This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
APDe-MVS97.82 197.73 198.08 799.15 2194.82 1098.81 298.30 2294.76 2198.30 398.90 193.77 599.68 3197.93 199.69 199.75 1
CNVR-MVS97.68 297.44 498.37 298.90 2895.86 297.27 9098.08 4795.81 397.87 898.31 3094.26 299.68 3197.02 399.49 2099.57 11
SteuartSystems-ACMMP97.62 397.53 297.87 1198.39 5594.25 1898.43 1598.27 2495.34 698.11 498.56 694.53 199.71 2496.57 1299.62 599.65 3
Skip Steuart: Steuart Systems R&D Blog.
TSAR-MVS + MP.97.42 497.33 597.69 2599.25 1794.24 1998.07 3397.85 8293.72 3998.57 298.35 2193.69 699.40 8097.06 299.46 2299.44 29
SD-MVS97.41 597.53 297.06 5198.57 4794.46 1297.92 3798.14 3794.82 1899.01 198.55 894.18 397.41 24596.94 499.64 399.32 39
HPM-MVS++97.34 696.97 1098.47 199.08 2396.16 197.55 6997.97 7495.59 496.61 3297.89 4892.57 1699.84 1195.95 2899.51 1699.40 32
NCCC97.30 797.03 898.11 698.77 3195.06 897.34 8498.04 6095.96 297.09 2497.88 5093.18 899.71 2495.84 3199.17 4799.56 13
ACMMP_Plus97.20 896.86 1598.23 399.09 2295.16 697.60 6598.19 3192.82 7097.93 798.74 291.60 3599.86 696.26 1699.52 1499.67 2
XVS97.18 996.96 1197.81 1499.38 794.03 2798.59 798.20 2994.85 1496.59 3498.29 3391.70 3399.80 1595.66 3399.40 2999.62 5
MCST-MVS97.18 996.84 1698.20 499.30 1595.35 397.12 10498.07 5293.54 4596.08 5097.69 6293.86 499.71 2496.50 1399.39 3199.55 15
Regformer-297.16 1196.99 997.67 2698.32 6193.84 3196.83 12398.10 4495.24 797.49 1098.25 3692.57 1699.61 4096.80 799.29 4099.56 13
HFP-MVS97.14 1296.92 1397.83 1299.42 394.12 2398.52 998.32 1993.21 5297.18 1798.29 3392.08 2599.83 1295.63 3599.59 799.54 17
Regformer-197.10 1396.96 1197.54 3398.32 6193.48 4196.83 12397.99 7295.20 997.46 1198.25 3692.48 1999.58 4896.79 999.29 4099.55 15
MTAPA97.08 1496.78 2197.97 999.37 994.42 1497.24 9298.08 4795.07 1196.11 4898.59 490.88 4599.90 196.18 2399.50 1899.58 9
MPTG97.07 1596.77 2297.97 999.37 994.42 1497.15 10398.08 4795.07 1196.11 4898.59 490.88 4599.90 196.18 2399.50 1899.58 9
region2R97.07 1596.84 1697.77 1999.46 193.79 3398.52 998.24 2693.19 5597.14 2098.34 2491.59 3699.87 595.46 4099.59 799.64 4
ACMMPR97.07 1596.84 1697.79 1699.44 293.88 2998.52 998.31 2193.21 5297.15 1998.33 2791.35 3899.86 695.63 3599.59 799.62 5
#test#97.02 1896.75 2397.83 1299.42 394.12 2398.15 2898.32 1992.57 7597.18 1798.29 3392.08 2599.83 1295.12 4599.59 799.54 17
CP-MVS97.02 1896.81 1997.64 2999.33 1393.54 3998.80 398.28 2392.99 6196.45 4198.30 3291.90 3099.85 895.61 3799.68 299.54 17
Regformer-496.97 2096.87 1497.25 4398.34 5892.66 6096.96 11298.01 6595.12 1097.14 2098.42 1591.82 3199.61 4096.90 599.13 5099.50 22
APD-MVScopyleft96.95 2196.60 2698.01 899.03 2594.93 997.72 5398.10 4491.50 9398.01 598.32 2992.33 2099.58 4894.85 5499.51 1699.53 20
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MSLP-MVS++96.94 2297.06 796.59 6398.72 3391.86 8197.67 5698.49 1294.66 2497.24 1598.41 1892.31 2398.94 10996.61 1199.46 2298.96 65
DeepC-MVS_fast93.89 296.93 2396.64 2597.78 1798.64 4294.30 1697.41 7898.04 6094.81 1996.59 3498.37 2091.24 3999.64 3995.16 4399.52 1499.42 31
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
mPP-MVS96.86 2496.60 2697.64 2999.40 593.44 4298.50 1298.09 4693.27 5195.95 5798.33 2791.04 4199.88 395.20 4299.57 1199.60 8
Regformer-396.85 2596.80 2097.01 5298.34 5892.02 7796.96 11297.76 8495.01 1397.08 2598.42 1591.71 3299.54 6096.80 799.13 5099.48 26
APD-MVS_3200maxsize96.81 2696.71 2497.12 5099.01 2692.31 6797.98 3598.06 5493.11 5897.44 1298.55 890.93 4399.55 5896.06 2599.25 4399.51 21
PGM-MVS96.81 2696.53 2997.65 2799.35 1293.53 4097.65 5998.98 192.22 8097.14 2098.44 1391.17 4099.85 894.35 6299.46 2299.57 11
MP-MVScopyleft96.77 2896.45 3397.72 2299.39 693.80 3298.41 1698.06 5493.37 4795.54 7098.34 2490.59 4899.88 394.83 5599.54 1299.49 24
PHI-MVS96.77 2896.46 3297.71 2498.40 5394.07 2598.21 2798.45 1589.86 13197.11 2398.01 4592.52 1899.69 2996.03 2799.53 1399.36 37
TSAR-MVS + GP.96.69 3096.49 3097.27 4298.31 6393.39 4396.79 13096.72 18994.17 3297.44 1297.66 6592.76 1099.33 8596.86 697.76 8799.08 56
HPM-MVS96.69 3096.45 3397.40 3599.36 1193.11 4998.87 198.06 5491.17 10496.40 4297.99 4690.99 4299.58 4895.61 3799.61 699.49 24
MVS_111021_HR96.68 3296.58 2896.99 5398.46 4992.31 6796.20 18798.90 294.30 3195.86 5997.74 6092.33 2099.38 8396.04 2699.42 2799.28 43
DELS-MVS96.61 3396.38 3597.30 3997.79 8593.19 4795.96 19998.18 3395.23 895.87 5897.65 6691.45 3799.70 2895.87 2999.44 2699.00 63
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
DeepPCF-MVS93.97 196.61 3397.09 695.15 12498.09 7686.63 22796.00 19898.15 3595.43 597.95 698.56 693.40 799.36 8496.77 1099.48 2199.45 27
EI-MVSNet-Vis-set96.51 3596.47 3196.63 6098.24 6791.20 10096.89 12097.73 8794.74 2296.49 3898.49 1090.88 4599.58 4896.44 1498.32 7299.13 51
HPM-MVS_fast96.51 3596.27 3797.22 4699.32 1492.74 5798.74 498.06 5490.57 12296.77 2798.35 2190.21 5299.53 6394.80 5799.63 499.38 36
test_prior396.46 3796.20 3997.23 4498.67 3692.99 5196.35 17398.00 6792.80 7196.03 5197.59 7392.01 2799.41 7895.01 4999.38 3299.29 41
abl_696.40 3896.21 3896.98 5498.89 2992.20 7297.89 3898.03 6293.34 5097.22 1698.42 1587.93 7599.72 2395.10 4699.07 5599.02 58
EI-MVSNet-UG-set96.34 3996.30 3696.47 7098.20 7190.93 11196.86 12197.72 9094.67 2396.16 4798.46 1190.43 4999.58 4896.23 1797.96 8198.90 72
train_agg96.30 4095.83 4397.72 2298.70 3494.19 2096.41 16498.02 6388.58 17296.03 5197.56 7792.73 1299.59 4595.04 4799.37 3699.39 33
ACMMPcopyleft96.27 4195.93 4197.28 4199.24 1892.62 6198.25 2498.81 392.99 6194.56 8098.39 1988.96 6199.85 894.57 6197.63 8899.36 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
MVS_111021_LR96.24 4296.19 4096.39 7498.23 7091.35 9596.24 18698.79 493.99 3595.80 6297.65 6689.92 5699.24 9095.87 2999.20 4698.58 88
agg_prior196.22 4395.77 4497.56 3298.67 3693.79 3396.28 18198.00 6788.76 16995.68 6597.55 7992.70 1499.57 5695.01 4999.32 3899.32 39
agg_prior396.16 4495.67 4597.62 3198.67 3693.88 2996.41 16498.00 6787.93 19195.81 6197.47 8192.33 2099.59 4595.04 4799.37 3699.39 33
DeepC-MVS93.07 396.06 4595.66 4697.29 4097.96 7993.17 4897.30 8998.06 5493.92 3693.38 9898.66 386.83 9099.73 2095.60 3999.22 4598.96 65
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CSCG96.05 4695.91 4296.46 7299.24 1890.47 12398.30 2098.57 1189.01 15693.97 9197.57 7592.62 1599.76 1894.66 6099.27 4299.15 49
canonicalmvs96.02 4795.45 4897.75 2197.59 9295.15 798.28 2197.60 10094.52 2696.27 4496.12 13787.65 7999.18 9496.20 2294.82 13998.91 71
CDPH-MVS95.97 4895.38 5097.77 1998.93 2794.44 1396.35 17397.88 7786.98 21496.65 3197.89 4891.99 2999.47 7192.26 9199.46 2299.39 33
UA-Net95.95 4995.53 4797.20 4897.67 8892.98 5397.65 5998.13 3894.81 1996.61 3298.35 2188.87 6299.51 6790.36 12497.35 9899.11 54
VNet95.89 5095.45 4897.21 4798.07 7792.94 5497.50 7298.15 3593.87 3797.52 997.61 7285.29 10699.53 6395.81 3295.27 13399.16 47
alignmvs95.87 5195.23 5497.78 1797.56 9495.19 597.86 4097.17 14594.39 2996.47 3996.40 12685.89 10099.20 9196.21 2195.11 13598.95 67
DP-MVS Recon95.68 5295.12 5797.37 3699.19 2094.19 2097.03 10798.08 4788.35 18095.09 7597.65 6689.97 5599.48 7092.08 10098.59 6898.44 102
MG-MVS95.61 5395.38 5096.31 7998.42 5290.53 12196.04 19497.48 11193.47 4695.67 6898.10 3989.17 5999.25 8991.27 11898.77 6399.13 51
CPTT-MVS95.57 5495.19 5596.70 5799.27 1691.48 9098.33 1998.11 4287.79 19495.17 7498.03 4387.09 8899.61 4093.51 7799.42 2799.02 58
3Dnovator+91.43 495.40 5594.48 7298.16 596.90 11195.34 498.48 1397.87 7994.65 2588.53 20498.02 4483.69 12299.71 2493.18 8598.96 6099.44 29
PS-MVSNAJ95.37 5695.33 5295.49 11497.35 9690.66 11995.31 22897.48 11193.85 3896.51 3795.70 16088.65 6699.65 3594.80 5798.27 7396.17 162
MVSFormer95.37 5695.16 5695.99 9396.34 13591.21 9898.22 2597.57 10391.42 9796.22 4597.32 8386.20 9797.92 20694.07 6499.05 5698.85 76
xiu_mvs_v2_base95.32 5895.29 5395.40 12097.22 9890.50 12295.44 22397.44 12393.70 4196.46 4096.18 13488.59 6999.53 6394.79 5997.81 8496.17 162
PVSNet_Blended_VisFu95.27 5994.91 5996.38 7598.20 7190.86 11397.27 9098.25 2590.21 12594.18 8797.27 8587.48 8499.73 2093.53 7697.77 8698.55 89
Vis-MVSNetpermissive95.23 6094.81 6096.51 6797.18 10091.58 8998.26 2398.12 3994.38 3094.90 7698.15 3882.28 16198.92 11091.45 11598.58 6999.01 62
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
EPP-MVSNet95.22 6195.04 5895.76 10097.49 9589.56 14498.67 597.00 16890.69 11494.24 8697.62 7189.79 5798.81 11993.39 8496.49 11798.92 70
EPNet95.20 6294.56 6797.14 4992.80 27492.68 5997.85 4294.87 26796.64 192.46 11197.80 5786.23 9599.65 3593.72 7498.62 6799.10 55
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
3Dnovator91.36 595.19 6394.44 7497.44 3496.56 12493.36 4598.65 698.36 1694.12 3389.25 19598.06 4282.20 16399.77 1793.41 8399.32 3899.18 46
OMC-MVS95.09 6494.70 6496.25 8598.46 4991.28 9696.43 16297.57 10392.04 8294.77 7897.96 4787.01 8999.09 10491.31 11796.77 11098.36 107
xiu_mvs_v1_base_debu95.01 6594.76 6195.75 10196.58 12191.71 8296.25 18397.35 13592.99 6196.70 2896.63 11482.67 15199.44 7596.22 1897.46 9196.11 167
xiu_mvs_v1_base95.01 6594.76 6195.75 10196.58 12191.71 8296.25 18397.35 13592.99 6196.70 2896.63 11482.67 15199.44 7596.22 1897.46 9196.11 167
xiu_mvs_v1_base_debi95.01 6594.76 6195.75 10196.58 12191.71 8296.25 18397.35 13592.99 6196.70 2896.63 11482.67 15199.44 7596.22 1897.46 9196.11 167
PAPM_NR95.01 6594.59 6696.26 8498.89 2990.68 11897.24 9297.73 8791.80 8792.93 10896.62 11789.13 6099.14 9989.21 14297.78 8598.97 64
lupinMVS94.99 6994.56 6796.29 8296.34 13591.21 9895.83 20596.27 20488.93 16196.22 4596.88 9886.20 9798.85 11695.27 4199.05 5698.82 79
Effi-MVS+94.93 7094.45 7396.36 7796.61 11991.47 9196.41 16497.41 12791.02 10994.50 8195.92 14487.53 8298.78 12293.89 7096.81 10998.84 78
IS-MVSNet94.90 7194.52 7096.05 9097.67 8890.56 12098.44 1496.22 20893.21 5293.99 8997.74 6085.55 10498.45 14789.98 12597.86 8299.14 50
MVS_Test94.89 7294.62 6595.68 10596.83 11589.55 14596.70 14397.17 14591.17 10495.60 6996.11 13987.87 7698.76 12593.01 8897.17 10298.72 82
PVSNet_Blended94.87 7394.56 6795.81 9898.27 6489.46 15095.47 22298.36 1688.84 16394.36 8396.09 14088.02 7299.58 4893.44 8198.18 7598.40 104
jason94.84 7494.39 7596.18 8795.52 16190.93 11196.09 19196.52 19789.28 14396.01 5597.32 8384.70 11498.77 12495.15 4498.91 6198.85 76
jason: jason.
API-MVS94.84 7494.49 7195.90 9597.90 8392.00 7897.80 4597.48 11189.19 14694.81 7796.71 10388.84 6399.17 9588.91 15098.76 6496.53 155
112194.71 7693.83 8097.34 3798.57 4793.64 3796.04 19497.73 8781.56 27595.68 6597.85 5490.23 5199.65 3587.68 17299.12 5398.73 81
WTY-MVS94.71 7694.02 7796.79 5697.71 8792.05 7596.59 15597.35 13590.61 12094.64 7996.93 9686.41 9499.39 8191.20 12094.71 14398.94 68
sss94.51 7893.80 8196.64 5897.07 10491.97 7996.32 17798.06 5488.94 16094.50 8196.78 10084.60 11599.27 8891.90 10396.02 12398.68 86
AdaColmapbinary94.34 7993.68 8496.31 7998.59 4491.68 8596.59 15597.81 8389.87 13092.15 11897.06 9583.62 12399.54 6089.34 13798.07 7897.70 130
CNLPA94.28 8093.53 8896.52 6498.38 5692.55 6396.59 15596.88 18390.13 12791.91 12297.24 8785.21 10799.09 10487.64 17597.83 8397.92 120
MAR-MVS94.22 8193.46 9196.51 6798.00 7892.19 7397.67 5697.47 11488.13 18993.00 10395.84 14884.86 11399.51 6787.99 16498.17 7697.83 126
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
PAPR94.18 8293.42 9596.48 6997.64 9091.42 9495.55 21797.71 9288.99 15792.34 11695.82 15089.19 5899.11 10186.14 19797.38 9698.90 72
HyFIR94.15 8393.51 8996.06 8998.27 6489.38 15295.18 23498.48 1485.60 23393.76 9397.11 9383.15 12999.61 4091.33 11698.72 6599.19 45
Vis-MVSNet (Re-imp)94.15 8393.88 7994.95 13397.61 9187.92 20098.10 3095.80 22892.22 8093.02 10297.45 8284.53 11797.91 20988.24 15997.97 8099.02 58
CDS-MVSNet94.14 8593.54 8795.93 9496.18 14291.46 9296.33 17697.04 16488.97 15993.56 9496.51 12187.55 8197.89 21089.80 12895.95 12498.44 102
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
PLCcopyleft91.00 694.11 8693.43 9396.13 8898.58 4691.15 10596.69 14597.39 12987.29 20691.37 13096.71 10388.39 7099.52 6687.33 18197.13 10397.73 128
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
FIs94.09 8793.70 8395.27 12295.70 15892.03 7698.10 3098.68 793.36 4990.39 14896.70 10587.63 8097.94 20292.25 9390.50 19495.84 175
PVSNet_BlendedMVS94.06 8893.92 7894.47 14798.27 6489.46 15096.73 13598.36 1690.17 12694.36 8395.24 17788.02 7299.58 4893.44 8190.72 19094.36 251
nrg03094.05 8993.31 9796.27 8395.22 17894.59 1198.34 1897.46 11692.93 6891.21 13996.64 11087.23 8798.22 15894.99 5285.80 23095.98 170
UGNet94.04 9093.28 9896.31 7996.85 11291.19 10197.88 3997.68 9494.40 2893.00 10396.18 13473.39 24999.61 4091.72 10898.46 7098.13 112
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
TAMVS94.01 9193.46 9195.64 10696.16 14490.45 12496.71 14096.89 18289.27 14493.46 9796.92 9787.29 8697.94 20288.70 15695.74 12898.53 91
114514_t93.95 9293.06 10096.63 6099.07 2491.61 8697.46 7797.96 7577.99 29293.00 10397.57 7586.14 9999.33 8589.22 14199.15 4898.94 68
FC-MVSNet-test93.94 9393.57 8595.04 12795.48 16291.45 9398.12 2998.71 593.37 4790.23 15196.70 10587.66 7897.85 21291.49 11390.39 19595.83 176
HY-MVS89.66 993.87 9492.95 10296.63 6097.10 10392.49 6595.64 21496.64 19489.05 15593.00 10395.79 15485.77 10399.45 7489.16 14494.35 14497.96 118
XVG-OURS-SEG-HR93.86 9593.55 8694.81 13797.06 10688.53 16995.28 22997.45 12091.68 9094.08 8897.68 6382.41 15998.90 11293.84 7292.47 16096.98 146
VDD-MVS93.82 9693.08 9996.02 9197.88 8489.96 13497.72 5395.85 22592.43 7795.86 5998.44 1368.42 27299.39 8196.31 1594.85 13798.71 84
mvs_anonymous93.82 9693.74 8294.06 16096.44 13285.41 23995.81 20697.05 16189.85 13390.09 16196.36 12887.44 8597.75 22293.97 6696.69 11499.02 58
HQP_MVS93.78 9893.43 9394.82 13596.21 13989.99 12997.74 4997.51 10994.85 1491.34 13296.64 11081.32 17498.60 13593.02 8692.23 16395.86 172
PS-MVSNAJss93.74 9993.51 8994.44 14893.91 24289.28 15697.75 4897.56 10692.50 7689.94 16496.54 12088.65 6698.18 16293.83 7390.90 18795.86 172
XVG-OURS93.72 10093.35 9694.80 13897.07 10488.61 16794.79 23897.46 11691.97 8593.99 8997.86 5381.74 16998.88 11592.64 9092.67 15996.92 148
HyFIR lowres test93.66 10192.92 10395.87 9698.24 6789.88 13594.58 24098.49 1285.06 24093.78 9295.78 15582.86 14898.67 13091.77 10795.71 12999.07 57
LFMVS93.60 10292.63 11296.52 6498.13 7591.27 9797.94 3693.39 29290.57 12296.29 4398.31 3069.00 26899.16 9694.18 6395.87 12699.12 53
F-COLMAP93.58 10392.98 10195.37 12198.40 5388.98 16197.18 10097.29 13987.75 19690.49 14597.10 9485.21 10799.50 6986.70 19096.72 11397.63 131
ab-mvs93.57 10492.55 11696.64 5897.28 9791.96 8095.40 22497.45 12089.81 13593.22 10096.28 13179.62 20199.46 7290.74 12193.11 15498.50 96
LS3D93.57 10492.61 11496.47 7097.59 9291.61 8697.67 5697.72 9085.17 23890.29 15098.34 2484.60 11599.73 2083.85 23798.27 7398.06 117
Fast-Effi-MVS+93.46 10692.75 10895.59 10896.77 11790.03 12696.81 12797.13 15188.19 18591.30 13494.27 21686.21 9698.63 13287.66 17496.46 11998.12 113
QAPM93.45 10792.27 12496.98 5496.77 11792.62 6198.39 1798.12 3984.50 24888.27 21097.77 5882.39 16099.81 1485.40 21198.81 6298.51 94
diffmvs93.43 10892.75 10895.48 11696.47 13189.61 14196.09 19197.14 14985.97 23093.09 10195.35 17384.87 11298.55 14089.51 13596.26 12298.28 109
UniMVSNet_NR-MVSNet93.37 10992.67 11195.47 11795.34 16992.83 5597.17 10198.58 1092.98 6690.13 15695.80 15188.37 7197.85 21291.71 10983.93 25695.73 185
1112_ss93.37 10992.42 12296.21 8697.05 10790.99 10796.31 17896.72 18986.87 22089.83 17096.69 10786.51 9399.14 9988.12 16193.67 14898.50 96
UniMVSNet (Re)93.31 11192.55 11695.61 10795.39 16593.34 4697.39 8098.71 593.14 5790.10 16094.83 18787.71 7798.03 18591.67 11183.99 25595.46 192
OPM-MVS93.28 11292.76 10694.82 13594.63 20590.77 11796.65 14897.18 14393.72 3991.68 12597.26 8679.33 20498.63 13292.13 9792.28 16295.07 217
VPA-MVSNet93.24 11392.48 12195.51 11295.70 15892.39 6697.86 4098.66 992.30 7992.09 12095.37 17280.49 18898.40 14893.95 6785.86 22995.75 183
MVSTER93.20 11492.81 10594.37 15196.56 12489.59 14397.06 10697.12 15291.24 10391.30 13495.96 14282.02 16698.05 18193.48 8090.55 19295.47 191
HQP-MVS93.19 11592.74 11094.54 14695.86 15189.33 15396.65 14897.39 12993.55 4290.14 15295.87 14680.95 17898.50 14492.13 9792.10 16895.78 179
test_djsdf93.07 11692.76 10694.00 16393.49 25588.70 16698.22 2597.57 10391.42 9790.08 16295.55 16782.85 14997.92 20694.07 6491.58 17695.40 198
VDDNet93.05 11792.07 12696.02 9196.84 11390.39 12598.08 3295.85 22586.22 22795.79 6398.46 1167.59 27599.19 9294.92 5394.85 13798.47 100
EI-MVSNet93.03 11892.88 10493.48 19595.77 15686.98 21996.44 16097.12 15290.66 11691.30 13497.64 6986.56 9298.05 18189.91 12690.55 19295.41 194
CLD-MVS92.98 11992.53 11894.32 15396.12 14889.20 15895.28 22997.47 11492.66 7389.90 16595.62 16380.58 18798.40 14892.73 8992.40 16195.38 200
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
ACMM89.79 892.96 12092.50 12094.35 15296.30 13788.71 16597.58 6897.36 13491.40 9990.53 14496.65 10979.77 19898.75 12691.24 11991.64 17495.59 188
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LPG-MVS_test92.94 12192.56 11594.10 15896.16 14488.26 17597.65 5997.46 11691.29 10090.12 15897.16 9079.05 20798.73 12792.25 9391.89 17195.31 204
BH-untuned92.94 12192.62 11393.92 17297.22 9886.16 23296.40 16996.25 20690.06 12889.79 17296.17 13683.19 12798.35 15287.19 18497.27 10097.24 143
DU-MVS92.90 12392.04 12795.49 11494.95 19192.83 5597.16 10298.24 2693.02 6090.13 15695.71 15883.47 12497.85 21291.71 10983.93 25695.78 179
PatchMatch-RL92.90 12392.02 12995.56 10998.19 7390.80 11595.27 23197.18 14387.96 19091.86 12495.68 16180.44 18998.99 10784.01 23397.54 9096.89 149
PMMVS92.86 12592.34 12394.42 15094.92 19386.73 22394.53 24296.38 20084.78 24594.27 8595.12 18183.13 13198.40 14891.47 11496.49 11798.12 113
OpenMVScopyleft89.19 1292.86 12591.68 13896.40 7395.34 16992.73 5898.27 2298.12 3984.86 24385.78 24297.75 5978.89 21399.74 1987.50 17898.65 6696.73 152
Test_1112_low_res92.84 12791.84 13395.85 9797.04 10889.97 13295.53 21996.64 19485.38 23489.65 18095.18 17885.86 10199.10 10287.70 17093.58 15398.49 98
131492.81 12892.03 12895.14 12595.33 17289.52 14896.04 19497.44 12387.72 19786.25 24095.33 17483.84 12098.79 12089.26 13997.05 10497.11 144
DP-MVS92.76 12991.51 14296.52 6498.77 3190.99 10797.38 8296.08 21282.38 26689.29 19297.87 5183.77 12199.69 2981.37 25696.69 11498.89 74
BH-RMVSNet92.72 13091.97 13094.97 13197.16 10187.99 19596.15 18895.60 23390.62 11891.87 12397.15 9278.41 21898.57 13883.16 24197.60 8998.36 107
ACMP89.59 1092.62 13192.14 12594.05 16196.40 13388.20 18197.36 8397.25 14291.52 9288.30 20896.64 11078.46 21798.72 12991.86 10691.48 17895.23 211
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
LCM-MVSNet-Re92.50 13292.52 11992.44 22596.82 11681.89 26596.92 11893.71 28792.41 7884.30 25294.60 19685.08 10997.03 25791.51 11297.36 9798.40 104
TranMVSNet+NR-MVSNet92.50 13291.63 13995.14 12594.76 20092.07 7497.53 7098.11 4292.90 6989.56 18396.12 13783.16 12897.60 23289.30 13883.20 26695.75 183
jajsoiax92.42 13491.89 13294.03 16293.33 26188.50 17097.73 5197.53 10792.00 8488.85 19896.50 12275.62 23298.11 16893.88 7191.56 17795.48 189
WR-MVS92.34 13591.53 14194.77 14095.13 18390.83 11496.40 16997.98 7391.88 8689.29 19295.54 16882.50 15597.80 21789.79 12985.27 23695.69 186
NR-MVSNet92.34 13591.27 14895.53 11194.95 19193.05 5097.39 8098.07 5292.65 7484.46 25095.71 15885.00 11097.77 22189.71 13083.52 26395.78 179
mvs_tets92.31 13791.76 13493.94 17193.41 25788.29 17397.63 6397.53 10792.04 8288.76 19996.45 12474.62 23998.09 17093.91 6991.48 17895.45 193
TAPA-MVS90.10 792.30 13891.22 15195.56 10998.33 6089.60 14296.79 13097.65 9781.83 27091.52 12797.23 8887.94 7498.91 11171.31 29198.37 7198.17 111
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
IterMVS-LS92.29 13991.94 13193.34 20296.25 13886.97 22096.57 15897.05 16190.67 11589.50 18694.80 18986.59 9197.64 22989.91 12686.11 22895.40 198
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
PVSNet86.66 1892.24 14091.74 13793.73 18397.77 8683.69 25592.88 27496.72 18987.91 19293.00 10394.86 18578.51 21699.05 10686.53 19197.45 9598.47 100
VPNet92.23 14191.31 14694.99 12995.56 16090.96 10997.22 9697.86 8192.96 6790.96 14096.62 11775.06 23598.20 15991.90 10383.65 26295.80 178
anonymousdsp92.16 14291.55 14093.97 16692.58 27889.55 14597.51 7197.42 12689.42 14188.40 20594.84 18680.66 18697.88 21191.87 10591.28 18294.48 247
XXY-MVS92.16 14291.23 15094.95 13394.75 20190.94 11097.47 7697.43 12589.14 15388.90 19696.43 12579.71 19998.24 15789.56 13487.68 21895.67 187
BH-w/o92.14 14491.75 13593.31 20396.99 11085.73 23595.67 21195.69 23088.73 17089.26 19494.82 18882.97 14398.07 17385.26 21396.32 12196.13 166
test_normal92.01 14590.75 16695.80 9993.24 26389.97 13295.93 20196.24 20790.62 11881.63 26893.45 23874.98 23698.89 11493.61 7597.04 10598.55 89
DI_MVS_plusplus_test92.01 14590.77 16495.73 10493.34 25989.78 13896.14 18996.18 21090.58 12181.80 26793.50 23574.95 23798.90 11293.51 7796.94 10698.51 94
WR-MVS_H92.00 14791.35 14393.95 16895.09 18589.47 14998.04 3498.68 791.46 9588.34 20694.68 19385.86 10197.56 23385.77 20584.24 25394.82 235
PatchmatchNetpermissive91.91 14891.35 14393.59 19095.38 16684.11 25093.15 27095.39 23989.54 13792.10 11993.68 22982.82 15098.13 16584.81 21795.32 13298.52 92
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
CP-MVSNet91.89 14991.24 14993.82 17495.05 18688.57 16897.82 4498.19 3191.70 8988.21 21195.76 15681.96 16797.52 23687.86 16684.65 25095.37 201
FMVSNet391.78 15090.69 16995.03 12896.53 12692.27 6997.02 10896.93 17889.79 13689.35 18994.65 19577.01 22597.47 24086.12 19888.82 20795.35 202
X-MVStestdata91.71 15189.67 20497.81 1499.38 794.03 2798.59 798.20 2994.85 1496.59 3432.69 32091.70 3399.80 1595.66 3399.40 2999.62 5
MVS91.71 15190.44 17495.51 11295.20 18091.59 8896.04 19497.45 12073.44 30487.36 22595.60 16485.42 10599.10 10285.97 20297.46 9195.83 176
EPNet_dtu91.71 15191.28 14792.99 21293.76 24783.71 25396.69 14595.28 24693.15 5687.02 23495.95 14383.37 12697.38 24779.46 26596.84 10797.88 123
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
v1neww91.70 15491.01 15493.75 18094.19 21988.14 18697.20 9796.98 16989.18 14889.87 16894.44 20283.10 13398.06 17889.06 14685.09 24095.06 220
v7new91.70 15491.01 15493.75 18094.19 21988.14 18697.20 9796.98 16989.18 14889.87 16894.44 20283.10 13398.06 17889.06 14685.09 24095.06 220
v691.69 15691.00 15693.75 18094.14 22488.12 18897.20 9796.98 16989.19 14689.90 16594.42 20483.04 13798.07 17389.07 14585.10 23995.07 217
PatchFormer-LS_test91.68 15791.18 15393.19 20895.24 17783.63 25695.53 21995.44 23889.82 13491.37 13092.58 25080.85 18598.52 14289.65 13390.16 19797.42 142
v114191.61 15890.89 15793.78 17794.01 23788.24 17796.96 11296.96 17389.17 15089.75 17494.29 21282.99 14198.03 18588.85 15285.00 24595.07 217
divwei89l23v2f11291.61 15890.89 15793.78 17794.01 23788.22 17996.96 11296.96 17389.17 15089.75 17494.28 21483.02 13998.03 18588.86 15184.98 24795.08 215
v191.61 15890.89 15793.78 17794.01 23788.21 18096.96 11296.96 17389.17 15089.78 17394.29 21282.97 14398.05 18188.85 15284.99 24695.08 215
v2v48291.59 16190.85 16293.80 17593.87 24488.17 18396.94 11796.88 18389.54 13789.53 18494.90 18481.70 17098.02 18889.25 14085.04 24495.20 212
V4291.58 16290.87 16093.73 18394.05 23688.50 17097.32 8796.97 17288.80 16889.71 17694.33 20982.54 15498.05 18189.01 14885.07 24294.64 244
PCF-MVS89.48 1191.56 16389.95 19396.36 7796.60 12092.52 6492.51 27897.26 14079.41 28588.90 19696.56 11984.04 11999.55 5877.01 27697.30 9997.01 145
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PS-CasMVS91.55 16490.84 16393.69 18694.96 19088.28 17497.84 4398.24 2691.46 9588.04 21395.80 15179.67 20097.48 23987.02 18784.54 25195.31 204
PAPM91.52 16590.30 17895.20 12395.30 17389.83 13693.38 26596.85 18586.26 22688.59 20395.80 15184.88 11198.15 16475.67 27995.93 12597.63 131
TR-MVS91.48 16690.59 17294.16 15796.40 13387.33 20995.67 21195.34 24587.68 19891.46 12895.52 16976.77 22698.35 15282.85 24593.61 15196.79 151
v791.47 16790.73 16793.68 18794.13 22588.16 18497.09 10597.05 16188.38 17889.80 17194.52 19782.21 16298.01 18988.00 16385.42 23394.87 229
tpmrst91.44 16891.32 14591.79 24695.15 18279.20 28793.42 26495.37 24188.55 17493.49 9693.67 23082.49 15698.27 15690.41 12389.34 20497.90 121
test-LLR91.42 16991.19 15292.12 23794.59 20680.66 27294.29 24792.98 29491.11 10690.76 14292.37 25379.02 20998.07 17388.81 15496.74 11197.63 131
MSDG91.42 16990.24 18294.96 13297.15 10288.91 16293.69 25996.32 20285.72 23286.93 23596.47 12380.24 19298.98 10880.57 25895.05 13696.98 146
GA-MVS91.38 17190.31 17794.59 14194.65 20487.62 20794.34 24596.19 20990.73 11390.35 14993.83 22671.84 25497.96 20087.22 18393.61 15198.21 110
v114491.37 17290.60 17193.68 18793.89 24388.23 17896.84 12297.03 16688.37 17989.69 17894.39 20582.04 16597.98 19387.80 16885.37 23494.84 231
GBi-Net91.35 17390.27 18094.59 14196.51 12791.18 10297.50 7296.93 17888.82 16589.35 18994.51 19873.87 24397.29 25186.12 19888.82 20795.31 204
test191.35 17390.27 18094.59 14196.51 12791.18 10297.50 7296.93 17888.82 16589.35 18994.51 19873.87 24397.29 25186.12 19888.82 20795.31 204
FMVSNet291.31 17590.08 18794.99 12996.51 12792.21 7097.41 7896.95 17688.82 16588.62 20194.75 19173.87 24397.42 24485.20 21488.55 21395.35 202
v891.29 17690.53 17393.57 19294.15 22388.12 18897.34 8497.06 16088.99 15788.32 20794.26 21783.08 13598.01 18987.62 17683.92 25894.57 245
CVMVSNet91.23 17791.75 13589.67 27495.77 15674.69 29596.44 16094.88 26685.81 23192.18 11797.64 6979.07 20695.58 28488.06 16295.86 12798.74 80
PEN-MVS91.20 17890.44 17493.48 19594.49 20987.91 20297.76 4798.18 3391.29 10087.78 21695.74 15780.35 19197.33 24985.46 21082.96 26795.19 213
Baseline_NR-MVSNet91.20 17890.62 17092.95 21393.83 24588.03 19497.01 10995.12 25588.42 17789.70 17795.13 18083.47 12497.44 24289.66 13283.24 26593.37 266
cascas91.20 17890.08 18794.58 14594.97 18989.16 16093.65 26197.59 10279.90 28489.40 18792.92 24475.36 23398.36 15192.14 9694.75 14296.23 158
CostFormer91.18 18190.70 16892.62 22394.84 19781.76 26694.09 25394.43 27184.15 25092.72 11093.77 22879.43 20398.20 15990.70 12292.18 16697.90 121
v119291.07 18290.23 18393.58 19193.70 24887.82 20396.73 13597.07 15887.77 19589.58 18194.32 21080.90 18497.97 19686.52 19285.48 23194.95 223
v14419291.06 18390.28 17993.39 19893.66 25087.23 21396.83 12397.07 15887.43 20289.69 17894.28 21481.48 17198.00 19287.18 18584.92 24894.93 227
v1091.04 18490.23 18393.49 19494.12 22788.16 18497.32 8797.08 15788.26 18288.29 20994.22 21882.17 16497.97 19686.45 19484.12 25494.33 252
v14890.99 18590.38 17692.81 21893.83 24585.80 23496.78 13296.68 19289.45 14088.75 20093.93 22482.96 14597.82 21687.83 16783.25 26494.80 236
LTVRE_ROB88.41 1390.99 18589.92 19494.19 15596.18 14289.55 14596.31 17897.09 15587.88 19385.67 24395.91 14578.79 21498.57 13881.50 25489.98 19894.44 249
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
pmmvs490.93 18789.85 19794.17 15693.34 25990.79 11694.60 23996.02 21384.62 24687.45 22295.15 17981.88 16897.45 24187.70 17087.87 21794.27 255
XVG-ACMP-BASELINE90.93 18790.21 18593.09 20994.31 21685.89 23395.33 22697.26 14091.06 10889.38 18895.44 17168.61 27098.60 13589.46 13691.05 18594.79 238
v192192090.85 18990.03 19093.29 20493.55 25186.96 22196.74 13497.04 16487.36 20489.52 18594.34 20880.23 19397.97 19686.27 19585.21 23794.94 225
CR-MVSNet90.82 19089.77 20093.95 16894.45 21187.19 21490.23 29495.68 23186.89 21992.40 11292.36 25680.91 18197.05 25581.09 25793.95 14697.60 136
v7n90.76 19189.86 19693.45 19793.54 25287.60 20897.70 5597.37 13288.85 16287.65 22094.08 22181.08 17698.10 16984.68 22083.79 26194.66 243
DWT-MVSNet_test90.76 19189.89 19593.38 19995.04 18783.70 25495.85 20494.30 27788.19 18590.46 14692.80 24573.61 24798.50 14488.16 16090.58 19197.95 119
RPSCF90.75 19390.86 16190.42 26896.84 11376.29 29395.61 21696.34 20183.89 25391.38 12997.87 5176.45 22798.78 12287.16 18692.23 16396.20 159
MVP-Stereo90.74 19490.08 18792.71 22193.19 26888.20 18195.86 20396.27 20486.07 22984.86 24894.76 19077.84 22297.75 22283.88 23698.01 7992.17 290
pm-mvs190.72 19589.65 20693.96 16794.29 21789.63 14097.79 4696.82 18689.07 15486.12 24195.48 17078.61 21597.78 21986.97 18881.67 27394.46 248
V490.71 19690.00 19192.82 21593.21 26687.03 21797.59 6797.16 14888.21 18387.69 21893.92 22580.93 18098.06 17887.39 17983.90 25993.39 265
v124090.70 19789.85 19793.23 20693.51 25486.80 22296.61 15397.02 16787.16 20889.58 18194.31 21179.55 20297.98 19385.52 20985.44 23294.90 228
v5290.70 19790.00 19192.82 21593.24 26387.03 21797.60 6597.14 14988.21 18387.69 21893.94 22380.91 18198.07 17387.39 17983.87 26093.36 267
EPMVS90.70 19789.81 19993.37 20094.73 20284.21 24993.67 26088.02 31189.50 13992.38 11493.49 23677.82 22397.78 21986.03 20192.68 15898.11 116
DTE-MVSNet90.56 20089.75 20293.01 21193.95 24087.25 21197.64 6297.65 9790.74 11287.12 22995.68 16179.97 19697.00 26083.33 24081.66 27494.78 239
ACMH87.59 1690.53 20189.42 20993.87 17396.21 13987.92 20097.24 9296.94 17788.45 17683.91 25896.27 13271.92 25398.62 13484.43 22589.43 20395.05 222
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
OurMVSNet-221017-090.51 20290.19 18691.44 25493.41 25781.25 26996.98 11196.28 20391.68 9086.55 23896.30 12974.20 24297.98 19388.96 14987.40 22395.09 214
COLMAP_ROBcopyleft87.81 1590.40 20389.28 21193.79 17697.95 8087.13 21696.92 11895.89 22482.83 26386.88 23797.18 8973.77 24699.29 8778.44 27093.62 15094.95 223
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
v74890.34 20489.54 20792.75 22093.25 26285.71 23697.61 6497.17 14588.54 17587.20 22893.54 23381.02 17798.01 18985.73 20781.80 27194.52 246
MS-PatchMatch90.27 20589.77 20091.78 24794.33 21584.72 24795.55 21796.73 18886.17 22886.36 23995.28 17671.28 25897.80 21784.09 23098.14 7792.81 272
tpm90.25 20689.74 20391.76 24993.92 24179.73 28393.98 25493.54 29188.28 18191.99 12193.25 24177.51 22497.44 24287.30 18287.94 21698.12 113
AllTest90.23 20788.98 21593.98 16497.94 8186.64 22496.51 15995.54 23585.38 23485.49 24596.77 10170.28 26499.15 9780.02 26192.87 15596.15 164
ACMH+87.92 1490.20 20889.18 21393.25 20596.48 13086.45 22896.99 11096.68 19288.83 16484.79 24996.22 13370.16 26698.53 14184.42 22688.04 21594.77 240
test-mter90.19 20989.54 20792.12 23794.59 20680.66 27294.29 24792.98 29487.68 19890.76 14292.37 25367.67 27498.07 17388.81 15496.74 11197.63 131
IterMVS90.15 21089.67 20491.61 25195.48 16283.72 25294.33 24696.12 21189.99 12987.31 22794.15 21975.78 23196.27 26686.97 18886.89 22594.83 233
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
TESTMET0.1,190.06 21189.42 20991.97 24194.41 21380.62 27494.29 24791.97 30187.28 20790.44 14792.47 25268.79 26997.67 22688.50 15896.60 11697.61 135
tpm289.96 21289.21 21292.23 23194.91 19581.25 26993.78 25794.42 27280.62 28291.56 12693.44 23976.44 22897.94 20285.60 20892.08 17097.49 140
IB-MVS87.33 1789.91 21388.28 22494.79 13995.26 17687.70 20695.12 23593.95 28589.35 14287.03 23392.49 25170.74 26299.19 9289.18 14381.37 27597.49 140
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
ADS-MVSNet89.89 21488.68 21993.53 19395.86 15184.89 24590.93 29095.07 25783.23 26191.28 13791.81 26379.01 21197.85 21279.52 26391.39 18097.84 124
FMVSNet189.88 21588.31 22394.59 14195.41 16491.18 10297.50 7296.93 17886.62 22387.41 22494.51 19865.94 28297.29 25183.04 24387.43 22195.31 204
pmmvs589.86 21688.87 21792.82 21592.86 27286.23 23196.26 18295.39 23984.24 24987.12 22994.51 19874.27 24197.36 24887.61 17787.57 21994.86 230
tpmvs89.83 21789.15 21491.89 24394.92 19380.30 27893.11 27195.46 23786.28 22588.08 21292.65 24780.44 18998.52 14281.47 25589.92 20096.84 150
tpmp4_e2389.58 21888.59 22092.54 22495.16 18181.53 26794.11 25295.09 25681.66 27188.60 20293.44 23975.11 23498.33 15582.45 25091.72 17397.75 127
Test489.48 21987.50 22995.44 11990.76 28889.72 13995.78 20997.09 15590.28 12477.67 29391.74 26555.42 30098.08 17191.92 10296.83 10898.52 92
ADS-MVSNet289.45 22088.59 22092.03 24095.86 15182.26 26390.93 29094.32 27683.23 26191.28 13791.81 26379.01 21195.99 27679.52 26391.39 18097.84 124
test0.0.03 189.37 22188.70 21891.41 25592.47 27985.63 23795.22 23392.70 29791.11 10686.91 23693.65 23179.02 20993.19 29778.00 27189.18 20595.41 194
SixPastTwentyTwo89.15 22288.54 22290.98 25893.49 25580.28 27996.70 14394.70 26890.78 11184.15 25595.57 16571.78 25597.71 22584.63 22185.07 24294.94 225
TransMVSNet (Re)88.94 22387.56 22793.08 21094.35 21488.45 17297.73 5195.23 25087.47 20184.26 25395.29 17579.86 19797.33 24979.44 26674.44 30193.45 264
USDC88.94 22387.83 22692.27 22794.66 20384.96 24493.86 25695.90 21987.34 20583.40 26095.56 16667.43 27698.19 16182.64 24989.67 20293.66 261
dp88.90 22588.26 22590.81 26294.58 20876.62 29292.85 27594.93 26485.12 23990.07 16393.07 24275.81 23098.12 16780.53 25987.42 22297.71 129
PatchT88.87 22687.42 23293.22 20794.08 23385.10 24289.51 29894.64 26981.92 26992.36 11588.15 29480.05 19597.01 25972.43 28793.65 14997.54 139
EU-MVSNet88.72 22788.90 21688.20 27893.15 26974.21 29696.63 15294.22 28085.18 23787.32 22695.97 14176.16 22994.98 28985.27 21286.17 22695.41 194
v1888.71 22887.52 22892.27 22794.16 22288.11 19096.82 12695.96 21487.03 21080.76 27489.81 27583.15 12996.22 26784.69 21975.31 29292.49 276
v1688.69 22987.50 22992.26 22994.19 21988.11 19096.81 12795.95 21587.01 21280.71 27689.80 27683.08 13596.20 26884.61 22275.34 29192.48 278
v1788.67 23087.47 23192.26 22994.13 22588.09 19296.81 12795.95 21587.02 21180.72 27589.75 27783.11 13296.20 26884.61 22275.15 29492.49 276
Patchmtry88.64 23187.25 23692.78 21994.09 23186.64 22489.82 29795.68 23180.81 28187.63 22192.36 25680.91 18197.03 25778.86 26885.12 23894.67 242
v1588.53 23287.31 23392.20 23294.09 23188.05 19396.72 13895.90 21987.01 21280.53 27989.60 28183.02 13996.13 27084.29 22774.64 29592.41 282
V1488.52 23387.30 23492.17 23494.12 22787.99 19596.72 13895.91 21886.98 21480.50 28089.63 27883.03 13896.12 27284.23 22874.60 29792.40 283
RPMNet88.52 23386.72 24793.95 16894.45 21187.19 21490.23 29494.99 26077.87 29492.40 11287.55 29980.17 19497.05 25568.84 29593.95 14697.60 136
MIMVSNet88.50 23586.76 24493.72 18594.84 19787.77 20491.39 28594.05 28286.41 22487.99 21492.59 24963.27 28695.82 28077.44 27292.84 15797.57 138
V988.49 23687.26 23592.18 23394.12 22787.97 19896.73 13595.90 21986.95 21680.40 28289.61 27982.98 14296.13 27084.14 22974.55 29892.44 280
v1288.46 23787.23 23892.17 23494.10 23087.99 19596.71 14095.90 21986.91 21780.34 28489.58 28282.92 14696.11 27484.09 23074.50 30092.42 281
v1388.45 23887.22 23992.16 23694.08 23387.95 19996.71 14095.90 21986.86 22180.27 28689.55 28382.92 14696.12 27284.02 23274.63 29692.40 283
v1188.41 23987.19 24292.08 23994.08 23387.77 20496.75 13395.85 22586.74 22280.50 28089.50 28482.49 15696.08 27583.55 23875.20 29392.38 285
Patchmatch-test188.40 24086.74 24693.36 20195.35 16886.38 22989.13 30094.96 26381.11 27687.10 23191.26 26872.64 25197.50 23774.37 28194.76 14096.20 159
tpm cat188.36 24187.21 24091.81 24595.13 18380.55 27592.58 27795.70 22974.97 30087.45 22291.96 26178.01 22198.17 16380.39 26088.74 21096.72 153
JIA-IIPM88.26 24287.04 24391.91 24293.52 25381.42 26889.38 29994.38 27380.84 28090.93 14180.74 30679.22 20597.92 20682.76 24691.62 17596.38 157
Patchmatch-test88.22 24386.65 24892.94 21495.27 17485.11 24188.98 30194.37 27481.11 27687.10 23191.26 26872.64 25197.50 23774.37 28194.76 14096.20 159
testgi87.97 24487.21 24090.24 27092.86 27280.76 27196.67 14794.97 26191.74 8885.52 24495.83 14962.66 28894.47 29176.25 27788.36 21495.48 189
LF4IMVS87.94 24587.25 23689.98 27292.38 28080.05 28294.38 24495.25 24987.59 20084.34 25194.74 19264.31 28597.66 22884.83 21687.45 22092.23 287
gg-mvs-nofinetune87.82 24685.61 25394.44 14894.46 21089.27 15791.21 28984.61 31780.88 27989.89 16774.98 30971.50 25697.53 23585.75 20697.21 10196.51 156
pmmvs687.81 24786.19 24992.69 22291.32 28586.30 23097.34 8496.41 19980.59 28384.05 25794.37 20767.37 27797.67 22684.75 21879.51 28194.09 257
K. test v387.64 24886.75 24590.32 26993.02 27179.48 28596.61 15392.08 30090.66 11680.25 28794.09 22067.21 27896.65 26385.96 20380.83 27894.83 233
testing_287.33 24985.03 25794.22 15487.77 30089.32 15594.97 23697.11 15489.22 14571.64 30288.73 28855.16 30197.94 20291.95 10188.73 21195.41 194
FMVSNet587.29 25085.79 25291.78 24794.80 19987.28 21095.49 22195.28 24684.09 25183.85 25991.82 26262.95 28794.17 29278.48 26985.34 23593.91 259
Anonymous2023120687.09 25186.14 25089.93 27391.22 28680.35 27696.11 19095.35 24283.57 25884.16 25493.02 24373.54 24895.61 28272.16 28886.14 22793.84 260
EG-PatchMatch MVS87.02 25285.44 25491.76 24992.67 27685.00 24396.08 19396.45 19883.41 26079.52 28993.49 23657.10 29697.72 22479.34 26790.87 18892.56 274
TinyColmap86.82 25385.35 25691.21 25694.91 19582.99 25893.94 25594.02 28483.58 25781.56 26994.68 19362.34 28998.13 16575.78 27887.35 22492.52 275
TDRefinement86.53 25484.76 26091.85 24482.23 31084.25 24896.38 17195.35 24284.97 24284.09 25694.94 18265.76 28398.34 15484.60 22474.52 29992.97 268
test_040286.46 25584.79 25991.45 25395.02 18885.55 23896.29 18094.89 26580.90 27882.21 26293.97 22268.21 27397.29 25162.98 30188.68 21291.51 294
DSMNet-mixed86.34 25686.12 25187.00 28389.88 29270.43 30194.93 23790.08 30877.97 29385.42 24792.78 24674.44 24093.96 29374.43 28095.14 13496.62 154
pmmvs-eth3d86.22 25784.45 26191.53 25288.34 29787.25 21194.47 24395.01 25883.47 25979.51 29089.61 27969.75 26795.71 28183.13 24276.73 28791.64 292
test20.0386.14 25885.40 25588.35 27690.12 28980.06 28195.90 20295.20 25188.59 17181.29 27093.62 23271.43 25792.65 29871.26 29281.17 27692.34 286
UnsupCasMVSNet_eth85.99 25984.45 26190.62 26589.97 29182.40 26293.62 26297.37 13289.86 13178.59 29292.37 25365.25 28495.35 28782.27 25270.75 30494.10 256
YYNet185.87 26084.23 26390.78 26492.38 28082.46 26193.17 26895.14 25482.12 26867.69 30392.36 25678.16 22095.50 28677.31 27479.73 28094.39 250
MDA-MVSNet_test_wron85.87 26084.23 26390.80 26392.38 28082.57 25993.17 26895.15 25382.15 26767.65 30492.33 25978.20 21995.51 28577.33 27379.74 27994.31 254
CMPMVSbinary62.92 2185.62 26284.92 25887.74 28089.14 29573.12 29994.17 25096.80 18773.98 30273.65 29894.93 18366.36 27997.61 23183.95 23591.28 18292.48 278
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PVSNet_082.17 1985.46 26383.64 26590.92 26095.27 17479.49 28490.55 29395.60 23383.76 25683.00 26189.95 27271.09 25997.97 19682.75 24760.79 31195.31 204
MDA-MVSNet-bldmvs85.00 26482.95 26791.17 25793.13 27083.33 25794.56 24195.00 25984.57 24765.13 30892.65 24770.45 26395.85 27873.57 28577.49 28494.33 252
MIMVSNet184.93 26583.05 26690.56 26689.56 29484.84 24695.40 22495.35 24283.91 25280.38 28392.21 26057.23 29593.34 29670.69 29482.75 27093.50 262
OpenMVS_ROBcopyleft81.14 2084.42 26682.28 26990.83 26190.06 29084.05 25195.73 21094.04 28373.89 30380.17 28891.53 26759.15 29397.64 22966.92 29789.05 20690.80 297
Patchmatch-RL test84.25 26782.75 26888.74 27588.74 29678.40 29088.12 30493.17 29387.11 20982.17 26389.29 28550.54 30595.60 28388.64 15777.02 28592.21 288
LP84.13 26881.85 27490.97 25993.20 26782.12 26487.68 30594.27 27976.80 29581.93 26588.52 28972.97 25095.95 27759.53 30681.73 27294.84 231
PM-MVS83.48 26981.86 27388.31 27787.83 29977.59 29193.43 26391.75 30286.91 21780.63 27789.91 27344.42 30895.84 27985.17 21576.73 28791.50 295
new-patchmatchnet83.18 27081.87 27287.11 28286.88 30275.99 29493.70 25895.18 25285.02 24177.30 29488.40 29165.99 28193.88 29474.19 28470.18 30591.47 296
new_pmnet82.89 27181.12 27788.18 27989.63 29380.18 28091.77 28492.57 29876.79 29675.56 29688.23 29361.22 29194.48 29071.43 29082.92 26889.87 299
test235682.77 27282.14 27184.65 28785.77 30470.36 30291.22 28893.69 29081.58 27381.82 26689.00 28760.63 29290.77 30464.74 29990.80 18992.82 270
testus82.63 27382.15 27084.07 28887.31 30167.67 30793.18 26694.29 27882.47 26582.14 26490.69 27053.01 30291.94 30166.30 29889.96 19992.62 273
MVS-HIRNet82.47 27481.21 27686.26 28695.38 16669.21 30688.96 30289.49 31066.28 30880.79 27374.08 31168.48 27197.39 24671.93 28995.47 13092.18 289
UnsupCasMVSNet_bld82.13 27579.46 27890.14 27188.00 29882.47 26090.89 29296.62 19678.94 28875.61 29584.40 30456.63 29796.31 26577.30 27566.77 31091.63 293
testpf80.97 27681.40 27579.65 29491.53 28472.43 30073.47 31689.55 30978.63 28980.81 27289.06 28661.36 29091.36 30383.34 23984.89 24975.15 310
pmmvs379.97 27777.50 28287.39 28182.80 30879.38 28692.70 27690.75 30670.69 30678.66 29187.47 30051.34 30493.40 29573.39 28669.65 30689.38 300
test123567879.82 27878.53 28083.69 28982.55 30967.55 30892.50 27994.13 28179.28 28672.10 30186.45 30257.27 29490.68 30561.60 30480.90 27792.82 270
N_pmnet78.73 27978.71 27978.79 29692.80 27446.50 32394.14 25143.71 32678.61 29080.83 27191.66 26674.94 23896.36 26467.24 29684.45 25293.50 262
111178.29 28077.55 28180.50 29283.89 30559.98 31591.89 28293.71 28775.06 29873.60 29987.67 29755.66 29892.60 29958.54 30877.92 28388.93 301
Anonymous2023121178.22 28175.30 28386.99 28486.14 30374.16 29795.62 21593.88 28666.43 30774.44 29787.86 29641.39 30995.11 28862.49 30269.46 30791.71 291
test1235674.97 28274.13 28477.49 29778.81 31156.23 31988.53 30392.75 29675.14 29767.50 30585.07 30344.88 30789.96 30658.71 30775.75 28986.26 302
LCM-MVSNet72.55 28369.39 28782.03 29070.81 32065.42 31190.12 29694.36 27555.02 31265.88 30781.72 30524.16 31989.96 30674.32 28368.10 30890.71 298
testmv72.22 28470.02 28578.82 29573.06 31861.75 31391.24 28792.31 29974.45 30161.06 31080.51 30734.21 31188.63 30955.31 31168.07 30986.06 303
FPMVS71.27 28569.85 28675.50 29974.64 31359.03 31791.30 28691.50 30358.80 31157.92 31188.28 29229.98 31585.53 31253.43 31282.84 26981.95 306
PMMVS270.19 28666.92 28980.01 29376.35 31265.67 31086.22 30787.58 31364.83 31062.38 30980.29 30826.78 31788.49 31063.79 30054.07 31285.88 304
no-one68.12 28763.78 29181.13 29174.01 31570.22 30487.61 30690.71 30772.63 30553.13 31371.89 31230.29 31391.45 30261.53 30532.21 31681.72 307
Gipumacopyleft67.86 28865.41 29075.18 30092.66 27773.45 29866.50 31894.52 27053.33 31357.80 31266.07 31530.81 31289.20 30848.15 31578.88 28262.90 314
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
.test124565.38 28969.22 28853.86 30883.89 30559.98 31591.89 28293.71 28775.06 29873.60 29987.67 29755.66 29892.60 29958.54 3082.96 3229.00 319
ANet_high63.94 29059.58 29277.02 29861.24 32366.06 30985.66 30987.93 31278.53 29142.94 31571.04 31325.42 31880.71 31452.60 31330.83 31884.28 305
PNet_i23d59.01 29155.87 29368.44 30373.98 31651.37 32081.36 31282.41 31952.37 31442.49 31770.39 31411.39 32079.99 31649.77 31438.71 31473.97 311
PMVScopyleft53.92 2258.58 29255.40 29468.12 30451.00 32448.64 32178.86 31487.10 31546.77 31635.84 32074.28 3108.76 32186.34 31142.07 31673.91 30269.38 312
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
wuykxyi23d56.92 29351.11 29874.38 30262.30 32261.47 31480.09 31384.87 31649.62 31530.80 32157.20 3197.03 32282.94 31355.69 31032.36 31578.72 309
E-PMN53.28 29452.56 29655.43 30674.43 31447.13 32283.63 31176.30 32242.23 31742.59 31662.22 31728.57 31674.40 31731.53 31831.51 31744.78 315
MVEpermissive50.73 2353.25 29548.81 29966.58 30565.34 32157.50 31872.49 31770.94 32440.15 31939.28 31963.51 3166.89 32473.48 31938.29 31742.38 31368.76 313
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
EMVS52.08 29651.31 29754.39 30772.62 31945.39 32483.84 31075.51 32341.13 31840.77 31859.65 31830.08 31473.60 31828.31 31929.90 31944.18 316
tmp_tt51.94 29753.82 29546.29 30933.73 32545.30 32578.32 31567.24 32518.02 32050.93 31487.05 30152.99 30353.11 32070.76 29325.29 32040.46 317
pcd1.5k->3k38.37 29840.51 30031.96 31094.29 2170.00 3290.00 32097.69 930.00 3240.00 3250.00 32681.45 1720.00 3240.00 32391.11 18495.89 171
wuyk23d25.11 29924.57 30226.74 31173.98 31639.89 32657.88 3199.80 32712.27 32110.39 3226.97 3257.03 32236.44 32125.43 32017.39 3213.89 321
cdsmvs_eth3d_5k23.24 30030.99 3010.00 3140.00 3280.00 3290.00 32097.63 990.00 3240.00 32596.88 9884.38 1180.00 3240.00 3230.00 3250.00 322
testmvs13.36 30116.33 3034.48 3135.04 3262.26 32893.18 2663.28 3282.70 3228.24 32321.66 3212.29 3262.19 3227.58 3212.96 3229.00 319
test12313.04 30215.66 3045.18 3124.51 3273.45 32792.50 2791.81 3292.50 3237.58 32420.15 3223.67 3252.18 3237.13 3221.07 3249.90 318
ab-mvs-re8.06 30310.74 3050.00 3140.00 3280.00 3290.00 3200.00 3300.00 3240.00 32596.69 1070.00 3270.00 3240.00 3230.00 3250.00 322
pcd_1.5k_mvsjas7.39 3049.85 3060.00 3140.00 3280.00 3290.00 3200.00 3300.00 3240.00 3250.00 32688.65 660.00 3240.00 3230.00 3250.00 322
sosnet-low-res0.00 3050.00 3070.00 3140.00 3280.00 3290.00 3200.00 3300.00 3240.00 3250.00 3260.00 3270.00 3240.00 3230.00 3250.00 322
sosnet0.00 3050.00 3070.00 3140.00 3280.00 3290.00 3200.00 3300.00 3240.00 3250.00 3260.00 3270.00 3240.00 3230.00 3250.00 322
uncertanet0.00 3050.00 3070.00 3140.00 3280.00 3290.00 3200.00 3300.00 3240.00 3250.00 3260.00 3270.00 3240.00 3230.00 3250.00 322
Regformer0.00 3050.00 3070.00 3140.00 3280.00 3290.00 3200.00 3300.00 3240.00 3250.00 3260.00 3270.00 3240.00 3230.00 3250.00 322
uanet0.00 3050.00 3070.00 3140.00 3280.00 3290.00 3200.00 3300.00 3240.00 3250.00 3260.00 3270.00 3240.00 3230.00 3250.00 322
ambc86.56 28583.60 30770.00 30585.69 30894.97 26180.60 27888.45 29037.42 31096.84 26282.69 24875.44 29092.86 269
MTGPAbinary98.08 47
mvs-test194.30 7697.00 10988.86 16496.41 16497.41 12790.84 11093.34 9996.30 12987.53 8298.79 12093.49 7996.36 120
test_post116.58 324
test_post17.58 323
patchmatchnet-post90.45 271
GG-mvs-BLEND93.62 18993.69 24989.20 15892.39 28183.33 31887.98 21589.84 27471.00 26096.87 26182.08 25395.40 13194.80 236
MTMP82.03 320
gm-plane-assit93.22 26578.89 28984.82 24493.52 23498.64 13187.72 169
test9_res94.81 5699.38 3299.45 27
TEST998.70 3494.19 2096.41 16498.02 6388.17 18796.03 5197.56 7792.74 1199.59 45
test_898.67 3694.06 2696.37 17298.01 6588.58 17295.98 5697.55 7992.73 1299.58 48
agg_prior293.94 6899.38 3299.50 22
agg_prior98.67 3693.79 3398.00 6795.68 6599.57 56
TestCases93.98 16497.94 8186.64 22495.54 23585.38 23485.49 24596.77 10170.28 26499.15 9780.02 26192.87 15596.15 164
test_prior493.66 3696.42 163
test_prior296.35 17392.80 7196.03 5197.59 7392.01 2795.01 4999.38 32
test_prior97.23 4498.67 3692.99 5198.00 6799.41 7899.29 41
旧先验295.94 20081.66 27197.34 1498.82 11892.26 91
新几何295.79 207
新几何197.32 3898.60 4393.59 3897.75 8581.58 273