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
APDe-MVS99.66 199.57 399.92 199.77 5399.89 499.75 3399.56 5899.02 2199.88 699.85 3499.18 1099.96 2099.22 4499.92 1399.90 1
SED-MVS99.61 299.52 899.88 699.84 3399.90 299.60 7899.48 14799.08 1699.91 299.81 6799.20 799.96 2098.91 7699.85 6099.79 62
DVP-MVS++99.59 399.50 1099.88 699.51 16199.88 899.87 699.51 10698.99 3199.88 699.81 6799.27 599.96 2098.85 9099.80 8999.81 46
Regformer-499.59 399.54 699.73 6199.76 5799.41 10199.58 9399.49 13499.02 2199.88 699.80 8399.00 2599.94 5899.45 2299.92 1399.84 22
TSAR-MVS + MP.99.58 599.50 1099.81 4199.91 199.66 5999.63 6599.39 21898.91 4699.78 3599.85 3499.36 299.94 5898.84 9399.88 3899.82 40
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
EI-MVSNet-UG-set99.58 599.57 399.64 8099.78 4899.14 13399.60 7899.45 18799.01 2499.90 499.83 4798.98 2799.93 7399.59 699.95 899.86 15
EI-MVSNet-Vis-set99.58 599.56 599.64 8099.78 4899.15 13299.61 7799.45 18799.01 2499.89 599.82 5499.01 1999.92 8599.56 999.95 899.85 18
DVP-MVScopyleft99.57 899.47 1399.88 699.85 2699.89 499.57 9999.37 23399.10 1299.81 2599.80 8398.94 3599.96 2098.93 7399.86 5399.81 46
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
Regformer-399.57 899.53 799.68 6899.76 5799.29 11499.58 9399.44 19699.01 2499.87 1299.80 8398.97 2899.91 9699.44 2499.92 1399.83 33
Regformer-299.54 1099.47 1399.75 5499.71 9599.52 8899.49 14599.49 13498.94 4199.83 2099.76 11399.01 1999.94 5899.15 5399.87 4299.80 56
SteuartSystems-ACMMP99.54 1099.42 1799.87 1299.82 3999.81 2799.59 8599.51 10698.62 6799.79 3099.83 4799.28 499.97 1298.48 14799.90 2599.84 22
Skip Steuart: Steuart Systems R&D Blog.
Regformer-199.53 1299.47 1399.72 6499.71 9599.44 9899.49 14599.46 17598.95 4099.83 2099.76 11399.01 1999.93 7399.17 5099.87 4299.80 56
XVS99.53 1299.42 1799.87 1299.85 2699.83 1799.69 4299.68 1998.98 3499.37 14699.74 12498.81 4999.94 5898.79 10299.86 5399.84 22
MTAPA99.52 1499.39 2199.89 499.90 499.86 1399.66 5399.47 16598.79 5799.68 6299.81 6798.43 8799.97 1298.88 7999.90 2599.83 33
HPM-MVS_fast99.51 1599.40 2099.85 2899.91 199.79 3399.76 3199.56 5897.72 16599.76 4499.75 11899.13 1299.92 8599.07 6099.92 1399.85 18
CS-MVS99.50 1699.49 1299.52 10899.76 5799.35 10699.90 199.55 6798.56 7199.77 3799.70 14098.75 6099.77 17899.64 399.78 9699.42 181
zzz-MVS99.49 1799.36 2799.89 499.90 499.86 1399.36 20399.47 16598.79 5799.68 6299.81 6798.43 8799.97 1298.88 7999.90 2599.83 33
HFP-MVS99.49 1799.37 2599.86 2199.87 1699.80 2999.66 5399.67 2298.15 11499.68 6299.69 14999.06 1699.96 2098.69 11699.87 4299.84 22
ACMMPR99.49 1799.36 2799.86 2199.87 1699.79 3399.66 5399.67 2298.15 11499.67 6899.69 14998.95 3299.96 2098.69 11699.87 4299.84 22
DeepC-MVS_fast98.69 199.49 1799.39 2199.77 5099.63 12999.59 7399.36 20399.46 17599.07 1899.79 3099.82 5498.85 4599.92 8598.68 11899.87 4299.82 40
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
region2R99.48 2199.35 3099.87 1299.88 1299.80 2999.65 6099.66 2798.13 11699.66 7399.68 15698.96 2999.96 2098.62 12599.87 4299.84 22
APD-MVS_3200maxsize99.48 2199.35 3099.85 2899.76 5799.83 1799.63 6599.54 7598.36 9199.79 3099.82 5498.86 4499.95 4798.62 12599.81 8599.78 70
DELS-MVS99.48 2199.42 1799.65 7599.72 8999.40 10399.05 27899.66 2799.14 799.57 10199.80 8398.46 8599.94 5899.57 899.84 6799.60 139
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
ZNCC-MVS99.47 2499.33 3499.87 1299.87 1699.81 2799.64 6399.67 2298.08 12799.55 10699.64 17698.91 4099.96 2098.72 11199.90 2599.82 40
ACMMP_NAP99.47 2499.34 3299.88 699.87 1699.86 1399.47 15699.48 14798.05 13399.76 4499.86 2898.82 4899.93 7398.82 10099.91 1899.84 22
DPE-MVScopyleft99.46 2699.32 3699.91 299.78 4899.88 899.36 20399.51 10698.73 6199.88 699.84 4398.72 6599.96 2098.16 17799.87 4299.88 8
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
MSLP-MVS++99.46 2699.47 1399.44 12699.60 14399.16 12899.41 17999.71 1398.98 3499.45 12299.78 10299.19 999.54 24099.28 3999.84 6799.63 133
SR-MVS-dyc-post99.45 2899.31 4399.85 2899.76 5799.82 2399.63 6599.52 9298.38 8799.76 4499.82 5498.53 7899.95 4798.61 12899.81 8599.77 72
PGM-MVS99.45 2899.31 4399.86 2199.87 1699.78 4099.58 9399.65 3297.84 15099.71 5599.80 8399.12 1399.97 1298.33 16399.87 4299.83 33
CP-MVS99.45 2899.32 3699.85 2899.83 3799.75 4399.69 4299.52 9298.07 12899.53 10999.63 18298.93 3999.97 1298.74 10799.91 1899.83 33
ACMMPcopyleft99.45 2899.32 3699.82 3899.89 999.67 5799.62 7199.69 1898.12 11899.63 8499.84 4398.73 6499.96 2098.55 14299.83 7699.81 46
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
SMA-MVScopyleft99.44 3299.30 4699.85 2899.73 8499.83 1799.56 10699.47 16597.45 19499.78 3599.82 5499.18 1099.91 9698.79 10299.89 3599.81 46
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
abl_699.44 3299.31 4399.83 3699.85 2699.75 4399.66 5399.59 4498.13 11699.82 2399.81 6798.60 7499.96 2098.46 15199.88 3899.79 62
mPP-MVS99.44 3299.30 4699.86 2199.88 1299.79 3399.69 4299.48 14798.12 11899.50 11499.75 11898.78 5299.97 1298.57 13699.89 3599.83 33
DROMVSNet99.44 3299.39 2199.58 9099.56 15399.49 9199.88 299.58 5098.38 8799.73 5099.69 14998.20 10299.70 21099.64 399.82 8299.54 152
test117299.43 3699.29 5099.85 2899.75 6899.82 2399.60 7899.56 5898.28 9999.74 4899.79 9598.53 7899.95 4798.55 14299.78 9699.79 62
xxxxxxxxxxxxxcwj99.43 3699.32 3699.75 5499.76 5799.59 7399.14 26199.53 8699.00 2899.71 5599.80 8398.95 3299.93 7398.19 17299.84 6799.74 83
SR-MVS99.43 3699.29 5099.86 2199.75 6899.83 1799.59 8599.62 3498.21 10899.73 5099.79 9598.68 6899.96 2098.44 15399.77 10199.79 62
#test#99.43 3699.29 5099.86 2199.87 1699.80 2999.55 11599.67 2297.83 15199.68 6299.69 14999.06 1699.96 2098.39 15599.87 4299.84 22
MCST-MVS99.43 3699.30 4699.82 3899.79 4699.74 4699.29 22399.40 21498.79 5799.52 11199.62 18898.91 4099.90 11198.64 12399.75 10599.82 40
MSP-MVS99.42 4199.27 5699.88 699.89 999.80 2999.67 4999.50 12698.70 6399.77 3799.49 23398.21 10199.95 4798.46 15199.77 10199.88 8
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
CS-MVS-test99.42 4199.39 2199.52 10899.77 5399.35 10699.80 2099.57 5298.56 7199.77 3799.44 24898.16 10699.77 17899.64 399.78 9699.42 181
UA-Net99.42 4199.29 5099.80 4399.62 13599.55 8099.50 13599.70 1598.79 5799.77 3799.96 197.45 12399.96 2098.92 7599.90 2599.89 2
HPM-MVScopyleft99.42 4199.28 5499.83 3699.90 499.72 4799.81 1699.54 7597.59 17799.68 6299.63 18298.91 4099.94 5898.58 13499.91 1899.84 22
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CNVR-MVS99.42 4199.30 4699.78 4899.62 13599.71 4999.26 23999.52 9298.82 5299.39 14199.71 13698.96 2999.85 13698.59 13399.80 8999.77 72
SD-MVS99.41 4699.52 899.05 17099.74 7699.68 5499.46 15999.52 9299.11 1199.88 699.91 899.43 197.70 35998.72 11199.93 1299.77 72
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
MVS_111021_LR99.41 4699.33 3499.65 7599.77 5399.51 9098.94 30899.85 698.82 5299.65 7999.74 12498.51 8199.80 16998.83 9699.89 3599.64 129
MVS_111021_HR99.41 4699.32 3699.66 7199.72 8999.47 9598.95 30699.85 698.82 5299.54 10799.73 13198.51 8199.74 18798.91 7699.88 3899.77 72
GST-MVS99.40 4999.24 6199.85 2899.86 2299.79 3399.60 7899.67 2297.97 13999.63 8499.68 15698.52 8099.95 4798.38 15799.86 5399.81 46
HPM-MVS++copyleft99.39 5099.23 6399.87 1299.75 6899.84 1699.43 17099.51 10698.68 6599.27 16899.53 22098.64 7399.96 2098.44 15399.80 8999.79 62
SF-MVS99.38 5199.24 6199.79 4699.79 4699.68 5499.57 9999.54 7597.82 15699.71 5599.80 8398.95 3299.93 7398.19 17299.84 6799.74 83
MP-MVS-pluss99.37 5299.20 6599.88 699.90 499.87 1299.30 21999.52 9297.18 22099.60 9499.79 9598.79 5199.95 4798.83 9699.91 1899.83 33
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
TSAR-MVS + GP.99.36 5399.36 2799.36 13299.67 11098.61 19499.07 27399.33 25099.00 2899.82 2399.81 6799.06 1699.84 14299.09 5899.42 14299.65 122
PVSNet_Blended_VisFu99.36 5399.28 5499.61 8599.86 2299.07 14299.47 15699.93 297.66 17399.71 5599.86 2897.73 11899.96 2099.47 2099.82 8299.79 62
NCCC99.34 5599.19 6699.79 4699.61 13999.65 6299.30 21999.48 14798.86 4899.21 18499.63 18298.72 6599.90 11198.25 16899.63 13199.80 56
MP-MVScopyleft99.33 5699.15 6999.87 1299.88 1299.82 2399.66 5399.46 17598.09 12399.48 11899.74 12498.29 9899.96 2097.93 19599.87 4299.82 40
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
PS-MVSNAJ99.32 5799.32 3699.30 14399.57 14998.94 16298.97 30199.46 17598.92 4599.71 5599.24 29999.01 1999.98 799.35 2999.66 12698.97 223
CSCG99.32 5799.32 3699.32 13899.85 2698.29 21799.71 3999.66 2798.11 12099.41 13499.80 8398.37 9499.96 2098.99 6699.96 799.72 96
PHI-MVS99.30 5999.17 6899.70 6799.56 15399.52 8899.58 9399.80 897.12 22699.62 8899.73 13198.58 7599.90 11198.61 12899.91 1899.68 112
DeepC-MVS98.35 299.30 5999.19 6699.64 8099.82 3999.23 12199.62 7199.55 6798.94 4199.63 8499.95 295.82 17999.94 5899.37 2899.97 599.73 90
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
xiu_mvs_v1_base_debu99.29 6199.27 5699.34 13399.63 12998.97 15399.12 26399.51 10698.86 4899.84 1599.47 24298.18 10399.99 199.50 1399.31 15299.08 208
xiu_mvs_v1_base99.29 6199.27 5699.34 13399.63 12998.97 15399.12 26399.51 10698.86 4899.84 1599.47 24298.18 10399.99 199.50 1399.31 15299.08 208
xiu_mvs_v1_base_debi99.29 6199.27 5699.34 13399.63 12998.97 15399.12 26399.51 10698.86 4899.84 1599.47 24298.18 10399.99 199.50 1399.31 15299.08 208
APD-MVScopyleft99.27 6499.08 7799.84 3599.75 6899.79 3399.50 13599.50 12697.16 22299.77 3799.82 5498.78 5299.94 5897.56 23199.86 5399.80 56
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
LS3D99.27 6499.12 7299.74 5999.18 25099.75 4399.56 10699.57 5298.45 8199.49 11799.85 3497.77 11799.94 5898.33 16399.84 6799.52 158
patch_mono-299.26 6699.62 198.16 27899.81 4294.59 34199.52 12499.64 3399.33 299.73 5099.90 1099.00 2599.99 199.69 199.98 299.89 2
ETV-MVS99.26 6699.21 6499.40 12899.46 18299.30 11399.56 10699.52 9298.52 7599.44 12699.27 29598.41 9199.86 13099.10 5799.59 13499.04 215
xiu_mvs_v2_base99.26 6699.25 6099.29 14699.53 15798.91 16699.02 28799.45 18798.80 5699.71 5599.26 29798.94 3599.98 799.34 3399.23 15798.98 222
CANet99.25 6999.14 7099.59 8799.41 19299.16 12899.35 20999.57 5298.82 5299.51 11399.61 19296.46 15699.95 4799.59 699.98 299.65 122
3Dnovator97.25 999.24 7099.05 7999.81 4199.12 26399.66 5999.84 1099.74 1099.09 1598.92 23799.90 1095.94 17399.98 798.95 7099.92 1399.79 62
dcpmvs_299.23 7199.58 298.16 27899.83 3794.68 34099.76 3199.52 9299.07 1899.98 199.88 1998.56 7799.93 7399.67 299.98 299.87 13
ETH3D-3000-0.199.21 7299.02 8799.77 5099.73 8499.69 5299.38 19699.51 10697.45 19499.61 9099.75 11898.51 8199.91 9697.45 24399.83 7699.71 103
test_prior399.21 7299.05 7999.68 6899.67 11099.48 9398.96 30299.56 5898.34 9399.01 22199.52 22398.68 6899.83 15397.96 19299.74 10899.74 83
CHOSEN 1792x268899.19 7499.10 7499.45 12299.89 998.52 20399.39 19199.94 198.73 6199.11 20299.89 1495.50 18999.94 5899.50 1399.97 599.89 2
F-COLMAP99.19 7499.04 8299.64 8099.78 4899.27 11799.42 17799.54 7597.29 21099.41 13499.59 19898.42 9099.93 7398.19 17299.69 11899.73 90
EIA-MVS99.18 7699.09 7699.45 12299.49 17399.18 12599.67 4999.53 8697.66 17399.40 13999.44 24898.10 10899.81 16498.94 7199.62 13299.35 189
3Dnovator+97.12 1399.18 7698.97 9699.82 3899.17 25699.68 5499.81 1699.51 10699.20 598.72 26399.89 1495.68 18499.97 1298.86 8899.86 5399.81 46
MVSFormer99.17 7899.12 7299.29 14699.51 16198.94 16299.88 299.46 17597.55 18299.80 2899.65 16997.39 12499.28 28299.03 6299.85 6099.65 122
sss99.17 7899.05 7999.53 10299.62 13598.97 15399.36 20399.62 3497.83 15199.67 6899.65 16997.37 12899.95 4799.19 4799.19 16099.68 112
DP-MVS99.16 8098.95 10099.78 4899.77 5399.53 8599.41 17999.50 12697.03 23799.04 21899.88 1997.39 12499.92 8598.66 12199.90 2599.87 13
baseline99.15 8199.02 8799.53 10299.66 11999.14 13399.72 3799.48 14798.35 9299.42 13099.84 4396.07 16799.79 17299.51 1299.14 16499.67 115
diffmvs99.14 8299.02 8799.51 11299.61 13998.96 15799.28 22599.49 13498.46 8099.72 5499.71 13696.50 15599.88 12499.31 3699.11 16699.67 115
CNLPA99.14 8298.99 9299.59 8799.58 14799.41 10199.16 25599.44 19698.45 8199.19 19099.49 23398.08 10999.89 11997.73 21399.75 10599.48 169
CDPH-MVS99.13 8498.91 10499.80 4399.75 6899.71 4999.15 25999.41 20896.60 26899.60 9499.55 21198.83 4799.90 11197.48 23899.83 7699.78 70
casdiffmvs99.13 8498.98 9599.56 9499.65 12499.16 12899.56 10699.50 12698.33 9699.41 13499.86 2895.92 17499.83 15399.45 2299.16 16199.70 105
jason99.13 8499.03 8499.45 12299.46 18298.87 16999.12 26399.26 27698.03 13699.79 3099.65 16997.02 13899.85 13699.02 6499.90 2599.65 122
jason: jason.
lupinMVS99.13 8499.01 9199.46 12199.51 16198.94 16299.05 27899.16 29197.86 14699.80 2899.56 20897.39 12499.86 13098.94 7199.85 6099.58 147
EPP-MVSNet99.13 8498.99 9299.53 10299.65 12499.06 14399.81 1699.33 25097.43 19899.60 9499.88 1997.14 13399.84 14299.13 5498.94 18199.69 108
MG-MVS99.13 8499.02 8799.45 12299.57 14998.63 19199.07 27399.34 24398.99 3199.61 9099.82 5497.98 11299.87 12797.00 26899.80 8999.85 18
testtj99.12 9098.87 10999.86 2199.72 8999.79 3399.44 16499.51 10697.29 21099.59 9799.74 12498.15 10799.96 2096.74 28399.69 11899.81 46
CHOSEN 280x42099.12 9099.13 7199.08 16699.66 11997.89 23898.43 34799.71 1398.88 4799.62 8899.76 11396.63 15199.70 21099.46 2199.99 199.66 118
DP-MVS Recon99.12 9098.95 10099.65 7599.74 7699.70 5199.27 23099.57 5296.40 28599.42 13099.68 15698.75 6099.80 16997.98 19199.72 11299.44 179
Vis-MVSNetpermissive99.12 9098.97 9699.56 9499.78 4899.10 13899.68 4799.66 2798.49 7799.86 1399.87 2594.77 21899.84 14299.19 4799.41 14399.74 83
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
TAMVS99.12 9099.08 7799.24 15499.46 18298.55 19799.51 12999.46 17598.09 12399.45 12299.82 5498.34 9599.51 24198.70 11398.93 18299.67 115
VNet99.11 9598.90 10599.73 6199.52 15999.56 7899.41 17999.39 21899.01 2499.74 4899.78 10295.56 18799.92 8599.52 1198.18 22099.72 96
CPTT-MVS99.11 9598.90 10599.74 5999.80 4599.46 9699.59 8599.49 13497.03 23799.63 8499.69 14997.27 13199.96 2097.82 20499.84 6799.81 46
HyFIR lowres test99.11 9598.92 10299.65 7599.90 499.37 10499.02 28799.91 397.67 17299.59 9799.75 11895.90 17699.73 19499.53 1099.02 17799.86 15
MVS_Test99.10 9898.97 9699.48 11699.49 17399.14 13399.67 4999.34 24397.31 20899.58 9999.76 11397.65 12099.82 16098.87 8399.07 17299.46 176
112199.09 9998.87 10999.75 5499.74 7699.60 7099.27 23099.48 14796.82 25399.25 17599.65 16998.38 9299.93 7397.53 23499.67 12599.73 90
CDS-MVSNet99.09 9999.03 8499.25 15299.42 18998.73 18399.45 16099.46 17598.11 12099.46 12199.77 10998.01 11199.37 26398.70 11398.92 18499.66 118
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PVSNet_Blended99.08 10198.97 9699.42 12799.76 5798.79 18098.78 32399.91 396.74 25599.67 6899.49 23397.53 12199.88 12498.98 6799.85 6099.60 139
OMC-MVS99.08 10199.04 8299.20 15799.67 11098.22 22199.28 22599.52 9298.07 12899.66 7399.81 6797.79 11699.78 17697.79 20699.81 8599.60 139
ETH3D cwj APD-0.1699.06 10398.84 11599.72 6499.51 16199.60 7099.23 24499.44 19697.04 23599.39 14199.67 16298.30 9799.92 8597.27 25099.69 11899.64 129
WTY-MVS99.06 10398.88 10899.61 8599.62 13599.16 12899.37 19999.56 5898.04 13499.53 10999.62 18896.84 14399.94 5898.85 9098.49 20699.72 96
IS-MVSNet99.05 10598.87 10999.57 9299.73 8499.32 10999.75 3399.20 28698.02 13799.56 10299.86 2896.54 15499.67 21698.09 18199.13 16599.73 90
PAPM_NR99.04 10698.84 11599.66 7199.74 7699.44 9899.39 19199.38 22497.70 16799.28 16599.28 29298.34 9599.85 13696.96 27299.45 14099.69 108
API-MVS99.04 10699.03 8499.06 16899.40 19799.31 11299.55 11599.56 5898.54 7399.33 15699.39 26598.76 5799.78 17696.98 27099.78 9698.07 341
mvs_anonymous99.03 10898.99 9299.16 16199.38 20198.52 20399.51 12999.38 22497.79 15799.38 14499.81 6797.30 12999.45 24699.35 2998.99 17999.51 164
train_agg99.02 10998.77 12399.77 5099.67 11099.65 6299.05 27899.41 20896.28 28998.95 23299.49 23398.76 5799.91 9697.63 22299.72 11299.75 78
canonicalmvs99.02 10998.86 11399.51 11299.42 18999.32 10999.80 2099.48 14798.63 6699.31 15898.81 33497.09 13599.75 18699.27 4197.90 23099.47 174
PLCcopyleft97.94 499.02 10998.85 11499.53 10299.66 11999.01 14899.24 24399.52 9296.85 24999.27 16899.48 23998.25 10099.91 9697.76 20999.62 13299.65 122
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
agg_prior199.01 11298.76 12599.76 5399.67 11099.62 6698.99 29499.40 21496.26 29298.87 24599.49 23398.77 5599.91 9697.69 21999.72 11299.75 78
AdaColmapbinary99.01 11298.80 12099.66 7199.56 15399.54 8299.18 25399.70 1598.18 11299.35 15299.63 18296.32 16199.90 11197.48 23899.77 10199.55 150
1112_ss98.98 11498.77 12399.59 8799.68 10999.02 14699.25 24199.48 14797.23 21799.13 19899.58 20196.93 14299.90 11198.87 8398.78 19399.84 22
MSDG98.98 11498.80 12099.53 10299.76 5799.19 12398.75 32699.55 6797.25 21499.47 11999.77 10997.82 11599.87 12796.93 27599.90 2599.54 152
CANet_DTU98.97 11698.87 10999.25 15299.33 21198.42 21499.08 27299.30 26799.16 699.43 12799.75 11895.27 19799.97 1298.56 13999.95 899.36 188
DPM-MVS98.95 11798.71 12999.66 7199.63 12999.55 8098.64 33699.10 29797.93 14299.42 13099.55 21198.67 7199.80 16995.80 30599.68 12399.61 137
114514_t98.93 11898.67 13399.72 6499.85 2699.53 8599.62 7199.59 4492.65 34999.71 5599.78 10298.06 11099.90 11198.84 9399.91 1899.74 83
PS-MVSNAJss98.92 11998.92 10298.90 19598.78 31298.53 19999.78 2699.54 7598.07 12899.00 22699.76 11399.01 1999.37 26399.13 5497.23 26298.81 233
Test_1112_low_res98.89 12098.66 13699.57 9299.69 10598.95 15999.03 28499.47 16596.98 23999.15 19699.23 30096.77 14799.89 11998.83 9698.78 19399.86 15
AllTest98.87 12198.72 12799.31 13999.86 2298.48 20999.56 10699.61 3697.85 14899.36 14999.85 3495.95 17199.85 13696.66 28999.83 7699.59 143
UGNet98.87 12198.69 13199.40 12899.22 24198.72 18499.44 16499.68 1999.24 499.18 19399.42 25492.74 27299.96 2099.34 3399.94 1199.53 157
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
Vis-MVSNet (Re-imp)98.87 12198.72 12799.31 13999.71 9598.88 16899.80 2099.44 19697.91 14499.36 14999.78 10295.49 19099.43 25597.91 19699.11 16699.62 135
test_yl98.86 12498.63 13899.54 9699.49 17399.18 12599.50 13599.07 30298.22 10699.61 9099.51 22795.37 19399.84 14298.60 13198.33 20999.59 143
DCV-MVSNet98.86 12498.63 13899.54 9699.49 17399.18 12599.50 13599.07 30298.22 10699.61 9099.51 22795.37 19399.84 14298.60 13198.33 20999.59 143
mvs-test198.86 12498.84 11598.89 19899.33 21197.77 24499.44 16499.30 26798.47 7899.10 20599.43 25196.78 14599.95 4798.73 10999.02 17798.96 225
EPNet98.86 12498.71 12999.30 14397.20 35998.18 22299.62 7198.91 31999.28 398.63 28199.81 6795.96 17099.99 199.24 4399.72 11299.73 90
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PVSNet_BlendedMVS98.86 12498.80 12099.03 17399.76 5798.79 18099.28 22599.91 397.42 20099.67 6899.37 26997.53 12199.88 12498.98 6797.29 26198.42 324
ab-mvs98.86 12498.63 13899.54 9699.64 12699.19 12399.44 16499.54 7597.77 15999.30 16099.81 6794.20 24099.93 7399.17 5098.82 19099.49 168
MAR-MVS98.86 12498.63 13899.54 9699.37 20399.66 5999.45 16099.54 7596.61 26699.01 22199.40 26197.09 13599.86 13097.68 22199.53 13899.10 203
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
COLMAP_ROBcopyleft97.56 698.86 12498.75 12699.17 16099.88 1298.53 19999.34 21299.59 4497.55 18298.70 27099.89 1495.83 17899.90 11198.10 18099.90 2599.08 208
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
GeoE98.85 13298.62 14399.53 10299.61 13999.08 14099.80 2099.51 10697.10 23099.31 15899.78 10295.23 20199.77 17898.21 17099.03 17599.75 78
HY-MVS97.30 798.85 13298.64 13799.47 11999.42 18999.08 14099.62 7199.36 23497.39 20399.28 16599.68 15696.44 15899.92 8598.37 15998.22 21599.40 186
PVSNet96.02 1798.85 13298.84 11598.89 19899.73 8497.28 25798.32 35399.60 4197.86 14699.50 11499.57 20596.75 14899.86 13098.56 13999.70 11799.54 152
PatchMatch-RL98.84 13598.62 14399.52 10899.71 9599.28 11599.06 27699.77 997.74 16499.50 11499.53 22095.41 19199.84 14297.17 26199.64 12999.44 179
Effi-MVS+98.81 13698.59 14999.48 11699.46 18299.12 13798.08 35999.50 12697.50 19099.38 14499.41 25896.37 16099.81 16499.11 5698.54 20399.51 164
alignmvs98.81 13698.56 15199.58 9099.43 18899.42 10099.51 12998.96 31298.61 6899.35 15298.92 33194.78 21599.77 17899.35 2998.11 22699.54 152
DeepPCF-MVS98.18 398.81 13699.37 2597.12 32699.60 14391.75 36398.61 33799.44 19699.35 199.83 2099.85 3498.70 6799.81 16499.02 6499.91 1899.81 46
PMMVS98.80 13998.62 14399.34 13399.27 22998.70 18598.76 32599.31 26397.34 20599.21 18499.07 31697.20 13299.82 16098.56 13998.87 18799.52 158
Effi-MVS+-dtu98.78 14098.89 10798.47 25099.33 21196.91 28499.57 9999.30 26798.47 7899.41 13498.99 32596.78 14599.74 18798.73 10999.38 14498.74 248
FIs98.78 14098.63 13899.23 15699.18 25099.54 8299.83 1399.59 4498.28 9998.79 25799.81 6796.75 14899.37 26399.08 5996.38 28098.78 236
Fast-Effi-MVS+-dtu98.77 14298.83 11998.60 23199.41 19296.99 27899.52 12499.49 13498.11 12099.24 17699.34 27896.96 14199.79 17297.95 19499.45 14099.02 218
FC-MVSNet-test98.75 14398.62 14399.15 16399.08 27299.45 9799.86 999.60 4198.23 10598.70 27099.82 5496.80 14499.22 29299.07 6096.38 28098.79 235
XVG-OURS98.73 14498.68 13298.88 20199.70 10297.73 24698.92 30999.55 6798.52 7599.45 12299.84 4395.27 19799.91 9698.08 18598.84 18999.00 219
ETH3 D test640098.70 14598.35 16199.73 6199.69 10599.60 7099.16 25599.45 18795.42 31899.27 16899.60 19597.39 12499.91 9695.36 31699.83 7699.70 105
Fast-Effi-MVS+98.70 14598.43 15699.51 11299.51 16199.28 11599.52 12499.47 16596.11 30799.01 22199.34 27896.20 16599.84 14297.88 19898.82 19099.39 187
XVG-OURS-SEG-HR98.69 14798.62 14398.89 19899.71 9597.74 24599.12 26399.54 7598.44 8499.42 13099.71 13694.20 24099.92 8598.54 14498.90 18699.00 219
131498.68 14898.54 15299.11 16598.89 29698.65 18999.27 23099.49 13496.89 24797.99 31899.56 20897.72 11999.83 15397.74 21299.27 15598.84 232
EI-MVSNet98.67 14998.67 13398.68 22899.35 20697.97 23299.50 13599.38 22496.93 24699.20 18799.83 4797.87 11399.36 26798.38 15797.56 24298.71 252
test_djsdf98.67 14998.57 15098.98 17998.70 32398.91 16699.88 299.46 17597.55 18299.22 18199.88 1995.73 18299.28 28299.03 6297.62 23798.75 244
QAPM98.67 14998.30 16699.80 4399.20 24599.67 5799.77 2899.72 1194.74 33098.73 26299.90 1095.78 18099.98 796.96 27299.88 3899.76 77
nrg03098.64 15298.42 15799.28 14999.05 27899.69 5299.81 1699.46 17598.04 13499.01 22199.82 5496.69 15099.38 26099.34 3394.59 32098.78 236
PAPR98.63 15398.34 16299.51 11299.40 19799.03 14598.80 32199.36 23496.33 28699.00 22699.12 31498.46 8599.84 14295.23 31899.37 15199.66 118
RRT_MVS98.60 15498.44 15599.05 17098.88 29799.14 13399.49 14599.38 22497.76 16099.29 16399.86 2895.38 19299.36 26798.81 10197.16 26698.64 284
CVMVSNet98.57 15598.67 13398.30 26899.35 20695.59 31899.50 13599.55 6798.60 6999.39 14199.83 4794.48 23299.45 24698.75 10698.56 20299.85 18
MVSTER98.49 15698.32 16499.00 17799.35 20699.02 14699.54 11899.38 22497.41 20199.20 18799.73 13193.86 25299.36 26798.87 8397.56 24298.62 294
OpenMVScopyleft96.50 1698.47 15798.12 17599.52 10899.04 27999.53 8599.82 1499.72 1194.56 33398.08 31399.88 1994.73 22199.98 797.47 24099.76 10499.06 214
IterMVS-LS98.46 15898.42 15798.58 23599.59 14598.00 23099.37 19999.43 20496.94 24599.07 21299.59 19897.87 11399.03 31998.32 16595.62 30098.71 252
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
anonymousdsp98.44 15998.28 16798.94 18598.50 33898.96 15799.77 2899.50 12697.07 23298.87 24599.77 10994.76 21999.28 28298.66 12197.60 23898.57 309
jajsoiax98.43 16098.28 16798.88 20198.60 33398.43 21299.82 1499.53 8698.19 10998.63 28199.80 8393.22 26299.44 25199.22 4497.50 24898.77 240
tttt051798.42 16198.14 17399.28 14999.66 11998.38 21599.74 3696.85 36497.68 16999.79 3099.74 12491.39 30899.89 11998.83 9699.56 13599.57 148
BH-untuned98.42 16198.36 15998.59 23299.49 17396.70 29099.27 23099.13 29597.24 21698.80 25599.38 26695.75 18199.74 18797.07 26699.16 16199.33 192
D2MVS98.41 16398.50 15398.15 28199.26 23196.62 29499.40 18799.61 3697.71 16698.98 22899.36 27296.04 16899.67 21698.70 11397.41 25798.15 339
BH-RMVSNet98.41 16398.08 18199.40 12899.41 19298.83 17699.30 21998.77 32997.70 16798.94 23499.65 16992.91 26899.74 18796.52 29199.55 13799.64 129
mvs_tets98.40 16598.23 16998.91 19398.67 32698.51 20599.66 5399.53 8698.19 10998.65 27999.81 6792.75 27099.44 25199.31 3697.48 25298.77 240
XXY-MVS98.38 16698.09 18099.24 15499.26 23199.32 10999.56 10699.55 6797.45 19498.71 26499.83 4793.23 26099.63 23198.88 7996.32 28298.76 242
ACMM97.58 598.37 16798.34 16298.48 24699.41 19297.10 26599.56 10699.45 18798.53 7499.04 21899.85 3493.00 26499.71 20498.74 10797.45 25398.64 284
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
thisisatest053098.35 16898.03 18799.31 13999.63 12998.56 19699.54 11896.75 36697.53 18799.73 5099.65 16991.25 31199.89 11998.62 12599.56 13599.48 169
tpmrst98.33 16998.48 15497.90 29899.16 25894.78 33899.31 21799.11 29697.27 21299.45 12299.59 19895.33 19599.84 14298.48 14798.61 19699.09 207
baseline198.31 17097.95 19799.38 13199.50 17198.74 18299.59 8598.93 31498.41 8599.14 19799.60 19594.59 22799.79 17298.48 14793.29 33799.61 137
PatchmatchNetpermissive98.31 17098.36 15998.19 27699.16 25895.32 32799.27 23098.92 31697.37 20499.37 14699.58 20194.90 20999.70 21097.43 24599.21 15899.54 152
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
Anonymous20240521198.30 17297.98 19299.26 15199.57 14998.16 22399.41 17998.55 34596.03 31299.19 19099.74 12491.87 29599.92 8599.16 5298.29 21499.70 105
VPA-MVSNet98.29 17397.95 19799.30 14399.16 25899.54 8299.50 13599.58 5098.27 10199.35 15299.37 26992.53 28299.65 22399.35 2994.46 32198.72 250
UniMVSNet (Re)98.29 17398.00 19099.13 16499.00 28499.36 10599.49 14599.51 10697.95 14098.97 23099.13 31196.30 16299.38 26098.36 16193.34 33698.66 280
HQP_MVS98.27 17598.22 17098.44 25599.29 22496.97 28099.39 19199.47 16598.97 3799.11 20299.61 19292.71 27599.69 21497.78 20797.63 23598.67 272
UniMVSNet_NR-MVSNet98.22 17697.97 19398.96 18298.92 29498.98 15099.48 15199.53 8697.76 16098.71 26499.46 24696.43 15999.22 29298.57 13692.87 34398.69 260
LPG-MVS_test98.22 17698.13 17498.49 24499.33 21197.05 27199.58 9399.55 6797.46 19199.24 17699.83 4792.58 28099.72 19898.09 18197.51 24698.68 265
RPSCF98.22 17698.62 14396.99 32799.82 3991.58 36499.72 3799.44 19696.61 26699.66 7399.89 1495.92 17499.82 16097.46 24199.10 16999.57 148
ADS-MVSNet98.20 17998.08 18198.56 23899.33 21196.48 29899.23 24499.15 29296.24 29499.10 20599.67 16294.11 24499.71 20496.81 28099.05 17399.48 169
OPM-MVS98.19 18098.10 17798.45 25298.88 29797.07 26999.28 22599.38 22498.57 7099.22 18199.81 6792.12 29199.66 21998.08 18597.54 24498.61 303
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
SCA98.19 18098.16 17198.27 27399.30 22095.55 31999.07 27398.97 31097.57 18099.43 12799.57 20592.72 27399.74 18797.58 22699.20 15999.52 158
miper_ehance_all_eth98.18 18298.10 17798.41 25799.23 23797.72 24798.72 32999.31 26396.60 26898.88 24399.29 29097.29 13099.13 30697.60 22495.99 28998.38 329
CR-MVSNet98.17 18397.93 20098.87 20599.18 25098.49 20799.22 24999.33 25096.96 24199.56 10299.38 26694.33 23699.00 32494.83 32498.58 19999.14 200
miper_enhance_ethall98.16 18498.08 18198.41 25798.96 29197.72 24798.45 34699.32 26096.95 24398.97 23099.17 30697.06 13799.22 29297.86 20095.99 28998.29 332
bset_n11_16_dypcd98.16 18497.97 19398.73 22398.26 34398.28 21997.99 36198.01 35497.68 16999.10 20599.63 18295.68 18499.15 30298.78 10596.55 27598.75 244
CLD-MVS98.16 18498.10 17798.33 26499.29 22496.82 28798.75 32699.44 19697.83 15199.13 19899.55 21192.92 26699.67 21698.32 16597.69 23498.48 315
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
thisisatest051598.14 18797.79 21199.19 15899.50 17198.50 20698.61 33796.82 36596.95 24399.54 10799.43 25191.66 30499.86 13098.08 18599.51 13999.22 197
pmmvs498.13 18897.90 20298.81 21698.61 33298.87 16998.99 29499.21 28596.44 28199.06 21699.58 20195.90 17699.11 31197.18 26096.11 28698.46 321
WR-MVS_H98.13 18897.87 20798.90 19599.02 28298.84 17399.70 4099.59 4497.27 21298.40 29899.19 30595.53 18899.23 28998.34 16293.78 33298.61 303
c3_l98.12 19098.04 18698.38 26199.30 22097.69 25098.81 32099.33 25096.67 26098.83 25199.34 27897.11 13498.99 32597.58 22695.34 30698.48 315
ACMH97.28 898.10 19197.99 19198.44 25599.41 19296.96 28299.60 7899.56 5898.09 12398.15 31199.91 890.87 31599.70 21098.88 7997.45 25398.67 272
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Anonymous2024052998.09 19297.68 22699.34 13399.66 11998.44 21199.40 18799.43 20493.67 34099.22 18199.89 1490.23 32399.93 7399.26 4298.33 20999.66 118
CP-MVSNet98.09 19297.78 21499.01 17598.97 29099.24 12099.67 4999.46 17597.25 21498.48 29399.64 17693.79 25399.06 31598.63 12494.10 32898.74 248
DU-MVS98.08 19497.79 21198.96 18298.87 30198.98 15099.41 17999.45 18797.87 14598.71 26499.50 23094.82 21299.22 29298.57 13692.87 34398.68 265
v2v48298.06 19597.77 21698.92 18998.90 29598.82 17799.57 9999.36 23496.65 26299.19 19099.35 27594.20 24099.25 28797.72 21594.97 31498.69 260
V4298.06 19597.79 21198.86 20898.98 28898.84 17399.69 4299.34 24396.53 27299.30 16099.37 26994.67 22499.32 27797.57 23094.66 31898.42 324
test-LLR98.06 19597.90 20298.55 24098.79 30997.10 26598.67 33297.75 35797.34 20598.61 28498.85 33294.45 23399.45 24697.25 25299.38 14499.10 203
WR-MVS98.06 19597.73 22299.06 16898.86 30499.25 11999.19 25299.35 23997.30 20998.66 27399.43 25193.94 24999.21 29798.58 13494.28 32598.71 252
ACMP97.20 1198.06 19597.94 19998.45 25299.37 20397.01 27699.44 16499.49 13497.54 18598.45 29499.79 9591.95 29499.72 19897.91 19697.49 25198.62 294
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
eth_miper_zixun_eth98.05 20097.96 19598.33 26499.26 23197.38 25598.56 34299.31 26396.65 26298.88 24399.52 22396.58 15299.12 31097.39 24795.53 30398.47 317
test111198.04 20198.11 17697.83 30299.74 7693.82 34999.58 9395.40 37199.12 1099.65 7999.93 490.73 31699.84 14299.43 2599.38 14499.82 40
ECVR-MVScopyleft98.04 20198.05 18598.00 29199.74 7694.37 34499.59 8594.98 37299.13 899.66 7399.93 490.67 31799.84 14299.40 2699.38 14499.80 56
EPNet_dtu98.03 20397.96 19598.23 27498.27 34295.54 32199.23 24498.75 33099.02 2197.82 32399.71 13696.11 16699.48 24293.04 34399.65 12899.69 108
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
FMVSNet398.03 20397.76 21998.84 21299.39 20098.98 15099.40 18799.38 22496.67 26099.07 21299.28 29292.93 26598.98 32697.10 26396.65 27198.56 310
ADS-MVSNet298.02 20598.07 18497.87 29999.33 21195.19 33099.23 24499.08 30096.24 29499.10 20599.67 16294.11 24498.93 33696.81 28099.05 17399.48 169
HQP-MVS98.02 20597.90 20298.37 26299.19 24796.83 28598.98 29899.39 21898.24 10298.66 27399.40 26192.47 28499.64 22697.19 25897.58 24098.64 284
LTVRE_ROB97.16 1298.02 20597.90 20298.40 25999.23 23796.80 28899.70 4099.60 4197.12 22698.18 31099.70 14091.73 30099.72 19898.39 15597.45 25398.68 265
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
cl____98.01 20897.84 20998.55 24099.25 23597.97 23298.71 33099.34 24396.47 28098.59 28799.54 21695.65 18699.21 29797.21 25495.77 29598.46 321
DIV-MVS_self_test98.01 20897.85 20898.48 24699.24 23697.95 23698.71 33099.35 23996.50 27398.60 28699.54 21695.72 18399.03 31997.21 25495.77 29598.46 321
miper_lstm_enhance98.00 21097.91 20198.28 27299.34 21097.43 25498.88 31399.36 23496.48 27898.80 25599.55 21195.98 16998.91 33797.27 25095.50 30498.51 313
BH-w/o98.00 21097.89 20698.32 26699.35 20696.20 30799.01 29298.90 32196.42 28398.38 29999.00 32495.26 19999.72 19896.06 29998.61 19699.03 216
v114497.98 21297.69 22598.85 21198.87 30198.66 18899.54 11899.35 23996.27 29199.23 18099.35 27594.67 22499.23 28996.73 28495.16 31098.68 265
EU-MVSNet97.98 21298.03 18797.81 30598.72 32096.65 29399.66 5399.66 2798.09 12398.35 30299.82 5495.25 20098.01 35297.41 24695.30 30798.78 236
tpmvs97.98 21298.02 18997.84 30199.04 27994.73 33999.31 21799.20 28696.10 31198.76 26099.42 25494.94 20599.81 16496.97 27198.45 20798.97 223
NR-MVSNet97.97 21597.61 23399.02 17498.87 30199.26 11899.47 15699.42 20697.63 17597.08 33999.50 23095.07 20499.13 30697.86 20093.59 33498.68 265
v897.95 21697.63 23298.93 18798.95 29298.81 17999.80 2099.41 20896.03 31299.10 20599.42 25494.92 20899.30 28096.94 27494.08 32998.66 280
Patchmatch-test97.93 21797.65 22998.77 22199.18 25097.07 26999.03 28499.14 29496.16 30298.74 26199.57 20594.56 22999.72 19893.36 33999.11 16699.52 158
PS-CasMVS97.93 21797.59 23698.95 18498.99 28599.06 14399.68 4799.52 9297.13 22498.31 30499.68 15692.44 28899.05 31698.51 14594.08 32998.75 244
TranMVSNet+NR-MVSNet97.93 21797.66 22898.76 22298.78 31298.62 19299.65 6099.49 13497.76 16098.49 29299.60 19594.23 23998.97 33398.00 19092.90 34198.70 256
v14419297.92 22097.60 23498.87 20598.83 30798.65 18999.55 11599.34 24396.20 29799.32 15799.40 26194.36 23599.26 28696.37 29695.03 31398.70 256
ACMH+97.24 1097.92 22097.78 21498.32 26699.46 18296.68 29299.56 10699.54 7598.41 8597.79 32599.87 2590.18 32499.66 21998.05 18997.18 26598.62 294
LFMVS97.90 22297.35 26799.54 9699.52 15999.01 14899.39 19198.24 34997.10 23099.65 7999.79 9584.79 35999.91 9699.28 3998.38 20899.69 108
Anonymous2023121197.88 22397.54 24098.90 19599.71 9598.53 19999.48 15199.57 5294.16 33698.81 25399.68 15693.23 26099.42 25698.84 9394.42 32398.76 242
OurMVSNet-221017-097.88 22397.77 21698.19 27698.71 32296.53 29699.88 299.00 30797.79 15798.78 25899.94 391.68 30199.35 27197.21 25496.99 26998.69 260
v7n97.87 22597.52 24198.92 18998.76 31698.58 19599.84 1099.46 17596.20 29798.91 23899.70 14094.89 21099.44 25196.03 30093.89 33198.75 244
baseline297.87 22597.55 23798.82 21499.18 25098.02 22999.41 17996.58 36896.97 24096.51 34499.17 30693.43 25799.57 23697.71 21699.03 17598.86 230
thres600view797.86 22797.51 24398.92 18999.72 8997.95 23699.59 8598.74 33397.94 14199.27 16898.62 34191.75 29899.86 13093.73 33598.19 21998.96 225
cl2297.85 22897.64 23198.48 24699.09 27097.87 23998.60 33999.33 25097.11 22998.87 24599.22 30192.38 28999.17 30198.21 17095.99 28998.42 324
v1097.85 22897.52 24198.86 20898.99 28598.67 18799.75 3399.41 20895.70 31598.98 22899.41 25894.75 22099.23 28996.01 30194.63 31998.67 272
GA-MVS97.85 22897.47 24799.00 17799.38 20197.99 23198.57 34099.15 29297.04 23598.90 24099.30 28889.83 32699.38 26096.70 28698.33 20999.62 135
tfpnnormal97.84 23197.47 24798.98 17999.20 24599.22 12299.64 6399.61 3696.32 28798.27 30799.70 14093.35 25999.44 25195.69 30795.40 30598.27 333
VPNet97.84 23197.44 25599.01 17599.21 24398.94 16299.48 15199.57 5298.38 8799.28 16599.73 13188.89 33699.39 25899.19 4793.27 33898.71 252
LCM-MVSNet-Re97.83 23398.15 17296.87 33299.30 22092.25 36199.59 8598.26 34897.43 19896.20 34799.13 31196.27 16398.73 34298.17 17698.99 17999.64 129
XVG-ACMP-BASELINE97.83 23397.71 22498.20 27599.11 26596.33 30399.41 17999.52 9298.06 13299.05 21799.50 23089.64 33099.73 19497.73 21397.38 25998.53 311
IterMVS97.83 23397.77 21698.02 28899.58 14796.27 30599.02 28799.48 14797.22 21898.71 26499.70 14092.75 27099.13 30697.46 24196.00 28898.67 272
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IterMVS-SCA-FT97.82 23697.75 22098.06 28599.57 14996.36 30299.02 28799.49 13497.18 22098.71 26499.72 13592.72 27399.14 30397.44 24495.86 29498.67 272
EPMVS97.82 23697.65 22998.35 26398.88 29795.98 31199.49 14594.71 37497.57 18099.26 17399.48 23992.46 28799.71 20497.87 19999.08 17199.35 189
MVP-Stereo97.81 23897.75 22097.99 29297.53 35296.60 29598.96 30298.85 32597.22 21897.23 33499.36 27295.28 19699.46 24595.51 31199.78 9697.92 353
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
v119297.81 23897.44 25598.91 19398.88 29798.68 18699.51 12999.34 24396.18 29999.20 18799.34 27894.03 24799.36 26795.32 31795.18 30998.69 260
v192192097.80 24097.45 25098.84 21298.80 30898.53 19999.52 12499.34 24396.15 30499.24 17699.47 24293.98 24899.29 28195.40 31495.13 31198.69 260
v14897.79 24197.55 23798.50 24398.74 31797.72 24799.54 11899.33 25096.26 29298.90 24099.51 22794.68 22399.14 30397.83 20393.15 34098.63 292
thres40097.77 24297.38 26398.92 18999.69 10597.96 23499.50 13598.73 33897.83 15199.17 19498.45 34691.67 30299.83 15393.22 34098.18 22098.96 225
thres100view90097.76 24397.45 25098.69 22799.72 8997.86 24199.59 8598.74 33397.93 14299.26 17398.62 34191.75 29899.83 15393.22 34098.18 22098.37 330
PEN-MVS97.76 24397.44 25598.72 22598.77 31598.54 19899.78 2699.51 10697.06 23498.29 30699.64 17692.63 27998.89 33998.09 18193.16 33998.72 250
Baseline_NR-MVSNet97.76 24397.45 25098.68 22899.09 27098.29 21799.41 17998.85 32595.65 31698.63 28199.67 16294.82 21299.10 31398.07 18892.89 34298.64 284
TR-MVS97.76 24397.41 26098.82 21499.06 27597.87 23998.87 31598.56 34496.63 26598.68 27299.22 30192.49 28399.65 22395.40 31497.79 23298.95 228
test_part197.75 24797.24 28099.29 14699.59 14599.63 6599.65 6099.49 13496.17 30098.44 29599.69 14989.80 32799.47 24398.68 11893.66 33398.78 236
Patchmtry97.75 24797.40 26198.81 21699.10 26898.87 16999.11 26999.33 25094.83 32898.81 25399.38 26694.33 23699.02 32196.10 29895.57 30198.53 311
dp97.75 24797.80 21097.59 31399.10 26893.71 35299.32 21598.88 32396.48 27899.08 21199.55 21192.67 27899.82 16096.52 29198.58 19999.24 196
TAPA-MVS97.07 1597.74 25097.34 27098.94 18599.70 10297.53 25199.25 24199.51 10691.90 35199.30 16099.63 18298.78 5299.64 22688.09 36399.87 4299.65 122
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
VDD-MVS97.73 25197.35 26798.88 20199.47 18197.12 26499.34 21298.85 32598.19 10999.67 6899.85 3482.98 36299.92 8599.49 1798.32 21399.60 139
MIMVSNet97.73 25197.45 25098.57 23699.45 18797.50 25299.02 28798.98 30996.11 30799.41 13499.14 31090.28 31998.74 34195.74 30698.93 18299.47 174
tfpn200view997.72 25397.38 26398.72 22599.69 10597.96 23499.50 13598.73 33897.83 15199.17 19498.45 34691.67 30299.83 15393.22 34098.18 22098.37 330
RRT_test8_iter0597.72 25397.60 23498.08 28399.23 23796.08 31099.63 6599.49 13497.54 18598.94 23499.81 6787.99 34799.35 27199.21 4696.51 27798.81 233
CostFormer97.72 25397.73 22297.71 30999.15 26194.02 34899.54 11899.02 30694.67 33199.04 21899.35 27592.35 29099.77 17898.50 14697.94 22999.34 191
FMVSNet297.72 25397.36 26598.80 21899.51 16198.84 17399.45 16099.42 20696.49 27498.86 25099.29 29090.26 32098.98 32696.44 29396.56 27498.58 308
test0.0.03 197.71 25797.42 25998.56 23898.41 34197.82 24298.78 32398.63 34297.34 20598.05 31798.98 32894.45 23398.98 32695.04 32197.15 26798.89 229
h-mvs3397.70 25897.28 27698.97 18199.70 10297.27 25899.36 20399.45 18798.94 4199.66 7399.64 17694.93 20699.99 199.48 1884.36 36099.65 122
v124097.69 25997.32 27398.79 21998.85 30598.43 21299.48 15199.36 23496.11 30799.27 16899.36 27293.76 25599.24 28894.46 32795.23 30898.70 256
cascas97.69 25997.43 25898.48 24698.60 33397.30 25698.18 35899.39 21892.96 34898.41 29798.78 33793.77 25499.27 28598.16 17798.61 19698.86 230
pm-mvs197.68 26197.28 27698.88 20199.06 27598.62 19299.50 13599.45 18796.32 28797.87 32199.79 9592.47 28499.35 27197.54 23393.54 33598.67 272
GBi-Net97.68 26197.48 24598.29 26999.51 16197.26 26099.43 17099.48 14796.49 27499.07 21299.32 28590.26 32098.98 32697.10 26396.65 27198.62 294
test197.68 26197.48 24598.29 26999.51 16197.26 26099.43 17099.48 14796.49 27499.07 21299.32 28590.26 32098.98 32697.10 26396.65 27198.62 294
tpm97.67 26497.55 23798.03 28699.02 28295.01 33399.43 17098.54 34696.44 28199.12 20099.34 27891.83 29799.60 23497.75 21196.46 27899.48 169
PCF-MVS97.08 1497.66 26597.06 28699.47 11999.61 13999.09 13998.04 36099.25 27891.24 35498.51 29099.70 14094.55 23099.91 9692.76 34799.85 6099.42 181
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
our_test_397.65 26697.68 22697.55 31598.62 33094.97 33498.84 31799.30 26796.83 25298.19 30999.34 27897.01 13999.02 32195.00 32296.01 28798.64 284
testgi97.65 26697.50 24498.13 28299.36 20596.45 29999.42 17799.48 14797.76 16097.87 32199.45 24791.09 31298.81 34094.53 32698.52 20499.13 202
thres20097.61 26897.28 27698.62 23099.64 12698.03 22899.26 23998.74 33397.68 16999.09 21098.32 35091.66 30499.81 16492.88 34498.22 21598.03 344
PAPM97.59 26997.09 28599.07 16799.06 27598.26 22098.30 35499.10 29794.88 32798.08 31399.34 27896.27 16399.64 22689.87 35698.92 18499.31 193
VDDNet97.55 27097.02 28799.16 16199.49 17398.12 22799.38 19699.30 26795.35 31999.68 6299.90 1082.62 36499.93 7399.31 3698.13 22599.42 181
TESTMET0.1,197.55 27097.27 27998.40 25998.93 29396.53 29698.67 33297.61 36096.96 24198.64 28099.28 29288.63 34099.45 24697.30 24999.38 14499.21 198
DWT-MVSNet_test97.53 27297.40 26197.93 29599.03 28194.86 33799.57 9998.63 34296.59 27098.36 30198.79 33589.32 33299.74 18798.14 17998.16 22499.20 199
pmmvs597.52 27397.30 27598.16 27898.57 33596.73 28999.27 23098.90 32196.14 30598.37 30099.53 22091.54 30799.14 30397.51 23695.87 29398.63 292
LF4IMVS97.52 27397.46 24997.70 31098.98 28895.55 31999.29 22398.82 32898.07 12898.66 27399.64 17689.97 32599.61 23397.01 26796.68 27097.94 351
DTE-MVSNet97.51 27597.19 28298.46 25198.63 32998.13 22699.84 1099.48 14796.68 25997.97 31999.67 16292.92 26698.56 34396.88 27992.60 34698.70 256
hse-mvs297.50 27697.14 28398.59 23299.49 17397.05 27199.28 22599.22 28298.94 4199.66 7399.42 25494.93 20699.65 22399.48 1883.80 36299.08 208
SixPastTwentyTwo97.50 27697.33 27298.03 28698.65 32796.23 30699.77 2898.68 34197.14 22397.90 32099.93 490.45 31899.18 30097.00 26896.43 27998.67 272
JIA-IIPM97.50 27697.02 28798.93 18798.73 31897.80 24399.30 21998.97 31091.73 35298.91 23894.86 36595.10 20399.71 20497.58 22697.98 22899.28 195
ppachtmachnet_test97.49 27997.45 25097.61 31298.62 33095.24 32898.80 32199.46 17596.11 30798.22 30899.62 18896.45 15798.97 33393.77 33495.97 29298.61 303
test-mter97.49 27997.13 28498.55 24098.79 30997.10 26598.67 33297.75 35796.65 26298.61 28498.85 33288.23 34499.45 24697.25 25299.38 14499.10 203
tpm297.44 28197.34 27097.74 30899.15 26194.36 34599.45 16098.94 31393.45 34598.90 24099.44 24891.35 30999.59 23597.31 24898.07 22799.29 194
tpm cat197.39 28297.36 26597.50 31799.17 25693.73 35199.43 17099.31 26391.27 35398.71 26499.08 31594.31 23899.77 17896.41 29598.50 20599.00 219
USDC97.34 28397.20 28197.75 30799.07 27395.20 32998.51 34499.04 30597.99 13898.31 30499.86 2889.02 33499.55 23995.67 30997.36 26098.49 314
UniMVSNet_ETH3D97.32 28496.81 29098.87 20599.40 19797.46 25399.51 12999.53 8695.86 31498.54 28999.77 10982.44 36599.66 21998.68 11897.52 24599.50 167
MVS97.28 28596.55 29499.48 11698.78 31298.95 15999.27 23099.39 21883.53 36498.08 31399.54 21696.97 14099.87 12794.23 33099.16 16199.63 133
DSMNet-mixed97.25 28697.35 26796.95 33097.84 34993.61 35599.57 9996.63 36796.13 30698.87 24598.61 34394.59 22797.70 35995.08 32098.86 18899.55 150
MS-PatchMatch97.24 28797.32 27396.99 32798.45 34093.51 35698.82 31999.32 26097.41 20198.13 31299.30 28888.99 33599.56 23795.68 30899.80 8997.90 354
TransMVSNet (Re)97.15 28896.58 29398.86 20899.12 26398.85 17299.49 14598.91 31995.48 31797.16 33799.80 8393.38 25899.11 31194.16 33291.73 34898.62 294
TinyColmap97.12 28996.89 28997.83 30299.07 27395.52 32298.57 34098.74 33397.58 17997.81 32499.79 9588.16 34599.56 23795.10 31997.21 26398.39 328
K. test v397.10 29096.79 29198.01 28998.72 32096.33 30399.87 697.05 36397.59 17796.16 34899.80 8388.71 33799.04 31796.69 28796.55 27598.65 282
PatchT97.03 29196.44 29698.79 21998.99 28598.34 21699.16 25599.07 30292.13 35099.52 11197.31 36094.54 23198.98 32688.54 36198.73 19599.03 216
AUN-MVS96.88 29296.31 29898.59 23299.48 18097.04 27499.27 23099.22 28297.44 19798.51 29099.41 25891.97 29399.66 21997.71 21683.83 36199.07 213
FMVSNet196.84 29396.36 29798.29 26999.32 21897.26 26099.43 17099.48 14795.11 32298.55 28899.32 28583.95 36198.98 32695.81 30496.26 28398.62 294
test250696.81 29496.65 29297.29 32299.74 7692.21 36299.60 7885.06 38199.13 899.77 3799.93 487.82 35199.85 13699.38 2799.38 14499.80 56
MVS_030496.79 29596.52 29597.59 31399.22 24194.92 33699.04 28399.59 4496.49 27498.43 29698.99 32580.48 36899.39 25897.15 26299.27 15598.47 317
RPMNet96.72 29695.90 30699.19 15899.18 25098.49 20799.22 24999.52 9288.72 36099.56 10297.38 35794.08 24699.95 4786.87 36798.58 19999.14 200
test_040296.64 29796.24 29997.85 30098.85 30596.43 30099.44 16499.26 27693.52 34296.98 34199.52 22388.52 34199.20 29992.58 34997.50 24897.93 352
X-MVStestdata96.55 29895.45 31399.87 1299.85 2699.83 1799.69 4299.68 1998.98 3499.37 14664.01 37798.81 4999.94 5898.79 10299.86 5399.84 22
pmmvs696.53 29996.09 30297.82 30498.69 32495.47 32399.37 19999.47 16593.46 34497.41 33099.78 10287.06 35399.33 27596.92 27792.70 34598.65 282
ET-MVSNet_ETH3D96.49 30095.64 31199.05 17099.53 15798.82 17798.84 31797.51 36197.63 17584.77 36599.21 30492.09 29298.91 33798.98 6792.21 34799.41 185
UnsupCasMVSNet_eth96.44 30196.12 30197.40 31998.65 32795.65 31699.36 20399.51 10697.13 22496.04 35098.99 32588.40 34298.17 34896.71 28590.27 35198.40 327
FMVSNet596.43 30296.19 30097.15 32399.11 26595.89 31399.32 21599.52 9294.47 33598.34 30399.07 31687.54 35297.07 36392.61 34895.72 29898.47 317
new_pmnet96.38 30396.03 30397.41 31898.13 34695.16 33299.05 27899.20 28693.94 33797.39 33198.79 33591.61 30699.04 31790.43 35495.77 29598.05 343
Anonymous2023120696.22 30496.03 30396.79 33497.31 35794.14 34799.63 6599.08 30096.17 30097.04 34099.06 31893.94 24997.76 35886.96 36695.06 31298.47 317
IB-MVS95.67 1896.22 30495.44 31498.57 23699.21 24396.70 29098.65 33597.74 35996.71 25797.27 33398.54 34486.03 35599.92 8598.47 15086.30 35899.10 203
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
Anonymous2024052196.20 30695.89 30797.13 32597.72 35194.96 33599.79 2599.29 27293.01 34797.20 33699.03 32189.69 32998.36 34691.16 35296.13 28598.07 341
gg-mvs-nofinetune96.17 30795.32 31598.73 22398.79 30998.14 22599.38 19694.09 37591.07 35698.07 31691.04 37089.62 33199.35 27196.75 28299.09 17098.68 265
test20.0396.12 30895.96 30596.63 33597.44 35395.45 32499.51 12999.38 22496.55 27196.16 34899.25 29893.76 25596.17 36887.35 36594.22 32698.27 333
PVSNet_094.43 1996.09 30995.47 31297.94 29499.31 21994.34 34697.81 36299.70 1597.12 22697.46 32998.75 33889.71 32899.79 17297.69 21981.69 36499.68 112
EG-PatchMatch MVS95.97 31095.69 31096.81 33397.78 35092.79 35999.16 25598.93 31496.16 30294.08 35799.22 30182.72 36399.47 24395.67 30997.50 24898.17 338
Patchmatch-RL test95.84 31195.81 30995.95 34095.61 36590.57 36598.24 35598.39 34795.10 32495.20 35398.67 34094.78 21597.77 35796.28 29790.02 35299.51 164
MVS-HIRNet95.75 31295.16 31697.51 31699.30 22093.69 35398.88 31395.78 36985.09 36398.78 25892.65 36791.29 31099.37 26394.85 32399.85 6099.46 176
MIMVSNet195.51 31395.04 31796.92 33197.38 35495.60 31799.52 12499.50 12693.65 34196.97 34299.17 30685.28 35896.56 36788.36 36295.55 30298.60 306
MDA-MVSNet_test_wron95.45 31494.60 32098.01 28998.16 34597.21 26399.11 26999.24 28093.49 34380.73 37098.98 32893.02 26398.18 34794.22 33194.45 32298.64 284
TDRefinement95.42 31594.57 32197.97 29389.83 37496.11 30999.48 15198.75 33096.74 25596.68 34399.88 1988.65 33999.71 20498.37 15982.74 36398.09 340
YYNet195.36 31694.51 32297.92 29697.89 34897.10 26599.10 27199.23 28193.26 34680.77 36999.04 32092.81 26998.02 35194.30 32894.18 32798.64 284
pmmvs-eth3d95.34 31794.73 31997.15 32395.53 36795.94 31299.35 20999.10 29795.13 32093.55 35897.54 35588.15 34697.91 35494.58 32589.69 35497.61 356
KD-MVS_self_test95.00 31894.34 32396.96 32997.07 36295.39 32699.56 10699.44 19695.11 32297.13 33897.32 35991.86 29697.27 36290.35 35581.23 36598.23 337
MDA-MVSNet-bldmvs94.96 31993.98 32597.92 29698.24 34497.27 25899.15 25999.33 25093.80 33980.09 37199.03 32188.31 34397.86 35693.49 33894.36 32498.62 294
N_pmnet94.95 32095.83 30892.31 34698.47 33979.33 37399.12 26392.81 37993.87 33897.68 32699.13 31193.87 25199.01 32391.38 35196.19 28498.59 307
KD-MVS_2432*160094.62 32193.72 32797.31 32097.19 36095.82 31498.34 35099.20 28695.00 32597.57 32798.35 34887.95 34898.10 34992.87 34577.00 36898.01 345
miper_refine_blended94.62 32193.72 32797.31 32097.19 36095.82 31498.34 35099.20 28695.00 32597.57 32798.35 34887.95 34898.10 34992.87 34577.00 36898.01 345
CL-MVSNet_self_test94.49 32393.97 32696.08 33996.16 36393.67 35498.33 35299.38 22495.13 32097.33 33298.15 35292.69 27796.57 36688.67 36079.87 36697.99 348
new-patchmatchnet94.48 32494.08 32495.67 34195.08 36892.41 36099.18 25399.28 27494.55 33493.49 35997.37 35887.86 35097.01 36491.57 35088.36 35597.61 356
OpenMVS_ROBcopyleft92.34 2094.38 32593.70 32996.41 33897.38 35493.17 35799.06 27698.75 33086.58 36194.84 35698.26 35181.53 36699.32 27789.01 35997.87 23196.76 361
CMPMVSbinary69.68 2394.13 32694.90 31891.84 34797.24 35880.01 37298.52 34399.48 14789.01 35891.99 36299.67 16285.67 35799.13 30695.44 31297.03 26896.39 363
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs394.09 32793.25 33096.60 33694.76 36994.49 34298.92 30998.18 35289.66 35796.48 34598.06 35386.28 35497.33 36189.68 35787.20 35797.97 350
UnsupCasMVSNet_bld93.53 32892.51 33196.58 33797.38 35493.82 34998.24 35599.48 14791.10 35593.10 36096.66 36174.89 36998.37 34594.03 33387.71 35697.56 358
PM-MVS92.96 32992.23 33295.14 34295.61 36589.98 36799.37 19998.21 35094.80 32995.04 35597.69 35465.06 37197.90 35594.30 32889.98 35397.54 359
test_method91.10 33091.36 33390.31 35095.85 36473.72 37894.89 36799.25 27868.39 37095.82 35199.02 32380.50 36798.95 33593.64 33694.89 31798.25 335
Gipumacopyleft90.99 33190.15 33493.51 34398.73 31890.12 36693.98 36899.45 18779.32 36692.28 36194.91 36469.61 37097.98 35387.42 36495.67 29992.45 367
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMMVS286.87 33285.37 33691.35 34990.21 37383.80 36898.89 31297.45 36283.13 36591.67 36395.03 36348.49 37694.70 37085.86 36877.62 36795.54 364
LCM-MVSNet86.80 33385.22 33791.53 34887.81 37580.96 37198.23 35798.99 30871.05 36890.13 36496.51 36248.45 37796.88 36590.51 35385.30 35996.76 361
FPMVS84.93 33485.65 33582.75 35586.77 37663.39 38098.35 34998.92 31674.11 36783.39 36798.98 32850.85 37592.40 37284.54 36994.97 31492.46 366
EGC-MVSNET82.80 33577.86 34197.62 31197.91 34796.12 30899.33 21499.28 2748.40 37825.05 37999.27 29584.11 36099.33 27589.20 35898.22 21597.42 360
tmp_tt82.80 33581.52 33886.66 35166.61 38168.44 37992.79 37097.92 35568.96 36980.04 37299.85 3485.77 35696.15 36997.86 20043.89 37495.39 365
E-PMN80.61 33779.88 33982.81 35490.75 37276.38 37697.69 36395.76 37066.44 37283.52 36692.25 36862.54 37387.16 37468.53 37361.40 37184.89 372
EMVS80.02 33879.22 34082.43 35691.19 37176.40 37597.55 36592.49 38066.36 37383.01 36891.27 36964.63 37285.79 37565.82 37460.65 37285.08 371
ANet_high77.30 33974.86 34384.62 35375.88 37977.61 37497.63 36493.15 37888.81 35964.27 37489.29 37136.51 37883.93 37675.89 37152.31 37392.33 368
MVEpermissive76.82 2176.91 34074.31 34484.70 35285.38 37876.05 37796.88 36693.17 37767.39 37171.28 37389.01 37221.66 38387.69 37371.74 37272.29 37090.35 369
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVScopyleft70.75 2275.98 34174.97 34279.01 35770.98 38055.18 38193.37 36998.21 35065.08 37461.78 37593.83 36621.74 38292.53 37178.59 37091.12 35089.34 370
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
wuyk23d40.18 34241.29 34736.84 35886.18 37749.12 38279.73 37122.81 38327.64 37525.46 37828.45 37821.98 38148.89 37755.80 37523.56 37712.51 375
testmvs39.17 34343.78 34525.37 36036.04 38316.84 38498.36 34826.56 38220.06 37638.51 37767.32 37329.64 38015.30 37937.59 37639.90 37543.98 374
test12339.01 34442.50 34628.53 35939.17 38220.91 38398.75 32619.17 38419.83 37738.57 37666.67 37433.16 37915.42 37837.50 37729.66 37649.26 373
cdsmvs_eth3d_5k24.64 34532.85 3480.00 3610.00 3840.00 3850.00 37299.51 1060.00 3790.00 38099.56 20896.58 1520.00 3800.00 3780.00 3780.00 376
ab-mvs-re8.30 34611.06 3490.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 38099.58 2010.00 3840.00 3800.00 3780.00 3780.00 376
pcd_1.5k_mvsjas8.27 34711.03 3500.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.27 38099.01 190.00 3800.00 3780.00 3780.00 376
test_blank0.13 3480.17 3510.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3801.57 3790.00 3840.00 3800.00 3780.00 3780.00 376
uanet_test0.02 3490.03 3520.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.27 3800.00 3840.00 3800.00 3780.00 3780.00 376
DCPMVS0.02 3490.03 3520.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.27 3800.00 3840.00 3800.00 3780.00 3780.00 376
sosnet-low-res0.02 3490.03 3520.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.27 3800.00 3840.00 3800.00 3780.00 3780.00 376
sosnet0.02 3490.03 3520.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.27 3800.00 3840.00 3800.00 3780.00 3780.00 376
uncertanet0.02 3490.03 3520.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.27 3800.00 3840.00 3800.00 3780.00 3780.00 376
Regformer0.02 3490.03 3520.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.27 3800.00 3840.00 3800.00 3780.00 3780.00 376
uanet0.02 3490.03 3520.00 3610.00 3840.00 3850.00 3720.00 3850.00 3790.00 3800.27 3800.00 3840.00 3800.00 3780.00 3780.00 376
FOURS199.91 199.93 199.87 699.56 5899.10 1299.81 25
MSC_two_6792asdad99.87 1299.51 16199.76 4199.33 25099.96 2098.87 8399.84 6799.89 2
PC_three_145298.18 11299.84 1599.70 14099.31 398.52 34498.30 16799.80 8999.81 46
No_MVS99.87 1299.51 16199.76 4199.33 25099.96 2098.87 8399.84 6799.89 2
test_one_060199.81 4299.88 899.49 13498.97 3799.65 7999.81 6799.09 14
eth-test20.00 384
eth-test0.00 384
ZD-MVS99.71 9599.79 3399.61 3696.84 25099.56 10299.54 21698.58 7599.96 2096.93 27599.75 105
RE-MVS-def99.34 3299.76 5799.82 2399.63 6599.52 9298.38 8799.76 4499.82 5498.75 6098.61 12899.81 8599.77 72
IU-MVS99.84 3399.88 899.32 26098.30 9899.84 1598.86 8899.85 6099.89 2
OPU-MVS99.64 8099.56 15399.72 4799.60 7899.70 14099.27 599.42 25698.24 16999.80 8999.79 62
test_241102_TWO99.48 14799.08 1699.88 699.81 6798.94 3599.96 2098.91 7699.84 6799.88 8
test_241102_ONE99.84 3399.90 299.48 14799.07 1899.91 299.74 12499.20 799.76 184
9.1499.10 7499.72 8999.40 18799.51 10697.53 18799.64 8399.78 10298.84 4699.91 9697.63 22299.82 82
save fliter99.76 5799.59 7399.14 26199.40 21499.00 28
test_0728_THIRD98.99 3199.81 2599.80 8399.09 1499.96 2098.85 9099.90 2599.88 8
test_0728_SECOND99.91 299.84 3399.89 499.57 9999.51 10699.96 2098.93 7399.86 5399.88 8
test072699.85 2699.89 499.62 7199.50 12699.10 1299.86 1399.82 5498.94 35
GSMVS99.52 158
test_part299.81 4299.83 1799.77 37
sam_mvs194.86 21199.52 158
sam_mvs94.72 222
ambc93.06 34592.68 37082.36 36998.47 34598.73 33895.09 35497.41 35655.55 37499.10 31396.42 29491.32 34997.71 355
MTGPAbinary99.47 165
test_post199.23 24465.14 37694.18 24399.71 20497.58 226
test_post65.99 37594.65 22699.73 194
patchmatchnet-post98.70 33994.79 21499.74 187
GG-mvs-BLEND98.45 25298.55 33698.16 22399.43 17093.68 37697.23 33498.46 34589.30 33399.22 29295.43 31398.22 21597.98 349
MTMP99.54 11898.88 323
gm-plane-assit98.54 33792.96 35894.65 33299.15 30999.64 22697.56 231
test9_res97.49 23799.72 11299.75 78
TEST999.67 11099.65 6299.05 27899.41 20896.22 29698.95 23299.49 23398.77 5599.91 96
test_899.67 11099.61 6899.03 28499.41 20896.28 28998.93 23699.48 23998.76 5799.91 96
agg_prior297.21 25499.73 11199.75 78
agg_prior99.67 11099.62 6699.40 21498.87 24599.91 96
TestCases99.31 13999.86 2298.48 20999.61 3697.85 14899.36 14999.85 3495.95 17199.85 13696.66 28999.83 7699.59 143
test_prior499.56 7898.99 294
test_prior298.96 30298.34 9399.01 22199.52 22398.68 6897.96 19299.74 108
test_prior99.68 6899.67 11099.48 9399.56 5899.83 15399.74 83
旧先验298.96 30296.70 25899.47 11999.94 5898.19 172
新几何299.01 292
新几何199.75 5499.75 6899.59 7399.54 7596.76 25499.29 16399.64 17698.43 8799.94 5896.92 27799.66 12699.72 96
旧先验199.74 7699.59 7399.54 7599.69 14998.47 8499.68 12399.73 90
无先验98.99 29499.51 10696.89 24799.93 7397.53 23499.72 96
原ACMM298.95 306
原ACMM199.65 7599.73 8499.33 10899.47 16597.46 19199.12 20099.66 16898.67 7199.91 9697.70 21899.69 11899.71 103
test22299.75 6899.49 9198.91 31199.49 13496.42 28399.34 15599.65 16998.28 9999.69 11899.72 96
testdata299.95 4796.67 288
segment_acmp98.96 29
testdata99.54 9699.75 6898.95 15999.51 10697.07 23299.43 12799.70 14098.87 4399.94 5897.76 20999.64 12999.72 96
testdata198.85 31698.32 97
test1299.75 5499.64 12699.61 6899.29 27299.21 18498.38 9299.89 11999.74 10899.74 83
plane_prior799.29 22497.03 275
plane_prior699.27 22996.98 27992.71 275
plane_prior599.47 16599.69 21497.78 20797.63 23598.67 272
plane_prior499.61 192
plane_prior397.00 27798.69 6499.11 202
plane_prior299.39 19198.97 37
plane_prior199.26 231
plane_prior96.97 28099.21 25198.45 8197.60 238
n20.00 385
nn0.00 385
door-mid98.05 353
lessismore_v097.79 30698.69 32495.44 32594.75 37395.71 35299.87 2588.69 33899.32 27795.89 30294.93 31698.62 294
LGP-MVS_train98.49 24499.33 21197.05 27199.55 6797.46 19199.24 17699.83 4792.58 28099.72 19898.09 18197.51 24698.68 265
test1199.35 239
door97.92 355
HQP5-MVS96.83 285
HQP-NCC99.19 24798.98 29898.24 10298.66 273
ACMP_Plane99.19 24798.98 29898.24 10298.66 273
BP-MVS97.19 258
HQP4-MVS98.66 27399.64 22698.64 284
HQP3-MVS99.39 21897.58 240
HQP2-MVS92.47 284
NP-MVS99.23 23796.92 28399.40 261
MDTV_nov1_ep13_2view95.18 33199.35 20996.84 25099.58 9995.19 20297.82 20499.46 176
MDTV_nov1_ep1398.32 16499.11 26594.44 34399.27 23098.74 33397.51 18999.40 13999.62 18894.78 21599.76 18497.59 22598.81 192
ACMMP++_ref97.19 264
ACMMP++97.43 256
Test By Simon98.75 60
ITE_SJBPF98.08 28399.29 22496.37 30198.92 31698.34 9398.83 25199.75 11891.09 31299.62 23295.82 30397.40 25898.25 335
DeepMVS_CXcopyleft93.34 34499.29 22482.27 37099.22 28285.15 36296.33 34699.05 31990.97 31499.73 19493.57 33797.77 23398.01 345