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 bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort by
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
#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
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
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
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
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
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
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-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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
test_prior297.80 21996.12 6397.89 7498.69 9195.96 2596.89 7099.60 47
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.
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
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
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
test9_res96.39 9399.57 5499.69 35
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
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
agg_prior295.87 10599.57 5499.68 41
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
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
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
test1299.18 3299.16 7698.19 3298.53 12498.07 5995.13 4999.72 8699.56 6099.63 55
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
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
test22299.23 7097.17 7197.40 24398.66 10388.68 28098.05 6098.96 6894.14 6999.53 6499.61 56
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
plane_prior598.56 11899.03 15696.07 9694.27 18596.92 196
plane_prior94.60 18898.44 14696.74 4694.22 187
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
HQP3-MVS98.46 13894.18 189
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
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
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
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
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
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
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
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
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
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
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
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
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
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
ACMMP++93.61 204
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
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
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
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
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
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
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
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
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
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
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
ACMMP++_ref92.97 216
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
lessismore_v094.45 27494.93 29188.44 28891.03 32586.77 28497.64 18476.23 29498.42 22490.31 24285.64 29296.51 255
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
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
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
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
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
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
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
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
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
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)
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)
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
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
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
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
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
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
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
.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
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
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
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
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
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
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
MTMP94.14 319
gm-plane-assit95.88 26987.47 29589.74 26796.94 23299.19 13493.32 174
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_prior99.30 5298.38 1798.72 8197.57 9299.81 50
test_prior498.01 4197.86 214
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
无先验97.58 23598.72 8191.38 23199.87 3493.36 17299.60 59
原ACMM297.67 229
testdata299.89 2591.65 221
segment_acmp96.85 3
testdata197.32 25396.34 57
plane_prior797.42 17594.63 183
plane_prior697.35 18094.61 18687.09 207
plane_prior498.28 131
plane_prior394.61 18697.02 3995.34 145
plane_prior298.80 8597.28 22
plane_prior197.37 179
n20.00 339
nn0.00 339
door-mid94.37 316
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
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
Test By Simon94.64 57