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 bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort 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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
#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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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_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-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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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_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
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
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
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
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
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
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
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
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
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
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-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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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.
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
.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
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
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
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
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
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
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)
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
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
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
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
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
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
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)
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
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
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
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
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
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
sosnet-low-res0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
sosnet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
uncertanet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
Regformer0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
uanet0.00 3140.00 3150.00 3240.00 3370.00 3380.00 3290.00 3390.00 3330.00 3340.00 3350.00 3410.00 3360.00 3330.00 3340.00 332
sam_mvs151.32 223
sam_mvs50.01 236
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
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
MTGPAbinary92.02 57
test_post178.90 2605.43 33148.81 24685.44 26559.25 228
test_post5.46 33050.36 23584.24 270
patchmatchnet-post74.00 29851.12 22688.60 241
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
MTMP32.83 332
gm-plane-assit81.40 25953.83 28362.72 24280.94 26492.39 16763.40 193
test9_res84.90 1795.70 1292.87 67
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_prior282.91 3895.45 1492.70 68
agg_prior92.85 4171.94 3891.78 7284.41 3994.93 64
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
test_prior472.60 2789.01 74
test_prior288.85 7875.41 7484.91 2993.54 2974.28 1783.31 3195.86 6
test_prior86.33 4592.61 4669.59 7092.97 2995.48 4293.91 29
旧先验286.56 16058.10 27387.04 1388.98 23474.07 108
新几何286.29 170
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
旧先验191.96 5465.79 13986.37 21193.08 4369.31 5192.74 4988.74 191
无先验87.48 12488.98 16460.00 26194.12 9467.28 16588.97 185
原ACMM286.86 148
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
test22291.50 5968.26 10084.16 21483.20 23954.63 29279.74 8491.63 6358.97 16491.42 5986.77 241
testdata291.01 20662.37 201
segment_acmp73.08 23
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
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_prior592.44 4295.38 4978.71 6286.32 11991.33 104
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
lessismore_v078.97 21881.01 26657.15 25565.99 32061.16 28582.82 23739.12 29091.34 19459.67 22346.92 31788.43 207
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
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
BP-MVS77.47 74
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
MDTV_nov1_ep13_2view37.79 32075.16 28055.10 29066.53 26249.34 24053.98 25987.94 215
ACMMP++_ref81.95 158
ACMMP++81.25 163
Test By Simon64.33 86
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
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