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-MVS99.02 198.84 199.55 199.57 2398.96 299.39 598.93 3597.38 1899.41 399.54 196.66 599.84 4298.86 199.85 299.87 1
SteuartSystems-ACMMP98.90 298.75 299.36 1299.22 7198.43 1699.10 4498.87 4897.38 1899.35 599.40 697.78 199.87 3497.77 3899.85 299.78 7
Skip Steuart: Steuart Systems R&D Blog.
TSAR-MVS + MP.98.78 398.62 499.24 2599.69 1798.28 2799.14 3798.66 10396.84 4399.56 299.31 2196.34 1099.70 9198.32 1999.73 3499.73 27
CNVR-MVS98.78 398.56 699.45 899.32 4598.87 598.47 14498.81 5897.72 498.76 3399.16 4297.05 299.78 7498.06 2499.66 4299.69 35
HSP-MVS98.70 598.52 899.24 2599.75 398.23 2899.26 1798.58 11697.52 899.41 398.78 8496.00 2399.79 6997.79 3799.59 5199.69 35
XVS98.70 598.49 1299.34 1399.70 1598.35 2299.29 1498.88 4697.40 1598.46 4599.20 3595.90 2999.89 2597.85 3399.74 3299.78 7
Regformer-298.69 798.52 899.19 2899.35 3798.01 4198.37 15398.81 5897.48 1299.21 999.21 3296.13 1699.80 5798.40 1799.73 3499.75 20
Regformer-198.66 898.51 1099.12 4099.35 3797.81 4998.37 15398.76 7197.49 1099.20 1099.21 3296.08 1999.79 6998.42 1599.73 3499.75 20
MCST-MVS98.65 998.37 1799.48 599.60 2298.87 598.41 15098.68 9397.04 3898.52 4498.80 8396.78 499.83 4397.93 2799.61 4699.74 25
Regformer-498.64 1098.53 798.99 4699.43 3597.37 6298.40 15198.79 6697.46 1399.09 1399.31 2195.86 3199.80 5798.64 399.76 2399.79 4
SD-MVS98.64 1098.68 398.53 7299.33 4298.36 2198.90 6098.85 5297.28 2299.72 199.39 796.63 797.60 27498.17 2299.85 299.64 53
HFP-MVS98.63 1298.40 1499.32 1699.72 1198.29 2599.23 2198.96 3096.10 6598.94 2199.17 3996.06 2099.92 1397.62 4499.78 1499.75 20
ACMMP_Plus98.61 1398.30 2599.55 199.62 2198.95 398.82 7698.81 5895.80 7299.16 1299.47 495.37 4099.92 1397.89 3199.75 2999.79 4
region2R98.61 1398.38 1699.29 1899.74 798.16 3499.23 2198.93 3596.15 6098.94 2199.17 3995.91 2899.94 397.55 4999.79 1099.78 7
NCCC98.61 1398.35 2099.38 1099.28 6098.61 1098.45 14598.76 7197.82 398.45 4898.93 7196.65 699.83 4397.38 5699.41 7599.71 32
Regformer-398.59 1698.50 1198.86 5699.43 3597.05 7398.40 15198.68 9397.43 1499.06 1499.31 2195.80 3299.77 7998.62 599.76 2399.78 7
ACMMPR98.59 1698.36 1899.29 1899.74 798.15 3599.23 2198.95 3296.10 6598.93 2599.19 3895.70 3399.94 397.62 4499.79 1099.78 7
MTAPA98.58 1898.29 2699.46 699.76 198.64 898.90 6098.74 7597.27 2698.02 6399.39 794.81 5499.96 197.91 2899.79 1099.77 14
HPM-MVS++98.58 1898.25 2999.55 199.50 2799.08 198.72 10698.66 10397.51 998.15 5598.83 8095.70 3399.92 1397.53 5199.67 3999.66 48
CP-MVS98.57 2098.36 1899.19 2899.66 1997.86 4699.34 1198.87 4895.96 6898.60 4199.13 4496.05 2299.94 397.77 3899.86 199.77 14
MSLP-MVS++98.56 2198.57 598.55 7099.26 6396.80 8298.71 10799.05 2297.28 2298.84 2799.28 2596.47 999.40 12198.52 1399.70 3799.47 77
MPTG98.55 2298.25 2999.46 699.76 198.64 898.55 13398.74 7597.27 2698.02 6399.39 794.81 5499.96 197.91 2899.79 1099.77 14
DeepC-MVS_fast96.70 198.55 2298.34 2199.18 3299.25 6498.04 3998.50 14198.78 6897.72 498.92 2699.28 2595.27 4499.82 4897.55 4999.77 1799.69 35
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
#test#98.54 2498.27 2799.32 1699.72 1198.29 2598.98 5498.96 3095.65 7898.94 2199.17 3996.06 2099.92 1397.21 5999.78 1499.75 20
APD-MVS_3200maxsize98.53 2598.33 2499.15 3799.50 2797.92 4599.15 3698.81 5896.24 5899.20 1099.37 1295.30 4399.80 5797.73 4099.67 3999.72 30
mPP-MVS98.51 2698.26 2899.25 2499.75 398.04 3999.28 1698.81 5896.24 5898.35 5299.23 2995.46 3899.94 397.42 5499.81 899.77 14
PGM-MVS98.49 2798.23 3299.27 2399.72 1198.08 3898.99 5199.49 595.43 8699.03 1599.32 2095.56 3599.94 396.80 7899.77 1799.78 7
EI-MVSNet-Vis-set98.47 2898.39 1598.69 6199.46 3296.49 9598.30 16398.69 9097.21 2898.84 2799.36 1695.41 3999.78 7498.62 599.65 4399.80 3
MVS_111021_HR98.47 2898.34 2198.88 5499.22 7197.32 6397.91 20599.58 397.20 2998.33 5399.00 6295.99 2499.64 10098.05 2599.76 2399.69 35
EI-MVSNet-UG-set98.41 3098.34 2198.61 6699.45 3396.32 10298.28 16598.68 9397.17 3198.74 3499.37 1295.25 4599.79 6998.57 799.54 6399.73 27
DELS-MVS98.40 3198.20 3498.99 4699.00 8297.66 5197.75 22398.89 4397.71 698.33 5398.97 6494.97 5299.88 3398.42 1599.76 2399.42 84
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023
TSAR-MVS + GP.98.38 3298.24 3198.81 5799.22 7197.25 6798.11 18598.29 16397.19 3098.99 2099.02 5796.22 1199.67 9698.52 1398.56 11099.51 69
HPM-MVS_fast98.38 3298.13 3599.12 4099.75 397.86 4699.44 498.82 5594.46 12498.94 2199.20 3595.16 4899.74 8597.58 4699.85 299.77 14
HPM-MVS98.36 3498.10 3699.13 3899.74 797.82 4899.53 198.80 6594.63 11798.61 4098.97 6495.13 4999.77 7997.65 4399.83 799.79 4
APD-MVScopyleft98.35 3598.00 4099.42 999.51 2698.72 798.80 8598.82 5594.52 12099.23 899.25 2895.54 3799.80 5796.52 8899.77 1799.74 25
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MVS_111021_LR98.34 3698.23 3298.67 6399.27 6196.90 7997.95 20099.58 397.14 3398.44 4999.01 6195.03 5199.62 10597.91 2899.75 2999.50 70
PHI-MVS98.34 3698.06 3799.18 3299.15 7898.12 3799.04 4799.09 1893.32 16998.83 2999.10 4896.54 899.83 4397.70 4299.76 2399.59 61
MP-MVScopyleft98.33 3898.01 3999.28 2099.75 398.18 3399.22 2798.79 6696.13 6297.92 7299.23 2994.54 5999.94 396.74 8099.78 1499.73 27
MP-MVS-pluss98.31 3997.92 4299.49 499.72 1198.88 498.43 14898.78 6894.10 13097.69 8499.42 595.25 4599.92 1398.09 2399.80 999.67 46
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
abl_698.30 4098.03 3899.13 3899.56 2497.76 5099.13 4098.82 5596.14 6199.26 699.37 1293.33 7699.93 996.96 6699.67 3999.69 35
ACMMPcopyleft98.23 4197.95 4199.09 4299.74 797.62 5499.03 4899.41 695.98 6797.60 9099.36 1694.45 6499.93 997.14 6098.85 9799.70 34
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
test_prior398.22 4297.90 4399.19 2899.31 4798.22 3097.80 21998.84 5396.12 6397.89 7498.69 9195.96 2599.70 9196.89 7099.60 4799.65 50
MVS_030598.00 4397.71 4698.87 5598.77 9397.19 6998.28 16598.71 8697.57 797.70 8298.92 7291.16 11399.93 998.71 299.60 4799.48 75
train_agg97.97 4497.52 5499.33 1599.31 4798.50 1297.92 20298.73 7992.98 18097.74 8098.68 9396.20 1299.80 5796.59 8499.57 5499.68 41
UA-Net97.96 4597.62 4898.98 4898.86 8897.47 5998.89 6499.08 1996.67 4998.72 3599.54 193.15 7999.81 5094.87 13398.83 9899.65 50
agg_prior197.95 4697.51 5599.28 2099.30 5298.38 1797.81 21898.72 8193.16 17497.57 9298.66 9696.14 1599.81 5096.63 8399.56 6099.66 48
CDPH-MVS97.94 4797.49 5699.28 2099.47 3198.44 1497.91 20598.67 10092.57 19398.77 3298.85 7895.93 2799.72 8695.56 11799.69 3899.68 41
DeepPCF-MVS96.37 297.93 4898.48 1396.30 21099.00 8289.54 27197.43 24298.87 4898.16 299.26 699.38 1196.12 1799.64 10098.30 2099.77 1799.72 30
DeepC-MVS95.98 397.88 4997.58 5098.77 5899.25 6496.93 7798.83 7498.75 7496.96 4196.89 11299.50 390.46 12499.87 3497.84 3599.76 2399.52 66
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
agg_prior397.87 5097.42 6099.23 2799.29 5598.23 2897.92 20298.72 8192.38 20697.59 9198.64 9896.09 1899.79 6996.59 8499.57 5499.68 41
DP-MVS Recon97.86 5197.46 5899.06 4499.53 2598.35 2298.33 15698.89 4392.62 19098.05 6098.94 7095.34 4299.65 9896.04 9999.42 7499.19 103
CSCG97.85 5297.74 4598.20 9299.67 1895.16 14999.22 2799.32 793.04 17797.02 10598.92 7295.36 4199.91 2197.43 5399.64 4499.52 66
MG-MVS97.81 5397.60 4998.44 7999.12 8095.97 11597.75 22398.78 6896.89 4298.46 4599.22 3193.90 7399.68 9594.81 13699.52 6599.67 46
VNet97.79 5497.40 6198.96 5098.88 8697.55 5698.63 12098.93 3596.74 4699.02 1698.84 7990.33 12799.83 4398.53 996.66 15699.50 70
PS-MVSNAJ97.73 5597.77 4497.62 12698.68 10195.58 13397.34 25198.51 12897.29 2198.66 3797.88 16194.51 6099.90 2397.87 3299.17 8597.39 180
CPTT-MVS97.72 5697.32 6398.92 5299.64 2097.10 7299.12 4298.81 5892.34 20798.09 5899.08 5493.01 8099.92 1396.06 9899.77 1799.75 20
PVSNet_Blended_VisFu97.70 5797.46 5898.44 7999.27 6195.91 12498.63 12099.16 1694.48 12397.67 8598.88 7592.80 8299.91 2197.11 6199.12 8699.50 70
canonicalmvs97.67 5897.23 6698.98 4898.70 9898.38 1799.34 1198.39 15096.76 4597.67 8597.40 19692.26 8999.49 11598.28 2196.28 16799.08 117
xiu_mvs_v2_base97.66 5997.70 4797.56 12998.61 10795.46 13997.44 24098.46 13897.15 3298.65 3898.15 14194.33 6699.80 5797.84 3598.66 10697.41 178
xiu_mvs_v1_base_debu97.60 6097.56 5197.72 11998.35 11495.98 11197.86 21498.51 12897.13 3499.01 1798.40 11791.56 10699.80 5798.53 998.68 10297.37 181
xiu_mvs_v1_base97.60 6097.56 5197.72 11998.35 11495.98 11197.86 21498.51 12897.13 3499.01 1798.40 11791.56 10699.80 5798.53 998.68 10297.37 181
xiu_mvs_v1_base_debi97.60 6097.56 5197.72 11998.35 11495.98 11197.86 21498.51 12897.13 3499.01 1798.40 11791.56 10699.80 5798.53 998.68 10297.37 181
MVSFormer97.57 6397.49 5697.84 11298.07 13395.76 12999.47 298.40 14894.98 10398.79 3098.83 8092.34 8698.41 23196.91 6899.59 5199.34 87
alignmvs97.56 6497.07 7399.01 4598.66 10298.37 2098.83 7498.06 21296.74 4698.00 6797.65 18290.80 12199.48 11998.37 1896.56 16099.19 103
OMC-MVS97.55 6597.34 6298.20 9299.33 4295.92 12298.28 16598.59 11195.52 8397.97 6899.10 4893.28 7899.49 11595.09 13298.88 9499.19 103
PAPM_NR97.46 6697.11 7098.50 7499.50 2796.41 9898.63 12098.60 11095.18 9497.06 10398.06 14794.26 6899.57 10893.80 16398.87 9699.52 66
EPP-MVSNet97.46 6697.28 6497.99 10698.64 10495.38 14199.33 1398.31 15893.61 16097.19 9899.07 5594.05 7099.23 13196.89 7098.43 11799.37 86
3Dnovator94.51 597.46 6696.93 7799.07 4397.78 15297.64 5299.35 1099.06 2097.02 3993.75 20899.16 4289.25 13999.92 1397.22 5899.75 2999.64 53
CNLPA97.45 6997.03 7498.73 5999.05 8197.44 6198.07 18998.53 12495.32 8996.80 11898.53 10693.32 7799.72 8694.31 15099.31 8099.02 120
lupinMVS97.44 7097.22 6798.12 9898.07 13395.76 12997.68 22897.76 22494.50 12198.79 3098.61 9992.34 8699.30 12697.58 4699.59 5199.31 90
3Dnovator+94.38 697.43 7196.78 8499.38 1097.83 14998.52 1199.37 798.71 8697.09 3792.99 22999.13 4489.36 13699.89 2596.97 6499.57 5499.71 32
Vis-MVSNetpermissive97.42 7297.11 7098.34 8598.66 10296.23 10599.22 2799.00 2596.63 5198.04 6299.21 3288.05 18599.35 12596.01 10199.21 8399.45 83
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
API-MVS97.41 7397.25 6597.91 10998.70 9896.80 8298.82 7698.69 9094.53 11998.11 5798.28 13194.50 6399.57 10894.12 15599.49 6697.37 181
sss97.39 7496.98 7698.61 6698.60 10896.61 9098.22 17098.93 3593.97 13798.01 6598.48 11291.98 9999.85 4096.45 9098.15 12699.39 85
PVSNet_Blended97.38 7597.12 6998.14 9599.25 6495.35 14497.28 25599.26 893.13 17597.94 7098.21 13892.74 8399.81 5096.88 7399.40 7799.27 97
112197.37 7696.77 8699.16 3599.34 3997.99 4498.19 17498.68 9390.14 25498.01 6598.97 6494.80 5699.87 3493.36 17299.46 7199.61 56
WTY-MVS97.37 7696.92 7898.72 6098.86 8896.89 8198.31 16198.71 8695.26 9197.67 8598.56 10592.21 9299.78 7495.89 10396.85 15399.48 75
jason97.32 7897.08 7298.06 10497.45 17495.59 13297.87 21397.91 22094.79 11098.55 4398.83 8091.12 11499.23 13197.58 4699.60 4799.34 87
jason: jason.
MVS_Test97.28 7997.00 7598.13 9798.33 11895.97 11598.74 10198.07 20994.27 12798.44 4998.07 14692.48 8599.26 12896.43 9198.19 12599.16 108
EPNet97.28 7996.87 8098.51 7394.98 28996.14 10798.90 6097.02 27998.28 195.99 14199.11 4691.36 11099.89 2596.98 6399.19 8499.50 70
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
IS-MVSNet97.22 8196.88 7998.25 9098.85 9096.36 10099.19 3397.97 21795.39 8897.23 9798.99 6391.11 11598.93 16894.60 14198.59 10899.47 77
PLCcopyleft95.07 497.20 8296.78 8498.44 7999.29 5596.31 10498.14 18098.76 7192.41 20496.39 13198.31 13094.92 5399.78 7494.06 15698.77 10199.23 101
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
CHOSEN 280x42097.18 8397.18 6897.20 13898.81 9293.27 22395.78 29899.15 1795.25 9296.79 11998.11 14492.29 8899.07 15098.56 899.85 299.25 99
LS3D97.16 8496.66 9198.68 6298.53 11297.19 6998.93 5898.90 4192.83 18795.99 14199.37 1292.12 9599.87 3493.67 16699.57 5498.97 125
AdaColmapbinary97.15 8596.70 8798.48 7699.16 7696.69 8798.01 19498.89 4394.44 12596.83 11498.68 9390.69 12299.76 8194.36 14799.29 8298.98 124
Effi-MVS+97.12 8696.69 8898.39 8398.19 12796.72 8697.37 24798.43 14593.71 15197.65 8898.02 14992.20 9399.25 12996.87 7697.79 13899.19 103
CHOSEN 1792x268897.12 8696.80 8198.08 10199.30 5294.56 19098.05 19099.71 193.57 16197.09 9998.91 7488.17 18099.89 2596.87 7699.56 6099.81 2
F-COLMAP97.09 8896.80 8197.97 10799.45 3394.95 15898.55 13398.62 10993.02 17896.17 13598.58 10494.01 7199.81 5093.95 15898.90 9299.14 111
TAMVS97.02 8996.79 8397.70 12298.06 13595.31 14698.52 13698.31 15893.95 13897.05 10498.61 9993.49 7598.52 20795.33 12397.81 13799.29 95
CDS-MVSNet96.99 9096.69 8897.90 11098.05 13695.98 11198.20 17298.33 15793.67 15896.95 10698.49 11093.54 7498.42 22495.24 12997.74 14199.31 90
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
114514_t96.93 9196.27 10498.92 5299.50 2797.63 5398.85 7198.90 4184.80 30197.77 7799.11 4692.84 8199.66 9794.85 13499.77 1799.47 77
MAR-MVS96.91 9296.40 9898.45 7898.69 10096.90 7998.66 11898.68 9392.40 20597.07 10297.96 15491.54 10999.75 8393.68 16598.92 9198.69 143
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
HyFIR lowres test96.90 9396.49 9698.14 9599.33 4295.56 13597.38 24599.65 292.34 20797.61 8998.20 13989.29 13899.10 14796.97 6497.60 14499.77 14
Vis-MVSNet (Re-imp)96.87 9496.55 9497.83 11398.73 9695.46 13999.20 3198.30 16194.96 10596.60 12298.87 7690.05 13198.59 19693.67 16698.60 10799.46 81
MVS_dtu96.84 9596.38 9998.24 9197.81 15096.01 11097.98 19798.09 20697.49 1096.55 12598.86 7786.53 21699.89 2595.19 13198.89 9398.82 135
PAPR96.84 9596.24 10698.65 6498.72 9796.92 7897.36 24998.57 11793.33 16896.67 12197.57 18994.30 6799.56 11091.05 23298.59 10899.47 77
HY-MVS93.96 896.82 9796.23 10798.57 6898.46 11397.00 7498.14 18098.21 17493.95 13896.72 12097.99 15391.58 10599.76 8194.51 14596.54 16198.95 129
MVS_test032696.78 9896.28 10398.26 8897.92 14496.13 10997.88 21198.07 20997.38 1896.05 13898.49 11086.68 21499.87 3494.78 13799.30 8198.79 137
UGNet96.78 9896.30 10298.19 9498.24 12295.89 12698.88 6698.93 3597.39 1796.81 11797.84 16582.60 26199.90 2396.53 8799.49 6698.79 137
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
PVSNet_BlendedMVS96.73 10096.60 9297.12 14499.25 6495.35 14498.26 16899.26 894.28 12697.94 7097.46 19392.74 8399.81 5096.88 7393.32 21196.20 266
mvs_anonymous96.70 10196.53 9597.18 14098.19 12793.78 21198.31 16198.19 17794.01 13394.47 16598.27 13492.08 9798.46 21697.39 5597.91 13299.31 90
1112_ss96.63 10296.00 11398.50 7498.56 10996.37 9998.18 17898.10 20392.92 18294.84 15498.43 11592.14 9499.58 10794.35 14896.51 16299.56 65
mvs-test196.60 10396.68 9096.37 20497.89 14691.81 24298.56 13198.10 20396.57 5296.52 12797.94 15690.81 11999.45 12095.72 11098.01 12997.86 169
PMMVS96.60 10396.33 10197.41 13397.90 14593.93 20797.35 25098.41 14692.84 18697.76 7897.45 19591.10 11699.20 13396.26 9497.91 13299.11 113
DP-MVS96.59 10595.93 11498.57 6899.34 3996.19 10698.70 11098.39 15089.45 27394.52 16399.35 1891.85 10199.85 4092.89 19198.88 9499.68 41
PatchMatch-RL96.59 10596.03 11298.27 8799.31 4796.51 9497.91 20599.06 2093.72 15096.92 11098.06 14788.50 17599.65 9891.77 21899.00 8998.66 146
XVG-OURS96.55 10796.41 9796.99 15098.75 9593.76 21297.50 23998.52 12695.67 7696.83 11499.30 2488.95 15099.53 11395.88 10496.26 16897.69 173
FIs96.51 10896.12 10997.67 12597.13 19597.54 5799.36 899.22 1495.89 6994.03 19998.35 12391.98 9998.44 22196.40 9292.76 21897.01 190
XVG-OURS-SEG-HR96.51 10896.34 10097.02 14998.77 9393.76 21297.79 22198.50 13395.45 8596.94 10799.09 5287.87 19199.55 11296.76 7995.83 17797.74 170
PS-MVSNAJss96.43 11096.26 10596.92 15895.84 27195.08 15399.16 3598.50 13395.87 7093.84 20698.34 12794.51 6098.61 19496.88 7393.45 20897.06 187
FC-MVSNet-test96.42 11196.05 11097.53 13096.95 20297.27 6599.36 899.23 1295.83 7193.93 20198.37 12192.00 9898.32 24096.02 10092.72 21997.00 191
ab-mvs96.42 11195.71 12398.55 7098.63 10596.75 8597.88 21198.74 7593.84 14396.54 12698.18 14085.34 23699.75 8395.93 10296.35 16599.15 109
PVSNet91.96 1896.35 11396.15 10896.96 15399.17 7592.05 23996.08 29098.68 9393.69 15497.75 7997.80 17188.86 15399.69 9494.26 15299.01 8899.15 109
Test_1112_low_res96.34 11495.66 12798.36 8498.56 10995.94 11997.71 22598.07 20992.10 21394.79 15897.29 20091.75 10299.56 11094.17 15396.50 16399.58 63
diffmvs96.32 11595.74 11898.07 10398.26 12196.14 10798.53 13598.23 17290.10 25596.88 11397.73 17490.16 13099.15 13693.90 16097.85 13698.91 131
Effi-MVS+-dtu96.29 11696.56 9395.51 23597.89 14690.22 26598.80 8598.10 20396.57 5296.45 13096.66 24690.81 11998.91 17095.72 11097.99 13097.40 179
QAPM96.29 11695.40 12998.96 5097.85 14897.60 5599.23 2198.93 3589.76 26593.11 22699.02 5789.11 14399.93 991.99 21299.62 4599.34 87
Fast-Effi-MVS+96.28 11895.70 12498.03 10598.29 12095.97 11598.58 12698.25 16991.74 22195.29 14897.23 20391.03 11899.15 13692.90 18997.96 13198.97 125
nrg03096.28 11895.72 12097.96 10896.90 20698.15 3599.39 598.31 15895.47 8494.42 17498.35 12392.09 9698.69 18897.50 5289.05 25397.04 189
131496.25 12095.73 11997.79 11697.13 19595.55 13798.19 17498.59 11193.47 16492.03 25197.82 16991.33 11199.49 11594.62 14098.44 11598.32 160
HQP_MVS96.14 12195.90 11596.85 15997.42 17594.60 18898.80 8598.56 11897.28 2295.34 14598.28 13187.09 20799.03 15696.07 9694.27 18596.92 196
MVSTER96.06 12295.72 12097.08 14798.23 12395.93 12198.73 10498.27 16494.86 10995.07 14998.09 14588.21 17998.54 20096.59 8493.46 20696.79 213
test_djsdf96.00 12395.69 12596.93 15695.72 27595.49 13899.47 298.40 14894.98 10394.58 16197.86 16289.16 14298.41 23196.91 6894.12 19396.88 205
EI-MVSNet95.96 12495.83 11796.36 20597.93 14293.70 21698.12 18398.27 16493.70 15395.07 14999.02 5792.23 9198.54 20094.68 13893.46 20696.84 209
BH-untuned95.95 12595.72 12096.65 17698.55 11192.26 23698.23 16997.79 22393.73 14994.62 16098.01 15188.97 14999.00 15993.04 18298.51 11198.68 144
MSDG95.93 12695.30 13997.83 11398.90 8495.36 14296.83 27798.37 15391.32 23694.43 17398.73 9090.27 12899.60 10690.05 24798.82 9998.52 151
BH-RMVSNet95.92 12795.32 13797.69 12398.32 11994.64 18298.19 17497.45 25394.56 11896.03 13998.61 9985.02 23999.12 14090.68 23699.06 8799.30 93
Fast-Effi-MVS+-dtu95.87 12895.85 11695.91 22397.74 15491.74 24698.69 11198.15 18895.56 8194.92 15297.68 18188.98 14898.79 18593.19 17797.78 13997.20 185
LFMVS95.86 12994.98 15098.47 7798.87 8796.32 10298.84 7396.02 29993.40 16698.62 3999.20 3574.99 29999.63 10397.72 4197.20 14899.46 81
OpenMVScopyleft93.04 1395.83 13095.00 14898.32 8697.18 19297.32 6399.21 3098.97 2889.96 25891.14 25699.05 5686.64 21599.92 1393.38 17199.47 6897.73 171
VDD-MVS95.82 13195.23 14197.61 12798.84 9193.98 20698.68 11597.40 25895.02 10297.95 6999.34 1974.37 30499.78 7498.64 396.80 15499.08 117
UniMVSNet (Re)95.78 13295.19 14397.58 12896.99 20197.47 5998.79 9099.18 1595.60 7993.92 20297.04 22191.68 10398.48 21195.80 10887.66 27496.79 213
VPA-MVSNet95.75 13395.11 14597.69 12397.24 18597.27 6598.94 5799.23 1295.13 9695.51 14497.32 19885.73 22998.91 17097.33 5789.55 24796.89 204
HQP-MVS95.72 13495.40 12996.69 16897.20 18994.25 20198.05 19098.46 13896.43 5494.45 16697.73 17486.75 21298.96 16395.30 12494.18 18996.86 208
UniMVSNet_NR-MVSNet95.71 13595.15 14497.40 13496.84 20996.97 7598.74 10199.24 1095.16 9593.88 20397.72 17791.68 10398.31 24295.81 10687.25 27996.92 196
PatchmatchNetpermissive95.71 13595.52 12896.29 21197.58 16390.72 25896.84 27697.52 23894.06 13197.08 10096.96 22989.24 14098.90 17392.03 21198.37 11899.26 98
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
OPM-MVS95.69 13795.33 13696.76 16396.16 25894.63 18398.43 14898.39 15096.64 5095.02 15198.78 8485.15 23899.05 15195.21 13094.20 18896.60 243
ACMM93.85 995.69 13795.38 13396.61 18297.61 16093.84 21098.91 5998.44 14295.25 9294.28 18498.47 11386.04 22799.12 14095.50 11993.95 19896.87 206
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
tpmrst95.63 13995.69 12595.44 24197.54 16688.54 28796.97 26597.56 23293.50 16397.52 9496.93 23689.49 13399.16 13595.25 12896.42 16498.64 147
LPG-MVS_test95.62 14095.34 13496.47 19797.46 17193.54 21798.99 5198.54 12194.67 11394.36 17698.77 8685.39 23399.11 14495.71 11294.15 19196.76 216
CLD-MVS95.62 14095.34 13496.46 20097.52 16893.75 21497.27 25698.46 13895.53 8294.42 17498.00 15286.21 22298.97 16096.25 9594.37 18396.66 234
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
PatchFormer-LS_test95.47 14295.27 14096.08 21997.59 16290.66 25998.10 18797.34 26293.98 13696.08 13696.15 26387.65 19999.12 14095.27 12795.24 18198.44 156
IterMVS-LS95.46 14395.21 14296.22 21398.12 13193.72 21598.32 16098.13 19193.71 15194.26 18597.31 19992.24 9098.10 25394.63 13990.12 23996.84 209
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
jajsoiax95.45 14495.03 14796.73 16495.42 28494.63 18399.14 3798.52 12695.74 7393.22 22098.36 12283.87 25598.65 19296.95 6794.04 19496.91 201
CVMVSNet95.43 14596.04 11193.57 28197.93 14283.62 30398.12 18398.59 11195.68 7596.56 12399.02 5787.51 20197.51 27793.56 16997.44 14599.60 59
anonymousdsp95.42 14694.91 15496.94 15595.10 28895.90 12599.14 3798.41 14693.75 14693.16 22297.46 19387.50 20398.41 23195.63 11694.03 19596.50 256
DU-MVS95.42 14694.76 15797.40 13496.53 22396.97 7598.66 11898.99 2795.43 8693.88 20397.69 17888.57 17098.31 24295.81 10687.25 27996.92 196
mvs_tets95.41 14895.00 14896.65 17695.58 27994.42 19399.00 5098.55 12095.73 7493.21 22198.38 12083.45 25898.63 19397.09 6294.00 19696.91 201
BH-w/o95.38 14995.08 14696.26 21298.34 11791.79 24397.70 22697.43 25592.87 18594.24 18797.22 20488.66 16898.84 17991.55 22297.70 14298.16 163
VDDNet95.36 15094.53 16197.86 11198.10 13295.13 15198.85 7197.75 22590.46 24798.36 5199.39 773.27 30699.64 10097.98 2696.58 15998.81 136
TAPA-MVS93.98 795.35 15194.56 16097.74 11899.13 7994.83 16898.33 15698.64 10886.62 28996.29 13398.61 9994.00 7299.29 12780.00 30199.41 7599.09 114
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP93.49 1095.34 15294.98 15096.43 20197.67 15693.48 21998.73 10498.44 14294.94 10892.53 23998.53 10684.50 24699.14 13895.48 12094.00 19696.66 234
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
COLMAP_ROBcopyleft93.27 1295.33 15394.87 15596.71 16599.29 5593.24 22598.58 12698.11 19889.92 26193.57 21199.10 4886.37 22099.79 6990.78 23498.10 12897.09 186
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
Patchmatch-test195.32 15494.97 15296.35 20697.67 15691.29 25197.33 25297.60 23094.68 11296.92 11096.95 23083.97 25298.50 21091.33 22798.32 12199.25 99
AllTest95.24 15594.65 15996.99 15099.25 6493.21 22698.59 12498.18 18091.36 23293.52 21398.77 8684.67 24399.72 8689.70 25597.87 13498.02 166
LCM-MVSNet-Re95.22 15695.32 13794.91 25898.18 12987.85 29498.75 9795.66 30595.11 9788.96 27596.85 23990.26 12997.65 27295.65 11598.44 11599.22 102
EPNet_dtu95.21 15794.95 15395.99 22096.17 25590.45 26398.16 17997.27 26996.77 4493.14 22598.33 12890.34 12698.42 22485.57 28998.81 10099.09 114
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
XXY-MVS95.20 15894.45 16697.46 13196.75 21496.56 9298.86 7098.65 10793.30 17193.27 21998.27 13484.85 24298.87 17694.82 13591.26 23596.96 193
WR-MVS95.15 15994.46 16497.22 13796.67 21996.45 9698.21 17198.81 5894.15 12893.16 22297.69 17887.51 20198.30 24495.29 12688.62 26396.90 203
TranMVSNet+NR-MVSNet95.14 16094.48 16297.11 14596.45 22896.36 10099.03 4899.03 2395.04 10193.58 21097.93 15788.27 17898.03 25894.13 15486.90 28496.95 195
test-LLR95.10 16194.87 15595.80 22896.77 21189.70 26996.91 26995.21 30795.11 9794.83 15695.72 27487.71 19598.97 16093.06 18098.50 11298.72 140
WR-MVS_H95.05 16294.46 16496.81 16196.86 20895.82 12899.24 2099.24 1093.87 14292.53 23996.84 24090.37 12598.24 24893.24 17587.93 26996.38 261
ADS-MVSNet95.00 16394.45 16696.63 17998.00 13791.91 24196.04 29197.74 22690.15 25296.47 12896.64 24887.89 18998.96 16390.08 24597.06 14999.02 120
VPNet94.99 16494.19 17797.40 13497.16 19396.57 9198.71 10798.97 2895.67 7694.84 15498.24 13780.36 27698.67 19196.46 8987.32 27796.96 193
EPMVS94.99 16494.48 16296.52 19397.22 18791.75 24597.23 25791.66 32494.11 12997.28 9696.81 24185.70 23098.84 17993.04 18297.28 14798.97 125
NR-MVSNet94.98 16694.16 17897.44 13296.53 22397.22 6898.74 10198.95 3294.96 10589.25 27397.69 17889.32 13798.18 25094.59 14287.40 27696.92 196
FMVSNet394.97 16794.26 17297.11 14598.18 12996.62 8898.56 13198.26 16893.67 15894.09 19597.10 20984.25 24898.01 25992.08 20792.14 22296.70 225
CostFormer94.95 16894.73 15895.60 23497.28 18389.06 27897.53 23796.89 28389.66 26996.82 11696.72 24486.05 22598.95 16795.53 11896.13 17398.79 137
PAPM94.95 16894.00 18997.78 11797.04 19895.65 13196.03 29398.25 16991.23 24194.19 19097.80 17191.27 11298.86 17882.61 29697.61 14398.84 134
CP-MVSNet94.94 17094.30 17196.83 16096.72 21695.56 13599.11 4398.95 3293.89 14092.42 24497.90 15987.19 20698.12 25294.32 14988.21 26696.82 212
TR-MVS94.94 17094.20 17697.17 14197.75 15394.14 20397.59 23497.02 27992.28 21195.75 14397.64 18483.88 25498.96 16389.77 25196.15 17298.40 157
RPSCF94.87 17295.40 12993.26 28598.89 8582.06 30998.33 15698.06 21290.30 25196.56 12399.26 2787.09 20799.49 11593.82 16296.32 16698.24 161
v1neww94.83 17394.22 17396.68 17196.39 23194.85 16198.87 6798.11 19892.45 19994.45 16697.06 21688.82 15898.54 20092.93 18688.91 25696.65 236
v7new94.83 17394.22 17396.68 17196.39 23194.85 16198.87 6798.11 19892.45 19994.45 16697.06 21688.82 15898.54 20092.93 18688.91 25696.65 236
v694.83 17394.21 17596.69 16896.36 23594.85 16198.87 6798.11 19892.46 19494.44 17297.05 22088.76 16498.57 19892.95 18588.92 25596.65 236
DWT-MVSNet_test94.82 17694.36 16996.20 21497.35 18090.79 25698.34 15596.57 29492.91 18395.33 14796.44 25482.00 26399.12 14094.52 14495.78 17898.70 142
GA-MVS94.81 17794.03 18797.14 14297.15 19493.86 20996.76 27897.58 23194.00 13494.76 15997.04 22180.91 26998.48 21191.79 21796.25 16999.09 114
V4294.78 17894.14 18096.70 16796.33 24295.22 14898.97 5598.09 20692.32 20994.31 18097.06 21688.39 17698.55 19992.90 18988.87 25896.34 263
divwei89l23v2f11294.76 17994.12 18396.67 17496.28 24894.85 16198.69 11198.12 19392.44 20194.29 18396.94 23288.85 15598.48 21192.67 19488.79 26296.67 231
CR-MVSNet94.76 17994.15 17996.59 18497.00 19993.43 22094.96 30497.56 23292.46 19496.93 10896.24 25888.15 18197.88 26987.38 27796.65 15798.46 154
v114194.75 18194.11 18496.67 17496.27 25094.86 16098.69 11198.12 19392.43 20294.31 18096.94 23288.78 16398.48 21192.63 19688.85 26096.67 231
v194.75 18194.11 18496.69 16896.27 25094.87 15998.69 11198.12 19392.43 20294.32 17996.94 23288.71 16798.54 20092.66 19588.84 26196.67 231
DI_MVS_plusplus_test94.74 18393.62 21398.09 10095.34 28595.92 12298.09 18897.34 26294.66 11585.89 28795.91 26880.49 27599.38 12396.66 8298.22 12398.97 125
test_normal94.72 18493.59 21598.11 9995.30 28695.95 11897.91 20597.39 26094.64 11685.70 29095.88 26980.52 27499.36 12496.69 8198.30 12299.01 123
v794.69 18594.04 18696.62 18196.41 23094.79 17698.78 9298.13 19191.89 21794.30 18297.16 20688.13 18398.45 21891.96 21489.65 24496.61 241
v2v48294.69 18594.03 18796.65 17696.17 25594.79 17698.67 11698.08 20892.72 18894.00 20097.16 20687.69 19898.45 21892.91 18888.87 25896.72 221
pmmvs494.69 18593.99 19196.81 16195.74 27395.94 11997.40 24397.67 22890.42 24993.37 21797.59 18789.08 14498.20 24992.97 18491.67 23096.30 265
PCF-MVS93.45 1194.68 18893.43 22498.42 8298.62 10696.77 8495.48 30098.20 17684.63 30293.34 21898.32 12988.55 17299.81 5084.80 29298.96 9098.68 144
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
MVS94.67 18993.54 21898.08 10196.88 20796.56 9298.19 17498.50 13378.05 31592.69 23498.02 14991.07 11799.63 10390.09 24498.36 11998.04 165
PS-CasMVS94.67 18993.99 19196.71 16596.68 21895.26 14799.13 4099.03 2393.68 15692.33 24597.95 15585.35 23598.10 25393.59 16888.16 26896.79 213
cascas94.63 19193.86 19896.93 15696.91 20594.27 20096.00 29498.51 12885.55 29794.54 16296.23 26084.20 24998.87 17695.80 10896.98 15297.66 174
tpmvs94.60 19294.36 16995.33 25097.46 17188.60 28596.88 27497.68 22791.29 23893.80 20796.42 25588.58 16999.24 13091.06 23096.04 17498.17 162
LTVRE_ROB92.95 1594.60 19293.90 19696.68 17197.41 17894.42 19398.52 13698.59 11191.69 22291.21 25598.35 12384.87 24199.04 15591.06 23093.44 20996.60 243
Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
v114494.59 19493.92 19496.60 18396.21 25294.78 17898.59 12498.14 19091.86 22094.21 18997.02 22387.97 18698.41 23191.72 21989.57 24596.61 241
ADS-MVSNet294.58 19594.40 16895.11 25598.00 13788.74 28296.04 29197.30 26690.15 25296.47 12896.64 24887.89 18997.56 27690.08 24597.06 14999.02 120
ACMH92.88 1694.55 19693.95 19396.34 20897.63 15893.26 22498.81 8298.49 13793.43 16589.74 26898.53 10681.91 26499.08 14993.69 16493.30 21296.70 225
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
XVG-ACMP-BASELINE94.54 19794.14 18095.75 23196.55 22291.65 24798.11 18598.44 14294.96 10594.22 18897.90 15979.18 28299.11 14494.05 15793.85 19996.48 258
GBi-Net94.49 19893.80 20196.56 18998.21 12495.00 15498.82 7698.18 18092.46 19494.09 19597.07 21381.16 26697.95 26292.08 20792.14 22296.72 221
test194.49 19893.80 20196.56 18998.21 12495.00 15498.82 7698.18 18092.46 19494.09 19597.07 21381.16 26697.95 26292.08 20792.14 22296.72 221
v894.47 20093.77 20496.57 18896.36 23594.83 16899.05 4698.19 17791.92 21693.16 22296.97 22888.82 15898.48 21191.69 22087.79 27296.39 260
FMVSNet294.47 20093.61 21497.04 14898.21 12496.43 9798.79 9098.27 16492.46 19493.50 21597.09 21181.16 26698.00 26091.09 22891.93 22696.70 225
Patchmatch-test94.42 20293.68 21196.63 17997.60 16191.76 24494.83 30897.49 25089.45 27394.14 19397.10 20988.99 14598.83 18185.37 29198.13 12799.29 95
PEN-MVS94.42 20293.73 20896.49 19596.28 24894.84 16699.17 3499.00 2593.51 16292.23 24797.83 16886.10 22497.90 26592.55 19986.92 28396.74 218
v14419294.39 20493.70 20996.48 19696.06 26194.35 19798.58 12698.16 18791.45 22794.33 17897.02 22387.50 20398.45 21891.08 22989.11 25296.63 239
Baseline_NR-MVSNet94.35 20593.81 20095.96 22196.20 25394.05 20598.61 12396.67 29191.44 22893.85 20597.60 18688.57 17098.14 25194.39 14686.93 28295.68 279
v119294.32 20693.58 21696.53 19296.10 25994.45 19298.50 14198.17 18591.54 22594.19 19097.06 21686.95 21198.43 22390.14 24389.57 24596.70 225
ACMH+92.99 1494.30 20793.77 20495.88 22597.81 15092.04 24098.71 10798.37 15393.99 13590.60 26398.47 11380.86 27199.05 15192.75 19392.40 22196.55 250
v14894.29 20893.76 20695.91 22396.10 25992.93 23098.58 12697.97 21792.59 19293.47 21696.95 23088.53 17398.32 24092.56 19887.06 28196.49 257
v1094.29 20893.55 21796.51 19496.39 23194.80 17398.99 5198.19 17791.35 23493.02 22896.99 22688.09 18498.41 23190.50 24088.41 26596.33 264
MVP-Stereo94.28 21093.92 19495.35 24994.95 29092.60 23497.97 19897.65 22991.61 22390.68 26297.09 21186.32 22198.42 22489.70 25599.34 7995.02 288
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
OurMVSNet-221017-094.21 21194.00 18994.85 26195.60 27889.22 27698.89 6497.43 25595.29 9092.18 24998.52 10982.86 26098.59 19693.46 17091.76 22996.74 218
v192192094.20 21293.47 22396.40 20395.98 26494.08 20498.52 13698.15 18891.33 23594.25 18697.20 20586.41 21998.42 22490.04 24889.39 25096.69 230
v7n94.19 21393.43 22496.47 19795.90 26794.38 19699.26 1798.34 15691.99 21592.76 23397.13 20888.31 17798.52 20789.48 26087.70 27396.52 253
tpm294.19 21393.76 20695.46 23997.23 18689.04 27997.31 25496.85 28687.08 28896.21 13496.79 24283.75 25798.74 18792.43 20396.23 17098.59 149
v5294.18 21593.52 21996.13 21795.95 26694.29 19999.23 2198.21 17491.42 22992.84 23196.89 23787.85 19298.53 20691.51 22387.81 27095.57 282
V494.18 21593.52 21996.13 21795.89 26894.31 19899.23 2198.22 17391.42 22992.82 23296.89 23787.93 18898.52 20791.51 22387.81 27095.58 281
TESTMET0.1,194.18 21593.69 21095.63 23396.92 20389.12 27796.91 26994.78 31293.17 17394.88 15396.45 25378.52 28398.92 16993.09 17998.50 11298.85 132
dp94.15 21893.90 19694.90 25997.31 18286.82 29996.97 26597.19 27391.22 24296.02 14096.61 25085.51 23299.02 15890.00 24994.30 18498.85 132
tpm94.13 21993.80 20195.12 25496.50 22587.91 29397.44 24095.89 30492.62 19096.37 13296.30 25784.13 25098.30 24493.24 17591.66 23199.14 111
IterMVS94.09 22093.85 19994.80 26497.99 13990.35 26497.18 26098.12 19393.68 15692.46 24397.34 19784.05 25197.41 27992.51 20191.33 23296.62 240
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
test-mter94.08 22193.51 22195.80 22896.77 21189.70 26996.91 26995.21 30792.89 18494.83 15695.72 27477.69 28798.97 16093.06 18098.50 11298.72 140
test0.0.03 194.08 22193.51 22195.80 22895.53 28192.89 23197.38 24595.97 30195.11 9792.51 24196.66 24687.71 19596.94 28587.03 28093.67 20197.57 175
v124094.06 22393.29 22796.34 20896.03 26393.90 20898.44 14698.17 18591.18 24394.13 19497.01 22586.05 22598.42 22489.13 26589.50 24896.70 225
X-MVStestdata94.06 22392.30 24099.34 1399.70 1598.35 2299.29 1498.88 4697.40 1598.46 4543.50 32995.90 2999.89 2597.85 3399.74 3299.78 7
DTE-MVSNet93.98 22593.26 22896.14 21696.06 26194.39 19599.20 3198.86 5193.06 17691.78 25297.81 17085.87 22897.58 27590.53 23986.17 28896.46 259
pm-mvs193.94 22693.06 22996.59 18496.49 22695.16 14998.95 5698.03 21692.32 20991.08 25797.84 16584.54 24598.41 23192.16 20586.13 29096.19 267
tpmp4_e2393.91 22793.42 22695.38 24797.62 15988.59 28697.52 23897.34 26287.94 28494.17 19296.79 24282.91 25999.05 15190.62 23895.91 17598.50 152
MS-PatchMatch93.84 22893.63 21294.46 27396.18 25489.45 27297.76 22298.27 16492.23 21292.13 25097.49 19179.50 27998.69 18889.75 25399.38 7895.25 284
v74893.75 22993.06 22995.82 22795.73 27492.64 23399.25 1998.24 17191.60 22492.22 24896.52 25187.60 20098.46 21690.64 23785.72 29196.36 262
EU-MVSNet93.66 23094.14 18092.25 29095.96 26583.38 30498.52 13698.12 19394.69 11192.61 23698.13 14387.36 20596.39 30391.82 21690.00 24196.98 192
pmmvs593.65 23192.97 23195.68 23295.49 28292.37 23598.20 17297.28 26889.66 26992.58 23797.26 20182.14 26298.09 25593.18 17890.95 23696.58 245
tpm cat193.36 23292.80 23395.07 25697.58 16387.97 29296.76 27897.86 22182.17 30993.53 21296.04 26686.13 22399.13 13989.24 26395.87 17698.10 164
JIA-IIPM93.35 23392.49 23795.92 22296.48 22790.65 26095.01 30396.96 28185.93 29596.08 13687.33 31687.70 19798.78 18691.35 22695.58 17998.34 158
SixPastTwentyTwo93.34 23492.86 23294.75 26595.67 27689.41 27498.75 9796.67 29193.89 14090.15 26698.25 13680.87 27098.27 24790.90 23390.64 23796.57 247
USDC93.33 23592.71 23595.21 25196.83 21090.83 25596.91 26997.50 24493.84 14390.72 26198.14 14277.69 28798.82 18289.51 25993.21 21595.97 272
IB-MVS91.98 1793.27 23691.97 24397.19 13997.47 17093.41 22297.09 26395.99 30093.32 16992.47 24295.73 27278.06 28599.53 11394.59 14282.98 29698.62 148
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021
MIMVSNet93.26 23792.21 24196.41 20297.73 15593.13 22895.65 29997.03 27891.27 24094.04 19896.06 26575.33 29797.19 28286.56 28296.23 17098.92 130
Patchmtry93.22 23892.35 23995.84 22696.77 21193.09 22994.66 31097.56 23287.37 28792.90 23096.24 25888.15 18197.90 26587.37 27890.10 24096.53 252
FMVSNet193.19 23992.07 24296.56 18997.54 16695.00 15498.82 7698.18 18090.38 25092.27 24697.07 21373.68 30597.95 26289.36 26291.30 23396.72 221
LF4IMVS93.14 24092.79 23494.20 27695.88 26988.67 28497.66 23097.07 27593.81 14591.71 25397.65 18277.96 28698.81 18391.47 22591.92 22795.12 285
testgi93.06 24192.45 23894.88 26096.43 22989.90 26698.75 9797.54 23795.60 7991.63 25497.91 15874.46 30397.02 28486.10 28593.67 20197.72 172
PatchT93.06 24191.97 24396.35 20696.69 21792.67 23294.48 31197.08 27486.62 28997.08 10092.23 31187.94 18797.90 26578.89 30596.69 15598.49 153
TransMVSNet (Re)92.67 24391.51 24796.15 21596.58 22194.65 18198.90 6096.73 28790.86 24589.46 27197.86 16285.62 23198.09 25586.45 28381.12 30195.71 278
K. test v392.55 24491.91 24594.48 27195.64 27789.24 27599.07 4594.88 31194.04 13286.78 28397.59 18777.64 29097.64 27392.08 20789.43 24996.57 247
DSMNet-mixed92.52 24592.58 23692.33 28994.15 29782.65 30798.30 16394.26 31789.08 27892.65 23595.73 27285.01 24095.76 30686.24 28497.76 14098.59 149
RPMNet92.52 24591.17 24896.59 18497.00 19993.43 22094.96 30497.26 27082.27 30896.93 10892.12 31286.98 21097.88 26976.32 31096.65 15798.46 154
TinyColmap92.31 24791.53 24694.65 26796.92 20389.75 26896.92 26796.68 29090.45 24889.62 26997.85 16476.06 29598.81 18386.74 28192.51 22095.41 283
gg-mvs-nofinetune92.21 24890.58 26297.13 14396.75 21495.09 15295.85 29689.40 32785.43 29894.50 16481.98 32080.80 27298.40 23792.16 20598.33 12097.88 168
Test492.21 24890.34 26497.82 11592.83 30395.87 12797.94 20198.05 21594.50 12182.12 30694.48 28559.54 32198.54 20095.39 12298.22 12399.06 119
v1892.10 25090.97 25095.50 23696.34 23894.85 16198.82 7697.52 23889.99 25785.31 29493.26 29388.90 15296.92 28688.82 26779.77 30594.73 291
v1792.08 25190.94 25195.48 23896.34 23894.83 16898.81 8297.52 23889.95 25985.32 29293.24 29488.91 15196.91 28788.76 26879.63 30694.71 293
v1692.08 25190.94 25195.49 23796.38 23494.84 16698.81 8297.51 24189.94 26085.25 29593.28 29288.86 15396.91 28788.70 26979.78 30494.72 292
v1591.94 25390.77 25595.43 24396.31 24694.83 16898.77 9397.50 24489.92 26185.13 29693.08 29788.76 16496.86 28988.40 27179.10 30894.61 297
V1491.93 25490.76 25695.42 24696.33 24294.81 17298.77 9397.51 24189.86 26385.09 29793.13 29588.80 16296.83 29188.32 27279.06 31094.60 298
V991.91 25590.73 25795.45 24096.32 24594.80 17398.77 9397.50 24489.81 26485.03 29993.08 29788.76 16496.86 28988.24 27379.03 31194.69 294
v1291.89 25690.70 25895.43 24396.31 24694.80 17398.76 9697.50 24489.76 26584.95 30093.00 30088.82 15896.82 29388.23 27479.00 31294.68 296
v1391.88 25790.69 25995.43 24396.33 24294.78 17898.75 9797.50 24489.68 26884.93 30192.98 30188.84 15696.83 29188.14 27579.09 30994.69 294
v1191.85 25890.68 26095.36 24896.34 23894.74 18098.80 8597.43 25589.60 27185.09 29793.03 29988.53 17396.75 29487.37 27879.96 30394.58 299
FMVSNet591.81 25990.92 25394.49 27097.21 18892.09 23898.00 19697.55 23689.31 27690.86 26095.61 27774.48 30295.32 30885.57 28989.70 24396.07 270
pmmvs691.77 26090.63 26195.17 25394.69 29591.24 25298.67 11697.92 21986.14 29289.62 26997.56 19075.79 29698.34 23890.75 23584.56 29595.94 273
Anonymous2023120691.66 26191.10 24993.33 28394.02 29987.35 29698.58 12697.26 27090.48 24690.16 26596.31 25683.83 25696.53 30179.36 30389.90 24296.12 268
Patchmatch-RL test91.49 26290.85 25493.41 28291.37 30784.40 30192.81 31695.93 30391.87 21987.25 28194.87 28288.99 14596.53 30192.54 20082.00 29899.30 93
test_040291.32 26390.27 26594.48 27196.60 22091.12 25398.50 14197.22 27286.10 29388.30 27896.98 22777.65 28997.99 26178.13 30792.94 21794.34 301
PVSNet_088.72 1991.28 26490.03 26795.00 25797.99 13987.29 29794.84 30798.50 13392.06 21489.86 26795.19 27879.81 27899.39 12292.27 20469.79 32098.33 159
EG-PatchMatch MVS91.13 26590.12 26694.17 27894.73 29489.00 28098.13 18297.81 22289.22 27785.32 29296.46 25267.71 31498.42 22487.89 27693.82 20095.08 286
LP91.12 26689.99 26894.53 26996.35 23788.70 28393.86 31597.35 26184.88 30090.98 25894.77 28384.40 24797.43 27875.41 31391.89 22897.47 176
TDRefinement91.06 26789.68 27095.21 25185.35 31991.49 24898.51 14097.07 27591.47 22688.83 27697.84 16577.31 29199.09 14892.79 19277.98 31395.04 287
UnsupCasMVSNet_eth90.99 26889.92 26994.19 27794.08 29889.83 26797.13 26298.67 10093.69 15485.83 28996.19 26275.15 29896.74 29589.14 26479.41 30796.00 271
test20.0390.89 26990.38 26392.43 28893.48 30088.14 29198.33 15697.56 23293.40 16687.96 27996.71 24580.69 27394.13 31279.15 30486.17 28895.01 289
MDA-MVSNet_test_wron90.71 27089.38 27394.68 26694.83 29290.78 25797.19 25997.46 25187.60 28572.41 31895.72 27486.51 21796.71 29885.92 28786.80 28596.56 249
YYNet190.70 27189.39 27294.62 26894.79 29390.65 26097.20 25897.46 25187.54 28672.54 31795.74 27186.51 21796.66 29986.00 28686.76 28696.54 251
testing_290.61 27288.50 27996.95 15490.08 31195.57 13497.69 22798.06 21293.02 17876.55 31392.48 30961.18 32098.44 22195.45 12191.98 22596.84 209
pmmvs-eth3d90.36 27389.05 27694.32 27591.10 30892.12 23797.63 23396.95 28288.86 27984.91 30293.13 29578.32 28496.74 29588.70 26981.81 30094.09 305
new_pmnet90.06 27489.00 27793.22 28694.18 29688.32 29096.42 28996.89 28386.19 29185.67 29193.62 29077.18 29297.10 28381.61 29889.29 25194.23 302
MDA-MVSNet-bldmvs89.97 27588.35 28194.83 26395.21 28791.34 24997.64 23197.51 24188.36 28271.17 31996.13 26479.22 28196.63 30083.65 29386.27 28796.52 253
CMPMVSbinary66.06 2189.70 27689.67 27189.78 29593.19 30176.56 31497.00 26498.35 15580.97 31181.57 30897.75 17374.75 30198.61 19489.85 25093.63 20394.17 303
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MIMVSNet189.67 27788.28 28293.82 27992.81 30491.08 25498.01 19497.45 25387.95 28387.90 28095.87 27067.63 31594.56 31178.73 30688.18 26795.83 275
MVS-HIRNet89.46 27888.40 28092.64 28797.58 16382.15 30894.16 31493.05 32375.73 31790.90 25982.52 31979.42 28098.33 23983.53 29498.68 10297.43 177
OpenMVS_ROBcopyleft86.42 2089.00 27987.43 28593.69 28093.08 30289.42 27397.91 20596.89 28378.58 31485.86 28894.69 28469.48 31198.29 24677.13 30893.29 21393.36 310
testus88.91 28089.08 27588.40 29891.39 30676.05 31596.56 28496.48 29589.38 27589.39 27295.17 28070.94 30993.56 31577.04 30995.41 18095.61 280
testpf88.74 28189.09 27487.69 29995.78 27283.16 30684.05 32694.13 32085.22 29990.30 26494.39 28774.92 30095.80 30589.77 25193.28 21484.10 320
test235688.68 28288.61 27888.87 29789.90 31278.23 31295.11 30296.66 29388.66 28189.06 27494.33 28973.14 30792.56 31975.56 31295.11 18295.81 276
new-patchmatchnet88.50 28387.45 28491.67 29290.31 31085.89 30097.16 26197.33 26589.47 27283.63 30492.77 30576.38 29395.06 31082.70 29577.29 31494.06 306
PM-MVS87.77 28486.55 28691.40 29391.03 30983.36 30596.92 26795.18 30991.28 23986.48 28693.42 29153.27 32296.74 29589.43 26181.97 29994.11 304
UnsupCasMVSNet_bld87.17 28585.12 28893.31 28491.94 30588.77 28194.92 30698.30 16184.30 30382.30 30590.04 31363.96 31997.25 28185.85 28874.47 31993.93 308
N_pmnet87.12 28687.77 28385.17 30695.46 28361.92 32897.37 24770.66 33585.83 29688.73 27796.04 26685.33 23797.76 27180.02 30090.48 23895.84 274
pmmvs386.67 28784.86 28992.11 29188.16 31487.19 29896.63 28194.75 31379.88 31387.22 28292.75 30666.56 31695.20 30981.24 29976.56 31693.96 307
test123567886.26 28885.81 28787.62 30086.97 31775.00 31996.55 28696.32 29886.08 29481.32 30992.98 30173.10 30892.05 32071.64 31687.32 27795.81 276
111184.94 28984.30 29086.86 30187.59 31575.10 31796.63 28196.43 29682.53 30680.75 31092.91 30368.94 31293.79 31368.24 31984.66 29491.70 312
Anonymous2023121183.69 29081.50 29290.26 29489.23 31380.10 31197.97 19897.06 27772.79 31982.05 30792.57 30750.28 32396.32 30476.15 31175.38 31794.37 300
test1235683.47 29183.37 29183.78 30784.43 32070.09 32495.12 30195.60 30682.98 30478.89 31292.43 31064.99 31791.41 32270.36 31785.55 29389.82 314
testmv78.74 29277.35 29382.89 30978.16 32869.30 32595.87 29594.65 31481.11 31070.98 32087.11 31746.31 32490.42 32365.28 32276.72 31588.95 315
LCM-MVSNet78.70 29376.24 29786.08 30377.26 32971.99 32294.34 31296.72 28861.62 32376.53 31489.33 31433.91 33292.78 31881.85 29774.60 31893.46 309
Gipumacopyleft78.40 29476.75 29583.38 30895.54 28080.43 31079.42 32797.40 25864.67 32173.46 31680.82 32245.65 32693.14 31766.32 32187.43 27576.56 325
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMMVS277.95 29575.44 29885.46 30482.54 32174.95 32094.23 31393.08 32272.80 31874.68 31587.38 31536.36 33091.56 32173.95 31463.94 32189.87 313
FPMVS77.62 29677.14 29479.05 31179.25 32560.97 32995.79 29795.94 30265.96 32067.93 32194.40 28637.73 32988.88 32568.83 31888.46 26487.29 316
no-one74.41 29770.76 29985.35 30579.88 32476.83 31394.68 30994.22 31880.33 31263.81 32279.73 32335.45 33193.36 31671.78 31536.99 32885.86 319
.test124573.05 29876.31 29663.27 31987.59 31575.10 31796.63 28196.43 29682.53 30680.75 31092.91 30368.94 31293.79 31368.24 31912.72 33120.91 329
ANet_high69.08 29965.37 30180.22 31065.99 33271.96 32390.91 32090.09 32682.62 30549.93 32878.39 32429.36 33381.75 32862.49 32538.52 32786.95 318
tmp_tt68.90 30066.97 30074.68 31550.78 33459.95 33087.13 32283.47 33338.80 32962.21 32396.23 26064.70 31876.91 33288.91 26630.49 32987.19 317
PNet_i23d67.70 30165.07 30275.60 31378.61 32659.61 33189.14 32188.24 32961.83 32252.37 32680.89 32118.91 33484.91 32762.70 32452.93 32382.28 321
PMVScopyleft61.03 2365.95 30263.57 30473.09 31657.90 33351.22 33485.05 32593.93 32154.45 32544.32 32983.57 31813.22 33589.15 32458.68 32681.00 30278.91 324
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
E-PMN64.94 30364.25 30367.02 31782.28 32259.36 33291.83 31985.63 33152.69 32660.22 32477.28 32541.06 32880.12 33046.15 32841.14 32561.57 327
EMVS64.07 30463.26 30566.53 31881.73 32358.81 33391.85 31884.75 33251.93 32859.09 32575.13 32643.32 32779.09 33142.03 32939.47 32661.69 326
wuykxyi23d63.73 30558.86 30778.35 31267.62 33167.90 32686.56 32387.81 33058.26 32442.49 33070.28 32811.55 33785.05 32663.66 32341.50 32482.11 322
MVEpermissive62.14 2263.28 30659.38 30674.99 31474.33 33065.47 32785.55 32480.50 33452.02 32751.10 32775.00 32710.91 33980.50 32951.60 32753.40 32278.99 323
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
pcd1.5k->3k39.42 30741.78 30832.35 32096.17 2550.00 3380.00 32998.54 1210.00 3330.00 3340.00 33587.78 1940.00 3360.00 33393.56 20597.06 187
wuyk23d30.17 30830.18 31030.16 32178.61 32643.29 33566.79 32814.21 33617.31 33014.82 33311.93 33411.55 33741.43 33337.08 33019.30 3305.76 331
cdsmvs_eth3d_5k23.98 30931.98 3090.00 3240.00 3370.00 3380.00 32998.59 1110.00 3330.00 33498.61 9990.60 1230.00 3360.00 3330.00 3340.00 332
testmvs21.48 31024.95 31111.09 32314.89 3356.47 33796.56 2849.87 3377.55 33117.93 33139.02 3309.43 3405.90 33516.56 33212.72 33120.91 329
test12320.95 31123.72 31212.64 32213.54 3368.19 33696.55 2866.13 3387.48 33216.74 33237.98 33112.97 3366.05 33416.69 3315.43 33323.68 328
ab-mvs-re8.20 31210.94 3130.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 33498.43 1150.00 3410.00 3360.00 3330.00 3340.00 332
pcd_1.5k_mvsjas7.88 31310.50 3140.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 33594.51 600.00 3360.00 3330.00 3340.00 332
sosnet-low-res0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
sosnet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
uncertanet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
Regformer0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
uanet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
sam_mvs189.45 134
sam_mvs88.99 145
semantic-postprocess94.85 26197.98 14190.56 26298.11 19893.75 14692.58 23797.48 19283.91 25397.41 27992.48 20291.30 23396.58 245
ambc89.49 29686.66 31875.78 31692.66 31796.72 28886.55 28592.50 30846.01 32597.90 26590.32 24182.09 29794.80 290
MTGPAbinary98.74 75
test_post196.68 28030.43 33387.85 19298.69 18892.59 197
test_post31.83 33288.83 15798.91 170
patchmatchnet-post95.10 28189.42 13598.89 174
GG-mvs-BLEND96.59 18496.34 23894.98 15796.51 28888.58 32893.10 22794.34 28880.34 27798.05 25789.53 25896.99 15196.74 218
MTMP94.14 319
gm-plane-assit95.88 26987.47 29589.74 26796.94 23299.19 13493.32 174
test9_res96.39 9399.57 5499.69 35
TEST999.31 4798.50 1297.92 20298.73 7992.63 18997.74 8098.68 9396.20 1299.80 57
test_899.29 5598.44 1497.89 21098.72 8192.98 18097.70 8298.66 9696.20 1299.80 57
agg_prior295.87 10599.57 5499.68 41
agg_prior99.30 5298.38 1798.72 8197.57 9299.81 50
TestCases96.99 15099.25 6493.21 22698.18 18091.36 23293.52 21398.77 8684.67 24399.72 8689.70 25597.87 13498.02 166
test_prior498.01 4197.86 214
test_prior297.80 21996.12 6397.89 7498.69 9195.96 2596.89 7099.60 47
test_prior99.19 2899.31 4798.22 3098.84 5399.70 9199.65 50
旧先验297.57 23691.30 23798.67 3699.80 5795.70 114
新几何297.64 231
新几何199.16 3599.34 3998.01 4198.69 9090.06 25698.13 5698.95 6994.60 5899.89 2591.97 21399.47 6899.59 61
旧先验199.29 5597.48 5898.70 8999.09 5295.56 3599.47 6899.61 56
无先验97.58 23598.72 8191.38 23199.87 3493.36 17299.60 59
原ACMM297.67 229
原ACMM198.65 6499.32 4596.62 8898.67 10093.27 17297.81 7698.97 6495.18 4799.83 4393.84 16199.46 7199.50 70
test22299.23 7097.17 7197.40 24398.66 10388.68 28098.05 6098.96 6894.14 6999.53 6499.61 56
testdata299.89 2591.65 221
segment_acmp96.85 3
testdata98.26 8899.20 7495.36 14298.68 9391.89 21798.60 4199.10 4894.44 6599.82 4894.27 15199.44 7399.58 63
testdata197.32 25396.34 57
test1299.18 3299.16 7698.19 3298.53 12498.07 5995.13 4999.72 8699.56 6099.63 55
plane_prior797.42 17594.63 183
plane_prior697.35 18094.61 18687.09 207
plane_prior598.56 11899.03 15696.07 9694.27 18596.92 196
plane_prior498.28 131
plane_prior394.61 18697.02 3995.34 145
plane_prior298.80 8597.28 22
plane_prior197.37 179
plane_prior94.60 18898.44 14696.74 4694.22 187
n20.00 339
nn0.00 339
door-mid94.37 316
lessismore_v094.45 27494.93 29188.44 28891.03 32586.77 28497.64 18476.23 29498.42 22490.31 24285.64 29296.51 255
LGP-MVS_train96.47 19797.46 17193.54 21798.54 12194.67 11394.36 17698.77 8685.39 23399.11 14495.71 11294.15 19196.76 216
test1198.66 103
door94.64 315
HQP5-MVS94.25 201
HQP-NCC97.20 18998.05 19096.43 5494.45 166
ACMP_Plane97.20 18998.05 19096.43 5494.45 166
BP-MVS95.30 124
HQP4-MVS94.45 16698.96 16396.87 206
HQP3-MVS98.46 13894.18 189
HQP2-MVS86.75 212
NP-MVS97.28 18394.51 19197.73 174
MDTV_nov1_ep13_2view84.26 30296.89 27390.97 24497.90 7389.89 13293.91 15999.18 107
MDTV_nov1_ep1395.40 12997.48 16988.34 28996.85 27597.29 26793.74 14897.48 9597.26 20189.18 14199.05 15191.92 21597.43 146
ACMMP++_ref92.97 216
ACMMP++93.61 204
Test By Simon94.64 57
ITE_SJBPF95.44 24197.42 17591.32 25097.50 24495.09 10093.59 20998.35 12381.70 26598.88 17589.71 25493.39 21096.12 268
DeepMVS_CXcopyleft86.78 30297.09 19772.30 32195.17 31075.92 31684.34 30395.19 27870.58 31095.35 30779.98 30289.04 25492.68 311