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

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

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

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

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




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort by
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
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
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
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
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.
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
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
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
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
ACMMPR94.43 1494.28 1494.91 1098.63 286.69 1896.94 1097.32 1488.63 5493.53 2897.26 1385.04 4099.54 792.35 2698.78 1198.50 9
HFP-MVS94.52 1094.40 1194.86 1298.61 386.81 1396.94 1097.34 988.63 5493.65 2197.21 1686.10 2799.49 1392.35 2698.77 1298.30 24
#test#94.32 1994.14 2094.86 1298.61 386.81 1396.43 2397.34 987.51 8293.65 2197.21 1686.10 2799.49 1391.68 4498.77 1298.30 24
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
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
test9_res91.91 3998.71 1798.07 42
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
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
agg_prior393.27 4292.89 4594.40 3797.49 3786.12 3894.07 13796.73 5281.46 20792.46 5096.05 6486.90 2199.15 3592.14 3298.69 1997.94 50
DeepC-MVS_fast89.43 294.04 2593.79 2894.80 2097.48 3986.78 1595.65 5196.89 4089.40 3692.81 3796.97 2585.37 3699.24 2890.87 5598.69 1998.38 19
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
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
agg_prior290.54 5898.68 2298.27 28
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_prior294.12 12987.67 7992.63 4396.39 5086.62 2391.50 4698.67 24
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
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
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
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
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
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
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
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
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
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
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
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
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
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
test1294.34 3897.13 5186.15 3796.29 7891.04 7285.08 3999.01 5298.13 4397.86 56
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
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
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
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
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
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
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
test22296.55 6381.70 12692.22 21895.01 16968.36 30190.20 7996.14 6180.26 8197.80 5196.05 111
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
旧先验196.79 5781.81 12595.67 11996.81 3186.69 2297.66 5396.97 85
Regformer-194.22 2294.13 2194.51 3195.54 8886.36 3094.57 10196.44 6991.69 994.32 1296.56 4587.05 2099.03 4793.35 1597.65 5498.15 36
Regformer-294.33 1894.22 1694.68 2595.54 8886.75 1794.57 10196.70 5691.84 694.41 1096.56 4587.19 1899.13 3793.50 1097.65 5498.16 35
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
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
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
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
MVSFormer91.68 6391.30 5992.80 7693.86 14683.88 7795.96 3695.90 10584.66 12891.76 6394.91 9177.92 10797.30 17089.64 6497.11 6097.24 73
lupinMVS90.92 7390.21 7593.03 6893.86 14683.88 7792.81 19993.86 21579.84 22091.76 6394.29 11077.92 10798.04 11490.48 6097.11 6097.17 78
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
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.
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
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
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
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
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
Regformer-393.68 3393.64 3393.81 5195.36 9284.61 5794.68 9695.83 11091.27 1293.60 2496.71 3485.75 3298.86 6892.87 1896.65 6997.96 49
Regformer-493.91 2993.81 2794.19 4295.36 9285.47 4794.68 9696.41 7291.60 1093.75 2096.71 3485.95 3099.10 4093.21 1696.65 6998.01 48
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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_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
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.
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
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
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
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
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
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
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
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
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
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
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
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-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
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
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
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
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-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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
plane_prior82.73 11095.21 6789.66 3489.88 153
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
HQP3-MVS96.04 9689.77 155
HQP-MVS89.80 9589.28 9391.34 12894.17 13281.56 12794.39 11396.04 9688.81 4885.43 15993.97 12273.83 16497.96 11787.11 9489.77 15594.50 167
XVG-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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
ACMMP++88.01 183
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
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
ACMMP++_ref87.47 186
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
ADS-MVSNet281.66 25279.71 25887.50 24991.35 21774.19 25683.33 30588.48 30172.90 28182.24 21785.77 28764.98 25293.20 29264.57 28983.74 21695.12 138
ADS-MVSNet81.56 25479.78 25686.90 26391.35 21771.82 27783.33 30589.16 29772.90 28182.24 21785.77 28764.98 25293.76 28464.57 28983.74 21695.12 138
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_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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
v114187.84 15087.09 14590.11 17591.23 22679.25 20194.08 13595.24 15884.44 13585.69 14491.31 20775.91 13497.44 15284.17 12481.74 24493.63 209
divwei89l23v2f11287.84 15087.09 14590.10 17791.23 22679.24 20394.09 13395.24 15884.44 13585.70 14291.31 20775.91 13497.44 15284.17 12481.73 24593.64 207
v187.85 14987.10 14490.11 17591.21 22879.24 20394.09 13395.24 15884.44 13585.70 14291.31 20775.96 13297.45 14584.18 12381.73 24593.64 207
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
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
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
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
semantic-postprocess88.18 23791.71 19776.87 24192.65 23685.40 11381.44 22890.54 22666.21 24495.00 27581.04 16581.05 25192.66 241
TinyColmap79.76 26977.69 26985.97 27191.71 19773.12 26489.55 25590.36 28075.03 26372.03 29690.19 23246.22 31196.19 23163.11 29381.03 25288.59 300
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
MDA-MVSNet_test_wron79.21 27377.19 27385.29 27688.22 28872.77 26985.87 28990.06 28674.34 27062.62 31387.56 26966.14 24691.99 30066.90 28273.01 28791.10 273
YYNet179.22 27277.20 27285.28 27788.20 28972.66 27185.87 28990.05 28874.33 27162.70 31287.61 26866.09 24792.03 29966.94 27972.97 28891.15 271
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)
lessismore_v086.04 27088.46 28668.78 29680.59 32273.01 29290.11 23455.39 29296.43 22275.06 24065.06 31092.90 233
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
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
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
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
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
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
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
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
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
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
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
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)
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
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
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
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
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
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
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
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
.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
testmvs8.92 31011.52 3111.12 3231.06 3350.46 33786.02 2870.65 3370.62 3312.74 3329.52 3320.31 3400.45 3352.38 3310.39 3312.46 330
test1238.76 31111.22 3121.39 3220.85 3360.97 33685.76 2910.35 3380.54 3322.45 3338.14 3330.60 3390.48 3342.16 3320.17 3332.71 329
cdsmvs_eth3d_5k22.14 30829.52 3090.00 3240.00 3370.00 3380.00 32995.76 1140.00 3330.00 33494.29 11075.66 1400.00 3360.00 3330.00 3340.00 332
pcd_1.5k_mvsjas6.64 3138.86 3140.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 33579.70 880.00 3360.00 3330.00 3340.00 332
sosnet-low-res0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
sosnet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
uncertanet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
Regformer0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
ab-mvs-re7.82 31210.43 3130.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 33493.88 1280.00 3410.00 3360.00 3330.00 3340.00 332
uanet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
sam_mvs171.70 188
sam_mvs70.60 203
MTGPAbinary96.97 32
test_post188.00 2759.81 33169.31 22395.53 25376.65 226
test_post10.29 33070.57 20795.91 242
patchmatchnet-post83.76 29471.53 19196.48 218
MTMP60.64 331
gm-plane-assit89.60 27668.00 29777.28 24788.99 24797.57 13579.44 199
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_prior97.38 4185.92 4196.72 5492.16 5498.97 58
test_prior485.96 4094.11 131
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
无先验93.28 18396.26 7973.95 27299.05 4380.56 17596.59 95
原ACMM292.94 197
testdata298.75 7678.30 210
segment_acmp87.16 19
testdata192.15 22087.94 70
plane_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
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
HQP4-MVS85.43 15997.96 11794.51 166
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
Test By Simon80.02 82