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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
region2R94.43 1494.27 1594.92 998.65 186.67 2096.92 1497.23 1988.60 5693.58 2597.27 1185.22 3799.54 792.21 2898.74 1698.56 8
ACMMPR94.43 1494.28 1494.91 1098.63 286.69 1896.94 1097.32 1488.63 5493.53 2897.26 1385.04 4099.54 792.35 2698.78 1198.50 9
HFP-MVS94.52 1094.40 1194.86 1298.61 386.81 1396.94 1097.34 988.63 5493.65 2197.21 1686.10 2799.49 1392.35 2698.77 1298.30 24
#test#94.32 1994.14 2094.86 1298.61 386.81 1396.43 2397.34 987.51 8293.65 2197.21 1686.10 2799.49 1391.68 4498.77 1298.30 24
XVS94.45 1294.32 1294.85 1498.54 586.60 2396.93 1297.19 2090.66 2192.85 3497.16 2185.02 4199.49 1391.99 3598.56 3398.47 12
X-MVStestdata88.31 13586.13 17194.85 1498.54 586.60 2396.93 1297.19 2090.66 2192.85 3423.41 32985.02 4199.49 1391.99 3598.56 3398.47 12
mPP-MVS93.99 2793.78 2994.63 2798.50 785.90 4496.87 1696.91 3988.70 5291.83 6297.17 2083.96 5099.55 591.44 4898.64 2998.43 18
HSP-MVS95.30 395.48 294.76 2298.49 886.52 2596.91 1596.73 5291.73 896.10 396.69 3689.90 199.30 2694.70 398.04 4798.45 16
MP-MVScopyleft94.25 2094.07 2394.77 2198.47 986.31 3396.71 2096.98 3189.04 4491.98 5897.19 1885.43 3599.56 192.06 3498.79 998.44 17
MCST-MVS94.45 1294.20 1995.19 598.46 1087.50 795.00 7797.12 2487.13 8592.51 4896.30 5289.24 699.34 2093.46 1198.62 3098.73 3
PGM-MVS93.96 2893.72 3194.68 2598.43 1186.22 3695.30 5997.78 187.45 8393.26 2997.33 984.62 4599.51 1190.75 5798.57 3298.32 23
MPTG94.47 1194.30 1395.00 798.42 1286.95 995.06 7696.97 3291.07 1393.14 3297.56 484.30 4799.56 193.43 1298.75 1498.47 12
MTAPA94.42 1694.22 1695.00 798.42 1286.95 994.36 12196.97 3291.07 1393.14 3297.56 484.30 4799.56 193.43 1298.75 1498.47 12
HPM-MVS94.02 2693.88 2694.43 3498.39 1485.78 4697.25 597.07 2886.90 8992.62 4596.80 3384.85 4499.17 3292.43 2398.65 2898.33 21
CP-MVS94.34 1794.21 1894.74 2498.39 1486.64 2297.60 197.24 1788.53 5892.73 4197.23 1485.20 3899.32 2492.15 3198.83 898.25 31
HPM-MVS_fast93.40 3993.22 3893.94 4698.36 1684.83 5497.15 796.80 4785.77 10592.47 4997.13 2282.38 5999.07 4190.51 5998.40 3797.92 54
DP-MVS Recon91.95 5791.28 6093.96 4598.33 1785.92 4194.66 9996.66 5982.69 18490.03 8295.82 7082.30 6199.03 4784.57 11696.48 7496.91 87
APDe-MVS95.46 195.64 194.91 1098.26 1886.29 3597.46 297.40 789.03 4596.20 298.10 189.39 599.34 2095.88 199.03 199.10 1
TSAR-MVS + MP.94.85 794.94 694.58 2998.25 1986.33 3196.11 3196.62 6288.14 6796.10 396.96 2689.09 798.94 6294.48 498.68 2298.48 11
HPM-MVS++95.14 594.91 795.83 198.25 1989.65 195.92 3896.96 3591.75 794.02 1796.83 3088.12 999.55 593.41 1498.94 398.28 26
CPTT-MVS91.99 5691.80 5592.55 8498.24 2181.98 12496.76 1996.49 6881.89 19890.24 7896.44 4978.59 9998.61 8389.68 6397.85 5097.06 83
MP-MVS-pluss94.21 2394.00 2594.85 1498.17 2286.65 2194.82 8697.17 2286.26 9892.83 3697.87 285.57 3499.56 194.37 698.92 498.34 20
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
CNVR-MVS95.40 295.37 395.50 398.11 2388.51 395.29 6196.96 3592.09 395.32 797.08 2389.49 499.33 2395.10 298.85 698.66 4
114514_t89.51 10388.50 11192.54 8598.11 2381.99 12395.16 7096.36 7670.19 29785.81 13595.25 8476.70 11698.63 8182.07 15296.86 6597.00 84
ACMMPcopyleft93.24 4592.88 4694.30 3998.09 2585.33 5096.86 1797.45 688.33 6190.15 8097.03 2481.44 7199.51 1190.85 5695.74 7998.04 45
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
APD-MVScopyleft94.24 2194.07 2394.75 2398.06 2686.90 1295.88 3996.94 3785.68 10895.05 997.18 1987.31 1799.07 4191.90 4298.61 3198.28 26
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
CSCG93.23 4693.05 4093.76 5398.04 2784.07 7496.22 2897.37 884.15 13990.05 8195.66 7687.77 1199.15 3589.91 6298.27 4098.07 42
ACMMP_Plus94.74 994.56 1095.28 498.02 2887.70 495.68 4797.34 988.28 6395.30 897.67 385.90 3199.54 793.91 998.95 298.60 6
APD-MVS_3200maxsize93.78 3193.77 3093.80 5297.92 2984.19 7296.30 2696.87 4386.96 8793.92 1997.47 683.88 5198.96 6192.71 2197.87 4998.26 30
NCCC94.81 894.69 995.17 697.83 3087.46 895.66 4996.93 3892.34 293.94 1896.58 4387.74 1299.44 1792.83 1998.40 3798.62 5
CDPH-MVS92.83 5092.30 5294.44 3297.79 3186.11 3994.06 14096.66 5980.09 21892.77 3896.63 4086.62 2399.04 4687.40 8798.66 2698.17 34
DP-MVS87.25 17185.36 19092.90 7497.65 3283.24 9394.81 8892.00 24874.99 26481.92 22495.00 9072.66 17999.05 4366.92 28192.33 13696.40 99
PAPM_NR91.22 6990.78 7092.52 8697.60 3381.46 13294.37 11796.24 8286.39 9687.41 10594.80 9882.06 6798.48 8982.80 14195.37 8697.61 64
TEST997.53 3486.49 2694.07 13796.78 4881.61 20492.77 3896.20 5787.71 1399.12 38
train_agg93.44 3793.08 3994.52 3097.53 3486.49 2694.07 13796.78 4881.86 19992.77 3896.20 5787.63 1499.12 3892.14 3298.69 1997.94 50
abl_693.18 4793.05 4093.57 5697.52 3684.27 7195.53 5496.67 5887.85 7493.20 3197.22 1580.35 7899.18 3191.91 3997.21 5997.26 72
test_897.49 3786.30 3494.02 14396.76 5181.86 19992.70 4296.20 5787.63 1499.02 49
agg_prior393.27 4292.89 4594.40 3797.49 3786.12 3894.07 13796.73 5281.46 20792.46 5096.05 6486.90 2199.15 3592.14 3298.69 1997.94 50
DeepC-MVS_fast89.43 294.04 2593.79 2894.80 2097.48 3986.78 1595.65 5196.89 4089.40 3692.81 3796.97 2585.37 3699.24 2890.87 5598.69 1998.38 19
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
AdaColmapbinary89.89 9489.07 9792.37 9397.41 4083.03 9994.42 11095.92 10282.81 18086.34 12794.65 10173.89 16299.02 4980.69 17295.51 8295.05 140
agg_prior193.29 4192.97 4394.26 4097.38 4185.92 4193.92 14896.72 5481.96 19392.16 5496.23 5587.85 1098.97 5891.95 3898.55 3597.90 55
agg_prior97.38 4185.92 4196.72 5492.16 5498.97 58
原ACMM192.01 10397.34 4381.05 14496.81 4678.89 22890.45 7595.92 6782.65 5798.84 7380.68 17398.26 4196.14 105
MSLP-MVS++93.72 3294.08 2292.65 8097.31 4483.43 8995.79 4297.33 1290.03 2693.58 2596.96 2684.87 4397.76 12692.19 3098.66 2696.76 91
新几何193.10 6497.30 4584.35 7095.56 12771.09 29491.26 6996.24 5482.87 5698.86 6879.19 20398.10 4496.07 109
test_prior393.60 3593.53 3493.82 4997.29 4684.49 6194.12 12996.88 4187.67 7992.63 4396.39 5086.62 2398.87 6591.50 4698.67 2498.11 40
test_prior93.82 4997.29 4684.49 6196.88 4198.87 6598.11 40
112190.42 8389.49 8793.20 6097.27 4884.46 6492.63 20495.51 13471.01 29591.20 7096.21 5682.92 5599.05 4380.56 17598.07 4596.10 107
PLCcopyleft84.53 789.06 11988.03 12592.15 10097.27 4882.69 11394.29 12295.44 14379.71 22284.01 19294.18 11476.68 11798.75 7677.28 22093.41 12095.02 141
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
SD-MVS94.96 695.33 493.88 4797.25 5086.69 1896.19 2997.11 2690.42 2396.95 197.27 1189.53 396.91 20294.38 598.85 698.03 46
test1294.34 3897.13 5186.15 3796.29 7891.04 7285.08 3999.01 5298.13 4397.86 56
MG-MVS91.77 5991.70 5692.00 10597.08 5280.03 16893.60 16995.18 16487.85 7490.89 7396.47 4882.06 6798.36 9385.07 10997.04 6297.62 63
SteuartSystems-ACMMP95.20 495.32 594.85 1496.99 5386.33 3197.33 397.30 1591.38 1195.39 697.46 788.98 899.40 1894.12 798.89 598.82 2
Skip Steuart: Steuart Systems R&D Blog.
MVS_111021_HR93.45 3693.31 3693.84 4896.99 5384.84 5393.24 18597.24 1788.76 5191.60 6695.85 6986.07 2998.66 7891.91 3998.16 4298.03 46
CNLPA89.07 11787.98 12692.34 9496.87 5584.78 5594.08 13593.24 22481.41 20884.46 17995.13 8875.57 14196.62 21077.21 22193.84 11295.61 128
PHI-MVS93.89 3093.65 3294.62 2896.84 5686.43 2896.69 2197.49 485.15 11993.56 2796.28 5385.60 3399.31 2592.45 2298.79 998.12 39
旧先验196.79 5781.81 12595.67 11996.81 3186.69 2297.66 5396.97 85
LFMVS90.08 8789.13 9692.95 7296.71 5882.32 11996.08 3289.91 29086.79 9092.15 5696.81 3162.60 26098.34 9687.18 9193.90 11098.19 33
TAPA-MVS84.62 688.16 13987.01 15091.62 12196.64 5980.65 15494.39 11396.21 8676.38 25186.19 13095.44 7979.75 8698.08 11162.75 29595.29 8896.13 106
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
MAR-MVS90.30 8489.37 9093.07 6796.61 6084.48 6395.68 4795.67 11982.36 18787.85 9992.85 15676.63 11898.80 7480.01 18596.68 6895.91 115
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
VNet92.24 5591.91 5493.24 5996.59 6183.43 8994.84 8596.44 6989.19 4194.08 1695.90 6877.85 11098.17 10388.90 6993.38 12198.13 38
TSAR-MVS + GP.93.66 3493.41 3594.41 3596.59 6186.78 1594.40 11193.93 21489.77 3194.21 1395.59 7887.35 1698.61 8392.72 2096.15 7697.83 58
test22296.55 6381.70 12692.22 21895.01 16968.36 30190.20 7996.14 6180.26 8197.80 5196.05 111
DeepPCF-MVS89.96 194.20 2494.77 892.49 8796.52 6480.00 16994.00 14597.08 2790.05 2595.65 597.29 1089.66 298.97 5893.95 898.71 1798.50 9
testdata90.49 15496.40 6577.89 22795.37 15072.51 28493.63 2396.69 3682.08 6697.65 13183.08 13597.39 5795.94 114
PVSNet_Blended_VisFu91.38 6690.91 6792.80 7696.39 6683.17 9594.87 8496.66 5983.29 16189.27 8794.46 10580.29 8099.17 3287.57 8595.37 8696.05 111
API-MVS90.66 7790.07 7992.45 8996.36 6784.57 5996.06 3395.22 16382.39 18689.13 8894.27 11380.32 7998.46 9080.16 18496.71 6794.33 172
F-COLMAP87.95 14786.80 15791.40 12796.35 6880.88 15094.73 9295.45 14179.65 22382.04 22294.61 10271.13 19598.50 8876.24 23091.05 14294.80 153
VDD-MVS90.74 7589.92 8393.20 6096.27 6983.02 10095.73 4493.86 21588.42 6092.53 4696.84 2962.09 26398.64 8090.95 5492.62 13497.93 53
OMC-MVS91.23 6890.62 7193.08 6596.27 6984.07 7493.52 17195.93 10186.95 8889.51 8596.13 6278.50 10198.35 9585.84 10492.90 13196.83 90
CHOSEN 1792x268888.84 12487.69 13092.30 9596.14 7181.42 13490.01 25095.86 10974.52 26987.41 10593.94 12375.46 14398.36 9380.36 17995.53 8197.12 81
PVSNet_BlendedMVS89.98 8989.70 8490.82 14696.12 7281.25 13793.92 14896.83 4483.49 15589.10 8992.26 17481.04 7598.85 7186.72 10087.86 18492.35 251
PVSNet_Blended90.73 7690.32 7491.98 10696.12 7281.25 13792.55 20896.83 4482.04 19289.10 8992.56 16681.04 7598.85 7186.72 10095.91 7795.84 119
UA-Net92.83 5092.54 5093.68 5496.10 7484.71 5695.66 4996.39 7491.92 493.22 3096.49 4783.16 5398.87 6584.47 11795.47 8497.45 70
DeepC-MVS88.79 393.31 4092.99 4294.26 4096.07 7585.83 4594.89 8296.99 3089.02 4689.56 8497.37 882.51 5899.38 1992.20 2998.30 3997.57 66
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
LS3D87.89 14886.32 16892.59 8396.07 7582.92 10495.23 6594.92 17775.66 25882.89 21095.98 6572.48 18399.21 2968.43 27395.23 9095.64 127
HyFIR lowres test88.09 14286.81 15691.93 10996.00 7780.63 15590.01 25095.79 11273.42 27587.68 10392.10 18073.86 16397.96 11780.75 17191.70 13897.19 77
MVS_111021_LR92.47 5392.29 5392.98 7195.99 7884.43 6893.08 19096.09 9188.20 6591.12 7195.72 7581.33 7397.76 12691.74 4397.37 5896.75 92
PatchMatch-RL86.77 18385.54 18390.47 15695.88 7982.71 11290.54 24392.31 24079.82 22184.32 18691.57 19868.77 22596.39 22373.16 25393.48 11992.32 252
EPP-MVSNet91.70 6291.56 5792.13 10295.88 7980.50 16097.33 395.25 15786.15 10089.76 8395.60 7783.42 5298.32 9887.37 8993.25 12497.56 67
IS-MVSNet91.43 6591.09 6492.46 8895.87 8181.38 13596.95 993.69 21989.72 3389.50 8695.98 6578.57 10097.77 12583.02 13796.50 7398.22 32
PAPR90.02 8889.27 9492.29 9695.78 8280.95 14892.68 20396.22 8381.91 19686.66 12093.75 13482.23 6298.44 9279.40 20294.79 9397.48 69
Vis-MVSNet (Re-imp)89.59 10189.44 8990.03 17995.74 8375.85 24995.61 5290.80 27487.66 8187.83 10095.40 8176.79 11596.46 22078.37 20896.73 6697.80 59
canonicalmvs93.27 4292.75 4894.85 1495.70 8487.66 596.33 2596.41 7290.00 2794.09 1594.60 10382.33 6098.62 8292.40 2592.86 13298.27 28
MVS_030593.26 4492.88 4694.41 3595.67 8585.37 4994.82 8696.55 6791.88 590.44 7795.74 7379.90 8399.52 1092.90 1798.05 4698.33 21
3Dnovator+87.14 492.42 5491.37 5895.55 295.63 8688.73 297.07 896.77 5090.84 1684.02 19196.62 4175.95 13399.34 2087.77 8297.68 5298.59 7
alignmvs93.08 4892.50 5194.81 1995.62 8787.61 695.99 3596.07 9389.77 3194.12 1494.87 9380.56 7798.66 7892.42 2493.10 12798.15 36
Regformer-194.22 2294.13 2194.51 3195.54 8886.36 3094.57 10196.44 6991.69 994.32 1296.56 4587.05 2099.03 4793.35 1597.65 5498.15 36
Regformer-294.33 1894.22 1694.68 2595.54 8886.75 1794.57 10196.70 5691.84 694.41 1096.56 4587.19 1899.13 3793.50 1097.65 5498.16 35
WTY-MVS89.60 10088.92 10191.67 12095.47 9081.15 14292.38 21394.78 18483.11 16489.06 9194.32 10878.67 9896.61 21281.57 16190.89 14397.24 73
DELS-MVS93.43 3893.25 3793.97 4495.42 9185.04 5293.06 19297.13 2390.74 1991.84 6095.09 8986.32 2699.21 2991.22 4998.45 3697.65 62
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
Regformer-393.68 3393.64 3393.81 5195.36 9284.61 5794.68 9695.83 11091.27 1293.60 2496.71 3485.75 3298.86 6892.87 1896.65 6997.96 49
Regformer-493.91 2993.81 2794.19 4295.36 9285.47 4794.68 9696.41 7291.60 1093.75 2096.71 3485.95 3099.10 4093.21 1696.65 6998.01 48
Vis-MVSNetpermissive91.75 6091.23 6193.29 5795.32 9483.78 7996.14 3095.98 9889.89 2890.45 7596.58 4375.09 14798.31 9984.75 11496.90 6397.78 61
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
BH-RMVSNet88.37 13387.48 13391.02 14195.28 9579.45 18592.89 19893.07 22785.45 11286.91 11494.84 9770.35 20897.76 12673.97 24894.59 9895.85 118
COLMAP_ROBcopyleft80.39 1683.96 23382.04 23989.74 19095.28 9579.75 17594.25 12492.28 24175.17 26278.02 25893.77 13258.60 28397.84 12365.06 28885.92 19791.63 263
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
PS-MVSNAJ91.18 7090.92 6691.96 10795.26 9782.60 11692.09 22395.70 11886.27 9791.84 6092.46 16779.70 8898.99 5689.08 6795.86 7894.29 173
BH-untuned88.60 12988.13 12490.01 18195.24 9878.50 21293.29 18294.15 20084.75 12684.46 17993.40 13675.76 13897.40 16377.59 21794.52 10094.12 179
ab-mvs89.41 10988.35 11592.60 8295.15 9982.65 11492.20 21995.60 12583.97 14188.55 9493.70 13574.16 15998.21 10282.46 14789.37 16096.94 86
VDDNet89.56 10288.49 11392.76 7895.07 10082.09 12196.30 2693.19 22581.05 21291.88 5996.86 2861.16 27298.33 9788.43 7492.49 13597.84 57
AllTest83.42 23881.39 24289.52 19795.01 10177.79 23093.12 18790.89 27277.41 24476.12 27393.34 13754.08 29797.51 13968.31 27484.27 21293.26 223
TestCases89.52 19795.01 10177.79 23090.89 27277.41 24476.12 27393.34 13754.08 29797.51 13968.31 27484.27 21293.26 223
EI-MVSNet-Vis-set93.01 4992.92 4493.29 5795.01 10183.51 8894.48 10495.77 11390.87 1592.52 4796.67 3884.50 4699.00 5591.99 3594.44 10497.36 71
xiu_mvs_v2_base91.13 7190.89 6891.86 11294.97 10482.42 11792.24 21795.64 12486.11 10291.74 6593.14 14979.67 9198.89 6489.06 6895.46 8594.28 174
Test_1112_low_res87.65 15886.51 16491.08 13794.94 10579.28 19991.77 22694.30 19676.04 25683.51 20392.37 17177.86 10997.73 13078.69 20789.13 16696.22 103
1112_ss88.42 13187.33 13791.72 11894.92 10680.98 14692.97 19694.54 18978.16 24183.82 19593.88 12878.78 9697.91 12179.45 19889.41 15996.26 102
QAPM89.51 10388.15 12393.59 5594.92 10684.58 5896.82 1896.70 5678.43 23683.41 20596.19 6073.18 17399.30 2677.11 22396.54 7296.89 89
BH-w/o87.57 16287.05 14989.12 20794.90 10877.90 22692.41 21193.51 22182.89 17983.70 19891.34 20375.75 13997.07 19175.49 23493.49 11792.39 249
EI-MVSNet-UG-set92.74 5292.62 4993.12 6394.86 10983.20 9494.40 11195.74 11690.71 2092.05 5796.60 4284.00 4998.99 5691.55 4593.63 11497.17 78
HY-MVS83.01 1289.03 12087.94 12892.29 9694.86 10982.77 10692.08 22494.49 19081.52 20686.93 11392.79 16278.32 10498.23 10079.93 18890.55 14495.88 117
Fast-Effi-MVS+89.41 10988.64 10791.71 11994.74 11180.81 15293.54 17095.10 16683.11 16486.82 11890.67 22279.74 8797.75 12980.51 17793.55 11596.57 96
ACMP84.23 889.01 12288.35 11590.99 14394.73 11281.27 13695.07 7495.89 10786.48 9483.67 19994.30 10969.33 22197.99 11687.10 9688.55 17193.72 204
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PVSNet78.82 1885.55 20484.65 20488.23 23694.72 11371.93 27687.12 28292.75 23378.80 23184.95 17190.53 22764.43 25596.71 20874.74 24293.86 11196.06 110
LCM-MVSNet-Re88.30 13688.32 11888.27 23394.71 11472.41 27593.15 18690.98 26987.77 7679.25 25291.96 18678.35 10395.75 24883.04 13695.62 8096.65 94
HQP_MVS90.60 8190.19 7691.82 11594.70 11582.73 11095.85 4096.22 8390.81 1786.91 11494.86 9474.23 15598.12 10688.15 7689.99 15094.63 156
plane_prior794.70 11582.74 109
ACMH+81.04 1485.05 21383.46 22589.82 18694.66 11779.37 19394.44 10894.12 20282.19 18978.04 25792.82 15958.23 28497.54 13773.77 25082.90 22692.54 243
ACMM84.12 989.14 11588.48 11491.12 13494.65 11881.22 13995.31 5796.12 9085.31 11585.92 13494.34 10670.19 21198.06 11385.65 10588.86 16994.08 183
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
plane_prior194.59 119
3Dnovator86.66 591.73 6190.82 6994.44 3294.59 11986.37 2997.18 697.02 2989.20 4084.31 18796.66 3973.74 16699.17 3286.74 9797.96 4897.79 60
plane_prior694.52 12182.75 10774.23 155
UGNet89.95 9188.95 10092.95 7294.51 12283.31 9295.70 4695.23 16189.37 3787.58 10493.94 12364.00 25698.78 7583.92 12896.31 7596.74 93
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
LPG-MVS_test89.45 10688.90 10291.12 13494.47 12381.49 13095.30 5996.14 8786.73 9185.45 15695.16 8669.89 21298.10 10887.70 8389.23 16493.77 200
LGP-MVS_train91.12 13494.47 12381.49 13096.14 8786.73 9185.45 15695.16 8669.89 21298.10 10887.70 8389.23 16493.77 200
ACMH80.38 1785.36 20683.68 21890.39 15794.45 12580.63 15594.73 9294.85 18082.09 19077.24 26392.65 16460.01 27897.58 13472.25 25784.87 20792.96 232
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LTVRE_ROB82.13 1386.26 19284.90 19890.34 16194.44 12681.50 12992.31 21594.89 17883.03 17179.63 24992.67 16369.69 21697.79 12471.20 26186.26 19691.72 262
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
MVS_Test91.31 6791.11 6291.93 10994.37 12780.14 16493.46 17395.80 11186.46 9591.35 6893.77 13282.21 6398.09 11087.57 8594.95 9297.55 68
NP-MVS94.37 12782.42 11793.98 121
TR-MVS86.78 18185.76 18189.82 18694.37 12778.41 21492.47 21092.83 23081.11 21186.36 12692.40 17068.73 22697.48 14173.75 25189.85 15493.57 214
Effi-MVS+91.59 6491.11 6293.01 6994.35 13083.39 9194.60 10095.10 16687.10 8690.57 7493.10 15181.43 7298.07 11289.29 6694.48 10197.59 65
CLD-MVS89.47 10588.90 10291.18 13394.22 13182.07 12292.13 22196.09 9187.90 7285.37 16592.45 16874.38 15397.56 13687.15 9290.43 14593.93 187
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
HQP-NCC94.17 13294.39 11388.81 4885.43 159
ACMP_Plane94.17 13294.39 11388.81 4885.43 159
HQP-MVS89.80 9589.28 9391.34 12894.17 13281.56 12794.39 11396.04 9688.81 4885.43 15993.97 12273.83 16497.96 11787.11 9489.77 15594.50 167
XVG-OURS89.40 11188.70 10691.52 12394.06 13581.46 13291.27 23896.07 9386.14 10188.89 9295.77 7268.73 22697.26 17687.39 8889.96 15295.83 120
sss88.93 12388.26 12290.94 14594.05 13680.78 15391.71 22995.38 14881.55 20588.63 9393.91 12775.04 14895.47 25982.47 14691.61 13996.57 96
PCF-MVS84.11 1087.74 15686.08 17492.70 7994.02 13784.43 6889.27 26195.87 10873.62 27484.43 18194.33 10778.48 10298.86 6870.27 26594.45 10394.81 152
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
GBi-Net87.26 16985.98 17691.08 13794.01 13883.10 9695.14 7194.94 17383.57 15184.37 18291.64 19166.59 24096.34 22678.23 21185.36 20293.79 196
test187.26 16985.98 17691.08 13794.01 13883.10 9695.14 7194.94 17383.57 15184.37 18291.64 19166.59 24096.34 22678.23 21185.36 20293.79 196
FMVSNet287.19 17485.82 18091.30 13094.01 13883.67 8294.79 8994.94 17383.57 15183.88 19392.05 18466.59 24096.51 21677.56 21885.01 20693.73 203
XVG-OURS-SEG-HR89.95 9189.45 8891.47 12594.00 14181.21 14091.87 22596.06 9585.78 10488.55 9495.73 7474.67 15197.27 17488.71 7189.64 15795.91 115
FIs90.51 8290.35 7390.99 14393.99 14280.98 14695.73 4497.54 389.15 4286.72 11994.68 9981.83 7097.24 17885.18 10888.31 17994.76 154
xiu_mvs_v1_base_debu90.64 7890.05 8092.40 9093.97 14384.46 6493.32 17695.46 13785.17 11692.25 5194.03 11670.59 20498.57 8590.97 5194.67 9494.18 175
xiu_mvs_v1_base90.64 7890.05 8092.40 9093.97 14384.46 6493.32 17695.46 13785.17 11692.25 5194.03 11670.59 20498.57 8590.97 5194.67 9494.18 175
xiu_mvs_v1_base_debi90.64 7890.05 8092.40 9093.97 14384.46 6493.32 17695.46 13785.17 11692.25 5194.03 11670.59 20498.57 8590.97 5194.67 9494.18 175
VPA-MVSNet89.62 9988.96 9991.60 12293.86 14682.89 10595.46 5597.33 1287.91 7188.43 9693.31 14174.17 15897.40 16387.32 9082.86 22794.52 165
MVSFormer91.68 6391.30 5992.80 7693.86 14683.88 7795.96 3695.90 10584.66 12891.76 6394.91 9177.92 10797.30 17089.64 6497.11 6097.24 73
lupinMVS90.92 7390.21 7593.03 6893.86 14683.88 7792.81 19993.86 21579.84 22091.76 6394.29 11077.92 10798.04 11490.48 6097.11 6097.17 78
IterMVS-LS88.36 13487.91 12989.70 19293.80 14978.29 21893.73 16095.08 16885.73 10684.75 17391.90 18879.88 8496.92 20183.83 13082.51 22993.89 189
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MSDG84.86 22083.09 23090.14 17093.80 14980.05 16789.18 26493.09 22678.89 22878.19 25591.91 18765.86 24997.27 17468.47 27288.45 17593.11 229
FMVSNet387.40 16786.11 17291.30 13093.79 15183.64 8394.20 12794.81 18383.89 14284.37 18291.87 18968.45 23196.56 21378.23 21185.36 20293.70 205
FC-MVSNet-test90.27 8590.18 7790.53 15093.71 15279.85 17395.77 4397.59 289.31 3886.27 12894.67 10081.93 6997.01 19584.26 12288.09 18294.71 155
TAMVS89.21 11488.29 12091.96 10793.71 15282.62 11593.30 18094.19 19882.22 18887.78 10293.94 12378.83 9596.95 20077.70 21692.98 12996.32 100
CDS-MVSNet89.45 10688.51 11092.29 9693.62 15483.61 8593.01 19394.68 18681.95 19487.82 10193.24 14578.69 9796.99 19680.34 18093.23 12596.28 101
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
UniMVSNet (Re)89.80 9589.07 9792.01 10393.60 15584.52 6094.78 9097.47 589.26 3986.44 12592.32 17382.10 6597.39 16684.81 11380.84 25794.12 179
VPNet88.20 13887.47 13490.39 15793.56 15679.46 18394.04 14195.54 13088.67 5386.96 11294.58 10469.33 22197.15 18484.05 12680.53 26194.56 163
mvs_anonymous89.37 11289.32 9189.51 19993.47 15774.22 25591.65 23294.83 18282.91 17885.45 15693.79 13181.23 7496.36 22586.47 10394.09 10897.94 50
UniMVSNet_NR-MVSNet89.92 9389.29 9291.81 11793.39 15883.72 8094.43 10997.12 2489.80 3086.46 12293.32 14083.16 5397.23 18084.92 11081.02 25394.49 169
Effi-MVS+-dtu88.65 12888.35 11589.54 19693.33 15976.39 24494.47 10694.36 19387.70 7785.43 15989.56 24373.45 16997.26 17685.57 10691.28 14194.97 143
mvs-test189.45 10689.14 9590.38 15993.33 15977.63 23594.95 7994.36 19387.70 7787.10 11192.81 16073.45 16998.03 11585.57 10693.04 12895.48 130
WR-MVS88.38 13287.67 13190.52 15293.30 16180.18 16293.26 18495.96 10088.57 5785.47 15592.81 16076.12 12296.91 20281.24 16382.29 23194.47 170
MVS_dtu89.71 9788.60 10993.01 6993.24 16283.54 8693.30 18094.05 20388.15 6686.91 11494.12 11569.51 21999.02 4983.89 12994.25 10796.48 98
diffmvs89.07 11788.32 11891.34 12893.24 16279.79 17492.29 21694.98 17280.24 21587.38 10892.45 16878.02 10597.33 16883.29 13492.93 13096.91 87
WR-MVS_H87.80 15487.37 13689.10 20993.23 16478.12 22195.61 5297.30 1587.90 7283.72 19792.01 18579.65 9296.01 23776.36 22780.54 26093.16 227
test_040281.30 25979.17 26387.67 24593.19 16578.17 22092.98 19591.71 25375.25 26176.02 27690.31 23159.23 28196.37 22450.22 31283.63 21988.47 304
OPM-MVS90.12 8689.56 8691.82 11593.14 16683.90 7694.16 12895.74 11688.96 4787.86 9895.43 8072.48 18397.91 12188.10 7990.18 14993.65 206
CP-MVSNet87.63 16087.26 14088.74 21493.12 16776.59 24395.29 6196.58 6588.43 5983.49 20492.98 15475.28 14495.83 24478.97 20481.15 25093.79 196
MVS_test032689.70 9888.72 10592.63 8193.09 16882.94 10393.45 17495.39 14788.13 6886.14 13293.33 13969.86 21498.94 6283.99 12795.11 9196.00 113
nrg03091.08 7290.39 7293.17 6293.07 16986.91 1196.41 2496.26 7988.30 6288.37 9794.85 9682.19 6497.64 13391.09 5082.95 22594.96 146
PAPM86.68 18485.39 18990.53 15093.05 17079.33 19889.79 25494.77 18578.82 23081.95 22393.24 14576.81 11497.30 17066.94 27993.16 12694.95 147
DU-MVS89.34 11388.50 11191.85 11393.04 17183.72 8094.47 10696.59 6489.50 3586.46 12293.29 14377.25 11197.23 18084.92 11081.02 25394.59 160
NR-MVSNet88.58 13087.47 13491.93 10993.04 17184.16 7394.77 9196.25 8189.05 4380.04 24693.29 14379.02 9497.05 19381.71 16080.05 26694.59 160
jason90.80 7490.10 7892.90 7493.04 17183.53 8793.08 19094.15 20080.22 21691.41 6794.91 9176.87 11397.93 12090.28 6196.90 6397.24 73
jason: jason.
PS-CasMVS87.32 16886.88 15288.63 21792.99 17476.33 24695.33 5696.61 6388.22 6483.30 20793.07 15273.03 17595.79 24778.36 20981.00 25593.75 202
MVSTER88.84 12488.29 12090.51 15392.95 17580.44 16193.73 16095.01 16984.66 12887.15 10993.12 15072.79 17797.21 18287.86 8187.36 18893.87 192
RPSCF85.07 21284.27 20687.48 25192.91 17670.62 28891.69 23192.46 23876.20 25582.67 21395.22 8563.94 25797.29 17377.51 21985.80 19994.53 164
FMVSNet185.85 19884.11 20891.08 13792.81 17783.10 9695.14 7194.94 17381.64 20282.68 21291.64 19159.01 28296.34 22675.37 23683.78 21593.79 196
OpenMVScopyleft83.78 1188.74 12787.29 13893.08 6592.70 17885.39 4896.57 2296.43 7178.74 23380.85 23496.07 6369.64 21799.01 5278.01 21496.65 6994.83 151
TranMVSNet+NR-MVSNet88.84 12487.95 12791.49 12492.68 17983.01 10194.92 8196.31 7789.88 2985.53 15093.85 13076.63 11896.96 19981.91 15679.87 27194.50 167
MVS87.44 16586.10 17391.44 12692.61 18083.62 8492.63 20495.66 12167.26 30581.47 22792.15 17677.95 10698.22 10179.71 19495.48 8392.47 246
CHOSEN 280x42085.15 21183.99 21088.65 21692.47 18178.40 21579.68 31492.76 23274.90 26681.41 22989.59 24169.85 21595.51 25579.92 18995.29 8892.03 256
131487.51 16386.57 16390.34 16192.42 18279.74 17692.63 20495.35 15278.35 23780.14 24491.62 19574.05 16097.15 18481.05 16493.53 11694.12 179
pcd1.5k->3k37.02 30638.84 30731.53 31992.33 1830.00 3380.00 32996.13 890.00 3330.00 3340.00 33572.70 1780.00 3360.00 33388.43 17694.60 159
PEN-MVS86.80 18086.27 17088.40 23092.32 18475.71 25095.18 6896.38 7587.97 6982.82 21193.15 14873.39 17195.92 24076.15 23179.03 27493.59 213
Patchmatch-test185.81 20084.71 20289.12 20792.15 18576.60 24291.12 24191.69 25583.53 15485.50 15388.56 25566.79 23895.00 27572.69 25590.35 14795.76 123
XXY-MVS87.65 15886.85 15490.03 17992.14 18680.60 15793.76 15795.23 16182.94 17684.60 17594.02 11974.27 15495.49 25881.04 16583.68 21894.01 186
IB-MVS80.51 1585.24 21083.26 22991.19 13292.13 18779.86 17291.75 22791.29 26483.28 16280.66 23788.49 25661.28 26898.46 9080.99 16879.46 27395.25 137
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
cascas86.43 19084.98 19590.80 14792.10 18880.92 14990.24 24695.91 10473.10 27883.57 20288.39 25765.15 25197.46 14384.90 11291.43 14094.03 185
Fast-Effi-MVS+-dtu87.44 16586.72 16089.63 19492.04 18977.68 23494.03 14293.94 21385.81 10382.42 21491.32 20670.33 20997.06 19280.33 18190.23 14894.14 178
PS-MVSNAJss89.97 9089.62 8591.02 14191.90 19080.85 15195.26 6495.98 9886.26 9886.21 12994.29 11079.70 8897.65 13188.87 7088.10 18094.57 162
ITE_SJBPF88.24 23591.88 19177.05 23992.92 22885.54 11080.13 24593.30 14257.29 28796.20 23072.46 25684.71 20891.49 265
EI-MVSNet89.10 11688.86 10489.80 18991.84 19278.30 21793.70 16495.01 16985.73 10687.15 10995.28 8279.87 8597.21 18283.81 13187.36 18893.88 191
CVMVSNet84.69 22784.79 20184.37 28391.84 19264.92 30693.70 16491.47 26066.19 30786.16 13195.28 8267.18 23793.33 29080.89 17090.42 14694.88 149
MVS-HIRNet73.70 28372.20 28378.18 29791.81 19456.42 31882.94 30882.58 31855.24 31768.88 30166.48 31855.32 29395.13 27158.12 30388.42 17783.01 311
PatchmatchNetpermissive85.85 19884.70 20389.29 20491.76 19575.54 25188.49 27191.30 26381.63 20385.05 16988.70 25271.71 18796.24 22974.61 24489.05 16796.08 108
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
TransMVSNet (Re)84.43 23083.06 23188.54 22691.72 19678.44 21395.18 6892.82 23182.73 18279.67 24892.12 17773.49 16895.96 23971.10 26468.73 30891.21 270
semantic-postprocess88.18 23791.71 19776.87 24192.65 23685.40 11381.44 22890.54 22666.21 24495.00 27581.04 16581.05 25192.66 241
TinyColmap79.76 26977.69 26985.97 27191.71 19773.12 26489.55 25590.36 28075.03 26372.03 29690.19 23246.22 31196.19 23163.11 29381.03 25288.59 300
MDTV_nov1_ep1383.56 22191.69 19969.93 29287.75 27891.54 25878.60 23484.86 17288.90 24869.54 21896.03 23570.25 26688.93 168
DTE-MVSNet86.11 19385.48 18787.98 24091.65 20074.92 25394.93 8095.75 11587.36 8482.26 21693.04 15372.85 17695.82 24574.04 24777.46 27993.20 225
PatchFormer-LS_test86.02 19485.13 19388.70 21591.52 20174.12 25891.19 24092.09 24482.71 18384.30 18887.24 27270.87 19996.98 19781.04 16585.17 20595.00 142
MIMVSNet82.59 24680.53 24988.76 21391.51 20278.32 21686.57 28590.13 28479.32 22480.70 23688.69 25352.98 29993.07 29566.03 28488.86 16994.90 148
tpmp4_e2383.87 23682.33 23788.48 22791.46 20372.82 26789.82 25391.57 25773.02 28081.86 22589.05 24666.20 24596.97 19871.57 25986.39 19595.66 126
pm-mvs186.61 18585.54 18389.82 18691.44 20480.18 16295.28 6394.85 18083.84 14381.66 22692.62 16572.45 18596.48 21879.67 19578.06 27692.82 238
Baseline_NR-MVSNet87.07 17686.63 16288.40 23091.44 20477.87 22894.23 12692.57 23784.12 14085.74 14192.08 18177.25 11196.04 23482.29 15079.94 26991.30 269
IterMVS84.88 21983.98 21187.60 24691.44 20476.03 24890.18 24892.41 23983.24 16381.06 23390.42 23066.60 23994.28 28079.46 19780.98 25692.48 245
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DWT-MVSNet_test84.95 21783.68 21888.77 21291.43 20773.75 26191.74 22890.98 26980.66 21483.84 19487.36 27062.44 26197.11 18878.84 20685.81 19895.46 131
MS-PatchMatch85.05 21384.16 20787.73 24491.42 20878.51 21191.25 23993.53 22077.50 24380.15 24391.58 19661.99 26495.51 25575.69 23394.35 10689.16 294
v1684.96 21683.74 21588.62 21891.40 20979.48 18193.83 15194.04 20483.03 17176.54 26786.59 27676.11 12595.42 26180.33 18171.80 29290.95 276
tpm284.08 23282.94 23287.48 25191.39 21071.27 28089.23 26390.37 27971.95 28884.64 17489.33 24467.30 23496.55 21575.17 23887.09 19294.63 156
v1neww87.98 14487.25 14190.16 16591.38 21179.41 18794.37 11795.28 15384.48 13185.77 13791.53 20076.12 12297.45 14584.45 11981.89 23893.61 211
v7new87.98 14487.25 14190.16 16591.38 21179.41 18794.37 11795.28 15384.48 13185.77 13791.53 20076.12 12297.45 14584.45 11981.89 23893.61 211
v887.50 16486.71 16189.89 18491.37 21379.40 19194.50 10395.38 14884.81 12583.60 20191.33 20476.05 12697.42 15682.84 14080.51 26392.84 236
v1884.97 21583.76 21388.60 22091.36 21479.41 18793.82 15394.04 20483.00 17476.61 26686.60 27576.19 12095.43 26080.39 17871.79 29390.96 274
v1784.93 21883.70 21788.62 21891.36 21479.48 18193.83 15194.03 20683.04 17076.51 26886.57 27776.05 12695.42 26180.31 18371.65 29490.96 274
v687.98 14487.25 14190.16 16591.36 21479.39 19294.37 11795.27 15684.48 13185.78 13691.51 20276.15 12197.46 14384.46 11881.88 24093.62 210
ADS-MVSNet281.66 25279.71 25887.50 24991.35 21774.19 25683.33 30588.48 30172.90 28182.24 21785.77 28764.98 25293.20 29264.57 28983.74 21695.12 138
ADS-MVSNet81.56 25479.78 25686.90 26391.35 21771.82 27783.33 30589.16 29772.90 28182.24 21785.77 28764.98 25293.76 28464.57 28983.74 21695.12 138
V984.77 22383.50 22488.58 22191.33 21979.46 18393.75 15894.00 21083.07 16676.07 27586.43 27875.97 13195.37 26479.91 19070.93 30090.91 278
GA-MVS86.61 18585.27 19290.66 14891.33 21978.71 21090.40 24493.81 21885.34 11485.12 16889.57 24261.25 26997.11 18880.99 16889.59 15896.15 104
v1284.74 22483.46 22588.58 22191.32 22179.50 17893.75 15894.01 20783.06 16775.98 27786.41 28275.82 13795.36 26679.87 19170.89 30190.89 280
v1184.67 22883.41 22888.44 22991.32 22179.13 20693.69 16793.99 21282.81 18076.20 27186.24 28575.48 14295.35 26779.53 19671.48 29690.85 282
V1484.79 22183.52 22388.57 22491.32 22179.43 18693.72 16294.01 20783.06 16776.22 27086.43 27876.01 13095.37 26479.96 18770.99 29890.91 278
v1384.72 22683.44 22788.58 22191.31 22479.52 17793.77 15694.00 21083.03 17175.85 27886.38 28375.84 13695.35 26779.83 19270.95 29990.87 281
v1584.79 22183.53 22288.57 22491.30 22579.41 18793.70 16494.01 20783.06 16776.27 26986.42 28176.03 12995.38 26380.01 18571.00 29790.92 277
v114187.84 15087.09 14590.11 17591.23 22679.25 20194.08 13595.24 15884.44 13585.69 14491.31 20775.91 13497.44 15284.17 12481.74 24493.63 209
divwei89l23v2f11287.84 15087.09 14590.10 17791.23 22679.24 20394.09 13395.24 15884.44 13585.70 14291.31 20775.91 13497.44 15284.17 12481.73 24593.64 207
v187.85 14987.10 14490.11 17591.21 22879.24 20394.09 13395.24 15884.44 13585.70 14291.31 20775.96 13297.45 14584.18 12381.73 24593.64 207
v787.75 15586.96 15190.12 17191.20 22979.50 17894.28 12395.46 13783.45 15685.75 13991.56 19975.13 14597.43 15483.60 13282.18 23393.42 220
XVG-ACMP-BASELINE86.00 19584.84 20089.45 20091.20 22978.00 22391.70 23095.55 12885.05 12182.97 20992.25 17554.49 29597.48 14182.93 13887.45 18792.89 234
v1087.25 17186.38 16589.85 18591.19 23179.50 17894.48 10495.45 14183.79 14683.62 20091.19 21175.13 14597.42 15681.94 15580.60 25992.63 242
FMVSNet581.52 25579.60 25987.27 25391.17 23277.95 22491.49 23492.26 24276.87 24976.16 27287.91 26551.67 30092.34 29767.74 27881.16 24891.52 264
USDC82.76 24381.26 24487.26 25491.17 23274.55 25489.27 26193.39 22378.26 23975.30 28092.08 18154.43 29696.63 20971.64 25885.79 20090.61 284
CostFormer85.77 20184.94 19788.26 23491.16 23472.58 27489.47 25991.04 26876.26 25486.45 12489.97 23670.74 20296.86 20582.35 14887.07 19395.34 136
tpm cat181.96 24980.27 25187.01 26091.09 23571.02 28487.38 28191.53 25966.25 30680.17 24286.35 28468.22 23396.15 23269.16 26982.29 23193.86 194
tpmvs83.35 24182.07 23887.20 25991.07 23671.00 28588.31 27391.70 25478.91 22780.49 24087.18 27369.30 22497.08 19068.12 27783.56 22093.51 218
v114487.61 16186.79 15890.06 17891.01 23779.34 19593.95 14795.42 14683.36 16085.66 14691.31 20774.98 14997.42 15683.37 13382.06 23493.42 220
v2v48287.84 15087.06 14890.17 16490.99 23879.23 20594.00 14595.13 16584.87 12385.53 15092.07 18374.45 15297.45 14584.71 11581.75 24393.85 195
SixPastTwentyTwo83.91 23482.90 23386.92 26290.99 23870.67 28793.48 17291.99 24985.54 11077.62 26192.11 17960.59 27496.87 20476.05 23277.75 27793.20 225
test-LLR85.87 19785.41 18887.25 25590.95 24071.67 27889.55 25589.88 29183.41 15784.54 17787.95 26367.25 23595.11 27281.82 15793.37 12294.97 143
test-mter84.54 22983.64 22087.25 25590.95 24071.67 27889.55 25589.88 29179.17 22584.54 17787.95 26355.56 29195.11 27281.82 15793.37 12294.97 143
v14887.04 17786.32 16889.21 20690.94 24277.26 23793.71 16394.43 19184.84 12484.36 18590.80 22076.04 12897.05 19382.12 15179.60 27293.31 222
mvs_tets88.06 14387.28 13990.38 15990.94 24279.88 17195.22 6695.66 12185.10 12084.21 19093.94 12363.53 25897.40 16388.50 7388.40 17893.87 192
MVP-Stereo85.97 19684.86 19989.32 20390.92 24482.19 12092.11 22294.19 19878.76 23278.77 25491.63 19468.38 23296.56 21375.01 24193.95 10989.20 293
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
Patchmatch-test81.37 25779.30 26187.58 24790.92 24474.16 25780.99 31187.68 30770.52 29676.63 26588.81 24971.21 19492.76 29660.01 30286.93 19495.83 120
jajsoiax88.24 13787.50 13290.48 15590.89 24680.14 16495.31 5795.65 12384.97 12284.24 18994.02 11965.31 25097.42 15688.56 7288.52 17393.89 189
tpmrst85.35 20784.99 19486.43 26890.88 24767.88 29888.71 26891.43 26180.13 21786.08 13388.80 25073.05 17496.02 23682.48 14583.40 22495.40 133
gg-mvs-nofinetune81.77 25079.37 26088.99 21090.85 24877.73 23386.29 28679.63 32474.88 26783.19 20869.05 31760.34 27596.11 23375.46 23594.64 9793.11 229
OurMVSNet-221017-085.35 20784.64 20587.49 25090.77 24972.59 27394.01 14494.40 19284.72 12779.62 25093.17 14761.91 26596.72 20681.99 15481.16 24893.16 227
v119287.25 17186.33 16790.00 18290.76 25079.04 20793.80 15495.48 13682.57 18585.48 15491.18 21273.38 17297.42 15682.30 14982.06 23493.53 215
test_djsdf89.03 12088.64 10790.21 16390.74 25179.28 19995.96 3695.90 10584.66 12885.33 16692.94 15574.02 16197.30 17089.64 6488.53 17294.05 184
v7n86.81 17985.76 18189.95 18390.72 25279.25 20195.07 7495.92 10284.45 13482.29 21590.86 21972.60 18197.53 13879.42 20180.52 26293.08 231
PVSNet_073.20 2077.22 27674.83 27984.37 28390.70 25371.10 28383.09 30789.67 29472.81 28373.93 28783.13 29860.79 27393.70 28568.54 27150.84 32088.30 305
DI_MVS_plusplus_test88.15 14086.82 15592.14 10190.67 25481.07 14393.01 19394.59 18883.83 14577.78 25990.63 22368.51 22998.16 10488.02 8094.37 10597.17 78
v14419287.19 17486.35 16689.74 19090.64 25578.24 21993.92 14895.43 14481.93 19585.51 15291.05 21774.21 15797.45 14582.86 13981.56 24793.53 215
V4287.68 15786.86 15390.15 16990.58 25680.14 16494.24 12595.28 15383.66 14885.67 14591.33 20474.73 15097.41 16184.43 12181.83 24192.89 234
CR-MVSNet85.35 20783.76 21390.12 17190.58 25679.34 19585.24 29491.96 25078.27 23885.55 14887.87 26671.03 19795.61 25073.96 24989.36 16195.40 133
RPMNet83.18 24280.87 24890.12 17190.58 25679.34 19585.24 29490.78 27571.44 29085.55 14882.97 29970.87 19995.61 25061.01 29889.36 16195.40 133
test_normal88.13 14186.78 15992.18 9990.55 25981.19 14192.74 20194.64 18783.84 14377.49 26290.51 22868.49 23098.16 10488.22 7594.55 9997.21 76
v192192086.97 17886.06 17589.69 19390.53 26078.11 22293.80 15495.43 14481.90 19785.33 16691.05 21772.66 17997.41 16182.05 15381.80 24293.53 215
v124086.78 18185.85 17989.56 19590.45 26177.79 23093.61 16895.37 15081.65 20185.43 15991.15 21471.50 19297.43 15481.47 16282.05 23693.47 219
tpm84.73 22584.02 20986.87 26590.33 26268.90 29589.06 26589.94 28980.85 21385.75 13989.86 23868.54 22895.97 23877.76 21584.05 21495.75 124
EG-PatchMatch MVS82.37 24880.34 25088.46 22890.27 26379.35 19492.80 20094.33 19577.14 24873.26 29190.18 23347.47 30996.72 20670.25 26687.32 19089.30 291
v74886.27 19185.28 19189.25 20590.26 26477.58 23694.89 8295.50 13584.28 13881.41 22990.46 22972.57 18297.32 16979.81 19378.36 27592.84 236
EPNet_dtu86.49 18985.94 17888.14 23890.24 26572.82 26794.11 13192.20 24386.66 9379.42 25192.36 17273.52 16795.81 24671.26 26093.66 11395.80 122
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
EPMVS83.90 23582.70 23687.51 24890.23 26672.67 27088.62 27081.96 32081.37 20985.01 17088.34 25866.31 24394.45 27875.30 23787.12 19195.43 132
EPNet91.79 5891.02 6594.10 4390.10 26785.25 5196.03 3492.05 24692.83 187.39 10795.78 7179.39 9399.01 5288.13 7897.48 5698.05 44
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PatchT82.68 24581.27 24386.89 26490.09 26870.94 28684.06 30190.15 28374.91 26585.63 14783.57 29569.37 22094.87 27765.19 28688.50 17494.84 150
Patchmtry82.71 24480.93 24788.06 23990.05 26976.37 24584.74 29691.96 25072.28 28681.32 23187.87 26671.03 19795.50 25768.97 27080.15 26592.32 252
pmmvs485.43 20583.86 21290.16 16590.02 27082.97 10290.27 24592.67 23575.93 25780.73 23591.74 19071.05 19695.73 24978.85 20583.46 22291.78 259
TESTMET0.1,183.74 23782.85 23486.42 26989.96 27171.21 28289.55 25587.88 30477.41 24483.37 20687.31 27156.71 28893.65 28680.62 17492.85 13394.40 171
dp81.47 25680.23 25285.17 27889.92 27265.49 30586.74 28390.10 28576.30 25381.10 23287.12 27462.81 25995.92 24068.13 27679.88 27094.09 182
K. test v381.59 25380.15 25485.91 27289.89 27369.42 29492.57 20787.71 30685.56 10973.44 28989.71 24055.58 29095.52 25477.17 22269.76 30492.78 239
MDA-MVSNet-bldmvs78.85 27476.31 27586.46 26789.76 27473.88 26088.79 26790.42 27879.16 22659.18 31488.33 25960.20 27694.04 28262.00 29668.96 30691.48 266
GG-mvs-BLEND87.94 24289.73 27577.91 22587.80 27678.23 32680.58 23883.86 29359.88 27995.33 26971.20 26192.22 13790.60 286
gm-plane-assit89.60 27668.00 29777.28 24788.99 24797.57 13579.44 199
v5286.50 18785.53 18689.39 20189.17 27778.99 20894.72 9595.54 13083.59 14982.10 21990.60 22571.59 19097.45 14582.52 14379.99 26891.73 261
anonymousdsp87.84 15087.09 14590.12 17189.13 27880.54 15894.67 9895.55 12882.05 19183.82 19592.12 17771.47 19397.15 18487.15 9287.80 18592.67 240
V486.50 18785.54 18389.39 20189.13 27878.99 20894.73 9295.54 13083.59 14982.10 21990.61 22471.60 18997.45 14582.52 14380.01 26791.74 260
N_pmnet68.89 29068.44 29170.23 30689.07 28028.79 33488.06 27419.50 33569.47 29971.86 29784.93 29061.24 27091.75 30254.70 30677.15 28090.15 287
pmmvs584.21 23182.84 23588.34 23288.95 28176.94 24092.41 21191.91 25275.63 25980.28 24191.18 21264.59 25495.57 25277.09 22483.47 22192.53 244
PMMVS85.71 20384.96 19687.95 24188.90 28277.09 23888.68 26990.06 28672.32 28586.47 12190.76 22172.15 18694.40 27981.78 15993.49 11792.36 250
JIA-IIPM81.04 26078.98 26687.25 25588.64 28373.48 26381.75 31089.61 29573.19 27782.05 22173.71 31466.07 24895.87 24371.18 26384.60 20992.41 248
Gipumacopyleft57.99 29854.91 29967.24 31188.51 28465.59 30452.21 32790.33 28143.58 32342.84 32251.18 32520.29 33085.07 32034.77 32570.45 30251.05 324
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
EU-MVSNet81.32 25880.95 24682.42 29188.50 28563.67 30793.32 17691.33 26264.02 31180.57 23992.83 15861.21 27192.27 29876.34 22880.38 26491.32 268
lessismore_v086.04 27088.46 28668.78 29680.59 32273.01 29290.11 23455.39 29296.43 22275.06 24065.06 31092.90 233
test0.0.03 182.41 24781.69 24084.59 28188.23 28772.89 26690.24 24687.83 30583.41 15779.86 24789.78 23967.25 23588.99 30865.18 28783.42 22391.90 258
MDA-MVSNet_test_wron79.21 27377.19 27385.29 27688.22 28872.77 26985.87 28990.06 28674.34 27062.62 31387.56 26966.14 24691.99 30066.90 28273.01 28791.10 273
YYNet179.22 27277.20 27285.28 27788.20 28972.66 27185.87 28990.05 28874.33 27162.70 31287.61 26866.09 24792.03 29966.94 27972.97 28891.15 271
Test485.75 20283.72 21691.83 11488.08 29081.03 14592.48 20995.54 13083.38 15973.40 29088.57 25450.99 30297.37 16786.61 10294.47 10297.09 82
pmmvs683.42 23881.60 24188.87 21188.01 29177.87 22894.96 7894.24 19774.67 26878.80 25391.09 21660.17 27796.49 21777.06 22575.40 28492.23 254
testgi80.94 26380.20 25383.18 28787.96 29266.29 30291.28 23790.70 27783.70 14778.12 25692.84 15751.37 30190.82 30563.34 29282.46 23092.43 247
LP75.51 28072.15 28485.61 27487.86 29373.93 25980.20 31388.43 30267.39 30270.05 29980.56 30758.18 28593.18 29346.28 31870.36 30389.71 290
Anonymous2023120681.03 26179.77 25784.82 28087.85 29470.26 29091.42 23592.08 24573.67 27377.75 26089.25 24562.43 26293.08 29461.50 29782.00 23791.12 272
OpenMVS_ROBcopyleft74.94 1979.51 27077.03 27486.93 26187.00 29576.23 24792.33 21490.74 27668.93 30074.52 28488.23 26049.58 30496.62 21057.64 30484.29 21187.94 306
LF4IMVS80.37 26579.07 26584.27 28586.64 29669.87 29389.39 26091.05 26776.38 25174.97 28290.00 23547.85 30894.25 28174.55 24580.82 25888.69 299
MIMVSNet179.38 27177.28 27185.69 27386.35 29773.67 26291.61 23392.75 23378.11 24272.64 29488.12 26148.16 30791.97 30160.32 29977.49 27891.43 267
test20.0379.95 26779.08 26482.55 29085.79 29867.74 29991.09 24291.08 26581.23 21074.48 28589.96 23761.63 26690.15 30660.08 30076.38 28189.76 288
Patchmatch-RL test81.67 25179.96 25586.81 26685.42 29971.23 28182.17 30987.50 30978.47 23577.19 26482.50 30070.81 20193.48 28882.66 14272.89 28995.71 125
UnsupCasMVSNet_eth80.07 26678.27 26885.46 27585.24 30072.63 27288.45 27294.87 17982.99 17571.64 29888.07 26256.34 28991.75 30273.48 25263.36 31592.01 257
testing_283.40 24081.02 24590.56 14985.06 30180.51 15991.37 23695.57 12682.92 17767.06 30685.54 28949.47 30597.24 17886.74 9785.44 20193.93 187
pmmvs-eth3d80.97 26278.72 26787.74 24384.99 30279.97 17090.11 24991.65 25675.36 26073.51 28886.03 28659.45 28093.96 28375.17 23872.21 29089.29 292
testpf71.41 28872.11 28569.30 30884.53 30359.79 31162.74 32483.14 31771.11 29368.83 30381.57 30546.70 31084.83 32174.51 24675.86 28363.30 319
CMPMVSbinary59.16 2180.52 26479.20 26284.48 28283.98 30467.63 30089.95 25293.84 21764.79 31066.81 30791.14 21557.93 28695.17 27076.25 22988.10 18090.65 283
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
UnsupCasMVSNet_bld76.23 27973.27 28185.09 27983.79 30572.92 26585.65 29393.47 22271.52 28968.84 30279.08 31049.77 30393.21 29166.81 28360.52 31789.13 296
PM-MVS78.11 27576.12 27784.09 28683.54 30670.08 29188.97 26685.27 31479.93 21974.73 28386.43 27834.70 32093.48 28879.43 20072.06 29188.72 298
DSMNet-mixed76.94 27776.29 27678.89 29483.10 30756.11 31987.78 27779.77 32360.65 31575.64 27988.71 25161.56 26788.34 31060.07 30189.29 16392.21 255
Anonymous2023121172.97 28469.63 28983.00 28983.05 30866.91 30192.69 20289.45 29661.06 31467.50 30583.46 29634.34 32193.61 28751.11 30963.97 31388.48 303
new_pmnet72.15 28670.13 28778.20 29582.95 30965.68 30383.91 30282.40 31962.94 31364.47 31079.82 30942.85 31486.26 31657.41 30574.44 28682.65 312
new-patchmatchnet76.41 27875.17 27880.13 29382.65 31059.61 31287.66 27991.08 26578.23 24069.85 30083.22 29754.76 29491.63 30464.14 29164.89 31189.16 294
testus74.41 28273.35 28077.59 29982.49 31157.08 31586.02 28790.21 28272.28 28672.89 29384.32 29237.08 31886.96 31452.24 30882.65 22888.73 297
test235674.50 28173.27 28178.20 29580.81 31259.84 31083.76 30488.33 30371.43 29172.37 29581.84 30345.60 31286.26 31650.97 31084.32 21088.50 301
ambc83.06 28879.99 31363.51 30877.47 31792.86 22974.34 28684.45 29128.74 32295.06 27473.06 25468.89 30790.61 284
111170.54 28969.71 28873.04 30379.30 31444.83 32784.23 29988.96 29867.33 30365.42 30882.28 30141.11 31688.11 31147.12 31671.60 29586.19 308
.test124557.63 29961.79 29645.14 31779.30 31444.83 32784.23 29988.96 29867.33 30365.42 30882.28 30141.11 31688.11 31147.12 3160.39 3312.46 330
TDRefinement79.81 26877.34 27087.22 25879.24 31675.48 25293.12 18792.03 24776.45 25075.01 28191.58 19649.19 30696.44 22170.22 26869.18 30589.75 289
test123567872.22 28570.31 28677.93 29878.04 31758.04 31485.76 29189.80 29370.15 29863.43 31180.20 30842.24 31587.24 31348.68 31474.50 28588.50 301
pmmvs371.81 28768.71 29081.11 29275.86 31870.42 28986.74 28383.66 31658.95 31668.64 30480.89 30636.93 31989.52 30763.10 29463.59 31483.39 310
DeepMVS_CXcopyleft56.31 31574.23 31951.81 32356.67 33344.85 32148.54 32075.16 31227.87 32458.74 33140.92 32252.22 31958.39 323
test1235664.99 29363.78 29268.61 31072.69 32039.14 33078.46 31587.61 30864.91 30955.77 31577.48 31128.10 32385.59 31844.69 31964.35 31281.12 314
FPMVS64.63 29462.55 29470.88 30570.80 32156.71 31684.42 29884.42 31551.78 31949.57 31881.61 30423.49 32781.48 32340.61 32376.25 28274.46 318
PMMVS259.60 29656.40 29869.21 30968.83 32246.58 32573.02 32277.48 32755.07 31849.21 31972.95 31617.43 33280.04 32449.32 31344.33 32180.99 315
testmv65.49 29262.66 29373.96 30268.78 32353.14 32284.70 29788.56 30065.94 30852.35 31774.65 31325.02 32685.14 31943.54 32060.40 31883.60 309
PNet_i23d50.48 30247.18 30260.36 31368.59 32444.56 32972.75 32372.61 32843.92 32233.91 32560.19 3236.16 33473.52 32738.50 32428.04 32463.01 320
wuyk23d21.27 30920.48 31023.63 32168.59 32436.41 33249.57 3286.85 3369.37 3297.89 3314.46 3344.03 33731.37 33217.47 33016.07 3303.12 328
no-one61.56 29556.58 29776.49 30167.80 32662.76 30978.13 31686.11 31063.16 31243.24 32164.70 32026.12 32588.95 30950.84 31129.15 32377.77 316
E-PMN43.23 30442.29 30446.03 31665.58 32737.41 33173.51 31964.62 32933.99 32628.47 32847.87 32619.90 33167.91 32822.23 32824.45 32632.77 325
LCM-MVSNet66.00 29162.16 29577.51 30064.51 32858.29 31383.87 30390.90 27148.17 32054.69 31673.31 31516.83 33386.75 31565.47 28561.67 31687.48 307
EMVS42.07 30541.12 30544.92 31863.45 32935.56 33373.65 31863.48 33033.05 32726.88 32945.45 32821.27 32967.14 32919.80 32923.02 32832.06 326
wuykxyi23d50.55 30144.13 30369.81 30756.77 33054.58 32173.22 32180.78 32139.79 32522.08 33046.69 3274.03 33779.71 32547.65 31526.13 32575.14 317
MVEpermissive39.65 2343.39 30338.59 30857.77 31456.52 33148.77 32455.38 32658.64 33229.33 32828.96 32752.65 3244.68 33664.62 33028.11 32733.07 32259.93 322
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
ANet_high58.88 29754.22 30072.86 30456.50 33256.67 31780.75 31286.00 31173.09 27937.39 32364.63 32122.17 32879.49 32643.51 32123.96 32782.43 313
PMVScopyleft47.18 2252.22 30048.46 30163.48 31245.72 33346.20 32673.41 32078.31 32541.03 32430.06 32665.68 3196.05 33583.43 32230.04 32665.86 30960.80 321
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
tmp_tt35.64 30739.24 30624.84 32014.87 33423.90 33562.71 32551.51 3346.58 33036.66 32462.08 32244.37 31330.34 33352.40 30722.00 32920.27 327
testmvs8.92 31011.52 3111.12 3231.06 3350.46 33786.02 2870.65 3370.62 3312.74 3329.52 3320.31 3400.45 3352.38 3310.39 3312.46 330
test1238.76 31111.22 3121.39 3220.85 3360.97 33685.76 2910.35 3380.54 3322.45 3338.14 3330.60 3390.48 3342.16 3320.17 3332.71 329
cdsmvs_eth3d_5k22.14 30829.52 3090.00 3240.00 3370.00 3380.00 32995.76 1140.00 3330.00 33494.29 11075.66 1400.00 3360.00 3330.00 3340.00 332
pcd_1.5k_mvsjas6.64 3138.86 3140.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 33579.70 880.00 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-re7.82 31210.43 3130.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 33493.88 1280.00 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_mvs171.70 188
sam_mvs70.60 203
MTGPAbinary96.97 32
test_post188.00 2759.81 33169.31 22395.53 25376.65 226
test_post10.29 33070.57 20795.91 242
patchmatchnet-post83.76 29471.53 19196.48 218
MTMP60.64 331
test9_res91.91 3998.71 1798.07 42
agg_prior290.54 5898.68 2298.27 28
test_prior485.96 4094.11 131
test_prior294.12 12987.67 7992.63 4396.39 5086.62 2391.50 4698.67 24
旧先验293.36 17571.25 29294.37 1197.13 18786.74 97
新几何293.11 189
无先验93.28 18396.26 7973.95 27299.05 4380.56 17596.59 95
原ACMM292.94 197
testdata298.75 7678.30 210
segment_acmp87.16 19
testdata192.15 22087.94 70
plane_prior596.22 8398.12 10688.15 7689.99 15094.63 156
plane_prior494.86 94
plane_prior382.75 10790.26 2486.91 114
plane_prior295.85 4090.81 17
plane_prior82.73 11095.21 6789.66 3489.88 153
n20.00 339
nn0.00 339
door-mid85.49 312
test1196.57 66
door85.33 313
HQP5-MVS81.56 127
BP-MVS87.11 94
HQP4-MVS85.43 15997.96 11794.51 166
HQP3-MVS96.04 9689.77 155
HQP2-MVS73.83 164
MDTV_nov1_ep13_2view55.91 32087.62 28073.32 27684.59 17670.33 20974.65 24395.50 129
ACMMP++_ref87.47 186
ACMMP++88.01 183
Test By Simon80.02 82