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-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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
#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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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_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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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_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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
.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
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)
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
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
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)
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
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
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
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
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
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
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
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
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
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
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
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
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
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
MTMP60.64 331
gm-plane-assit89.60 27668.00 29777.28 24788.99 24797.57 13579.44 199
test9_res91.91 3998.71 1798.07 42
TEST997.53 3486.49 2694.07 13796.78 4881.61 20492.77 3896.20 5787.71 1399.12 38
test_897.49 3786.30 3494.02 14396.76 5181.86 19992.70 4296.20 5787.63 1499.02 49
agg_prior290.54 5898.68 2298.27 28
agg_prior97.38 4185.92 4196.72 5492.16 5498.97 58
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
test_prior485.96 4094.11 131
test_prior294.12 12987.67 7992.63 4396.39 5086.62 2391.50 4698.67 24
test_prior93.82 4997.29 4684.49 6196.88 4198.87 6598.11 40
旧先验293.36 17571.25 29294.37 1197.13 18786.74 97
新几何293.11 189
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
旧先验196.79 5781.81 12595.67 11996.81 3186.69 2297.66 5396.97 85
无先验93.28 18396.26 7973.95 27299.05 4380.56 17596.59 95
原ACMM292.94 197
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
test22296.55 6381.70 12692.22 21895.01 16968.36 30190.20 7996.14 6180.26 8197.80 5196.05 111
testdata298.75 7678.30 210
segment_acmp87.16 19
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
testdata192.15 22087.94 70
test1294.34 3897.13 5186.15 3796.29 7891.04 7285.08 3999.01 5298.13 4397.86 56
plane_prior794.70 11582.74 109
plane_prior694.52 12182.75 10774.23 155
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_prior194.59 119
plane_prior82.73 11095.21 6789.66 3489.88 153
n20.00 339
nn0.00 339
door-mid85.49 312
lessismore_v086.04 27088.46 28668.78 29680.59 32273.01 29290.11 23455.39 29296.43 22275.06 24065.06 31092.90 233
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
test1196.57 66
door85.33 313
HQP5-MVS81.56 127
HQP-NCC94.17 13294.39 11388.81 4885.43 159
ACMP_Plane94.17 13294.39 11388.81 4885.43 159
BP-MVS87.11 94
HQP4-MVS85.43 15997.96 11794.51 166
HQP3-MVS96.04 9689.77 155
HQP2-MVS73.83 164
NP-MVS94.37 12782.42 11793.98 121
MDTV_nov1_ep13_2view55.91 32087.62 28073.32 27684.59 17670.33 20974.65 24395.50 129
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
ACMMP++_ref87.47 186
ACMMP++88.01 183
Test By Simon80.02 82
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
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