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.
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SED-MVS99.28 599.11 799.77 899.93 2799.30 1199.96 2598.43 12097.27 2199.80 1799.94 496.71 24100.00 1100.00 1100.00 1100.00 1
IU-MVS99.93 2799.31 998.41 13697.71 899.84 9100.00 1100.00 1100.00 1
OPU-MVS99.93 299.89 5099.80 299.96 2599.80 6097.44 14100.00 1100.00 199.98 35100.00 1
test_241102_TWO98.43 12097.27 2199.80 1799.94 497.18 21100.00 1100.00 1100.00 1100.00 1
PC_three_145296.96 3099.80 1799.79 6497.49 10100.00 199.99 599.98 35100.00 1
DVP-MVScopyleft99.30 499.16 399.73 1199.93 2799.29 1499.95 4398.32 16097.28 1999.83 1199.91 1597.22 19100.00 199.99 5100.00 199.89 94
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
test_0728_SECOND99.82 799.94 1499.47 799.95 4398.43 120100.00 199.99 5100.00 1100.00 1
DPE-MVScopyleft99.26 699.10 899.74 1099.89 5099.24 1899.87 9398.44 11297.48 1699.64 3999.94 496.68 2699.99 4099.99 5100.00 199.99 24
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
MSC_two_6792asdad99.93 299.91 4499.80 298.41 136100.00 199.96 9100.00 1100.00 1
No_MVS99.93 299.91 4499.80 298.41 136100.00 199.96 9100.00 1100.00 1
ETH3 D test640098.81 2398.54 2899.59 2199.93 2798.93 2699.93 6798.46 10794.56 10599.84 999.92 1394.32 8499.86 9599.96 999.98 35100.00 1
patch_mono-298.24 6499.12 595.59 21399.67 9286.91 32999.95 4398.89 4397.60 1299.90 299.76 7696.54 2899.98 4699.94 1299.82 9199.88 96
DVP-MVS++99.26 699.09 999.77 899.91 4499.31 999.95 4398.43 12096.48 4399.80 1799.93 1197.44 14100.00 199.92 1399.98 35100.00 1
test_0728_THIRD96.48 4399.83 1199.91 1597.87 6100.00 199.92 13100.00 1100.00 1
DeepPCF-MVS95.94 297.71 8798.98 1293.92 27799.63 9481.76 35599.96 2598.56 7999.47 199.19 8199.99 194.16 91100.00 199.92 1399.93 67100.00 1
TSAR-MVS + GP.98.60 3498.51 3098.86 9099.73 8696.63 13099.97 1897.92 20798.07 598.76 10199.55 11295.00 6099.94 7399.91 1697.68 15999.99 24
dcpmvs_297.42 9798.09 6095.42 21899.58 10087.24 32699.23 22596.95 30094.28 12098.93 9399.73 8994.39 7899.16 16499.89 1799.82 9199.86 100
APDe-MVS99.06 1198.91 1499.51 3199.94 1498.76 4499.91 7598.39 14397.20 2599.46 5799.85 3595.53 4699.79 11499.86 18100.00 199.99 24
xxxxxxxxxxxxxcwj98.98 1598.79 1799.54 2699.82 7098.79 3799.96 2597.52 24497.66 1099.81 1399.89 2194.70 6899.86 9599.84 1999.93 6799.96 74
SF-MVS98.67 3198.40 3799.50 3299.77 7898.67 4899.90 8098.21 17793.53 15399.81 1399.89 2194.70 6899.86 9599.84 1999.93 6799.96 74
9.1498.38 4099.87 5799.91 7598.33 15893.22 16299.78 2599.89 2194.57 7199.85 9999.84 1999.97 48
ETH3D-3000-0.198.68 3098.42 3399.47 3799.83 6898.57 5599.90 8098.37 15093.81 14499.81 1399.90 1994.34 8099.86 9599.84 1999.98 3599.97 67
SD-MVS98.92 1798.70 1999.56 2499.70 9098.73 4599.94 6198.34 15796.38 4899.81 1399.76 7694.59 7099.98 4699.84 1999.96 5299.97 67
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
TSAR-MVS + MP.98.93 1698.77 1899.41 4299.74 8298.67 4899.77 13298.38 14796.73 3799.88 499.74 8794.89 6599.59 14599.80 2499.98 3599.97 67
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
PHI-MVS98.41 5098.21 5199.03 7899.86 5997.10 11699.98 998.80 5290.78 24199.62 4399.78 7095.30 50100.00 199.80 2499.93 6799.99 24
test_prior398.99 1498.84 1699.43 3899.94 1498.49 6199.95 4398.65 6295.78 6499.73 3099.76 7696.00 3399.80 11199.78 26100.00 199.99 24
test_prior299.95 4395.78 6499.73 3099.76 7696.00 3399.78 26100.00 1
CANet98.27 6097.82 7599.63 1599.72 8899.10 2199.98 998.51 9997.00 2998.52 11199.71 9387.80 19999.95 6599.75 2899.38 11999.83 102
CNVR-MVS99.40 199.26 199.84 699.98 299.51 699.98 998.69 5798.20 399.93 199.98 296.82 23100.00 199.75 28100.00 199.99 24
ETH3D cwj APD-0.1698.40 5298.07 6299.40 4499.59 9698.41 6499.86 10598.24 17392.18 20399.73 3099.87 2893.47 10799.85 9999.74 3099.95 5599.93 85
SMA-MVScopyleft98.76 2798.48 3199.62 1899.87 5798.87 3199.86 10598.38 14793.19 16399.77 2699.94 495.54 44100.00 199.74 3099.99 22100.00 1
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
MCST-MVS99.32 399.14 499.86 599.97 399.59 599.97 1898.64 6598.47 299.13 8399.92 1396.38 30100.00 199.74 30100.00 1100.00 1
CHOSEN 280x42099.01 1399.03 1098.95 8699.38 11198.87 3198.46 29499.42 2197.03 2899.02 8799.09 14599.35 198.21 22599.73 3399.78 9499.77 110
agg_prior198.88 2098.66 2199.54 2699.93 2798.77 4099.96 2598.43 12094.63 10399.63 4099.85 3595.79 4199.85 9999.72 3499.99 2299.99 24
test9_res99.71 3599.99 22100.00 1
ZD-MVS99.92 3698.57 5598.52 9292.34 19899.31 7199.83 5195.06 5699.80 11199.70 3699.97 48
train_agg98.88 2098.65 2299.59 2199.92 3698.92 2799.96 2598.43 12094.35 11599.71 3499.86 3195.94 3599.85 9999.69 3799.98 3599.99 24
testtj98.89 1998.69 2099.52 2999.94 1498.56 5799.90 8098.55 8595.14 8499.72 3399.84 4895.46 47100.00 199.65 3899.99 2299.99 24
NCCC99.37 299.25 299.71 1399.96 899.15 2099.97 1898.62 6998.02 699.90 299.95 397.33 17100.00 199.54 39100.00 1100.00 1
MSLP-MVS++99.13 899.01 1199.49 3499.94 1498.46 6399.98 998.86 4797.10 2699.80 1799.94 495.92 37100.00 199.51 40100.00 1100.00 1
MSP-MVS99.09 999.12 598.98 8399.93 2797.24 10999.95 4398.42 13297.50 1599.52 5499.88 2497.43 1699.71 13499.50 4199.98 35100.00 1
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
agg_prior299.48 42100.00 1100.00 1
PAPM98.60 3498.42 3399.14 6696.05 25998.96 2499.90 8099.35 2496.68 3998.35 12099.66 10496.45 2998.51 19399.45 4399.89 7899.96 74
SteuartSystems-ACMMP99.02 1298.97 1399.18 5798.72 14797.71 8699.98 998.44 11296.85 3199.80 1799.91 1597.57 899.85 9999.44 4499.99 2299.99 24
Skip Steuart: Steuart Systems R&D Blog.
APD-MVScopyleft98.62 3398.35 4599.41 4299.90 4798.51 6099.87 9398.36 15294.08 12899.74 2999.73 8994.08 9299.74 13099.42 4599.99 2299.99 24
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
PS-MVSNAJ98.44 4898.20 5299.16 6298.80 14498.92 2799.54 18498.17 18297.34 1799.85 799.85 3591.20 15799.89 8499.41 4699.67 10198.69 211
xiu_mvs_v2_base98.23 6597.97 6799.02 8098.69 14898.66 5099.52 18698.08 19397.05 2799.86 599.86 3190.65 16899.71 13499.39 4798.63 13698.69 211
test117298.38 5498.25 4998.77 9399.88 5496.56 13499.80 12598.36 15294.68 10099.20 7899.80 6093.28 11499.78 11699.34 4899.92 7199.98 55
HPM-MVS++copyleft99.07 1098.88 1599.63 1599.90 4799.02 2399.95 4398.56 7997.56 1499.44 5999.85 3595.38 49100.00 199.31 4999.99 2299.87 98
SR-MVS98.46 4698.30 4898.93 8799.88 5497.04 11799.84 11298.35 15594.92 9199.32 7099.80 6093.35 10999.78 11699.30 5099.95 5599.96 74
MVS_111021_HR98.72 2898.62 2499.01 8199.36 11297.18 11299.93 6799.90 196.81 3598.67 10599.77 7293.92 9699.89 8499.27 5199.94 6199.96 74
MVS_111021_LR98.42 4998.38 4098.53 11599.39 11095.79 16199.87 9399.86 296.70 3898.78 9899.79 6492.03 14799.90 8099.17 5299.86 8399.88 96
PVSNet_BlendedMVS96.05 14595.82 14496.72 18599.59 9696.99 12099.95 4399.10 2994.06 13198.27 12395.80 27289.00 19099.95 6599.12 5387.53 26693.24 327
PVSNet_Blended97.94 7397.64 7998.83 9199.59 9696.99 120100.00 199.10 2995.38 7898.27 12399.08 14689.00 19099.95 6599.12 5399.25 12399.57 146
Regformer-198.79 2598.60 2599.36 4899.85 6098.34 6699.87 9398.52 9296.05 5799.41 6299.79 6494.93 6399.76 12399.07 5599.90 7699.99 24
xiu_mvs_v1_base_debu97.43 9397.06 9898.55 11097.74 19998.14 7099.31 21597.86 21396.43 4599.62 4399.69 9885.56 22199.68 13899.05 5698.31 14397.83 220
xiu_mvs_v1_base97.43 9397.06 9898.55 11097.74 19998.14 7099.31 21597.86 21396.43 4599.62 4399.69 9885.56 22199.68 13899.05 5698.31 14397.83 220
xiu_mvs_v1_base_debi97.43 9397.06 9898.55 11097.74 19998.14 7099.31 21597.86 21396.43 4599.62 4399.69 9885.56 22199.68 13899.05 5698.31 14397.83 220
Regformer-298.78 2698.59 2699.36 4899.85 6098.32 6799.87 9398.52 9296.04 5899.41 6299.79 6494.92 6499.76 12399.05 5699.90 7699.98 55
CP-MVS98.45 4798.32 4698.87 8999.96 896.62 13199.97 1898.39 14394.43 11098.90 9499.87 2894.30 85100.00 199.04 6099.99 2299.99 24
DeepC-MVS_fast96.59 198.81 2398.54 2899.62 1899.90 4798.85 3399.24 22498.47 10598.14 499.08 8499.91 1593.09 120100.00 199.04 6099.99 22100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ETV-MVS97.92 7597.80 7698.25 13098.14 17796.48 13599.98 997.63 22795.61 7299.29 7599.46 12092.55 13498.82 17499.02 6298.54 13799.46 162
VDD-MVS93.77 20192.94 20796.27 20198.55 15490.22 29298.77 27797.79 21890.85 23996.82 15699.42 12261.18 35999.77 12098.95 6394.13 21598.82 206
APD-MVS_3200maxsize98.25 6398.08 6198.78 9299.81 7396.60 13299.82 11998.30 16593.95 13899.37 6899.77 7292.84 12699.76 12398.95 6399.92 7199.97 67
VNet97.21 10596.57 11599.13 7198.97 12897.82 8499.03 24899.21 2894.31 11899.18 8298.88 17086.26 21699.89 8498.93 6594.32 21399.69 119
XVS98.70 2998.55 2799.15 6499.94 1497.50 9999.94 6198.42 13296.22 5399.41 6299.78 7094.34 8099.96 5898.92 6699.95 5599.99 24
X-MVStestdata93.83 19792.06 22899.15 6499.94 1497.50 9999.94 6198.42 13296.22 5399.41 6241.37 38094.34 8099.96 5898.92 6699.95 5599.99 24
MP-MVS-pluss98.07 7097.64 7999.38 4799.74 8298.41 6499.74 14398.18 18193.35 15796.45 16699.85 3592.64 13299.97 5698.91 6899.89 7899.77 110
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
SR-MVS-dyc-post98.31 5798.17 5498.71 9699.79 7596.37 14199.76 13798.31 16294.43 11099.40 6699.75 8293.28 11499.78 11698.90 6999.92 7199.97 67
RE-MVS-def98.13 5799.79 7596.37 14199.76 13798.31 16294.43 11099.40 6699.75 8292.95 12398.90 6999.92 7199.97 67
HPM-MVScopyleft97.96 7297.72 7798.68 9899.84 6596.39 14099.90 8098.17 18292.61 18698.62 10899.57 11191.87 15099.67 14198.87 7199.99 2299.99 24
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
MP-MVScopyleft98.23 6597.97 6799.03 7899.94 1497.17 11599.95 4398.39 14394.70 9998.26 12599.81 5991.84 151100.00 198.85 7299.97 4899.93 85
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
test_yl97.83 7997.37 8899.21 5499.18 11697.98 7899.64 16899.27 2691.43 22697.88 13498.99 15495.84 3999.84 10898.82 7395.32 20599.79 106
DCV-MVSNet97.83 7997.37 8899.21 5499.18 11697.98 7899.64 16899.27 2691.43 22697.88 13498.99 15495.84 3999.84 10898.82 7395.32 20599.79 106
Regformer-398.58 3798.41 3599.10 7299.84 6597.57 9299.66 16098.52 9295.79 6399.01 8899.77 7294.40 7499.75 12698.82 7399.83 8599.98 55
Regformer-498.56 3898.39 3999.08 7499.84 6597.52 9599.66 16098.52 9295.76 6699.01 8899.77 7294.33 8399.75 12698.80 7699.83 8599.98 55
#test#98.59 3698.41 3599.14 6699.96 897.43 10499.95 4398.61 7195.00 8799.31 7199.85 3594.22 87100.00 198.78 7799.98 3599.98 55
PVSNet_088.03 1991.80 24890.27 26096.38 19898.27 16990.46 28899.94 6199.61 1293.99 13586.26 31597.39 22871.13 32899.89 8498.77 7867.05 36298.79 208
DROMVSNet97.38 10097.24 9397.80 14497.41 21595.64 16999.99 397.06 28794.59 10499.63 4099.32 13089.20 18898.14 22798.76 7999.23 12499.62 133
CS-MVS-test97.88 7697.94 7197.70 15299.28 11595.20 18399.98 997.15 27795.53 7599.62 4399.79 6492.08 14698.38 20998.75 8099.28 12299.52 155
MG-MVS98.91 1898.65 2299.68 1499.94 1499.07 2299.64 16899.44 1997.33 1899.00 9099.72 9194.03 9499.98 4698.73 81100.00 1100.00 1
HFP-MVS98.56 3898.37 4299.14 6699.96 897.43 10499.95 4398.61 7194.77 9699.31 7199.85 3594.22 87100.00 198.70 8299.98 3599.98 55
ACMMPR98.50 4398.32 4699.05 7699.96 897.18 11299.95 4398.60 7394.77 9699.31 7199.84 4893.73 102100.00 198.70 8299.98 3599.98 55
zzz-MVS98.33 5698.00 6599.30 5099.85 6097.93 8199.80 12598.28 16795.76 6697.18 14799.88 2492.74 129100.00 198.67 8499.88 8099.99 24
MTAPA98.29 5997.96 7099.30 5099.85 6097.93 8199.39 20598.28 16795.76 6697.18 14799.88 2492.74 129100.00 198.67 8499.88 8099.99 24
region2R98.54 4098.37 4299.05 7699.96 897.18 11299.96 2598.55 8594.87 9499.45 5899.85 3594.07 93100.00 198.67 84100.00 199.98 55
ACMMP_NAP98.49 4498.14 5699.54 2699.66 9398.62 5499.85 10898.37 15094.68 10099.53 5199.83 5192.87 125100.00 198.66 8799.84 8499.99 24
mPP-MVS98.39 5398.20 5298.97 8499.97 396.92 12399.95 4398.38 14795.04 8698.61 10999.80 6093.39 108100.00 198.64 88100.00 199.98 55
DELS-MVS98.54 4098.22 5099.50 3299.15 11998.65 52100.00 198.58 7597.70 998.21 12799.24 13992.58 13399.94 7398.63 8999.94 6199.92 91
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
alignmvs97.81 8197.33 9199.25 5298.77 14698.66 5099.99 398.44 11294.40 11498.41 11699.47 11893.65 10499.42 15698.57 9094.26 21499.67 122
CDPH-MVS98.65 3298.36 4499.49 3499.94 1498.73 4599.87 9398.33 15893.97 13699.76 2799.87 2894.99 6199.75 12698.55 91100.00 199.98 55
EI-MVSNet-Vis-set98.27 6098.11 5998.75 9599.83 6896.59 13399.40 20198.51 9995.29 8198.51 11299.76 7693.60 10699.71 13498.53 9299.52 11299.95 82
canonicalmvs97.09 10996.32 12199.39 4698.93 13298.95 2599.72 15197.35 26094.45 10897.88 13499.42 12286.71 21099.52 14798.48 9393.97 21899.72 116
API-MVS97.86 7797.66 7898.47 11899.52 10395.41 17499.47 19598.87 4691.68 21898.84 9599.85 3592.34 14099.99 4098.44 9499.96 52100.00 1
lupinMVS97.85 7897.60 8198.62 10397.28 22597.70 8899.99 397.55 23895.50 7799.43 6099.67 10290.92 16498.71 18398.40 9599.62 10499.45 164
CS-MVS97.79 8397.91 7397.43 16299.10 12094.42 19899.99 397.10 28295.07 8599.68 3799.75 8292.95 12398.34 21398.38 9699.14 12799.54 151
EI-MVSNet-UG-set98.14 6797.99 6698.60 10599.80 7496.27 14399.36 21098.50 10395.21 8398.30 12299.75 8293.29 11399.73 13398.37 9799.30 12199.81 104
diffmvs97.00 11096.64 11298.09 13697.64 20696.17 15199.81 12197.19 27194.67 10298.95 9199.28 13186.43 21398.76 17998.37 9797.42 16599.33 178
CPTT-MVS97.64 8997.32 9298.58 10899.97 395.77 16299.96 2598.35 15589.90 25498.36 11999.79 6491.18 16099.99 4098.37 9799.99 2299.99 24
ZNCC-MVS98.31 5798.03 6399.17 6099.88 5497.59 9199.94 6198.44 11294.31 11898.50 11399.82 5593.06 12199.99 4098.30 10099.99 2299.93 85
DP-MVS Recon98.41 5098.02 6499.56 2499.97 398.70 4799.92 7198.44 11292.06 20898.40 11899.84 4895.68 42100.00 198.19 10199.71 9999.97 67
GG-mvs-BLEND98.54 11398.21 17298.01 7693.87 35498.52 9297.92 13297.92 21499.02 297.94 24198.17 10299.58 10999.67 122
GST-MVS98.27 6097.97 6799.17 6099.92 3697.57 9299.93 6798.39 14394.04 13498.80 9799.74 8792.98 122100.00 198.16 10399.76 9599.93 85
CSCG97.10 10797.04 10197.27 17199.89 5091.92 25799.90 8099.07 3288.67 27495.26 18999.82 5593.17 11999.98 4698.15 10499.47 11599.90 93
MAR-MVS97.43 9397.19 9598.15 13599.47 10794.79 19399.05 24698.76 5392.65 18498.66 10699.82 5588.52 19699.98 4698.12 10599.63 10399.67 122
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
PAPR98.52 4298.16 5599.58 2399.97 398.77 4099.95 4398.43 12095.35 7998.03 12999.75 8294.03 9499.98 4698.11 10699.83 8599.99 24
CLD-MVS94.06 19593.90 18494.55 25096.02 26090.69 28099.98 997.72 22096.62 4291.05 23398.85 17777.21 28898.47 19498.11 10689.51 23594.48 243
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
VDDNet93.12 21691.91 23296.76 18396.67 25292.65 24198.69 28398.21 17782.81 33897.75 13799.28 13161.57 35799.48 15498.09 10894.09 21698.15 216
HY-MVS92.50 797.79 8397.17 9799.63 1598.98 12799.32 897.49 32299.52 1495.69 7098.32 12197.41 22693.32 11199.77 12098.08 10995.75 19899.81 104
EIA-MVS97.53 9197.46 8597.76 14998.04 18194.84 19099.98 997.61 23294.41 11397.90 13399.59 10992.40 13898.87 17298.04 11099.13 12899.59 139
LFMVS94.75 17693.56 19498.30 12899.03 12395.70 16798.74 27897.98 20087.81 28798.47 11499.39 12667.43 34199.53 14698.01 11195.20 20799.67 122
AdaColmapbinary97.23 10496.80 10898.51 11699.99 195.60 17099.09 23598.84 4993.32 15996.74 15899.72 9186.04 217100.00 198.01 11199.43 11899.94 84
EPNet98.49 4498.40 3798.77 9399.62 9596.80 12799.90 8099.51 1697.60 1299.20 7899.36 12993.71 10399.91 7997.99 11398.71 13599.61 136
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
ACMMPcopyleft97.74 8697.44 8698.66 10099.92 3696.13 15299.18 22999.45 1894.84 9596.41 16999.71 9391.40 15499.99 4097.99 11398.03 15599.87 98
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
WTY-MVS98.10 6997.60 8199.60 2098.92 13499.28 1699.89 8899.52 1495.58 7398.24 12699.39 12693.33 11099.74 13097.98 11595.58 20199.78 109
jason97.24 10396.86 10598.38 12695.73 27197.32 10899.97 1897.40 25795.34 8098.60 11099.54 11487.70 20098.56 19097.94 11699.47 11599.25 185
jason: jason.
BP-MVS97.92 117
HQP-MVS94.61 18194.50 17294.92 23495.78 26591.85 25899.87 9397.89 20996.82 3293.37 20998.65 18380.65 26498.39 20597.92 11789.60 23094.53 239
h-mvs3394.92 17194.36 17496.59 18998.85 14191.29 27398.93 25998.94 3795.90 6098.77 9998.42 19990.89 16699.77 12097.80 11970.76 35298.72 210
hse-mvs294.38 18794.08 18095.31 22298.27 16990.02 29799.29 22098.56 7995.90 6098.77 9998.00 20890.89 16698.26 22397.80 11969.20 35897.64 225
131496.84 11695.96 13599.48 3696.74 24998.52 5998.31 30198.86 4795.82 6289.91 24698.98 15687.49 20299.96 5897.80 11999.73 9799.96 74
HQP_MVS94.49 18594.36 17494.87 23595.71 27491.74 26299.84 11297.87 21196.38 4893.01 21398.59 18780.47 26898.37 21197.79 12289.55 23394.52 241
plane_prior597.87 21198.37 21197.79 12289.55 23394.52 241
gg-mvs-nofinetune93.51 20791.86 23498.47 11897.72 20397.96 8092.62 35898.51 9974.70 36197.33 14469.59 37298.91 397.79 24497.77 12499.56 11099.67 122
casdiffmvs96.42 13495.97 13397.77 14897.30 22394.98 18699.84 11297.09 28493.75 14896.58 16299.26 13785.07 22698.78 17797.77 12497.04 17399.54 151
PGM-MVS98.34 5598.13 5798.99 8299.92 3697.00 11999.75 14099.50 1793.90 14199.37 6899.76 7693.24 117100.00 197.75 12699.96 5299.98 55
DeepC-MVS94.51 496.92 11496.40 12098.45 12099.16 11895.90 15899.66 16098.06 19496.37 5194.37 19899.49 11783.29 24099.90 8097.63 12799.61 10799.55 148
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
HPM-MVS_fast97.80 8297.50 8498.68 9899.79 7596.42 13799.88 9098.16 18591.75 21798.94 9299.54 11491.82 15299.65 14397.62 12899.99 2299.99 24
baseline96.43 13395.98 13097.76 14997.34 21995.17 18499.51 18897.17 27493.92 14096.90 15399.28 13185.37 22498.64 18797.50 12996.86 17899.46 162
abl_697.67 8897.34 9098.66 10099.68 9196.11 15599.68 15698.14 18893.80 14599.27 7699.70 9588.65 19599.98 4697.46 13099.72 9899.89 94
PLCcopyleft95.54 397.93 7497.89 7498.05 13899.82 7094.77 19499.92 7198.46 10793.93 13997.20 14699.27 13495.44 4899.97 5697.41 13199.51 11499.41 169
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MVS96.60 12895.56 14999.72 1296.85 24299.22 1998.31 30198.94 3791.57 22090.90 23499.61 10886.66 21199.96 5897.36 13299.88 8099.99 24
XVG-OURS-SEG-HR94.79 17394.70 17095.08 22898.05 18089.19 30699.08 23797.54 24093.66 15094.87 19299.58 11078.78 27999.79 11497.31 13393.40 22296.25 233
3Dnovator91.47 1296.28 14195.34 15499.08 7496.82 24497.47 10299.45 19898.81 5095.52 7689.39 26099.00 15381.97 24799.95 6597.27 13499.83 8599.84 101
iter_conf0596.07 14495.95 13796.44 19498.43 16097.52 9599.91 7596.85 31194.16 12492.49 22297.98 21198.20 497.34 25997.26 13588.29 25394.45 250
cascas94.64 18093.61 18997.74 15197.82 19396.26 14499.96 2597.78 21985.76 31394.00 20397.54 22276.95 29199.21 15997.23 13695.43 20397.76 224
LCM-MVSNet-Re92.31 23692.60 21591.43 31697.53 21079.27 36599.02 24991.83 37292.07 20680.31 34494.38 32883.50 23895.48 33597.22 13797.58 16199.54 151
CNLPA97.76 8597.38 8798.92 8899.53 10296.84 12599.87 9398.14 18893.78 14696.55 16499.69 9892.28 14199.98 4697.13 13899.44 11799.93 85
Effi-MVS+96.30 13995.69 14698.16 13297.85 19196.26 14497.41 32397.21 27090.37 24698.65 10798.58 18986.61 21298.70 18497.11 13997.37 16799.52 155
PVSNet_Blended_VisFu97.27 10296.81 10798.66 10098.81 14396.67 12999.92 7198.64 6594.51 10796.38 17098.49 19389.05 18999.88 9097.10 14098.34 14199.43 167
3Dnovator+91.53 1196.31 13895.24 15699.52 2996.88 24198.64 5399.72 15198.24 17395.27 8288.42 28598.98 15682.76 24299.94 7397.10 14099.83 8599.96 74
iter_conf_final96.01 14795.93 13896.28 20098.38 16297.03 11899.87 9397.03 29194.05 13392.61 22097.98 21198.01 597.34 25997.02 14288.39 25294.47 244
PAPM_NR98.12 6897.93 7298.70 9799.94 1496.13 15299.82 11998.43 12094.56 10597.52 14099.70 9594.40 7499.98 4697.00 14399.98 3599.99 24
CHOSEN 1792x268896.81 11796.53 11697.64 15398.91 13693.07 22899.65 16499.80 395.64 7195.39 18698.86 17484.35 23399.90 8096.98 14499.16 12699.95 82
旧先验299.46 19794.21 12399.85 799.95 6596.96 145
PMMVS96.76 12096.76 10996.76 18398.28 16892.10 25299.91 7597.98 20094.12 12699.53 5199.39 12686.93 20998.73 18196.95 14697.73 15799.45 164
EPP-MVSNet96.69 12596.60 11396.96 17797.74 19993.05 23099.37 20898.56 7988.75 27295.83 18099.01 15196.01 3298.56 19096.92 14797.20 17099.25 185
ET-MVSNet_ETH3D94.37 18893.28 20497.64 15398.30 16597.99 7799.99 397.61 23294.35 11571.57 36399.45 12196.23 3195.34 33896.91 14885.14 28299.59 139
HyFIR lowres test96.66 12796.43 11997.36 16899.05 12293.91 21099.70 15399.80 390.54 24396.26 17298.08 20592.15 14498.23 22496.84 14995.46 20299.93 85
OMC-MVS97.28 10197.23 9497.41 16399.76 7993.36 22699.65 16497.95 20396.03 5997.41 14399.70 9589.61 17999.51 14896.73 15098.25 14699.38 171
mvsmamba94.10 19393.72 18895.25 22493.57 30894.13 20399.67 15996.45 33093.63 15291.34 23097.77 21786.29 21597.22 27096.65 15188.10 25694.40 252
CostFormer96.10 14395.88 14296.78 18297.03 23292.55 24397.08 33097.83 21690.04 25398.72 10394.89 31495.01 5998.29 21796.54 15295.77 19699.50 159
sss97.57 9097.03 10299.18 5798.37 16398.04 7599.73 14899.38 2293.46 15598.76 10199.06 14791.21 15699.89 8496.33 15397.01 17499.62 133
114514_t97.41 9896.83 10699.14 6699.51 10597.83 8399.89 8898.27 17088.48 27899.06 8599.66 10490.30 17299.64 14496.32 15499.97 4899.96 74
ACMP92.05 992.74 22592.42 22293.73 28295.91 26488.72 31199.81 12197.53 24294.13 12587.00 30298.23 20274.07 31698.47 19496.22 15588.86 24293.99 295
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
IB-MVS92.85 694.99 17093.94 18398.16 13297.72 20395.69 16899.99 398.81 5094.28 12092.70 21996.90 24395.08 5499.17 16396.07 15673.88 35099.60 138
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
XVG-OURS94.82 17294.74 16995.06 22998.00 18289.19 30699.08 23797.55 23894.10 12794.71 19399.62 10780.51 26699.74 13096.04 15793.06 22696.25 233
ab-mvs94.69 17793.42 19898.51 11698.07 17996.26 14496.49 33798.68 5890.31 24894.54 19497.00 24176.30 29899.71 13495.98 15893.38 22399.56 147
mvs_anonymous95.65 15895.03 16397.53 15698.19 17395.74 16499.33 21297.49 24890.87 23890.47 23897.10 23588.23 19797.16 27395.92 15997.66 16099.68 120
nrg03093.51 20792.53 21996.45 19294.36 29597.20 11199.81 12197.16 27691.60 21989.86 24897.46 22486.37 21497.68 24795.88 16080.31 31994.46 245
LPG-MVS_test92.96 21992.71 21393.71 28495.43 28088.67 31299.75 14097.62 22992.81 17390.05 24198.49 19375.24 30698.40 20395.84 16189.12 23794.07 287
LGP-MVS_train93.71 28495.43 28088.67 31297.62 22992.81 17390.05 24198.49 19375.24 30698.40 20395.84 16189.12 23794.07 287
bld_raw_conf00592.79 22392.18 22494.61 24593.38 31592.27 24898.99 25195.20 35693.34 15889.25 26497.67 22078.03 28697.21 27195.81 16387.99 25994.35 260
VPA-MVSNet92.70 22791.55 23996.16 20395.09 28496.20 14998.88 26499.00 3491.02 23691.82 22595.29 30176.05 30297.96 23895.62 16481.19 30794.30 264
ECVR-MVScopyleft95.66 15795.05 16297.51 15898.66 15093.71 21498.85 27098.45 10994.93 8996.86 15498.96 16075.22 30899.20 16095.34 16598.15 14799.64 128
F-COLMAP96.93 11396.95 10496.87 18099.71 8991.74 26299.85 10897.95 20393.11 16695.72 18299.16 14392.35 13999.94 7395.32 16699.35 12098.92 200
BH-w/o95.71 15595.38 15396.68 18698.49 15892.28 24799.84 11297.50 24792.12 20592.06 22498.79 17884.69 22898.67 18695.29 16799.66 10299.09 196
原ACMM198.96 8599.73 8696.99 12098.51 9994.06 13199.62 4399.85 3594.97 6299.96 5895.11 16899.95 5599.92 91
RRT_MVS93.14 21592.92 20893.78 28193.31 31690.04 29699.66 16097.69 22292.53 19288.91 27497.76 21884.36 23196.93 29395.10 16986.99 26994.37 255
Anonymous20240521193.10 21791.99 23096.40 19699.10 12089.65 30398.88 26497.93 20583.71 33394.00 20398.75 17968.79 33399.88 9095.08 17091.71 22899.68 120
test111195.57 15994.98 16497.37 16698.56 15293.37 22598.86 26898.45 10994.95 8896.63 16098.95 16475.21 30999.11 16595.02 17198.14 14999.64 128
testdata98.42 12399.47 10795.33 17698.56 7993.78 14699.79 2499.85 3593.64 10599.94 7394.97 17299.94 61100.00 1
test250697.53 9197.19 9598.58 10898.66 15096.90 12498.81 27399.77 594.93 8997.95 13198.96 16092.51 13599.20 16094.93 17398.15 14799.64 128
gm-plane-assit96.97 23593.76 21391.47 22498.96 16098.79 17694.92 174
PVSNet91.05 1397.13 10696.69 11198.45 12099.52 10395.81 16099.95 4399.65 1194.73 9899.04 8699.21 14184.48 23099.95 6594.92 17498.74 13499.58 145
tpmrst96.27 14295.98 13097.13 17397.96 18493.15 22796.34 33998.17 18292.07 20698.71 10495.12 30593.91 9798.73 18194.91 17696.62 17999.50 159
VPNet91.81 24590.46 25495.85 21094.74 29095.54 17198.98 25398.59 7492.14 20490.77 23697.44 22568.73 33597.54 25294.89 17777.89 33394.46 245
baseline296.71 12496.49 11797.37 16695.63 27895.96 15799.74 14398.88 4592.94 16891.61 22698.97 15897.72 798.62 18894.83 17898.08 15497.53 228
Effi-MVS+-dtu94.53 18495.30 15592.22 30897.77 19682.54 34899.59 17497.06 28794.92 9195.29 18895.37 29585.81 21897.89 24294.80 17997.07 17296.23 235
mvs-test195.53 16095.97 13394.20 26497.77 19685.44 33799.95 4397.06 28794.92 9196.58 16298.72 18085.81 21898.98 16994.80 17998.11 15098.18 215
MVSTER95.53 16095.22 15796.45 19298.56 15297.72 8599.91 7597.67 22492.38 19791.39 22897.14 23397.24 1897.30 26494.80 17987.85 26094.34 262
thisisatest051597.41 9897.02 10398.59 10797.71 20597.52 9599.97 1898.54 8991.83 21397.45 14299.04 14897.50 999.10 16694.75 18296.37 18599.16 190
mvs_tets91.81 24591.08 24694.00 27491.63 34490.58 28598.67 28597.43 25292.43 19687.37 29997.05 23971.76 32397.32 26394.75 18288.68 24594.11 284
Anonymous2024052992.10 24190.65 25296.47 19098.82 14290.61 28498.72 28098.67 6175.54 35993.90 20598.58 18966.23 34499.90 8094.70 18490.67 22998.90 203
MVSFormer96.94 11296.60 11397.95 14097.28 22597.70 8899.55 18297.27 26791.17 23099.43 6099.54 11490.92 16496.89 29594.67 18599.62 10499.25 185
test_djsdf92.83 22292.29 22394.47 25591.90 34092.46 24499.55 18297.27 26791.17 23089.96 24496.07 26981.10 25796.89 29594.67 18588.91 23994.05 289
UGNet95.33 16494.57 17197.62 15598.55 15494.85 18998.67 28599.32 2595.75 6996.80 15796.27 26372.18 32299.96 5894.58 18799.05 12998.04 218
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
jajsoiax91.92 24391.18 24594.15 26591.35 34690.95 27799.00 25097.42 25492.61 18687.38 29897.08 23672.46 32197.36 25794.53 18888.77 24394.13 283
MVS_Test96.46 13295.74 14598.61 10498.18 17497.23 11099.31 21597.15 27791.07 23498.84 9597.05 23988.17 19898.97 17094.39 18997.50 16299.61 136
PS-MVSNAJss93.64 20693.31 20394.61 24592.11 33792.19 25099.12 23297.38 25892.51 19488.45 28096.99 24291.20 15797.29 26794.36 19087.71 26394.36 257
无先验99.49 19298.71 5593.46 155100.00 194.36 19099.99 24
112198.03 7197.57 8399.40 4499.74 8298.21 6998.31 30198.62 6992.78 17699.53 5199.83 5195.08 54100.00 194.36 19099.92 7199.99 24
MDTV_nov1_ep13_2view96.26 14496.11 34391.89 21198.06 12894.40 7494.30 19399.67 122
thres20096.96 11196.21 12399.22 5398.97 12898.84 3499.85 10899.71 693.17 16496.26 17298.88 17089.87 17799.51 14894.26 19494.91 20899.31 180
BH-untuned95.18 16594.83 16796.22 20298.36 16491.22 27499.80 12597.32 26490.91 23791.08 23298.67 18283.51 23798.54 19294.23 19599.61 10798.92 200
FIs94.10 19393.43 19796.11 20494.70 29196.82 12699.58 17598.93 4192.54 19189.34 26297.31 22987.62 20197.10 27994.22 19686.58 27194.40 252
tpm295.47 16295.18 15996.35 19996.91 23791.70 26696.96 33397.93 20588.04 28498.44 11595.40 29193.32 11197.97 23694.00 19795.61 20099.38 171
bld_raw_dy_0_6492.74 22592.03 22994.87 23593.09 32393.46 22099.12 23295.41 35092.84 17290.44 23997.54 22278.08 28597.04 28593.94 19887.77 26294.11 284
OpenMVScopyleft90.15 1594.77 17593.59 19298.33 12796.07 25897.48 10199.56 18098.57 7790.46 24486.51 30898.95 16478.57 28199.94 7393.86 19999.74 9697.57 227
thres100view90096.74 12295.92 14099.18 5798.90 13798.77 4099.74 14399.71 692.59 18895.84 17898.86 17489.25 18599.50 15093.84 20094.57 20999.27 183
tfpn200view996.79 11895.99 12899.19 5698.94 13098.82 3599.78 12999.71 692.86 16996.02 17598.87 17289.33 18399.50 15093.84 20094.57 20999.27 183
thres40096.78 11995.99 12899.16 6298.94 13098.82 3599.78 12999.71 692.86 16996.02 17598.87 17289.33 18399.50 15093.84 20094.57 20999.16 190
DPM-MVS98.83 2298.46 3299.97 199.33 11399.92 199.96 2598.44 11297.96 799.55 4999.94 497.18 21100.00 193.81 20399.94 6199.98 55
CDS-MVSNet96.34 13696.07 12597.13 17397.37 21794.96 18799.53 18597.91 20891.55 22195.37 18798.32 20195.05 5797.13 27693.80 20495.75 19899.30 181
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
baseline195.78 15294.86 16698.54 11398.47 15998.07 7399.06 24297.99 19892.68 18294.13 20298.62 18693.28 11498.69 18593.79 20585.76 27598.84 205
OPM-MVS93.21 21292.80 21194.44 25793.12 32190.85 27999.77 13297.61 23296.19 5591.56 22798.65 18375.16 31098.47 19493.78 20689.39 23693.99 295
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
TAMVS95.85 15095.58 14896.65 18897.07 22993.50 21999.17 23097.82 21791.39 22995.02 19198.01 20792.20 14297.30 26493.75 20795.83 19599.14 193
thisisatest053097.10 10796.72 11098.22 13197.60 20896.70 12899.92 7198.54 8991.11 23397.07 15098.97 15897.47 1299.03 16793.73 20896.09 18898.92 200
IS-MVSNet96.29 14095.90 14197.45 16098.13 17894.80 19299.08 23797.61 23292.02 20995.54 18598.96 16090.64 16998.08 23093.73 20897.41 16699.47 161
test_low_dy_conf_00193.16 21392.88 20994.01 27293.16 31890.65 28399.58 17597.66 22692.21 20291.34 23097.80 21682.45 24497.05 28293.64 21088.05 25794.32 263
ACMM91.95 1092.88 22192.52 22093.98 27695.75 27089.08 30999.77 13297.52 24493.00 16789.95 24597.99 21076.17 30098.46 19793.63 21188.87 24194.39 254
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Vis-MVSNet (Re-imp)96.32 13795.98 13097.35 16997.93 18694.82 19199.47 19598.15 18791.83 21395.09 19099.11 14491.37 15597.47 25593.47 21297.43 16399.74 113
thres600view796.69 12595.87 14399.14 6698.90 13798.78 3999.74 14399.71 692.59 18895.84 17898.86 17489.25 18599.50 15093.44 21394.50 21299.16 190
Vis-MVSNetpermissive95.72 15395.15 16097.45 16097.62 20794.28 20199.28 22198.24 17394.27 12296.84 15598.94 16679.39 27498.76 17993.25 21498.49 13899.30 181
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
FC-MVSNet-test93.81 19993.15 20695.80 21194.30 29796.20 14999.42 20098.89 4392.33 19989.03 27297.27 23187.39 20496.83 29993.20 21586.48 27294.36 257
UniMVSNet_NR-MVSNet92.95 22092.11 22695.49 21494.61 29395.28 17899.83 11899.08 3191.49 22289.21 26796.86 24687.14 20696.73 30393.20 21577.52 33694.46 245
DU-MVS92.46 23391.45 24295.49 21494.05 30095.28 17899.81 12198.74 5492.25 20189.21 26796.64 25381.66 25196.73 30393.20 21577.52 33694.46 245
WR-MVS92.31 23691.25 24495.48 21794.45 29495.29 17799.60 17398.68 5890.10 25088.07 28896.89 24480.68 26396.80 30193.14 21879.67 32394.36 257
UniMVSNet (Re)93.07 21892.13 22595.88 20894.84 28896.24 14899.88 9098.98 3592.49 19589.25 26495.40 29187.09 20797.14 27593.13 21978.16 33194.26 266
QAPM95.40 16394.17 17899.10 7296.92 23697.71 8699.40 20198.68 5889.31 25988.94 27398.89 16982.48 24399.96 5893.12 22099.83 8599.62 133
tttt051796.85 11596.49 11797.92 14297.48 21495.89 15999.85 10898.54 8990.72 24296.63 16098.93 16897.47 1299.02 16893.03 22195.76 19798.85 204
TR-MVS94.54 18293.56 19497.49 15997.96 18494.34 20098.71 28197.51 24690.30 24994.51 19698.69 18175.56 30398.77 17892.82 22295.99 19099.35 176
CANet_DTU96.76 12096.15 12498.60 10598.78 14597.53 9499.84 11297.63 22797.25 2499.20 7899.64 10681.36 25599.98 4692.77 22398.89 13098.28 214
AUN-MVS93.28 21192.60 21595.34 22098.29 16690.09 29599.31 21598.56 7991.80 21696.35 17198.00 20889.38 18298.28 21992.46 22469.22 35797.64 225
anonymousdsp91.79 25090.92 24894.41 26090.76 35192.93 23298.93 25997.17 27489.08 26187.46 29795.30 29878.43 28496.92 29492.38 22588.73 24493.39 323
XVG-ACMP-BASELINE91.22 25890.75 24992.63 30593.73 30685.61 33498.52 29397.44 25192.77 17789.90 24796.85 24766.64 34398.39 20592.29 22688.61 24693.89 303
miper_enhance_ethall94.36 19093.98 18295.49 21498.68 14995.24 18099.73 14897.29 26693.28 16189.86 24895.97 27094.37 7997.05 28292.20 22784.45 28794.19 272
RPSCF91.80 24892.79 21288.83 33598.15 17669.87 36998.11 31196.60 32583.93 33194.33 19999.27 13479.60 27399.46 15591.99 22893.16 22597.18 229
cl2293.77 20193.25 20595.33 22199.49 10694.43 19799.61 17298.09 19190.38 24589.16 27095.61 27990.56 17097.34 25991.93 22984.45 28794.21 271
1112_ss96.01 14795.20 15898.42 12397.80 19496.41 13899.65 16496.66 32392.71 17992.88 21799.40 12492.16 14399.30 15791.92 23093.66 21999.55 148
Test_1112_low_res95.72 15394.83 16798.42 12397.79 19596.41 13899.65 16496.65 32492.70 18092.86 21896.13 26792.15 14499.30 15791.88 23193.64 22099.55 148
tmp_tt65.23 33962.94 34272.13 35444.90 38350.03 37981.05 37089.42 37838.45 37348.51 37599.90 1954.09 36678.70 37591.84 23218.26 37787.64 366
XXY-MVS91.82 24490.46 25495.88 20893.91 30395.40 17598.87 26797.69 22288.63 27687.87 29097.08 23674.38 31597.89 24291.66 23384.07 29194.35 260
D2MVS92.76 22492.59 21893.27 29495.13 28389.54 30599.69 15499.38 2292.26 20087.59 29394.61 32285.05 22797.79 24491.59 23488.01 25892.47 339
UniMVSNet_ETH3D90.06 28588.58 29194.49 25494.67 29288.09 32197.81 31997.57 23783.91 33288.44 28197.41 22657.44 36397.62 25091.41 23588.59 24897.77 223
NR-MVSNet91.56 25390.22 26195.60 21294.05 30095.76 16398.25 30498.70 5691.16 23280.78 34396.64 25383.23 24196.57 30991.41 23577.73 33594.46 245
新几何199.42 4199.75 8198.27 6898.63 6892.69 18199.55 4999.82 5594.40 74100.00 191.21 23799.94 6199.99 24
UA-Net96.54 12995.96 13598.27 12998.23 17195.71 16698.00 31598.45 10993.72 14998.41 11699.27 13488.71 19499.66 14291.19 23897.69 15899.44 166
EPMVS96.53 13096.01 12798.09 13698.43 16096.12 15496.36 33899.43 2093.53 15397.64 13895.04 30794.41 7398.38 20991.13 23998.11 15099.75 112
EI-MVSNet93.73 20393.40 20194.74 24096.80 24592.69 23899.06 24297.67 22488.96 26791.39 22899.02 14988.75 19397.30 26491.07 24087.85 26094.22 269
test_part192.15 24090.72 25096.44 19498.87 14097.46 10398.99 25198.26 17185.89 31086.34 31396.34 26181.71 24997.48 25491.06 24178.99 32594.37 255
test_post195.78 34859.23 37993.20 11897.74 24691.06 241
SCA94.69 17793.81 18797.33 17097.10 22894.44 19698.86 26898.32 16093.30 16096.17 17495.59 28176.48 29697.95 23991.06 24197.43 16399.59 139
Baseline_NR-MVSNet90.33 27789.51 27592.81 30392.84 32889.95 29999.77 13293.94 36784.69 32889.04 27195.66 27881.66 25196.52 31090.99 24476.98 34291.97 345
IterMVS-LS92.69 22892.11 22694.43 25996.80 24592.74 23599.45 19896.89 30888.98 26589.65 25595.38 29488.77 19296.34 31790.98 24582.04 30194.22 269
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
LS3D95.84 15195.11 16198.02 13999.85 6095.10 18598.74 27898.50 10387.22 29493.66 20799.86 3187.45 20399.95 6590.94 24699.81 9399.02 198
CVMVSNet94.68 17994.94 16593.89 27996.80 24586.92 32899.06 24298.98 3594.45 10894.23 20199.02 14985.60 22095.31 33990.91 24795.39 20499.43 167
BH-RMVSNet95.18 16594.31 17697.80 14498.17 17595.23 18199.76 13797.53 24292.52 19394.27 20099.25 13876.84 29298.80 17590.89 24899.54 11199.35 176
Anonymous2023121189.86 28788.44 29394.13 26798.93 13290.68 28198.54 29198.26 17176.28 35586.73 30495.54 28370.60 32997.56 25190.82 24980.27 32094.15 279
miper_ehance_all_eth93.16 21392.60 21594.82 23997.57 20993.56 21799.50 19097.07 28688.75 27288.85 27595.52 28590.97 16396.74 30290.77 25084.45 28794.17 273
tpm93.70 20593.41 20094.58 24895.36 28287.41 32597.01 33196.90 30790.85 23996.72 15994.14 33090.40 17196.84 29890.75 25188.54 24999.51 157
TESTMET0.1,196.74 12296.26 12298.16 13297.36 21896.48 13599.96 2598.29 16691.93 21095.77 18198.07 20695.54 4498.29 21790.55 25298.89 13099.70 117
testdata299.99 4090.54 253
c3_l92.53 23191.87 23394.52 25197.40 21692.99 23199.40 20196.93 30587.86 28588.69 27895.44 28989.95 17696.44 31390.45 25480.69 31694.14 282
test-LLR96.47 13196.04 12697.78 14697.02 23395.44 17299.96 2598.21 17794.07 12995.55 18396.38 25893.90 9898.27 22190.42 25598.83 13299.64 128
test-mter96.39 13595.93 13897.78 14697.02 23395.44 17299.96 2598.21 17791.81 21595.55 18396.38 25895.17 5198.27 22190.42 25598.83 13299.64 128
PCF-MVS94.20 595.18 16594.10 17998.43 12298.55 15495.99 15697.91 31797.31 26590.35 24789.48 25999.22 14085.19 22599.89 8490.40 25798.47 13999.41 169
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CP-MVSNet91.23 25790.22 26194.26 26293.96 30292.39 24699.09 23598.57 7788.95 26886.42 31196.57 25579.19 27696.37 31590.29 25878.95 32694.02 290
TranMVSNet+NR-MVSNet91.68 25290.61 25394.87 23593.69 30793.98 20899.69 15498.65 6291.03 23588.44 28196.83 25080.05 27196.18 32390.26 25976.89 34494.45 250
PatchMatch-RL96.04 14695.40 15197.95 14099.59 9695.22 18299.52 18699.07 3293.96 13796.49 16598.35 20082.28 24599.82 11090.15 26099.22 12598.81 207
MDTV_nov1_ep1395.69 14697.90 18794.15 20295.98 34598.44 11293.12 16597.98 13095.74 27495.10 5398.58 18990.02 26196.92 176
eth_miper_zixun_eth92.41 23491.93 23193.84 28097.28 22590.68 28198.83 27196.97 29988.57 27789.19 26995.73 27689.24 18796.69 30589.97 26281.55 30494.15 279
Fast-Effi-MVS+95.02 16994.19 17797.52 15797.88 18894.55 19599.97 1897.08 28588.85 27194.47 19797.96 21384.59 22998.41 20189.84 26397.10 17199.59 139
Fast-Effi-MVS+-dtu93.72 20493.86 18693.29 29397.06 23086.16 33199.80 12596.83 31392.66 18392.58 22197.83 21581.39 25497.67 24889.75 26496.87 17796.05 237
ACMH89.72 1790.64 26989.63 27093.66 28895.64 27788.64 31498.55 28997.45 25089.03 26381.62 33897.61 22169.75 33198.41 20189.37 26587.62 26593.92 301
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
pmmvs492.10 24191.07 24795.18 22692.82 33094.96 18799.48 19496.83 31387.45 29088.66 27996.56 25683.78 23696.83 29989.29 26684.77 28593.75 312
PatchmatchNetpermissive95.94 14995.45 15097.39 16597.83 19294.41 19996.05 34498.40 14092.86 16997.09 14995.28 30294.21 9098.07 23289.26 26798.11 15099.70 117
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
ACMH+89.98 1690.35 27689.54 27392.78 30495.99 26186.12 33298.81 27397.18 27389.38 25883.14 33197.76 21868.42 33798.43 19989.11 26886.05 27493.78 311
DP-MVS94.54 18293.42 19897.91 14399.46 10994.04 20598.93 25997.48 24981.15 34490.04 24399.55 11287.02 20899.95 6588.97 26998.11 15099.73 114
PS-CasMVS90.63 27089.51 27593.99 27593.83 30491.70 26698.98 25398.52 9288.48 27886.15 31696.53 25775.46 30496.31 31888.83 27078.86 32893.95 298
cl____92.31 23691.58 23794.52 25197.33 22192.77 23399.57 17896.78 31886.97 29987.56 29495.51 28689.43 18196.62 30788.60 27182.44 29894.16 278
DIV-MVS_self_test92.32 23591.60 23694.47 25597.31 22292.74 23599.58 17596.75 31986.99 29887.64 29295.54 28389.55 18096.50 31188.58 27282.44 29894.17 273
pmmvs590.17 28389.09 28293.40 29192.10 33889.77 30299.74 14395.58 34785.88 31287.24 30195.74 27473.41 31996.48 31288.54 27383.56 29493.95 298
LF4IMVS89.25 29788.85 28690.45 32592.81 33181.19 35898.12 31094.79 36091.44 22586.29 31497.11 23465.30 34998.11 22988.53 27485.25 28092.07 342
JIA-IIPM91.76 25190.70 25194.94 23396.11 25787.51 32493.16 35798.13 19075.79 35897.58 13977.68 36992.84 12697.97 23688.47 27596.54 18099.33 178
miper_lstm_enhance91.81 24591.39 24393.06 30097.34 21989.18 30899.38 20696.79 31786.70 30287.47 29695.22 30390.00 17595.86 33388.26 27681.37 30694.15 279
WR-MVS_H91.30 25490.35 25794.15 26594.17 29992.62 24299.17 23098.94 3788.87 27086.48 31094.46 32784.36 23196.61 30888.19 27778.51 32993.21 328
tpmvs94.28 19293.57 19396.40 19698.55 15491.50 27195.70 34998.55 8587.47 28992.15 22394.26 32991.42 15398.95 17188.15 27895.85 19498.76 209
OurMVSNet-221017-089.81 28889.48 27790.83 32191.64 34381.21 35798.17 30995.38 35291.48 22385.65 32097.31 22972.66 32097.29 26788.15 27884.83 28493.97 297
GeoE94.36 19093.48 19696.99 17697.29 22493.54 21899.96 2596.72 32188.35 28193.43 20898.94 16682.05 24698.05 23388.12 28096.48 18399.37 173
TDRefinement84.76 31882.56 32591.38 31774.58 37484.80 34197.36 32494.56 36384.73 32780.21 34596.12 26863.56 35398.39 20587.92 28163.97 36390.95 353
CMPMVSbinary61.59 2184.75 31985.14 31383.57 34790.32 35462.54 37396.98 33297.59 23674.33 36269.95 36596.66 25164.17 35198.32 21587.88 28288.41 25189.84 360
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
Patchmatch-RL test86.90 30885.98 31089.67 33084.45 36875.59 36689.71 36692.43 37086.89 30077.83 35290.94 35394.22 8793.63 35687.75 28369.61 35499.79 106
GA-MVS93.83 19792.84 21096.80 18195.73 27193.57 21699.88 9097.24 26992.57 19092.92 21596.66 25178.73 28097.67 24887.75 28394.06 21799.17 189
ADS-MVSNet293.80 20093.88 18593.55 29097.87 18985.94 33394.24 35096.84 31290.07 25196.43 16794.48 32590.29 17395.37 33787.44 28597.23 16899.36 174
ADS-MVSNet94.79 17394.02 18197.11 17597.87 18993.79 21194.24 35098.16 18590.07 25196.43 16794.48 32590.29 17398.19 22687.44 28597.23 16899.36 174
v14890.70 26789.63 27093.92 27792.97 32690.97 27699.75 14096.89 30887.51 28888.27 28695.01 30881.67 25097.04 28587.40 28777.17 34193.75 312
V4291.28 25690.12 26594.74 24093.42 31393.46 22099.68 15697.02 29287.36 29189.85 25095.05 30681.31 25697.34 25987.34 28880.07 32193.40 322
v2v48291.30 25490.07 26695.01 23093.13 31993.79 21199.77 13297.02 29288.05 28389.25 26495.37 29580.73 26297.15 27487.28 28980.04 32294.09 286
IterMVS90.91 26290.17 26393.12 29796.78 24890.42 29098.89 26297.05 29089.03 26386.49 30995.42 29076.59 29595.02 34187.22 29084.09 29093.93 300
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
PEN-MVS90.19 28289.06 28393.57 28993.06 32490.90 27899.06 24298.47 10588.11 28285.91 31896.30 26276.67 29395.94 33287.07 29176.91 34393.89 303
IterMVS-SCA-FT90.85 26590.16 26492.93 30196.72 25089.96 29898.89 26296.99 29588.95 26886.63 30695.67 27776.48 29695.00 34287.04 29284.04 29393.84 307
tpm cat193.51 20792.52 22096.47 19097.77 19691.47 27296.13 34298.06 19480.98 34592.91 21693.78 33389.66 17898.87 17287.03 29396.39 18499.09 196
GBi-Net90.88 26389.82 26894.08 26897.53 21091.97 25398.43 29696.95 30087.05 29589.68 25294.72 31671.34 32596.11 32487.01 29485.65 27694.17 273
test190.88 26389.82 26894.08 26897.53 21091.97 25398.43 29696.95 30087.05 29589.68 25294.72 31671.34 32596.11 32487.01 29485.65 27694.17 273
FMVSNet392.69 22891.58 23795.99 20698.29 16697.42 10699.26 22397.62 22989.80 25689.68 25295.32 29781.62 25396.27 32087.01 29485.65 27694.29 265
dp95.05 16894.43 17396.91 17897.99 18392.73 23796.29 34097.98 20089.70 25795.93 17794.67 32093.83 10198.45 19886.91 29796.53 18199.54 151
MSDG94.37 18893.36 20297.40 16498.88 13993.95 20999.37 20897.38 25885.75 31590.80 23599.17 14284.11 23599.88 9086.35 29898.43 14098.36 213
EU-MVSNet90.14 28490.34 25889.54 33192.55 33381.06 35998.69 28398.04 19691.41 22886.59 30796.84 24980.83 26193.31 35986.20 29981.91 30294.26 266
pm-mvs189.36 29487.81 30194.01 27293.40 31491.93 25698.62 28896.48 32986.25 30783.86 32896.14 26673.68 31897.04 28586.16 30075.73 34893.04 331
COLMAP_ROBcopyleft90.47 1492.18 23991.49 24194.25 26399.00 12688.04 32298.42 29996.70 32282.30 34188.43 28399.01 15176.97 29099.85 9986.11 30196.50 18294.86 238
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ITE_SJBPF92.38 30695.69 27685.14 33895.71 34392.81 17389.33 26398.11 20470.23 33098.42 20085.91 30288.16 25593.59 319
K. test v388.05 30387.24 30590.47 32491.82 34282.23 35198.96 25697.42 25489.05 26276.93 35495.60 28068.49 33695.42 33685.87 30381.01 31393.75 312
AllTest92.48 23291.64 23595.00 23199.01 12488.43 31698.94 25896.82 31586.50 30388.71 27698.47 19774.73 31299.88 9085.39 30496.18 18696.71 231
TestCases95.00 23199.01 12488.43 31696.82 31586.50 30388.71 27698.47 19774.73 31299.88 9085.39 30496.18 18696.71 231
FMVSNet291.02 26089.56 27295.41 21997.53 21095.74 16498.98 25397.41 25687.05 29588.43 28395.00 31071.34 32596.24 32285.12 30685.21 28194.25 268
v114491.09 25989.83 26794.87 23593.25 31793.69 21599.62 17196.98 29786.83 30189.64 25694.99 31180.94 25997.05 28285.08 30781.16 30893.87 305
v890.54 27289.17 28094.66 24393.43 31293.40 22499.20 22796.94 30485.76 31387.56 29494.51 32381.96 24897.19 27284.94 30878.25 33093.38 324
ambc83.23 34877.17 37362.61 37287.38 36894.55 36476.72 35586.65 36330.16 37496.36 31684.85 30969.86 35390.73 354
MVS_030489.28 29688.31 29592.21 30997.05 23186.53 33097.76 32099.57 1385.58 31893.86 20692.71 34251.04 37096.30 31984.49 31092.72 22793.79 310
LTVRE_ROB88.28 1890.29 27989.05 28494.02 27195.08 28590.15 29497.19 32797.43 25284.91 32683.99 32797.06 23874.00 31798.28 21984.08 31187.71 26393.62 318
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
SixPastTwentyTwo88.73 29988.01 30090.88 31991.85 34182.24 35098.22 30795.18 35888.97 26682.26 33496.89 24471.75 32496.67 30684.00 31282.98 29593.72 316
v14419290.79 26689.52 27494.59 24793.11 32292.77 23399.56 18096.99 29586.38 30589.82 25194.95 31380.50 26797.10 27983.98 31380.41 31793.90 302
USDC90.00 28688.96 28593.10 29994.81 28988.16 32098.71 28195.54 34893.66 15083.75 32997.20 23265.58 34698.31 21683.96 31487.49 26792.85 334
MVP-Stereo90.93 26190.45 25692.37 30791.25 34888.76 31098.05 31496.17 33587.27 29384.04 32695.30 29878.46 28397.27 26983.78 31599.70 10091.09 350
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
MS-PatchMatch90.65 26890.30 25991.71 31594.22 29885.50 33698.24 30597.70 22188.67 27486.42 31196.37 26067.82 33998.03 23483.62 31699.62 10491.60 347
DTE-MVSNet89.40 29388.24 29792.88 30292.66 33289.95 29999.10 23498.22 17687.29 29285.12 32396.22 26476.27 29995.30 34083.56 31775.74 34793.41 321
pmmvs685.69 31183.84 31791.26 31890.00 35784.41 34297.82 31896.15 33675.86 35781.29 34095.39 29361.21 35896.87 29783.52 31873.29 35192.50 338
lessismore_v090.53 32290.58 35280.90 36095.80 34177.01 35395.84 27166.15 34596.95 29183.03 31975.05 34993.74 315
v1090.25 28088.82 28794.57 24993.53 31093.43 22299.08 23796.87 31085.00 32387.34 30094.51 32380.93 26097.02 29082.85 32079.23 32493.26 326
DeepMVS_CXcopyleft82.92 34995.98 26358.66 37596.01 33892.72 17878.34 35195.51 28658.29 36298.08 23082.57 32185.29 27992.03 344
PM-MVS80.47 33078.88 33485.26 34583.79 37072.22 36895.89 34791.08 37385.71 31676.56 35688.30 35836.64 37393.90 35382.39 32269.57 35589.66 361
v119290.62 27189.25 27994.72 24293.13 31993.07 22899.50 19097.02 29286.33 30689.56 25895.01 30879.22 27597.09 28182.34 32381.16 30894.01 292
v192192090.46 27389.12 28194.50 25392.96 32792.46 24499.49 19296.98 29786.10 30889.61 25795.30 29878.55 28297.03 28882.17 32480.89 31594.01 292
MIMVSNet90.30 27888.67 29095.17 22796.45 25391.64 26892.39 35997.15 27785.99 30990.50 23793.19 34066.95 34294.86 34582.01 32593.43 22199.01 199
UnsupCasMVSNet_eth85.52 31383.99 31490.10 32789.36 35983.51 34496.65 33597.99 19889.14 26075.89 35893.83 33263.25 35493.92 35281.92 32667.90 36192.88 333
FMVSNet188.50 30086.64 30694.08 26895.62 27991.97 25398.43 29696.95 30083.00 33686.08 31794.72 31659.09 36196.11 32481.82 32784.07 29194.17 273
test0.0.03 193.86 19693.61 18994.64 24495.02 28792.18 25199.93 6798.58 7594.07 12987.96 28998.50 19293.90 9894.96 34381.33 32893.17 22496.78 230
v7n89.65 29188.29 29693.72 28392.22 33690.56 28699.07 24197.10 28285.42 32186.73 30494.72 31680.06 27097.13 27681.14 32978.12 33293.49 320
pmmvs-eth3d84.03 32481.97 32790.20 32684.15 36987.09 32798.10 31294.73 36283.05 33574.10 36187.77 36065.56 34794.01 35181.08 33069.24 35689.49 362
v124090.20 28188.79 28894.44 25793.05 32592.27 24899.38 20696.92 30685.89 31089.36 26194.87 31577.89 28797.03 28880.66 33181.08 31194.01 292
our_test_390.39 27489.48 27793.12 29792.40 33489.57 30499.33 21296.35 33287.84 28685.30 32194.99 31184.14 23496.09 32780.38 33284.56 28693.71 317
TinyColmap87.87 30686.51 30791.94 31295.05 28685.57 33597.65 32194.08 36584.40 32981.82 33796.85 24762.14 35698.33 21480.25 33386.37 27391.91 346
Patchmtry89.70 29088.49 29293.33 29296.24 25689.94 30191.37 36496.23 33378.22 35287.69 29193.31 33891.04 16196.03 32980.18 33482.10 30094.02 290
KD-MVS_2432*160088.00 30486.10 30893.70 28696.91 23794.04 20597.17 32897.12 28084.93 32481.96 33592.41 34592.48 13694.51 34879.23 33552.68 37092.56 336
miper_refine_blended88.00 30486.10 30893.70 28696.91 23794.04 20597.17 32897.12 28084.93 32481.96 33592.41 34592.48 13694.51 34879.23 33552.68 37092.56 336
CR-MVSNet93.45 21092.62 21495.94 20796.29 25492.66 23992.01 36196.23 33392.62 18596.94 15193.31 33891.04 16196.03 32979.23 33595.96 19199.13 194
EG-PatchMatch MVS85.35 31683.81 31889.99 32990.39 35381.89 35398.21 30896.09 33781.78 34374.73 36093.72 33451.56 36997.12 27879.16 33888.61 24690.96 352
test_method80.79 32979.70 33284.08 34692.83 32967.06 37199.51 18895.42 34954.34 36981.07 34293.53 33544.48 37292.22 36278.90 33977.23 34092.94 332
DSMNet-mixed88.28 30288.24 29788.42 33989.64 35875.38 36798.06 31389.86 37585.59 31788.20 28792.14 34976.15 30191.95 36378.46 34096.05 18997.92 219
UnsupCasMVSNet_bld79.97 33377.03 33688.78 33685.62 36781.98 35293.66 35597.35 26075.51 36070.79 36483.05 36648.70 37194.91 34478.31 34160.29 36889.46 363
EPNet_dtu95.71 15595.39 15296.66 18798.92 13493.41 22399.57 17898.90 4296.19 5597.52 14098.56 19192.65 13197.36 25777.89 34298.33 14299.20 188
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
testgi89.01 29888.04 29991.90 31393.49 31184.89 34099.73 14895.66 34593.89 14385.14 32298.17 20359.68 36094.66 34777.73 34388.88 24096.16 236
Patchmatch-test92.65 23091.50 24096.10 20596.85 24290.49 28791.50 36397.19 27182.76 33990.23 24095.59 28195.02 5898.00 23577.41 34496.98 17599.82 103
YYNet185.50 31583.33 32092.00 31190.89 35088.38 31999.22 22696.55 32679.60 35057.26 37092.72 34179.09 27893.78 35577.25 34577.37 33993.84 307
MDA-MVSNet_test_wron85.51 31483.32 32192.10 31090.96 34988.58 31599.20 22796.52 32779.70 34957.12 37192.69 34379.11 27793.86 35477.10 34677.46 33893.86 306
tfpnnormal89.29 29587.61 30294.34 26194.35 29694.13 20398.95 25798.94 3783.94 33084.47 32595.51 28674.84 31197.39 25677.05 34780.41 31791.48 349
TransMVSNet (Re)87.25 30785.28 31293.16 29693.56 30991.03 27598.54 29194.05 36683.69 33481.09 34196.16 26575.32 30596.40 31476.69 34868.41 35992.06 343
FMVSNet588.32 30187.47 30390.88 31996.90 24088.39 31897.28 32595.68 34482.60 34084.67 32492.40 34779.83 27291.16 36576.39 34981.51 30593.09 329
ppachtmachnet_test89.58 29288.35 29493.25 29592.40 33490.44 28999.33 21296.73 32085.49 31985.90 31995.77 27381.09 25896.00 33176.00 35082.49 29793.30 325
MVS-HIRNet86.22 31083.19 32295.31 22296.71 25190.29 29192.12 36097.33 26362.85 36786.82 30370.37 37169.37 33297.49 25375.12 35197.99 15698.15 216
MDA-MVSNet-bldmvs84.09 32381.52 32991.81 31491.32 34788.00 32398.67 28595.92 34080.22 34755.60 37293.32 33768.29 33893.60 35773.76 35276.61 34593.82 309
KD-MVS_self_test83.59 32682.06 32688.20 34086.93 36480.70 36197.21 32696.38 33182.87 33782.49 33388.97 35767.63 34092.32 36173.75 35362.30 36691.58 348
Anonymous2024052185.15 31783.81 31889.16 33388.32 36182.69 34698.80 27595.74 34279.72 34881.53 33990.99 35265.38 34894.16 35072.69 35481.11 31090.63 355
new_pmnet84.49 32282.92 32489.21 33290.03 35682.60 34796.89 33495.62 34680.59 34675.77 35989.17 35665.04 35094.79 34672.12 35581.02 31290.23 357
new-patchmatchnet81.19 32879.34 33386.76 34382.86 37180.36 36497.92 31695.27 35482.09 34272.02 36286.87 36262.81 35590.74 36771.10 35663.08 36489.19 364
pmmvs380.27 33177.77 33587.76 34180.32 37282.43 34998.23 30691.97 37172.74 36478.75 34987.97 35957.30 36490.99 36670.31 35762.37 36589.87 359
TAPA-MVS92.12 894.42 18693.60 19196.90 17999.33 11391.78 26199.78 12998.00 19789.89 25594.52 19599.47 11891.97 14899.18 16269.90 35899.52 11299.73 114
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CL-MVSNet_self_test84.50 32183.15 32388.53 33886.00 36681.79 35498.82 27297.35 26085.12 32283.62 33090.91 35476.66 29491.40 36469.53 35960.36 36792.40 340
LCM-MVSNet67.77 33664.73 33976.87 35162.95 38056.25 37789.37 36793.74 36944.53 37261.99 36780.74 36720.42 38086.53 37169.37 36059.50 36987.84 365
OpenMVS_ROBcopyleft79.82 2083.77 32581.68 32890.03 32888.30 36282.82 34598.46 29495.22 35573.92 36376.00 35791.29 35155.00 36596.94 29268.40 36188.51 25090.34 356
N_pmnet80.06 33280.78 33077.89 35091.94 33945.28 38198.80 27556.82 38478.10 35380.08 34693.33 33677.03 28995.76 33468.14 36282.81 29692.64 335
Anonymous2023120686.32 30985.42 31189.02 33489.11 36080.53 36399.05 24695.28 35385.43 32082.82 33293.92 33174.40 31493.44 35866.99 36381.83 30393.08 330
test20.0384.72 32083.99 31486.91 34288.19 36380.62 36298.88 26495.94 33988.36 28078.87 34894.62 32168.75 33489.11 36966.52 36475.82 34691.00 351
PatchT90.38 27588.75 28995.25 22495.99 26190.16 29391.22 36597.54 24076.80 35497.26 14586.01 36491.88 14996.07 32866.16 36595.91 19399.51 157
test_040285.58 31283.94 31690.50 32393.81 30585.04 33998.55 28995.20 35676.01 35679.72 34795.13 30464.15 35296.26 32166.04 36686.88 27090.21 358
MIMVSNet182.58 32780.51 33188.78 33686.68 36584.20 34396.65 33595.41 35078.75 35178.59 35092.44 34451.88 36889.76 36865.26 36778.95 32692.38 341
RPMNet89.76 28987.28 30497.19 17296.29 25492.66 23992.01 36198.31 16270.19 36696.94 15185.87 36587.25 20599.78 11662.69 36895.96 19199.13 194
FPMVS68.72 33568.72 33768.71 35565.95 37844.27 38395.97 34694.74 36151.13 37053.26 37390.50 35525.11 37883.00 37360.80 36980.97 31478.87 369
PMMVS267.15 33764.15 34076.14 35270.56 37762.07 37493.89 35387.52 37958.09 36860.02 36878.32 36822.38 37984.54 37259.56 37047.03 37281.80 368
EGC-MVSNET69.38 33463.76 34186.26 34490.32 35481.66 35696.24 34193.85 3680.99 3813.22 38292.33 34852.44 36792.92 36059.53 37184.90 28384.21 367
testmvs40.60 34544.45 34829.05 36219.49 38614.11 38799.68 15618.47 38520.74 37864.59 36698.48 19610.95 38317.09 38256.66 37211.01 37855.94 375
Gipumacopyleft66.95 33865.00 33872.79 35391.52 34567.96 37066.16 37395.15 35947.89 37158.54 36967.99 37329.74 37587.54 37050.20 37377.83 33462.87 373
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
test12337.68 34639.14 34933.31 36119.94 38524.83 38698.36 3009.75 38615.53 37951.31 37487.14 36119.62 38117.74 38147.10 3743.47 38057.36 374
ANet_high56.10 34052.24 34367.66 35649.27 38256.82 37683.94 36982.02 38070.47 36533.28 37964.54 37417.23 38269.16 37745.59 37523.85 37677.02 370
PMVScopyleft49.05 2353.75 34151.34 34560.97 35840.80 38434.68 38474.82 37289.62 37737.55 37428.67 38072.12 3707.09 38481.63 37443.17 37668.21 36066.59 372
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVEpermissive53.74 2251.54 34347.86 34762.60 35759.56 38150.93 37879.41 37177.69 38135.69 37636.27 37861.76 3775.79 38669.63 37637.97 37736.61 37367.24 371
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN52.30 34252.18 34452.67 35971.51 37545.40 38093.62 35676.60 38236.01 37543.50 37664.13 37527.11 37767.31 37831.06 37826.06 37445.30 377
EMVS51.44 34451.22 34652.11 36070.71 37644.97 38294.04 35275.66 38335.34 37742.40 37761.56 37828.93 37665.87 37927.64 37924.73 37545.49 376
wuyk23d20.37 34820.84 35118.99 36365.34 37927.73 38550.43 3747.67 3879.50 3808.01 3816.34 3816.13 38526.24 38023.40 38010.69 3792.99 378
test_blank0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.02 3820.00 3870.00 3830.00 3810.00 3810.00 379
uanet_test0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3830.00 3870.00 3830.00 3810.00 3810.00 379
DCPMVS0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3830.00 3870.00 3830.00 3810.00 3810.00 379
cdsmvs_eth3d_5k23.43 34731.24 3500.00 3640.00 3870.00 3880.00 37598.09 1910.00 3820.00 38399.67 10283.37 2390.00 3830.00 3810.00 3810.00 379
pcd_1.5k_mvsjas7.60 35010.13 3530.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 38391.20 1570.00 3830.00 3810.00 3810.00 379
sosnet-low-res0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3830.00 3870.00 3830.00 3810.00 3810.00 379
sosnet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3830.00 3870.00 3830.00 3810.00 3810.00 379
uncertanet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3830.00 3870.00 3830.00 3810.00 3810.00 379
Regformer0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3830.00 3870.00 3830.00 3810.00 3810.00 379
ab-mvs-re8.28 34911.04 3520.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 38399.40 1240.00 3870.00 3830.00 3810.00 3810.00 379
uanet0.00 3510.00 3540.00 3640.00 3870.00 3880.00 3750.00 3880.00 3820.00 3830.00 3830.00 3870.00 3830.00 3810.00 3810.00 379
FOURS199.92 3697.66 9099.95 4398.36 15295.58 7399.52 54
test_one_060199.94 1499.30 1198.41 13696.63 4099.75 2899.93 1197.49 10
eth-test20.00 387
eth-test0.00 387
test_241102_ONE99.93 2799.30 1198.43 12097.26 2399.80 1799.88 2496.71 24100.00 1
save fliter99.82 7098.79 3799.96 2598.40 14097.66 10
test072699.93 2799.29 1499.96 2598.42 13297.28 1999.86 599.94 497.22 19
GSMVS99.59 139
test_part299.89 5099.25 1799.49 56
sam_mvs194.72 6799.59 139
sam_mvs94.25 86
MTGPAbinary98.28 167
test_post63.35 37694.43 7298.13 228
patchmatchnet-post91.70 35095.12 5297.95 239
MTMP99.87 9396.49 328
TEST999.92 3698.92 2799.96 2598.43 12093.90 14199.71 3499.86 3195.88 3899.85 99
test_899.92 3698.88 3099.96 2598.43 12094.35 11599.69 3699.85 3595.94 3599.85 99
agg_prior99.93 2798.77 4098.43 12099.63 4099.85 99
test_prior498.05 7499.94 61
test_prior99.43 3899.94 1498.49 6198.65 6299.80 11199.99 24
新几何299.40 201
旧先验199.76 7997.52 9598.64 6599.85 3595.63 4399.94 6199.99 24
原ACMM299.90 80
test22299.55 10197.41 10799.34 21198.55 8591.86 21299.27 7699.83 5193.84 10099.95 5599.99 24
segment_acmp96.68 26
testdata199.28 22196.35 52
test1299.43 3899.74 8298.56 5798.40 14099.65 3894.76 6699.75 12699.98 3599.99 24
plane_prior795.71 27491.59 270
plane_prior695.76 26991.72 26580.47 268
plane_prior498.59 187
plane_prior391.64 26896.63 4093.01 213
plane_prior299.84 11296.38 48
plane_prior195.73 271
plane_prior91.74 26299.86 10596.76 3689.59 232
n20.00 388
nn0.00 388
door-mid89.69 376
test1198.44 112
door90.31 374
HQP5-MVS91.85 258
HQP-NCC95.78 26599.87 9396.82 3293.37 209
ACMP_Plane95.78 26599.87 9396.82 3293.37 209
HQP4-MVS93.37 20998.39 20594.53 239
HQP3-MVS97.89 20989.60 230
HQP2-MVS80.65 264
NP-MVS95.77 26891.79 26098.65 183
ACMMP++_ref87.04 268
ACMMP++88.23 254
Test By Simon92.82 128