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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort bysort bysort by
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
无先验93.28 18396.26 7973.95 27299.05 4380.56 17596.59 95
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
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
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
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
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
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
test_897.49 3786.30 3494.02 14396.76 5181.86 19992.70 4296.20 5787.63 1499.02 49
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
test1294.34 3897.13 5186.15 3796.29 7891.04 7285.08 3999.01 5298.13 4397.86 56
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
testdata298.75 7678.30 210
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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_prior596.22 8398.12 10688.15 7689.99 15094.63 156
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
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
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
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
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
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
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
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
HQP4-MVS85.43 15997.96 11794.51 166
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
gm-plane-assit89.60 27668.00 29777.28 24788.99 24797.57 13579.44 199
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
旧先验293.36 17571.25 29294.37 1197.13 18786.74 97
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
patchmatchnet-post83.76 29471.53 19196.48 218
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
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
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
lessismore_v086.04 27088.46 28668.78 29680.59 32273.01 29290.11 23455.39 29296.43 22275.06 24065.06 31092.90 233
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
test_post10.29 33070.57 20795.91 242
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
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
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
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
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
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
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
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
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
test_post188.00 2759.81 33169.31 22395.53 25376.65 226
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)
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
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
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
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
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
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)
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
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
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
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
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
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
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
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
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
新几何293.11 189
旧先验196.79 5781.81 12595.67 11996.81 3186.69 2297.66 5396.97 85
原ACMM292.94 197
test22296.55 6381.70 12692.22 21895.01 16968.36 30190.20 7996.14 6180.26 8197.80 5196.05 111
segment_acmp87.16 19
testdata192.15 22087.94 70
plane_prior794.70 11582.74 109
plane_prior694.52 12182.75 10774.23 155
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
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
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
ACMMP++_ref87.47 186
ACMMP++88.01 183
Test By Simon80.02 82