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 bysorted bysort bysort by
HSP-MVS89.28 189.76 187.85 1794.28 1573.46 1492.90 892.73 3680.27 1291.35 194.16 2078.35 296.77 889.59 194.22 4193.33 51
APDe-MVS89.15 289.63 287.73 1994.49 871.69 4093.83 293.96 275.70 7091.06 296.03 176.84 397.03 489.09 295.65 1394.47 11
MP-MVS-pluss87.67 1287.72 1187.54 2593.64 2672.04 3789.80 5593.50 975.17 8186.34 1695.29 270.86 3796.00 3288.78 396.04 394.58 7
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
CNVR-MVS88.93 489.13 488.33 394.77 273.82 690.51 3993.00 2480.90 988.06 994.06 2476.43 496.84 688.48 495.99 494.34 14
TSAR-MVS + MP.88.02 1088.11 887.72 2193.68 2572.13 3691.41 2692.35 4774.62 8788.90 593.85 2775.75 896.00 3287.80 594.63 3195.04 2
ACMMP_Plus88.05 988.08 987.94 1093.70 2373.05 1890.86 3393.59 776.27 6488.14 795.09 371.06 3696.67 1287.67 696.37 294.09 21
SD-MVS88.06 788.50 786.71 3992.60 4872.71 2491.81 2393.19 1877.87 3190.32 394.00 2574.83 1093.78 11387.63 794.27 4093.65 40
SteuartSystems-ACMMP88.72 588.86 588.32 492.14 5272.96 1993.73 393.67 680.19 1488.10 894.80 473.76 2097.11 287.51 895.82 894.90 4
Skip Steuart: Steuart Systems R&D Blog.
HPM-MVS++89.02 389.15 388.63 195.01 176.03 192.38 1492.85 3280.26 1387.78 1194.27 1675.89 796.81 787.45 996.44 193.05 61
MPTG87.53 1487.41 1587.90 1494.18 1974.25 290.23 4792.02 5779.45 1885.88 1894.80 468.07 5696.21 2686.69 1095.34 1793.23 53
MTAPA87.23 2087.00 2087.90 1494.18 1974.25 286.58 15992.02 5779.45 1885.88 1894.80 468.07 5696.21 2686.69 1095.34 1793.23 53
DeepPCF-MVS80.84 188.10 688.56 686.73 3892.24 5069.03 7889.57 6093.39 1377.53 3889.79 494.12 2278.98 196.58 1985.66 1295.72 994.58 7
MP-MVScopyleft87.71 1187.64 1287.93 1394.36 1473.88 492.71 1392.65 3977.57 3483.84 4794.40 1572.24 3096.28 2485.65 1395.30 2193.62 42
HPM-MVS87.11 2286.98 2187.50 2693.88 2272.16 3592.19 1893.33 1476.07 6783.81 4893.95 2669.77 4796.01 3185.15 1494.66 3094.32 15
train_agg86.43 3086.20 3187.13 3293.26 3372.96 1988.75 8391.89 6668.69 18585.00 2793.10 3974.43 1395.41 4784.97 1595.71 1093.02 62
agg_prior386.16 3585.85 3787.10 3393.31 3072.86 2388.77 8191.68 7668.29 19184.26 4292.83 4772.83 2595.42 4684.97 1595.71 1093.02 62
test9_res84.90 1795.70 1292.87 67
NCCC88.06 788.01 1088.24 594.41 1273.62 791.22 3092.83 3381.50 685.79 2193.47 3373.02 2497.00 584.90 1794.94 2494.10 20
MCST-MVS87.37 1887.25 1687.73 1994.53 772.46 3189.82 5393.82 473.07 11584.86 3492.89 4576.22 596.33 2284.89 1995.13 2294.40 12
DeepC-MVS79.81 287.08 2486.88 2487.69 2391.16 6272.32 3490.31 4593.94 377.12 4382.82 5994.23 1872.13 3197.09 384.83 2095.37 1693.65 40
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
agg_prior186.22 3486.09 3486.62 4192.85 4171.94 3888.59 8891.78 7268.96 18284.41 3993.18 3874.94 994.93 6484.75 2195.33 1993.01 64
HFP-MVS87.58 1387.47 1487.94 1094.58 573.54 1193.04 593.24 1576.78 5184.91 2994.44 1270.78 3896.61 1584.53 2294.89 2693.66 35
ACMMPR87.44 1587.23 1788.08 794.64 373.59 893.04 593.20 1776.78 5184.66 3594.52 768.81 5496.65 1384.53 2294.90 2594.00 27
Regformer-286.63 2986.53 2786.95 3589.33 9171.24 4388.43 9192.05 5682.50 186.88 1490.09 9374.45 1295.61 3884.38 2490.63 6794.01 26
region2R87.42 1787.20 1888.09 694.63 473.55 993.03 793.12 2076.73 5484.45 3894.52 769.09 5296.70 1184.37 2594.83 2894.03 24
APD-MVScopyleft87.44 1587.52 1387.19 3094.24 1672.39 3291.86 2292.83 3373.01 11688.58 694.52 773.36 2196.49 2084.26 2695.01 2392.70 68
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
CP-MVS87.11 2286.92 2287.68 2494.20 1873.86 593.98 192.82 3576.62 5683.68 4994.46 1167.93 5895.95 3484.20 2794.39 3693.23 53
MVS_030586.01 3685.56 3987.36 2890.03 7870.65 5489.55 6192.48 4081.57 580.80 8091.10 7267.18 6697.13 184.06 2893.27 4594.30 16
Regformer-186.41 3286.33 2886.64 4089.33 9170.93 4888.43 9191.39 8682.14 386.65 1590.09 9374.39 1595.01 6383.97 2990.63 6793.97 28
#test#87.33 1987.13 1987.94 1094.58 573.54 1192.34 1593.24 1575.23 7884.91 2994.44 1270.78 3896.61 1583.75 3094.89 2693.66 35
test_prior386.73 2686.86 2586.33 4592.61 4669.59 7088.85 7892.97 2975.41 7484.91 2993.54 2974.28 1795.48 4283.31 3195.86 693.91 29
test_prior288.85 7875.41 7484.91 2993.54 2974.28 1783.31 3195.86 6
Regformer-485.68 4285.45 4086.35 4488.95 10469.67 6988.29 10091.29 8881.73 485.36 2390.01 9572.62 2795.35 5283.28 3387.57 10094.03 24
PHI-MVS86.43 3086.17 3387.24 2990.88 6770.96 4692.27 1794.07 172.45 12785.22 2591.90 5769.47 4996.42 2183.28 3395.94 594.35 13
XVS87.18 2186.91 2388.00 894.42 1073.33 1692.78 992.99 2679.14 2083.67 5094.17 1967.45 6396.60 1783.06 3594.50 3394.07 22
X-MVStestdata80.37 11577.83 15188.00 894.42 1073.33 1692.78 992.99 2679.14 2083.67 5012.47 32967.45 6396.60 1783.06 3594.50 3394.07 22
APD-MVS_3200maxsize85.97 3785.88 3586.22 4892.69 4469.53 7291.93 2192.99 2673.54 10385.94 1794.51 1065.80 7895.61 3883.04 3792.51 5293.53 46
agg_prior282.91 3895.45 1492.70 68
mPP-MVS86.67 2886.32 2987.72 2194.41 1273.55 992.74 1192.22 5076.87 4982.81 6094.25 1766.44 7196.24 2582.88 3994.28 3993.38 48
PGM-MVS86.68 2786.27 3087.90 1494.22 1773.38 1590.22 4893.04 2175.53 7283.86 4694.42 1467.87 6096.64 1482.70 4094.57 3293.66 35
ACMMPcopyleft85.89 3985.39 4187.38 2793.59 2772.63 2692.74 1193.18 1976.78 5180.73 8193.82 2864.33 8696.29 2382.67 4190.69 6693.23 53
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
Regformer-385.23 4885.07 4685.70 5588.95 10469.01 8088.29 10089.91 13480.95 885.01 2690.01 9572.45 2894.19 9182.50 4287.57 10093.90 31
abl_685.23 4884.95 4886.07 5192.23 5170.48 5690.80 3592.08 5573.51 10585.26 2494.16 2062.75 11295.92 3582.46 4391.30 6191.81 95
TSAR-MVS + GP.85.71 4185.33 4286.84 3691.34 6072.50 2989.07 7387.28 20176.41 5885.80 2090.22 9174.15 1995.37 5181.82 4491.88 5492.65 71
alignmvs85.48 4385.32 4385.96 5389.51 8769.47 7489.74 5792.47 4176.17 6587.73 1291.46 6970.32 4193.78 11381.51 4588.95 8194.63 6
canonicalmvs85.91 3885.87 3686.04 5289.84 8269.44 7690.45 4393.00 2476.70 5588.01 1091.23 7173.28 2293.91 10481.50 4688.80 8494.77 5
MVS_111021_HR85.14 5084.75 5086.32 4791.65 5872.70 2585.98 17590.33 11576.11 6682.08 6591.61 6471.36 3594.17 9381.02 4792.58 5192.08 87
HPM-MVS_fast85.35 4784.95 4886.57 4393.69 2470.58 5592.15 1991.62 7773.89 9682.67 6294.09 2362.60 11995.54 4180.93 4892.93 4793.57 43
CPTT-MVS83.73 5583.33 5684.92 7193.28 3270.86 5092.09 2090.38 11068.75 18479.57 8692.83 4760.60 15593.04 15080.92 4991.56 5890.86 117
DeepC-MVS_fast79.65 386.91 2586.62 2687.76 1893.52 2872.37 3391.26 2793.04 2176.62 5684.22 4393.36 3571.44 3496.76 980.82 5095.33 1994.16 18
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
nrg03083.88 5383.53 5384.96 6886.77 16269.28 7790.46 4292.67 3774.79 8582.95 5691.33 7072.70 2693.09 14780.79 5179.28 18692.50 74
EI-MVSNet-Vis-set84.19 5283.81 5285.31 5888.18 12967.85 10787.66 11589.73 13880.05 1682.95 5689.59 10270.74 4094.82 7180.66 5284.72 13293.28 52
MSLP-MVS++85.43 4585.76 3884.45 8091.93 5570.24 5790.71 3692.86 3177.46 4084.22 4392.81 5067.16 6792.94 15280.36 5394.35 3890.16 147
MVS_111021_LR82.61 7282.11 7084.11 9088.82 10971.58 4185.15 19286.16 21474.69 8680.47 8291.04 7662.29 12790.55 21280.33 5490.08 7390.20 146
DELS-MVS85.41 4685.30 4485.77 5488.49 12067.93 10685.52 18993.44 1178.70 2783.63 5289.03 11674.57 1195.71 3780.26 5594.04 4293.66 35
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
EI-MVSNet-UG-set83.81 5483.38 5585.09 6587.87 13667.53 11187.44 12689.66 13979.74 1782.23 6489.41 11170.24 4294.74 7379.95 5683.92 13892.99 65
CSCG86.41 3286.19 3287.07 3492.91 4072.48 3090.81 3493.56 873.95 9583.16 5591.07 7575.94 695.19 5479.94 5794.38 3793.55 44
OPM-MVS83.50 5982.95 6185.14 6388.79 11270.95 4789.13 7291.52 8177.55 3780.96 7891.75 5960.71 15194.50 8079.67 5886.51 11789.97 159
CDPH-MVS85.76 4085.29 4587.17 3193.49 2971.08 4488.58 8992.42 4568.32 19084.61 3693.48 3172.32 2996.15 2979.00 5995.43 1594.28 17
MVSFormer82.85 6982.05 7285.24 6187.35 14970.21 5890.50 4090.38 11068.55 18781.32 7289.47 10561.68 13393.46 12978.98 6090.26 7092.05 89
test_djsdf80.30 11679.32 11583.27 11883.98 21165.37 14890.50 4090.38 11068.55 18776.19 14888.70 12056.44 18293.46 12978.98 6080.14 17990.97 114
HQP_MVS83.64 5783.14 5785.14 6390.08 7668.71 9091.25 2892.44 4279.12 2278.92 9391.00 7960.42 15795.38 4978.71 6286.32 11991.33 104
plane_prior592.44 4295.38 4978.71 6286.32 11991.33 104
LPG-MVS_test82.08 7681.27 8084.50 7889.23 9968.76 8690.22 4891.94 6475.37 7676.64 14291.51 6654.29 19794.91 6678.44 6483.78 13989.83 163
LGP-MVS_train84.50 7889.23 9968.76 8691.94 6475.37 7676.64 14291.51 6654.29 19794.91 6678.44 6483.78 13989.83 163
lupinMVS81.39 9080.27 9584.76 7487.35 14970.21 5885.55 18686.41 20962.85 23981.32 7288.61 12461.68 13392.24 17378.41 6690.26 7091.83 93
jason81.39 9080.29 9484.70 7586.63 16369.90 6585.95 17686.77 20563.24 23381.07 7789.47 10561.08 14792.15 17478.33 6790.07 7492.05 89
jason: jason.
xiu_mvs_v1_base_debu80.80 10179.72 10284.03 9587.35 14970.19 6085.56 18388.77 17469.06 17781.83 6688.16 13550.91 22792.85 15478.29 6887.56 10289.06 175
xiu_mvs_v1_base80.80 10179.72 10284.03 9587.35 14970.19 6085.56 18388.77 17469.06 17781.83 6688.16 13550.91 22792.85 15478.29 6887.56 10289.06 175
xiu_mvs_v1_base_debi80.80 10179.72 10284.03 9587.35 14970.19 6085.56 18388.77 17469.06 17781.83 6688.16 13550.91 22792.85 15478.29 6887.56 10289.06 175
Effi-MVS+83.62 5883.08 5885.24 6188.38 12567.45 11288.89 7689.15 15575.50 7382.27 6388.28 13369.61 4894.45 8177.81 7187.84 9893.84 33
PS-MVSNAJss82.07 7781.31 7984.34 8586.51 16567.27 11789.27 6591.51 8271.75 13679.37 8890.22 9163.15 10094.27 8677.69 7282.36 15591.49 102
ACMP74.13 681.51 8980.57 8984.36 8389.42 8968.69 9389.97 5191.50 8474.46 8875.04 17190.41 8753.82 20294.54 7677.56 7382.91 14789.86 162
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
BP-MVS77.47 74
HQP-MVS82.61 7282.02 7384.37 8289.33 9166.98 12189.17 6792.19 5276.41 5877.23 13390.23 9060.17 16095.11 5777.47 7485.99 12391.03 111
MVS_Test83.15 6483.06 5983.41 11486.86 15963.21 20386.11 17392.00 6074.31 9082.87 5889.44 11070.03 4393.21 13877.39 7688.50 9393.81 34
3Dnovator+77.84 485.48 4384.47 5188.51 291.08 6373.49 1393.18 493.78 580.79 1076.66 14193.37 3460.40 15996.75 1077.20 7793.73 4495.29 1
anonymousdsp78.60 15377.15 16382.98 13380.51 27167.08 11987.24 13389.53 14265.66 21475.16 16787.19 16052.52 20792.25 17277.17 7879.34 18589.61 169
test_normal79.81 13078.45 13783.89 10282.70 24365.40 14585.82 18089.48 14469.39 16870.12 22285.66 20357.15 17993.71 12277.08 7988.62 8892.56 73
VDD-MVS83.01 6882.36 6884.96 6891.02 6466.40 12888.91 7588.11 18477.57 3484.39 4193.29 3652.19 21493.91 10477.05 8088.70 8694.57 9
XVG-OURS-SEG-HR80.81 9979.76 10183.96 10085.60 17568.78 8583.54 22390.50 10770.66 15376.71 14091.66 6060.69 15291.26 19576.94 8181.58 16191.83 93
DI_MVS_plusplus_test79.89 12778.58 13383.85 10382.89 23965.32 14986.12 17289.55 14169.64 16770.55 21385.82 20057.24 17793.81 11176.85 8288.55 9092.41 77
jajsoiax79.29 14277.96 14883.27 11884.68 18766.57 12789.25 6690.16 12369.20 17475.46 15689.49 10445.75 26193.13 14576.84 8380.80 16890.11 150
mvs_tets79.13 14577.77 15483.22 12184.70 18666.37 12989.17 6790.19 12269.38 17075.40 15989.46 10744.17 26793.15 14376.78 8480.70 17090.14 148
testing_275.73 20573.34 21282.89 14177.37 29165.22 15284.10 21690.54 10669.09 17660.46 28781.15 26040.48 28592.84 15776.36 8580.54 17490.60 129
v2v48280.23 11879.29 11983.05 12983.62 21964.14 18287.04 14289.97 13073.61 10078.18 11587.22 15861.10 14693.82 11076.11 8676.78 21691.18 109
CLD-MVS82.31 7481.65 7784.29 8688.47 12167.73 11085.81 18192.35 4775.78 6878.33 10786.58 18164.01 8994.35 8376.05 8787.48 10590.79 118
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
EPNet83.72 5682.92 6286.14 5084.22 19469.48 7391.05 3285.27 22181.30 776.83 13891.65 6166.09 7495.56 4076.00 8893.85 4393.38 48
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
Test477.83 17275.90 18983.62 10680.24 27365.25 15185.27 19190.67 10069.03 18066.48 26383.75 22843.07 27293.00 15175.93 8988.66 8792.62 72
v680.40 11179.54 10682.98 13384.09 20464.50 17587.57 11890.22 11973.25 10878.47 10186.63 17862.84 10793.86 10775.73 9077.02 20590.58 132
v1neww80.40 11179.54 10682.98 13384.10 20264.51 17187.57 11890.22 11973.25 10878.47 10186.65 17662.83 10893.86 10775.72 9177.02 20590.58 132
v7new80.40 11179.54 10682.98 13384.10 20264.51 17187.57 11890.22 11973.25 10878.47 10186.65 17662.83 10893.86 10775.72 9177.02 20590.58 132
XVG-OURS80.41 11079.23 12183.97 9985.64 17469.02 7983.03 22690.39 10971.09 14677.63 12591.49 6854.62 19691.35 19375.71 9383.47 14191.54 99
V4279.38 14178.24 14582.83 14581.10 26565.50 14485.55 18689.82 13571.57 14178.21 11386.12 19460.66 15393.18 14275.64 9475.46 23289.81 165
PS-MVSNAJ81.69 8381.02 8583.70 10589.51 8768.21 10284.28 21290.09 12570.79 14981.26 7585.62 20463.15 10094.29 8475.62 9588.87 8388.59 200
xiu_mvs_v2_base81.69 8381.05 8483.60 10789.15 10268.03 10584.46 20690.02 12970.67 15281.30 7486.53 18563.17 9994.19 9175.60 9688.54 9188.57 202
v180.19 12079.31 11682.85 14283.83 21664.12 18487.14 13590.07 12873.13 11178.27 10986.38 19062.72 11493.75 11775.41 9776.82 21490.68 123
v114180.19 12079.31 11682.85 14283.84 21464.12 18487.14 13590.08 12673.13 11178.27 10986.39 18862.67 11793.75 11775.40 9876.83 21390.68 123
divwei89l23v2f11280.19 12079.31 11682.85 14283.84 21464.11 18687.13 13890.08 12673.13 11178.27 10986.39 18862.69 11593.75 11775.40 9876.82 21490.68 123
OMC-MVS82.69 7081.97 7584.85 7288.75 11467.42 11387.98 10790.87 9774.92 8479.72 8591.65 6162.19 13093.96 9975.26 10086.42 11893.16 58
v780.24 11779.26 12083.15 12384.07 20864.94 15987.56 12190.67 10072.26 13178.28 10886.51 18661.45 13894.03 9875.14 10177.41 19990.49 137
v114480.03 12479.03 12483.01 13183.78 21764.51 17187.11 14090.57 10571.96 13578.08 11886.20 19361.41 13993.94 10174.93 10277.23 20190.60 129
MVSTER79.01 14777.88 15082.38 15783.07 23364.80 16384.08 21788.95 16769.01 18178.69 9587.17 16154.70 19492.43 16574.69 10380.57 17289.89 161
PVSNet_Blended_VisFu82.62 7181.83 7684.96 6890.80 6969.76 6788.74 8591.70 7569.39 16878.96 9288.46 12965.47 7994.87 7074.42 10488.57 8990.24 145
v879.97 12679.02 12582.80 14684.09 20464.50 17587.96 10890.29 11874.13 9475.24 16686.81 16562.88 10593.89 10674.39 10575.40 23390.00 158
v14419279.47 13878.37 14182.78 14983.35 22463.96 18986.96 14490.36 11369.99 16077.50 12685.67 20260.66 15393.77 11574.27 10676.58 21790.62 127
ACMM73.20 880.78 10479.84 9983.58 10889.31 9668.37 9789.99 5091.60 7870.28 15777.25 13189.66 10053.37 20493.53 12774.24 10782.85 14888.85 186
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
旧先验286.56 16058.10 27387.04 1388.98 23474.07 108
v119279.59 13478.43 14083.07 12883.55 22164.52 16986.93 14690.58 10470.83 14877.78 12285.90 19659.15 16393.94 10173.96 10977.19 20390.76 119
v1079.74 13278.67 12982.97 13784.06 20964.95 15887.88 11390.62 10373.11 11475.11 16986.56 18261.46 13794.05 9773.68 11075.55 23089.90 160
v5277.94 17076.37 17582.67 15179.39 28365.52 14186.43 16389.94 13272.28 12972.15 20084.94 21855.70 18693.44 13173.64 11172.84 25589.06 175
V477.95 16876.37 17582.67 15179.40 28265.52 14186.43 16389.94 13272.28 12972.14 20184.95 21755.72 18593.44 13173.64 11172.86 25489.05 179
v192192079.22 14378.03 14782.80 14683.30 22763.94 19086.80 15090.33 11569.91 16177.48 12785.53 20658.44 16793.75 11773.60 11376.85 21190.71 122
Effi-MVS+-dtu80.03 12478.57 13484.42 8185.13 18168.74 8888.77 8188.10 18674.99 8274.97 17283.49 23257.27 17593.36 13473.53 11480.88 16691.18 109
mvs-test180.88 9479.40 11285.29 5985.13 18169.75 6889.28 6488.10 18674.99 8276.44 14586.72 16857.27 17594.26 8973.53 11483.18 14591.87 92
VDDNet81.52 8780.67 8884.05 9390.44 7164.13 18389.73 5885.91 21771.11 14583.18 5493.48 3150.54 23393.49 12873.40 11688.25 9594.54 10
3Dnovator76.31 583.38 6382.31 6986.59 4287.94 13572.94 2290.64 3792.14 5477.21 4175.47 15592.83 4758.56 16694.72 7473.24 11792.71 5092.13 86
v124078.99 14877.78 15382.64 15383.21 22863.54 19386.62 15890.30 11769.74 16677.33 12985.68 20157.04 18093.76 11673.13 11876.92 20890.62 127
MG-MVS83.41 6183.45 5483.28 11792.74 4362.28 21688.17 10489.50 14375.22 7981.49 7192.74 5166.75 6895.11 5772.85 11991.58 5792.45 75
EPP-MVSNet83.40 6283.02 6084.57 7690.13 7564.47 17792.32 1690.73 9974.45 8979.35 8991.10 7269.05 5395.12 5672.78 12087.22 10794.13 19
v1877.67 17776.35 17981.64 17684.09 20464.47 17787.27 13189.01 16072.59 12669.39 23382.04 24762.85 10691.80 17772.72 12167.20 28088.63 194
v1677.69 17476.36 17881.68 17484.15 19964.63 16887.33 12888.99 16272.69 12569.31 23682.08 24562.80 11191.79 17872.70 12267.23 27988.63 194
v1777.68 17576.35 17981.69 17384.15 19964.65 16687.33 12888.99 16272.70 12469.25 23782.07 24662.82 11091.79 17872.69 12367.15 28188.63 194
IterMVS-LS80.06 12379.38 11382.11 16185.89 16963.20 20486.79 15189.34 14774.19 9175.45 15786.72 16866.62 6992.39 16772.58 12476.86 21090.75 120
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
EI-MVSNet80.52 10979.98 9782.12 16084.28 19163.19 20586.41 16588.95 16774.18 9278.69 9587.54 14966.62 6992.43 16572.57 12580.57 17290.74 121
Vis-MVSNetpermissive83.46 6082.80 6485.43 5790.25 7468.74 8890.30 4690.13 12476.33 6380.87 7992.89 4561.00 14894.20 9072.45 12690.97 6393.35 50
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
v1577.51 18276.12 18281.66 17584.09 20464.65 16687.14 13588.96 16672.76 12268.90 23881.91 25462.74 11391.73 18172.32 12766.29 28688.61 197
V1477.52 18076.12 18281.70 17284.15 19964.77 16487.21 13488.95 16772.80 12168.79 23981.94 25362.69 11591.72 18372.31 12866.27 28788.60 198
V977.52 18076.11 18581.73 17184.19 19864.89 16187.26 13288.94 17072.87 12068.65 24281.96 25262.65 11891.72 18372.27 12966.24 28888.60 198
v1277.51 18276.09 18681.76 17084.22 19464.99 15787.30 13088.93 17172.92 11768.48 24681.97 25062.54 12291.70 18672.24 13066.21 29088.58 201
v1377.50 18476.07 18781.77 16884.23 19365.07 15687.34 12788.91 17272.92 11768.35 24781.97 25062.53 12391.69 18772.20 13166.22 28988.56 203
LFMVS81.82 8281.23 8183.57 10991.89 5663.43 19889.84 5281.85 25377.04 4683.21 5393.10 3952.26 21393.43 13371.98 13289.95 7593.85 32
v1177.45 18576.06 18881.59 17984.22 19464.52 16987.11 14089.02 15872.76 12268.76 24081.90 25562.09 13191.71 18571.98 13266.73 28288.56 203
v14878.72 15177.80 15281.47 18182.73 24261.96 21986.30 16988.08 18873.26 10776.18 14985.47 20862.46 12592.36 16971.92 13473.82 24990.09 152
diffmvs79.51 13578.59 13282.25 15983.31 22662.66 21184.17 21388.11 18467.64 19376.09 15287.47 15164.01 8991.15 19871.71 13584.82 13192.94 66
PVSNet_BlendedMVS80.60 10680.02 9682.36 15888.85 10665.40 14586.16 17192.00 6069.34 17178.11 11686.09 19566.02 7694.27 8671.52 13682.06 15687.39 226
PVSNet_Blended80.98 9380.34 9282.90 13988.85 10665.40 14584.43 20892.00 6067.62 19578.11 11685.05 21666.02 7694.27 8671.52 13689.50 7789.01 182
MVS_test032679.86 12878.74 12883.23 12085.76 17263.99 18886.77 15489.97 13073.63 9973.53 18286.56 18253.05 20694.38 8271.43 13887.94 9791.33 104
UA-Net85.08 5184.96 4785.45 5692.07 5368.07 10489.78 5690.86 9882.48 284.60 3793.20 3769.35 5095.22 5371.39 13990.88 6593.07 60
MVS_dtu79.86 12878.53 13583.85 10386.55 16464.93 16086.47 16287.68 19573.52 10474.35 17887.89 14051.92 21894.53 7771.28 14087.08 10992.08 87
VNet82.21 7582.41 6681.62 17790.82 6860.93 22384.47 20489.78 13676.36 6284.07 4591.88 5864.71 8590.26 21470.68 14188.89 8293.66 35
mvs_anonymous79.42 14079.11 12380.34 19984.45 19057.97 24782.59 22787.62 19667.40 19976.17 15188.56 12768.47 5589.59 22370.65 14286.05 12293.47 47
VPA-MVSNet80.60 10680.55 9080.76 19488.07 13160.80 22686.86 14891.58 7975.67 7180.24 8389.45 10963.34 9490.25 21570.51 14379.22 18791.23 108
PAPM_NR83.02 6782.41 6684.82 7392.47 4966.37 12987.93 11191.80 7073.82 9777.32 13090.66 8467.90 5994.90 6870.37 14489.48 7893.19 57
UniMVSNet_NR-MVSNet81.88 8081.54 7882.92 13888.46 12263.46 19687.13 13892.37 4680.19 1478.38 10589.14 11371.66 3393.05 14870.05 14576.46 21992.25 82
DU-MVS81.12 9280.52 9182.90 13987.80 13963.46 19687.02 14391.87 6879.01 2578.38 10589.07 11465.02 8393.05 14870.05 14576.46 21992.20 83
XVG-ACMP-BASELINE76.11 20174.27 20581.62 17783.20 22964.67 16583.60 22289.75 13769.75 16471.85 20387.09 16232.78 30492.11 17569.99 14780.43 17588.09 212
FIs82.07 7782.42 6581.04 19088.80 11158.34 24288.26 10293.49 1076.93 4878.47 10191.04 7669.92 4592.34 17069.87 14884.97 12892.44 76
114514_t80.68 10579.51 10984.20 8894.09 2167.27 11789.64 5991.11 9358.75 27174.08 17990.72 8358.10 16995.04 6269.70 14989.42 7990.30 144
Patchmatch-RL test70.24 24867.78 25777.61 23777.43 29059.57 23371.16 29070.33 30962.94 23868.65 24272.77 30150.62 23285.49 26469.58 15066.58 28487.77 219
UniMVSNet (Re)81.60 8681.11 8383.09 12688.38 12564.41 17987.60 11693.02 2378.42 3078.56 9888.16 13569.78 4693.26 13769.58 15076.49 21891.60 97
semantic-postprocess80.11 20482.69 24464.85 16283.47 23669.16 17570.49 21684.15 22450.83 23188.15 24569.23 15272.14 26087.34 228
v7n78.97 14977.58 15783.14 12483.45 22365.51 14388.32 9891.21 9073.69 9872.41 19586.32 19157.93 17093.81 11169.18 15375.65 22890.11 150
testdata79.97 20690.90 6664.21 18184.71 22559.27 26785.40 2292.91 4462.02 13289.08 23268.95 15491.37 6086.63 245
GA-MVS76.87 19375.17 19681.97 16482.75 24162.58 21281.44 23986.35 21272.16 13474.74 17482.89 23546.20 25692.02 17668.85 15581.09 16491.30 107
v74877.97 16776.65 17181.92 16682.29 24963.28 20187.53 12290.35 11473.50 10670.76 21285.55 20558.28 16892.81 15868.81 15672.76 25689.67 168
UGNet80.83 9879.59 10584.54 7788.04 13268.09 10389.42 6288.16 18376.95 4776.22 14789.46 10749.30 24193.94 10168.48 15790.31 6991.60 97
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
FC-MVSNet-test81.52 8782.02 7380.03 20588.42 12455.97 27287.95 10993.42 1277.10 4477.38 12890.98 8169.96 4491.79 17868.46 15884.50 13392.33 78
DP-MVS Recon83.11 6682.09 7186.15 4994.44 970.92 4988.79 8092.20 5170.53 15479.17 9091.03 7864.12 8896.03 3068.39 15990.14 7291.50 101
IS-MVSNet83.15 6482.81 6384.18 8989.94 8063.30 20091.59 2488.46 18179.04 2479.49 8792.16 5265.10 8294.28 8567.71 16091.86 5594.95 3
Fast-Effi-MVS+-dtu78.02 16576.49 17282.62 15483.16 23266.96 12386.94 14587.45 20072.45 12771.49 20884.17 22354.79 19391.58 19067.61 16180.31 17689.30 173
PAPR81.66 8580.89 8683.99 9890.27 7364.00 18786.76 15591.77 7468.84 18377.13 13789.50 10367.63 6194.88 6967.55 16288.52 9293.09 59
cascas76.72 19574.64 19982.99 13285.78 17165.88 13782.33 22989.21 15460.85 25572.74 19081.02 26247.28 25093.75 11767.48 16385.02 12789.34 172
131476.53 19675.30 19580.21 20383.93 21262.32 21584.66 19988.81 17360.23 25970.16 22184.07 22555.30 18990.73 21067.37 16483.21 14487.59 223
无先验87.48 12488.98 16460.00 26194.12 9467.28 16588.97 185
112180.84 9679.77 10084.05 9393.11 3770.78 5184.66 19985.42 22057.37 28181.76 7092.02 5463.41 9394.12 9467.28 16592.93 4787.26 231
原ACMM184.35 8493.01 3968.79 8492.44 4263.96 23181.09 7691.57 6566.06 7595.45 4467.19 16794.82 2988.81 188
Baseline_NR-MVSNet78.15 16278.33 14377.61 23785.79 17056.21 27086.78 15285.76 21873.60 10177.93 12087.57 14765.02 8388.99 23367.14 16875.33 23487.63 221
TranMVSNet+NR-MVSNet80.84 9680.31 9382.42 15687.85 13762.33 21487.74 11491.33 8780.55 1177.99 11989.86 9765.23 8192.62 16067.05 16975.24 23792.30 80
Fast-Effi-MVS+80.81 9979.92 9883.47 11088.85 10664.51 17185.53 18889.39 14670.79 14978.49 10085.06 21567.54 6293.58 12467.03 17086.58 11592.32 79
VPNet78.69 15278.66 13078.76 22188.31 12755.72 27484.45 20786.63 20776.79 5078.26 11290.55 8659.30 16289.70 22266.63 17177.05 20490.88 116
PM-MVS66.41 26864.14 26873.20 27073.92 30256.45 26478.97 25864.96 32363.88 23264.72 27380.24 26819.84 32083.44 27466.24 17264.52 29479.71 296
test-LLR72.94 23072.43 21774.48 26281.35 26158.04 24578.38 26277.46 28266.66 20169.95 22679.00 27748.06 24779.24 28866.13 17384.83 12986.15 249
test-mter71.41 23870.39 23674.48 26281.35 26158.04 24578.38 26277.46 28260.32 25869.95 22679.00 27736.08 30179.24 28866.13 17384.83 12986.15 249
MVS78.19 16176.99 16581.78 16785.66 17366.99 12084.66 19990.47 10855.08 29172.02 20285.27 21163.83 9194.11 9666.10 17589.80 7684.24 269
NR-MVSNet80.23 11879.38 11382.78 14987.80 13963.34 19986.31 16891.09 9479.01 2572.17 19889.07 11467.20 6592.81 15866.08 17675.65 22892.20 83
CVMVSNet72.99 22972.58 21674.25 26584.28 19150.85 29686.41 16583.45 23744.56 31273.23 18687.54 14949.38 23985.70 26265.90 17778.44 19186.19 248
IterMVS74.29 21372.94 21478.35 22981.53 25763.49 19581.58 23782.49 24568.06 19269.99 22583.69 23051.66 22185.54 26365.85 17871.64 26386.01 253
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
OurMVSNet-221017-074.26 21472.42 21879.80 20883.76 21859.59 23285.92 17886.64 20666.39 20666.96 25887.58 14639.46 28891.60 18965.76 17969.27 27288.22 209
tpmrst72.39 23272.13 21973.18 27180.54 27049.91 30079.91 25079.08 27663.11 23471.69 20579.95 27055.32 18882.77 27765.66 18073.89 24786.87 239
MAR-MVS81.84 8180.70 8785.27 6091.32 6171.53 4289.82 5390.92 9669.77 16378.50 9986.21 19262.36 12694.52 7965.36 18192.05 5389.77 166
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
ab-mvs79.51 13578.97 12681.14 18888.46 12260.91 22483.84 21889.24 15370.36 15679.03 9188.87 11863.23 9890.21 21665.12 18282.57 15392.28 81
IB-MVS68.01 1575.85 20473.36 21183.31 11684.76 18566.03 13283.38 22485.06 22370.21 15969.40 23281.05 26145.76 26094.66 7565.10 18375.49 23189.25 174
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
PatchFormer-LS_test74.50 21273.05 21378.86 22082.95 23759.55 23581.65 23682.30 24867.44 19871.62 20678.15 28152.34 21188.92 23865.05 18475.90 22588.12 211
WR-MVS79.49 13779.22 12280.27 20288.79 11258.35 24185.06 19388.61 17978.56 2877.65 12488.34 13163.81 9290.66 21164.98 18577.22 20291.80 96
CostFormer75.24 21073.90 20879.27 21482.65 24558.27 24380.80 24082.73 24461.57 25075.33 16483.13 23455.52 18791.07 20564.98 18578.34 19388.45 206
API-MVS81.99 7981.23 8184.26 8790.94 6570.18 6391.10 3189.32 14871.51 14278.66 9788.28 13365.26 8095.10 6064.74 18791.23 6287.51 224
新几何183.42 11293.13 3570.71 5285.48 21957.43 28081.80 6991.98 5563.28 9592.27 17164.60 18892.99 4687.27 230
pm-mvs177.25 18976.68 17078.93 21984.22 19458.62 23986.41 16588.36 18271.37 14373.31 18488.01 13961.22 14489.15 23164.24 18973.01 25389.03 181
TESTMET0.1,169.89 25169.00 24272.55 27279.27 28556.85 25778.38 26274.71 29857.64 27868.09 24877.19 28837.75 29576.70 29963.92 19084.09 13784.10 272
QAPM80.88 9479.50 11085.03 6688.01 13468.97 8291.59 2492.00 6066.63 20475.15 16892.16 5257.70 17195.45 4463.52 19188.76 8590.66 126
LCM-MVSNet-Re77.05 19076.94 16677.36 24087.20 15551.60 29080.06 24780.46 26575.20 8067.69 25186.72 16862.48 12488.98 23463.44 19289.25 8091.51 100
gm-plane-assit81.40 25953.83 28362.72 24280.94 26492.39 16763.40 193
DWT-MVSNet_test73.70 21871.86 22179.21 21682.91 23858.94 23782.34 22882.17 24965.21 21671.05 21178.31 27944.21 26690.17 21763.29 19477.28 20088.53 205
AdaColmapbinary80.58 10879.42 11184.06 9293.09 3868.91 8389.36 6388.97 16569.27 17275.70 15489.69 9957.20 17895.77 3663.06 19588.41 9487.50 225
GBi-Net78.40 15577.40 15981.40 18387.60 14463.01 20688.39 9589.28 14971.63 13875.34 16187.28 15454.80 19091.11 19962.72 19679.57 18190.09 152
test178.40 15577.40 15981.40 18387.60 14463.01 20688.39 9589.28 14971.63 13875.34 16187.28 15454.80 19091.11 19962.72 19679.57 18190.09 152
FMVSNet377.88 17176.85 16780.97 19186.84 16062.36 21386.52 16188.77 17471.13 14475.34 16186.66 17554.07 20091.10 20262.72 19679.57 18189.45 171
CMPMVSbinary51.72 2170.19 24968.16 24976.28 24873.15 30757.55 25279.47 25383.92 23248.02 31056.48 30284.81 21943.13 27186.42 25862.67 19981.81 16084.89 263
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
FMVSNet278.20 16077.21 16281.20 18687.60 14462.89 21087.47 12589.02 15871.63 13875.29 16587.28 15454.80 19091.10 20262.38 20079.38 18489.61 169
testdata291.01 20662.37 201
CP-MVSNet78.22 15878.34 14277.84 23387.83 13854.54 27887.94 11091.17 9277.65 3273.48 18388.49 12862.24 12988.43 24262.19 20274.07 24490.55 135
XXY-MVS75.41 20875.56 19274.96 25883.59 22057.82 25080.59 24483.87 23366.54 20574.93 17388.31 13263.24 9780.09 28662.16 20376.85 21186.97 238
pmmvs674.69 21173.39 21078.61 22381.38 26057.48 25386.64 15787.95 19064.99 22070.18 21986.61 17950.43 23489.52 22462.12 20470.18 27088.83 187
1112_ss77.40 18876.43 17380.32 20089.11 10360.41 22983.65 22087.72 19462.13 24773.05 18886.72 16862.58 12189.97 21862.11 20580.80 16890.59 131
PS-CasMVS78.01 16678.09 14677.77 23587.71 14254.39 28088.02 10691.22 8977.50 3973.26 18588.64 12360.73 15088.41 24361.88 20673.88 24890.53 136
CDS-MVSNet79.07 14677.70 15583.17 12287.60 14468.23 10184.40 21086.20 21367.49 19776.36 14686.54 18461.54 13690.79 20961.86 20787.33 10690.49 137
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
OpenMVScopyleft72.83 1079.77 13178.33 14384.09 9185.17 17869.91 6490.57 3890.97 9566.70 20072.17 19891.91 5654.70 19493.96 9961.81 20890.95 6488.41 208
K. test v371.19 23968.51 24579.21 21683.04 23557.78 25184.35 21176.91 28672.90 11962.99 28282.86 23639.27 28991.09 20461.65 20952.66 31388.75 190
CHOSEN 1792x268877.63 17875.69 19083.44 11189.98 7968.58 9578.70 26187.50 19856.38 28675.80 15386.84 16458.67 16591.40 19261.58 21085.75 12690.34 143
PCF-MVS73.52 780.38 11478.84 12785.01 6787.71 14268.99 8183.65 22091.46 8563.00 23677.77 12390.28 8866.10 7395.09 6161.40 21188.22 9690.94 115
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
HY-MVS69.67 1277.95 16877.15 16380.36 19887.57 14860.21 23083.37 22587.78 19366.11 20875.37 16087.06 16363.27 9690.48 21361.38 21282.43 15490.40 142
HyFIR lowres test77.53 17975.40 19483.94 10189.59 8566.62 12580.36 24588.64 17856.29 28776.45 14485.17 21257.64 17293.28 13661.34 21383.10 14691.91 91
PMMVS69.34 25368.67 24471.35 27975.67 29862.03 21875.17 27973.46 30350.00 30868.68 24179.05 27552.07 21578.13 29361.16 21482.77 14973.90 309
FMVSNet177.44 18676.12 18281.40 18386.81 16163.01 20688.39 9589.28 14970.49 15574.39 17787.28 15449.06 24491.11 19960.91 21578.52 18990.09 152
sss73.60 21973.64 20973.51 26982.80 24055.01 27676.12 27381.69 25462.47 24474.68 17585.85 19957.32 17478.11 29460.86 21680.93 16587.39 226
Test_1112_low_res76.40 19775.44 19379.27 21489.28 9758.09 24481.69 23587.07 20359.53 26572.48 19486.67 17461.30 14189.33 22760.81 21780.15 17890.41 141
BH-untuned79.47 13878.60 13182.05 16289.19 10165.91 13686.07 17488.52 18072.18 13275.42 15887.69 14461.15 14593.54 12660.38 21886.83 11286.70 243
WTY-MVS75.65 20675.68 19175.57 25486.40 16656.82 25877.92 26782.40 24665.10 21876.18 14987.72 14263.13 10380.90 28260.31 21981.96 15789.00 184
pmmvs474.03 21671.91 22080.39 19781.96 25268.32 9881.45 23882.14 25059.32 26669.87 22885.13 21352.40 21088.13 24660.21 22074.74 24084.73 266
PEN-MVS77.73 17377.69 15677.84 23387.07 15753.91 28287.91 11291.18 9177.56 3673.14 18788.82 11961.23 14389.17 23059.95 22172.37 25790.43 140
CR-MVSNet73.37 22271.27 22879.67 21081.32 26365.19 15375.92 27580.30 26759.92 26272.73 19181.19 25852.50 20886.69 25459.84 22277.71 19587.11 236
lessismore_v078.97 21881.01 26657.15 25565.99 32061.16 28582.82 23739.12 29091.34 19459.67 22346.92 31788.43 207
CNLPA78.08 16376.79 16981.97 16490.40 7271.07 4587.59 11784.55 22766.03 21172.38 19689.64 10157.56 17386.04 26059.61 22483.35 14288.79 189
testpf56.51 28857.58 28553.30 30871.99 31041.19 31646.89 32469.32 31558.06 27452.87 31069.45 30927.99 30972.73 31359.59 22562.07 29745.98 321
BH-RMVSNet79.61 13378.44 13983.14 12489.38 9065.93 13584.95 19587.15 20273.56 10278.19 11489.79 9856.67 18193.36 13459.53 22686.74 11390.13 149
MS-PatchMatch73.83 21772.67 21577.30 24283.87 21366.02 13381.82 23284.66 22661.37 25368.61 24482.82 23747.29 24988.21 24459.27 22784.32 13677.68 301
test_post178.90 2605.43 33148.81 24685.44 26559.25 228
SixPastTwentyTwo73.37 22271.26 22979.70 20985.08 18357.89 24985.57 18283.56 23571.03 14765.66 26785.88 19742.10 27992.57 16259.11 22963.34 29588.65 193
WR-MVS_H78.51 15478.49 13678.56 22488.02 13356.38 26788.43 9192.67 3777.14 4273.89 18087.55 14866.25 7289.24 22958.92 23073.55 25190.06 156
PLCcopyleft70.83 1178.05 16476.37 17583.08 12791.88 5767.80 10888.19 10389.46 14564.33 22669.87 22888.38 13053.66 20393.58 12458.86 23182.73 15087.86 217
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
RPSCF73.23 22671.46 22578.54 22582.50 24759.85 23182.18 23082.84 24358.96 26871.15 21089.41 11145.48 26384.77 26958.82 23271.83 26291.02 113
EU-MVSNet68.53 25767.61 25971.31 28078.51 28747.01 30684.47 20484.27 23042.27 31366.44 26484.79 22040.44 28683.76 27158.76 23368.54 27883.17 277
pmmvs-eth3d70.50 24667.83 25578.52 22677.37 29166.18 13181.82 23281.51 25658.90 26963.90 27880.42 26742.69 27586.28 25958.56 23465.30 29283.11 279
TAMVS78.89 15077.51 15883.03 13087.80 13967.79 10984.72 19885.05 22467.63 19476.75 13987.70 14362.25 12890.82 20858.53 23587.13 10890.49 137
ACMH+68.96 1476.01 20274.01 20682.03 16388.60 11765.31 15088.86 7787.55 19770.25 15867.75 25087.47 15141.27 28293.19 14158.37 23675.94 22487.60 222
tpm72.37 23471.71 22474.35 26482.19 25052.00 28779.22 25677.29 28464.56 22372.95 18983.68 23151.35 22283.26 27658.33 23775.80 22687.81 218
BH-w/o78.21 15977.33 16180.84 19288.81 11065.13 15584.87 19687.85 19269.75 16474.52 17684.74 22161.34 14093.11 14658.24 23885.84 12584.27 268
Vis-MVSNet (Re-imp)78.36 15778.45 13778.07 23188.64 11651.78 28986.70 15679.63 27374.14 9375.11 16990.83 8261.29 14289.75 22058.10 23991.60 5692.69 70
MVP-Stereo76.12 20074.46 20381.13 18985.37 17769.79 6684.42 20987.95 19065.03 21967.46 25385.33 21053.28 20591.73 18158.01 24083.27 14381.85 288
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
ambc75.24 25773.16 30650.51 29863.05 31587.47 19964.28 27577.81 28517.80 32389.73 22157.88 24160.64 30285.49 256
TR-MVS77.44 18676.18 18181.20 18688.24 12863.24 20284.61 20286.40 21067.55 19677.81 12186.48 18754.10 19993.15 14357.75 24282.72 15187.20 232
F-COLMAP76.38 19874.33 20482.50 15589.28 9766.95 12488.41 9489.03 15764.05 22866.83 25988.61 12446.78 25392.89 15357.48 24378.55 18887.67 220
EG-PatchMatch MVS74.04 21571.82 22380.71 19584.92 18467.42 11385.86 17988.08 18866.04 21064.22 27683.85 22635.10 30392.56 16357.44 24480.83 16782.16 287
PatchmatchNetpermissive73.12 22771.33 22778.49 22783.18 23060.85 22579.63 25178.57 27764.13 22771.73 20479.81 27351.20 22485.97 26157.40 24576.36 22188.66 192
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
DTE-MVSNet76.99 19176.80 16877.54 23986.24 16753.06 28687.52 12390.66 10277.08 4572.50 19388.67 12260.48 15689.52 22457.33 24670.74 26890.05 157
UnsupCasMVSNet_eth67.33 26265.99 26371.37 27773.48 30451.47 29275.16 28085.19 22265.20 21760.78 28680.93 26542.35 27677.20 29857.12 24753.69 31285.44 257
pmmvs571.55 23770.20 23775.61 25377.83 28856.39 26681.74 23480.89 25957.76 27767.46 25384.49 22249.26 24285.32 26657.08 24875.29 23585.11 262
TransMVSNet (Re)75.39 20974.56 20177.86 23285.50 17657.10 25686.78 15286.09 21672.17 13371.53 20787.34 15363.01 10489.31 22856.84 24961.83 29887.17 233
EPMVS69.02 25468.16 24971.59 27579.61 27949.80 30277.40 26966.93 31962.82 24070.01 22379.05 27545.79 25977.86 29656.58 25075.26 23687.13 235
tpm273.26 22571.46 22578.63 22283.34 22556.71 26180.65 24380.40 26656.63 28573.55 18182.02 24851.80 21991.24 19656.35 25178.42 19287.95 214
LTVRE_ROB69.57 1376.25 19974.54 20281.41 18288.60 11764.38 18079.24 25589.12 15670.76 15169.79 23087.86 14149.09 24393.20 14056.21 25280.16 17786.65 244
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
ACMH67.68 1675.89 20373.93 20781.77 16888.71 11566.61 12688.62 8789.01 16069.81 16266.78 26086.70 17341.95 28191.51 19155.64 25378.14 19487.17 233
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
Patchmatch-test173.49 22071.85 22278.41 22884.05 21062.17 21779.96 24979.29 27566.30 20772.38 19679.58 27451.95 21785.08 26755.46 25477.67 19787.99 213
CHOSEN 280x42066.51 26764.71 26671.90 27481.45 25863.52 19457.98 31968.95 31753.57 29862.59 28376.70 28946.22 25575.29 30655.25 25579.68 18076.88 307
EPNet_dtu75.46 20774.86 19777.23 24382.57 24654.60 27786.89 14783.09 24071.64 13766.25 26585.86 19855.99 18488.04 24754.92 25686.55 11689.05 179
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
PVSNet64.34 1872.08 23570.87 23375.69 25286.21 16856.44 26574.37 28580.73 26262.06 24870.17 22082.23 24342.86 27483.31 27554.77 25784.45 13587.32 229
ITE_SJBPF78.22 23081.77 25460.57 22783.30 23869.25 17367.54 25287.20 15936.33 30087.28 25254.34 25874.62 24186.80 240
MDTV_nov1_ep13_2view37.79 32075.16 28055.10 29066.53 26249.34 24053.98 25987.94 215
tpmp4_e2373.45 22171.17 23080.31 20183.55 22159.56 23481.88 23182.33 24757.94 27670.51 21581.62 25651.19 22591.63 18853.96 26077.51 19889.75 167
gg-mvs-nofinetune69.95 25067.96 25275.94 25083.07 23354.51 27977.23 27070.29 31063.11 23470.32 21762.33 31343.62 26988.69 24053.88 26187.76 9984.62 267
PatchMatch-RL72.38 23370.90 23276.80 24688.60 11767.38 11579.53 25276.17 28862.75 24169.36 23482.00 24945.51 26284.89 26853.62 26280.58 17178.12 299
Patchmtry70.74 24269.16 24175.49 25580.72 26754.07 28174.94 28480.30 26758.34 27270.01 22381.19 25852.50 20886.54 25653.37 26371.09 26685.87 255
USDC70.33 24768.37 24676.21 24980.60 26956.23 26979.19 25786.49 20860.89 25461.29 28485.47 20831.78 30789.47 22653.37 26376.21 22282.94 284
LF4IMVS64.02 27662.19 27669.50 28670.90 31253.29 28576.13 27277.18 28552.65 30258.59 29280.98 26323.55 31576.52 30053.06 26566.66 28378.68 298
PAPM77.68 17576.40 17481.51 18087.29 15461.85 22083.78 21989.59 14064.74 22171.23 20988.70 12062.59 12093.66 12352.66 26687.03 11189.01 182
tpm cat170.57 24468.31 24777.35 24182.41 24857.95 24878.08 26680.22 26952.04 30368.54 24577.66 28652.00 21687.84 24951.77 26772.07 26186.25 247
MDTV_nov1_ep1369.97 23883.18 23053.48 28477.10 27180.18 27060.45 25669.33 23580.44 26648.89 24586.90 25351.60 26878.51 190
JIA-IIPM66.32 26962.82 27576.82 24577.09 29461.72 22165.34 31175.38 29058.04 27564.51 27462.32 31442.05 28086.51 25751.45 26969.22 27382.21 286
MSDG73.36 22470.99 23180.49 19684.51 18965.80 13880.71 24286.13 21565.70 21365.46 26883.74 22944.60 26490.91 20751.13 27076.89 20984.74 265
PatchT68.46 25867.85 25470.29 28380.70 26843.93 31072.47 28874.88 29460.15 26070.55 21376.57 29049.94 23781.59 28050.58 27174.83 23985.34 258
GG-mvs-BLEND75.38 25681.59 25655.80 27379.32 25469.63 31267.19 25673.67 30043.24 27088.90 23950.41 27284.50 13381.45 290
AllTest70.96 24168.09 25179.58 21285.15 17963.62 19184.58 20379.83 27162.31 24560.32 28886.73 16632.02 30588.96 23650.28 27371.57 26486.15 249
TestCases79.58 21285.15 17963.62 19179.83 27162.31 24560.32 28886.73 16632.02 30588.96 23650.28 27371.57 26486.15 249
TAPA-MVS73.13 979.15 14477.94 14982.79 14889.59 8562.99 20988.16 10591.51 8265.77 21277.14 13691.09 7460.91 14993.21 13850.26 27587.05 11092.17 85
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
YYNet165.03 27162.91 27371.38 27675.85 29756.60 26369.12 30174.66 30057.28 28254.12 30577.87 28445.85 25874.48 30849.95 27661.52 30083.05 280
MDA-MVSNet_test_wron65.03 27162.92 27271.37 27775.93 29656.73 25969.09 30274.73 29757.28 28254.03 30677.89 28345.88 25774.39 30949.89 27761.55 29982.99 282
tpmvs71.09 24069.29 24076.49 24782.04 25156.04 27178.92 25981.37 25864.05 22867.18 25778.28 28049.74 23889.77 21949.67 27872.37 25783.67 273
UnsupCasMVSNet_bld63.70 27761.53 27970.21 28473.69 30351.39 29372.82 28781.89 25255.63 28957.81 29671.80 30338.67 29178.61 29149.26 27952.21 31480.63 292
dp66.80 26465.43 26470.90 28279.74 27848.82 30375.12 28274.77 29659.61 26464.08 27777.23 28742.89 27380.72 28348.86 28066.58 28483.16 278
FMVSNet569.50 25267.96 25274.15 26682.97 23655.35 27580.01 24882.12 25162.56 24363.02 28081.53 25736.92 29881.92 27948.42 28174.06 24585.17 261
LCM-MVSNet54.25 28949.68 29567.97 29253.73 32645.28 30766.85 31080.78 26135.96 31939.45 31862.23 3158.70 33278.06 29548.24 28251.20 31580.57 293
RPMNet71.62 23668.94 24379.67 21081.32 26365.19 15375.92 27578.30 27957.60 27972.73 19176.45 29152.30 21286.69 25448.14 28377.71 19587.11 236
TDRefinement67.49 26064.34 26776.92 24473.47 30561.07 22284.86 19782.98 24159.77 26358.30 29485.13 21326.06 31287.89 24847.92 28460.59 30381.81 289
PVSNet_057.27 2061.67 27959.27 28068.85 28979.61 27957.44 25468.01 30573.44 30455.93 28858.54 29370.41 30644.58 26577.55 29747.01 28535.91 31971.55 311
DP-MVS76.78 19474.57 20083.42 11293.29 3169.46 7588.55 9083.70 23463.98 23070.20 21888.89 11754.01 20194.80 7246.66 28681.88 15986.01 253
COLMAP_ROBcopyleft66.92 1773.01 22870.41 23580.81 19387.13 15665.63 14088.30 9984.19 23162.96 23763.80 27987.69 14438.04 29492.56 16346.66 28674.91 23884.24 269
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
MIMVSNet70.69 24369.30 23974.88 25984.52 18856.35 26875.87 27779.42 27464.59 22267.76 24982.41 24041.10 28381.54 28146.64 28881.34 16286.75 242
LS3D76.95 19274.82 19883.37 11590.45 7067.36 11689.15 7186.94 20461.87 24969.52 23190.61 8551.71 22094.53 7746.38 28986.71 11488.21 210
MDA-MVSNet-bldmvs66.68 26563.66 26975.75 25179.28 28460.56 22873.92 28678.35 27864.43 22450.13 31379.87 27244.02 26883.67 27246.10 29056.86 30783.03 281
new-patchmatchnet61.73 27861.73 27861.70 30172.74 30824.50 33169.16 30078.03 28061.40 25156.72 30175.53 29438.42 29276.48 30145.95 29157.67 30584.13 271
TinyColmap67.30 26364.81 26574.76 26181.92 25356.68 26280.29 24681.49 25760.33 25756.27 30383.22 23324.77 31487.66 25145.52 29269.47 27179.95 295
pmmvs357.79 28554.26 28968.37 29164.02 31956.72 26075.12 28265.17 32140.20 31552.93 30969.86 30820.36 31975.48 30545.45 29355.25 31172.90 310
OpenMVS_ROBcopyleft64.09 1970.56 24568.19 24877.65 23680.26 27259.41 23685.01 19482.96 24258.76 27065.43 26982.33 24137.63 29791.23 19745.34 29476.03 22382.32 285
test0.0.03 168.00 25967.69 25868.90 28877.55 28947.43 30475.70 27872.95 30566.66 20166.56 26182.29 24248.06 24775.87 30344.97 29574.51 24283.41 275
testgi66.67 26666.53 26267.08 29375.62 29941.69 31575.93 27476.50 28766.11 20865.20 27286.59 18035.72 30274.71 30743.71 29673.38 25284.84 264
Anonymous2023120668.60 25567.80 25671.02 28180.23 27450.75 29778.30 26580.47 26456.79 28466.11 26682.63 23946.35 25478.95 29043.62 29775.70 22783.36 276
MIMVSNet168.58 25666.78 26173.98 26780.07 27551.82 28880.77 24184.37 22864.40 22559.75 29182.16 24436.47 29983.63 27342.73 29870.33 26986.48 246
test20.0367.45 26166.95 26068.94 28775.48 30144.84 30877.50 26877.67 28166.66 20163.01 28183.80 22747.02 25178.40 29242.53 29968.86 27683.58 274
ADS-MVSNet266.20 27063.33 27074.82 26079.92 27658.75 23867.55 30775.19 29253.37 29965.25 27075.86 29242.32 27780.53 28441.57 30068.91 27485.18 259
ADS-MVSNet64.36 27562.88 27468.78 29079.92 27647.17 30567.55 30771.18 30853.37 29965.25 27075.86 29242.32 27773.99 31141.57 30068.91 27485.18 259
Patchmatch-test64.82 27363.24 27169.57 28579.42 28149.82 30163.49 31469.05 31651.98 30459.95 29080.13 26950.91 22770.98 31740.66 30273.57 25087.90 216
MVS-HIRNet59.14 28257.67 28463.57 29881.65 25543.50 31171.73 28965.06 32239.59 31751.43 31157.73 31738.34 29382.58 27839.53 30373.95 24664.62 316
DSMNet-mixed57.77 28656.90 28660.38 30267.70 31735.61 32169.18 29953.97 32632.30 32357.49 29879.88 27140.39 28768.57 32138.78 30472.37 25776.97 304
Anonymous2023121164.82 27361.79 27773.91 26877.11 29350.92 29585.29 19081.53 25554.19 29357.98 29578.03 28226.90 31087.83 25037.92 30557.12 30682.99 282
N_pmnet52.79 29253.26 29051.40 31178.99 2867.68 33569.52 2973.89 33551.63 30657.01 30074.98 29540.83 28465.96 32437.78 30664.67 29380.56 294
no-one51.08 29345.79 29866.95 29457.92 32450.49 29959.63 31876.04 28948.04 30931.85 31956.10 32019.12 32180.08 28736.89 30726.52 32170.29 312
test_040272.79 23170.44 23479.84 20788.13 13065.99 13485.93 17784.29 22965.57 21567.40 25585.49 20746.92 25292.61 16135.88 30874.38 24380.94 291
new_pmnet50.91 29450.29 29352.78 30968.58 31634.94 32463.71 31356.63 32539.73 31644.95 31465.47 31221.93 31858.48 32634.98 30956.62 30864.92 315
wuykxyi23d39.76 30133.18 30459.51 30446.98 33044.01 30957.70 32067.74 31824.13 32513.98 33034.33 3251.27 33771.33 31634.23 31018.23 32463.18 317
testus59.00 28357.91 28262.25 30072.25 30939.09 31869.74 29575.02 29353.04 30157.21 29973.72 29918.76 32270.33 31832.86 31168.57 27777.35 302
LP61.36 28057.78 28372.09 27375.54 30058.53 24067.16 30975.22 29151.90 30554.13 30469.97 30737.73 29680.45 28532.74 31255.63 30977.29 303
111157.11 28756.82 28857.97 30569.10 31428.28 32668.90 30374.54 30154.01 29553.71 30774.51 29623.09 31667.90 32232.28 31361.26 30177.73 300
.test124545.55 29750.02 29432.14 31769.10 31428.28 32668.90 30374.54 30154.01 29553.71 30774.51 29623.09 31667.90 32232.28 3130.02 3310.25 330
test235659.50 28158.08 28163.74 29771.23 31141.88 31367.59 30672.42 30753.72 29757.65 29770.74 30526.31 31172.40 31432.03 31571.06 26776.93 305
test123567858.74 28456.89 28764.30 29569.70 31341.87 31471.05 29174.87 29554.06 29450.63 31271.53 30425.30 31374.10 31031.80 31663.10 29676.93 305
ANet_high50.57 29546.10 29763.99 29648.67 32939.13 31770.99 29380.85 26061.39 25231.18 32157.70 31817.02 32473.65 31231.22 31715.89 32879.18 297
testmv53.85 29051.03 29262.31 29961.46 32138.88 31970.95 29474.69 29951.11 30741.26 31566.85 31014.28 32672.13 31529.19 31849.51 31675.93 308
PMMVS240.82 30038.86 30146.69 31353.84 32516.45 33348.61 32349.92 32837.49 31831.67 32060.97 3168.14 33356.42 32728.42 31930.72 32067.19 313
test1235649.28 29648.51 29651.59 31062.06 32019.11 33260.40 31672.45 30647.60 31140.64 31765.68 31113.84 32768.72 32027.29 32046.67 31866.94 314
tmp_tt18.61 30821.40 30910.23 3214.82 33410.11 33434.70 32630.74 3331.48 33023.91 32526.07 32828.42 30813.41 33327.12 32115.35 3297.17 327
PNet_i23d38.26 30235.42 30246.79 31258.74 32235.48 32259.65 31751.25 32732.45 32223.44 32647.53 3222.04 33658.96 32525.60 32218.09 32645.92 322
FPMVS53.68 29151.64 29159.81 30365.08 31851.03 29469.48 29869.58 31341.46 31440.67 31672.32 30216.46 32570.00 31924.24 32365.42 29158.40 318
Gipumacopyleft45.18 29841.86 29955.16 30777.03 29551.52 29132.50 32780.52 26332.46 32127.12 32235.02 3249.52 33175.50 30422.31 32460.21 30438.45 323
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
DeepMVS_CXcopyleft27.40 31940.17 33326.90 32924.59 33417.44 32823.95 32448.61 3219.77 33026.48 33118.06 32524.47 32228.83 324
PMVScopyleft37.38 2244.16 29940.28 30055.82 30640.82 33242.54 31265.12 31263.99 32434.43 32024.48 32357.12 3193.92 33476.17 30217.10 32655.52 31048.75 319
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVEpermissive26.22 2330.37 30625.89 30843.81 31444.55 33135.46 32328.87 32839.07 33118.20 32718.58 32740.18 3232.68 33547.37 33017.07 32723.78 32348.60 320
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E-PMN31.77 30430.64 30535.15 31552.87 32727.67 32857.09 32147.86 32924.64 32416.40 32833.05 32611.23 32954.90 32814.46 32818.15 32522.87 325
EMVS30.81 30529.65 30634.27 31650.96 32825.95 33056.58 32246.80 33024.01 32615.53 32930.68 32712.47 32854.43 32912.81 32917.05 32722.43 326
wuyk23d16.82 30915.94 31019.46 32058.74 32231.45 32539.22 3253.74 3366.84 3296.04 3312.70 3321.27 33724.29 33210.54 33014.40 3302.63 328
testmvs6.04 3128.02 3130.10 3230.08 3350.03 33769.74 2950.04 3370.05 3310.31 3321.68 3330.02 3400.04 3340.24 3310.02 3310.25 330
test1236.12 3118.11 3120.14 3220.06 3360.09 33671.05 2910.03 3380.04 3320.25 3331.30 3340.05 3390.03 3350.21 3320.01 3330.29 329
cdsmvs_eth3d_5k19.96 30726.61 3070.00 3240.00 3370.00 3380.00 32989.26 1520.00 3330.00 33488.61 12461.62 1350.00 3360.00 3330.00 3340.00 332
pcd_1.5k_mvsjas5.26 3137.02 3140.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 33563.15 1000.00 3360.00 3330.00 3340.00 332
pcd1.5k->3k34.07 30335.26 30330.50 31886.92 1580.00 3380.00 32991.58 790.00 3330.00 3340.00 33556.23 1830.00 3360.00 33382.60 15291.49 102
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-re7.23 3109.64 3110.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 33486.72 1680.00 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_mvs151.32 223
sam_mvs50.01 236
MTGPAbinary92.02 57
test_post5.46 33050.36 23584.24 270
patchmatchnet-post74.00 29851.12 22688.60 241
MTMP32.83 332
TEST993.26 3372.96 1988.75 8391.89 6668.44 18985.00 2793.10 3974.36 1695.41 47
test_893.13 3572.57 2888.68 8691.84 6968.69 18584.87 3393.10 3974.43 1395.16 55
agg_prior92.85 4171.94 3891.78 7284.41 3994.93 64
test_prior472.60 2789.01 74
test_prior86.33 4592.61 4669.59 7092.97 2995.48 4293.91 29
新几何286.29 170
旧先验191.96 5465.79 13986.37 21193.08 4369.31 5192.74 4988.74 191
原ACMM286.86 148
test22291.50 5968.26 10084.16 21483.20 23954.63 29279.74 8491.63 6358.97 16491.42 5986.77 241
segment_acmp73.08 23
testdata184.14 21575.71 69
test1286.80 3792.63 4570.70 5391.79 7182.71 6171.67 3296.16 2894.50 3393.54 45
plane_prior790.08 7668.51 96
plane_prior689.84 8268.70 9260.42 157
plane_prior491.00 79
plane_prior368.60 9478.44 2978.92 93
plane_prior291.25 2879.12 22
plane_prior189.90 81
plane_prior68.71 9090.38 4477.62 3386.16 121
n20.00 339
nn0.00 339
door-mid69.98 311
test1192.23 49
door69.44 314
HQP5-MVS66.98 121
HQP-NCC89.33 9189.17 6776.41 5877.23 133
ACMP_Plane89.33 9189.17 6776.41 5877.23 133
HQP4-MVS77.24 13295.11 5791.03 111
HQP3-MVS92.19 5285.99 123
HQP2-MVS60.17 160
NP-MVS89.62 8468.32 9890.24 89
ACMMP++_ref81.95 158
ACMMP++81.25 163
Test By Simon64.33 86