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.
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3Dnovator+77.84 485.48 1184.47 1388.51 191.08 2073.49 393.18 293.78 380.79 376.66 4193.37 860.40 4696.75 477.20 1993.73 1295.29 1
NCCC88.06 388.01 388.24 294.41 273.62 291.22 1292.83 1081.50 185.79 493.47 773.02 597.00 284.90 394.94 794.10 8
SteuartSystems-ACMMP88.16 188.22 287.98 392.00 1572.76 592.99 393.57 479.38 487.27 394.47 271.72 796.63 587.17 195.44 394.56 4
Skip Steuart: Steuart Systems R&D Blog.
DeepC-MVS_fast79.65 386.91 786.62 787.76 493.52 772.37 1091.26 1193.04 976.62 1284.22 693.36 971.44 896.76 380.82 1195.33 594.16 6
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepC-MVS79.81 287.08 686.88 687.69 591.16 1972.32 1190.31 1893.94 277.12 982.82 1094.23 472.13 697.09 184.83 495.37 493.65 10
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CP-MVS87.11 586.92 587.68 694.20 473.86 193.98 192.82 1276.62 1283.68 794.46 367.93 1295.95 1184.20 694.39 893.23 14
ACMMPcopyleft85.89 1085.39 1087.38 793.59 672.63 792.74 493.18 876.78 1180.73 1493.82 664.33 2496.29 982.67 890.69 2393.23 14
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
PHI-MVS86.43 886.17 987.24 890.88 2270.96 1592.27 694.07 172.45 3285.22 591.90 1769.47 1096.42 883.28 795.94 194.35 5
DNCC-MVS87.44 487.52 487.19 994.24 372.39 991.86 892.83 1073.01 3188.58 294.52 173.36 496.49 784.26 595.01 692.70 19
CSCG86.41 986.19 887.07 1092.91 1172.48 890.81 1593.56 573.95 2883.16 991.07 2575.94 295.19 1679.94 1494.38 993.55 11
DeepPCF-MVS80.84 188.10 288.56 186.73 1192.24 1469.03 2389.57 2593.39 777.53 789.79 194.12 578.98 196.58 685.66 295.72 294.58 3
3Dnovator76.31 583.38 1982.31 2186.59 1287.94 5972.94 490.64 1692.14 1677.21 875.47 4892.83 1158.56 4894.72 2973.24 2692.71 1392.13 24
MVS_111021_HR85.14 1384.75 1286.32 1391.65 1772.70 685.98 5590.33 3576.11 1782.08 1191.61 2071.36 994.17 3981.02 992.58 1492.08 25
DP-MVS Recon83.11 2182.09 2386.15 1494.44 170.92 1688.79 3292.20 1470.53 4179.17 2091.03 2764.12 2696.03 1068.39 3690.14 2591.50 27
EPNet83.72 1582.92 1786.14 1584.22 8069.48 2191.05 1485.27 7081.30 276.83 3991.65 1866.09 1895.56 1476.00 2193.85 1193.38 12
DELS-MVS85.41 1285.30 1185.77 1688.49 5267.93 3485.52 5993.44 678.70 683.63 889.03 4274.57 395.71 1380.26 1394.04 1093.66 9
Vis-MVSNetpermissive83.46 1682.80 1985.43 1790.25 2768.74 2990.30 1990.13 3676.33 1680.87 1392.89 1061.00 4394.20 3872.45 3090.97 2193.35 13
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MAR-MVS81.84 2980.70 3085.27 1891.32 1871.53 1389.82 2390.92 3169.77 4878.50 2586.21 7362.36 3494.52 3365.36 4292.05 1589.77 51
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
QAPM80.88 3379.50 3785.03 1988.01 5868.97 2591.59 992.00 1766.63 6375.15 5792.16 1457.70 5095.45 1563.52 4788.76 3090.66 34
PCF-MVS73.52 780.38 3978.84 4185.01 2087.71 6168.99 2483.65 7291.46 2863.00 8277.77 3190.28 3366.10 1795.09 2161.40 5888.22 3490.94 30
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PVSNet_Blended_VisFu82.62 2481.83 2584.96 2190.80 2369.76 2088.74 3391.70 2469.39 5078.96 2288.46 4765.47 2194.87 2774.42 2488.57 3190.24 41
CPTT-MVS83.73 1483.33 1584.92 2293.28 970.86 1792.09 790.38 3468.75 5679.57 1792.83 1160.60 4593.04 5480.92 1091.56 1990.86 31
OMC-MVS82.69 2381.97 2484.85 2388.75 4667.42 3887.98 4490.87 3274.92 2279.72 1691.65 1862.19 3793.96 4075.26 2286.42 4693.16 17
PAPM_NR83.02 2282.41 2084.82 2492.47 1366.37 4687.93 4591.80 2273.82 2977.32 3290.66 3067.90 1394.90 2570.37 3389.48 2893.19 16
EPP-MVSNet83.40 1883.02 1684.57 2590.13 2864.47 6192.32 590.73 3374.45 2579.35 1991.10 2369.05 1195.12 1772.78 2887.22 3794.13 7
UGNet80.83 3479.59 3584.54 2688.04 5768.09 3389.42 2688.16 5676.95 1076.22 4589.46 4049.30 8593.94 4268.48 3590.31 2491.60 26
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
LPG-MVS_test82.08 2781.27 2784.50 2789.23 3868.76 2790.22 2091.94 2075.37 1976.64 4291.51 2154.29 6394.91 2378.44 1583.78 5189.83 49
LGP-MVS_train84.50 2789.23 3868.76 2791.94 2075.37 1976.64 4291.51 2154.29 6394.91 2378.44 1583.78 5189.83 49
ACMP74.13 681.51 3180.57 3184.36 2989.42 3168.69 3089.97 2291.50 2774.46 2475.04 5990.41 3253.82 6894.54 3177.56 1782.91 5489.86 48
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
CLD-MVS82.31 2681.65 2684.29 3088.47 5367.73 3785.81 5892.35 1375.78 1878.33 2686.58 7064.01 2794.35 3476.05 2087.48 3590.79 32
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
API-MVS81.99 2881.23 2884.26 3190.94 2170.18 1891.10 1389.32 4171.51 3878.66 2488.28 5065.26 2295.10 2064.74 4691.23 2087.51 73
114514_t80.68 3679.51 3684.20 3294.09 567.27 4289.64 2491.11 2958.75 10474.08 6490.72 2958.10 4995.04 2269.70 3489.42 2990.30 40
IS-MVSNet83.15 2082.81 1884.18 3389.94 2963.30 6591.59 988.46 5579.04 579.49 1892.16 1465.10 2394.28 3567.71 3791.86 1694.95 2
MVS_111021_LR82.61 2582.11 2284.11 3488.82 4471.58 1285.15 6086.16 6874.69 2380.47 1591.04 2662.29 3590.55 7480.33 1290.08 2690.20 42
OpenMVScopyleft72.83 1079.77 4178.33 4584.09 3585.17 7569.91 1990.57 1790.97 3066.70 6272.17 7391.91 1654.70 6193.96 4061.81 5790.95 2288.41 65
AdaColmapbinary80.58 3879.42 3884.06 3693.09 1068.91 2689.36 2788.97 5169.27 5275.70 4789.69 3657.20 5395.77 1263.06 4888.41 3387.50 74
PAPR81.66 3080.89 2983.99 3790.27 2664.00 6386.76 5091.77 2368.84 5577.13 3889.50 3967.63 1494.88 2667.55 3888.52 3293.09 18
ACMM73.20 880.78 3579.84 3483.58 3889.31 3568.37 3189.99 2191.60 2570.28 4477.25 3389.66 3753.37 7193.53 4774.24 2582.85 5588.85 61
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
DP-MVS76.78 6374.57 6883.42 3993.29 869.46 2288.55 3583.70 8063.98 8070.20 8088.89 4354.01 6794.80 2846.66 10881.88 6486.01 91
LS3D76.95 6274.82 6683.37 4090.45 2467.36 4189.15 3086.94 6461.87 9069.52 8790.61 3151.71 7894.53 3246.38 11186.71 4488.21 66
IB-MVS68.01 1575.85 7073.36 7583.31 4184.76 7766.03 4783.38 7485.06 7270.21 4669.40 8881.05 9945.76 9394.66 3065.10 4475.49 9689.25 56
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
MG-MVS83.41 1783.45 1483.28 4292.74 1262.28 7488.17 4289.50 3875.22 2181.49 1292.74 1366.75 1595.11 1872.85 2791.58 1892.45 21
CDS-MVSNet79.07 4677.70 4883.17 4387.60 6268.23 3284.40 6886.20 6767.49 6176.36 4486.54 7161.54 3890.79 7361.86 5687.33 3690.49 36
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
BH-RMVSNet79.61 4278.44 4483.14 4489.38 3265.93 4984.95 6287.15 6273.56 3078.19 2789.79 3556.67 5493.36 4859.53 6986.74 4390.13 43
PLCcopyleft70.83 1178.05 5576.37 5983.08 4591.88 1667.80 3588.19 4189.46 3964.33 7769.87 8588.38 4853.66 7093.58 4558.86 7082.73 5787.86 69
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
TAMVS78.89 4877.51 4983.03 4687.80 6067.79 3684.72 6585.05 7367.63 5876.75 4087.70 5362.25 3690.82 7258.53 7287.13 3990.49 36
cascas76.72 6474.64 6782.99 4785.78 7465.88 5182.33 7689.21 4660.85 9472.74 6881.02 10047.28 8993.75 4367.48 3985.02 4989.34 55
PVSNet_Blended80.98 3280.34 3282.90 4888.85 4265.40 5484.43 6792.00 1767.62 5978.11 2885.05 8066.02 1994.27 3671.52 3189.50 2789.01 58
TAPA-MVS73.13 979.15 4577.94 4682.79 4989.59 3062.99 7188.16 4391.51 2665.77 6877.14 3791.09 2460.91 4493.21 4950.26 10187.05 4092.17 23
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
F-COLMAP76.38 6674.33 7082.50 5089.28 3666.95 4488.41 3689.03 4864.05 7966.83 9788.61 4646.78 9192.89 5557.48 7878.55 7987.67 71
MVSTER79.01 4777.88 4782.38 5183.07 8664.80 6084.08 6988.95 5269.01 5478.69 2387.17 6254.70 6192.43 5974.69 2380.57 7289.89 47
PVSNet_BlendedMVS80.60 3780.02 3382.36 5288.85 4265.40 5486.16 5392.00 1769.34 5178.11 2886.09 7466.02 1994.27 3671.52 3182.06 6187.39 75
IterMVS-LS80.06 4079.38 3982.11 5385.89 7363.20 6786.79 4989.34 4074.19 2675.45 4986.72 6466.62 1692.39 6072.58 2976.86 8990.75 33
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
BH-untuned79.47 4478.60 4282.05 5489.19 4065.91 5086.07 5488.52 5472.18 3375.42 5087.69 5461.15 4293.54 4660.38 6586.83 4286.70 87
ACMH+68.96 1476.01 6874.01 7182.03 5588.60 4965.31 5688.86 3187.55 6170.25 4567.75 9487.47 5641.27 10493.19 5158.37 7375.94 9487.60 72
CNLPA78.08 5476.79 5681.97 5690.40 2571.07 1487.59 4684.55 7466.03 6772.38 7289.64 3857.56 5186.04 9259.61 6883.35 5388.79 62
ACMH67.68 1675.89 6973.93 7281.77 5788.71 4766.61 4588.62 3489.01 5069.81 4766.78 9886.70 6741.95 10391.51 6255.64 8578.14 8487.17 79
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
PAPM77.68 5876.40 5881.51 5887.29 6761.85 7683.78 7189.59 3764.74 7371.23 7688.70 4562.59 3293.66 4452.66 9587.03 4189.01 58
LTVRE_ROB69.57 1376.25 6774.54 6981.41 5988.60 4964.38 6279.24 9289.12 4770.76 4069.79 8687.86 5149.09 8693.20 5056.21 8480.16 7386.65 88
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
test178.40 4977.40 5081.40 6087.60 6263.01 6888.39 3789.28 4271.63 3575.34 5287.28 5754.80 5891.11 6562.72 4979.57 7590.09 44
FMVSNet177.44 5976.12 6181.40 6086.81 7063.01 6888.39 3789.28 4270.49 4274.39 6387.28 5749.06 8791.11 6560.91 6278.52 8090.09 44
GBi-Net78.40 4977.40 5081.40 6087.60 6263.01 6888.39 3789.28 4271.63 3575.34 5287.28 5754.80 5891.11 6562.72 4979.57 7590.09 44
FMVSNet278.20 5377.21 5381.20 6387.60 6262.89 7287.47 4789.02 4971.63 3575.29 5687.28 5754.80 5891.10 6862.38 5379.38 7889.61 53
TR-MVS77.44 5976.18 6081.20 6388.24 5563.24 6684.61 6686.40 6667.55 6077.81 3086.48 7254.10 6593.15 5257.75 7782.72 5887.20 78
ab-mvs79.51 4378.97 4081.14 6588.46 5460.91 7983.84 7089.24 4570.36 4379.03 2188.87 4463.23 3090.21 7665.12 4382.57 5992.28 22
FMVSNet377.88 5776.85 5580.97 6686.84 6962.36 7386.52 5288.77 5371.13 3975.34 5286.66 6954.07 6691.10 6862.72 4979.57 7589.45 54
BH-w/o78.21 5277.33 5280.84 6788.81 4565.13 5984.87 6387.85 5869.75 4974.52 6284.74 8261.34 3993.11 5358.24 7585.84 4884.27 99
COLMAP_ROBcopyleft66.92 1773.01 8470.41 9080.81 6887.13 6865.63 5388.30 4084.19 7762.96 8363.80 10787.69 5438.04 11092.56 5746.66 10874.91 9884.24 100
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
EG-PatchMatch MVS74.04 7671.82 7880.71 6984.92 7667.42 3885.86 5788.08 5766.04 6664.22 10583.85 8335.10 11692.56 5757.44 7980.83 6982.16 105
MSDG73.36 8070.99 8580.49 7084.51 7965.80 5280.71 8386.13 6965.70 6965.46 10283.74 8444.60 9690.91 7151.13 9976.89 8884.74 98
HY-MVS69.67 1277.95 5677.15 5480.36 7187.57 6660.21 8383.37 7587.78 5966.11 6575.37 5187.06 6363.27 2890.48 7561.38 5982.43 6090.40 39
1112_ss77.40 6176.43 5780.32 7289.11 4160.41 8283.65 7287.72 6062.13 8873.05 6686.72 6462.58 3389.97 7762.11 5580.80 7090.59 35
tpmp4_e2373.45 7871.17 8480.31 7383.55 8259.56 8681.88 7882.33 9057.94 10770.51 7981.62 9551.19 8291.63 6153.96 9077.51 8789.75 52
test_040272.79 8570.44 8979.84 7488.13 5665.99 4885.93 5684.29 7665.57 7067.40 9685.49 7746.92 9092.61 5635.88 12074.38 10180.94 107
CR-MVSNet73.37 7971.27 8379.67 7581.32 9865.19 5775.92 10180.30 9959.92 9872.73 6981.19 9752.50 7286.69 8759.84 6777.71 8587.11 81
RPMNet71.62 9068.94 9479.67 7581.32 9865.19 5775.92 10178.30 10757.60 10872.73 6976.45 11352.30 7486.69 8748.14 10577.71 8587.11 81
CostFormer75.24 7473.90 7379.27 7782.65 8958.27 8980.80 8182.73 8661.57 9175.33 5583.13 8855.52 5691.07 7064.98 4578.34 8388.45 64
Test_1112_low_res76.40 6575.44 6479.27 7789.28 3658.09 9081.69 7987.07 6359.53 10172.48 7186.67 6861.30 4089.33 8060.81 6480.15 7490.41 38
tpm273.26 8171.46 8078.63 7983.34 8356.71 9680.65 8480.40 9856.63 10973.55 6582.02 9351.80 7791.24 6356.35 8378.42 8287.95 67
RPSCF73.23 8271.46 8078.54 8082.50 9159.85 8582.18 7782.84 8558.96 10271.15 7789.41 4145.48 9584.77 9658.82 7171.83 10791.02 29
PatchmatchNetpermissive73.12 8371.33 8278.49 8183.18 8460.85 8079.63 8978.57 10664.13 7871.73 7479.81 10651.20 8185.97 9357.40 8076.36 9188.66 63
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
IterMVS74.29 7572.94 7678.35 8281.53 9763.49 6481.58 8082.49 8768.06 5769.99 8483.69 8551.66 7985.54 9465.85 4071.64 10886.01 91
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
ITE_SJBPF78.22 8381.77 9560.57 8183.30 8169.25 5367.54 9587.20 6136.33 11587.28 8554.34 8874.62 10086.80 85
Vis-MVSNet (Re-imp)78.36 5178.45 4378.07 8488.64 4851.78 10986.70 5179.63 10374.14 2775.11 5890.83 2861.29 4189.75 7858.10 7691.60 1792.69 20
OpenMVS_ROBcopyleft64.09 1970.56 9568.19 9877.65 8580.26 10559.41 8785.01 6182.96 8458.76 10365.43 10382.33 9037.63 11291.23 6445.34 11376.03 9382.32 103
tpm cat170.57 9468.31 9777.35 8682.41 9257.95 9178.08 9580.22 10152.04 11568.54 9277.66 10952.00 7687.84 8351.77 9672.07 10686.25 90
EPNet_dtu75.46 7274.86 6577.23 8782.57 9054.60 10386.89 4883.09 8271.64 3466.25 10085.86 7555.99 5588.04 8154.92 8686.55 4589.05 57
TDRefinement67.49 10364.34 10776.92 8873.47 11761.07 7884.86 6482.98 8359.77 9958.30 11485.13 7926.06 11887.89 8247.92 10660.59 11881.81 106
JIA-IIPM66.32 10762.82 10876.82 8977.09 11161.72 7765.34 12075.38 11258.04 10664.51 10462.32 12142.05 10286.51 9051.45 9869.22 11282.21 104
PatchMatch-RL72.38 8770.90 8676.80 9088.60 4967.38 4079.53 9076.17 11062.75 8569.36 8982.00 9445.51 9484.89 9553.62 9180.58 7178.12 114
CMPMVSbinary51.72 2170.19 9768.16 9976.28 9173.15 11857.55 9379.47 9183.92 7848.02 12056.48 11884.81 8143.13 9886.42 9162.67 5281.81 6584.89 97
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
USDC70.33 9668.37 9676.21 9280.60 10256.23 10079.19 9486.49 6560.89 9361.29 10985.47 7831.78 11789.47 7953.37 9276.21 9282.94 102
PVSNet64.34 1872.08 8970.87 8775.69 9386.21 7256.44 9874.37 10980.73 9662.06 8970.17 8182.23 9142.86 10083.31 9854.77 8784.45 5087.32 77
WTY-MVS75.65 7175.68 6275.57 9486.40 7156.82 9577.92 9682.40 8965.10 7276.18 4687.72 5263.13 3180.90 10660.31 6681.96 6289.00 60
Patchmtry70.74 9269.16 9375.49 9580.72 10054.07 10474.94 10880.30 9958.34 10570.01 8281.19 9752.50 7286.54 8953.37 9271.09 10985.87 93
XXY-MVS75.41 7375.56 6374.96 9683.59 8157.82 9280.59 8583.87 7966.54 6474.93 6088.31 4963.24 2980.09 10962.16 5476.85 9086.97 83
MIMVSNet70.69 9369.30 9274.88 9784.52 7856.35 9975.87 10379.42 10464.59 7467.76 9382.41 8941.10 10581.54 10546.64 11081.34 6686.75 86
TinyColmap67.30 10564.81 10674.76 9881.92 9456.68 9780.29 8681.49 9460.33 9656.27 11983.22 8724.77 11987.66 8445.52 11269.47 11179.95 110
tpm72.37 8871.71 7974.35 9982.19 9352.00 10779.22 9377.29 10864.56 7572.95 6783.68 8651.35 8083.26 9958.33 7475.80 9587.81 70
FMVSNet569.50 9867.96 10174.15 10082.97 8755.35 10180.01 8782.12 9162.56 8663.02 10881.53 9636.92 11381.92 10348.42 10474.06 10285.17 96
MIMVSNet168.58 10166.78 10373.98 10180.07 10651.82 10880.77 8284.37 7564.40 7659.75 11182.16 9236.47 11483.63 9742.73 11470.33 11086.48 89
HyFIR71.37 9170.50 8873.97 10280.52 10459.87 8470.92 11482.42 8856.28 11065.84 10176.50 11253.72 6983.21 10061.07 6187.21 3878.84 112
sss73.60 7773.64 7473.51 10382.80 8855.01 10276.12 10081.69 9362.47 8774.68 6185.85 7657.32 5278.11 11360.86 6380.93 6887.39 75
tpmrst72.39 8672.13 7773.18 10480.54 10349.91 11579.91 8879.08 10563.11 8171.69 7579.95 10455.32 5782.77 10165.66 4173.89 10486.87 84
LP61.36 11157.78 11272.09 10575.54 11458.53 8867.16 11975.22 11351.90 11654.13 12069.97 11837.73 11180.45 10832.74 12355.63 12177.29 115
EPMVS69.02 10068.16 9971.59 10679.61 10849.80 11677.40 9766.93 12162.82 8470.01 8279.05 10745.79 9277.86 11456.58 8275.26 9787.13 80
UnsupCasMVSNet_eth67.33 10465.99 10471.37 10773.48 11651.47 11175.16 10585.19 7165.20 7160.78 11080.93 10242.35 10177.20 11657.12 8153.69 12385.44 94
PMMVS69.34 9968.67 9571.35 10875.67 11362.03 7575.17 10473.46 11650.00 11868.68 9179.05 10752.07 7578.13 11261.16 6082.77 5673.90 117
dp66.80 10665.43 10570.90 10979.74 10748.82 11875.12 10774.77 11559.61 10064.08 10677.23 11042.89 9980.72 10748.86 10366.58 11483.16 101
PatchT68.46 10267.85 10270.29 11080.70 10143.93 12072.47 11174.88 11460.15 9770.55 7876.57 11149.94 8381.59 10450.58 10074.83 9985.34 95
UnsupCasMVSNet_bld63.70 10961.53 11070.21 11173.69 11551.39 11272.82 11081.89 9255.63 11257.81 11571.80 11638.67 10878.61 11149.26 10252.21 12480.63 108
LF4IMVS64.02 10862.19 10969.50 11270.90 11953.29 10676.13 9977.18 10952.65 11458.59 11280.98 10123.55 12076.52 11753.06 9466.66 11378.68 113
PVSNet_057.27 2061.67 11059.27 11168.85 11379.61 10857.44 9468.01 11873.44 11755.93 11158.54 11370.41 11744.58 9777.55 11547.01 10735.91 12571.55 118
no-one51.08 11745.79 12066.95 11457.92 12650.49 11459.63 12576.04 11148.04 11931.85 12556.10 12519.12 12480.08 11036.89 11926.52 12670.29 119
ANet_high50.57 11946.10 11963.99 11548.67 12739.13 12370.99 11380.85 9561.39 9231.18 12657.70 12317.02 12573.65 12031.22 12415.89 13179.18 111
MVS-HIRNet59.14 11257.67 11363.57 11681.65 9643.50 12171.73 11265.06 12239.59 12351.43 12157.73 12238.34 10982.58 10239.53 11673.95 10364.62 121
DSMNet-mixed57.77 11356.90 11460.38 11767.70 12235.61 12569.18 11753.97 12532.30 12857.49 11679.88 10540.39 10768.57 12438.78 11772.37 10576.97 116
FPMVS53.68 11451.64 11659.81 11865.08 12351.03 11369.48 11669.58 11841.46 12140.67 12472.32 11516.46 12670.00 12324.24 12665.42 11558.40 123
wuykxyi23d39.76 12233.18 12459.51 11946.98 12844.01 11957.70 12667.74 12024.13 12913.98 13234.33 1301.27 13271.33 12234.23 12218.23 12963.18 122
HyFIR lowres test51.79 11650.01 11857.11 12068.82 12049.21 11760.50 12353.26 12634.52 12443.77 12364.94 12020.34 12371.75 12139.87 11564.06 11750.39 124
PMVScopyleft37.38 2244.16 12140.28 12255.82 12140.82 13042.54 12265.12 12163.99 12334.43 12524.48 12857.12 1243.92 12976.17 11817.10 12955.52 12248.75 125
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
Gipumacopyleft45.18 12041.86 12155.16 12277.03 11251.52 11032.50 12880.52 9732.46 12627.12 12735.02 1299.52 12875.50 11922.31 12760.21 11938.45 128
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
new_pmnet50.91 11850.29 11752.78 12368.58 12134.94 12863.71 12256.63 12439.73 12244.95 12265.47 11921.93 12158.48 12734.98 12156.62 12064.92 120
N_pmnet52.79 11553.26 11551.40 12478.99 1107.68 13169.52 1153.89 13051.63 11757.01 11774.98 11440.83 10665.96 12537.78 11864.67 11680.56 109
PNet_i23d38.26 12335.42 12346.79 12558.74 12435.48 12659.65 12451.25 12732.45 12723.44 13047.53 1272.04 13158.96 12625.60 12518.09 13045.92 127
MVEpermissive26.22 2330.37 12425.89 12543.81 12644.55 12935.46 12728.87 12939.07 12818.20 13018.58 13140.18 1282.68 13047.37 12817.07 13023.78 12848.60 126
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
DeepMVS_CXcopyleft27.40 12740.17 13126.90 13024.59 12917.44 13123.95 12948.61 1269.77 12726.48 12918.06 12824.47 12728.83 129
wuyk23d16.82 12515.94 12619.46 12858.74 12431.45 12939.22 1273.74 1316.84 1326.04 1332.70 1311.27 13224.29 13010.54 13114.40 1322.63 130
ab-mvs-re7.23 1269.64 1270.00 1290.00 1320.00 1320.00 1300.00 1320.00 1330.00 13486.72 640.00 1340.00 1310.00 1320.00 1330.00 131
HQP2-MVS60.17 47
ACMMP++_ref81.95 63
HQP-MVS21.25 122
door69.44 119
NP-MVS90.24 34
Test By Simon64.33 24
ACMMP++81.25 67
HQP5-MVS66.98 43
MDTV_nov1_ep1369.97 9183.18 8453.48 10577.10 9880.18 10260.45 9569.33 9080.44 10348.89 8886.90 8651.60 9778.51 81
MDTV_nov1_ep13_2view37.79 12475.16 10555.10 11366.53 9949.34 8453.98 8987.94 68
HQP-NCC89.33 3389.17 2876.41 1477.23 35
BP-MVS77.47 18
HQP4-MVS77.24 3495.11 1891.03 28
HQP3-MVS92.19 1585.99 47
ACMP_Plane89.33 3389.17 2876.41 1477.23 35