18798.97 170
NR-MVSNet94.98 21894.16 23197.44 16996.53 29797.22 10198.74 12998.95 3594.96 15489.25 34097.69 23389.32 18698.18 30394.59 19587.40 33496.92 251
FMVSNet394.97 21994.26 22697.11 18998.18 19196.62 12298.56 16698.26 21893.67 21394.09 24797.10 27284.25 29398.01 31792.08 26792.14 27496.70 283
CostFormer94.95 22094.73 20495.60 28597.28 25289.06 33797.53 27896.89 33489.66 32896.82 16496.72 30886.05 26298.95 21795.53 16896.13 22098.79 181
PAPM94.95 22094.00 24197.78 14797.04 26995.65 17496.03 34498.25 22091.23 30094.19 24297.80 22791.27 15198.86 22982.61 35497.61 18198.84 179
CP-MVSNet94.94 22294.30 22596.83 20996.72 28895.56 17799.11 5498.95 3593.89 19492.42 30897.90 21487.19 24198.12 30894.32 20388.21 32596.82 270
TR-MVS94.94 22294.20 22897.17 18497.75 21794.14 24197.59 27597.02 32692.28 26695.75 19897.64 23983.88 30298.96 21389.77 30696.15 21998.40 201
RPSCF94.87 22495.40 16893.26 33598.89 13082.06 36998.33 19598.06 25890.30 31796.56 17499.26 4787.09 24299.49 15393.82 21996.32 21098.24 207
test_part194.82 22593.82 25497.82 14498.84 13697.82 7799.03 6998.81 8092.31 26592.51 30497.89 21681.96 31198.67 24594.80 18888.24 32496.98 244
GA-MVS94.81 22694.03 23797.14 18697.15 26493.86 24796.76 33097.58 28894.00 18994.76 21797.04 28580.91 32098.48 26491.79 27696.25 21699.09 157
c3_l94.79 22794.43 22195.89 27697.75 21793.12 27797.16 30598.03 26192.23 26793.46 27597.05 28491.39 14698.01 31793.58 22789.21 31396.53 305
V4294.78 22894.14 23396.70 21796.33 31195.22 19298.97 8398.09 25092.32 26394.31 23597.06 28288.39 21498.55 25692.90 24788.87 31996.34 321
CR-MVSNet94.76 22994.15 23296.59 23097.00 27093.43 26494.96 35497.56 28992.46 25496.93 15796.24 32388.15 21997.88 32987.38 32996.65 19998.46 199
v2v48294.69 23094.03 23796.65 22196.17 31694.79 21498.67 14898.08 25192.72 24794.00 25297.16 27087.69 23498.45 27092.91 24688.87 31996.72 279
pmmvs494.69 23093.99 24396.81 21195.74 33095.94 16097.40 28397.67 28290.42 31493.37 27697.59 24389.08 19598.20 30292.97 24491.67 28196.30 325
cl2294.68 23294.19 22996.13 26598.11 19793.60 25796.94 31598.31 20592.43 25893.32 27896.87 30286.51 25298.28 29994.10 21291.16 28896.51 311
eth_miper_zixun_eth94.68 23294.41 22295.47 28897.64 22591.71 29696.73 33298.07 25392.71 24893.64 26597.21 26890.54 16698.17 30493.38 23089.76 30296.54 303
PCF-MVS93.45 1194.68 23293.43 27698.42 10698.62 15596.77 11795.48 35298.20 22484.63 35793.34 27798.32 18088.55 21199.81 7584.80 34798.96 12698.68 187
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MVS94.67 23593.54 27298.08 12996.88 27996.56 12898.19 21998.50 17278.05 36592.69 29798.02 20291.07 15699.63 13390.09 29998.36 15798.04 213
PS-CasMVS94.67 23593.99 24396.71 21596.68 29095.26 19199.13 5099.03 2693.68 21192.33 30997.95 21085.35 27598.10 30993.59 22688.16 32796.79 271
cascas94.63 23793.86 25296.93 20296.91 27794.27 23696.00 34598.51 16785.55 35494.54 22196.23 32584.20 29698.87 22795.80 15796.98 19297.66 225
tpmvs94.60 23894.36 22495.33 29397.46 24088.60 34596.88 32497.68 28191.29 29793.80 26296.42 32088.58 20899.24 17491.06 28696.04 22298.17 210
LTVRE_ROB92.95 1594.60 23893.90 24996.68 22097.41 24894.42 23098.52 17098.59 14891.69 28291.21 32298.35 17484.87 28299.04 20191.06 28693.44 26196.60 294
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 24093.92 24696.60 22996.21 31394.78 21598.59 15998.14 23891.86 27894.21 24197.02 28787.97 22498.41 28291.72 27889.57 30596.61 293
ADS-MVSNet294.58 24194.40 22395.11 29998.00 20388.74 34396.04 34297.30 31290.15 31896.47 18296.64 31387.89 22697.56 33790.08 30097.06 18999.02 165
ACMH92.88 1694.55 24293.95 24596.34 25797.63 22693.26 27298.81 11998.49 17793.43 22289.74 33598.53 15381.91 31299.08 19693.69 22193.30 26496.70 283
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
XVG-ACMP-BASELINE94.54 24394.14 23395.75 28296.55 29691.65 29798.11 23198.44 18394.96 15494.22 24097.90 21479.18 33299.11 19194.05 21493.85 24596.48 315
AUN-MVS94.53 24493.73 26396.92 20598.50 16293.52 26298.34 19498.10 24593.83 19995.94 19797.98 20885.59 27099.03 20294.35 20180.94 35898.22 208
DIV-MVS_self_test94.52 24594.03 23795.99 26997.57 23393.38 26897.05 30997.94 26991.74 27992.81 29297.10 27289.12 19398.07 31392.60 25390.30 29696.53 305
cl____94.51 24694.01 24096.02 26897.58 22993.40 26797.05 30997.96 26891.73 28192.76 29497.08 27889.06 19698.13 30792.61 25290.29 29796.52 308
GBi-Net94.49 24793.80 25696.56 23498.21 18695.00 20098.82 11398.18 22892.46 25494.09 24797.07 27981.16 31797.95 32192.08 26792.14 27496.72 279
test194.49 24793.80 25696.56 23498.21 18695.00 20098.82 11398.18 22892.46 25494.09 24797.07 27981.16 31797.95 32192.08 26792.14 27496.72 279
v894.47 24993.77 25996.57 23396.36 30894.83 21199.05 6598.19 22591.92 27593.16 28296.97 29288.82 20698.48 26491.69 27987.79 32996.39 319
FMVSNet294.47 24993.61 26997.04 19298.21 18696.43 13598.79 12498.27 21492.46 25493.50 27397.09 27681.16 31798.00 31991.09 28491.93 27796.70 283
test250694.44 25193.91 24896.04 26799.02 11888.99 34099.06 6379.47 38396.96 5898.36 8799.26 4777.21 34699.52 15196.78 12499.04 12199.59 87
Patchmatch-test94.42 25293.68 26796.63 22597.60 22891.76 29394.83 35897.49 30089.45 33194.14 24497.10 27288.99 19798.83 23285.37 34398.13 16399.29 132
PEN-MVS94.42 25293.73 26396.49 24396.28 31294.84 20999.17 4399.00 2893.51 21892.23 31197.83 22486.10 26197.90 32592.55 25886.92 34096.74 276
v14419294.39 25493.70 26596.48 24496.06 32194.35 23498.58 16198.16 23591.45 28894.33 23497.02 28787.50 23798.45 27091.08 28589.11 31496.63 291
Baseline_NR-MVSNet94.35 25593.81 25595.96 27296.20 31494.05 24398.61 15896.67 34391.44 28993.85 25997.60 24288.57 20998.14 30694.39 19986.93 33995.68 339
miper_lstm_enhance94.33 25694.07 23695.11 29997.75 21790.97 30897.22 29998.03 26191.67 28392.76 29496.97 29290.03 17497.78 33192.51 26089.64 30496.56 300
v119294.32 25793.58 27096.53 24096.10 31994.45 22898.50 17598.17 23391.54 28694.19 24297.06 28286.95 24698.43 27390.14 29889.57 30596.70 283
ACMH+92.99 1494.30 25893.77 25995.88 27797.81 21592.04 28998.71 13898.37 19693.99 19090.60 32998.47 16080.86 32299.05 19892.75 25192.40 27396.55 302
v14894.29 25993.76 26195.91 27496.10 31992.93 27998.58 16197.97 26692.59 25293.47 27496.95 29688.53 21298.32 29192.56 25787.06 33896.49 314
v1094.29 25993.55 27196.51 24296.39 30694.80 21398.99 7998.19 22591.35 29393.02 28896.99 29088.09 22198.41 28290.50 29588.41 32396.33 323
MVP-Stereo94.28 26193.92 24695.35 29294.95 34692.60 28297.97 24397.65 28391.61 28590.68 32897.09 27686.32 25898.42 27489.70 30999.34 11195.02 351
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
UniMVSNet_ETH3D94.24 26293.33 27896.97 19997.19 26193.38 26898.74 12998.57 15491.21 30293.81 26198.58 14972.85 36298.77 23895.05 18193.93 24498.77 183
OurMVSNet-221017-094.21 26394.00 24194.85 30795.60 33489.22 33598.89 9797.43 30595.29 13592.18 31298.52 15682.86 30898.59 25293.46 22991.76 27996.74 276
v192192094.20 26493.47 27596.40 25395.98 32494.08 24298.52 17098.15 23691.33 29494.25 23897.20 26986.41 25698.42 27490.04 30389.39 31196.69 288
v7n94.19 26593.43 27696.47 24595.90 32694.38 23399.26 2798.34 20191.99 27392.76 29497.13 27188.31 21598.52 26189.48 31487.70 33096.52 308
tpm294.19 26593.76 26195.46 28997.23 25589.04 33897.31 29496.85 33887.08 34496.21 18996.79 30683.75 30698.74 23992.43 26396.23 21798.59 194
TESTMET0.1,194.18 26793.69 26695.63 28496.92 27589.12 33696.91 31894.78 35993.17 23294.88 21196.45 31978.52 33498.92 21993.09 23998.50 14998.85 177
dp94.15 26893.90 24994.90 30597.31 25186.82 36096.97 31397.19 31891.22 30196.02 19496.61 31585.51 27299.02 20590.00 30494.30 22998.85 177
ET-MVSNet_ETH3D94.13 26992.98 28497.58 16498.22 18596.20 14597.31 29495.37 35394.53 17079.56 36597.63 24186.51 25297.53 33896.91 10790.74 29299.02 165
tpm94.13 26993.80 25695.12 29896.50 30087.91 35497.44 28095.89 35192.62 25096.37 18696.30 32284.13 29798.30 29593.24 23591.66 28299.14 152
IterMVS-SCA-FT94.11 27193.87 25194.85 30797.98 20790.56 31797.18 30298.11 24393.75 20192.58 30097.48 25083.97 30097.41 34092.48 26291.30 28596.58 296
Anonymous2023121194.10 27293.26 28196.61 22799.11 11294.28 23599.01 7598.88 5186.43 34792.81 29297.57 24581.66 31498.68 24494.83 18589.02 31796.88 260
IterMVS94.09 27393.85 25394.80 31097.99 20590.35 31997.18 30298.12 24093.68 21192.46 30797.34 25884.05 29897.41 34092.51 26091.33 28496.62 292
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test-mter94.08 27493.51 27395.80 27996.77 28389.70 32696.91 31895.21 35492.89 24394.83 21495.72 33877.69 34198.97 20993.06 24098.50 14998.72 184
test0.0.03 194.08 27493.51 27395.80 27995.53 33792.89 28097.38 28595.97 34895.11 14592.51 30496.66 31087.71 23196.94 34787.03 33193.67 24997.57 226
v124094.06 27693.29 28096.34 25796.03 32393.90 24698.44 18298.17 23391.18 30394.13 24597.01 28986.05 26298.42 27489.13 31989.50 30996.70 283
X-MVStestdata94.06 27692.30 29699.34 2699.70 2498.35 4899.29 2398.88 5197.40 2798.46 7943.50 37695.90 4499.89 3997.85 5699.74 4599.78 16
DTE-MVSNet93.98 27893.26 28196.14 26496.06 32194.39 23299.20 3998.86 6493.06 23691.78 31797.81 22685.87 26597.58 33690.53 29486.17 34596.46 317
pm-mvs193.94 27993.06 28396.59 23096.49 30195.16 19398.95 8798.03 26192.32 26391.08 32497.84 22184.54 28998.41 28292.16 26586.13 34796.19 328
MS-PatchMatch93.84 28093.63 26894.46 32196.18 31589.45 33197.76 26398.27 21492.23 26792.13 31397.49 24979.50 32998.69 24189.75 30799.38 10995.25 344
tfpnnormal93.66 28192.70 29096.55 23996.94 27495.94 16098.97 8399.19 1691.04 30591.38 32197.34 25884.94 28198.61 24985.45 34289.02 31795.11 348
EU-MVSNet93.66 28194.14 23392.25 34295.96 32583.38 36598.52 17098.12 24094.69 16392.61 29998.13 19687.36 24096.39 35891.82 27590.00 30096.98 244
our_test_393.65 28393.30 27994.69 31295.45 34089.68 32896.91 31897.65 28391.97 27491.66 31996.88 30089.67 18097.93 32488.02 32691.49 28396.48 315
pmmvs593.65 28392.97 28595.68 28395.49 33892.37 28398.20 21597.28 31489.66 32892.58 30097.26 26382.14 31098.09 31193.18 23890.95 29196.58 296
tpm cat193.36 28592.80 28795.07 30197.58 22987.97 35396.76 33097.86 27582.17 36193.53 26996.04 33186.13 26099.13 18789.24 31795.87 22398.10 212
JIA-IIPM93.35 28692.49 29395.92 27396.48 30290.65 31595.01 35396.96 32885.93 35196.08 19287.33 36787.70 23398.78 23791.35 28395.58 22598.34 204
SixPastTwentyTwo93.34 28792.86 28694.75 31195.67 33289.41 33398.75 12696.67 34393.89 19490.15 33398.25 18880.87 32198.27 30090.90 28990.64 29396.57 298
USDC93.33 28892.71 28995.21 29596.83 28290.83 31196.91 31897.50 29893.84 19790.72 32798.14 19577.69 34198.82 23389.51 31393.21 26695.97 333
IB-MVS91.98 1793.27 28991.97 30097.19 18297.47 23993.41 26697.09 30895.99 34793.32 22692.47 30695.73 33678.06 33999.53 14894.59 19582.98 35098.62 193
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 29092.21 29796.41 25197.73 22193.13 27695.65 34997.03 32491.27 29994.04 25096.06 33075.33 35397.19 34386.56 33396.23 21798.92 175
ppachtmachnet_test93.22 29192.63 29194.97 30395.45 34090.84 31096.88 32497.88 27490.60 30992.08 31497.26 26388.08 22297.86 33085.12 34490.33 29596.22 326
Patchmtry93.22 29192.35 29595.84 27896.77 28393.09 27894.66 35997.56 28987.37 34392.90 29096.24 32388.15 21997.90 32587.37 33090.10 29996.53 305
FMVSNet193.19 29392.07 29896.56 23497.54 23495.00 20098.82 11398.18 22890.38 31592.27 31097.07 27973.68 36097.95 32189.36 31691.30 28596.72 279
LF4IMVS93.14 29492.79 28894.20 32495.88 32788.67 34497.66 27097.07 32193.81 20091.71 31897.65 23777.96 34098.81 23491.47 28291.92 27895.12 347
testgi93.06 29592.45 29494.88 30696.43 30589.90 32398.75 12697.54 29595.60 11891.63 32097.91 21374.46 35897.02 34586.10 33693.67 24997.72 223
PatchT93.06 29591.97 30096.35 25696.69 28992.67 28194.48 36097.08 32086.62 34597.08 14992.23 36287.94 22597.90 32578.89 36496.69 19798.49 198
MVS_030492.81 29792.01 29995.23 29497.46 24091.33 30298.17 22498.81 8091.13 30493.80 26295.68 34166.08 36998.06 31490.79 29096.13 22096.32 324
RPMNet92.81 29791.34 30597.24 17997.00 27093.43 26494.96 35498.80 9182.27 36096.93 15792.12 36386.98 24599.82 6876.32 36896.65 19998.46 199
TransMVSNet (Re)92.67 29991.51 30496.15 26396.58 29594.65 21698.90 9396.73 33990.86 30789.46 33997.86 21885.62 26998.09 31186.45 33481.12 35695.71 338
K. test v392.55 30091.91 30294.48 31995.64 33389.24 33499.07 6294.88 35894.04 18586.78 35197.59 24377.64 34497.64 33492.08 26789.43 31096.57 298
DSMNet-mixed92.52 30192.58 29292.33 34094.15 35482.65 36798.30 20394.26 36589.08 33592.65 29895.73 33685.01 28095.76 36186.24 33597.76 17698.59 194
TinyColmap92.31 30291.53 30394.65 31496.92 27589.75 32596.92 31696.68 34290.45 31389.62 33697.85 22076.06 35198.81 23486.74 33292.51 27295.41 342
gg-mvs-nofinetune92.21 30390.58 31097.13 18796.75 28695.09 19795.85 34689.40 37785.43 35594.50 22381.98 37080.80 32398.40 28892.16 26598.33 15897.88 216
FMVSNet591.81 30490.92 30794.49 31897.21 25792.09 28698.00 24197.55 29489.31 33390.86 32695.61 34274.48 35795.32 36485.57 34089.70 30396.07 331
pmmvs691.77 30590.63 30995.17 29794.69 35291.24 30598.67 14897.92 27186.14 34989.62 33697.56 24775.79 35298.34 28990.75 29284.56 34995.94 334
Anonymous2023120691.66 30691.10 30693.33 33394.02 35887.35 35798.58 16197.26 31690.48 31190.16 33296.31 32183.83 30496.53 35679.36 36289.90 30196.12 329
Patchmatch-RL test91.49 30790.85 30893.41 33191.37 36784.40 36292.81 36495.93 35091.87 27787.25 34994.87 34888.99 19796.53 35692.54 25982.00 35299.30 130
test_040291.32 30890.27 31394.48 31996.60 29391.12 30698.50 17597.22 31786.10 35088.30 34696.98 29177.65 34397.99 32078.13 36692.94 26994.34 355
PVSNet_088.72 1991.28 30990.03 31595.00 30297.99 20587.29 35894.84 35798.50 17292.06 27289.86 33495.19 34479.81 32899.39 16492.27 26469.79 36998.33 205
Anonymous2024052191.18 31090.44 31193.42 33093.70 35988.47 34798.94 8997.56 28988.46 33889.56 33895.08 34777.15 34896.97 34683.92 35089.55 30794.82 353
EG-PatchMatch MVS91.13 31190.12 31494.17 32694.73 35189.00 33998.13 22897.81 27689.22 33485.32 35896.46 31867.71 36698.42 27487.89 32893.82 24695.08 349
TDRefinement91.06 31289.68 31795.21 29585.35 37491.49 30098.51 17497.07 32191.47 28788.83 34497.84 22177.31 34599.09 19592.79 25077.98 36295.04 350
UnsupCasMVSNet_eth90.99 31389.92 31694.19 32594.08 35589.83 32497.13 30798.67 13393.69 20985.83 35696.19 32875.15 35496.74 35089.14 31879.41 36096.00 332
test20.0390.89 31490.38 31292.43 33993.48 36088.14 35298.33 19597.56 28993.40 22387.96 34796.71 30980.69 32494.13 36979.15 36386.17 34595.01 352
MDA-MVSNet_test_wron90.71 31589.38 32094.68 31394.83 34890.78 31297.19 30197.46 30187.60 34172.41 37095.72 33886.51 25296.71 35385.92 33886.80 34296.56 300
YYNet190.70 31689.39 31994.62 31594.79 35090.65 31597.20 30097.46 30187.54 34272.54 36995.74 33486.51 25296.66 35486.00 33786.76 34396.54 303
KD-MVS_self_test90.38 31789.38 32093.40 33292.85 36388.94 34197.95 24497.94 26990.35 31690.25 33193.96 35579.82 32795.94 36084.62 34976.69 36495.33 343
pmmvs-eth3d90.36 31889.05 32394.32 32391.10 36892.12 28597.63 27496.95 32988.86 33684.91 35993.13 35878.32 33596.74 35088.70 32181.81 35494.09 359
CL-MVSNet_self_test90.11 31989.14 32293.02 33791.86 36688.23 35196.51 33898.07 25390.49 31090.49 33094.41 35084.75 28595.34 36380.79 35874.95 36695.50 341
new_pmnet90.06 32089.00 32493.22 33694.18 35388.32 35096.42 34096.89 33486.19 34885.67 35793.62 35677.18 34797.10 34481.61 35689.29 31294.23 356
MDA-MVSNet-bldmvs89.97 32188.35 32694.83 30995.21 34391.34 30197.64 27197.51 29788.36 33971.17 37196.13 32979.22 33196.63 35583.65 35186.27 34496.52 308
CMPMVSbinary66.06 2189.70 32289.67 31889.78 34693.19 36176.56 37197.00 31298.35 19980.97 36281.57 36397.75 22974.75 35698.61 24989.85 30593.63 25294.17 357
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MIMVSNet189.67 32388.28 32793.82 32792.81 36491.08 30798.01 23997.45 30387.95 34087.90 34895.87 33367.63 36794.56 36878.73 36588.18 32695.83 336
KD-MVS_2432*160089.61 32487.96 32894.54 31694.06 35691.59 29895.59 35097.63 28589.87 32488.95 34294.38 35278.28 33696.82 34884.83 34568.05 37095.21 345
miper_refine_blended89.61 32487.96 32894.54 31694.06 35691.59 29895.59 35097.63 28589.87 32488.95 34294.38 35278.28 33696.82 34884.83 34568.05 37095.21 345
MVS-HIRNet89.46 32688.40 32592.64 33897.58 22982.15 36894.16 36393.05 37175.73 36790.90 32582.52 36979.42 33098.33 29083.53 35298.68 13897.43 227
OpenMVS_ROBcopyleft86.42 2089.00 32787.43 33293.69 32893.08 36289.42 33297.91 24896.89 33478.58 36485.86 35594.69 34969.48 36498.29 29877.13 36793.29 26593.36 364
new-patchmatchnet88.50 32887.45 33191.67 34490.31 37085.89 36197.16 30597.33 31189.47 33083.63 36192.77 35976.38 34995.06 36682.70 35377.29 36394.06 360
PM-MVS87.77 32986.55 33391.40 34591.03 36983.36 36696.92 31695.18 35691.28 29886.48 35493.42 35753.27 37396.74 35089.43 31581.97 35394.11 358
UnsupCasMVSNet_bld87.17 33085.12 33493.31 33491.94 36588.77 34294.92 35698.30 21184.30 35882.30 36290.04 36463.96 37197.25 34285.85 33974.47 36893.93 362
N_pmnet87.12 33187.77 33085.17 35195.46 33961.92 37897.37 28770.66 38485.83 35288.73 34596.04 33185.33 27797.76 33280.02 35990.48 29495.84 335
pmmvs386.67 33284.86 33592.11 34388.16 37187.19 35996.63 33494.75 36079.88 36387.22 35092.75 36066.56 36895.20 36581.24 35776.56 36593.96 361
test_method79.03 33378.17 33681.63 35386.06 37354.40 38382.75 37296.89 33439.54 37680.98 36495.57 34358.37 37294.73 36784.74 34878.61 36195.75 337
LCM-MVSNet78.70 33476.24 33986.08 34977.26 38071.99 37594.34 36196.72 34061.62 37176.53 36689.33 36533.91 38092.78 37181.85 35574.60 36793.46 363
Gipumacopyleft78.40 33576.75 33883.38 35295.54 33680.43 37079.42 37397.40 30864.67 37073.46 36880.82 37145.65 37593.14 37066.32 37287.43 33376.56 373
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMMVS277.95 33675.44 34085.46 35082.54 37574.95 37394.23 36293.08 37072.80 36874.68 36787.38 36636.36 37991.56 37273.95 36963.94 37289.87 367
FPMVS77.62 33777.14 33779.05 35579.25 37860.97 37995.79 34795.94 34965.96 36967.93 37294.40 35137.73 37888.88 37468.83 37188.46 32287.29 368
EGC-MVSNET75.22 33869.54 34192.28 34194.81 34989.58 32997.64 27196.50 3451.82 3815.57 38295.74 33468.21 36596.26 35973.80 37091.71 28090.99 366
ANet_high69.08 33965.37 34380.22 35465.99 38271.96 37690.91 36890.09 37682.62 35949.93 37778.39 37229.36 38181.75 37562.49 37338.52 37686.95 370
tmp_tt68.90 34066.97 34274.68 35750.78 38459.95 38087.13 36983.47 38138.80 37762.21 37396.23 32564.70 37076.91 37988.91 32030.49 37787.19 369
PMVScopyleft61.03 2365.95 34163.57 34573.09 35857.90 38351.22 38485.05 37193.93 36954.45 37244.32 37883.57 36813.22 38289.15 37358.68 37481.00 35778.91 372
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
E-PMN64.94 34264.25 34467.02 35982.28 37659.36 38191.83 36785.63 37952.69 37360.22 37477.28 37341.06 37780.12 37746.15 37641.14 37461.57 375
EMVS64.07 34363.26 34666.53 36081.73 37758.81 38291.85 36684.75 38051.93 37559.09 37575.13 37443.32 37679.09 37842.03 37739.47 37561.69 374
MVEpermissive62.14 2263.28 34459.38 34774.99 35674.33 38165.47 37785.55 37080.50 38252.02 37451.10 37675.00 37510.91 38580.50 37651.60 37553.40 37378.99 371
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuyk23d30.17 34530.18 34930.16 36178.61 37943.29 38566.79 37414.21 38517.31 37814.82 38111.93 38111.55 38441.43 38037.08 37819.30 3785.76 378
cdsmvs_eth3d_5k23.98 34631.98 3480.00 3640.00 3870.00 3880.00 37598.59 1480.00 3820.00 38398.61 14490.60 1650.00 3830.00 3810.00 3810.00 379
testmvs21.48 34724.95 35011.09 36314.89 3856.47 38796.56 3369.87 3867.55 37917.93 37939.02 3779.43 3865.90 38216.56 38012.72 37920.91 377
test12320.95 34823.72 35112.64 36213.54 3868.19 38696.55 3376.13 3877.48 38016.74 38037.98 37812.97 3836.05 38116.69 3795.43 38023.68 376
ab-mvs-re8.20 34910.94 3520.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 38398.43 1640.00 3870.00 3830.00 3810.00 3810.00 379
pcd_1.5k_mvsjas7.88 35010.50 3530.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 38294.51 910.00 3830.00 3810.00 3810.00 379
test_blank0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
uanet_test0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
DCPMVS0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
sosnet-low-res0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
sosnet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
uncertanet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
Regformer0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
uanet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3820.00 3870.00 3830.00 3810.00 3810.00 379
FOURS199.82 198.66 2699.69 198.95 3597.46 2399.39 15
MSC_two_6792asdad99.62 699.17 10399.08 1198.63 14399.94 498.53 1499.80 1999.86 2
PC_three_145295.08 14999.60 599.16 6897.86 298.47 26797.52 8599.72 5499.74 37
No_MVS99.62 699.17 10399.08 1198.63 14399.94 498.53 1499.80 1999.86 2
test_one_060199.66 2899.25 298.86 6497.55 1699.20 2699.47 1097.57 6
eth-test20.00 387
eth-test0.00 387
ZD-MVS99.46 5598.70 2398.79 9693.21 23098.67 6798.97 9795.70 5099.83 6096.07 14499.58 80
RE-MVS-def98.34 3399.49 4997.86 7399.11 5498.80 9196.49 7899.17 3099.35 3295.29 6997.72 6599.65 6499.71 50
IU-MVS99.71 2199.23 798.64 14195.28 13699.63 498.35 3299.81 1299.83 7
OPU-MVS99.37 2399.24 9699.05 1499.02 7399.16 6897.81 399.37 16597.24 9399.73 4799.70 54
test_241102_TWO98.87 5897.65 1099.53 999.48 897.34 1199.94 498.43 2699.80 1999.83 7
test_241102_ONE99.71 2199.24 598.87 5897.62 1299.73 199.39 1897.53 799.74 111
9.1498.06 5599.47 5298.71 13898.82 7494.36 17799.16 3299.29 4396.05 3699.81 7597.00 10199.71 56
save fliter99.46 5598.38 4098.21 21298.71 11897.95 3
test_0728_THIRD97.32 3399.45 1199.46 1397.88 199.94 498.47 2299.86 199.85 4
test_0728_SECOND99.71 199.72 1399.35 198.97 8398.88 5199.94 498.47 2299.81 1299.84 6
test072699.72 1399.25 299.06 6398.88 5197.62 1299.56 699.50 597.42 9
GSMVS99.20 139
test_part299.63 3199.18 1099.27 21
sam_mvs189.45 18399.20 139
sam_mvs88.99 197
ambc89.49 34786.66 37275.78 37292.66 36596.72 34086.55 35392.50 36146.01 37497.90 32590.32 29682.09 35194.80 354
MTGPAbinary98.74 108
test_post196.68 33330.43 38087.85 22998.69 24192.59 255
test_post31.83 37988.83 20598.91 220
patchmatchnet-post95.10 34689.42 18498.89 224
GG-mvs-BLEND96.59 23096.34 31094.98 20396.51 33888.58 37893.10 28794.34 35480.34 32698.05 31589.53 31296.99 19196.74 276
MTMP98.89 9794.14 367
gm-plane-assit95.88 32787.47 35689.74 32796.94 29799.19 17993.32 234
test9_res96.39 13999.57 8199.69 57
TEST999.31 7498.50 3497.92 24698.73 11292.63 24997.74 12598.68 13696.20 2799.80 84
test_899.29 8298.44 3697.89 25298.72 11492.98 23997.70 12898.66 13996.20 2799.80 84
agg_prior295.87 15499.57 8199.68 63
agg_prior99.30 7998.38 4098.72 11497.57 13899.81 75
TestCases96.99 19599.25 9093.21 27498.18 22891.36 29193.52 27098.77 12684.67 28699.72 11389.70 30997.87 17198.02 214
test_prior498.01 6797.86 255
test_prior297.80 26096.12 9497.89 11998.69 13495.96 4096.89 11199.60 74
test_prior99.19 4699.31 7498.22 5598.84 6999.70 11999.65 73
旧先验297.57 27791.30 29698.67 6799.80 8495.70 164
新几何297.64 271
新几何199.16 5399.34 6698.01 6798.69 12290.06 32198.13 9498.95 10594.60 8999.89 3991.97 27399.47 9999.59 87
旧先验199.29 8297.48 8898.70 12199.09 8495.56 5399.47 9999.61 82
无先验97.58 27698.72 11491.38 29099.87 4893.36 23299.60 85
原ACMM297.67 269
原ACMM198.65 8499.32 7296.62 12298.67 13393.27 22997.81 12198.97 9795.18 7599.83 6093.84 21899.46 10299.50 100
test22299.23 9797.17 10397.40 28398.66 13688.68 33798.05 9998.96 10394.14 10099.53 9299.61 82
testdata299.89 3991.65 280
segment_acmp96.85 14
testdata98.26 11699.20 10195.36 18698.68 12591.89 27698.60 7599.10 7894.44 9699.82 6894.27 20599.44 10499.58 91
testdata197.32 29396.34 86
test1299.18 5099.16 10798.19 5798.53 16298.07 9895.13 7799.72 11399.56 8699.63 79
plane_prior797.42 24594.63 218
plane_prior697.35 25094.61 22187.09 242
plane_prior598.56 15699.03 20296.07 14494.27 23096.92 251
plane_prior498.28 183
plane_prior394.61 22197.02 5595.34 202
plane_prior298.80 12097.28 36
plane_prior197.37 249
plane_prior94.60 22398.44 18296.74 6894.22 232
n20.00 388
nn0.00 388
door-mid94.37 363
lessismore_v094.45 32294.93 34788.44 34891.03 37586.77 35297.64 23976.23 35098.42 27490.31 29785.64 34896.51 311
LGP-MVS_train96.47 24597.46 24093.54 25998.54 16094.67 16594.36 23298.77 12685.39 27399.11 19195.71 16294.15 23696.76 274
test1198.66 136
door94.64 361
HQP5-MVS94.25 238
HQP-NCC97.20 25898.05 23596.43 8194.45 225
ACMP_Plane97.20 25898.05 23596.43 8194.45 225
BP-MVS95.30 173
HQP4-MVS94.45 22598.96 21396.87 262
HQP3-MVS98.46 17994.18 234
HQP2-MVS86.75 248
NP-MVS97.28 25294.51 22797.73 230
MDTV_nov1_ep13_2view84.26 36396.89 32390.97 30697.90 11889.89 17693.91 21699.18 148
MDTV_nov1_ep1395.40 16897.48 23888.34 34996.85 32697.29 31393.74 20397.48 14197.26 26389.18 19199.05 19891.92 27497.43 185
ACMMP++_ref92.97 268
ACMMP++93.61 254
Test By Simon94.64 87
ITE_SJBPF95.44 29097.42 24591.32 30397.50 29895.09 14893.59 26698.35 17481.70 31398.88 22689.71 30893.39 26296.12 329
DeepMVS_CXcopyleft86.78 34897.09 26872.30 37495.17 35775.92 36684.34 36095.19 34470.58 36395.35 36279.98 36189.04 31692.68 365