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 bysort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
APDe-MVS99.02 198.84 199.55 399.57 2798.96 599.39 598.93 3697.38 1899.41 499.54 196.66 699.84 4698.86 299.85 299.87 1
SteuartSystems-ACMMP98.90 398.75 299.36 1499.22 7698.43 1999.10 5398.87 5197.38 1899.35 799.40 897.78 199.87 3897.77 4199.85 299.78 8
Skip Steuart: Steuart Systems R&D Blog.
SD-MVS98.64 1198.68 398.53 7899.33 4798.36 2598.90 7998.85 5597.28 2299.72 199.39 996.63 897.60 31098.17 2399.85 299.64 56
ESAPD98.92 298.67 499.65 199.58 2699.20 198.42 18298.91 4297.58 799.54 399.46 697.10 299.94 397.64 4899.84 799.83 2
TSAR-MVS + MP.98.78 498.62 599.24 2899.69 1898.28 3199.14 4598.66 11296.84 4499.56 299.31 2396.34 1299.70 9698.32 2099.73 3699.73 29
MSLP-MVS++98.56 2398.57 698.55 7499.26 6896.80 8798.71 13399.05 2397.28 2298.84 3199.28 2896.47 1199.40 14298.52 1499.70 3999.47 80
CNVR-MVS98.78 498.56 799.45 1099.32 5098.87 898.47 17498.81 6597.72 498.76 3799.16 4597.05 399.78 7998.06 2699.66 4499.69 38
Regformer-498.64 1198.53 898.99 5099.43 4097.37 6798.40 18498.79 7497.46 1399.09 1799.31 2395.86 3399.80 6298.64 499.76 2599.79 5
HSP-MVS98.70 698.52 999.24 2899.75 398.23 3299.26 1898.58 12597.52 899.41 498.78 9196.00 2599.79 7497.79 4099.59 5599.69 38
Regformer-298.69 898.52 999.19 3199.35 4298.01 4598.37 18698.81 6597.48 1299.21 1399.21 3596.13 1899.80 6298.40 1899.73 3699.75 22
Regformer-198.66 998.51 1199.12 4399.35 4297.81 5498.37 18698.76 8097.49 1199.20 1499.21 3596.08 2199.79 7498.42 1699.73 3699.75 22
Regformer-398.59 1798.50 1298.86 6099.43 4097.05 7898.40 18498.68 10297.43 1499.06 1899.31 2395.80 3499.77 8498.62 699.76 2599.78 8
XVS98.70 698.49 1399.34 1599.70 1698.35 2699.29 1498.88 4897.40 1598.46 5099.20 3895.90 3199.89 2997.85 3699.74 3499.78 8
DeepPCF-MVS96.37 297.93 5198.48 1496.30 24499.00 9389.54 30897.43 27598.87 5198.16 299.26 1099.38 1396.12 1999.64 10798.30 2199.77 1999.72 32
HFP-MVS98.63 1398.40 1599.32 1999.72 1198.29 2999.23 2398.96 3196.10 6798.94 2599.17 4296.06 2299.92 1597.62 4999.78 1699.75 22
EI-MVSNet-Vis-set98.47 3098.39 1698.69 6599.46 3796.49 10498.30 19798.69 9997.21 2998.84 3199.36 1895.41 4199.78 7998.62 699.65 4599.80 4
region2R98.61 1498.38 1799.29 2199.74 798.16 3899.23 2398.93 3696.15 6298.94 2599.17 4295.91 3099.94 397.55 5499.79 1299.78 8
MCST-MVS98.65 1098.37 1899.48 799.60 2598.87 898.41 18398.68 10297.04 3998.52 4998.80 8996.78 599.83 4797.93 3099.61 5199.74 27
ACMMPR98.59 1798.36 1999.29 2199.74 798.15 3999.23 2398.95 3396.10 6798.93 2999.19 4195.70 3599.94 397.62 4999.79 1299.78 8
CP-MVS98.57 2298.36 1999.19 3199.66 2097.86 5099.34 1198.87 5195.96 7098.60 4699.13 4796.05 2499.94 397.77 4199.86 199.77 15
NCCC98.61 1498.35 2199.38 1299.28 6598.61 1398.45 17598.76 8097.82 398.45 5498.93 7896.65 799.83 4797.38 6199.41 7999.71 35
EI-MVSNet-UG-set98.41 3398.34 2298.61 7099.45 3896.32 11198.28 19998.68 10297.17 3298.74 3899.37 1495.25 4899.79 7498.57 899.54 6799.73 29
MVS_111021_HR98.47 3098.34 2298.88 5999.22 7697.32 6897.91 23999.58 397.20 3098.33 5999.00 6795.99 2699.64 10798.05 2899.76 2599.69 38
DeepC-MVS_fast96.70 198.55 2498.34 2299.18 3599.25 6998.04 4398.50 17198.78 7697.72 498.92 3099.28 2895.27 4699.82 5397.55 5499.77 1999.69 38
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
APD-MVS_3200maxsize98.53 2798.33 2599.15 4099.50 3297.92 4999.15 4498.81 6596.24 6099.20 1499.37 1495.30 4599.80 6297.73 4399.67 4199.72 32
ACMMP_Plus98.61 1498.30 2699.55 399.62 2498.95 698.82 10298.81 6595.80 7499.16 1699.47 595.37 4299.92 1597.89 3499.75 3199.79 5
MTAPA98.58 1998.29 2799.46 899.76 198.64 1198.90 7998.74 8497.27 2698.02 7099.39 994.81 5799.96 197.91 3199.79 1299.77 15
#test#98.54 2698.27 2899.32 1999.72 1198.29 2998.98 7198.96 3195.65 8198.94 2599.17 4296.06 2299.92 1597.21 6499.78 1699.75 22
mPP-MVS98.51 2898.26 2999.25 2799.75 398.04 4399.28 1698.81 6596.24 6098.35 5899.23 3295.46 4099.94 397.42 5999.81 999.77 15
SMA-MVS98.58 1998.25 3099.56 299.51 3099.04 498.95 7498.80 7293.67 18299.37 699.52 396.52 1099.89 2998.06 2699.81 999.76 21
zzz-MVS98.55 2498.25 3099.46 899.76 198.64 1198.55 16398.74 8497.27 2698.02 7099.39 994.81 5799.96 197.91 3199.79 1299.77 15
HPM-MVS++copyleft98.58 1998.25 3099.55 399.50 3299.08 398.72 13298.66 11297.51 998.15 6198.83 8695.70 3599.92 1597.53 5699.67 4199.66 51
TSAR-MVS + GP.98.38 3598.24 3398.81 6199.22 7697.25 7398.11 22098.29 17697.19 3198.99 2499.02 6296.22 1399.67 10398.52 1498.56 11399.51 72
PGM-MVS98.49 2998.23 3499.27 2699.72 1198.08 4298.99 6899.49 595.43 9099.03 1999.32 2295.56 3799.94 396.80 8699.77 1999.78 8
MVS_111021_LR98.34 3998.23 3498.67 6799.27 6696.90 8497.95 23499.58 397.14 3498.44 5599.01 6695.03 5499.62 11297.91 3199.75 3199.50 74
DELS-MVS98.40 3498.20 3698.99 5099.00 9397.66 5697.75 25698.89 4597.71 698.33 5998.97 6994.97 5599.88 3798.42 1699.76 2599.42 89
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
HPM-MVS_fast98.38 3598.13 3799.12 4399.75 397.86 5099.44 498.82 6194.46 14498.94 2599.20 3895.16 5199.74 9097.58 5199.85 299.77 15
GST-MVS98.43 3298.12 3899.34 1599.72 1198.38 2099.09 5498.82 6195.71 7798.73 3999.06 5995.27 4699.93 1097.07 6899.63 4999.72 32
HPM-MVScopyleft98.36 3798.10 3999.13 4199.74 797.82 5399.53 198.80 7294.63 13798.61 4598.97 6995.13 5299.77 8497.65 4799.83 899.79 5
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
PHI-MVS98.34 3998.06 4099.18 3599.15 8398.12 4199.04 6399.09 1993.32 20098.83 3399.10 5196.54 999.83 4797.70 4599.76 2599.59 64
abl_698.30 4398.03 4199.13 4199.56 2897.76 5599.13 4998.82 6196.14 6399.26 1099.37 1493.33 7999.93 1096.96 7299.67 4199.69 38
MP-MVScopyleft98.33 4198.01 4299.28 2399.75 398.18 3799.22 2998.79 7496.13 6497.92 8199.23 3294.54 6299.94 396.74 8899.78 1699.73 29
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
APD-MVScopyleft98.35 3898.00 4399.42 1199.51 3098.72 1098.80 11198.82 6194.52 14099.23 1299.25 3195.54 3999.80 6296.52 9699.77 1999.74 27
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ACMMPcopyleft98.23 4497.95 4499.09 4599.74 797.62 5999.03 6499.41 695.98 6997.60 10299.36 1894.45 6799.93 1097.14 6598.85 10099.70 37
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
MP-MVS-pluss98.31 4297.92 4599.49 699.72 1198.88 798.43 18098.78 7694.10 15197.69 9399.42 795.25 4899.92 1598.09 2599.80 1199.67 49
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
test_prior398.22 4597.90 4699.19 3199.31 5298.22 3497.80 25298.84 5696.12 6597.89 8398.69 9895.96 2799.70 9696.89 7699.60 5299.65 53
PS-MVSNAJ97.73 5897.77 4797.62 14398.68 13195.58 15097.34 28498.51 13797.29 2198.66 4297.88 17594.51 6399.90 2797.87 3599.17 8997.39 208
CANet98.05 4697.76 4898.90 5898.73 12397.27 7098.35 18898.78 7697.37 2097.72 9198.96 7491.53 11799.92 1598.79 399.65 4599.51 72
CSCG97.85 5597.74 4998.20 9999.67 1995.16 16899.22 2999.32 793.04 20897.02 12198.92 8095.36 4399.91 2497.43 5899.64 4799.52 69
xiu_mvs_v2_base97.66 6497.70 5097.56 15198.61 13795.46 15797.44 27398.46 14797.15 3398.65 4398.15 15294.33 6999.80 6297.84 3898.66 10997.41 206
UA-Net97.96 4897.62 5198.98 5298.86 11597.47 6498.89 8399.08 2096.67 5098.72 4099.54 193.15 8299.81 5594.87 14798.83 10199.65 53
MG-MVS97.81 5697.60 5298.44 8599.12 8595.97 12397.75 25698.78 7696.89 4398.46 5099.22 3493.90 7699.68 10294.81 15199.52 6999.67 49
DeepC-MVS95.98 397.88 5297.58 5398.77 6299.25 6996.93 8298.83 10098.75 8396.96 4296.89 12999.50 490.46 13399.87 3897.84 3899.76 2599.52 69
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
xiu_mvs_v1_base_debu97.60 6597.56 5497.72 13198.35 14795.98 11997.86 24798.51 13797.13 3599.01 2198.40 12691.56 11399.80 6298.53 1098.68 10597.37 210
xiu_mvs_v1_base97.60 6597.56 5497.72 13198.35 14795.98 11997.86 24798.51 13797.13 3599.01 2198.40 12691.56 11399.80 6298.53 1098.68 10597.37 210
xiu_mvs_v1_base_debi97.60 6597.56 5497.72 13198.35 14795.98 11997.86 24798.51 13797.13 3599.01 2198.40 12691.56 11399.80 6298.53 1098.68 10597.37 210
train_agg97.97 4797.52 5799.33 1899.31 5298.50 1597.92 23698.73 8992.98 21197.74 8998.68 10096.20 1499.80 6296.59 9299.57 5899.68 44
agg_prior197.95 4997.51 5899.28 2399.30 5798.38 2097.81 25198.72 9193.16 20597.57 10498.66 10396.14 1799.81 5596.63 9199.56 6499.66 51
CDPH-MVS97.94 5097.49 5999.28 2399.47 3698.44 1797.91 23998.67 10992.57 22598.77 3698.85 8495.93 2999.72 9195.56 12999.69 4099.68 44
casdiffmvs197.72 5997.49 5998.41 8998.52 14396.71 9299.14 4598.32 16895.15 11298.46 5098.31 13993.10 8399.21 16498.14 2498.27 12799.31 97
MVSFormer97.57 6897.49 5997.84 12198.07 17095.76 14599.47 298.40 15794.98 12098.79 3498.83 8692.34 9198.41 26596.91 7499.59 5599.34 92
PVSNet_Blended_VisFu97.70 6197.46 6298.44 8599.27 6695.91 13998.63 14999.16 1794.48 14397.67 9498.88 8292.80 8699.91 2497.11 6699.12 9099.50 74
DP-MVS Recon97.86 5497.46 6299.06 4899.53 2998.35 2698.33 19098.89 4592.62 22298.05 6698.94 7795.34 4499.65 10596.04 11099.42 7899.19 113
agg_prior397.87 5397.42 6499.23 3099.29 6098.23 3297.92 23698.72 9192.38 23897.59 10398.64 10596.09 2099.79 7496.59 9299.57 5899.68 44
VNet97.79 5797.40 6598.96 5498.88 11397.55 6198.63 14998.93 3696.74 4799.02 2098.84 8590.33 13699.83 4798.53 1096.66 16799.50 74
OMC-MVS97.55 7097.34 6698.20 9999.33 4795.92 13798.28 19998.59 12095.52 8697.97 7799.10 5193.28 8199.49 13395.09 14598.88 9799.19 113
CPTT-MVS97.72 5997.32 6798.92 5699.64 2197.10 7799.12 5198.81 6592.34 23998.09 6499.08 5793.01 8499.92 1596.06 10999.77 1999.75 22
EPP-MVSNet97.46 7197.28 6897.99 11398.64 13495.38 15999.33 1398.31 16993.61 18597.19 11199.07 5894.05 7399.23 15696.89 7698.43 12099.37 91
MVS_030497.70 6197.25 6999.07 4698.90 10497.83 5298.20 20598.74 8497.51 998.03 6999.06 5986.12 23399.93 1099.02 199.64 4799.44 87
API-MVS97.41 7997.25 6997.91 11798.70 12896.80 8798.82 10298.69 9994.53 13998.11 6398.28 14294.50 6699.57 12194.12 17099.49 7097.37 210
canonicalmvs97.67 6397.23 7198.98 5298.70 12898.38 2099.34 1198.39 15996.76 4697.67 9497.40 21292.26 9599.49 13398.28 2296.28 18999.08 131
lupinMVS97.44 7597.22 7298.12 10698.07 17095.76 14597.68 26197.76 23894.50 14198.79 3498.61 10792.34 9199.30 14897.58 5199.59 5599.31 97
CHOSEN 280x42097.18 9297.18 7397.20 17098.81 11993.27 25895.78 33499.15 1895.25 10696.79 13698.11 15592.29 9499.07 18298.56 999.85 299.25 107
casdiffmvs97.42 7797.12 7498.31 9498.35 14796.55 10299.05 6098.20 18994.97 12297.55 10698.11 15592.33 9399.18 16797.70 4597.85 14299.18 117
PVSNet_Blended97.38 8197.12 7498.14 10399.25 6995.35 16297.28 28899.26 893.13 20697.94 7998.21 14992.74 8799.81 5596.88 7999.40 8199.27 105
Vis-MVSNetpermissive97.42 7797.11 7698.34 9298.66 13296.23 11499.22 2999.00 2696.63 5298.04 6899.21 3588.05 19599.35 14796.01 11299.21 8799.45 86
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
PAPM_NR97.46 7197.11 7698.50 8099.50 3296.41 10798.63 14998.60 11995.18 10997.06 11898.06 15994.26 7199.57 12193.80 17798.87 9999.52 69
jason97.32 8597.08 7898.06 11197.45 20995.59 14997.87 24697.91 23394.79 12898.55 4898.83 8691.12 12199.23 15697.58 5199.60 5299.34 92
jason: jason.
alignmvs97.56 6997.07 7999.01 4998.66 13298.37 2498.83 10098.06 22596.74 4798.00 7697.65 19590.80 12899.48 13798.37 1996.56 17199.19 113
diffmvs197.35 8497.07 7998.20 9998.25 15596.13 11798.61 15298.34 16595.47 8797.66 9798.01 16392.54 8999.30 14896.44 9998.29 12699.17 119
CNLPA97.45 7497.03 8198.73 6399.05 8797.44 6698.07 22498.53 13395.32 10396.80 13598.53 11493.32 8099.72 9194.31 16599.31 8599.02 135
MVS_Test97.28 8697.00 8298.13 10598.33 15295.97 12398.74 12798.07 22394.27 14798.44 5598.07 15892.48 9099.26 15396.43 10098.19 13099.16 120
sss97.39 8096.98 8398.61 7098.60 13896.61 9698.22 20398.93 3693.97 16098.01 7498.48 11991.98 10599.85 4396.45 9898.15 13199.39 90
3Dnovator94.51 597.46 7196.93 8499.07 4697.78 18797.64 5799.35 1099.06 2197.02 4093.75 24299.16 4589.25 14899.92 1597.22 6399.75 3199.64 56
WTY-MVS97.37 8296.92 8598.72 6498.86 11596.89 8698.31 19598.71 9695.26 10597.67 9498.56 11392.21 9899.78 7995.89 11596.85 16299.48 79
IS-MVSNet97.22 8896.88 8698.25 9798.85 11796.36 10999.19 3597.97 23095.39 9297.23 11098.99 6891.11 12298.93 20094.60 15698.59 11199.47 80
EPNet97.28 8696.87 8798.51 7994.98 32796.14 11698.90 7997.02 29598.28 195.99 17599.11 4991.36 11899.89 2996.98 6999.19 8899.50 74
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268897.12 9596.80 8898.08 10999.30 5794.56 22298.05 22599.71 193.57 18697.09 11498.91 8188.17 18999.89 2996.87 8299.56 6499.81 3
F-COLMAP97.09 9796.80 8897.97 11499.45 3894.95 18198.55 16398.62 11893.02 20996.17 17098.58 11294.01 7499.81 5593.95 17398.90 9699.14 123
TAMVS97.02 9996.79 9097.70 13698.06 17295.31 16498.52 16698.31 16993.95 16197.05 11998.61 10793.49 7898.52 24195.33 13697.81 14399.29 103
0601test97.22 8896.78 9198.54 7698.73 12396.60 9798.45 17598.31 16994.70 12998.02 7098.42 12490.80 12899.70 9696.81 8496.79 16499.34 92
Anonymous2024052197.22 8896.78 9198.54 7698.73 12396.60 9798.45 17598.31 16994.70 12998.02 7098.42 12490.80 12899.70 9696.81 8496.79 16499.34 92
PLCcopyleft95.07 497.20 9196.78 9198.44 8599.29 6096.31 11398.14 21598.76 8092.41 23696.39 16698.31 13994.92 5699.78 7994.06 17198.77 10499.23 109
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
3Dnovator+94.38 697.43 7696.78 9199.38 1297.83 18598.52 1499.37 798.71 9697.09 3892.99 26399.13 4789.36 14599.89 2996.97 7099.57 5899.71 35
112197.37 8296.77 9599.16 3899.34 4497.99 4898.19 20998.68 10290.14 29098.01 7498.97 6994.80 5999.87 3893.36 18699.46 7599.61 59
diffmvs97.03 9896.75 9697.88 11998.14 16795.25 16698.54 16598.13 20595.17 11097.03 12097.94 16991.83 10899.30 14896.01 11297.94 13799.11 126
AdaColmapbinary97.15 9496.70 9798.48 8299.16 8196.69 9398.01 22998.89 4594.44 14596.83 13198.68 10090.69 13199.76 8694.36 16299.29 8698.98 139
Effi-MVS+97.12 9596.69 9898.39 9098.19 16196.72 9197.37 28098.43 15493.71 17597.65 9898.02 16192.20 9999.25 15496.87 8297.79 14499.19 113
CDS-MVSNet96.99 10096.69 9897.90 11898.05 17395.98 11998.20 20598.33 16793.67 18296.95 12298.49 11893.54 7798.42 25895.24 14397.74 14799.31 97
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
mvs-test196.60 11296.68 10096.37 23897.89 18291.81 27798.56 16198.10 21896.57 5396.52 15197.94 16990.81 12699.45 14095.72 12298.01 13497.86 194
LS3D97.16 9396.66 10198.68 6698.53 14297.19 7598.93 7798.90 4392.83 21995.99 17599.37 1492.12 10199.87 3893.67 18099.57 5898.97 140
PVSNet_BlendedMVS96.73 10996.60 10297.12 17699.25 6995.35 16298.26 20199.26 894.28 14697.94 7997.46 20792.74 8799.81 5596.88 7993.32 24396.20 303
Effi-MVS+-dtu96.29 12496.56 10395.51 26997.89 18290.22 30198.80 11198.10 21896.57 5396.45 16596.66 28090.81 12698.91 20295.72 12297.99 13597.40 207
CANet_DTU96.96 10196.55 10498.21 9898.17 16596.07 11897.98 23298.21 18697.24 2897.13 11398.93 7886.88 22299.91 2495.00 14699.37 8398.66 160
Vis-MVSNet (Re-imp)96.87 10596.55 10497.83 12298.73 12395.46 15799.20 3398.30 17494.96 12396.60 14498.87 8390.05 13998.59 23093.67 18098.60 11099.46 84
mvs_anonymous96.70 11096.53 10697.18 17298.19 16193.78 24598.31 19598.19 19194.01 15694.47 19998.27 14592.08 10398.46 25097.39 6097.91 13899.31 97
HyFIR lowres test96.90 10496.49 10798.14 10399.33 4795.56 15297.38 27899.65 292.34 23997.61 10198.20 15089.29 14799.10 17996.97 7097.60 15299.77 15
XVG-OURS96.55 11696.41 10896.99 18298.75 12293.76 24697.50 27298.52 13595.67 7996.83 13199.30 2788.95 15999.53 13095.88 11696.26 19097.69 201
MAR-MVS96.91 10396.40 10998.45 8498.69 13096.90 8498.66 14798.68 10292.40 23797.07 11797.96 16791.54 11699.75 8893.68 17998.92 9598.69 156
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
XVG-OURS-SEG-HR96.51 11796.34 11097.02 18198.77 12193.76 24697.79 25498.50 14295.45 8996.94 12499.09 5587.87 20199.55 12996.76 8795.83 20797.74 197
PMMVS96.60 11296.33 11197.41 16297.90 18193.93 24197.35 28398.41 15592.84 21897.76 8797.45 20991.10 12399.20 16596.26 10497.91 13899.11 126
UGNet96.78 10896.30 11298.19 10298.24 15695.89 14198.88 8698.93 3697.39 1796.81 13497.84 17982.60 29499.90 2796.53 9599.49 7098.79 151
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
114514_t96.93 10296.27 11398.92 5699.50 3297.63 5898.85 9698.90 4384.80 33897.77 8699.11 4992.84 8599.66 10494.85 14899.77 1999.47 80
PS-MVSNAJss96.43 11996.26 11496.92 19095.84 30795.08 17399.16 4398.50 14295.87 7293.84 24098.34 13694.51 6398.61 22796.88 7993.45 24097.06 220
PAPR96.84 10696.24 11598.65 6898.72 12796.92 8397.36 28298.57 12693.33 19996.67 13897.57 20294.30 7099.56 12391.05 24898.59 11199.47 80
HY-MVS93.96 896.82 10796.23 11698.57 7298.46 14497.00 7998.14 21598.21 18693.95 16196.72 13797.99 16691.58 11299.76 8694.51 16096.54 17298.95 144
PVSNet91.96 1896.35 12296.15 11796.96 18599.17 8092.05 27496.08 32698.68 10293.69 17897.75 8897.80 18588.86 16299.69 10194.26 16799.01 9299.15 121
FIs96.51 11796.12 11897.67 13997.13 23097.54 6299.36 899.22 1495.89 7194.03 23398.35 13291.98 10598.44 25596.40 10192.76 25097.01 223
FC-MVSNet-test96.42 12096.05 11997.53 15296.95 23797.27 7099.36 899.23 1295.83 7393.93 23598.37 13092.00 10498.32 27496.02 11192.72 25197.00 224
CVMVSNet95.43 16996.04 12093.57 31797.93 17983.62 34098.12 21898.59 12095.68 7896.56 14599.02 6287.51 21197.51 31393.56 18397.44 15499.60 62
PatchMatch-RL96.59 11496.03 12198.27 9599.31 5296.51 10397.91 23999.06 2193.72 17496.92 12798.06 15988.50 18499.65 10591.77 23399.00 9398.66 160
1112_ss96.63 11196.00 12298.50 8098.56 13996.37 10898.18 21398.10 21892.92 21494.84 18898.43 12292.14 10099.58 12094.35 16396.51 17399.56 68
DP-MVS96.59 11495.93 12398.57 7299.34 4496.19 11598.70 13698.39 15989.45 30894.52 19799.35 2091.85 10799.85 4392.89 20598.88 9799.68 44
HQP_MVS96.14 12995.90 12496.85 19197.42 21094.60 22098.80 11198.56 12797.28 2295.34 17998.28 14287.09 21799.03 18896.07 10794.27 21796.92 229
Fast-Effi-MVS+-dtu95.87 13895.85 12595.91 25797.74 18991.74 28198.69 13898.15 20295.56 8494.92 18697.68 19488.98 15798.79 21793.19 19197.78 14597.20 218
EI-MVSNet95.96 13495.83 12696.36 23997.93 17993.70 25198.12 21898.27 17793.70 17795.07 18399.02 6292.23 9798.54 23494.68 15293.46 23896.84 244
131496.25 12895.73 12797.79 12597.13 23095.55 15498.19 20998.59 12093.47 18992.03 28797.82 18391.33 11999.49 13394.62 15598.44 11898.32 181
nrg03096.28 12695.72 12897.96 11696.90 24298.15 3999.39 598.31 16995.47 8794.42 20898.35 13292.09 10298.69 22097.50 5789.05 28797.04 222
BH-untuned95.95 13595.72 12896.65 20898.55 14192.26 27198.23 20297.79 23793.73 17394.62 19498.01 16388.97 15899.00 19193.04 19698.51 11498.68 157
MVSTER96.06 13195.72 12897.08 17998.23 15795.93 13098.73 13098.27 17794.86 12795.07 18398.09 15788.21 18898.54 23496.59 9293.46 23896.79 248
ab-mvs96.42 12095.71 13198.55 7498.63 13596.75 9097.88 24598.74 8493.84 16696.54 14998.18 15185.34 25499.75 8895.93 11496.35 18199.15 121
Fast-Effi-MVS+96.28 12695.70 13298.03 11298.29 15495.97 12398.58 15698.25 18291.74 25495.29 18297.23 22591.03 12599.15 16992.90 20397.96 13698.97 140
test_djsdf96.00 13395.69 13396.93 18895.72 31195.49 15699.47 298.40 15794.98 12094.58 19597.86 17689.16 15198.41 26596.91 7494.12 22596.88 239
tpmrst95.63 15095.69 13395.44 27597.54 20188.54 32496.97 29897.56 24793.50 18897.52 10796.93 26489.49 14299.16 16895.25 14296.42 17698.64 162
Test_1112_low_res96.34 12395.66 13598.36 9198.56 13995.94 12797.71 25898.07 22392.10 24594.79 19297.29 22191.75 10999.56 12394.17 16896.50 17499.58 66
PatchmatchNetpermissive95.71 14695.52 13696.29 24597.58 19890.72 29496.84 31197.52 25394.06 15397.08 11596.96 25789.24 14998.90 20592.03 22598.37 12199.26 106
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
tttt051796.07 13095.51 13797.78 12698.41 14594.84 19799.28 1694.33 35294.26 14897.64 9998.64 10584.05 28299.47 13895.34 13597.60 15299.03 134
MDTV_nov1_ep1395.40 13897.48 20488.34 32696.85 31097.29 28293.74 17297.48 10897.26 22289.18 15099.05 18391.92 22997.43 155
HQP-MVS95.72 14495.40 13896.69 20097.20 22494.25 23598.05 22598.46 14796.43 5594.45 20097.73 18886.75 22398.96 19595.30 13794.18 22196.86 243
QAPM96.29 12495.40 13898.96 5497.85 18497.60 6099.23 2398.93 3689.76 30093.11 26099.02 6289.11 15299.93 1091.99 22699.62 5099.34 92
RPSCF94.87 20495.40 13893.26 32198.89 11282.06 34698.33 19098.06 22590.30 28796.56 14599.26 3087.09 21799.49 13393.82 17696.32 18398.24 182
ACMM93.85 995.69 14895.38 14296.61 21497.61 19593.84 24498.91 7898.44 15195.25 10694.28 21898.47 12086.04 24399.12 17295.50 13193.95 23096.87 241
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
thisisatest053096.01 13295.36 14397.97 11498.38 14695.52 15598.88 8694.19 35594.04 15497.64 9998.31 13983.82 28999.46 13995.29 13997.70 14998.93 145
LPG-MVS_test95.62 15195.34 14496.47 23197.46 20693.54 25298.99 6898.54 13094.67 13394.36 21098.77 9385.39 25199.11 17695.71 12494.15 22396.76 251
CLD-MVS95.62 15195.34 14496.46 23497.52 20393.75 24897.27 28998.46 14795.53 8594.42 20898.00 16586.21 23198.97 19296.25 10594.37 21596.66 269
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
OPM-MVS95.69 14895.33 14696.76 19596.16 29494.63 21598.43 18098.39 15996.64 5195.02 18598.78 9185.15 25699.05 18395.21 14494.20 22096.60 278
LCM-MVSNet-Re95.22 18795.32 14794.91 29398.18 16387.85 33198.75 12395.66 33795.11 11488.96 31396.85 27390.26 13897.65 30895.65 12798.44 11899.22 110
BH-RMVSNet95.92 13795.32 14797.69 13798.32 15394.64 21498.19 20997.45 26894.56 13896.03 17398.61 10785.02 25799.12 17290.68 25299.06 9199.30 101
MSDG95.93 13695.30 14997.83 12298.90 10495.36 16096.83 31298.37 16291.32 26994.43 20798.73 9790.27 13799.60 11390.05 26998.82 10298.52 166
PatchFormer-LS_test95.47 16695.27 15096.08 25397.59 19790.66 29598.10 22297.34 27793.98 15996.08 17196.15 30087.65 20999.12 17295.27 14195.24 21298.44 171
VDD-MVS95.82 14195.23 15197.61 14898.84 11893.98 24098.68 14297.40 27395.02 11997.95 7899.34 2174.37 34099.78 7998.64 496.80 16399.08 131
IterMVS-LS95.46 16795.21 15296.22 24798.12 16893.72 25098.32 19498.13 20593.71 17594.26 21997.31 22092.24 9698.10 28794.63 15390.12 27396.84 244
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
UniMVSNet (Re)95.78 14295.19 15397.58 14996.99 23697.47 6498.79 11699.18 1695.60 8293.92 23697.04 24991.68 11098.48 24595.80 12087.66 31096.79 248
UniMVSNet_NR-MVSNet95.71 14695.15 15497.40 16496.84 24596.97 8098.74 12799.24 1095.16 11193.88 23797.72 19091.68 11098.31 27695.81 11887.25 31596.92 229
tfpn100095.72 14495.11 15597.58 14999.00 9395.73 14799.24 2195.49 33994.08 15296.87 13097.45 20985.81 24599.30 14891.78 23296.22 19497.71 200
VPA-MVSNet95.75 14395.11 15597.69 13797.24 22097.27 7098.94 7699.23 1295.13 11395.51 17897.32 21985.73 24698.91 20297.33 6289.55 28196.89 237
BH-w/o95.38 17595.08 15796.26 24698.34 15191.79 27897.70 25997.43 27092.87 21794.24 22197.22 22688.66 17798.84 21191.55 23797.70 14998.16 184
jajsoiax95.45 16895.03 15896.73 19695.42 32294.63 21599.14 4598.52 13595.74 7593.22 25498.36 13183.87 28798.65 22596.95 7394.04 22696.91 234
mvs_tets95.41 17395.00 15996.65 20895.58 31594.42 22599.00 6798.55 12995.73 7693.21 25598.38 12983.45 29198.63 22697.09 6794.00 22896.91 234
OpenMVScopyleft93.04 1395.83 14095.00 15998.32 9397.18 22797.32 6899.21 3298.97 2989.96 29391.14 29499.05 6186.64 22599.92 1593.38 18599.47 7297.73 198
LFMVS95.86 13994.98 16198.47 8398.87 11496.32 11198.84 9996.02 32593.40 19798.62 4499.20 3874.99 33599.63 11097.72 4497.20 15799.46 84
ACMP93.49 1095.34 18094.98 16196.43 23597.67 19193.48 25498.73 13098.44 15194.94 12692.53 27498.53 11484.50 27199.14 17095.48 13294.00 22896.66 269
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
Patchmatch-test195.32 18294.97 16396.35 24097.67 19191.29 28697.33 28597.60 24594.68 13296.92 12796.95 25883.97 28498.50 24491.33 24398.32 12499.25 107
EPNet_dtu95.21 18894.95 16495.99 25496.17 29190.45 29998.16 21497.27 28496.77 4593.14 25998.33 13790.34 13598.42 25885.57 32398.81 10399.09 128
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
view60095.60 15494.93 16597.62 14399.05 8794.85 18899.09 5497.01 29795.36 9796.52 15197.37 21384.55 26699.59 11489.07 28896.39 17798.40 172
view80095.60 15494.93 16597.62 14399.05 8794.85 18899.09 5497.01 29795.36 9796.52 15197.37 21384.55 26699.59 11489.07 28896.39 17798.40 172
conf0.05thres100095.60 15494.93 16597.62 14399.05 8794.85 18899.09 5497.01 29795.36 9796.52 15197.37 21384.55 26699.59 11489.07 28896.39 17798.40 172
tfpn95.60 15494.93 16597.62 14399.05 8794.85 18899.09 5497.01 29795.36 9796.52 15197.37 21384.55 26699.59 11489.07 28896.39 17798.40 172
anonymousdsp95.42 17194.91 16996.94 18795.10 32695.90 14099.14 4598.41 15593.75 17093.16 25697.46 20787.50 21398.41 26595.63 12894.03 22796.50 291
tfpn_ndepth95.53 16094.90 17097.39 16798.96 10195.88 14299.05 6095.27 34093.80 16996.95 12296.93 26485.53 24999.40 14291.54 23896.10 19796.89 237
thisisatest051595.61 15394.89 17197.76 12898.15 16695.15 17096.77 31394.41 35092.95 21397.18 11297.43 21184.78 26299.45 14094.63 15397.73 14898.68 157
test-LLR95.10 19294.87 17295.80 26296.77 24789.70 30596.91 30295.21 34195.11 11494.83 19095.72 31187.71 20598.97 19293.06 19498.50 11598.72 153
COLMAP_ROBcopyleft93.27 1295.33 18194.87 17296.71 19799.29 6093.24 26098.58 15698.11 21389.92 29693.57 24599.10 5186.37 22999.79 7490.78 25098.10 13397.09 219
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
conf0.0195.56 15894.84 17497.72 13198.90 10495.93 13099.17 3695.70 33193.42 19196.50 15697.16 22886.12 23399.22 15890.51 25696.06 19898.02 187
conf0.00295.56 15894.84 17497.72 13198.90 10495.93 13099.17 3695.70 33193.42 19196.50 15697.16 22886.12 23399.22 15890.51 25696.06 19898.02 187
thresconf0.0295.50 16194.84 17497.51 15398.90 10495.93 13099.17 3695.70 33193.42 19196.50 15697.16 22886.12 23399.22 15890.51 25696.06 19897.37 210
tfpn_n40095.50 16194.84 17497.51 15398.90 10495.93 13099.17 3695.70 33193.42 19196.50 15697.16 22886.12 23399.22 15890.51 25696.06 19897.37 210
tfpnconf95.50 16194.84 17497.51 15398.90 10495.93 13099.17 3695.70 33193.42 19196.50 15697.16 22886.12 23399.22 15890.51 25696.06 19897.37 210
tfpnview1195.50 16194.84 17497.51 15398.90 10495.93 13099.17 3695.70 33193.42 19196.50 15697.16 22886.12 23399.22 15890.51 25696.06 19897.37 210
thres600view795.49 16594.77 18097.67 13998.98 9795.02 17498.85 9696.90 30595.38 9396.63 14096.90 26684.29 27399.59 11488.65 29796.33 18298.40 172
DU-MVS95.42 17194.76 18197.40 16496.53 25996.97 8098.66 14798.99 2895.43 9093.88 23797.69 19188.57 17998.31 27695.81 11887.25 31596.92 229
tfpn11195.43 16994.74 18297.51 15398.98 9794.92 18298.87 8896.90 30595.38 9396.61 14196.88 26984.29 27399.59 11488.43 29896.32 18398.02 187
CostFormer94.95 20094.73 18395.60 26897.28 21889.06 31597.53 27096.89 30989.66 30496.82 13396.72 27886.05 24198.95 19995.53 13096.13 19698.79 151
conf200view1195.40 17494.70 18497.50 15898.98 9794.92 18298.87 8896.90 30595.38 9396.61 14196.88 26984.29 27399.56 12388.11 30496.29 18598.02 187
thres100view90095.38 17594.70 18497.41 16298.98 9794.92 18298.87 8896.90 30595.38 9396.61 14196.88 26984.29 27399.56 12388.11 30496.29 18597.76 195
AllTest95.24 18694.65 18696.99 18299.25 6993.21 26198.59 15498.18 19491.36 26593.52 24798.77 9384.67 26399.72 9189.70 27797.87 14098.02 187
tfpn200view995.32 18294.62 18797.43 16198.94 10294.98 17898.68 14296.93 30395.33 10196.55 14796.53 28584.23 27899.56 12388.11 30496.29 18597.76 195
thres40095.38 17594.62 18797.65 14298.94 10294.98 17898.68 14296.93 30395.33 10196.55 14796.53 28584.23 27899.56 12388.11 30496.29 18598.40 172
thres20095.25 18594.57 18997.28 16898.81 11994.92 18298.20 20597.11 28995.24 10896.54 14996.22 29884.58 26599.53 13087.93 30996.50 17497.39 208
TAPA-MVS93.98 795.35 17994.56 19097.74 13099.13 8494.83 20098.33 19098.64 11786.62 32496.29 16898.61 10794.00 7599.29 15280.00 33799.41 7999.09 128
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
VDDNet95.36 17894.53 19197.86 12098.10 16995.13 17198.85 9697.75 23990.46 28398.36 5799.39 973.27 34299.64 10797.98 2996.58 17098.81 150
Anonymous20240521195.28 18494.49 19297.67 13999.00 9393.75 24898.70 13697.04 29390.66 28096.49 16298.80 8978.13 32099.83 4796.21 10695.36 21199.44 87
TranMVSNet+NR-MVSNet95.14 19194.48 19397.11 17796.45 26496.36 10999.03 6499.03 2495.04 11893.58 24497.93 17188.27 18798.03 29294.13 16986.90 32096.95 228
EPMVS94.99 19694.48 19396.52 22797.22 22291.75 28097.23 29091.66 36194.11 15097.28 10996.81 27585.70 24798.84 21193.04 19697.28 15698.97 140
WR-MVS_H95.05 19494.46 19596.81 19396.86 24495.82 14499.24 2199.24 1093.87 16592.53 27496.84 27490.37 13498.24 28293.24 18987.93 30596.38 297
WR-MVS95.15 19094.46 19597.22 16996.67 25596.45 10598.21 20498.81 6594.15 14993.16 25697.69 19187.51 21198.30 27895.29 13988.62 29996.90 236
ADS-MVSNet95.00 19594.45 19796.63 21198.00 17491.91 27696.04 32797.74 24090.15 28896.47 16396.64 28287.89 19998.96 19590.08 26797.06 15899.02 135
XXY-MVS95.20 18994.45 19797.46 15996.75 25096.56 10098.86 9598.65 11693.30 20293.27 25398.27 14584.85 26198.87 20894.82 15091.26 26896.96 226
ADS-MVSNet294.58 22794.40 19995.11 28998.00 17488.74 31996.04 32797.30 28190.15 28896.47 16396.64 28287.89 19997.56 31290.08 26797.06 15899.02 135
tpmvs94.60 22494.36 20095.33 28497.46 20688.60 32296.88 30897.68 24191.29 27193.80 24196.42 29188.58 17899.24 15591.06 24696.04 20498.17 183
DWT-MVSNet_test94.82 20894.36 20096.20 24897.35 21590.79 29298.34 18996.57 32092.91 21595.33 18196.44 29082.00 29699.12 17294.52 15995.78 20898.70 155
CP-MVSNet94.94 20294.30 20296.83 19296.72 25295.56 15299.11 5298.95 3393.89 16392.42 27997.90 17387.19 21698.12 28694.32 16488.21 30296.82 247
FMVSNet394.97 19994.26 20397.11 17798.18 16396.62 9498.56 16198.26 18193.67 18294.09 22997.10 23784.25 27798.01 29392.08 22192.14 25496.70 260
Anonymous2024052995.10 19294.22 20497.75 12999.01 9294.26 23498.87 8898.83 6085.79 33396.64 13998.97 6978.73 31799.85 4396.27 10394.89 21499.12 125
v1neww94.83 20594.22 20496.68 20396.39 26794.85 18898.87 8898.11 21392.45 23194.45 20097.06 24488.82 16798.54 23492.93 20088.91 29296.65 271
v7new94.83 20594.22 20496.68 20396.39 26794.85 18898.87 8898.11 21392.45 23194.45 20097.06 24488.82 16798.54 23492.93 20088.91 29296.65 271
v694.83 20594.21 20796.69 20096.36 27194.85 18898.87 8898.11 21392.46 22694.44 20697.05 24888.76 17398.57 23292.95 19988.92 29196.65 271
TR-MVS94.94 20294.20 20897.17 17397.75 18894.14 23797.59 26797.02 29592.28 24395.75 17797.64 19783.88 28698.96 19589.77 27396.15 19598.40 172
VPNet94.99 19694.19 20997.40 16497.16 22896.57 9998.71 13398.97 2995.67 7994.84 18898.24 14880.36 31098.67 22496.46 9787.32 31396.96 226
NR-MVSNet94.98 19894.16 21097.44 16096.53 25997.22 7498.74 12798.95 3394.96 12389.25 31197.69 19189.32 14698.18 28494.59 15787.40 31296.92 229
CR-MVSNet94.76 21194.15 21196.59 21797.00 23493.43 25594.96 34097.56 24792.46 22696.93 12596.24 29488.15 19097.88 30487.38 31196.65 16898.46 169
V4294.78 21094.14 21296.70 19996.33 27895.22 16798.97 7298.09 22192.32 24194.31 21497.06 24488.39 18598.55 23392.90 20388.87 29496.34 299
EU-MVSNet93.66 26394.14 21292.25 32695.96 30183.38 34198.52 16698.12 20894.69 13192.61 27198.13 15487.36 21596.39 33991.82 23090.00 27596.98 225
XVG-ACMP-BASELINE94.54 22994.14 21295.75 26596.55 25891.65 28298.11 22098.44 15194.96 12394.22 22297.90 17379.18 31699.11 17694.05 17293.85 23196.48 293
divwei89l23v2f11294.76 21194.12 21596.67 20696.28 28494.85 18898.69 13898.12 20892.44 23394.29 21796.94 26088.85 16498.48 24592.67 20888.79 29896.67 266
v114194.75 21394.11 21696.67 20696.27 28694.86 18798.69 13898.12 20892.43 23494.31 21496.94 26088.78 17298.48 24592.63 21088.85 29696.67 266
v194.75 21394.11 21696.69 20096.27 28694.87 18698.69 13898.12 20892.43 23494.32 21396.94 26088.71 17698.54 23492.66 20988.84 29796.67 266
v794.69 21794.04 21896.62 21396.41 26694.79 20898.78 11898.13 20591.89 25094.30 21697.16 22888.13 19298.45 25291.96 22889.65 27896.61 276
v2v48294.69 21794.03 21996.65 20896.17 29194.79 20898.67 14598.08 22292.72 22094.00 23497.16 22887.69 20898.45 25292.91 20288.87 29496.72 256
GA-MVS94.81 20994.03 21997.14 17497.15 22993.86 24396.76 31497.58 24694.00 15794.76 19397.04 24980.91 30398.48 24591.79 23196.25 19199.09 128
OurMVSNet-221017-094.21 24394.00 22194.85 29695.60 31489.22 31398.89 8397.43 27095.29 10492.18 28498.52 11782.86 29398.59 23093.46 18491.76 26196.74 253
PAPM94.95 20094.00 22197.78 12697.04 23395.65 14896.03 32998.25 18291.23 27494.19 22497.80 18591.27 12098.86 21082.61 33297.61 15198.84 149
pmmvs494.69 21793.99 22396.81 19395.74 30995.94 12797.40 27697.67 24290.42 28593.37 25197.59 20089.08 15398.20 28392.97 19891.67 26296.30 301
PS-CasMVS94.67 22193.99 22396.71 19796.68 25495.26 16599.13 4999.03 2493.68 18092.33 28097.95 16885.35 25398.10 28793.59 18288.16 30496.79 248
ACMH92.88 1694.55 22893.95 22596.34 24297.63 19393.26 25998.81 10898.49 14693.43 19089.74 30698.53 11481.91 29799.08 18193.69 17893.30 24496.70 260
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
MVP-Stereo94.28 24293.92 22695.35 28394.95 32892.60 26997.97 23397.65 24391.61 25690.68 30097.09 23986.32 23098.42 25889.70 27799.34 8495.02 326
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
v114494.59 22693.92 22696.60 21696.21 28894.78 21098.59 15498.14 20491.86 25394.21 22397.02 25187.97 19698.41 26591.72 23489.57 27996.61 276
dp94.15 25093.90 22894.90 29497.31 21786.82 33696.97 29897.19 28891.22 27596.02 17496.61 28485.51 25099.02 19090.00 27194.30 21698.85 147
LTVRE_ROB92.95 1594.60 22493.90 22896.68 20397.41 21394.42 22598.52 16698.59 12091.69 25591.21 29398.35 13284.87 26099.04 18791.06 24693.44 24196.60 278
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
cascas94.63 22393.86 23096.93 18896.91 24194.27 23396.00 33098.51 13785.55 33494.54 19696.23 29684.20 28098.87 20895.80 12096.98 16197.66 202
IterMVS94.09 25393.85 23194.80 29997.99 17690.35 30097.18 29398.12 20893.68 18092.46 27897.34 21784.05 28297.41 31592.51 21591.33 26596.62 275
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Baseline_NR-MVSNet94.35 23793.81 23295.96 25596.20 28994.05 23998.61 15296.67 31791.44 26193.85 23997.60 19988.57 17998.14 28594.39 16186.93 31895.68 316
tpm94.13 25193.80 23395.12 28896.50 26187.91 33097.44 27395.89 33092.62 22296.37 16796.30 29384.13 28198.30 27893.24 18991.66 26399.14 123
GBi-Net94.49 23093.80 23396.56 22298.21 15895.00 17598.82 10298.18 19492.46 22694.09 22997.07 24181.16 30097.95 29692.08 22192.14 25496.72 256
test194.49 23093.80 23396.56 22298.21 15895.00 17598.82 10298.18 19492.46 22694.09 22997.07 24181.16 30097.95 29692.08 22192.14 25496.72 256
v894.47 23293.77 23696.57 22196.36 27194.83 20099.05 6098.19 19191.92 24993.16 25696.97 25688.82 16798.48 24591.69 23587.79 30896.39 296
ACMH+92.99 1494.30 23993.77 23695.88 25997.81 18692.04 27598.71 13398.37 16293.99 15890.60 30198.47 12080.86 30599.05 18392.75 20792.40 25396.55 285
v14894.29 24093.76 23895.91 25796.10 29592.93 26598.58 15697.97 23092.59 22493.47 25096.95 25888.53 18298.32 27492.56 21287.06 31796.49 292
tpm294.19 24593.76 23895.46 27397.23 22189.04 31697.31 28796.85 31287.08 32396.21 16996.79 27683.75 29098.74 21992.43 21796.23 19298.59 164
PEN-MVS94.42 23493.73 24096.49 22996.28 28494.84 19799.17 3699.00 2693.51 18792.23 28297.83 18286.10 24097.90 30092.55 21386.92 31996.74 253
v14419294.39 23693.70 24196.48 23096.06 29794.35 22998.58 15698.16 20191.45 26094.33 21297.02 25187.50 21398.45 25291.08 24589.11 28696.63 274
TESTMET0.1,194.18 24793.69 24295.63 26796.92 23989.12 31496.91 30294.78 34693.17 20494.88 18796.45 28978.52 31898.92 20193.09 19398.50 11598.85 147
Patchmatch-test94.42 23493.68 24396.63 21197.60 19691.76 27994.83 34497.49 26589.45 30894.14 22797.10 23788.99 15498.83 21385.37 32698.13 13299.29 103
MS-PatchMatch93.84 26193.63 24494.46 30996.18 29089.45 30997.76 25598.27 17792.23 24492.13 28597.49 20579.50 31398.69 22089.75 27599.38 8295.25 321
DI_MVS_plusplus_test94.74 21593.62 24598.09 10895.34 32395.92 13798.09 22397.34 27794.66 13585.89 32595.91 30580.49 30999.38 14596.66 9098.22 12898.97 140
FMVSNet294.47 23293.61 24697.04 18098.21 15896.43 10698.79 11698.27 17792.46 22693.50 24997.09 23981.16 30098.00 29491.09 24491.93 25896.70 260
test_normal94.72 21693.59 24798.11 10795.30 32495.95 12697.91 23997.39 27594.64 13685.70 32895.88 30680.52 30899.36 14696.69 8998.30 12599.01 138
v119294.32 23893.58 24896.53 22696.10 29594.45 22498.50 17198.17 19991.54 25894.19 22497.06 24486.95 22198.43 25790.14 26589.57 27996.70 260
v1094.29 24093.55 24996.51 22896.39 26794.80 20598.99 6898.19 19191.35 26793.02 26296.99 25488.09 19398.41 26590.50 26288.41 30196.33 300
MVS94.67 22193.54 25098.08 10996.88 24396.56 10098.19 20998.50 14278.05 35292.69 26998.02 16191.07 12499.63 11090.09 26698.36 12298.04 186
v5294.18 24793.52 25196.13 25195.95 30294.29 23199.23 2398.21 18691.42 26292.84 26596.89 26787.85 20298.53 24091.51 23987.81 30695.57 319
V494.18 24793.52 25196.13 25195.89 30494.31 23099.23 2398.22 18591.42 26292.82 26696.89 26787.93 19898.52 24191.51 23987.81 30695.58 318
test-mter94.08 25493.51 25395.80 26296.77 24789.70 30596.91 30295.21 34192.89 21694.83 19095.72 31177.69 32398.97 19293.06 19498.50 11598.72 153
test0.0.03 194.08 25493.51 25395.80 26295.53 31792.89 26697.38 27895.97 32795.11 11492.51 27696.66 28087.71 20596.94 32187.03 31493.67 23397.57 203
v192192094.20 24493.47 25596.40 23795.98 30094.08 23898.52 16698.15 20291.33 26894.25 22097.20 22786.41 22898.42 25890.04 27089.39 28496.69 265
v7n94.19 24593.43 25696.47 23195.90 30394.38 22899.26 1898.34 16591.99 24792.76 26897.13 23688.31 18698.52 24189.48 28287.70 30996.52 288
PCF-MVS93.45 1194.68 22093.43 25698.42 8898.62 13696.77 8995.48 33698.20 18984.63 33993.34 25298.32 13888.55 18199.81 5584.80 32898.96 9498.68 157
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
tpmp4_e2393.91 26093.42 25895.38 28197.62 19488.59 32397.52 27197.34 27787.94 31994.17 22696.79 27682.91 29299.05 18390.62 25495.91 20598.50 167
our_test_393.65 26593.30 25994.69 30195.45 32089.68 30796.91 30297.65 24391.97 24891.66 29096.88 26989.67 14197.93 29988.02 30891.49 26496.48 293
v124094.06 25693.29 26096.34 24296.03 29993.90 24298.44 17898.17 19991.18 27694.13 22897.01 25386.05 24198.42 25889.13 28789.50 28296.70 260
Anonymous2023121194.10 25293.26 26196.61 21499.11 8694.28 23299.01 6698.88 4886.43 32692.81 26797.57 20281.66 29998.68 22394.83 14989.02 28996.88 239
DTE-MVSNet93.98 25893.26 26196.14 25096.06 29794.39 22799.20 3398.86 5493.06 20791.78 28897.81 18485.87 24497.58 31190.53 25586.17 32496.46 295
v74893.75 26293.06 26395.82 26195.73 31092.64 26899.25 2098.24 18491.60 25792.22 28396.52 28787.60 21098.46 25090.64 25385.72 32796.36 298
pm-mvs193.94 25993.06 26396.59 21796.49 26295.16 16898.95 7498.03 22992.32 24191.08 29597.84 17984.54 27098.41 26592.16 21986.13 32696.19 304
pmmvs593.65 26592.97 26595.68 26695.49 31892.37 27098.20 20597.28 28389.66 30492.58 27297.26 22282.14 29598.09 28993.18 19290.95 26996.58 280
SixPastTwentyTwo93.34 26992.86 26694.75 30095.67 31289.41 31198.75 12396.67 31793.89 16390.15 30498.25 14780.87 30498.27 28190.90 24990.64 27096.57 282
tpm cat193.36 26792.80 26795.07 29097.58 19887.97 32996.76 31497.86 23582.17 34693.53 24696.04 30386.13 23299.13 17189.24 28595.87 20698.10 185
LF4IMVS93.14 27692.79 26894.20 31295.88 30588.67 32197.66 26397.07 29193.81 16891.71 28997.65 19577.96 32298.81 21591.47 24191.92 25995.12 322
USDC93.33 27092.71 26995.21 28596.83 24690.83 29196.91 30297.50 25993.84 16690.72 29998.14 15377.69 32398.82 21489.51 28193.21 24795.97 309
tfpnnormal93.66 26392.70 27096.55 22596.94 23895.94 12798.97 7299.19 1591.04 27791.38 29297.34 21784.94 25998.61 22785.45 32589.02 28995.11 323
ppachtmachnet_test93.22 27392.63 27194.97 29295.45 32090.84 29096.88 30897.88 23490.60 28192.08 28697.26 22288.08 19497.86 30685.12 32790.33 27296.22 302
DSMNet-mixed92.52 28192.58 27292.33 32594.15 33582.65 34498.30 19794.26 35389.08 31392.65 27095.73 30985.01 25895.76 34186.24 31897.76 14698.59 164
JIA-IIPM93.35 26892.49 27395.92 25696.48 26390.65 29695.01 33996.96 30185.93 33196.08 17187.33 35287.70 20798.78 21891.35 24295.58 20998.34 179
testgi93.06 27792.45 27494.88 29596.43 26589.90 30298.75 12397.54 25295.60 8291.63 29197.91 17274.46 33997.02 32086.10 31993.67 23397.72 199
Patchmtry93.22 27392.35 27595.84 26096.77 24793.09 26494.66 34697.56 24787.37 32292.90 26496.24 29488.15 19097.90 30087.37 31290.10 27496.53 287
X-MVStestdata94.06 25692.30 27699.34 1599.70 1698.35 2699.29 1498.88 4897.40 1598.46 5043.50 36595.90 3199.89 2997.85 3699.74 3499.78 8
MIMVSNet93.26 27292.21 27796.41 23697.73 19093.13 26395.65 33597.03 29491.27 27394.04 23296.06 30275.33 33397.19 31886.56 31696.23 19298.92 146
FMVSNet193.19 27592.07 27896.56 22297.54 20195.00 17598.82 10298.18 19490.38 28692.27 28197.07 24173.68 34197.95 29689.36 28491.30 26696.72 256
PatchT93.06 27791.97 27996.35 24096.69 25392.67 26794.48 34797.08 29086.62 32497.08 11592.23 34787.94 19797.90 30078.89 34196.69 16698.49 168
IB-MVS91.98 1793.27 27191.97 27997.19 17197.47 20593.41 25797.09 29695.99 32693.32 20092.47 27795.73 30978.06 32199.53 13094.59 15782.98 33298.62 163
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
K. test v392.55 28091.91 28194.48 30795.64 31389.24 31299.07 5994.88 34594.04 15486.78 32197.59 20077.64 32697.64 30992.08 22189.43 28396.57 282
TinyColmap92.31 28391.53 28294.65 30396.92 23989.75 30496.92 30096.68 31690.45 28489.62 30797.85 17876.06 33198.81 21586.74 31592.51 25295.41 320
TransMVSNet (Re)92.67 27991.51 28396.15 24996.58 25794.65 21398.90 7996.73 31390.86 27989.46 30997.86 17685.62 24898.09 28986.45 31781.12 33795.71 315
RPMNet92.52 28191.17 28496.59 21797.00 23493.43 25594.96 34097.26 28582.27 34596.93 12592.12 34886.98 22097.88 30476.32 34696.65 16898.46 169
Anonymous2023120691.66 29791.10 28593.33 31994.02 33787.35 33398.58 15697.26 28590.48 28290.16 30396.31 29283.83 28896.53 33779.36 33989.90 27696.12 305
v1892.10 28690.97 28695.50 27096.34 27494.85 18898.82 10297.52 25389.99 29285.31 33293.26 33088.90 16196.92 32288.82 29379.77 34194.73 329
v1792.08 28790.94 28795.48 27296.34 27494.83 20098.81 10897.52 25389.95 29485.32 33093.24 33188.91 16096.91 32388.76 29479.63 34294.71 331
v1692.08 28790.94 28795.49 27196.38 27094.84 19798.81 10897.51 25689.94 29585.25 33393.28 32988.86 16296.91 32388.70 29579.78 34094.72 330
FMVSNet591.81 29590.92 28994.49 30697.21 22392.09 27398.00 23197.55 25189.31 31190.86 29895.61 31474.48 33895.32 34385.57 32389.70 27796.07 307
Patchmatch-RL test91.49 29890.85 29093.41 31891.37 34584.40 33892.81 35295.93 32991.87 25287.25 31994.87 31988.99 15496.53 33792.54 21482.00 33499.30 101
v1591.94 28990.77 29195.43 27796.31 28294.83 20098.77 11997.50 25989.92 29685.13 33493.08 33488.76 17396.86 32588.40 29979.10 34494.61 335
V1491.93 29090.76 29295.42 28096.33 27894.81 20498.77 11997.51 25689.86 29885.09 33593.13 33288.80 17196.83 32788.32 30079.06 34694.60 336
V991.91 29190.73 29395.45 27496.32 28194.80 20598.77 11997.50 25989.81 29985.03 33793.08 33488.76 17396.86 32588.24 30179.03 34794.69 332
v1291.89 29290.70 29495.43 27796.31 28294.80 20598.76 12297.50 25989.76 30084.95 33893.00 33788.82 16796.82 32988.23 30279.00 34894.68 334
v1391.88 29390.69 29595.43 27796.33 27894.78 21098.75 12397.50 25989.68 30384.93 33992.98 33888.84 16596.83 32788.14 30379.09 34594.69 332
v1191.85 29490.68 29695.36 28296.34 27494.74 21298.80 11197.43 27089.60 30685.09 33593.03 33688.53 18296.75 33087.37 31279.96 33994.58 337
pmmvs691.77 29690.63 29795.17 28794.69 33391.24 28798.67 14597.92 23286.14 32889.62 30797.56 20475.79 33298.34 27290.75 25184.56 33195.94 310
gg-mvs-nofinetune92.21 28490.58 29897.13 17596.75 25095.09 17295.85 33289.40 36485.43 33594.50 19881.98 35680.80 30698.40 27192.16 21998.33 12397.88 193
test20.0390.89 30590.38 29992.43 32493.48 33888.14 32898.33 19097.56 24793.40 19787.96 31796.71 27980.69 30794.13 34779.15 34086.17 32495.01 327
Test492.21 28490.34 30097.82 12492.83 34195.87 14397.94 23598.05 22894.50 14182.12 34494.48 32259.54 35798.54 23495.39 13498.22 12899.06 133
test_040291.32 29990.27 30194.48 30796.60 25691.12 28898.50 17197.22 28786.10 32988.30 31696.98 25577.65 32597.99 29578.13 34392.94 24994.34 338
EG-PatchMatch MVS91.13 30190.12 30294.17 31494.73 33289.00 31798.13 21797.81 23689.22 31285.32 33096.46 28867.71 35098.42 25887.89 31093.82 23295.08 324
PVSNet_088.72 1991.28 30090.03 30395.00 29197.99 17687.29 33494.84 34398.50 14292.06 24689.86 30595.19 31579.81 31299.39 14492.27 21869.79 35598.33 180
LP91.12 30289.99 30494.53 30596.35 27388.70 32093.86 35197.35 27684.88 33790.98 29694.77 32084.40 27297.43 31475.41 34891.89 26097.47 204
UnsupCasMVSNet_eth90.99 30489.92 30594.19 31394.08 33689.83 30397.13 29598.67 10993.69 17885.83 32796.19 29975.15 33496.74 33189.14 28679.41 34396.00 308
TDRefinement91.06 30389.68 30695.21 28585.35 35691.49 28398.51 17097.07 29191.47 25988.83 31497.84 17977.31 32799.09 18092.79 20677.98 34995.04 325
CMPMVSbinary66.06 2189.70 31289.67 30789.78 33093.19 33976.56 35097.00 29798.35 16480.97 34881.57 34597.75 18774.75 33798.61 22789.85 27293.63 23594.17 340
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
YYNet190.70 30789.39 30894.62 30494.79 33190.65 29697.20 29197.46 26687.54 32172.54 35495.74 30886.51 22696.66 33586.00 32086.76 32296.54 286
MDA-MVSNet_test_wron90.71 30689.38 30994.68 30294.83 33090.78 29397.19 29297.46 26687.60 32072.41 35595.72 31186.51 22696.71 33485.92 32186.80 32196.56 284
testpf88.74 31789.09 31087.69 33495.78 30883.16 34384.05 36294.13 35785.22 33690.30 30294.39 32474.92 33695.80 34089.77 27393.28 24684.10 357
testus88.91 31689.08 31188.40 33391.39 34476.05 35196.56 32096.48 32189.38 31089.39 31095.17 31770.94 34593.56 35077.04 34595.41 21095.61 317
pmmvs-eth3d90.36 30989.05 31294.32 31191.10 34692.12 27297.63 26696.95 30288.86 31484.91 34093.13 33278.32 31996.74 33188.70 29581.81 33694.09 342
new_pmnet90.06 31089.00 31393.22 32294.18 33488.32 32796.42 32596.89 30986.19 32785.67 32993.62 32777.18 32897.10 31981.61 33489.29 28594.23 339
test235688.68 31888.61 31488.87 33289.90 35078.23 34895.11 33896.66 31988.66 31689.06 31294.33 32673.14 34392.56 35475.56 34795.11 21395.81 313
testing_290.61 30888.50 31596.95 18690.08 34995.57 15197.69 26098.06 22593.02 20976.55 35092.48 34561.18 35698.44 25595.45 13391.98 25796.84 244
MVS-HIRNet89.46 31488.40 31692.64 32397.58 19882.15 34594.16 35093.05 36075.73 35490.90 29782.52 35579.42 31498.33 27383.53 33098.68 10597.43 205
MDA-MVSNet-bldmvs89.97 31188.35 31794.83 29895.21 32591.34 28497.64 26497.51 25688.36 31771.17 35696.13 30179.22 31596.63 33683.65 32986.27 32396.52 288
MIMVSNet189.67 31388.28 31893.82 31592.81 34291.08 28998.01 22997.45 26887.95 31887.90 31895.87 30767.63 35194.56 34678.73 34288.18 30395.83 312
N_pmnet87.12 32287.77 31985.17 34195.46 31961.92 36497.37 28070.66 37285.83 33288.73 31596.04 30385.33 25597.76 30780.02 33690.48 27195.84 311
new-patchmatchnet88.50 31987.45 32091.67 32890.31 34885.89 33797.16 29497.33 28089.47 30783.63 34292.77 34276.38 32995.06 34582.70 33177.29 35094.06 343
OpenMVS_ROBcopyleft86.42 2089.00 31587.43 32193.69 31693.08 34089.42 31097.91 23996.89 30978.58 35185.86 32694.69 32169.48 34798.29 28077.13 34493.29 24593.36 347
PM-MVS87.77 32086.55 32291.40 32991.03 34783.36 34296.92 30095.18 34391.28 27286.48 32493.42 32853.27 35896.74 33189.43 28381.97 33594.11 341
test123567886.26 32485.81 32387.62 33586.97 35475.00 35596.55 32296.32 32486.08 33081.32 34692.98 33873.10 34492.05 35571.64 35187.32 31395.81 313
UnsupCasMVSNet_bld87.17 32185.12 32493.31 32091.94 34388.77 31894.92 34298.30 17484.30 34082.30 34390.04 34963.96 35597.25 31785.85 32274.47 35493.93 345
pmmvs386.67 32384.86 32592.11 32788.16 35187.19 33596.63 31794.75 34779.88 35087.22 32092.75 34366.56 35295.20 34481.24 33576.56 35293.96 344
111184.94 32584.30 32686.86 33687.59 35275.10 35396.63 31796.43 32282.53 34380.75 34792.91 34068.94 34893.79 34868.24 35484.66 33091.70 349
test1235683.47 32683.37 32783.78 34284.43 35770.09 36095.12 33795.60 33882.98 34178.89 34992.43 34664.99 35391.41 35770.36 35285.55 32989.82 351
testmv78.74 32777.35 32882.89 34478.16 36569.30 36195.87 33194.65 34881.11 34770.98 35787.11 35346.31 35990.42 35865.28 35776.72 35188.95 352
FPMVS77.62 33177.14 32979.05 34679.25 36260.97 36595.79 33395.94 32865.96 35667.93 35894.40 32337.73 36488.88 36068.83 35388.46 30087.29 353
Gipumacopyleft78.40 32976.75 33083.38 34395.54 31680.43 34779.42 36397.40 27364.67 35773.46 35380.82 35845.65 36193.14 35266.32 35687.43 31176.56 362
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
.test124573.05 33376.31 33163.27 35487.59 35275.10 35396.63 31796.43 32282.53 34380.75 34792.91 34068.94 34893.79 34868.24 35412.72 36620.91 366
LCM-MVSNet78.70 32876.24 33286.08 33877.26 36671.99 35894.34 34896.72 31461.62 35976.53 35189.33 35033.91 36792.78 35381.85 33374.60 35393.46 346
PMMVS277.95 33075.44 33385.46 33982.54 35874.95 35694.23 34993.08 35972.80 35574.68 35287.38 35136.36 36591.56 35673.95 34963.94 35689.87 350
no-one74.41 33270.76 33485.35 34079.88 36176.83 34994.68 34594.22 35480.33 34963.81 35979.73 35935.45 36693.36 35171.78 35036.99 36385.86 356
tmp_tt68.90 33566.97 33574.68 35050.78 37159.95 36687.13 35883.47 37038.80 36562.21 36096.23 29664.70 35476.91 36788.91 29230.49 36487.19 354
ANet_high69.08 33465.37 33680.22 34565.99 36971.96 35990.91 35690.09 36382.62 34249.93 36578.39 36029.36 36881.75 36362.49 36038.52 36286.95 355
PNet_i23d67.70 33665.07 33775.60 34878.61 36359.61 36789.14 35788.24 36661.83 35852.37 36380.89 35718.91 36984.91 36262.70 35952.93 35882.28 358
E-PMN64.94 33864.25 33867.02 35282.28 35959.36 36891.83 35585.63 36852.69 36260.22 36177.28 36141.06 36380.12 36546.15 36341.14 36061.57 364
PMVScopyleft61.03 2365.95 33763.57 33973.09 35157.90 37051.22 37085.05 36193.93 35854.45 36144.32 36683.57 35413.22 37089.15 35958.68 36181.00 33878.91 361
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
EMVS64.07 33963.26 34066.53 35381.73 36058.81 36991.85 35484.75 36951.93 36459.09 36275.13 36243.32 36279.09 36642.03 36439.47 36161.69 363
MVEpermissive62.14 2263.28 34159.38 34174.99 34974.33 36765.47 36385.55 36080.50 37152.02 36351.10 36475.00 36310.91 37480.50 36451.60 36253.40 35778.99 360
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
wuykxyi23d63.73 34058.86 34278.35 34767.62 36867.90 36286.56 35987.81 36758.26 36042.49 36770.28 36411.55 37285.05 36163.66 35841.50 35982.11 359
v1.041.12 34254.83 3430.00 35999.63 220.00 3740.00 36598.84 5696.40 5899.27 899.31 230.00 3760.00 3710.00 3680.00 3690.00 369
pcd1.5k->3k39.42 34341.78 34432.35 35596.17 2910.00 3740.00 36598.54 1300.00 3690.00 3710.00 37187.78 2040.00 3710.00 36893.56 23797.06 220
cdsmvs_eth3d_5k23.98 34531.98 3450.00 3590.00 3740.00 3740.00 36598.59 1200.00 3690.00 37198.61 10790.60 1320.00 3710.00 3680.00 3690.00 369
wuyk23d30.17 34430.18 34630.16 35678.61 36343.29 37166.79 36414.21 37317.31 36614.82 37011.93 37011.55 37241.43 36837.08 36519.30 3655.76 368
testmvs21.48 34624.95 34711.09 35814.89 3726.47 37396.56 3209.87 3747.55 36717.93 36839.02 3669.43 3755.90 37016.56 36712.72 36620.91 366
test12320.95 34723.72 34812.64 35713.54 3738.19 37296.55 3226.13 3757.48 36816.74 36937.98 36712.97 3716.05 36916.69 3665.43 36823.68 365
ab-mvs-re8.20 34810.94 3490.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 37198.43 1220.00 3760.00 3710.00 3680.00 3690.00 369
pcd_1.5k_mvsjas7.88 34910.50 3500.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 37194.51 630.00 3710.00 3680.00 3690.00 369
sosnet-low-res0.00 3500.00 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 3710.00 3760.00 3710.00 3680.00 3690.00 369
sosnet0.00 3500.00 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 3710.00 3760.00 3710.00 3680.00 3690.00 369
uncertanet0.00 3500.00 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 3710.00 3760.00 3710.00 3680.00 3690.00 369
Regformer0.00 3500.00 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 3710.00 3760.00 3710.00 3680.00 3690.00 369
uanet0.00 3500.00 3510.00 3590.00 3740.00 3740.00 3650.00 3760.00 3690.00 3710.00 3710.00 3760.00 3710.00 3680.00 3690.00 369
GSMVS99.20 111
test_part299.63 2299.18 299.27 8
test_part10.00 3590.00 3740.00 36598.84 560.00 3760.00 3710.00 3680.00 3690.00 369
sam_mvs189.45 14399.20 111
sam_mvs88.99 154
semantic-postprocess94.85 29697.98 17890.56 29898.11 21393.75 17092.58 27297.48 20683.91 28597.41 31592.48 21691.30 26696.58 280
ambc89.49 33186.66 35575.78 35292.66 35396.72 31486.55 32392.50 34446.01 36097.90 30090.32 26382.09 33394.80 328
MTGPAbinary98.74 84
test_post196.68 31630.43 36987.85 20298.69 22092.59 211
test_post31.83 36888.83 16698.91 202
patchmatchnet-post95.10 31889.42 14498.89 206
GG-mvs-BLEND96.59 21796.34 27494.98 17896.51 32488.58 36593.10 26194.34 32580.34 31198.05 29189.53 28096.99 16096.74 253
MTMP98.89 8394.14 356
gm-plane-assit95.88 30587.47 33289.74 30296.94 26099.19 16693.32 188
test9_res96.39 10299.57 5899.69 38
TEST999.31 5298.50 1597.92 23698.73 8992.63 22197.74 8998.68 10096.20 1499.80 62
test_899.29 6098.44 1797.89 24498.72 9192.98 21197.70 9298.66 10396.20 1499.80 62
agg_prior295.87 11799.57 5899.68 44
agg_prior99.30 5798.38 2098.72 9197.57 10499.81 55
TestCases96.99 18299.25 6993.21 26198.18 19491.36 26593.52 24798.77 9384.67 26399.72 9189.70 27797.87 14098.02 187
test_prior498.01 4597.86 247
test_prior297.80 25296.12 6597.89 8398.69 9895.96 2796.89 7699.60 52
test_prior99.19 3199.31 5298.22 3498.84 5699.70 9699.65 53
旧先验297.57 26991.30 27098.67 4199.80 6295.70 126
新几何297.64 264
新几何199.16 3899.34 4498.01 4598.69 9990.06 29198.13 6298.95 7694.60 6199.89 2991.97 22799.47 7299.59 64
旧先验199.29 6097.48 6398.70 9899.09 5595.56 3799.47 7299.61 59
无先验97.58 26898.72 9191.38 26499.87 3893.36 18699.60 62
原ACMM297.67 262
原ACMM198.65 6899.32 5096.62 9498.67 10993.27 20397.81 8598.97 6995.18 5099.83 4793.84 17599.46 7599.50 74
test22299.23 7597.17 7697.40 27698.66 11288.68 31598.05 6698.96 7494.14 7299.53 6899.61 59
testdata299.89 2991.65 236
segment_acmp96.85 4
testdata98.26 9699.20 7995.36 16098.68 10291.89 25098.60 4699.10 5194.44 6899.82 5394.27 16699.44 7799.58 66
testdata197.32 28696.34 59
test1299.18 3599.16 8198.19 3698.53 13398.07 6595.13 5299.72 9199.56 6499.63 58
plane_prior797.42 21094.63 215
plane_prior697.35 21594.61 21887.09 217
plane_prior598.56 12799.03 18896.07 10794.27 21796.92 229
plane_prior498.28 142
plane_prior394.61 21897.02 4095.34 179
plane_prior298.80 11197.28 22
plane_prior197.37 214
plane_prior94.60 22098.44 17896.74 4794.22 219
n20.00 376
nn0.00 376
door-mid94.37 351
lessismore_v094.45 31094.93 32988.44 32591.03 36286.77 32297.64 19776.23 33098.42 25890.31 26485.64 32896.51 290
LGP-MVS_train96.47 23197.46 20693.54 25298.54 13094.67 13394.36 21098.77 9385.39 25199.11 17695.71 12494.15 22396.76 251
test1198.66 112
door94.64 349
HQP5-MVS94.25 235
HQP-NCC97.20 22498.05 22596.43 5594.45 200
ACMP_Plane97.20 22498.05 22596.43 5594.45 200
BP-MVS95.30 137
HQP4-MVS94.45 20098.96 19596.87 241
HQP3-MVS98.46 14794.18 221
HQP2-MVS86.75 223
NP-MVS97.28 21894.51 22397.73 188
MDTV_nov1_ep13_2view84.26 33996.89 30790.97 27897.90 8289.89 14093.91 17499.18 117
ACMMP++_ref92.97 248
ACMMP++93.61 236
Test By Simon94.64 60
ITE_SJBPF95.44 27597.42 21091.32 28597.50 25995.09 11793.59 24398.35 13281.70 29898.88 20789.71 27693.39 24296.12 305
DeepMVS_CXcopyleft86.78 33797.09 23272.30 35795.17 34475.92 35384.34 34195.19 31570.58 34695.35 34279.98 33889.04 28892.68 348