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 bysorted bysort bysort bysort bysort by
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
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
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
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
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
SteuartSystems-ACMMP95.20 495.32 594.85 1496.99 5386.33 3197.33 397.30 1591.38 1195.39 697.46 788.98 899.40 1894.12 798.89 598.82 2
Skip Steuart: Steuart Systems R&D Blog.
HPM-MVS++95.14 594.91 795.83 198.25 1989.65 195.92 3896.96 3591.75 794.02 1796.83 3088.12 999.55 593.41 1498.94 398.28 26
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
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
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
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
test_897.49 3786.30 3494.02 14396.76 5181.86 19992.70 4296.20 5787.63 1499.02 49
TSAR-MVS + GP.93.66 3493.41 3594.41 3596.59 6186.78 1594.40 11193.93 21489.77 3194.21 1395.59 7887.35 1698.61 8392.72 2096.15 7697.83 58
APD-MVScopyleft94.24 2194.07 2394.75 2398.06 2686.90 1295.88 3996.94 3785.68 10895.05 997.18 1987.31 1799.07 4191.90 4298.61 3198.28 26
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
Regformer-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
segment_acmp87.16 19
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
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
旧先验196.79 5781.81 12595.67 11996.81 3186.69 2297.66 5396.97 85
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
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
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
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
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
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
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
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
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
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
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
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
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
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
test1294.34 3897.13 5186.15 3796.29 7891.04 7285.08 3999.01 5298.13 4397.86 56
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
test22296.55 6381.70 12692.22 21895.01 16968.36 30190.20 7996.14 6180.26 8197.80 5196.05 111
Test By Simon80.02 82
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
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.
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
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
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
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
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
PS-MVSNAJ91.18 7090.92 6691.96 10795.26 9782.60 11692.09 22395.70 11886.27 9791.84 6092.46 16779.70 8898.99 5689.08 6795.86 7894.29 173
xiu_mvs_v2_base91.13 7190.89 6891.86 11294.97 10482.42 11792.24 21795.64 12486.11 10291.74 6593.14 14979.67 9198.89 6489.06 6895.46 8594.28 174
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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_prior694.52 12182.75 10774.23 155
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
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
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
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
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
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
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
HQP2-MVS73.83 164
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
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
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
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
Effi-MVS+-dtu88.65 12888.35 11589.54 19693.33 15976.39 24494.47 10694.36 19387.70 7785.43 15989.56 24373.45 16997.26 17685.57 10691.28 14194.97 143
mvs-test189.45 10689.14 9590.38 15993.33 15977.63 23594.95 7994.36 19387.70 7787.10 11192.81 16073.45 16998.03 11585.57 10693.04 12895.48 130
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
sam_mvs171.70 188
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
patchmatchnet-post83.76 29471.53 19196.48 218
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
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
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
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
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
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
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
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
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
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
sam_mvs70.60 203
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
test_post10.29 33070.57 20795.91 242
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
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
MDTV_nov1_ep13_2view55.91 32087.62 28073.32 27684.59 17670.33 20974.65 24395.50 129
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
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_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
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
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
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
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
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
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
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
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_post188.00 2759.81 33169.31 22395.53 25376.65 226
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
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
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
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
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
DI_MVS_plusplus_test88.15 14086.82 15592.14 10190.67 25481.07 14393.01 19394.59 18883.83 14577.78 25990.63 22368.51 22998.16 10488.02 8094.37 10597.17 78
test_normal88.13 14186.78 15992.18 9990.55 25981.19 14192.74 20194.64 18783.84 14377.49 26290.51 22868.49 23098.16 10488.22 7594.55 9997.21 76
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
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.
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
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
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
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
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
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.
GBi-Net87.26 16985.98 17691.08 13794.01 13883.10 9695.14 7194.94 17383.57 15184.37 18291.64 19166.59 24096.34 22678.23 21185.36 20293.79 196
test187.26 16985.98 17691.08 13794.01 13883.10 9695.14 7194.94 17383.57 15184.37 18291.64 19166.59 24096.34 22678.23 21185.36 20293.79 196
FMVSNet287.19 17485.82 18091.30 13094.01 13883.67 8294.79 8994.94 17383.57 15183.88 19392.05 18466.59 24096.51 21677.56 21885.01 20693.73 203
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
lessismore_v086.04 27088.46 28668.78 29680.59 32273.01 29290.11 23455.39 29296.43 22275.06 24065.06 31092.90 233
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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)
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)
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
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
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
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
MTGPAbinary96.97 32
MTMP60.64 331
gm-plane-assit89.60 27668.00 29777.28 24788.99 24797.57 13579.44 199
test9_res91.91 3998.71 1798.07 42
agg_prior290.54 5898.68 2298.27 28
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
testdata192.15 22087.94 70
plane_prior794.70 11582.74 109
plane_prior596.22 8398.12 10688.15 7689.99 15094.63 156
plane_prior494.86 94
plane_prior382.75 10790.26 2486.91 114
plane_prior295.85 4090.81 17
plane_prior194.59 119
plane_prior82.73 11095.21 6789.66 3489.88 153
n20.00 339
nn0.00 339
door-mid85.49 312
test1196.57 66
door85.33 313
HQP5-MVS81.56 127
HQP-NCC94.17 13294.39 11388.81 4885.43 159
ACMP_Plane94.17 13294.39 11388.81 4885.43 159
BP-MVS87.11 94
HQP4-MVS85.43 15997.96 11794.51 166
HQP3-MVS96.04 9689.77 155
NP-MVS94.37 12782.42 11793.98 121
ACMMP++_ref87.47 186
ACMMP++88.01 183