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-MVS95.23 195.69 194.70 197.12 897.81 297.19 192.83 195.06 290.98 596.47 192.77 793.38 195.34 494.21 1096.68 398.17 1
HSP-MVS94.83 295.37 294.21 496.82 1797.94 196.69 292.37 693.97 690.29 996.16 293.71 292.70 494.80 1193.13 2796.37 697.90 4
HPM-MVS++94.60 394.91 594.24 397.86 196.53 2396.14 592.51 393.87 890.76 793.45 1193.84 192.62 595.11 794.08 1395.58 3597.48 9
SD-MVS94.53 495.22 393.73 895.69 2897.03 895.77 1491.95 794.41 391.35 494.97 393.34 491.80 1394.72 1493.99 1495.82 2298.07 2
TSAR-MVS + MP.94.48 594.97 493.90 795.53 2997.01 996.69 290.71 1594.24 490.92 694.97 392.19 993.03 294.83 1093.60 1896.51 597.97 3
APD-MVScopyleft94.37 694.47 1094.26 297.18 696.99 1096.53 492.68 292.45 1789.96 1094.53 691.63 1392.89 394.58 1593.82 1596.31 997.26 12
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
CNVR-MVS94.37 694.65 694.04 697.29 597.11 696.00 792.43 593.45 989.85 1290.92 1893.04 592.59 695.77 194.82 396.11 1297.42 11
SteuartSystems-ACMMP94.06 894.65 693.38 1296.97 1397.36 496.12 691.78 892.05 2187.34 2394.42 790.87 1791.87 1295.47 394.59 696.21 1097.77 6
Skip Steuart: Steuart Systems R&D Blog.
ACMMP_Plus93.94 994.49 993.30 1397.03 1197.31 595.96 891.30 1293.41 1188.55 1793.00 1290.33 2091.43 1995.53 294.41 895.53 3797.47 10
MCST-MVS93.81 1094.06 1293.53 1096.79 1896.85 1495.95 991.69 1092.20 1987.17 2490.83 2093.41 391.96 1094.49 1793.50 2197.61 197.12 16
MPTG93.80 1193.45 1994.20 597.53 296.43 2795.88 1291.12 1494.09 592.74 387.68 2690.77 1892.04 994.74 1393.56 2095.91 1696.85 20
ACMMPR93.72 1293.94 1393.48 1197.07 996.93 1195.78 1390.66 1793.88 789.24 1493.53 1089.08 2792.24 793.89 2393.50 2195.88 1796.73 24
NCCC93.69 1393.66 1693.72 997.37 496.66 2095.93 1192.50 493.40 1288.35 1887.36 2892.33 892.18 894.89 994.09 1296.00 1396.91 19
MP-MVScopyleft93.35 1493.59 1793.08 1697.39 396.82 1595.38 1790.71 1590.82 2888.07 2092.83 1490.29 2191.32 2094.03 1993.19 2695.61 3397.16 14
CP-MVS93.25 1593.26 2093.24 1496.84 1696.51 2495.52 1690.61 1892.37 1888.88 1590.91 1989.52 2391.91 1193.64 2592.78 3395.69 2897.09 17
DeepC-MVS_fast88.76 193.10 1693.02 2393.19 1597.13 796.51 2495.35 1891.19 1393.14 1488.14 1985.26 3489.49 2491.45 1695.17 595.07 195.85 2096.48 27
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
TSAR-MVS + ACMM92.97 1794.51 891.16 2895.88 2696.59 2195.09 2190.45 2193.42 1083.01 4494.68 590.74 1988.74 3294.75 1293.78 1693.82 11397.63 7
train_agg92.87 1893.53 1892.09 2396.88 1595.38 3995.94 1090.59 1990.65 3083.65 4294.31 891.87 1290.30 2493.38 2792.42 3495.17 5396.73 24
PGM-MVS92.76 1993.03 2292.45 2197.03 1196.67 1995.73 1587.92 3390.15 3586.53 2892.97 1388.33 3391.69 1493.62 2693.03 2895.83 2196.41 30
CSCG92.76 1993.16 2192.29 2296.30 2097.74 394.67 2588.98 2792.46 1689.73 1386.67 3092.15 1088.69 3392.26 4192.92 3195.40 4197.89 5
TSAR-MVS + GP.92.71 2193.91 1491.30 2791.96 6196.00 3293.43 3187.94 3292.53 1586.27 3293.57 991.94 1191.44 1893.29 2892.89 3296.78 297.15 15
DeepPCF-MVS88.51 292.64 2294.42 1190.56 3294.84 3496.92 1291.31 5189.61 2395.16 184.55 3789.91 2291.45 1490.15 2695.12 694.81 492.90 13497.58 8
X-MVS92.36 2392.75 2491.90 2596.89 1496.70 1695.25 1990.48 2091.50 2683.95 3988.20 2488.82 2989.11 2993.75 2493.43 2395.75 2796.83 22
DeepC-MVS87.86 392.26 2491.86 2792.73 1896.18 2196.87 1395.19 2091.76 992.17 2086.58 2781.79 4085.85 3990.88 2294.57 1694.61 595.80 2397.18 13
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PHI-MVS92.05 2593.74 1590.08 3494.96 3197.06 793.11 3587.71 3590.71 2980.78 5392.40 1591.03 1587.68 4394.32 1894.48 796.21 1096.16 33
ACMMPcopyleft92.03 2692.16 2591.87 2695.88 2696.55 2294.47 2689.49 2491.71 2485.26 3391.52 1784.48 4490.21 2592.82 3691.63 4095.92 1596.42 29
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
MSLP-MVS++92.02 2791.40 2892.75 1796.01 2495.88 3593.73 3089.00 2589.89 3690.31 881.28 4388.85 2891.45 1692.88 3594.24 996.00 1396.76 23
3Dnovator+86.06 491.60 2890.86 3292.47 2096.00 2596.50 2694.70 2487.83 3490.49 3189.92 1174.68 6889.35 2590.66 2394.02 2094.14 1195.67 3096.85 20
CPTT-MVS91.39 2990.95 3091.91 2495.06 3095.24 4195.02 2288.98 2791.02 2786.71 2684.89 3688.58 3291.60 1590.82 5989.67 7294.08 9196.45 28
CDPH-MVS91.14 3092.01 2690.11 3396.18 2196.18 3094.89 2388.80 2988.76 4077.88 6889.18 2387.71 3687.29 4793.13 3093.31 2595.62 3295.84 36
MVS_111021_HR90.56 3191.29 2989.70 3994.71 3695.63 3791.81 4786.38 4087.53 4381.29 5087.96 2585.43 4187.69 4293.90 2292.93 3096.33 795.69 39
3Dnovator85.17 590.48 3289.90 3691.16 2894.88 3395.74 3693.82 2885.36 4689.28 3787.81 2174.34 7087.40 3788.56 3493.07 3193.74 1796.53 495.71 38
AdaColmapbinary90.29 3388.38 4592.53 1996.10 2395.19 4292.98 3691.40 1189.08 3988.65 1678.35 5481.44 5791.30 2190.81 6090.21 5994.72 6593.59 65
OMC-MVS90.23 3490.40 3390.03 3593.45 4695.29 4091.89 4686.34 4193.25 1384.94 3681.72 4186.65 3888.90 3091.69 4790.27 5894.65 6993.95 61
MVS_111021_LR90.14 3590.89 3189.26 4393.23 4894.05 5690.43 5584.65 5190.16 3484.52 3890.14 2183.80 4887.99 3992.50 3990.92 4794.74 6494.70 53
DELS-MVS89.71 3689.68 3789.74 3793.75 4396.22 2993.76 2985.84 4282.53 5785.05 3578.96 5184.24 4584.25 6094.91 894.91 295.78 2696.02 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
EPNet89.60 3789.91 3589.24 4496.45 1993.61 6192.95 3788.03 3185.74 4983.36 4387.29 2983.05 5180.98 7492.22 4291.85 3893.69 12095.58 42
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
QAPM89.49 3889.58 3889.38 4294.73 3595.94 3392.35 3985.00 4985.69 5080.03 5776.97 6087.81 3587.87 4092.18 4592.10 3696.33 796.40 31
canonicalmvs89.36 3989.92 3488.70 4891.38 6295.92 3491.81 4782.61 7290.37 3282.73 4682.09 3879.28 6988.30 3791.17 5493.59 1995.36 4497.04 18
HQP-MVS89.13 4089.58 3888.60 5093.53 4593.67 5993.29 3387.58 3688.53 4175.50 7287.60 2780.32 6187.07 4890.66 6589.95 6694.62 7196.35 32
TAPA-MVS84.37 788.91 4188.93 4188.89 4593.00 5294.85 4792.00 4384.84 5091.68 2580.05 5679.77 4784.56 4388.17 3890.11 6989.00 7995.30 4892.57 87
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
PCF-MVS84.60 688.66 4287.75 5489.73 3893.06 5196.02 3193.22 3490.00 2282.44 5980.02 5877.96 5585.16 4287.36 4688.54 8088.54 8394.72 6595.61 41
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
CLD-MVS88.66 4288.52 4388.82 4691.37 6394.22 5392.82 3882.08 7588.27 4285.14 3481.86 3978.53 7185.93 5491.17 5490.61 5395.55 3695.00 46
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
PLCcopyleft83.76 988.61 4486.83 5890.70 3094.22 3992.63 6991.50 4987.19 3789.16 3886.87 2575.51 6580.87 5889.98 2790.01 7089.20 7594.41 8190.45 128
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
TSAR-MVS + COLMAP88.40 4589.09 4087.60 5692.72 5693.92 5892.21 4085.57 4591.73 2373.72 8091.75 1673.22 9287.64 4491.49 4889.71 7193.73 11991.82 100
CNLPA88.40 4587.00 5690.03 3593.73 4494.28 5289.56 6385.81 4391.87 2287.55 2269.53 9581.49 5689.23 2889.45 7688.59 8294.31 8593.82 63
MAR-MVS88.39 4788.44 4488.33 5394.90 3295.06 4490.51 5483.59 6185.27 5179.07 6177.13 5882.89 5287.70 4192.19 4492.32 3594.23 8694.20 59
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
ACMP83.90 888.32 4888.06 4888.62 4992.18 5993.98 5791.28 5285.24 4786.69 4581.23 5185.62 3275.13 8187.01 4989.83 7189.77 7094.79 6195.43 45
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
LGP-MVS_train88.25 4988.55 4287.89 5492.84 5593.66 6093.35 3285.22 4885.77 4874.03 7986.60 3176.29 7886.62 5191.20 5290.58 5595.29 4995.75 37
PVSNet_BlendedMVS88.19 5088.00 4988.42 5192.71 5794.82 4889.08 6883.81 5784.91 5286.38 2979.14 4978.11 7282.66 6393.05 3291.10 4395.86 1894.86 49
PVSNet_Blended88.19 5088.00 4988.42 5192.71 5794.82 4889.08 6883.81 5784.91 5286.38 2979.14 4978.11 7282.66 6393.05 3291.10 4395.86 1894.86 49
OpenMVScopyleft82.53 1187.71 5286.84 5788.73 4794.42 3895.06 4491.02 5383.49 6482.50 5882.24 4867.62 10585.48 4085.56 5591.19 5391.30 4295.67 3094.75 51
ACMM83.27 1087.68 5386.09 6389.54 4193.26 4792.19 7191.43 5086.74 3986.02 4782.85 4575.63 6475.14 8088.41 3590.68 6489.99 6394.59 7292.97 73
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
OPM-MVS87.56 5485.80 6489.62 4093.90 4294.09 5594.12 2788.18 3075.40 10377.30 7176.41 6177.93 7488.79 3192.20 4390.82 4895.40 4193.72 64
PVSNet_Blended_VisFu87.40 5587.80 5186.92 5992.86 5395.40 3888.56 7183.45 6779.55 8282.26 4774.49 6984.03 4679.24 11192.97 3491.53 4195.15 5596.65 26
MVS_Test86.93 5687.24 5586.56 6090.10 7593.47 6390.31 5680.12 8883.55 5678.12 6479.58 4879.80 6485.45 5690.17 6890.59 5495.29 4993.53 66
EPP-MVSNet86.55 5787.76 5385.15 6490.52 7094.41 5187.24 8882.32 7481.79 6273.60 8178.57 5382.41 5382.07 6791.23 5090.39 5795.14 5695.48 43
DI_MVS_plusplus_trai86.41 5885.54 6587.42 5789.24 7893.13 6792.16 4282.65 7082.30 6080.75 5468.30 10280.41 6085.01 5790.56 6690.07 6194.70 6794.01 60
IS_MVSNet86.18 5988.18 4783.85 7591.02 6694.72 5087.48 8082.46 7381.05 6970.28 9176.98 5982.20 5576.65 12593.97 2193.38 2495.18 5294.97 47
UA-Net86.07 6087.78 5284.06 7292.85 5495.11 4387.73 7784.38 5273.22 11773.18 8379.99 4689.22 2671.47 15393.22 2993.03 2894.76 6390.69 123
MVSTER86.03 6186.12 6285.93 6188.62 8189.93 10189.33 6579.91 9181.87 6181.35 4981.07 4474.91 8280.66 7992.13 4690.10 6095.68 2992.80 79
LS3D85.96 6284.37 7187.81 5594.13 4093.27 6690.26 5789.00 2584.91 5272.84 8571.74 8172.47 9487.45 4589.53 7589.09 7793.20 12989.60 130
UGNet85.90 6388.23 4683.18 8188.96 7994.10 5487.52 7983.60 6081.66 6377.90 6780.76 4583.19 5066.70 17091.13 5690.71 5294.39 8296.06 34
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
diffmvs85.70 6486.35 6184.95 6687.75 8690.96 7889.09 6778.56 11186.50 4680.44 5577.86 5683.93 4781.64 6985.52 12686.79 9992.21 14192.87 76
Effi-MVS+85.33 6585.08 6785.63 6389.69 7793.42 6489.90 5880.31 8679.32 8372.48 8773.52 7574.03 8586.55 5290.99 5789.98 6494.83 6094.27 58
FC-MVSNet-train85.18 6685.31 6685.03 6590.67 6991.62 7587.66 7883.61 5979.75 7974.37 7878.69 5271.21 9878.91 11291.23 5089.96 6594.96 5994.69 54
GBi-Net84.51 6784.80 6884.17 6984.20 12489.95 9889.70 6080.37 8281.17 6575.50 7269.63 9079.69 6679.75 9790.73 6190.72 4995.52 3891.71 104
test184.51 6784.80 6884.17 6984.20 12489.95 9889.70 6080.37 8281.17 6575.50 7269.63 9079.69 6679.75 9790.73 6190.72 4995.52 3891.71 104
FMVSNet384.44 6984.64 7084.21 6884.32 12390.13 9689.85 5980.37 8281.17 6575.50 7269.63 9079.69 6679.62 10089.72 7390.52 5695.59 3491.58 109
Vis-MVSNetpermissive84.38 7086.68 6081.70 10087.65 9094.89 4688.14 7380.90 8074.48 10768.23 10077.53 5780.72 5969.98 15792.68 3791.90 3795.33 4794.58 55
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
FMVSNet283.87 7183.73 7484.05 7384.20 12489.95 9889.70 6080.21 8779.17 8574.89 7665.91 11077.49 7579.75 9790.87 5891.00 4695.52 3891.71 104
MSDG83.87 7181.02 8887.19 5892.17 6089.80 10489.15 6685.72 4480.61 7479.24 6066.66 10868.75 10682.69 6287.95 8687.44 9194.19 8785.92 160
Fast-Effi-MVS+83.77 7382.98 7684.69 6787.98 8491.87 7388.10 7477.70 12178.10 9073.04 8469.13 9768.51 10786.66 5090.49 6789.85 6894.67 6892.88 75
Vis-MVSNet (Re-imp)83.65 7486.81 5979.96 12890.46 7292.71 6884.84 12982.00 7680.93 7162.44 14476.29 6282.32 5465.54 17392.29 4091.66 3994.49 7691.47 110
RPSCF83.46 7583.36 7583.59 7887.75 8687.35 13684.82 13079.46 10283.84 5578.12 6482.69 3779.87 6282.60 6582.47 16481.13 16888.78 17086.13 158
PatchMatch-RL83.34 7681.36 8585.65 6290.33 7489.52 11184.36 13381.82 7780.87 7379.29 5974.04 7162.85 12486.05 5388.40 8287.04 9692.04 14386.77 153
IterMVS-LS83.28 7782.95 7783.65 7688.39 8388.63 12486.80 10678.64 11076.56 9573.43 8272.52 8075.35 7980.81 7786.43 10988.51 8493.84 11292.66 83
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
IB-MVS79.09 1282.60 7882.19 7983.07 8291.08 6593.55 6280.90 15981.35 7876.56 9580.87 5264.81 11769.97 10168.87 16085.64 11990.06 6295.36 4494.74 52
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
CHOSEN 1792x268882.16 7980.91 8983.61 7791.14 6492.01 7289.55 6479.15 10679.87 7870.29 9052.51 18272.56 9381.39 7088.87 7988.17 8690.15 16292.37 93
Effi-MVS+-dtu82.05 8081.76 8182.38 8687.72 8890.56 8286.90 10478.05 11773.85 11266.85 10771.29 8371.90 9682.00 6886.64 10485.48 14092.76 13692.58 86
EPNet_dtu81.98 8183.82 7379.83 13094.10 4185.97 15487.29 8584.08 5680.61 7459.96 16281.62 4277.19 7662.91 17787.21 9086.38 11090.66 15887.77 146
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
UniMVSNet_NR-MVSNet81.87 8281.33 8682.50 8585.31 11191.30 7685.70 11984.25 5375.89 9964.21 13066.95 10764.65 11880.22 8487.07 9389.18 7695.27 5194.29 56
ACMH78.52 1481.86 8380.45 9283.51 7990.51 7191.22 7785.62 12284.23 5470.29 13862.21 14569.04 9964.05 12084.48 5987.57 8888.45 8594.01 9692.54 90
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH+79.08 1381.84 8480.06 9583.91 7489.92 7690.62 8186.21 11483.48 6673.88 11165.75 12066.38 10965.30 11584.63 5885.90 11487.25 9393.45 12491.13 113
MS-PatchMatch81.79 8581.44 8482.19 8990.35 7389.29 11588.08 7575.36 14777.60 9169.00 9664.37 12078.87 7077.14 12488.03 8585.70 13693.19 13086.24 157
PMMVS81.65 8684.05 7278.86 13578.56 18182.63 17583.10 13967.22 17881.39 6470.11 9384.91 3579.74 6582.12 6687.31 8985.70 13692.03 14486.67 156
FMVSNet181.64 8780.61 9182.84 8482.36 16589.20 11788.67 7079.58 10070.79 13272.63 8658.95 16272.26 9579.34 11090.73 6190.72 4994.47 7791.62 108
CDS-MVSNet81.63 8882.09 8081.09 11587.21 9590.28 9287.46 8280.33 8569.06 15170.66 8871.30 8273.87 8667.99 16389.58 7489.87 6792.87 13590.69 123
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
HyFIR lowres test81.62 8979.45 10584.14 7191.00 6793.38 6588.27 7278.19 11576.28 9770.18 9248.78 18573.69 8883.52 6187.05 9487.83 8993.68 12189.15 133
UniMVSNet (Re)81.22 9081.08 8781.39 10785.35 11091.76 7484.93 12882.88 6976.13 9865.02 12864.94 11563.09 12275.17 13287.71 8789.04 7894.97 5894.88 48
DU-MVS81.20 9180.30 9382.25 8784.98 11890.94 7985.70 11983.58 6275.74 10064.21 13065.30 11359.60 15780.22 8486.89 9789.31 7394.77 6294.29 56
CostFormer80.94 9280.21 9481.79 9587.69 8988.58 12587.47 8170.66 16480.02 7677.88 6873.03 7671.40 9778.24 11679.96 17479.63 17088.82 16988.84 134
USDC80.69 9379.89 9881.62 10386.48 10089.11 12086.53 11078.86 10781.15 6863.48 13772.98 7759.12 16281.16 7287.10 9285.01 14493.23 12884.77 166
TranMVSNet+NR-MVSNet80.52 9479.84 9981.33 10984.92 12090.39 8685.53 12484.22 5574.27 10860.68 16064.93 11659.96 15277.48 12186.75 10289.28 7495.12 5793.29 67
DWT-MVSNet_training80.51 9578.05 12483.39 8088.64 8088.33 13086.11 11676.33 13279.65 8078.64 6369.62 9358.89 16480.82 7580.50 17182.03 16689.77 16587.36 148
COLMAP_ROBcopyleft76.78 1580.50 9678.49 11082.85 8390.96 6889.65 10986.20 11583.40 6877.15 9366.54 10862.27 12565.62 11477.89 11985.23 13884.70 14892.11 14284.83 165
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
CHOSEN 280x42080.28 9781.66 8278.67 13782.92 15879.24 18785.36 12566.79 18078.11 8970.32 8975.03 6779.87 6281.09 7389.07 7883.16 15785.54 18687.17 150
NR-MVSNet80.25 9879.98 9780.56 12485.20 11390.94 7985.65 12183.58 6275.74 10061.36 15565.30 11356.75 17172.38 14988.46 8188.80 8095.16 5493.87 62
v680.11 9978.47 11182.01 9083.97 13190.49 8387.19 9379.67 9671.59 12567.51 10261.26 12962.46 13079.81 9685.49 12886.18 12393.89 10691.86 97
v1neww80.09 10078.45 11382.00 9183.97 13190.49 8387.18 9479.67 9671.49 12667.44 10361.24 13162.41 13179.83 9385.49 12886.19 12093.88 10891.86 97
v7new80.09 10078.45 11382.00 9183.97 13190.49 8387.18 9479.67 9671.49 12667.44 10361.24 13162.41 13179.83 9385.49 12886.19 12093.88 10891.86 97
pmmvs479.99 10278.08 12082.22 8883.04 15587.16 13984.95 12778.80 10978.64 8774.53 7764.61 11859.41 15879.45 10984.13 15084.54 15092.53 13888.08 141
Fast-Effi-MVS+-dtu79.95 10380.69 9079.08 13386.36 10189.14 11985.85 11772.28 15872.85 12059.32 16570.43 8868.42 10877.57 12086.14 11186.44 10993.11 13191.39 111
v879.90 10478.39 11681.66 10283.97 13189.81 10387.16 9777.40 12371.49 12667.71 10161.24 13162.49 12879.83 9385.48 13286.17 12493.89 10692.02 96
v2v48279.84 10578.07 12181.90 9483.75 14490.21 9587.17 9679.85 9570.65 13365.93 11961.93 12660.07 15180.82 7585.25 13786.71 10093.88 10891.70 107
Baseline_NR-MVSNet79.84 10578.37 11781.55 10584.98 11886.66 14385.06 12683.49 6475.57 10263.31 13858.22 16660.97 14578.00 11886.89 9787.13 9494.47 7793.15 69
tpmp4_e2379.82 10777.96 12982.00 9187.59 9186.93 14087.81 7672.21 15979.99 7778.02 6667.83 10464.77 11678.74 11379.99 17378.90 17387.65 17587.29 149
v779.79 10878.28 11881.54 10683.73 14590.34 9187.27 8678.27 11470.50 13565.59 12160.59 14660.47 14780.46 8186.90 9686.63 10393.92 10292.56 88
v179.76 10978.06 12381.74 9883.89 13890.38 8787.20 9079.88 9470.23 13966.17 11660.92 13961.56 13579.50 10785.37 13386.17 12493.81 11491.77 101
v114179.75 11078.04 12581.75 9683.89 13890.37 8887.20 9079.89 9370.23 13966.18 11360.92 13961.48 13979.54 10385.36 13486.17 12493.81 11491.76 103
divwei89l23v2f11279.75 11078.04 12581.75 9683.90 13590.37 8887.21 8979.90 9270.20 14166.18 11360.92 13961.48 13979.52 10685.36 13486.17 12493.81 11491.77 101
v1879.71 11277.98 12881.73 9984.02 13086.67 14287.37 8376.35 13172.61 12168.86 9761.35 12862.65 12579.94 8985.49 12886.21 11593.85 11190.92 116
v1679.65 11377.91 13081.69 10184.04 12886.65 14587.20 9076.32 13372.41 12268.71 9861.13 13662.52 12779.93 9085.55 12486.22 11393.92 10290.91 117
v1079.62 11478.19 11981.28 11083.73 14589.69 10887.27 8676.86 12770.50 13565.46 12260.58 14860.47 14780.44 8286.91 9586.63 10393.93 10092.55 89
v1779.59 11577.88 13181.60 10484.03 12986.66 14387.13 9976.31 13472.09 12368.29 9961.15 13562.57 12679.90 9185.55 12486.20 11893.93 10090.93 115
V4279.59 11578.43 11580.94 11982.79 16189.71 10786.66 10776.73 12971.38 12967.42 10561.01 13762.30 13378.39 11585.56 12386.48 10793.65 12292.60 85
GA-MVS79.52 11779.71 10279.30 13285.68 10690.36 9084.55 13178.44 11270.47 13757.87 17068.52 10161.38 14376.21 12789.40 7787.89 8793.04 13389.96 129
test-LLR79.47 11879.84 9979.03 13487.47 9282.40 17881.24 15478.05 11773.72 11362.69 14173.76 7274.42 8373.49 14484.61 14682.99 15991.25 15287.01 151
v114479.38 11977.83 13281.18 11283.62 14790.23 9387.15 9878.35 11369.13 15064.02 13460.20 15459.41 15880.14 8786.78 10086.57 10593.81 11492.53 91
MDTV_nov1_ep1379.14 12079.49 10478.74 13685.40 10986.89 14184.32 13470.29 16678.85 8669.42 9475.37 6673.29 9175.64 13080.61 17079.48 17287.36 17681.91 174
v1579.13 12177.37 13681.19 11183.90 13586.56 14787.01 10076.15 13870.20 14166.48 10960.71 14461.55 13679.60 10185.59 12286.19 12093.98 9890.80 122
V1479.11 12277.35 13881.16 11383.90 13586.54 14886.94 10176.10 14070.14 14366.41 11160.59 14661.54 13779.59 10285.64 11986.20 11894.04 9490.82 120
V979.08 12377.32 14081.14 11483.89 13886.52 14986.85 10576.06 14170.02 14466.42 11060.44 14961.52 13879.54 10385.68 11886.21 11594.08 9190.83 119
TDRefinement79.05 12477.05 14681.39 10788.45 8289.00 12286.92 10282.65 7074.21 10964.41 12959.17 15959.16 16074.52 13785.23 13885.09 14391.37 15087.51 147
v1279.03 12577.28 14181.06 11683.88 14286.49 15086.62 10876.02 14269.99 14566.18 11360.34 15261.44 14179.54 10385.70 11786.21 11594.11 9090.82 120
v1179.02 12677.36 13780.95 11883.89 13886.48 15186.53 11075.77 14669.69 14765.21 12760.36 15160.24 15080.32 8387.20 9186.54 10693.96 9991.02 114
v1378.99 12777.25 14381.02 11783.87 14386.47 15286.60 10975.96 14469.87 14666.07 11760.25 15361.41 14279.49 10885.72 11686.22 11394.14 8990.84 118
v119278.94 12877.33 13980.82 12083.25 15189.90 10286.91 10377.72 12068.63 15462.61 14359.17 15957.53 16880.62 8086.89 9786.47 10893.79 11892.75 82
v14419278.81 12977.22 14480.67 12282.95 15689.79 10586.40 11277.42 12268.26 15663.13 13959.50 15758.13 16680.08 8885.93 11386.08 12994.06 9392.83 78
IterMVS78.79 13079.71 10277.71 14285.26 11285.91 15584.54 13269.84 17073.38 11661.25 15670.53 8770.35 9974.43 13885.21 14083.80 15490.95 15688.77 135
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CR-MVSNet78.71 13178.86 10778.55 13885.85 10585.15 16382.30 14668.23 17374.71 10565.37 12464.39 11969.59 10377.18 12285.10 14284.87 14592.34 14088.21 139
PatchmatchNetpermissive78.67 13278.85 10878.46 13986.85 9986.03 15383.77 13668.11 17580.88 7266.19 11272.90 7873.40 9078.06 11779.25 17877.71 18087.75 17481.75 175
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
v14878.59 13376.84 14980.62 12383.61 14889.16 11883.65 13779.24 10569.38 14969.34 9559.88 15660.41 14975.19 13183.81 15284.63 14992.70 13790.63 125
v192192078.57 13476.99 14780.41 12682.93 15789.63 11086.38 11377.14 12568.31 15561.80 15058.89 16356.79 17080.19 8686.50 10886.05 13194.02 9592.76 81
pm-mvs178.51 13577.75 13479.40 13184.83 12189.30 11483.55 13879.38 10362.64 17863.68 13658.73 16464.68 11770.78 15589.79 7287.84 8894.17 8891.28 112
v124078.15 13676.53 15080.04 12782.85 16089.48 11385.61 12376.77 12867.05 15861.18 15858.37 16556.16 17579.89 9286.11 11286.08 12993.92 10292.47 92
dps78.02 13775.94 15880.44 12586.06 10286.62 14682.58 14169.98 16875.14 10477.76 7069.08 9859.93 15378.47 11479.47 17677.96 17787.78 17383.40 170
anonymousdsp77.94 13879.00 10676.71 15379.03 17987.83 13379.58 16472.87 15765.80 16758.86 16965.82 11162.48 12975.99 12886.77 10188.66 8193.92 10295.68 40
test-mter77.79 13980.02 9675.18 16481.18 17382.85 17380.52 16262.03 19573.62 11562.16 14673.55 7473.83 8773.81 14284.67 14583.34 15691.37 15088.31 138
TESTMET0.1,177.78 14079.84 9975.38 16380.86 17482.40 17881.24 15462.72 19473.72 11362.69 14173.76 7274.42 8373.49 14484.61 14682.99 15991.25 15287.01 151
tpm cat177.78 14075.28 16780.70 12187.14 9685.84 15685.81 11870.40 16577.44 9278.80 6263.72 12164.01 12176.55 12675.60 18875.21 18885.51 18785.12 163
EPMVS77.53 14278.07 12176.90 15286.89 9884.91 16682.18 14966.64 18181.00 7064.11 13372.75 7969.68 10274.42 13979.36 17778.13 17687.14 17980.68 180
v7n77.22 14376.23 15378.38 14081.89 16889.10 12182.24 14876.36 13065.96 16661.21 15756.56 16955.79 17675.07 13486.55 10586.68 10193.52 12392.95 74
RPMNet77.07 14477.63 13576.42 15585.56 10885.15 16381.37 15165.27 18774.71 10560.29 16163.71 12266.59 11273.64 14382.71 16182.12 16492.38 13988.39 137
pmmvs576.93 14576.33 15277.62 14381.97 16788.40 12981.32 15374.35 15165.42 17261.42 15463.07 12357.95 16773.23 14785.60 12185.35 14293.41 12588.55 136
TinyColmap76.73 14673.95 17279.96 12885.16 11585.64 15982.34 14578.19 11570.63 13462.06 14760.69 14549.61 18980.81 7785.12 14183.69 15591.22 15482.27 173
CVMVSNet76.70 14778.46 11274.64 16983.34 15084.48 16781.83 15074.58 14868.88 15251.23 18269.77 8970.05 10067.49 16684.27 14983.81 15389.38 16787.96 143
WR-MVS76.63 14878.02 12775.02 16584.14 12789.76 10678.34 17280.64 8169.56 14852.32 17861.26 12961.24 14460.66 17884.45 14887.07 9593.99 9792.77 80
TransMVSNet (Re)76.57 14975.16 16878.22 14185.60 10787.24 13782.46 14281.23 7959.80 18559.05 16857.07 16859.14 16166.60 17188.09 8486.82 9794.37 8387.95 144
v5276.55 15075.89 15977.31 14779.94 17888.49 12781.07 15773.62 15465.49 17061.66 15256.29 17258.90 16374.30 14083.47 15685.62 13893.28 12692.99 71
V476.55 15075.89 15977.32 14679.95 17788.50 12681.07 15773.62 15465.47 17161.71 15156.31 17158.87 16574.28 14183.48 15585.62 13893.28 12692.98 72
tpmrst76.55 15075.99 15777.20 14887.32 9483.05 17182.86 14065.62 18578.61 8867.22 10669.19 9665.71 11375.87 12976.75 18575.33 18784.31 19183.28 171
FC-MVSNet-test76.53 15381.62 8370.58 17884.99 11785.73 15774.81 17978.85 10877.00 9439.13 20275.90 6373.50 8954.08 18586.54 10685.99 13291.65 14686.68 154
PatchT76.42 15477.81 13374.80 16778.46 18284.30 16871.82 18565.03 18973.89 11065.37 12461.58 12766.70 11177.18 12285.10 14284.87 14590.94 15788.21 139
TAMVS76.42 15477.16 14575.56 16183.05 15485.55 16080.58 16171.43 16165.40 17361.04 15967.27 10669.22 10567.99 16384.88 14484.78 14789.28 16883.01 172
EG-PatchMatch MVS76.40 15675.47 16577.48 14485.86 10490.22 9482.45 14373.96 15359.64 18659.60 16452.75 18162.20 13468.44 16288.23 8387.50 9094.55 7487.78 145
CP-MVSNet76.36 15776.41 15176.32 15782.73 16288.64 12379.39 16579.62 9967.21 15753.70 17460.72 14355.22 17867.91 16583.52 15486.34 11194.55 7493.19 68
tpm76.30 15876.05 15676.59 15486.97 9783.01 17283.83 13567.06 17971.83 12463.87 13569.56 9462.88 12373.41 14679.79 17578.59 17484.41 19086.68 154
v74876.17 15975.10 16977.43 14581.60 16988.01 13179.02 16976.28 13564.47 17464.14 13256.55 17056.26 17470.40 15682.50 16385.77 13493.11 13192.15 94
test0.0.03 176.03 16078.51 10973.12 17587.47 9285.13 16576.32 17678.05 11773.19 11950.98 18370.64 8569.28 10455.53 18185.33 13684.38 15190.39 16081.63 176
PEN-MVS76.02 16176.07 15475.95 16083.17 15387.97 13279.65 16380.07 9066.57 16251.45 18060.94 13855.47 17766.81 16982.72 16086.80 9894.59 7292.03 95
SixPastTwentyTwo76.02 16175.72 16276.36 15683.38 14987.54 13475.50 17876.22 13665.50 16957.05 17170.64 8553.97 18274.54 13680.96 16982.12 16491.44 14889.35 132
PS-CasMVS75.90 16375.86 16175.96 15982.59 16388.46 12879.23 16879.56 10166.00 16552.77 17659.48 15854.35 18167.14 16883.37 15786.23 11294.47 7793.10 70
WR-MVS_H75.84 16476.93 14874.57 17082.86 15989.50 11278.34 17279.36 10466.90 16052.51 17760.20 15459.71 15459.73 17983.61 15385.77 13494.65 6992.84 77
LTVRE_ROB74.41 1675.78 16574.72 17077.02 15185.88 10389.22 11682.44 14477.17 12450.57 19745.45 19065.44 11252.29 18581.25 7185.50 12787.42 9289.94 16492.62 84
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
gg-mvs-nofinetune75.64 16677.26 14273.76 17187.92 8592.20 7087.32 8464.67 19051.92 19635.35 20346.44 18977.05 7771.97 15092.64 3891.02 4595.34 4689.53 131
FMVSNet575.50 16776.07 15474.83 16676.16 18781.19 18181.34 15270.21 16773.20 11861.59 15358.97 16168.33 10968.50 16185.87 11585.85 13391.18 15579.11 184
DTE-MVSNet75.14 16875.44 16674.80 16783.18 15287.19 13878.25 17480.11 8966.05 16448.31 18660.88 14254.67 17964.54 17582.57 16286.17 12494.43 8090.53 127
pmmvs674.83 16972.89 17577.09 14982.11 16687.50 13580.88 16076.97 12652.79 19561.91 14946.66 18860.49 14669.28 15986.74 10385.46 14191.39 14990.56 126
MIMVSNet74.69 17075.60 16473.62 17276.02 18985.31 16281.21 15667.43 17671.02 13159.07 16754.48 17464.07 11966.14 17286.52 10786.64 10291.83 14581.17 178
ADS-MVSNet74.53 17175.69 16373.17 17481.57 17180.71 18379.27 16763.03 19379.27 8459.94 16367.86 10368.32 11071.08 15477.33 18276.83 18384.12 19379.53 181
pmmvs-eth3d74.32 17271.96 17777.08 15077.33 18582.71 17478.41 17176.02 14266.65 16165.98 11854.23 17749.02 19173.14 14882.37 16582.69 16191.61 14786.05 159
PM-MVS74.17 17373.10 17375.41 16276.07 18882.53 17677.56 17571.69 16071.04 13061.92 14861.23 13447.30 19274.82 13581.78 16779.80 16990.42 15988.05 142
CMPMVSbinary56.49 1773.84 17471.73 17876.31 15885.20 11385.67 15875.80 17773.23 15662.26 17965.40 12353.40 18059.70 15571.77 15280.25 17279.56 17186.45 18281.28 177
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MDTV_nov1_ep13_2view73.21 17572.91 17473.56 17380.01 17584.28 16978.62 17066.43 18268.64 15359.12 16660.39 15059.69 15669.81 15878.82 18077.43 18287.36 17681.11 179
testgi71.92 17674.20 17169.27 18184.58 12283.06 17073.40 18174.39 15064.04 17646.17 18968.90 10057.15 16948.89 19284.07 15183.08 15888.18 17279.09 185
Anonymous2023120670.80 17770.59 18071.04 17781.60 16982.49 17774.64 18075.87 14564.17 17549.27 18444.85 19253.59 18354.68 18483.07 15882.34 16390.17 16183.65 169
gm-plane-assit70.29 17870.65 17969.88 17985.03 11678.50 18858.41 19965.47 18650.39 19840.88 19549.60 18450.11 18875.14 13391.43 4989.78 6994.32 8484.73 167
EU-MVSNet69.98 17972.30 17667.28 18475.67 19079.39 18573.12 18269.94 16963.59 17742.80 19362.93 12456.71 17255.07 18379.13 17978.55 17587.06 18085.82 161
MVS-HIRNet68.83 18066.39 18471.68 17677.58 18375.52 19166.45 19165.05 18862.16 18062.84 14044.76 19356.60 17371.96 15178.04 18175.06 18986.18 18472.56 193
LP68.35 18167.23 18269.67 18077.49 18479.38 18672.84 18461.37 19666.94 15955.08 17247.00 18750.35 18765.16 17475.61 18776.03 18486.08 18575.28 190
test20.0368.31 18270.05 18166.28 18682.41 16480.84 18267.35 19076.11 13958.44 18840.80 19653.77 17854.54 18042.28 19883.07 15881.96 16788.73 17177.76 187
N_pmnet66.85 18366.63 18367.11 18578.73 18074.66 19270.53 18671.07 16266.46 16346.54 18851.68 18351.91 18655.48 18274.68 19072.38 19480.29 19874.65 191
MDA-MVSNet-bldmvs66.22 18464.49 18768.24 18261.67 20282.11 18070.07 18776.16 13759.14 18747.94 18754.35 17635.82 20467.33 16764.94 20275.68 18686.30 18379.36 182
MIMVSNet165.00 18566.24 18563.55 19058.41 20680.01 18469.00 18874.03 15255.81 19341.88 19436.81 20149.48 19047.89 19381.32 16882.40 16290.08 16377.88 186
test235663.96 18664.10 18963.78 18974.71 19171.55 19565.83 19267.38 17757.11 19040.41 19753.58 17941.13 19849.35 19177.00 18477.57 18185.01 18970.79 194
testpf63.91 18765.23 18662.38 19181.32 17269.95 19862.71 19754.16 20361.29 18248.73 18557.31 16752.50 18450.97 18867.50 19868.86 19976.36 20179.21 183
new-patchmatchnet63.80 18863.31 19064.37 18876.49 18675.99 19063.73 19470.99 16357.27 18943.08 19245.86 19043.80 19345.13 19773.20 19370.68 19886.80 18176.34 189
FPMVS63.63 18960.08 19567.78 18380.01 17571.50 19672.88 18369.41 17261.82 18153.11 17545.12 19142.11 19650.86 18966.69 19963.84 20180.41 19769.46 198
testus63.31 19064.48 18861.94 19373.99 19371.99 19463.56 19663.25 19257.01 19139.41 20154.38 17538.73 20246.24 19677.01 18377.93 17885.20 18874.29 192
Anonymous2023121162.95 19160.42 19465.89 18774.22 19278.37 18967.66 18974.47 14940.37 20539.59 20027.51 20438.26 20352.13 18675.39 18977.89 17987.28 17885.16 162
pmmvs361.89 19261.74 19262.06 19264.30 20070.83 19764.22 19352.14 20548.78 19944.47 19141.67 19541.70 19763.03 17676.06 18676.02 18584.18 19277.14 188
new_pmnet59.28 19361.47 19356.73 19861.66 20368.29 19959.57 19854.91 20160.83 18334.38 20444.66 19443.65 19449.90 19071.66 19671.56 19779.94 19969.67 197
GG-mvs-BLEND57.56 19482.61 7828.34 2070.22 21290.10 9779.37 1660.14 21179.56 810.40 21571.25 8483.40 490.30 21286.27 11083.87 15289.59 16683.83 168
111157.32 19557.20 19657.46 19571.89 19767.50 20252.34 20058.78 19846.57 20039.69 19837.38 19938.78 20046.37 19474.15 19174.36 19375.70 20261.66 201
testmv56.62 19656.41 19756.86 19671.92 19567.58 20052.17 20265.69 18340.60 20328.53 20637.90 19731.52 20540.10 20072.64 19474.73 19182.78 19569.91 195
test123567856.61 19756.40 19856.86 19671.92 19567.58 20052.17 20265.69 18340.58 20428.52 20737.89 19831.49 20640.10 20072.64 19474.72 19282.78 19569.90 196
PMVScopyleft50.48 1855.81 19851.93 19960.33 19472.90 19449.34 20748.78 20469.51 17143.49 20254.25 17336.26 20241.04 19939.71 20265.07 20160.70 20276.85 20067.58 199
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
test1235650.02 19951.22 20048.61 20063.00 20160.15 20547.60 20656.49 20038.02 20624.74 20936.14 20325.93 20824.79 20566.19 20071.68 19675.07 20360.44 203
Gipumacopyleft49.17 20047.05 20151.65 19959.67 20548.39 20841.98 20763.47 19155.64 19433.33 20514.90 20713.78 21241.34 19969.31 19772.30 19570.11 20555.00 205
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
no-one44.14 20143.91 20344.40 20259.91 20461.10 20434.07 20960.09 19727.71 20814.44 21119.11 20619.28 21023.90 20747.36 20666.69 20073.98 20466.11 200
PMMVS241.68 20244.74 20238.10 20346.97 20952.32 20640.63 20848.08 20635.51 2077.36 21426.86 20524.64 20916.72 20855.24 20459.03 20368.85 20659.59 204
.test124541.43 20338.48 20444.88 20171.89 19767.50 20252.34 20058.78 19846.57 20039.69 19837.38 19938.78 20046.37 19474.15 1911.18 2080.20 2123.76 210
E-PMN31.40 20426.80 20636.78 20451.39 20829.96 21120.20 21154.17 20225.93 21012.75 21214.73 2088.58 21434.10 20427.36 20837.83 20648.07 20943.18 207
MVEpermissive30.17 1930.88 20533.52 20527.80 20823.78 21139.16 21018.69 21346.90 20721.88 21115.39 21014.37 2097.31 21524.41 20641.63 20756.22 20437.64 21154.07 206
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
EMVS30.49 20625.44 20736.39 20551.47 20729.89 21220.17 21254.00 20426.49 20912.02 21313.94 2108.84 21334.37 20325.04 20934.37 20746.29 21039.53 208
testmvs1.03 2071.63 2080.34 2090.09 2130.35 2140.61 2150.16 2101.49 2120.10 2163.15 2110.15 2160.86 2111.32 2101.18 2080.20 2123.76 210
test1230.87 2081.40 2090.25 2100.03 2140.25 2150.35 2160.08 2121.21 2130.05 2172.84 2120.03 2170.89 2100.43 2111.16 2100.13 2143.87 209
sosnet-low-res0.00 2090.00 2100.00 2110.00 2150.00 2160.00 2170.00 2130.00 2140.00 2180.00 2130.00 2180.00 2130.00 2120.00 2110.00 2150.00 212
sosnet0.00 2090.00 2100.00 2110.00 2150.00 2160.00 2170.00 2130.00 2140.00 2180.00 2130.00 2180.00 2130.00 2120.00 2110.00 2150.00 212
ambc61.92 19170.98 19973.54 19363.64 19560.06 18452.23 17938.44 19619.17 21157.12 18082.33 16675.03 19083.21 19484.89 164
MTAPA92.97 291.03 15
MTMP93.14 190.21 22
Patchmatch-RL test8.55 214
tmp_tt32.73 20643.96 21021.15 21326.71 2108.99 20965.67 16851.39 18156.01 17342.64 19511.76 20956.60 20350.81 20553.55 208
XVS93.11 4996.70 1691.91 4483.95 3988.82 2995.79 24
X-MVStestdata93.11 4996.70 1691.91 4483.95 3988.82 2995.79 24
abl_690.66 3194.65 3796.27 2892.21 4086.94 3890.23 3386.38 2985.50 3392.96 688.37 3695.40 4195.46 44
mPP-MVS97.06 1088.08 34
NP-MVS87.47 44
Patchmtry85.54 16182.30 14668.23 17365.37 124
DeepMVS_CXcopyleft48.31 20948.03 20526.08 20856.42 19225.77 20847.51 18631.31 20751.30 18748.49 20553.61 20761.52 202