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
indooroutdoorcourty.delive.electrofacadekickermeadowofficepipesplaygr.reliefrelief.terraceterrai.
sort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
APDe-MVS88.00 190.50 185.08 190.95 491.58 392.03 175.53 791.15 180.10 892.27 288.34 580.80 288.00 986.99 1391.09 495.16 1
HSP-MVS87.45 290.22 284.22 690.00 1791.80 290.59 375.80 389.93 378.35 1492.54 189.18 280.89 187.99 1086.29 2489.70 3493.85 7
HPM-MVS++87.09 388.92 784.95 292.61 187.91 3390.23 876.06 288.85 681.20 487.33 887.93 679.47 588.59 488.23 490.15 2793.60 14
SD-MVS86.96 489.45 384.05 990.13 1489.23 1689.77 1174.59 889.17 480.70 589.93 689.67 178.47 787.57 1486.79 1690.67 1193.76 10
TSAR-MVS + MP.86.88 589.23 484.14 789.78 2088.67 2590.59 373.46 2088.99 580.52 791.26 388.65 379.91 486.96 2486.22 2590.59 1293.83 8
APD-MVScopyleft86.84 688.91 884.41 390.66 790.10 690.78 275.64 487.38 1178.72 1290.68 586.82 980.15 387.13 1986.45 2290.51 1493.83 8
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
ACMMP_Plus86.52 789.01 583.62 1190.28 1390.09 790.32 674.05 1488.32 879.74 987.04 1085.59 1676.97 2389.35 188.44 390.35 2394.27 5
CNVR-MVS86.36 888.19 1184.23 591.33 389.84 890.34 575.56 587.36 1278.97 1181.19 2286.76 1078.74 689.30 288.58 190.45 2094.33 4
HFP-MVS86.15 987.95 1284.06 890.80 589.20 1789.62 1374.26 1087.52 980.63 686.82 1184.19 2278.22 987.58 1387.19 1190.81 693.13 18
SteuartSystems-ACMMP85.99 1088.31 1083.27 1590.73 689.84 890.27 774.31 984.56 2475.88 2387.32 985.04 1777.31 1889.01 388.46 291.14 393.96 6
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MPTG85.71 1186.88 1784.34 490.54 1187.11 3789.77 1174.17 1288.54 783.08 278.60 2686.10 1278.11 1087.80 1287.46 990.35 2392.56 20
ACMMPR85.52 1287.53 1483.17 1690.13 1489.27 1489.30 1473.97 1586.89 1477.14 1986.09 1283.18 2577.74 1487.42 1587.20 1090.77 792.63 19
MP-MVScopyleft85.50 1387.40 1583.28 1490.65 889.51 1389.16 1774.11 1383.70 2778.06 1685.54 1484.89 2077.31 1887.40 1687.14 1290.41 2193.65 13
NCCC85.34 1486.59 1983.88 1091.48 288.88 1989.79 1075.54 686.67 1577.94 1776.55 2984.99 1878.07 1188.04 787.68 790.46 1993.31 15
DeepPCF-MVS79.04 185.30 1588.93 681.06 2588.77 2890.48 485.46 3973.08 2190.97 273.77 3084.81 1685.95 1377.43 1788.22 687.73 687.85 6594.34 3
CSCG85.28 1687.68 1382.49 1989.95 1891.99 188.82 1871.20 3086.41 1679.63 1079.26 2388.36 473.94 3386.64 2686.67 1991.40 294.41 2
MCST-MVS85.13 1786.62 1883.39 1290.55 1089.82 1089.29 1573.89 1784.38 2576.03 2279.01 2585.90 1478.47 787.81 1186.11 2792.11 193.29 16
TSAR-MVS + ACMM85.10 1888.81 980.77 2889.55 2288.53 2788.59 2172.55 2387.39 1071.90 3690.95 487.55 774.57 2887.08 2186.54 2087.47 7093.67 11
train_agg84.86 1987.21 1682.11 2190.59 985.47 4889.81 973.55 1983.95 2673.30 3189.84 787.23 875.61 2686.47 2885.46 3289.78 3092.06 26
DeepC-MVS78.47 284.81 2086.03 2383.37 1389.29 2590.38 588.61 2076.50 186.25 1777.22 1875.12 3380.28 3777.59 1688.39 588.17 591.02 593.66 12
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
CP-MVS84.74 2186.43 2182.77 1889.48 2388.13 3288.64 1973.93 1684.92 1976.77 2081.94 2083.50 2377.29 2086.92 2586.49 2190.49 1593.14 17
PGM-MVS84.42 2286.29 2282.23 2090.04 1688.82 2189.23 1671.74 2882.82 3074.61 2684.41 1782.09 2777.03 2287.13 1986.73 1890.73 992.06 26
DeepC-MVS_fast78.24 384.27 2385.50 2582.85 1790.46 1289.24 1587.83 2674.24 1184.88 2076.23 2175.26 3281.05 3577.62 1588.02 887.62 890.69 1092.41 22
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TSAR-MVS + GP.83.69 2486.58 2080.32 2985.14 4786.96 3884.91 4370.25 3484.71 2373.91 2985.16 1585.63 1577.92 1285.44 3485.71 3089.77 3192.45 21
ACMMPcopyleft83.42 2585.27 2681.26 2488.47 2988.49 2888.31 2472.09 2583.42 2872.77 3482.65 1878.22 4175.18 2786.24 3185.76 2990.74 892.13 25
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
X-MVS83.23 2685.20 2780.92 2789.71 2188.68 2288.21 2573.60 1882.57 3171.81 3977.07 2781.92 2971.72 4886.98 2386.86 1490.47 1692.36 23
CDPH-MVS82.64 2785.03 2879.86 3289.41 2488.31 2988.32 2371.84 2780.11 3867.47 5482.09 1981.44 3371.85 4685.89 3386.15 2690.24 2591.25 32
3Dnovator+75.73 482.40 2882.76 3381.97 2288.02 3089.67 1186.60 3071.48 2981.28 3678.18 1564.78 6877.96 4377.13 2187.32 1786.83 1590.41 2191.48 30
PHI-MVS82.36 2985.89 2478.24 4286.40 4089.52 1285.52 3769.52 4182.38 3365.67 5981.35 2182.36 2673.07 3887.31 1886.76 1789.24 4191.56 29
MSLP-MVS++82.09 3082.66 3481.42 2387.03 3687.22 3685.82 3570.04 3580.30 3778.66 1368.67 5581.04 3677.81 1385.19 3784.88 3789.19 4391.31 31
CPTT-MVS81.77 3183.10 3280.21 3085.93 4386.45 4387.72 2770.98 3182.54 3271.53 4274.23 3881.49 3276.31 2582.85 5581.87 5188.79 5092.26 24
MVS_030481.73 3283.86 2979.26 3586.22 4289.18 1886.41 3167.15 5575.28 4870.75 4674.59 3583.49 2474.42 3087.05 2286.34 2390.58 1391.08 34
CANet81.62 3383.41 3079.53 3487.06 3588.59 2685.47 3867.96 5176.59 4674.05 2774.69 3481.98 2872.98 3986.14 3285.47 3189.68 3590.42 40
HQP-MVS81.19 3483.27 3178.76 3987.40 3385.45 4986.95 2870.47 3381.31 3566.91 5779.24 2476.63 4571.67 4984.43 4183.78 4289.19 4392.05 28
OMC-MVS80.26 3582.59 3577.54 4583.04 5585.54 4783.25 5065.05 6887.32 1372.42 3572.04 4378.97 3973.30 3683.86 4481.60 5488.15 5688.83 48
MVS_111021_HR80.13 3681.46 3878.58 4085.77 4485.17 5283.45 4969.28 4274.08 5470.31 4774.31 3775.26 5173.13 3786.46 2985.15 3589.53 3789.81 43
LGP-MVS_train79.83 3781.22 4078.22 4386.28 4185.36 5186.76 2969.59 3977.34 4365.14 6175.68 3170.79 6471.37 5184.60 3984.01 4090.18 2690.74 36
ACMP73.23 779.79 3880.53 4378.94 3785.61 4585.68 4685.61 3669.59 3977.33 4471.00 4574.45 3669.16 7371.88 4483.15 5283.37 4589.92 2990.57 39
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
3Dnovator73.76 579.75 3980.52 4478.84 3884.94 5287.35 3484.43 4565.54 6578.29 4273.97 2863.00 7475.62 5074.07 3285.00 3885.34 3390.11 2889.04 46
AdaColmapbinary79.74 4078.62 5181.05 2689.23 2686.06 4584.95 4271.96 2679.39 4175.51 2463.16 7268.84 7876.51 2483.55 4882.85 4788.13 5786.46 61
OPM-MVS79.68 4179.28 5080.15 3187.99 3186.77 4088.52 2272.72 2264.55 8067.65 5367.87 5974.33 5474.31 3186.37 3085.25 3489.73 3389.81 43
PCF-MVS73.28 679.42 4280.41 4578.26 4184.88 5388.17 3086.08 3269.85 3675.23 5068.43 4968.03 5878.38 4071.76 4781.26 6980.65 7088.56 5391.18 33
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CLD-MVS79.35 4381.23 3977.16 4785.01 5086.92 3985.87 3460.89 11580.07 4075.35 2572.96 4073.21 5768.43 6485.41 3684.63 3887.41 7185.44 72
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
MAR-MVS79.21 4480.32 4677.92 4487.46 3288.15 3183.95 4667.48 5474.28 5268.25 5064.70 6977.04 4472.17 4385.42 3585.00 3688.22 5487.62 55
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
canonicalmvs79.16 4582.37 3675.41 5382.33 6086.38 4480.80 5563.18 7982.90 2967.34 5572.79 4176.07 4769.62 5783.46 5184.41 3989.20 4290.60 38
DELS-MVS79.15 4681.07 4176.91 4883.54 5487.31 3584.45 4464.92 6969.98 5969.34 4871.62 4576.26 4669.84 5686.57 2785.90 2889.39 3989.88 42
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
EPNet79.08 4780.62 4277.28 4688.90 2783.17 6583.65 4772.41 2474.41 5167.15 5676.78 2874.37 5364.43 9983.70 4783.69 4387.15 7688.19 50
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
ACMM72.26 878.86 4878.13 5279.71 3386.89 3783.40 6286.02 3370.50 3275.28 4871.49 4363.01 7369.26 7273.57 3584.11 4383.98 4189.76 3287.84 53
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
QAPM78.47 4980.22 4776.43 5085.03 4986.75 4180.62 5666.00 6273.77 5565.35 6065.54 6678.02 4272.69 4083.71 4683.36 4688.87 4990.41 41
TSAR-MVS + COLMAP78.34 5081.64 3774.48 6080.13 7185.01 5381.73 5165.93 6484.75 2261.68 7085.79 1366.27 8471.39 5082.91 5480.78 6186.01 12485.98 63
MVS_111021_LR78.13 5179.85 4976.13 5181.12 6481.50 7280.28 5765.25 6676.09 4771.32 4476.49 3072.87 5872.21 4282.79 5681.29 5686.59 11187.91 52
TAPA-MVS71.42 977.69 5280.05 4874.94 5680.68 6784.52 5581.36 5263.14 8084.77 2164.82 6368.72 5375.91 4971.86 4581.62 6079.55 8287.80 6685.24 75
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
CNLPA77.20 5377.54 5676.80 4982.63 5784.31 5679.77 6064.64 7085.17 1873.18 3256.37 10669.81 6974.53 2981.12 7178.69 8986.04 12387.29 58
PVSNet_Blended_VisFu76.57 5477.90 5375.02 5580.56 6886.58 4279.24 6466.18 5964.81 7768.18 5165.61 6471.45 6167.05 6684.16 4281.80 5288.90 4790.92 35
PVSNet_BlendedMVS76.21 5577.52 5774.69 5879.46 7383.79 5977.50 9864.34 7369.88 6071.88 3768.54 5670.42 6667.05 6683.48 4979.63 7887.89 6386.87 59
PVSNet_Blended76.21 5577.52 5774.69 5879.46 7383.79 5977.50 9864.34 7369.88 6071.88 3768.54 5670.42 6667.05 6683.48 4979.63 7887.89 6386.87 59
OpenMVScopyleft70.44 1076.15 5776.82 6475.37 5485.01 5084.79 5478.99 6962.07 10371.27 5867.88 5257.91 9872.36 5970.15 5582.23 5881.41 5588.12 5887.78 54
PLCcopyleft68.99 1175.68 5875.31 6876.12 5282.94 5681.26 7579.94 5966.10 6077.15 4566.86 5859.13 8768.53 7973.73 3480.38 8079.04 8687.13 8081.68 122
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
MVS_Test75.37 5977.13 6273.31 6479.07 7681.32 7479.98 5860.12 13469.72 6264.11 6570.53 4773.22 5668.90 6080.14 8679.48 8487.67 6785.50 70
Effi-MVS+75.28 6076.20 6574.20 6181.15 6383.24 6381.11 5363.13 8166.37 6660.27 7564.30 7068.88 7770.93 5481.56 6281.69 5388.61 5187.35 56
DI_MVS_plusplus_trai75.13 6176.12 6673.96 6278.18 8181.55 7180.97 5462.54 9768.59 6365.13 6261.43 7574.81 5269.32 5981.01 7379.59 8087.64 6885.89 64
UA-Net74.47 6277.80 5470.59 8185.33 4685.40 5073.54 13465.98 6360.65 10456.00 10572.11 4279.15 3854.63 16083.13 5382.25 4988.04 5981.92 120
LS3D74.08 6373.39 7374.88 5785.05 4882.62 6879.71 6168.66 4572.82 5658.80 8057.61 9961.31 9771.07 5380.32 8278.87 8886.00 12680.18 135
EPP-MVSNet74.00 6477.41 5970.02 9680.53 6983.91 5874.99 11562.68 9365.06 7549.77 14168.68 5472.09 6063.06 10582.49 5780.73 6289.12 4588.91 47
IS_MVSNet73.33 6577.34 6068.65 10981.29 6283.47 6174.45 11863.58 7765.75 7248.49 14467.11 6370.61 6554.63 16084.51 4083.58 4489.48 3886.34 62
CANet_DTU73.29 6676.96 6369.00 10577.04 9982.06 7079.49 6356.30 16867.85 6453.29 11971.12 4670.37 6861.81 11581.59 6180.96 5986.09 11884.73 84
diffmvs73.13 6775.65 6770.19 9374.07 14377.17 12778.24 9257.45 16172.44 5764.02 6669.05 5175.92 4864.86 9775.18 15375.27 15582.47 16484.53 85
Fast-Effi-MVS+73.11 6873.66 7172.48 6677.72 9280.88 8178.55 8458.83 15365.19 7460.36 7459.98 8262.42 9571.22 5281.66 5980.61 7288.20 5584.88 83
UGNet72.78 6977.67 5567.07 13071.65 16583.24 6375.20 10963.62 7664.93 7656.72 9971.82 4473.30 5549.02 17581.02 7280.70 6886.22 11588.67 49
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
Vis-MVSNetpermissive72.77 7077.20 6167.59 12074.19 14284.01 5776.61 10561.69 10860.62 10550.61 13570.25 4971.31 6355.57 15583.85 4582.28 4886.90 9088.08 51
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
FC-MVSNet-train72.60 7175.07 6969.71 10081.10 6578.79 10673.74 13265.23 6766.10 6953.34 11870.36 4863.40 9256.92 14381.44 6380.96 5987.93 6184.46 86
MVSTER72.06 7274.24 7069.51 10170.39 17375.97 14976.91 10257.36 16364.64 7961.39 7268.86 5263.76 9063.46 10281.44 6379.70 7787.56 6985.31 74
Effi-MVS+-dtu71.82 7371.86 8171.78 6778.77 7780.47 9078.55 8461.67 10960.68 10355.49 10658.48 9165.48 8668.85 6176.92 13775.55 15287.35 7285.46 71
IterMVS-LS71.69 7472.82 7770.37 9077.54 9476.34 14575.13 11360.46 12261.53 9957.57 8864.89 6767.33 8166.04 9177.09 13677.37 11385.48 13985.18 76
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
MSDG71.52 7569.87 9573.44 6382.21 6179.35 9979.52 6264.59 7166.15 6861.87 6953.21 15056.09 12965.85 9578.94 10178.50 9086.60 11076.85 161
ACMH+66.54 1371.36 7670.09 9072.85 6582.59 5881.13 7678.56 8368.04 4961.55 9852.52 12551.50 16954.14 14268.56 6378.85 10279.50 8386.82 9783.94 91
IB-MVS66.94 1271.21 7771.66 8270.68 7879.18 7582.83 6772.61 14161.77 10759.66 11163.44 6853.26 14859.65 10259.16 12876.78 14082.11 5087.90 6287.33 57
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
GBi-Net70.78 7873.37 7467.76 11472.95 15378.00 11475.15 11062.72 8864.13 8151.44 12758.37 9269.02 7457.59 13581.33 6680.72 6386.70 10582.02 114
test170.78 7873.37 7467.76 11472.95 15378.00 11475.15 11062.72 8864.13 8151.44 12758.37 9269.02 7457.59 13581.33 6680.72 6386.70 10582.02 114
ACMH65.37 1470.71 8070.00 9171.54 6882.51 5982.47 6977.78 9568.13 4856.19 14946.06 15854.30 13151.20 17868.68 6280.66 7580.72 6386.07 11984.45 87
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
UniMVSNet_NR-MVSNet70.59 8172.19 7968.72 10777.72 9280.72 8273.81 13069.65 3861.99 9343.23 16960.54 7857.50 10858.57 12979.56 9481.07 5889.34 4083.97 89
FMVSNet370.49 8272.90 7667.67 11872.88 15677.98 11774.96 11662.72 8864.13 8151.44 12758.37 9269.02 7457.43 13879.43 9679.57 8186.59 11181.81 121
FMVSNet270.39 8372.67 7867.72 11772.95 15378.00 11475.15 11062.69 9263.29 8651.25 13155.64 10868.49 8057.59 13580.91 7480.35 7486.70 10582.02 114
v670.35 8469.94 9270.83 7074.68 13580.62 8378.81 7460.16 13258.81 11658.17 8455.01 11757.31 11366.32 8477.53 12176.73 13286.82 9783.62 93
v1neww70.34 8569.93 9370.82 7174.68 13580.61 8478.80 7560.17 12958.74 11858.10 8555.00 11857.28 11466.33 8277.53 12176.74 12886.82 9783.61 94
v7new70.34 8569.93 9370.82 7174.68 13580.61 8478.80 7560.17 12958.74 11858.10 8555.00 11857.28 11466.33 8277.53 12176.74 12886.82 9783.61 94
v770.33 8769.87 9570.88 6974.79 12781.04 7779.22 6560.57 11957.70 12856.65 10154.23 13655.29 13466.95 6978.28 10877.47 10987.12 8385.05 79
v870.23 8869.86 9770.67 7974.69 13479.82 9578.79 7759.18 14358.80 11758.20 8355.00 11857.33 11166.31 8577.51 12476.71 13686.82 9783.88 92
v1070.22 8969.76 9970.74 7574.79 12780.30 9379.22 6559.81 13757.71 12756.58 10254.22 13855.31 13266.95 6978.28 10877.47 10987.12 8385.07 78
MS-PatchMatch70.17 9070.49 8869.79 9880.98 6677.97 11977.51 9758.95 14562.33 9155.22 10953.14 15165.90 8562.03 11079.08 10077.11 11784.08 15677.91 151
v1870.10 9169.52 10270.77 7474.66 13877.06 13078.84 7258.84 15260.01 10959.23 7755.06 11657.47 10966.34 8177.50 12576.75 12686.71 10482.77 108
v1670.07 9269.46 10470.79 7374.74 13377.08 12978.79 7758.86 14759.75 11059.15 7854.87 12357.33 11166.38 7977.61 11976.77 12186.81 10282.79 106
v2v48270.05 9369.46 10470.74 7574.62 13980.32 9279.00 6860.62 11857.41 12956.89 9455.43 11155.14 13566.39 7877.25 13377.14 11686.90 9083.57 99
v1770.03 9469.43 10970.72 7774.75 13277.09 12878.78 7958.85 14959.53 11358.72 8154.87 12357.39 11066.38 7977.60 12076.75 12686.83 9682.80 104
divwei89l23v2f11269.97 9569.44 10770.58 8374.78 12980.50 8878.85 7060.30 12456.97 13356.75 9754.67 12856.27 12565.92 9377.37 12876.72 13386.88 9383.58 98
v169.97 9569.45 10670.59 8174.78 12980.51 8778.84 7260.30 12456.98 13256.81 9654.69 12656.29 12465.91 9477.37 12876.71 13686.89 9283.59 96
v114169.96 9769.44 10770.58 8374.78 12980.50 8878.85 7060.30 12456.95 13456.74 9854.68 12756.26 12665.93 9277.38 12776.72 13386.88 9383.57 99
v114469.93 9869.36 11070.61 8074.89 12080.93 7879.11 6760.64 11755.97 15255.31 10853.85 14354.14 14266.54 7678.10 11077.44 11187.14 7985.09 77
DU-MVS69.63 9970.91 8568.13 11375.99 10879.54 9673.81 13069.20 4361.20 10143.23 16958.52 8953.50 14958.57 12979.22 9880.45 7387.97 6083.97 89
v1569.61 10068.88 11570.46 8574.81 12677.03 13378.75 8058.83 15357.06 13157.18 9054.55 12956.37 12066.13 8977.70 11676.76 12387.03 8782.69 111
V1469.59 10168.86 11670.45 8774.83 12577.04 13178.70 8158.83 15356.95 13457.08 9254.41 13056.34 12166.15 8677.77 11576.76 12387.08 8582.74 109
V969.58 10268.83 11770.46 8574.85 12477.04 13178.65 8258.85 14956.83 13757.12 9154.26 13456.31 12266.14 8877.83 11476.76 12387.13 8082.79 106
v1269.54 10368.79 11970.41 8874.88 12177.03 13378.54 8758.85 14956.71 13856.87 9554.13 13956.23 12766.15 8677.89 11276.74 12887.17 7582.80 104
UniMVSNet (Re)69.53 10471.90 8066.76 13676.42 10280.93 7872.59 14268.03 5061.75 9741.68 17758.34 9557.23 11653.27 16779.53 9580.62 7188.57 5284.90 82
v1369.52 10568.76 12170.41 8874.88 12177.02 13578.52 8858.86 14756.61 14356.91 9354.00 14156.17 12866.11 9077.93 11176.74 12887.21 7482.83 103
v119269.50 10668.83 11770.29 9174.49 14080.92 8078.55 8460.54 12055.04 16154.21 11152.79 15852.33 16666.92 7177.88 11377.35 11487.04 8685.51 69
HyFIR lowres test69.47 10768.94 11470.09 9576.77 10182.93 6676.63 10460.17 12959.00 11554.03 11340.54 20065.23 8767.89 6576.54 14478.30 9485.03 14580.07 136
v1169.37 10868.65 12570.20 9274.87 12376.97 13678.29 9158.55 15756.38 14656.04 10454.02 14054.98 13666.47 7778.30 10776.91 11986.97 8883.02 102
v14419269.34 10968.68 12470.12 9474.06 14480.54 8678.08 9460.54 12054.99 16354.13 11252.92 15552.80 16266.73 7477.13 13576.72 13387.15 7685.63 65
TranMVSNet+NR-MVSNet69.25 11070.81 8667.43 12177.23 9879.46 9873.48 13669.66 3760.43 10639.56 18158.82 8853.48 15155.74 15379.59 9281.21 5788.89 4882.70 110
CHOSEN 1792x268869.20 11169.26 11169.13 10376.86 10078.93 10177.27 10060.12 13461.86 9554.42 11042.54 19461.61 9666.91 7278.55 10578.14 9879.23 17983.23 101
v192192069.03 11268.32 13069.86 9774.03 14580.37 9177.55 9660.25 12854.62 16453.59 11752.36 16551.50 17766.75 7377.17 13476.69 13886.96 8985.56 66
CostFormer68.92 11369.58 10168.15 11275.98 11076.17 14878.22 9351.86 18465.80 7161.56 7163.57 7162.83 9361.85 11370.40 18868.67 18679.42 17779.62 141
FMVSNet168.84 11470.47 8966.94 13271.35 17077.68 12274.71 11762.35 10256.93 13649.94 14050.01 17564.59 8857.07 14181.33 6680.72 6386.25 11482.00 117
NR-MVSNet68.79 11570.56 8766.71 13877.48 9579.54 9673.52 13569.20 4361.20 10139.76 18058.52 8950.11 18451.37 17180.26 8480.71 6788.97 4683.59 96
V4268.76 11669.63 10067.74 11664.93 19478.01 11378.30 9056.48 16758.65 12056.30 10354.26 13457.03 11764.85 9877.47 12677.01 11885.60 13784.96 81
v124068.64 11767.89 13669.51 10173.89 14780.26 9476.73 10359.97 13653.43 17353.08 12051.82 16850.84 18066.62 7576.79 13976.77 12186.78 10385.34 73
Fast-Effi-MVS+-dtu68.34 11869.47 10367.01 13175.15 11677.97 11977.12 10155.40 17157.87 12246.68 15556.17 10760.39 9862.36 10876.32 14576.25 14285.35 14181.34 123
tpmp4_e2368.32 11967.08 14469.76 9977.86 8575.22 15978.37 8956.17 17066.06 7064.27 6457.15 10354.89 13763.40 10370.97 18168.29 19178.46 18177.00 160
GA-MVS68.14 12069.17 11266.93 13373.77 14878.50 11074.45 11858.28 15855.11 16048.44 14560.08 8053.99 14561.50 11678.43 10677.57 10785.13 14380.54 130
conf200view1168.11 12168.72 12267.39 12377.83 8778.93 10174.28 12362.81 8456.64 14046.70 15452.65 16053.47 15256.59 14480.41 7678.43 9186.11 11680.53 131
tfpn200view968.11 12168.72 12267.40 12277.83 8778.93 10174.28 12362.81 8456.64 14046.82 15252.65 16053.47 15256.59 14480.41 7678.43 9186.11 11680.52 132
EPNet_dtu68.08 12371.00 8464.67 14979.64 7268.62 18375.05 11463.30 7866.36 6745.27 16267.40 6166.84 8343.64 18975.37 15174.98 15981.15 16977.44 154
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
thres20067.98 12468.55 12767.30 12577.89 8478.86 10474.18 12762.75 8656.35 14746.48 15652.98 15453.54 14856.46 14680.41 7677.97 9986.05 12179.78 140
thres40067.95 12568.62 12667.17 12777.90 8278.59 10974.27 12562.72 8856.34 14845.77 16053.00 15353.35 15656.46 14680.21 8578.43 9185.91 13080.43 133
pmmvs467.89 12667.39 14168.48 11071.60 16773.57 16774.45 11860.98 11464.65 7857.97 8754.95 12151.73 17561.88 11273.78 16075.11 15783.99 15877.91 151
v14867.85 12767.53 13768.23 11173.25 15177.57 12574.26 12657.36 16355.70 15457.45 8953.53 14455.42 13161.96 11175.23 15273.92 16285.08 14481.32 124
Vis-MVSNet (Re-imp)67.83 12873.52 7261.19 16978.37 8076.72 13966.80 17262.96 8265.50 7334.17 19567.19 6269.68 7039.20 19879.39 9779.44 8585.68 13676.73 162
PatchMatch-RL67.78 12966.65 14969.10 10473.01 15272.69 16968.49 16061.85 10662.93 8960.20 7656.83 10550.42 18269.52 5875.62 15074.46 16181.51 16773.62 181
thres600view767.68 13068.43 12866.80 13477.90 8278.86 10473.84 12962.75 8656.07 15044.70 16652.85 15752.81 16155.58 15480.41 7677.77 10286.05 12180.28 134
COLMAP_ROBcopyleft62.73 1567.66 13166.76 14868.70 10880.49 7077.98 11775.29 10862.95 8363.62 8449.96 13947.32 18750.72 18158.57 12976.87 13875.50 15384.94 14875.33 171
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
CDS-MVSNet67.65 13269.83 9865.09 14475.39 11576.55 14074.42 12163.75 7553.55 17249.37 14359.41 8562.45 9444.44 18779.71 9079.82 7683.17 16277.36 155
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
RPSCF67.64 13371.25 8363.43 15861.86 20070.73 17567.26 16850.86 18974.20 5358.91 7967.49 6069.33 7164.10 10071.41 17468.45 19077.61 18377.17 156
view60067.63 13468.36 12966.77 13577.84 8678.66 10773.74 13262.62 9556.04 15144.98 16352.86 15652.83 16055.48 15780.36 8177.75 10385.95 12980.02 137
thres100view90067.60 13568.02 13367.12 12977.83 8777.75 12173.90 12862.52 9856.64 14046.82 15252.65 16053.47 15255.92 15078.77 10377.62 10685.72 13579.23 144
Baseline_NR-MVSNet67.53 13668.77 12066.09 14075.99 10874.75 16272.43 14368.41 4661.33 10038.33 18451.31 17054.13 14456.03 14979.22 9878.19 9685.37 14082.45 112
USDC67.36 13767.90 13566.74 13771.72 16375.23 15771.58 14960.28 12767.45 6550.54 13660.93 7645.20 20062.08 10976.56 14374.50 16084.25 15575.38 170
view80067.35 13868.22 13266.35 13977.83 8778.62 10872.97 14062.58 9655.71 15344.13 16752.69 15952.24 17054.58 16280.27 8378.19 9686.01 12479.79 139
DWT-MVSNet_training67.24 13965.96 15668.74 10676.15 10674.36 16574.37 12256.66 16661.82 9660.51 7358.23 9749.76 18665.07 9670.04 18970.39 17679.70 17677.11 158
EG-PatchMatch MVS67.24 13966.94 14567.60 11978.73 7881.35 7373.28 13859.49 13946.89 19951.42 13043.65 19153.49 15055.50 15681.38 6580.66 6987.15 7681.17 125
v7n67.05 14166.94 14567.17 12772.35 15878.97 10073.26 13958.88 14651.16 18450.90 13248.21 18050.11 18460.96 11877.70 11677.38 11286.68 10885.05 79
tfpn66.58 14267.18 14265.88 14177.82 9178.45 11172.07 14562.52 9855.35 15743.21 17152.54 16446.12 19753.68 16380.02 8778.23 9585.99 12779.55 142
IterMVS66.36 14368.30 13164.10 15169.48 18074.61 16373.41 13750.79 19057.30 13048.28 14660.64 7759.92 10160.85 12274.14 15872.66 16881.80 16678.82 147
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
conf0.05thres100066.26 14466.77 14765.66 14277.45 9678.10 11271.85 14862.44 10151.47 18343.00 17247.92 18251.66 17653.40 16579.71 9077.97 9985.82 13180.56 129
TDRefinement66.09 14565.03 16867.31 12469.73 17776.75 13875.33 10664.55 7260.28 10749.72 14245.63 18942.83 20360.46 12375.75 14775.95 14884.08 15678.04 150
pm-mvs165.62 14667.42 13963.53 15773.66 14976.39 14469.66 15460.87 11649.73 19143.97 16851.24 17157.00 11848.16 17679.89 8877.84 10184.85 15179.82 138
tpm cat165.41 14763.81 17667.28 12675.61 11472.88 16875.32 10752.85 17862.97 8863.66 6753.24 14953.29 15861.83 11465.54 20064.14 20374.43 19774.60 173
anonymousdsp65.28 14867.98 13462.13 16358.73 20873.98 16667.10 17050.69 19148.41 19447.66 15154.27 13252.75 16361.45 11776.71 14180.20 7587.13 8089.53 45
v5265.23 14966.24 15164.06 15261.94 19876.42 14272.06 14654.30 17349.94 18850.04 13847.41 18552.42 16460.23 12575.71 14876.22 14385.78 13285.56 66
V465.23 14966.23 15264.06 15261.94 19876.42 14272.05 14754.31 17249.91 19050.06 13747.42 18452.40 16560.24 12475.71 14876.22 14385.78 13285.56 66
v74865.12 15165.24 16364.98 14669.77 17676.45 14169.47 15657.06 16549.93 18950.70 13347.87 18349.50 18857.14 14073.64 16275.18 15685.75 13484.14 88
tfpn_ndepth65.09 15267.12 14362.73 16075.75 11376.23 14668.00 16260.36 12358.16 12140.27 17954.89 12254.22 14146.80 18276.69 14275.66 15085.19 14273.98 179
PMMVS65.06 15369.17 11260.26 17555.25 21763.43 20066.71 17343.01 21562.41 9050.64 13469.44 5067.04 8263.29 10474.36 15773.54 16482.68 16373.99 178
CR-MVSNet64.83 15465.54 16164.01 15470.64 17269.41 17865.97 17752.74 17957.81 12452.65 12254.27 13256.31 12260.92 11972.20 17073.09 16681.12 17075.69 167
TransMVSNet (Re)64.74 15565.66 16063.66 15677.40 9775.33 15469.86 15362.67 9447.63 19741.21 17850.01 17552.33 16645.31 18679.57 9377.69 10585.49 13877.07 159
test-LLR64.42 15664.36 17264.49 15075.02 11863.93 19766.61 17461.96 10454.41 16547.77 14857.46 10060.25 9955.20 15870.80 18269.33 18180.40 17374.38 175
MDTV_nov1_ep1364.37 15765.24 16363.37 15968.94 18270.81 17472.40 14450.29 19360.10 10853.91 11560.07 8159.15 10457.21 13969.43 19267.30 19377.47 18469.78 192
tfpnview1164.33 15866.17 15362.18 16276.25 10375.23 15767.45 16561.16 11055.50 15536.38 18955.35 11251.89 17246.96 17877.28 13276.10 14784.86 15071.85 187
tfpnnormal64.27 15963.64 17765.02 14575.84 11175.61 15171.24 15162.52 9847.79 19642.97 17342.65 19344.49 20152.66 16978.77 10376.86 12084.88 14979.29 143
tfpn_n40064.23 16066.05 15462.12 16476.20 10475.24 15567.43 16661.15 11154.04 17036.38 18955.35 11251.89 17246.94 17977.31 13076.15 14584.59 15272.36 184
tfpnconf64.23 16066.05 15462.12 16476.20 10475.24 15567.43 16661.15 11154.04 17036.38 18955.35 11251.89 17246.94 17977.31 13076.15 14584.59 15272.36 184
PatchmatchNetpermissive64.21 16264.65 17063.69 15571.29 17168.66 18269.63 15551.70 18663.04 8753.77 11659.83 8458.34 10660.23 12568.54 19566.06 19875.56 19268.08 196
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
dps64.00 16362.99 17965.18 14373.29 15072.07 17168.98 15953.07 17757.74 12658.41 8255.55 11047.74 19360.89 12169.53 19167.14 19576.44 18971.19 189
tfpn100063.81 16466.31 15060.90 17175.76 11275.74 15065.14 18160.14 13356.47 14435.99 19255.11 11552.30 16843.42 19076.21 14675.34 15484.97 14773.01 183
pmmvs-eth3d63.52 16562.44 18664.77 14866.82 18870.12 17769.41 15759.48 14054.34 16852.71 12146.24 18844.35 20256.93 14272.37 16573.77 16383.30 16075.91 164
WR-MVS63.03 16667.40 14057.92 18575.14 11777.60 12460.56 19666.10 6054.11 16923.88 20753.94 14253.58 14734.50 20373.93 15977.71 10487.35 7280.94 126
PEN-MVS62.96 16765.77 15959.70 17873.98 14675.45 15263.39 18967.61 5352.49 17625.49 20653.39 14549.12 18940.85 19671.94 17277.26 11586.86 9580.72 128
TinyColmap62.84 16861.03 19264.96 14769.61 17871.69 17268.48 16159.76 13855.41 15647.69 15047.33 18634.20 21362.76 10774.52 15572.59 16981.44 16871.47 188
CP-MVSNet62.68 16965.49 16259.40 18171.84 16175.34 15362.87 19167.04 5652.64 17527.19 20453.38 14648.15 19141.40 19471.26 17575.68 14986.07 11982.00 117
gg-mvs-nofinetune62.55 17065.05 16759.62 17978.72 7977.61 12370.83 15253.63 17439.71 21122.04 21636.36 20464.32 8947.53 17781.16 7079.03 8785.00 14677.17 156
CVMVSNet62.55 17065.89 15758.64 18366.95 18669.15 18066.49 17656.29 16952.46 17732.70 19659.27 8658.21 10750.09 17371.77 17371.39 17379.31 17878.99 146
CMPMVSbinary47.78 1762.49 17262.52 18462.46 16170.01 17570.66 17662.97 19051.84 18551.98 17956.71 10042.87 19253.62 14657.80 13472.23 16870.37 17775.45 19475.91 164
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
pmmvs662.41 17362.88 18061.87 16671.38 16975.18 16167.76 16459.45 14141.64 20742.52 17637.33 20252.91 15946.87 18177.67 11876.26 14183.23 16179.18 145
tpm62.41 17363.15 17861.55 16872.24 15963.79 19971.31 15046.12 20657.82 12355.33 10759.90 8354.74 13853.63 16467.24 19864.29 20170.65 20874.25 177
PS-CasMVS62.38 17565.06 16659.25 18271.73 16275.21 16062.77 19266.99 5751.94 18126.96 20552.00 16747.52 19441.06 19571.16 17875.60 15185.97 12881.97 119
pmmvs562.37 17664.04 17460.42 17365.03 19271.67 17367.17 16952.70 18150.30 18544.80 16454.23 13651.19 17949.37 17472.88 16473.48 16583.45 15974.55 174
tpmrst62.00 17762.35 18761.58 16771.62 16664.14 19669.07 15848.22 20262.21 9253.93 11458.26 9655.30 13355.81 15263.22 20562.62 20670.85 20770.70 190
PatchT61.97 17864.04 17459.55 18060.49 20267.40 18656.54 20348.65 19856.69 13952.65 12251.10 17252.14 17160.92 11972.20 17073.09 16678.03 18275.69 167
DTE-MVSNet61.85 17964.96 16958.22 18474.32 14174.39 16461.01 19567.85 5251.76 18221.91 21753.28 14748.17 19037.74 19972.22 16976.44 13986.52 11378.49 148
SixPastTwentyTwo61.84 18062.45 18561.12 17069.20 18172.20 17062.03 19357.40 16246.54 20038.03 18657.14 10441.72 20558.12 13369.67 19071.58 17281.94 16578.30 149
WR-MVS_H61.83 18165.87 15857.12 18871.72 16376.87 13761.45 19466.19 5851.97 18022.92 21453.13 15252.30 16833.80 20471.03 17975.00 15886.65 10980.78 127
LTVRE_ROB59.44 1661.82 18262.64 18360.87 17272.83 15777.19 12664.37 18558.97 14433.56 22028.00 20352.59 16342.21 20463.93 10174.52 15576.28 14077.15 18682.13 113
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
RPMNet61.71 18362.88 18060.34 17469.51 17969.41 17863.48 18849.23 19457.81 12445.64 16150.51 17350.12 18353.13 16868.17 19768.49 18981.07 17175.62 169
TESTMET0.1,161.10 18464.36 17257.29 18757.53 21063.93 19766.61 17436.22 22154.41 16547.77 14857.46 10060.25 9955.20 15870.80 18269.33 18180.40 17374.38 175
test-mter60.84 18564.62 17156.42 19055.99 21564.18 19565.39 17934.23 22354.39 16746.21 15757.40 10259.49 10355.86 15171.02 18069.65 17980.87 17276.20 163
PM-MVS60.48 18660.94 19359.94 17658.85 20766.83 18964.27 18651.39 18755.03 16248.03 14750.00 17740.79 20758.26 13269.20 19367.13 19678.84 18077.60 153
MDTV_nov1_ep13_2view60.16 18760.51 19459.75 17765.39 19169.05 18168.00 16248.29 20051.99 17845.95 15948.01 18149.64 18753.39 16668.83 19466.52 19777.47 18469.55 193
EPMVS60.00 18861.97 18857.71 18668.46 18363.17 20364.54 18448.23 20163.30 8544.72 16560.19 7956.05 13050.85 17265.27 20262.02 20869.44 21063.81 203
TAMVS59.58 18962.81 18255.81 19266.03 19065.64 19463.86 18748.74 19749.95 18737.07 18854.77 12558.54 10544.44 18772.29 16771.79 17074.70 19666.66 198
test0.0.03 158.80 19061.58 19055.56 19375.02 11868.45 18459.58 20061.96 10452.74 17429.57 19949.75 17854.56 13931.46 20671.19 17669.77 17875.75 19064.57 201
CHOSEN 280x42058.70 19161.88 18954.98 19555.45 21650.55 22064.92 18240.36 21755.21 15838.13 18548.31 17963.76 9063.03 10673.73 16168.58 18868.00 21373.04 182
MIMVSNet58.52 19261.34 19155.22 19460.76 20167.01 18866.81 17149.02 19656.43 14538.90 18340.59 19954.54 14040.57 19773.16 16371.65 17175.30 19566.00 199
FMVSNet557.24 19360.02 19553.99 19856.45 21262.74 20465.27 18047.03 20355.14 15939.55 18240.88 19753.42 15541.83 19172.35 16671.10 17573.79 19964.50 202
gm-plane-assit57.00 19457.62 20056.28 19176.10 10762.43 20747.62 21646.57 20433.84 21923.24 21037.52 20140.19 20859.61 12779.81 8977.55 10884.55 15472.03 186
FC-MVSNet-test56.90 19565.20 16547.21 20766.98 18563.20 20249.11 21458.60 15659.38 11411.50 22765.60 6556.68 11924.66 21871.17 17771.36 17472.38 20369.02 194
Anonymous2023120656.36 19657.80 19954.67 19670.08 17466.39 19160.46 19757.54 16049.50 19329.30 20033.86 21046.64 19535.18 20270.44 18668.88 18575.47 19368.88 195
ADS-MVSNet55.94 19758.01 19753.54 20162.48 19758.48 20959.12 20146.20 20559.65 11242.88 17452.34 16653.31 15746.31 18462.00 20960.02 21364.23 21960.24 211
EU-MVSNet54.63 19858.69 19649.90 20556.99 21162.70 20556.41 20450.64 19245.95 20223.14 21150.42 17446.51 19636.63 20065.51 20164.85 20075.57 19174.91 172
MVS-HIRNet54.41 19952.10 20657.11 18958.99 20656.10 21249.68 21349.10 19546.18 20152.15 12633.18 21146.11 19856.10 14863.19 20659.70 21476.64 18860.25 210
testgi54.39 20057.86 19850.35 20471.59 16867.24 18754.95 20653.25 17643.36 20423.78 20844.64 19047.87 19224.96 21570.45 18568.66 18773.60 20062.78 206
test20.0353.93 20156.28 20151.19 20372.19 16065.83 19253.20 20861.08 11342.74 20522.08 21537.07 20345.76 19924.29 21970.44 18669.04 18374.31 19863.05 205
LP53.62 20253.43 20253.83 19958.51 20962.59 20657.31 20246.04 20747.86 19542.69 17536.08 20636.86 21146.53 18364.38 20364.25 20271.92 20462.00 208
MDA-MVSNet-bldmvs53.37 20353.01 20553.79 20043.67 22567.95 18559.69 19957.92 15943.69 20332.41 19741.47 19527.89 22352.38 17056.97 21965.99 19976.68 18767.13 197
FPMVS51.87 20450.00 20954.07 19766.83 18757.25 21060.25 19850.91 18850.25 18634.36 19436.04 20732.02 21541.49 19358.98 21756.07 21770.56 20959.36 212
Anonymous2023121151.46 20550.59 20752.46 20267.30 18466.70 19055.00 20559.22 14229.96 22217.62 22219.11 22428.74 22235.72 20166.42 19969.52 18079.92 17573.71 180
MIMVSNet149.27 20653.25 20444.62 21144.61 22261.52 20853.61 20752.18 18241.62 20818.68 21928.14 21841.58 20625.50 21368.46 19669.04 18373.15 20162.37 207
pmmvs347.65 20749.08 21145.99 20944.61 22254.79 21550.04 21131.95 22633.91 21829.90 19830.37 21233.53 21446.31 18463.50 20463.67 20473.14 20263.77 204
testpf47.41 20848.47 21446.18 20866.30 18950.67 21948.15 21542.60 21637.10 21528.75 20140.97 19639.01 21030.82 20752.95 22253.74 22160.46 22064.87 200
N_pmnet47.35 20950.13 20844.11 21259.98 20351.64 21851.86 20944.80 21149.58 19220.76 21840.65 19840.05 20929.64 20859.84 21555.15 21857.63 22154.00 219
test235647.20 21048.62 21345.54 21056.38 21354.89 21450.62 21045.08 21038.65 21223.40 20936.23 20531.10 21729.31 20962.76 20762.49 20768.48 21254.23 218
new-patchmatchnet46.97 21149.47 21044.05 21362.82 19656.55 21145.35 21752.01 18342.47 20617.04 22335.73 20835.21 21221.84 22461.27 21054.83 21965.26 21860.26 209
GG-mvs-BLEND46.86 21267.51 13822.75 2250.05 23276.21 14764.69 1830.04 23061.90 940.09 23555.57 10971.32 620.08 23070.54 18467.19 19471.58 20569.86 191
PMVScopyleft39.38 1846.06 21343.30 21849.28 20662.93 19538.75 22641.88 21953.50 17533.33 22135.46 19328.90 21531.01 21833.04 20558.61 21854.63 22068.86 21157.88 215
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
testus45.61 21449.06 21241.59 21556.13 21455.28 21343.51 21839.64 21937.74 21318.23 22035.52 20931.28 21624.69 21762.46 20862.90 20567.33 21458.26 214
111143.08 21544.02 21741.98 21459.22 20449.27 22241.48 22045.63 20835.01 21623.06 21228.60 21630.15 21927.22 21060.42 21357.97 21555.27 22446.74 221
testmv42.58 21644.36 21540.49 21654.63 21852.76 21641.21 22244.37 21228.83 22312.87 22427.16 21925.03 22423.01 22060.83 21161.13 20966.88 21554.81 216
test123567842.57 21744.36 21540.49 21654.63 21852.75 21741.21 22244.37 21228.82 22412.87 22427.15 22025.01 22523.01 22060.83 21161.13 20966.88 21554.81 216
new_pmnet38.40 21842.64 21933.44 22037.54 22845.00 22436.60 22432.72 22540.27 20912.72 22629.89 21328.90 22124.78 21653.17 22152.90 22256.31 22248.34 220
Gipumacopyleft36.38 21935.80 22237.07 21845.76 22133.90 22729.81 22648.47 19939.91 21018.02 2218.00 2308.14 23225.14 21459.29 21661.02 21155.19 22540.31 223
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
no-one36.35 22037.59 22134.91 21946.13 22049.89 22127.99 22743.56 21420.91 2287.03 23014.64 22615.50 23018.92 22542.95 22360.20 21265.84 21759.03 213
test1235635.10 22138.50 22031.13 22244.14 22443.70 22532.27 22534.42 22226.51 2269.47 22825.22 22220.34 22610.86 22753.47 22056.15 21655.59 22344.11 222
.test124530.81 22229.14 22432.77 22159.22 20449.27 22241.48 22045.63 20835.01 21623.06 21228.60 21630.15 21927.22 21060.42 2130.10 2280.01 2320.43 230
PMMVS225.60 22329.75 22320.76 22628.00 22930.93 22823.10 22829.18 22723.14 2271.46 23418.23 22516.54 2285.08 22840.22 22441.40 22437.76 22637.79 225
E-PMN21.77 22418.24 22625.89 22340.22 22619.58 23012.46 23139.87 21818.68 2306.71 2319.57 2274.31 23522.36 22319.89 22827.28 22633.73 22728.34 227
EMVS20.98 22517.15 22725.44 22439.51 22719.37 23112.66 23039.59 22019.10 2296.62 2329.27 2284.40 23422.43 22217.99 22924.40 22731.81 22825.53 228
MVEpermissive19.12 1920.47 22623.27 22517.20 22712.66 23125.41 22910.52 23234.14 22414.79 2316.53 2338.79 2294.68 23316.64 22629.49 22641.63 22322.73 23038.11 224
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
testmvs0.09 2270.15 2280.02 2290.01 2330.02 2340.05 2350.01 2310.11 2320.01 2360.26 2320.01 2360.06 2320.10 2300.10 2280.01 2320.43 230
test1230.09 2270.14 2290.02 2290.00 2340.02 2340.02 2360.01 2310.09 2330.00 2370.30 2310.00 2370.08 2300.03 2310.09 2300.01 2320.45 229
test_full0.00 2290.00 2300.00 2310.00 2340.00 2360.00 2370.00 2330.00 2340.00 2370.00 2330.00 2370.00 2330.00 2320.00 2310.00 2350.00 232
sosnet-low-res0.00 2290.00 2300.00 2310.00 2340.00 2360.00 2370.00 2330.00 2340.00 2370.00 2330.00 2370.00 2330.00 2320.00 2310.00 2350.00 232
sosnet0.00 2290.00 2300.00 2310.00 2340.00 2360.00 2370.00 2330.00 2340.00 2370.00 2330.00 2370.00 2330.00 2320.00 2310.00 2350.00 232
ambc53.42 20364.99 19363.36 20149.96 21247.07 19837.12 18728.97 21416.36 22941.82 19275.10 15467.34 19271.55 20675.72 166
MTAPA83.48 186.45 11
MTMP82.66 384.91 19
Patchmatch-RL test2.85 234
tmp_tt14.50 22814.68 2307.17 23310.46 2332.21 22937.73 21428.71 20225.26 22116.98 2274.37 22931.49 22529.77 22526.56 229
XVS86.63 3888.68 2285.00 4071.81 3981.92 2990.47 16
X-MVStestdata86.63 3888.68 2285.00 4071.81 3981.92 2990.47 16
abl_679.05 3687.27 3488.85 2083.62 4868.25 4781.68 3472.94 3373.79 3984.45 2172.55 4189.66 3690.64 37
mPP-MVS89.90 1981.29 34
NP-MVS80.10 39
Patchmtry65.80 19365.97 17752.74 17952.65 122
DeepMVS_CXcopyleft18.74 23218.55 2298.02 22826.96 2257.33 22923.81 22313.05 23125.99 21225.17 22722.45 23136.25 226