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 6798.87 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 7798.58 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 1098.93 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 18198.91 4597.58 1599.54 899.46 1397.10 1299.94 497.64 7099.84 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 5298.87 5897.38 3099.35 1799.40 1797.78 599.87 4897.77 5999.85 599.78 16
Skip Steuart: Steuart Systems R&D Blog.
TSAR-MVS + MP.98.78 798.62 999.24 4399.69 2698.28 5399.14 4398.66 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 17398.81 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 2498.88 5197.52 1799.41 1398.78 12496.00 3899.79 9697.79 5899.59 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 20898.52 16497.95 399.32 1899.39 1896.22 2499.84 5797.72 6299.73 4799.67 67
XVS98.70 1098.49 2099.34 2699.70 2498.35 4899.29 2098.88 5197.40 2798.46 7999.20 5995.90 4499.89 3997.85 5499.74 4599.78 16
Regformer-298.69 1298.52 1599.19 4699.35 6498.01 6798.37 18598.81 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 18598.76 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 18298.68 12597.04 5498.52 7898.80 12296.78 1699.83 6097.93 4799.61 7399.74 37
Regformer-498.64 1598.53 1498.99 6699.43 6197.37 9298.40 18398.79 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 8898.85 6897.28 3699.72 399.39 1896.63 1997.60 33298.17 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 2798.96 3396.10 9498.94 4599.17 6396.06 3499.92 2597.62 7199.78 2799.75 32
ACMMP_NAP98.61 1898.30 3999.55 999.62 3298.95 1798.82 10798.81 8095.80 10299.16 3299.47 1095.37 6399.92 2597.89 5199.75 4299.79 13
region2R98.61 1898.38 2599.29 3499.74 898.16 6099.23 2798.93 3996.15 8998.94 4599.17 6395.91 4399.94 497.55 7899.79 2399.78 16
NCCC98.61 1898.35 2999.38 2099.28 8698.61 2998.45 17498.76 10397.82 698.45 8298.93 10796.65 1899.83 6097.38 8699.41 10699.71 50
SF-MVS98.59 2198.32 3899.41 1999.54 3898.71 2299.04 6098.81 8095.12 13999.32 1899.39 1896.22 2499.84 5797.72 6299.73 4799.67 67
Regformer-398.59 2198.50 1798.86 7699.43 6197.05 10698.40 18398.68 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 2798.95 3596.10 9498.93 5099.19 6295.70 5099.94 497.62 7199.79 2399.78 16
SMA-MVScopyleft98.58 2498.25 4399.56 899.51 4399.04 1598.95 8198.80 9193.67 20999.37 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 8898.74 10897.27 4098.02 10499.39 1894.81 8499.96 297.91 4899.79 2399.77 23
HPM-MVS++copyleft98.58 2498.25 4399.55 999.50 4599.08 1198.72 13198.66 13697.51 1898.15 9398.83 11995.70 5099.92 2597.53 8099.67 6099.66 71
SR-MVS98.57 2798.35 2999.24 4399.53 3998.18 5899.09 5398.82 7496.58 7499.10 3599.32 3795.39 6199.82 6897.70 6799.63 7099.72 46
CP-MVS98.57 2798.36 2799.19 4699.66 2897.86 7399.34 1698.87 5895.96 9798.60 7599.13 7396.05 3699.94 497.77 5999.86 199.77 23
test117298.56 2998.35 2999.16 5399.53 3997.94 7199.09 5398.83 7296.52 7799.05 3899.34 3595.34 6599.82 6897.86 5399.64 6899.73 42
MSLP-MVS++98.56 2998.57 1198.55 9099.26 8996.80 11698.71 13299.05 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 16398.74 10897.27 4098.02 10499.39 1894.81 8499.96 297.91 4899.79 2399.77 23
DeepC-MVS_fast96.70 198.55 3198.34 3399.18 5099.25 9098.04 6598.50 17098.78 9997.72 798.92 5199.28 4495.27 7099.82 6897.55 7899.77 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 4998.80 9196.49 7899.17 3099.35 3295.34 6599.82 6897.72 6299.65 6499.71 50
#test#98.54 3398.27 4199.32 3199.72 1398.29 5198.98 7698.96 3395.65 11098.94 4599.17 6396.06 3499.92 2597.21 9199.78 2799.75 32
APD-MVS_3200maxsize98.53 3598.33 3799.15 5699.50 4597.92 7299.15 4198.81 8096.24 8699.20 2699.37 2695.30 6899.80 8497.73 6199.67 6099.72 46
mPP-MVS98.51 3698.26 4299.25 4299.75 498.04 6599.28 2298.81 8096.24 8698.35 8999.23 5295.46 5799.94 497.42 8499.81 1299.77 23
ZNCC-MVS98.49 3798.20 4999.35 2599.73 1298.39 3999.19 3798.86 6495.77 10398.31 9299.10 7895.46 5799.93 1997.57 7799.81 1299.74 37
CS-MVS-test98.49 3798.50 1798.46 10199.20 10197.05 10699.64 498.50 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 7399.49 595.43 12099.03 3999.32 3795.56 5399.94 496.80 11799.77 3099.78 16
EI-MVSNet-Vis-set98.47 4098.39 2498.69 8199.46 5596.49 13298.30 19998.69 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 24499.58 397.20 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 12099.67 398.47 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 5398.82 7495.71 10698.73 6499.06 8895.27 7099.93 1997.07 9599.63 7099.72 46
EI-MVSNet-UG-set98.41 4498.34 3398.61 8699.45 5996.32 14098.28 20298.68 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 26098.89 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 10198.11 22798.29 21497.19 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 7399.44 998.82 7494.46 17198.94 4599.20 5995.16 7699.74 11197.58 7499.85 599.77 23
patch_mono-298.36 4898.87 396.82 20699.53 3990.68 31198.64 14799.29 897.88 599.19 2999.52 396.80 1599.97 199.11 199.86 199.82 10
HPM-MVScopyleft98.36 4898.10 5499.13 5799.74 897.82 7799.53 698.80 9194.63 16498.61 7498.97 9795.13 7799.77 10597.65 6999.83 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 14298.84 6994.66 16399.11 3499.25 5095.46 5799.81 7596.80 11799.73 4799.63 79
APD-MVScopyleft98.35 5098.00 5999.42 1899.51 4398.72 2198.80 11498.82 7494.52 16899.23 2499.25 5095.54 5599.80 8496.52 12899.77 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 11397.95 24099.58 397.14 4998.44 8399.01 9495.03 8099.62 13597.91 4899.75 4299.50 100
PHI-MVS98.34 5298.06 5599.18 5099.15 10998.12 6399.04 6099.09 2193.32 22298.83 5799.10 7896.54 2099.83 6097.70 6799.76 3699.59 87
testtj98.33 5497.95 6199.47 1499.49 4998.70 2398.83 10498.86 6495.48 11798.91 5299.17 6395.48 5699.93 1995.80 15399.53 9299.76 30
MP-MVScopyleft98.33 5498.01 5899.28 3899.75 498.18 5899.22 3198.79 9696.13 9197.92 11799.23 5294.54 9099.94 496.74 12299.78 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 17998.78 9994.10 17997.69 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 4698.82 7496.14 9099.26 2299.37 2693.33 10999.93 1996.96 10099.67 6099.69 57
ACMMPcopyleft98.23 5897.95 6199.09 6299.74 897.62 8499.03 6399.41 695.98 9697.60 13799.36 3094.45 9599.93 1997.14 9298.85 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 25698.84 6996.12 9297.89 11998.69 13295.96 4099.70 11996.89 10699.60 7499.65 73
DROMVSNet98.21 6098.11 5398.49 9898.34 17597.26 10099.61 598.43 18696.78 6598.87 5498.84 11793.72 10699.01 20898.91 399.50 9599.19 143
dcpmvs_298.08 6198.59 1096.56 23099.57 3590.34 31799.15 4198.38 19696.82 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 9698.35 18898.78 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 24298.73 11292.98 23597.74 12598.68 13496.20 2799.80 8496.59 12499.57 8199.68 63
ETH3D cwj APD-0.1697.96 6497.52 7799.29 3499.05 11498.52 3298.33 19198.68 12593.18 22798.68 6699.13 7394.62 8899.83 6096.45 13099.55 9099.52 94
ETV-MVS97.96 6497.81 6598.40 10798.42 16697.27 9698.73 12798.55 15896.84 6298.38 8697.44 25095.39 6199.35 16697.62 7198.89 12998.58 197
UA-Net97.96 6497.62 7098.98 6898.86 13397.47 8998.89 9299.08 2296.67 7198.72 6599.54 193.15 11299.81 7594.87 17998.83 13499.65 73
agg_prior197.95 6797.51 7999.28 3899.30 7998.38 4097.81 25598.72 11493.16 22997.57 13898.66 13796.14 3099.81 7596.63 12399.56 8699.66 71
CDPH-MVS97.94 6897.49 8099.28 3899.47 5298.44 3697.91 24498.67 13392.57 25098.77 6098.85 11595.93 4299.72 11395.56 16399.69 5899.68 63
DeepPCF-MVS96.37 297.93 6998.48 2296.30 25499.00 12189.54 32797.43 27898.87 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 11198.83 10498.75 10696.96 5896.89 16199.50 590.46 16699.87 4897.84 5699.76 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 19198.89 4892.62 24798.05 9998.94 10695.34 6599.65 12896.04 14499.42 10599.19 143
CSCG97.85 7297.74 6898.20 12099.67 2795.16 18999.22 3199.32 793.04 23397.02 15498.92 10995.36 6499.91 3497.43 8399.64 6899.52 94
MG-MVS97.81 7397.60 7198.44 10399.12 11195.97 15597.75 26098.78 9996.89 6198.46 7999.22 5493.90 10599.68 12594.81 18399.52 9499.67 67
VNet97.79 7497.40 8698.96 7098.88 13197.55 8698.63 14998.93 3996.74 6899.02 4098.84 11790.33 16999.83 6098.53 1496.66 19899.50 100
EIA-MVS97.75 7597.58 7298.27 11498.38 16896.44 13499.01 6998.60 14695.88 9997.26 14397.53 24394.97 8199.33 16897.38 8699.20 11699.05 163
PS-MVSNAJ97.73 7697.77 6697.62 16298.68 15095.58 17397.34 28798.51 16797.29 3598.66 7197.88 21194.51 9199.90 3797.87 5299.17 11897.39 231
CPTT-MVS97.72 7797.32 8998.92 7299.64 3097.10 10599.12 4898.81 8092.34 25898.09 9799.08 8693.01 11399.92 2596.06 14399.77 3099.75 32
PVSNet_Blended_VisFu97.70 7897.46 8298.44 10399.27 8795.91 16398.63 14999.16 1894.48 17097.67 13098.88 11292.80 11599.91 3497.11 9399.12 11999.50 100
canonicalmvs97.67 7997.23 9298.98 6898.70 14798.38 4099.34 1698.39 19396.76 6797.67 13097.40 25392.26 12399.49 15398.28 3596.28 21499.08 161
xiu_mvs_v2_base97.66 8097.70 6997.56 16698.61 15695.46 17997.44 27698.46 17997.15 4898.65 7298.15 18894.33 9799.80 8497.84 5698.66 14297.41 229
baseline97.64 8197.44 8498.25 11798.35 17096.20 14499.00 7198.32 20496.33 8598.03 10299.17 6391.35 14899.16 18198.10 3998.29 16099.39 118
casdiffmvs97.63 8297.41 8598.28 11398.33 17796.14 14798.82 10798.32 20496.38 8397.95 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 17095.98 15097.86 25198.51 16797.13 5099.01 4198.40 16291.56 14199.80 8498.53 1498.68 13897.37 233
xiu_mvs_v1_base97.60 8397.56 7497.72 15298.35 17095.98 15097.86 25198.51 16797.13 5099.01 4198.40 16291.56 14199.80 8498.53 1498.68 13897.37 233
xiu_mvs_v1_base_debi97.60 8397.56 7497.72 15298.35 17095.98 15097.86 25198.51 16797.13 5099.01 4198.40 16291.56 14199.80 8498.53 1498.68 13897.37 233
ETH3 D test640097.59 8697.01 10199.34 2699.40 6398.56 3098.20 21198.81 8091.63 28198.44 8398.85 11593.98 10499.82 6894.11 20899.69 5899.64 76
diffmvs97.58 8797.40 8698.13 12598.32 17995.81 16898.06 23098.37 19796.20 8898.74 6298.89 11191.31 15099.25 17298.16 3798.52 14799.34 121
MVSFormer97.57 8897.49 8097.84 14198.07 19795.76 16999.47 798.40 19194.98 14798.79 5898.83 11992.34 12098.41 27896.91 10299.59 7799.34 121
alignmvs97.56 8997.07 9999.01 6598.66 15198.37 4698.83 10498.06 25996.74 6898.00 11097.65 23290.80 16099.48 15798.37 3196.56 20299.19 143
DPM-MVS97.55 9096.99 10399.23 4599.04 11698.55 3197.17 30098.35 20094.85 15497.93 11698.58 14595.07 7999.71 11892.60 25099.34 11199.43 115
OMC-MVS97.55 9097.34 8898.20 12099.33 6995.92 16298.28 20298.59 14895.52 11697.97 11199.10 7893.28 11199.49 15395.09 17698.88 13099.19 143
PAPM_NR97.46 9297.11 9698.50 9699.50 4596.41 13698.63 14998.60 14695.18 13597.06 15298.06 19494.26 9999.57 13993.80 21798.87 13299.52 94
EPP-MVSNet97.46 9297.28 9097.99 13498.64 15395.38 18199.33 1998.31 20693.61 21297.19 14599.07 8794.05 10199.23 17596.89 10698.43 15499.37 120
3Dnovator94.51 597.46 9296.93 10599.07 6397.78 21497.64 8299.35 1599.06 2397.02 5593.75 26099.16 6889.25 18799.92 2597.22 9099.75 4299.64 76
CNLPA97.45 9597.03 10098.73 7999.05 11497.44 9198.07 22998.53 16295.32 12896.80 16698.53 14993.32 11099.72 11394.31 20199.31 11399.02 165
lupinMVS97.44 9697.22 9398.12 12798.07 19795.76 16997.68 26497.76 27594.50 16998.79 5898.61 14092.34 12099.30 16997.58 7499.59 7799.31 127
3Dnovator+94.38 697.43 9796.78 11299.38 2097.83 21298.52 3299.37 1298.71 11897.09 5392.99 28699.13 7389.36 18499.89 3996.97 9899.57 8199.71 50
Vis-MVSNetpermissive97.42 9897.11 9698.34 11098.66 15196.23 14399.22 3199.00 2896.63 7398.04 10199.21 5588.05 22199.35 16696.01 14699.21 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 11698.82 10798.69 12294.53 16698.11 9598.28 17794.50 9499.57 13994.12 20799.49 9697.37 233
sss97.39 10096.98 10498.61 8698.60 15796.61 12598.22 20798.93 3993.97 18798.01 10898.48 15491.98 13399.85 5496.45 13098.15 16299.39 118
PVSNet_Blended97.38 10197.12 9598.14 12399.25 9095.35 18497.28 29299.26 993.13 23097.94 11498.21 18492.74 11699.81 7596.88 10999.40 10899.27 134
112197.37 10296.77 11699.16 5399.34 6697.99 7098.19 21598.68 12590.14 31798.01 10898.97 9794.80 8699.87 4893.36 22999.46 10299.61 82
WTY-MVS97.37 10296.92 10698.72 8098.86 13396.89 11598.31 19798.71 11895.26 13197.67 13098.56 14892.21 12699.78 10095.89 14896.85 19399.48 105
jason97.32 10497.08 9898.06 13197.45 24395.59 17297.87 25097.91 27094.79 15598.55 7798.83 11991.12 15399.23 17597.58 7499.60 7499.34 121
jason: jason.
MVS_Test97.28 10597.00 10298.13 12598.33 17795.97 15598.74 12398.07 25494.27 17598.44 8398.07 19392.48 11899.26 17196.43 13298.19 16199.16 149
EPNet97.28 10596.87 10898.51 9594.98 34196.14 14798.90 8897.02 32198.28 195.99 19599.11 7691.36 14799.89 3996.98 9799.19 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 12698.45 17498.31 20694.70 15798.02 10498.42 16090.80 16099.70 11996.81 11596.79 19599.34 121
DCV-MVSNet97.22 10796.78 11298.54 9298.73 14296.60 12698.45 17498.31 20694.70 15798.02 10498.42 16090.80 16099.70 11996.81 11596.79 19599.34 121
IS-MVSNet97.22 10796.88 10798.25 11798.85 13596.36 13899.19 3797.97 26495.39 12297.23 14498.99 9691.11 15498.93 21994.60 18998.59 14499.47 107
PLCcopyleft95.07 497.20 11096.78 11298.44 10399.29 8296.31 14298.14 22298.76 10392.41 25696.39 18598.31 17594.92 8399.78 10094.06 21098.77 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 18098.81 13893.27 26695.78 34499.15 1995.25 13296.79 16798.11 19192.29 12299.07 19898.56 1399.85 599.25 136
LS3D97.16 11296.66 12198.68 8298.53 16197.19 10398.93 8598.90 4692.83 24395.99 19599.37 2692.12 12999.87 4893.67 22199.57 8198.97 170
AdaColmapbinary97.15 11396.70 11798.48 9999.16 10796.69 12298.01 23598.89 4894.44 17296.83 16298.68 13490.69 16399.76 10794.36 19799.29 11498.98 169
Effi-MVS+97.12 11496.69 11898.39 10898.19 18896.72 12197.37 28398.43 18693.71 20297.65 13398.02 19692.20 12799.25 17296.87 11297.79 17499.19 143
CHOSEN 1792x268897.12 11496.80 10998.08 12999.30 7994.56 22298.05 23199.71 193.57 21397.09 14898.91 11088.17 21699.89 3996.87 11299.56 8699.81 11
F-COLMAP97.09 11696.80 10997.97 13599.45 5994.95 20398.55 16398.62 14593.02 23496.17 19098.58 14594.01 10299.81 7593.95 21298.90 12899.14 152
TAMVS97.02 11796.79 11197.70 15598.06 19995.31 18698.52 16598.31 20693.95 18897.05 15398.61 14093.49 10898.52 26095.33 16897.81 17399.29 132
CDS-MVSNet96.99 11896.69 11897.90 13998.05 20095.98 15098.20 21198.33 20393.67 20996.95 15598.49 15393.54 10798.42 27195.24 17497.74 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 19296.07 14997.98 23898.21 22297.24 4297.13 14798.93 10786.88 24599.91 3495.00 17899.37 11098.66 191
114514_t96.93 12096.27 13398.92 7299.50 4597.63 8398.85 10098.90 4684.80 35397.77 12299.11 7692.84 11499.66 12794.85 18099.77 3099.47 107
MAR-MVS96.91 12196.40 12998.45 10298.69 14996.90 11398.66 14598.68 12592.40 25797.07 15197.96 20391.54 14499.75 10993.68 21998.92 12798.69 187
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 17497.38 28199.65 292.34 25897.61 13698.20 18589.29 18699.10 19596.97 9897.60 18299.77 23
Vis-MVSNet (Re-imp)96.87 12396.55 12497.83 14298.73 14295.46 17999.20 3598.30 21294.96 14996.60 17398.87 11390.05 17298.59 25493.67 22198.60 14399.46 111
PAPR96.84 12496.24 13598.65 8498.72 14696.92 11297.36 28598.57 15493.33 22196.67 16997.57 24094.30 9899.56 14291.05 28598.59 14499.47 107
HY-MVS93.96 896.82 12596.23 13698.57 8898.46 16597.00 10898.14 22298.21 22293.95 18896.72 16897.99 20091.58 14099.76 10794.51 19496.54 20398.95 173
UGNet96.78 12696.30 13298.19 12298.24 18295.89 16598.88 9598.93 3997.39 2996.81 16597.84 21682.60 30499.90 3796.53 12799.49 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 18699.25 9095.35 18498.26 20599.26 994.28 17497.94 11497.46 24792.74 11699.81 7596.88 10993.32 25896.20 324
mvs_anonymous96.70 12896.53 12697.18 18298.19 18893.78 24498.31 19798.19 22594.01 18494.47 22298.27 18092.08 13198.46 26697.39 8597.91 16999.31 127
1112_ss96.63 12996.00 14398.50 9698.56 15896.37 13798.18 21998.10 24592.92 23894.84 21098.43 15892.14 12899.58 13894.35 19896.51 20499.56 93
mvs-test196.60 13096.68 12096.37 24997.89 20991.81 28698.56 16198.10 24596.57 7596.52 18097.94 20590.81 15899.45 16195.72 15698.01 16697.86 219
PMMVS96.60 13096.33 13197.41 17297.90 20893.93 24097.35 28698.41 18992.84 24297.76 12397.45 24991.10 15599.20 17896.26 13697.91 16999.11 155
DP-MVS96.59 13295.93 14498.57 8899.34 6696.19 14698.70 13698.39 19389.45 32894.52 22099.35 3291.85 13599.85 5492.89 24698.88 13099.68 63
PatchMatch-RL96.59 13296.03 14298.27 11499.31 7496.51 13197.91 24499.06 2393.72 20196.92 15998.06 19488.50 21099.65 12891.77 27499.00 12598.66 191
GeoE96.58 13496.07 13998.10 12898.35 17095.89 16599.34 1698.12 24093.12 23196.09 19198.87 11389.71 17898.97 21092.95 24298.08 16599.43 115
XVG-OURS96.55 13596.41 12896.99 19298.75 14193.76 24597.50 27598.52 16495.67 10896.83 16299.30 4288.95 20099.53 14895.88 14996.26 21597.69 225
FIs96.51 13696.12 13897.67 15897.13 26597.54 8799.36 1399.22 1595.89 9894.03 24898.35 16891.98 13398.44 26996.40 13392.76 26597.01 242
XVG-OURS-SEG-HR96.51 13696.34 13097.02 19198.77 14093.76 24597.79 25898.50 17295.45 11996.94 15699.09 8487.87 22699.55 14796.76 12195.83 22497.74 222
PS-MVSNAJss96.43 13896.26 13496.92 20195.84 32595.08 19599.16 4098.50 17295.87 10093.84 25698.34 17294.51 9198.61 25096.88 10993.45 25597.06 240
FC-MVSNet-test96.42 13996.05 14097.53 16896.95 27497.27 9699.36 1399.23 1395.83 10193.93 25098.37 16692.00 13298.32 28796.02 14592.72 26697.00 243
ab-mvs96.42 13995.71 15398.55 9098.63 15496.75 11997.88 24998.74 10893.84 19396.54 17898.18 18785.34 27199.75 10995.93 14796.35 20899.15 150
PVSNet91.96 1896.35 14196.15 13796.96 19699.17 10392.05 28396.08 33798.68 12593.69 20597.75 12497.80 22288.86 20199.69 12494.26 20399.01 12499.15 150
Test_1112_low_res96.34 14295.66 15898.36 10998.56 15895.94 15897.71 26298.07 25492.10 26894.79 21497.29 25891.75 13799.56 14294.17 20596.50 20599.58 91
Effi-MVS+-dtu96.29 14396.56 12395.51 28397.89 20990.22 31898.80 11498.10 24596.57 7596.45 18496.66 30690.81 15898.91 22195.72 15697.99 16797.40 230
QAPM96.29 14395.40 16398.96 7097.85 21197.60 8599.23 2798.93 3989.76 32393.11 28399.02 9089.11 19299.93 1991.99 26999.62 7299.34 121
Fast-Effi-MVS+96.28 14595.70 15598.03 13298.29 18195.97 15598.58 15598.25 22091.74 27695.29 20397.23 26291.03 15799.15 18492.90 24497.96 16898.97 170
nrg03096.28 14595.72 15097.96 13796.90 27998.15 6199.39 1098.31 20695.47 11894.42 22898.35 16892.09 13098.69 24297.50 8289.05 31297.04 241
131496.25 14795.73 14997.79 14697.13 26595.55 17698.19 21598.59 14893.47 21692.03 31297.82 22091.33 14999.49 15394.62 18898.44 15298.32 207
h-mvs3396.17 14895.62 15997.81 14599.03 11794.45 22498.64 14798.75 10697.48 2098.67 6798.72 13189.76 17699.86 5397.95 4581.59 35299.11 155
HQP_MVS96.14 14995.90 14596.85 20497.42 24494.60 22098.80 11498.56 15697.28 3695.34 20098.28 17787.09 24099.03 20396.07 14094.27 23196.92 249
tttt051796.07 15095.51 16297.78 14798.41 16794.84 20699.28 2294.33 36194.26 17697.64 13498.64 13984.05 29399.47 15995.34 16797.60 18299.03 164
MVSTER96.06 15195.72 15097.08 18998.23 18395.93 16198.73 12798.27 21594.86 15395.07 20498.09 19288.21 21498.54 25896.59 12493.46 25396.79 267
RRT_MVS96.04 15295.53 16097.56 16697.07 26997.32 9398.57 16098.09 25095.15 13795.02 20698.44 15788.20 21598.58 25696.17 13993.09 26296.79 267
thisisatest053096.01 15395.36 16897.97 13598.38 16895.52 17798.88 9594.19 36394.04 18197.64 13498.31 17583.82 30099.46 16095.29 17197.70 17998.93 174
test_djsdf96.00 15495.69 15696.93 19895.72 32795.49 17899.47 798.40 19194.98 14794.58 21897.86 21389.16 19098.41 27896.91 10294.12 23996.88 258
EI-MVSNet95.96 15595.83 14796.36 25097.93 20693.70 25198.12 22598.27 21593.70 20495.07 20499.02 9092.23 12598.54 25894.68 18593.46 25396.84 263
ECVR-MVScopyleft95.95 15695.71 15396.65 21799.02 11890.86 30599.03 6391.80 37096.96 5898.10 9699.26 4781.31 31299.51 15296.90 10599.04 12199.59 87
BH-untuned95.95 15695.72 15096.65 21798.55 16092.26 27998.23 20697.79 27493.73 20094.62 21798.01 19888.97 19999.00 20993.04 23998.51 14898.68 188
test111195.94 15895.78 14896.41 24698.99 12490.12 31999.04 6092.45 36996.99 5798.03 10299.27 4681.40 31199.48 15796.87 11299.04 12199.63 79
MSDG95.93 15995.30 17497.83 14298.90 12995.36 18296.83 32498.37 19791.32 29294.43 22798.73 13090.27 17099.60 13690.05 29998.82 13598.52 198
BH-RMVSNet95.92 16095.32 17297.69 15698.32 17994.64 21498.19 21597.45 30094.56 16596.03 19398.61 14085.02 27499.12 18990.68 29099.06 12099.30 130
Fast-Effi-MVS+-dtu95.87 16195.85 14695.91 27097.74 21891.74 29098.69 13898.15 23695.56 11394.92 20897.68 23188.98 19898.79 23793.19 23497.78 17597.20 237
LFMVS95.86 16294.98 18898.47 10098.87 13296.32 14098.84 10396.02 34293.40 21998.62 7399.20 5974.99 35299.63 13397.72 6297.20 18899.46 111
baseline195.84 16395.12 18198.01 13398.49 16495.98 15098.73 12797.03 31995.37 12596.22 18898.19 18689.96 17499.16 18194.60 18987.48 32998.90 176
OpenMVScopyleft93.04 1395.83 16495.00 18698.32 11197.18 26297.32 9399.21 3498.97 3189.96 31991.14 32099.05 8986.64 24899.92 2593.38 22799.47 9997.73 223
VDD-MVS95.82 16595.23 17697.61 16398.84 13693.98 23998.68 13997.40 30495.02 14697.95 11299.34 3574.37 35699.78 10098.64 896.80 19499.08 161
UniMVSNet (Re)95.78 16695.19 17897.58 16496.99 27397.47 8998.79 11899.18 1795.60 11193.92 25197.04 28191.68 13898.48 26295.80 15387.66 32896.79 267
VPA-MVSNet95.75 16795.11 18297.69 15697.24 25497.27 9698.94 8399.23 1395.13 13895.51 19997.32 25685.73 26398.91 22197.33 8889.55 30496.89 257
HQP-MVS95.72 16895.40 16396.69 21597.20 25894.25 23498.05 23198.46 17996.43 8094.45 22397.73 22586.75 24698.96 21495.30 16994.18 23596.86 262
hse-mvs295.71 16995.30 17496.93 19898.50 16293.53 25698.36 18798.10 24597.48 2098.67 6797.99 20089.76 17699.02 20697.95 4580.91 35698.22 209
UniMVSNet_NR-MVSNet95.71 16995.15 17997.40 17496.84 28296.97 10998.74 12399.24 1195.16 13693.88 25397.72 22791.68 13898.31 28995.81 15187.25 33396.92 249
PatchmatchNetpermissive95.71 16995.52 16196.29 25597.58 22890.72 31096.84 32397.52 29394.06 18097.08 14996.96 29089.24 18898.90 22492.03 26898.37 15599.26 135
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
OPM-MVS95.69 17295.33 17196.76 20996.16 31494.63 21598.43 17998.39 19396.64 7295.02 20698.78 12485.15 27399.05 19995.21 17594.20 23496.60 291
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMM93.85 995.69 17295.38 16796.61 22397.61 22593.84 24398.91 8798.44 18395.25 13294.28 23498.47 15586.04 26199.12 18995.50 16593.95 24496.87 260
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
tpmrst95.63 17495.69 15695.44 28797.54 23388.54 34396.97 30997.56 28693.50 21597.52 14096.93 29489.49 18099.16 18195.25 17396.42 20798.64 193
LPG-MVS_test95.62 17595.34 16996.47 24097.46 23993.54 25498.99 7398.54 16094.67 16194.36 23098.77 12685.39 26899.11 19295.71 15894.15 23796.76 271
CLD-MVS95.62 17595.34 16996.46 24397.52 23693.75 24797.27 29398.46 17995.53 11494.42 22898.00 19986.21 25698.97 21096.25 13794.37 22996.66 286
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
thisisatest051595.61 17794.89 19297.76 14998.15 19395.15 19196.77 32594.41 35992.95 23797.18 14697.43 25184.78 27999.45 16194.63 18697.73 17898.68 188
thres600view795.49 17894.77 19597.67 15898.98 12595.02 19698.85 10096.90 32795.38 12396.63 17196.90 29584.29 28699.59 13788.65 31996.33 20998.40 202
SCA95.46 17995.13 18096.46 24397.67 22191.29 30097.33 28897.60 28494.68 16096.92 15997.10 26883.97 29598.89 22592.59 25298.32 15999.20 139
IterMVS-LS95.46 17995.21 17796.22 25798.12 19493.72 25098.32 19698.13 23993.71 20294.26 23597.31 25792.24 12498.10 30694.63 18690.12 29596.84 263
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
jajsoiax95.45 18195.03 18596.73 21195.42 33894.63 21599.14 4398.52 16495.74 10493.22 27798.36 16783.87 29898.65 24896.95 10194.04 24096.91 254
CVMVSNet95.43 18296.04 14193.57 32697.93 20683.62 36198.12 22598.59 14895.68 10796.56 17499.02 9087.51 23297.51 33693.56 22597.44 18499.60 85
anonymousdsp95.42 18394.91 19196.94 19795.10 34095.90 16499.14 4398.41 18993.75 19793.16 27997.46 24787.50 23498.41 27895.63 16294.03 24196.50 310
DU-MVS95.42 18394.76 19697.40 17496.53 29796.97 10998.66 14598.99 3095.43 12093.88 25397.69 22888.57 20698.31 28995.81 15187.25 33396.92 249
mvs_tets95.41 18595.00 18696.65 21795.58 33194.42 22699.00 7198.55 15895.73 10593.21 27898.38 16583.45 30298.63 24997.09 9494.00 24296.91 254
thres100view90095.38 18694.70 19997.41 17298.98 12594.92 20498.87 9796.90 32795.38 12396.61 17296.88 29684.29 28699.56 14288.11 32096.29 21197.76 220
thres40095.38 18694.62 20297.65 16198.94 12794.98 20098.68 13996.93 32595.33 12696.55 17696.53 31284.23 28999.56 14288.11 32096.29 21198.40 202
BH-w/o95.38 18695.08 18396.26 25698.34 17591.79 28797.70 26397.43 30292.87 24194.24 23797.22 26388.66 20498.84 23191.55 27897.70 17998.16 212
VDDNet95.36 18994.53 20697.86 14098.10 19695.13 19398.85 10097.75 27690.46 30998.36 8799.39 1873.27 35899.64 13097.98 4496.58 20198.81 180
TAPA-MVS93.98 795.35 19094.56 20597.74 15199.13 11094.83 20898.33 19198.64 14186.62 34296.29 18798.61 14094.00 10399.29 17080.00 35799.41 10699.09 157
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP93.49 1095.34 19194.98 18896.43 24597.67 22193.48 25898.73 12798.44 18394.94 15292.53 29998.53 14984.50 28599.14 18695.48 16694.00 24296.66 286
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
COLMAP_ROBcopyleft93.27 1295.33 19294.87 19396.71 21299.29 8293.24 26898.58 15598.11 24389.92 32093.57 26499.10 7886.37 25499.79 9690.78 28898.10 16497.09 238
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
tfpn200view995.32 19394.62 20297.43 17198.94 12794.98 20098.68 13996.93 32595.33 12696.55 17696.53 31284.23 28999.56 14288.11 32096.29 21197.76 220
Anonymous20240521195.28 19494.49 20897.67 15899.00 12193.75 24798.70 13697.04 31890.66 30596.49 18198.80 12278.13 33599.83 6096.21 13895.36 22799.44 114
thres20095.25 19594.57 20497.28 17798.81 13894.92 20498.20 21197.11 31495.24 13496.54 17896.22 32484.58 28399.53 14887.93 32496.50 20597.39 231
AllTest95.24 19694.65 20196.99 19299.25 9093.21 26998.59 15398.18 22891.36 28893.52 26698.77 12684.67 28199.72 11389.70 30697.87 17198.02 215
LCM-MVSNet-Re95.22 19795.32 17294.91 30198.18 19087.85 35298.75 12095.66 34895.11 14088.96 33896.85 29990.26 17197.65 33095.65 16198.44 15299.22 138
EPNet_dtu95.21 19894.95 19095.99 26596.17 31290.45 31598.16 22197.27 31096.77 6693.14 28298.33 17390.34 16898.42 27185.57 33798.81 13699.09 157
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
XXY-MVS95.20 19994.45 21397.46 16996.75 28796.56 12998.86 9998.65 14093.30 22493.27 27698.27 18084.85 27898.87 22894.82 18291.26 28396.96 246
D2MVS95.18 20095.08 18395.48 28497.10 26792.07 28298.30 19999.13 2094.02 18392.90 28796.73 30389.48 18198.73 24194.48 19593.60 25295.65 337
WR-MVS95.15 20194.46 21197.22 17996.67 29296.45 13398.21 20898.81 8094.15 17793.16 27997.69 22887.51 23298.30 29195.29 17188.62 31896.90 256
TranMVSNet+NR-MVSNet95.14 20294.48 20997.11 18796.45 30296.36 13899.03 6399.03 2695.04 14593.58 26397.93 20688.27 21398.03 31394.13 20686.90 33896.95 248
baseline295.11 20394.52 20796.87 20396.65 29393.56 25398.27 20494.10 36593.45 21792.02 31397.43 25187.45 23699.19 17993.88 21497.41 18697.87 218
miper_enhance_ethall95.10 20494.75 19796.12 26297.53 23593.73 24996.61 33198.08 25292.20 26793.89 25296.65 30892.44 11998.30 29194.21 20491.16 28496.34 318
Anonymous2024052995.10 20494.22 22397.75 15099.01 12094.26 23398.87 9798.83 7285.79 35096.64 17098.97 9778.73 33099.85 5496.27 13594.89 22899.12 154
test-LLR95.10 20494.87 19395.80 27596.77 28489.70 32396.91 31495.21 35195.11 14094.83 21295.72 33587.71 22898.97 21093.06 23798.50 14998.72 184
WR-MVS_H95.05 20794.46 21196.81 20796.86 28195.82 16799.24 2699.24 1193.87 19292.53 29996.84 30090.37 16798.24 29893.24 23287.93 32596.38 317
miper_ehance_all_eth95.01 20894.69 20095.97 26797.70 22093.31 26597.02 30798.07 25492.23 26493.51 26896.96 29091.85 13598.15 30293.68 21991.16 28496.44 315
ADS-MVSNet95.00 20994.45 21396.63 22198.00 20191.91 28596.04 33897.74 27790.15 31596.47 18296.64 30987.89 22498.96 21490.08 29797.06 18999.02 165
VPNet94.99 21094.19 22597.40 17497.16 26396.57 12898.71 13298.97 3195.67 10894.84 21098.24 18380.36 32198.67 24696.46 12987.32 33296.96 246
EPMVS94.99 21094.48 20996.52 23697.22 25691.75 28997.23 29491.66 37194.11 17897.28 14296.81 30185.70 26498.84 23193.04 23997.28 18798.97 170
NR-MVSNet94.98 21294.16 22897.44 17096.53 29797.22 10298.74 12398.95 3594.96 14989.25 33797.69 22889.32 18598.18 30094.59 19187.40 33196.92 249
FMVSNet394.97 21394.26 22297.11 18798.18 19096.62 12398.56 16198.26 21993.67 20994.09 24497.10 26884.25 28898.01 31492.08 26492.14 26996.70 280
CostFormer94.95 21494.73 19895.60 28297.28 25289.06 33497.53 27496.89 32989.66 32596.82 16496.72 30486.05 25998.95 21895.53 16496.13 22098.79 181
PAPM94.95 21494.00 23897.78 14797.04 27095.65 17196.03 34098.25 22091.23 29794.19 24097.80 22291.27 15198.86 23082.61 35197.61 18198.84 179
CP-MVSNet94.94 21694.30 22096.83 20596.72 28995.56 17499.11 4998.95 3593.89 19092.42 30597.90 20887.19 23898.12 30594.32 20088.21 32296.82 266
TR-MVS94.94 21694.20 22497.17 18397.75 21594.14 23697.59 27197.02 32192.28 26395.75 19897.64 23483.88 29798.96 21489.77 30396.15 21998.40 202
bset_n11_16_dypcd94.89 21894.27 22196.76 20994.41 34995.15 19195.67 34595.64 34995.53 11494.65 21697.52 24487.10 23998.29 29496.58 12691.35 27996.83 265
RPSCF94.87 21995.40 16393.26 33298.89 13082.06 36698.33 19198.06 25990.30 31496.56 17499.26 4787.09 24099.49 15393.82 21696.32 21098.24 208
test_part194.82 22093.82 25197.82 14498.84 13697.82 7799.03 6398.81 8092.31 26292.51 30197.89 21081.96 30798.67 24694.80 18488.24 32196.98 244
DWT-MVSNet_test94.82 22094.36 21896.20 25897.35 24990.79 30898.34 18996.57 34092.91 23995.33 20296.44 31682.00 30699.12 18994.52 19395.78 22598.70 186
GA-MVS94.81 22294.03 23497.14 18497.15 26493.86 24296.76 32697.58 28594.00 18594.76 21597.04 28180.91 31698.48 26291.79 27396.25 21699.09 157
c3_l94.79 22394.43 21595.89 27297.75 21593.12 27297.16 30198.03 26192.23 26493.46 27197.05 28091.39 14698.01 31493.58 22489.21 31096.53 302
V4294.78 22494.14 23096.70 21496.33 30795.22 18898.97 7798.09 25092.32 26094.31 23397.06 27888.39 21198.55 25792.90 24488.87 31696.34 318
CR-MVSNet94.76 22594.15 22996.59 22697.00 27193.43 25994.96 35197.56 28692.46 25196.93 15796.24 32088.15 21797.88 32687.38 32696.65 19998.46 200
v2v48294.69 22694.03 23496.65 21796.17 31294.79 21198.67 14298.08 25292.72 24494.00 24997.16 26687.69 23198.45 26792.91 24388.87 31696.72 276
pmmvs494.69 22693.99 24096.81 20795.74 32695.94 15897.40 27997.67 27990.42 31193.37 27397.59 23889.08 19398.20 29992.97 24191.67 27696.30 322
cl2294.68 22894.19 22596.13 26198.11 19593.60 25296.94 31198.31 20692.43 25593.32 27596.87 29886.51 24998.28 29694.10 20991.16 28496.51 308
eth_miper_zixun_eth94.68 22894.41 21695.47 28597.64 22391.71 29196.73 32898.07 25492.71 24593.64 26197.21 26490.54 16598.17 30193.38 22789.76 29996.54 300
PCF-MVS93.45 1194.68 22893.43 27398.42 10698.62 15596.77 11895.48 34998.20 22484.63 35493.34 27498.32 17488.55 20899.81 7584.80 34498.96 12698.68 188
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MVS94.67 23193.54 26998.08 12996.88 28096.56 12998.19 21598.50 17278.05 36292.69 29498.02 19691.07 15699.63 13390.09 29698.36 15798.04 214
PS-CasMVS94.67 23193.99 24096.71 21296.68 29195.26 18799.13 4699.03 2693.68 20792.33 30697.95 20485.35 27098.10 30693.59 22388.16 32496.79 267
cascas94.63 23393.86 24996.93 19896.91 27894.27 23296.00 34198.51 16785.55 35194.54 21996.23 32284.20 29198.87 22895.80 15396.98 19297.66 226
tpmvs94.60 23494.36 21895.33 29097.46 23988.60 34296.88 32097.68 27891.29 29493.80 25896.42 31788.58 20599.24 17491.06 28396.04 22298.17 211
LTVRE_ROB92.95 1594.60 23493.90 24696.68 21697.41 24794.42 22698.52 16598.59 14891.69 27991.21 31998.35 16884.87 27799.04 20291.06 28393.44 25696.60 291
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 23693.92 24396.60 22596.21 30994.78 21298.59 15398.14 23891.86 27594.21 23997.02 28387.97 22298.41 27891.72 27589.57 30296.61 290
ADS-MVSNet294.58 23794.40 21795.11 29698.00 20188.74 34096.04 33897.30 30790.15 31596.47 18296.64 30987.89 22497.56 33490.08 29797.06 18999.02 165
RRT_test8_iter0594.56 23894.19 22595.67 28097.60 22691.34 29698.93 8598.42 18894.75 15693.39 27297.87 21279.00 32998.61 25096.78 11990.99 28797.07 239
ACMH92.88 1694.55 23993.95 24296.34 25297.63 22493.26 26798.81 11398.49 17793.43 21889.74 33298.53 14981.91 30899.08 19793.69 21893.30 25996.70 280
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
XVG-ACMP-BASELINE94.54 24094.14 23095.75 27896.55 29691.65 29298.11 22798.44 18394.96 14994.22 23897.90 20879.18 32899.11 19294.05 21193.85 24696.48 312
AUN-MVS94.53 24193.73 26096.92 20198.50 16293.52 25798.34 18998.10 24593.83 19595.94 19797.98 20285.59 26699.03 20394.35 19880.94 35598.22 209
DIV-MVS_self_test94.52 24294.03 23495.99 26597.57 23293.38 26397.05 30597.94 26791.74 27692.81 28997.10 26889.12 19198.07 31092.60 25090.30 29396.53 302
cl____94.51 24394.01 23796.02 26497.58 22893.40 26297.05 30597.96 26691.73 27892.76 29197.08 27489.06 19498.13 30492.61 24990.29 29496.52 305
GBi-Net94.49 24493.80 25396.56 23098.21 18595.00 19798.82 10798.18 22892.46 25194.09 24497.07 27581.16 31397.95 31892.08 26492.14 26996.72 276
test194.49 24493.80 25396.56 23098.21 18595.00 19798.82 10798.18 22892.46 25194.09 24497.07 27581.16 31397.95 31892.08 26492.14 26996.72 276
v894.47 24693.77 25696.57 22996.36 30594.83 20899.05 5998.19 22591.92 27293.16 27996.97 28888.82 20398.48 26291.69 27687.79 32696.39 316
FMVSNet294.47 24693.61 26697.04 19098.21 18596.43 13598.79 11898.27 21592.46 25193.50 26997.09 27281.16 31398.00 31691.09 28191.93 27296.70 280
test250694.44 24893.91 24596.04 26399.02 11888.99 33799.06 5779.47 38096.96 5898.36 8799.26 4777.21 34399.52 15196.78 11999.04 12199.59 87
Patchmatch-test94.42 24993.68 26496.63 22197.60 22691.76 28894.83 35597.49 29789.45 32894.14 24297.10 26888.99 19598.83 23385.37 34098.13 16399.29 132
PEN-MVS94.42 24993.73 26096.49 23896.28 30894.84 20699.17 3999.00 2893.51 21492.23 30897.83 21986.10 25897.90 32292.55 25586.92 33796.74 273
v14419294.39 25193.70 26296.48 23996.06 31794.35 23098.58 15598.16 23591.45 28594.33 23297.02 28387.50 23498.45 26791.08 28289.11 31196.63 288
Baseline_NR-MVSNet94.35 25293.81 25295.96 26896.20 31094.05 23898.61 15296.67 33891.44 28693.85 25597.60 23788.57 20698.14 30394.39 19686.93 33695.68 336
miper_lstm_enhance94.33 25394.07 23395.11 29697.75 21590.97 30497.22 29598.03 26191.67 28092.76 29196.97 28890.03 17397.78 32892.51 25789.64 30196.56 297
v119294.32 25493.58 26796.53 23596.10 31594.45 22498.50 17098.17 23391.54 28394.19 24097.06 27886.95 24498.43 27090.14 29589.57 30296.70 280
ACMH+92.99 1494.30 25593.77 25695.88 27397.81 21392.04 28498.71 13298.37 19793.99 18690.60 32698.47 15580.86 31899.05 19992.75 24892.40 26896.55 299
v14894.29 25693.76 25895.91 27096.10 31592.93 27498.58 15597.97 26492.59 24993.47 27096.95 29288.53 20998.32 28792.56 25487.06 33596.49 311
v1094.29 25693.55 26896.51 23796.39 30494.80 21098.99 7398.19 22591.35 29093.02 28596.99 28688.09 21998.41 27890.50 29288.41 32096.33 320
MVP-Stereo94.28 25893.92 24395.35 28994.95 34292.60 27797.97 23997.65 28091.61 28290.68 32597.09 27286.32 25598.42 27189.70 30699.34 11195.02 348
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
UniMVSNet_ETH3D94.24 25993.33 27596.97 19597.19 26193.38 26398.74 12398.57 15491.21 29993.81 25798.58 14572.85 35998.77 23995.05 17793.93 24598.77 183
OurMVSNet-221017-094.21 26094.00 23894.85 30495.60 33089.22 33298.89 9297.43 30295.29 12992.18 30998.52 15282.86 30398.59 25493.46 22691.76 27496.74 273
v192192094.20 26193.47 27296.40 24895.98 32094.08 23798.52 16598.15 23691.33 29194.25 23697.20 26586.41 25398.42 27190.04 30089.39 30896.69 285
v7n94.19 26293.43 27396.47 24095.90 32294.38 22999.26 2498.34 20291.99 27092.76 29197.13 26788.31 21298.52 26089.48 31187.70 32796.52 305
tpm294.19 26293.76 25895.46 28697.23 25589.04 33597.31 29096.85 33387.08 34196.21 18996.79 30283.75 30198.74 24092.43 26096.23 21798.59 195
TESTMET0.1,194.18 26493.69 26395.63 28196.92 27689.12 33396.91 31494.78 35693.17 22894.88 20996.45 31578.52 33198.92 22093.09 23698.50 14998.85 177
dp94.15 26593.90 24694.90 30297.31 25186.82 35796.97 30997.19 31391.22 29896.02 19496.61 31185.51 26799.02 20690.00 30194.30 23098.85 177
ET-MVSNet_ETH3D94.13 26692.98 28197.58 16498.22 18496.20 14497.31 29095.37 35094.53 16679.56 36297.63 23686.51 24997.53 33596.91 10290.74 28999.02 165
tpm94.13 26693.80 25395.12 29596.50 29987.91 35197.44 27695.89 34792.62 24796.37 18696.30 31984.13 29298.30 29193.24 23291.66 27799.14 152
IterMVS-SCA-FT94.11 26893.87 24894.85 30497.98 20590.56 31497.18 29898.11 24393.75 19792.58 29797.48 24683.97 29597.41 33792.48 25991.30 28196.58 293
Anonymous2023121194.10 26993.26 27896.61 22399.11 11294.28 23199.01 6998.88 5186.43 34492.81 28997.57 24081.66 31098.68 24594.83 18189.02 31496.88 258
IterMVS94.09 27093.85 25094.80 30797.99 20390.35 31697.18 29898.12 24093.68 20792.46 30497.34 25484.05 29397.41 33792.51 25791.33 28096.62 289
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test-mter94.08 27193.51 27095.80 27596.77 28489.70 32396.91 31495.21 35192.89 24094.83 21295.72 33577.69 33898.97 21093.06 23798.50 14998.72 184
test0.0.03 194.08 27193.51 27095.80 27595.53 33392.89 27597.38 28195.97 34495.11 14092.51 30196.66 30687.71 22896.94 34487.03 32893.67 24897.57 227
v124094.06 27393.29 27796.34 25296.03 31993.90 24198.44 17798.17 23391.18 30094.13 24397.01 28586.05 25998.42 27189.13 31689.50 30696.70 280
X-MVStestdata94.06 27392.30 29399.34 2699.70 2498.35 4899.29 2098.88 5197.40 2798.46 7943.50 37395.90 4499.89 3997.85 5499.74 4599.78 16
DTE-MVSNet93.98 27593.26 27896.14 26096.06 31794.39 22899.20 3598.86 6493.06 23291.78 31497.81 22185.87 26297.58 33390.53 29186.17 34296.46 314
pm-mvs193.94 27693.06 28096.59 22696.49 30095.16 18998.95 8198.03 26192.32 26091.08 32197.84 21684.54 28498.41 27892.16 26286.13 34496.19 325
MS-PatchMatch93.84 27793.63 26594.46 31896.18 31189.45 32897.76 25998.27 21592.23 26492.13 31097.49 24579.50 32598.69 24289.75 30499.38 10995.25 341
tfpnnormal93.66 27892.70 28796.55 23496.94 27595.94 15898.97 7799.19 1691.04 30291.38 31897.34 25484.94 27698.61 25085.45 33989.02 31495.11 345
EU-MVSNet93.66 27894.14 23092.25 33995.96 32183.38 36298.52 16598.12 24094.69 15992.61 29698.13 19087.36 23796.39 35591.82 27290.00 29796.98 244
our_test_393.65 28093.30 27694.69 30995.45 33689.68 32596.91 31497.65 28091.97 27191.66 31696.88 29689.67 17997.93 32188.02 32391.49 27896.48 312
pmmvs593.65 28092.97 28295.68 27995.49 33492.37 27898.20 21197.28 30989.66 32592.58 29797.26 25982.14 30598.09 30893.18 23590.95 28896.58 293
tpm cat193.36 28292.80 28495.07 29897.58 22887.97 35096.76 32697.86 27282.17 35893.53 26596.04 32886.13 25799.13 18789.24 31495.87 22398.10 213
JIA-IIPM93.35 28392.49 29095.92 26996.48 30190.65 31295.01 35096.96 32385.93 34896.08 19287.33 36487.70 23098.78 23891.35 28095.58 22698.34 205
SixPastTwentyTwo93.34 28492.86 28394.75 30895.67 32889.41 33098.75 12096.67 33893.89 19090.15 33098.25 18280.87 31798.27 29790.90 28690.64 29096.57 295
USDC93.33 28592.71 28695.21 29296.83 28390.83 30796.91 31497.50 29593.84 19390.72 32498.14 18977.69 33898.82 23489.51 31093.21 26195.97 330
IB-MVS91.98 1793.27 28691.97 29797.19 18197.47 23893.41 26197.09 30495.99 34393.32 22292.47 30395.73 33378.06 33699.53 14894.59 19182.98 34798.62 194
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 28792.21 29496.41 24697.73 21993.13 27195.65 34697.03 31991.27 29694.04 24796.06 32775.33 35097.19 34086.56 33096.23 21798.92 175
ppachtmachnet_test93.22 28892.63 28894.97 30095.45 33690.84 30696.88 32097.88 27190.60 30692.08 31197.26 25988.08 22097.86 32785.12 34190.33 29296.22 323
Patchmtry93.22 28892.35 29295.84 27496.77 28493.09 27394.66 35697.56 28687.37 34092.90 28796.24 32088.15 21797.90 32287.37 32790.10 29696.53 302
FMVSNet193.19 29092.07 29596.56 23097.54 23395.00 19798.82 10798.18 22890.38 31292.27 30797.07 27573.68 35797.95 31889.36 31391.30 28196.72 276
LF4IMVS93.14 29192.79 28594.20 32195.88 32388.67 34197.66 26697.07 31693.81 19691.71 31597.65 23277.96 33798.81 23591.47 27991.92 27395.12 344
testgi93.06 29292.45 29194.88 30396.43 30389.90 32098.75 12097.54 29295.60 11191.63 31797.91 20774.46 35597.02 34286.10 33393.67 24897.72 224
PatchT93.06 29291.97 29796.35 25196.69 29092.67 27694.48 35797.08 31586.62 34297.08 14992.23 35987.94 22397.90 32278.89 36196.69 19798.49 199
MVS_030492.81 29492.01 29695.23 29197.46 23991.33 29898.17 22098.81 8091.13 30193.80 25895.68 33866.08 36698.06 31190.79 28796.13 22096.32 321
RPMNet92.81 29491.34 30297.24 17897.00 27193.43 25994.96 35198.80 9182.27 35796.93 15792.12 36086.98 24399.82 6876.32 36596.65 19998.46 200
TransMVSNet (Re)92.67 29691.51 30196.15 25996.58 29594.65 21398.90 8896.73 33490.86 30489.46 33697.86 21385.62 26598.09 30886.45 33181.12 35395.71 335
K. test v392.55 29791.91 29994.48 31695.64 32989.24 33199.07 5694.88 35594.04 18186.78 34897.59 23877.64 34197.64 33192.08 26489.43 30796.57 295
DSMNet-mixed92.52 29892.58 28992.33 33794.15 35182.65 36498.30 19994.26 36289.08 33292.65 29595.73 33385.01 27595.76 35886.24 33297.76 17698.59 195
TinyColmap92.31 29991.53 30094.65 31196.92 27689.75 32296.92 31296.68 33790.45 31089.62 33397.85 21576.06 34898.81 23586.74 32992.51 26795.41 339
gg-mvs-nofinetune92.21 30090.58 30797.13 18596.75 28795.09 19495.85 34289.40 37485.43 35294.50 22181.98 36780.80 31998.40 28492.16 26298.33 15897.88 217
FMVSNet591.81 30190.92 30494.49 31597.21 25792.09 28198.00 23797.55 29189.31 33090.86 32395.61 33974.48 35495.32 36185.57 33789.70 30096.07 328
pmmvs691.77 30290.63 30695.17 29494.69 34891.24 30198.67 14297.92 26986.14 34689.62 33397.56 24275.79 34998.34 28590.75 28984.56 34695.94 331
Anonymous2023120691.66 30391.10 30393.33 33094.02 35587.35 35498.58 15597.26 31190.48 30890.16 32996.31 31883.83 29996.53 35379.36 35989.90 29896.12 326
Patchmatch-RL test91.49 30490.85 30593.41 32891.37 36484.40 35992.81 36195.93 34691.87 27487.25 34694.87 34588.99 19596.53 35392.54 25682.00 34999.30 130
test_040291.32 30590.27 31094.48 31696.60 29491.12 30298.50 17097.22 31286.10 34788.30 34396.98 28777.65 34097.99 31778.13 36392.94 26494.34 352
PVSNet_088.72 1991.28 30690.03 31295.00 29997.99 20387.29 35594.84 35498.50 17292.06 26989.86 33195.19 34179.81 32499.39 16492.27 26169.79 36698.33 206
Anonymous2024052191.18 30790.44 30893.42 32793.70 35688.47 34498.94 8397.56 28688.46 33589.56 33595.08 34477.15 34596.97 34383.92 34789.55 30494.82 350
EG-PatchMatch MVS91.13 30890.12 31194.17 32394.73 34789.00 33698.13 22497.81 27389.22 33185.32 35596.46 31467.71 36398.42 27187.89 32593.82 24795.08 346
TDRefinement91.06 30989.68 31495.21 29285.35 37191.49 29598.51 16997.07 31691.47 28488.83 34197.84 21677.31 34299.09 19692.79 24777.98 35995.04 347
UnsupCasMVSNet_eth90.99 31089.92 31394.19 32294.08 35289.83 32197.13 30398.67 13393.69 20585.83 35396.19 32575.15 35196.74 34789.14 31579.41 35796.00 329
test20.0390.89 31190.38 30992.43 33693.48 35788.14 34998.33 19197.56 28693.40 21987.96 34496.71 30580.69 32094.13 36679.15 36086.17 34295.01 349
MDA-MVSNet_test_wron90.71 31289.38 31794.68 31094.83 34490.78 30997.19 29797.46 29887.60 33872.41 36795.72 33586.51 24996.71 35085.92 33586.80 33996.56 297
YYNet190.70 31389.39 31694.62 31294.79 34690.65 31297.20 29697.46 29887.54 33972.54 36695.74 33186.51 24996.66 35186.00 33486.76 34096.54 300
KD-MVS_self_test90.38 31489.38 31793.40 32992.85 36088.94 33897.95 24097.94 26790.35 31390.25 32893.96 35279.82 32395.94 35784.62 34676.69 36195.33 340
pmmvs-eth3d90.36 31589.05 32094.32 32091.10 36592.12 28097.63 27096.95 32488.86 33384.91 35693.13 35578.32 33296.74 34788.70 31881.81 35194.09 356
CL-MVSNet_self_test90.11 31689.14 31993.02 33491.86 36388.23 34896.51 33498.07 25490.49 30790.49 32794.41 34784.75 28095.34 36080.79 35574.95 36395.50 338
new_pmnet90.06 31789.00 32193.22 33394.18 35088.32 34796.42 33696.89 32986.19 34585.67 35493.62 35377.18 34497.10 34181.61 35389.29 30994.23 353
MDA-MVSNet-bldmvs89.97 31888.35 32394.83 30695.21 33991.34 29697.64 26797.51 29488.36 33671.17 36896.13 32679.22 32796.63 35283.65 34886.27 34196.52 305
CMPMVSbinary66.06 2189.70 31989.67 31589.78 34393.19 35876.56 36897.00 30898.35 20080.97 35981.57 36097.75 22474.75 35398.61 25089.85 30293.63 25094.17 354
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MIMVSNet189.67 32088.28 32493.82 32492.81 36191.08 30398.01 23597.45 30087.95 33787.90 34595.87 33067.63 36494.56 36578.73 36288.18 32395.83 333
KD-MVS_2432*160089.61 32187.96 32594.54 31394.06 35391.59 29395.59 34797.63 28289.87 32188.95 33994.38 34978.28 33396.82 34584.83 34268.05 36795.21 342
miper_refine_blended89.61 32187.96 32594.54 31394.06 35391.59 29395.59 34797.63 28289.87 32188.95 33994.38 34978.28 33396.82 34584.83 34268.05 36795.21 342
MVS-HIRNet89.46 32388.40 32292.64 33597.58 22882.15 36594.16 36093.05 36875.73 36490.90 32282.52 36679.42 32698.33 28683.53 34998.68 13897.43 228
OpenMVS_ROBcopyleft86.42 2089.00 32487.43 32993.69 32593.08 35989.42 32997.91 24496.89 32978.58 36185.86 35294.69 34669.48 36198.29 29477.13 36493.29 26093.36 361
new-patchmatchnet88.50 32587.45 32891.67 34190.31 36785.89 35897.16 30197.33 30689.47 32783.63 35892.77 35676.38 34695.06 36382.70 35077.29 36094.06 357
PM-MVS87.77 32686.55 33091.40 34291.03 36683.36 36396.92 31295.18 35391.28 29586.48 35193.42 35453.27 37096.74 34789.43 31281.97 35094.11 355
UnsupCasMVSNet_bld87.17 32785.12 33193.31 33191.94 36288.77 33994.92 35398.30 21284.30 35582.30 35990.04 36163.96 36897.25 33985.85 33674.47 36593.93 359
N_pmnet87.12 32887.77 32785.17 34895.46 33561.92 37597.37 28370.66 38185.83 34988.73 34296.04 32885.33 27297.76 32980.02 35690.48 29195.84 332
pmmvs386.67 32984.86 33292.11 34088.16 36887.19 35696.63 33094.75 35779.88 36087.22 34792.75 35766.56 36595.20 36281.24 35476.56 36293.96 358
test_method79.03 33078.17 33381.63 35086.06 37054.40 38082.75 36996.89 32939.54 37380.98 36195.57 34058.37 36994.73 36484.74 34578.61 35895.75 334
LCM-MVSNet78.70 33176.24 33686.08 34677.26 37771.99 37294.34 35896.72 33561.62 36876.53 36389.33 36233.91 37792.78 36881.85 35274.60 36493.46 360
Gipumacopyleft78.40 33276.75 33583.38 34995.54 33280.43 36779.42 37097.40 30464.67 36773.46 36580.82 36845.65 37293.14 36766.32 36987.43 33076.56 370
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMMVS277.95 33375.44 33785.46 34782.54 37274.95 37094.23 35993.08 36772.80 36574.68 36487.38 36336.36 37691.56 36973.95 36663.94 36989.87 364
FPMVS77.62 33477.14 33479.05 35279.25 37560.97 37695.79 34395.94 34565.96 36667.93 36994.40 34837.73 37588.88 37168.83 36888.46 31987.29 365
EGC-MVSNET75.22 33569.54 33892.28 33894.81 34589.58 32697.64 26796.50 3411.82 3785.57 37995.74 33168.21 36296.26 35673.80 36791.71 27590.99 363
ANet_high69.08 33665.37 34080.22 35165.99 37971.96 37390.91 36590.09 37382.62 35649.93 37478.39 36929.36 37881.75 37262.49 37038.52 37386.95 367
tmp_tt68.90 33766.97 33974.68 35450.78 38159.95 37787.13 36683.47 37838.80 37462.21 37096.23 32264.70 36776.91 37688.91 31730.49 37487.19 366
PMVScopyleft61.03 2365.95 33863.57 34273.09 35557.90 38051.22 38185.05 36893.93 36654.45 36944.32 37583.57 36513.22 37989.15 37058.68 37181.00 35478.91 369
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
E-PMN64.94 33964.25 34167.02 35682.28 37359.36 37891.83 36485.63 37652.69 37060.22 37177.28 37041.06 37480.12 37446.15 37341.14 37161.57 372
EMVS64.07 34063.26 34366.53 35781.73 37458.81 37991.85 36384.75 37751.93 37259.09 37275.13 37143.32 37379.09 37542.03 37439.47 37261.69 371
MVEpermissive62.14 2263.28 34159.38 34474.99 35374.33 37865.47 37485.55 36780.50 37952.02 37151.10 37375.00 37210.91 38280.50 37351.60 37253.40 37078.99 368
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuyk23d30.17 34230.18 34630.16 35878.61 37643.29 38266.79 37114.21 38217.31 37514.82 37811.93 37811.55 38141.43 37737.08 37519.30 3755.76 375
cdsmvs_eth3d_5k23.98 34331.98 3450.00 3610.00 3840.00 3850.00 37298.59 1480.00 3790.00 38098.61 14090.60 1640.00 3800.00 3780.00 3780.00 376
testmvs21.48 34424.95 34711.09 36014.89 3826.47 38496.56 3329.87 3837.55 37617.93 37639.02 3749.43 3835.90 37916.56 37712.72 37620.91 374
test12320.95 34523.72 34812.64 35913.54 3838.19 38396.55 3336.13 3847.48 37716.74 37737.98 37512.97 3806.05 37816.69 3765.43 37723.68 373
ab-mvs-re8.20 34610.94 3490.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 38098.43 1580.00 3840.00 3800.00 3780.00 3780.00 376
pcd_1.5k_mvsjas7.88 34710.50 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 37994.51 910.00 3800.00 3780.00 3780.00 376
test_blank0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
uanet_test0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
DCPMVS0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
sosnet-low-res0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
sosnet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
uncertanet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
Regformer0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
uanet0.00 3480.00 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.00 3790.00 3840.00 3800.00 3780.00 3780.00 376
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 14499.60 599.16 6897.86 298.47 26597.52 8199.72 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-test20.00 384
eth-test0.00 384
ZD-MVS99.46 5598.70 2398.79 9693.21 22698.67 6798.97 9795.70 5099.83 6096.07 14099.58 80
RE-MVS-def98.34 3399.49 4997.86 7399.11 4998.80 9196.49 7899.17 3099.35 3295.29 6997.72 6299.65 6499.71 50
IU-MVS99.71 2199.23 798.64 14195.28 13099.63 498.35 3299.81 1299.83 7
OPU-MVS99.37 2399.24 9699.05 1499.02 6799.16 6897.81 399.37 16597.24 8999.73 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 13298.82 7494.36 17399.16 3299.29 4396.05 3699.81 7597.00 9699.71 56
save fliter99.46 5598.38 4098.21 20898.71 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 7798.88 5199.94 498.47 2299.81 1299.84 6
test072699.72 1399.25 299.06 5798.88 5197.62 1299.56 699.50 597.42 9
GSMVS99.20 139
test_part299.63 3199.18 1099.27 21
sam_mvs189.45 18299.20 139
sam_mvs88.99 195
ambc89.49 34486.66 36975.78 36992.66 36296.72 33586.55 35092.50 35846.01 37197.90 32290.32 29382.09 34894.80 351
MTGPAbinary98.74 108
test_post196.68 32930.43 37787.85 22798.69 24292.59 252
test_post31.83 37688.83 20298.91 221
patchmatchnet-post95.10 34389.42 18398.89 225
GG-mvs-BLEND96.59 22696.34 30694.98 20096.51 33488.58 37593.10 28494.34 35180.34 32298.05 31289.53 30996.99 19196.74 273
MTMP98.89 9294.14 364
gm-plane-assit95.88 32387.47 35389.74 32496.94 29399.19 17993.32 231
test9_res96.39 13499.57 8199.69 57
TEST999.31 7498.50 3497.92 24298.73 11292.63 24697.74 12598.68 13496.20 2799.80 84
test_899.29 8298.44 3697.89 24898.72 11492.98 23597.70 12898.66 13796.20 2799.80 84
agg_prior295.87 15099.57 8199.68 63
agg_prior99.30 7998.38 4098.72 11497.57 13899.81 75
TestCases96.99 19299.25 9093.21 26998.18 22891.36 28893.52 26698.77 12684.67 28199.72 11389.70 30697.87 17198.02 215
test_prior498.01 6797.86 251
test_prior297.80 25696.12 9297.89 11998.69 13295.96 4096.89 10699.60 74
test_prior99.19 4699.31 7498.22 5598.84 6999.70 11999.65 73
旧先验297.57 27391.30 29398.67 6799.80 8495.70 160
新几何297.64 267
新几何199.16 5399.34 6698.01 6798.69 12290.06 31898.13 9498.95 10594.60 8999.89 3991.97 27099.47 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 27298.72 11491.38 28799.87 4893.36 22999.60 85
原ACMM297.67 265
原ACMM198.65 8499.32 7296.62 12398.67 13393.27 22597.81 12198.97 9795.18 7599.83 6093.84 21599.46 10299.50 100
test22299.23 9797.17 10497.40 27998.66 13688.68 33498.05 9998.96 10394.14 10099.53 9299.61 82
testdata299.89 3991.65 277
segment_acmp96.85 14
testdata98.26 11699.20 10195.36 18298.68 12591.89 27398.60 7599.10 7894.44 9699.82 6894.27 20299.44 10499.58 91
testdata197.32 28996.34 84
test1299.18 5099.16 10798.19 5798.53 16298.07 9895.13 7799.72 11399.56 8699.63 79
plane_prior797.42 24494.63 215
plane_prior697.35 24994.61 21887.09 240
plane_prior598.56 15699.03 20396.07 14094.27 23196.92 249
plane_prior498.28 177
plane_prior394.61 21897.02 5595.34 200
plane_prior298.80 11497.28 36
plane_prior197.37 248
plane_prior94.60 22098.44 17796.74 6894.22 233
n20.00 385
nn0.00 385
door-mid94.37 360
lessismore_v094.45 31994.93 34388.44 34591.03 37286.77 34997.64 23476.23 34798.42 27190.31 29485.64 34596.51 308
LGP-MVS_train96.47 24097.46 23993.54 25498.54 16094.67 16194.36 23098.77 12685.39 26899.11 19295.71 15894.15 23796.76 271
test1198.66 136
door94.64 358
HQP5-MVS94.25 234
HQP-NCC97.20 25898.05 23196.43 8094.45 223
ACMP_Plane97.20 25898.05 23196.43 8094.45 223
BP-MVS95.30 169
HQP4-MVS94.45 22398.96 21496.87 260
HQP3-MVS98.46 17994.18 235
HQP2-MVS86.75 246
NP-MVS97.28 25294.51 22397.73 225
MDTV_nov1_ep13_2view84.26 36096.89 31990.97 30397.90 11889.89 17593.91 21399.18 148
MDTV_nov1_ep1395.40 16397.48 23788.34 34696.85 32297.29 30893.74 19997.48 14197.26 25989.18 18999.05 19991.92 27197.43 185
ACMMP++_ref92.97 263
ACMMP++93.61 251
Test By Simon94.64 87
ITE_SJBPF95.44 28797.42 24491.32 29997.50 29595.09 14393.59 26298.35 16881.70 30998.88 22789.71 30593.39 25796.12 326
DeepMVS_CXcopyleft86.78 34597.09 26872.30 37195.17 35475.92 36384.34 35795.19 34170.58 36095.35 35979.98 35889.04 31392.68 362