This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sort bysorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
DVP-MVS++90.23 191.01 187.89 2494.34 2771.25 6195.06 194.23 378.38 3892.78 495.74 682.45 397.49 489.42 1996.68 294.95 12
SED-MVS90.08 290.85 287.77 2695.30 270.98 6893.57 894.06 1177.24 6093.10 195.72 882.99 197.44 789.07 2496.63 494.88 16
DVP-MVScopyleft89.60 390.35 387.33 4195.27 571.25 6193.49 1092.73 6577.33 5792.12 995.78 480.98 997.40 989.08 2296.41 1293.33 110
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
MSP-MVS89.51 489.91 588.30 1094.28 3073.46 1792.90 1794.11 780.27 1091.35 1494.16 4978.35 1396.77 2489.59 1794.22 6294.67 30
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
DPE-MVScopyleft89.48 589.98 488.01 1694.80 1172.69 3191.59 4694.10 975.90 9992.29 795.66 1081.67 697.38 1187.44 4496.34 1593.95 72
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
MM89.16 689.23 788.97 490.79 9873.65 1092.66 2491.17 13686.57 187.39 5394.97 2171.70 5897.68 192.19 195.63 2895.57 1
APDe-MVScopyleft89.15 789.63 687.73 2894.49 1871.69 5493.83 493.96 1475.70 10491.06 1696.03 176.84 1497.03 1789.09 2195.65 2794.47 44
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
SMA-MVScopyleft89.08 889.23 788.61 694.25 3173.73 992.40 2593.63 2274.77 13492.29 795.97 274.28 3097.24 1388.58 3296.91 194.87 18
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
HPM-MVS++copyleft89.02 989.15 988.63 595.01 976.03 192.38 2892.85 6080.26 1187.78 4494.27 4375.89 1996.81 2387.45 4396.44 993.05 128
CNVR-MVS88.93 1089.13 1088.33 894.77 1273.82 890.51 6593.00 4780.90 788.06 3994.06 5476.43 1696.84 2188.48 3595.99 1894.34 51
SteuartSystems-ACMMP88.72 1188.86 1188.32 992.14 7472.96 2593.73 593.67 2180.19 1288.10 3894.80 2373.76 3497.11 1587.51 4295.82 2194.90 15
Skip Steuart: Steuart Systems R&D Blog.
SF-MVS88.46 1288.74 1287.64 3592.78 6671.95 5192.40 2594.74 275.71 10289.16 2595.10 1875.65 2196.19 4787.07 4596.01 1794.79 23
DeepPCF-MVS80.84 188.10 1388.56 1486.73 5592.24 7369.03 10689.57 9393.39 3177.53 5389.79 2194.12 5178.98 1296.58 3585.66 5395.72 2494.58 36
lecture88.09 1488.59 1386.58 5893.26 5269.77 9293.70 694.16 577.13 6589.76 2295.52 1472.26 4996.27 4486.87 4694.65 4893.70 88
SD-MVS88.06 1588.50 1586.71 5692.60 7172.71 2991.81 4293.19 3677.87 4290.32 1994.00 5874.83 2393.78 15387.63 4194.27 6193.65 93
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
NCCC88.06 1588.01 1988.24 1194.41 2273.62 1191.22 5792.83 6181.50 585.79 6793.47 7573.02 4297.00 1884.90 5994.94 4094.10 63
ACMMP_NAP88.05 1788.08 1887.94 1993.70 4173.05 2290.86 6093.59 2476.27 9288.14 3795.09 1971.06 6896.67 2987.67 4096.37 1494.09 64
TSAR-MVS + MP.88.02 1888.11 1787.72 3093.68 4372.13 4891.41 5392.35 8374.62 13888.90 2893.85 6675.75 2096.00 5587.80 3994.63 5095.04 10
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
ZNCC-MVS87.94 1987.85 2188.20 1294.39 2473.33 1993.03 1593.81 1876.81 7485.24 7294.32 4071.76 5696.93 1985.53 5695.79 2294.32 53
MP-MVScopyleft87.71 2087.64 2387.93 2194.36 2673.88 692.71 2392.65 7177.57 4983.84 10494.40 3772.24 5096.28 4385.65 5495.30 3593.62 96
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
MGCNet87.69 2187.55 2688.12 1389.45 13471.76 5391.47 5289.54 19282.14 386.65 6194.28 4268.28 10897.46 690.81 695.31 3495.15 8
MP-MVS-pluss87.67 2287.72 2287.54 3693.64 4472.04 5089.80 8493.50 2675.17 12286.34 6395.29 1770.86 7096.00 5588.78 3096.04 1694.58 36
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HFP-MVS87.58 2387.47 2887.94 1994.58 1673.54 1593.04 1393.24 3476.78 7684.91 7794.44 3570.78 7196.61 3284.53 6794.89 4293.66 89
reproduce-ours87.47 2487.61 2487.07 4693.27 5071.60 5591.56 4993.19 3674.98 12588.96 2695.54 1271.20 6696.54 3686.28 5093.49 6793.06 126
our_new_method87.47 2487.61 2487.07 4693.27 5071.60 5591.56 4993.19 3674.98 12588.96 2695.54 1271.20 6696.54 3686.28 5093.49 6793.06 126
ACMMPR87.44 2687.23 3388.08 1594.64 1373.59 1293.04 1393.20 3576.78 7684.66 8494.52 2868.81 9996.65 3084.53 6794.90 4194.00 69
APD-MVScopyleft87.44 2687.52 2787.19 4394.24 3272.39 4191.86 4192.83 6173.01 18588.58 3094.52 2873.36 3596.49 3884.26 7095.01 3792.70 142
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
GST-MVS87.42 2887.26 3187.89 2494.12 3672.97 2492.39 2793.43 2976.89 7284.68 8193.99 6070.67 7396.82 2284.18 7495.01 3793.90 75
region2R87.42 2887.20 3488.09 1494.63 1473.55 1393.03 1593.12 4176.73 7984.45 8994.52 2869.09 9396.70 2784.37 6994.83 4594.03 67
fmvsm_s_conf0.5_n_987.39 3087.95 2085.70 7789.48 13367.88 14988.59 14089.05 22080.19 1290.70 1795.40 1574.56 2593.92 14691.54 292.07 8795.31 5
MCST-MVS87.37 3187.25 3287.73 2894.53 1772.46 4089.82 8293.82 1773.07 18384.86 8092.89 9076.22 1796.33 4184.89 6195.13 3694.40 47
reproduce_model87.28 3287.39 3086.95 5093.10 5871.24 6591.60 4593.19 3674.69 13588.80 2995.61 1170.29 7796.44 3986.20 5293.08 7193.16 120
MTAPA87.23 3387.00 3687.90 2294.18 3574.25 586.58 21792.02 9979.45 2285.88 6594.80 2368.07 11096.21 4686.69 4895.34 3293.23 113
XVS87.18 3486.91 4188.00 1794.42 2073.33 1992.78 1992.99 5079.14 2683.67 10894.17 4867.45 11796.60 3383.06 8294.50 5394.07 65
HPM-MVScopyleft87.11 3586.98 3887.50 3993.88 3972.16 4792.19 3493.33 3276.07 9683.81 10593.95 6369.77 8496.01 5485.15 5794.66 4794.32 53
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
CP-MVS87.11 3586.92 4087.68 3494.20 3473.86 793.98 392.82 6476.62 8283.68 10794.46 3267.93 11295.95 5884.20 7394.39 5793.23 113
DeepC-MVS79.81 287.08 3786.88 4287.69 3391.16 8772.32 4590.31 7493.94 1577.12 6682.82 12294.23 4672.13 5297.09 1684.83 6295.37 3193.65 93
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepC-MVS_fast79.65 386.91 3886.62 4687.76 2793.52 4672.37 4391.26 5493.04 4276.62 8284.22 9593.36 7971.44 6296.76 2580.82 10895.33 3394.16 59
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
balanced_conf0386.78 3986.99 3786.15 6691.24 8667.61 15790.51 6592.90 5777.26 5987.44 5291.63 12371.27 6596.06 5085.62 5595.01 3794.78 24
SR-MVS86.73 4086.67 4486.91 5194.11 3772.11 4992.37 2992.56 7674.50 13986.84 6094.65 2767.31 11995.77 6084.80 6392.85 7492.84 140
CS-MVS86.69 4186.95 3985.90 7490.76 9967.57 15992.83 1893.30 3379.67 1984.57 8892.27 10271.47 6195.02 9684.24 7293.46 6995.13 9
PGM-MVS86.68 4286.27 5187.90 2294.22 3373.38 1890.22 7693.04 4275.53 10783.86 10394.42 3667.87 11496.64 3182.70 9394.57 5293.66 89
mPP-MVS86.67 4386.32 4987.72 3094.41 2273.55 1392.74 2192.22 8976.87 7382.81 12394.25 4566.44 12996.24 4582.88 8794.28 6093.38 106
fmvsm_s_conf0.5_n_886.56 4487.17 3584.73 11587.76 21665.62 20689.20 10892.21 9179.94 1789.74 2394.86 2268.63 10294.20 13190.83 591.39 9994.38 48
CANet86.45 4586.10 5787.51 3890.09 11170.94 7289.70 8892.59 7581.78 481.32 14491.43 13370.34 7597.23 1484.26 7093.36 7094.37 49
train_agg86.43 4686.20 5287.13 4593.26 5272.96 2588.75 13291.89 10768.69 28885.00 7593.10 8374.43 2795.41 7684.97 5895.71 2593.02 130
PHI-MVS86.43 4686.17 5587.24 4290.88 9570.96 7092.27 3394.07 1072.45 19185.22 7391.90 11269.47 8796.42 4083.28 8195.94 1994.35 50
CSCG86.41 4886.19 5487.07 4692.91 6372.48 3790.81 6193.56 2573.95 15483.16 11591.07 14575.94 1895.19 8579.94 11994.38 5893.55 101
fmvsm_s_conf0.5_n_1086.38 4986.76 4385.24 9087.33 23267.30 16989.50 9590.98 14176.25 9390.56 1894.75 2568.38 10594.24 13090.80 792.32 8494.19 58
fmvsm_s_conf0.5_n_386.36 5087.46 2983.09 19387.08 24665.21 21589.09 11790.21 16979.67 1989.98 2095.02 2073.17 3991.71 25591.30 391.60 9492.34 159
NormalMVS86.29 5185.88 6187.52 3793.26 5272.47 3891.65 4392.19 9379.31 2484.39 9192.18 10464.64 15195.53 6780.70 11194.65 4894.56 40
SPE-MVS-test86.29 5186.48 4785.71 7691.02 9167.21 17592.36 3093.78 1978.97 3383.51 11191.20 14070.65 7495.15 8781.96 9794.89 4294.77 25
fmvsm_l_conf0.5_n_386.02 5386.32 4985.14 9387.20 23768.54 12689.57 9390.44 15875.31 11587.49 5094.39 3872.86 4492.72 21189.04 2690.56 11394.16 59
EC-MVSNet86.01 5486.38 4884.91 10789.31 14366.27 18992.32 3193.63 2279.37 2384.17 9791.88 11369.04 9795.43 7383.93 7693.77 6593.01 131
MVSMamba_PlusPlus85.99 5585.96 6086.05 6991.09 8867.64 15689.63 9192.65 7172.89 18884.64 8591.71 11871.85 5496.03 5184.77 6494.45 5694.49 43
casdiffmvs_mvgpermissive85.99 5586.09 5885.70 7787.65 22167.22 17488.69 13693.04 4279.64 2185.33 7192.54 9973.30 3694.50 11983.49 7891.14 10395.37 2
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
APD-MVS_3200maxsize85.97 5785.88 6186.22 6392.69 6869.53 9591.93 3892.99 5073.54 16785.94 6494.51 3165.80 14195.61 6383.04 8492.51 7993.53 103
test_fmvsmconf_n85.92 5886.04 5985.57 8285.03 30269.51 9689.62 9290.58 15373.42 17187.75 4694.02 5672.85 4593.24 18190.37 890.75 11093.96 70
sasdasda85.91 5985.87 6386.04 7089.84 12169.44 10190.45 7193.00 4776.70 8088.01 4191.23 13773.28 3793.91 14781.50 10088.80 14594.77 25
canonicalmvs85.91 5985.87 6386.04 7089.84 12169.44 10190.45 7193.00 4776.70 8088.01 4191.23 13773.28 3793.91 14781.50 10088.80 14594.77 25
ACMMPcopyleft85.89 6185.39 7287.38 4093.59 4572.63 3392.74 2193.18 4076.78 7680.73 15893.82 6764.33 15396.29 4282.67 9490.69 11193.23 113
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
fmvsm_l_conf0.5_n_985.84 6286.63 4583.46 17687.12 24566.01 19388.56 14289.43 19675.59 10689.32 2494.32 4072.89 4391.21 28090.11 1192.33 8393.16 120
SR-MVS-dyc-post85.77 6385.61 6886.23 6293.06 6070.63 7891.88 3992.27 8573.53 16885.69 6894.45 3365.00 14995.56 6482.75 8991.87 9092.50 152
CDPH-MVS85.76 6485.29 7787.17 4493.49 4771.08 6688.58 14192.42 8168.32 29584.61 8693.48 7372.32 4896.15 4979.00 12795.43 3094.28 55
TSAR-MVS + GP.85.71 6585.33 7486.84 5291.34 8472.50 3689.07 11887.28 27176.41 8585.80 6690.22 17274.15 3295.37 8181.82 9891.88 8992.65 146
dcpmvs_285.63 6686.15 5684.06 15191.71 8064.94 22586.47 22091.87 10973.63 16386.60 6293.02 8876.57 1591.87 24983.36 7992.15 8595.35 3
test_fmvsmconf0.1_n85.61 6785.65 6785.50 8382.99 35469.39 10389.65 8990.29 16773.31 17587.77 4594.15 5071.72 5793.23 18290.31 990.67 11293.89 76
fmvsm_s_conf0.5_n_685.55 6886.20 5283.60 17187.32 23465.13 21888.86 12491.63 12075.41 11188.23 3693.45 7668.56 10392.47 22289.52 1892.78 7593.20 118
alignmvs85.48 6985.32 7585.96 7389.51 13069.47 9889.74 8692.47 7776.17 9487.73 4891.46 13270.32 7693.78 15381.51 9988.95 14294.63 34
3Dnovator+77.84 485.48 6984.47 8888.51 791.08 8973.49 1693.18 1293.78 1980.79 876.66 24093.37 7860.40 22396.75 2677.20 14993.73 6695.29 6
MSLP-MVS++85.43 7185.76 6584.45 12391.93 7770.24 8190.71 6292.86 5977.46 5584.22 9592.81 9467.16 12192.94 20280.36 11494.35 5990.16 244
DELS-MVS85.41 7285.30 7685.77 7588.49 17867.93 14885.52 25393.44 2878.70 3483.63 11089.03 20574.57 2495.71 6280.26 11694.04 6393.66 89
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
fmvsm_s_conf0.5_n_485.39 7385.75 6684.30 13186.70 25765.83 19988.77 13089.78 18175.46 11088.35 3293.73 6969.19 9293.06 19791.30 388.44 15494.02 68
SymmetryMVS85.38 7484.81 8287.07 4691.47 8372.47 3891.65 4388.06 25179.31 2484.39 9192.18 10464.64 15195.53 6780.70 11190.91 10893.21 116
HPM-MVS_fast85.35 7584.95 8186.57 5993.69 4270.58 8092.15 3691.62 12173.89 15782.67 12594.09 5262.60 17595.54 6680.93 10692.93 7393.57 99
test_fmvsm_n_192085.29 7685.34 7385.13 9686.12 27269.93 8888.65 13890.78 14969.97 25588.27 3493.98 6171.39 6391.54 26588.49 3490.45 11593.91 73
fmvsm_s_conf0.5_n_585.22 7785.55 6984.25 13886.26 26667.40 16589.18 10989.31 20572.50 19088.31 3393.86 6569.66 8591.96 24389.81 1391.05 10493.38 106
MVS_111021_HR85.14 7884.75 8386.32 6191.65 8172.70 3085.98 23590.33 16476.11 9582.08 13291.61 12671.36 6494.17 13481.02 10592.58 7892.08 175
casdiffmvspermissive85.11 7985.14 7885.01 10087.20 23765.77 20387.75 17392.83 6177.84 4384.36 9492.38 10172.15 5193.93 14581.27 10490.48 11495.33 4
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
UA-Net85.08 8084.96 8085.45 8492.07 7568.07 14189.78 8590.86 14782.48 284.60 8793.20 8269.35 8995.22 8471.39 22090.88 10993.07 125
MGCFI-Net85.06 8185.51 7083.70 16989.42 13563.01 27789.43 9892.62 7476.43 8487.53 4991.34 13572.82 4693.42 17481.28 10388.74 14894.66 33
DPM-MVS84.93 8284.29 8986.84 5290.20 10973.04 2387.12 19393.04 4269.80 25982.85 12191.22 13973.06 4196.02 5376.72 16194.63 5091.46 196
baseline84.93 8284.98 7984.80 11287.30 23565.39 21287.30 18992.88 5877.62 4784.04 10092.26 10371.81 5593.96 13981.31 10290.30 11795.03 11
ETV-MVS84.90 8484.67 8485.59 8189.39 13868.66 12388.74 13492.64 7379.97 1684.10 9885.71 30169.32 9095.38 7880.82 10891.37 10092.72 141
test_fmvsmconf0.01_n84.73 8584.52 8785.34 8780.25 39669.03 10689.47 9689.65 18873.24 17986.98 5894.27 4366.62 12593.23 18290.26 1089.95 12593.78 85
fmvsm_l_conf0.5_n84.47 8684.54 8584.27 13585.42 28968.81 11288.49 14487.26 27368.08 29788.03 4093.49 7272.04 5391.77 25188.90 2889.14 14192.24 166
BP-MVS184.32 8783.71 9786.17 6487.84 20967.85 15089.38 10389.64 18977.73 4583.98 10192.12 10956.89 25395.43 7384.03 7591.75 9395.24 7
EI-MVSNet-Vis-set84.19 8883.81 9485.31 8888.18 19067.85 15087.66 17589.73 18680.05 1582.95 11889.59 19070.74 7294.82 10480.66 11384.72 21793.28 112
fmvsm_l_conf0.5_n_a84.13 8984.16 9084.06 15185.38 29068.40 12988.34 15186.85 28367.48 30487.48 5193.40 7770.89 6991.61 25688.38 3689.22 13892.16 173
fmvsm_s_conf0.5_n_284.04 9084.11 9183.81 16786.17 27065.00 22386.96 19987.28 27174.35 14388.25 3594.23 4661.82 19192.60 21489.85 1288.09 15993.84 79
test_fmvsmvis_n_192084.02 9183.87 9384.49 12284.12 32069.37 10488.15 15987.96 25470.01 25383.95 10293.23 8168.80 10091.51 26888.61 3189.96 12492.57 147
viewcassd2359sk1183.89 9283.74 9684.34 12887.76 21664.91 22886.30 22792.22 8975.47 10983.04 11791.52 12870.15 7993.53 16679.26 12387.96 16094.57 38
nrg03083.88 9383.53 10184.96 10286.77 25569.28 10590.46 7092.67 6874.79 13382.95 11891.33 13672.70 4793.09 19580.79 11079.28 29992.50 152
EI-MVSNet-UG-set83.81 9483.38 10485.09 9887.87 20767.53 16187.44 18489.66 18779.74 1882.23 12989.41 19970.24 7894.74 10979.95 11883.92 23292.99 133
fmvsm_s_conf0.1_n_283.80 9583.79 9583.83 16585.62 28364.94 22587.03 19686.62 28974.32 14487.97 4394.33 3960.67 21592.60 21489.72 1487.79 16393.96 70
fmvsm_s_conf0.5_n83.80 9583.71 9784.07 14886.69 25867.31 16889.46 9783.07 34371.09 22086.96 5993.70 7069.02 9891.47 27088.79 2984.62 21993.44 105
viewmacassd2359aftdt83.76 9783.66 9984.07 14886.59 26164.56 23386.88 20491.82 11275.72 10183.34 11292.15 10868.24 10992.88 20579.05 12489.15 14094.77 25
CPTT-MVS83.73 9883.33 10684.92 10693.28 4970.86 7492.09 3790.38 16068.75 28779.57 17392.83 9260.60 21993.04 20080.92 10791.56 9790.86 214
EPNet83.72 9982.92 11386.14 6884.22 31869.48 9791.05 5985.27 30781.30 676.83 23591.65 12166.09 13695.56 6476.00 16793.85 6493.38 106
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
viewmanbaseed2359cas83.66 10083.55 10084.00 15986.81 25364.53 23486.65 21491.75 11774.89 12983.15 11691.68 11968.74 10192.83 20979.02 12589.24 13794.63 34
patch_mono-283.65 10184.54 8580.99 26190.06 11665.83 19984.21 28788.74 23671.60 20885.01 7492.44 10074.51 2683.50 38882.15 9692.15 8593.64 95
HQP_MVS83.64 10283.14 10785.14 9390.08 11268.71 11991.25 5592.44 7879.12 2878.92 18591.00 15060.42 22195.38 7878.71 13186.32 18891.33 197
fmvsm_s_conf0.5_n_a83.63 10383.41 10384.28 13386.14 27168.12 13989.43 9882.87 34870.27 24887.27 5593.80 6869.09 9391.58 25888.21 3783.65 24093.14 123
Effi-MVS+83.62 10483.08 10885.24 9088.38 18467.45 16288.89 12389.15 21675.50 10882.27 12888.28 23069.61 8694.45 12277.81 14187.84 16293.84 79
fmvsm_s_conf0.1_n83.56 10583.38 10484.10 14284.86 30467.28 17089.40 10283.01 34470.67 23287.08 5693.96 6268.38 10591.45 27188.56 3384.50 22093.56 100
GDP-MVS83.52 10682.64 11886.16 6588.14 19368.45 12889.13 11592.69 6672.82 18983.71 10691.86 11555.69 26095.35 8280.03 11789.74 12994.69 29
OPM-MVS83.50 10782.95 11285.14 9388.79 16870.95 7189.13 11591.52 12577.55 5280.96 15291.75 11760.71 21394.50 11979.67 12286.51 18689.97 260
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
Vis-MVSNetpermissive83.46 10882.80 11585.43 8590.25 10868.74 11790.30 7590.13 17276.33 9180.87 15592.89 9061.00 21094.20 13172.45 21290.97 10693.35 109
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MG-MVS83.41 10983.45 10283.28 18392.74 6762.28 29488.17 15789.50 19475.22 11681.49 14292.74 9866.75 12395.11 9072.85 20291.58 9692.45 156
EPP-MVSNet83.40 11083.02 11084.57 11890.13 11064.47 23992.32 3190.73 15074.45 14279.35 17991.10 14369.05 9695.12 8872.78 20387.22 17294.13 61
3Dnovator76.31 583.38 11182.31 12486.59 5787.94 20472.94 2890.64 6392.14 9877.21 6275.47 26692.83 9258.56 23594.72 11073.24 19992.71 7792.13 174
fmvsm_s_conf0.5_n_783.34 11284.03 9281.28 25285.73 28065.13 21885.40 25489.90 17974.96 12782.13 13193.89 6466.65 12487.92 34286.56 4991.05 10490.80 215
fmvsm_s_conf0.1_n_a83.32 11382.99 11184.28 13383.79 32868.07 14189.34 10582.85 34969.80 25987.36 5494.06 5468.34 10791.56 26187.95 3883.46 24693.21 116
KinetiMVS83.31 11482.61 11985.39 8687.08 24667.56 16088.06 16191.65 11977.80 4482.21 13091.79 11657.27 24894.07 13777.77 14289.89 12794.56 40
EIA-MVS83.31 11482.80 11584.82 11089.59 12665.59 20788.21 15592.68 6774.66 13778.96 18386.42 28869.06 9595.26 8375.54 17490.09 12193.62 96
h-mvs3383.15 11682.19 12786.02 7290.56 10170.85 7588.15 15989.16 21576.02 9784.67 8291.39 13461.54 19695.50 6982.71 9175.48 35191.72 186
MVS_Test83.15 11683.06 10983.41 18086.86 25063.21 27386.11 23392.00 10174.31 14582.87 12089.44 19870.03 8093.21 18477.39 14888.50 15393.81 81
IS-MVSNet83.15 11682.81 11484.18 14089.94 11963.30 27191.59 4688.46 24479.04 3079.49 17492.16 10665.10 14694.28 12567.71 25891.86 9294.95 12
DP-MVS Recon83.11 11982.09 13086.15 6694.44 1970.92 7388.79 12992.20 9270.53 23779.17 18191.03 14864.12 15596.03 5168.39 25590.14 12091.50 192
PAPM_NR83.02 12082.41 12184.82 11092.47 7266.37 18787.93 16791.80 11373.82 15877.32 22390.66 15767.90 11394.90 10070.37 23089.48 13493.19 119
VDD-MVS83.01 12182.36 12384.96 10291.02 9166.40 18688.91 12288.11 24777.57 4984.39 9193.29 8052.19 29493.91 14777.05 15288.70 14994.57 38
viewdifsd2359ckpt1382.91 12282.29 12584.77 11386.96 24966.90 18287.47 18091.62 12172.19 19681.68 14090.71 15666.92 12293.28 17775.90 16887.15 17494.12 62
MVSFormer82.85 12382.05 13185.24 9087.35 22770.21 8290.50 6790.38 16068.55 29081.32 14489.47 19361.68 19393.46 17178.98 12890.26 11892.05 176
viewdifsd2359ckpt0782.83 12482.78 11782.99 20086.51 26362.58 28585.09 26290.83 14875.22 11682.28 12791.63 12369.43 8892.03 23977.71 14386.32 18894.34 51
OMC-MVS82.69 12581.97 13484.85 10988.75 17067.42 16387.98 16390.87 14674.92 12879.72 17191.65 12162.19 18593.96 13975.26 17886.42 18793.16 120
PVSNet_Blended_VisFu82.62 12681.83 13684.96 10290.80 9769.76 9388.74 13491.70 11869.39 26778.96 18388.46 22565.47 14394.87 10374.42 18588.57 15090.24 242
MVS_111021_LR82.61 12782.11 12884.11 14188.82 16271.58 5785.15 25986.16 29774.69 13580.47 16391.04 14662.29 18290.55 29880.33 11590.08 12290.20 243
HQP-MVS82.61 12782.02 13284.37 12589.33 14066.98 17889.17 11092.19 9376.41 8577.23 22690.23 17160.17 22495.11 9077.47 14685.99 19791.03 207
RRT-MVS82.60 12982.10 12984.10 14287.98 20362.94 28287.45 18391.27 13277.42 5679.85 16990.28 16856.62 25694.70 11279.87 12088.15 15894.67 30
diffmvs_AUTHOR82.38 13082.27 12682.73 21983.26 34263.80 25383.89 29489.76 18373.35 17482.37 12690.84 15366.25 13290.79 29282.77 8887.93 16193.59 98
CLD-MVS82.31 13181.65 13784.29 13288.47 17967.73 15485.81 24392.35 8375.78 10078.33 20086.58 28364.01 15694.35 12376.05 16687.48 16890.79 216
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
VNet82.21 13282.41 12181.62 24190.82 9660.93 31084.47 27889.78 18176.36 9084.07 9991.88 11364.71 15090.26 30070.68 22788.89 14393.66 89
diffmvspermissive82.10 13381.88 13582.76 21783.00 35263.78 25583.68 29989.76 18372.94 18682.02 13389.85 17765.96 14090.79 29282.38 9587.30 17193.71 87
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
LPG-MVS_test82.08 13481.27 14084.50 12089.23 14868.76 11590.22 7691.94 10575.37 11376.64 24191.51 12954.29 27394.91 9878.44 13383.78 23389.83 265
FIs82.07 13582.42 12081.04 26088.80 16758.34 33988.26 15493.49 2776.93 7178.47 19791.04 14669.92 8292.34 23069.87 23984.97 21392.44 157
PS-MVSNAJss82.07 13581.31 13984.34 12886.51 26367.27 17189.27 10691.51 12671.75 20379.37 17890.22 17263.15 16794.27 12677.69 14482.36 26191.49 193
API-MVS81.99 13781.23 14184.26 13790.94 9370.18 8791.10 5889.32 20471.51 21078.66 19088.28 23065.26 14495.10 9364.74 28591.23 10287.51 332
SSM_040481.91 13880.84 14985.13 9689.24 14768.26 13387.84 17289.25 21071.06 22280.62 15990.39 16559.57 22694.65 11472.45 21287.19 17392.47 155
UniMVSNet_NR-MVSNet81.88 13981.54 13882.92 20488.46 18063.46 26787.13 19292.37 8280.19 1278.38 19889.14 20171.66 6093.05 19870.05 23576.46 33492.25 164
MAR-MVS81.84 14080.70 15085.27 8991.32 8571.53 5889.82 8290.92 14369.77 26178.50 19486.21 29262.36 18194.52 11865.36 27992.05 8889.77 268
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
LFMVS81.82 14181.23 14183.57 17491.89 7863.43 26989.84 8181.85 36077.04 6983.21 11393.10 8352.26 29393.43 17371.98 21589.95 12593.85 77
hse-mvs281.72 14280.94 14784.07 14888.72 17167.68 15585.87 23987.26 27376.02 9784.67 8288.22 23361.54 19693.48 16982.71 9173.44 37991.06 205
GeoE81.71 14381.01 14683.80 16889.51 13064.45 24088.97 12088.73 23771.27 21678.63 19189.76 18366.32 13193.20 18769.89 23886.02 19693.74 86
xiu_mvs_v2_base81.69 14481.05 14483.60 17189.15 15168.03 14384.46 28090.02 17470.67 23281.30 14786.53 28663.17 16694.19 13375.60 17388.54 15188.57 310
PS-MVSNAJ81.69 14481.02 14583.70 16989.51 13068.21 13884.28 28690.09 17370.79 22981.26 14885.62 30663.15 16794.29 12475.62 17288.87 14488.59 309
PAPR81.66 14680.89 14883.99 16090.27 10764.00 24786.76 21191.77 11668.84 28677.13 23389.50 19167.63 11594.88 10267.55 26088.52 15293.09 124
UniMVSNet (Re)81.60 14781.11 14383.09 19388.38 18464.41 24187.60 17693.02 4678.42 3778.56 19388.16 23469.78 8393.26 18069.58 24276.49 33391.60 187
SSM_040781.58 14880.48 15684.87 10888.81 16367.96 14587.37 18589.25 21071.06 22279.48 17590.39 16559.57 22694.48 12172.45 21285.93 19992.18 169
Elysia81.53 14980.16 16485.62 7985.51 28668.25 13588.84 12792.19 9371.31 21380.50 16189.83 17846.89 35494.82 10476.85 15489.57 13193.80 83
StellarMVS81.53 14980.16 16485.62 7985.51 28668.25 13588.84 12792.19 9371.31 21380.50 16189.83 17846.89 35494.82 10476.85 15489.57 13193.80 83
FC-MVSNet-test81.52 15182.02 13280.03 28388.42 18355.97 37887.95 16593.42 3077.10 6777.38 22190.98 15269.96 8191.79 25068.46 25484.50 22092.33 160
VDDNet81.52 15180.67 15184.05 15490.44 10464.13 24689.73 8785.91 30071.11 21983.18 11493.48 7350.54 32093.49 16873.40 19688.25 15694.54 42
ACMP74.13 681.51 15380.57 15384.36 12689.42 13568.69 12289.97 8091.50 12974.46 14175.04 28890.41 16453.82 27994.54 11677.56 14582.91 25389.86 264
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
jason81.39 15480.29 16184.70 11686.63 26069.90 9085.95 23686.77 28463.24 35781.07 15089.47 19361.08 20992.15 23678.33 13690.07 12392.05 176
jason: jason.
lupinMVS81.39 15480.27 16284.76 11487.35 22770.21 8285.55 24986.41 29162.85 36481.32 14488.61 22061.68 19392.24 23478.41 13590.26 11891.83 179
test_yl81.17 15680.47 15783.24 18689.13 15263.62 25686.21 23089.95 17772.43 19481.78 13889.61 18857.50 24593.58 16170.75 22586.90 17892.52 150
DCV-MVSNet81.17 15680.47 15783.24 18689.13 15263.62 25686.21 23089.95 17772.43 19481.78 13889.61 18857.50 24593.58 16170.75 22586.90 17892.52 150
guyue81.13 15880.64 15282.60 22286.52 26263.92 25186.69 21387.73 26273.97 15380.83 15789.69 18456.70 25491.33 27678.26 14085.40 21092.54 149
DU-MVS81.12 15980.52 15582.90 20587.80 21163.46 26787.02 19791.87 10979.01 3178.38 19889.07 20365.02 14793.05 19870.05 23576.46 33492.20 167
PVSNet_Blended80.98 16080.34 15982.90 20588.85 15965.40 21084.43 28292.00 10167.62 30178.11 20585.05 32266.02 13894.27 12671.52 21789.50 13389.01 290
FA-MVS(test-final)80.96 16179.91 17184.10 14288.30 18765.01 22284.55 27790.01 17573.25 17879.61 17287.57 25058.35 23794.72 11071.29 22186.25 19192.56 148
QAPM80.88 16279.50 18585.03 9988.01 20268.97 11091.59 4692.00 10166.63 31775.15 28492.16 10657.70 24295.45 7163.52 29188.76 14790.66 223
TranMVSNet+NR-MVSNet80.84 16380.31 16082.42 22587.85 20862.33 29287.74 17491.33 13180.55 977.99 20989.86 17665.23 14592.62 21267.05 26775.24 36192.30 162
UGNet80.83 16479.59 18384.54 11988.04 19968.09 14089.42 10088.16 24676.95 7076.22 25289.46 19549.30 33793.94 14268.48 25390.31 11691.60 187
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
AstraMVS80.81 16580.14 16682.80 21186.05 27563.96 24886.46 22185.90 30173.71 16180.85 15690.56 16154.06 27791.57 26079.72 12183.97 23192.86 138
Fast-Effi-MVS+80.81 16579.92 17083.47 17588.85 15964.51 23685.53 25189.39 19870.79 22978.49 19585.06 32167.54 11693.58 16167.03 26886.58 18492.32 161
XVG-OURS-SEG-HR80.81 16579.76 17683.96 16285.60 28468.78 11483.54 30690.50 15670.66 23576.71 23991.66 12060.69 21491.26 27776.94 15381.58 26991.83 179
IMVS_040380.80 16880.12 16782.87 20787.13 24063.59 26085.19 25689.33 20070.51 23878.49 19589.03 20563.26 16393.27 17972.56 20885.56 20691.74 182
xiu_mvs_v1_base_debu80.80 16879.72 17984.03 15687.35 22770.19 8485.56 24688.77 23269.06 28081.83 13488.16 23450.91 31492.85 20678.29 13787.56 16589.06 285
xiu_mvs_v1_base80.80 16879.72 17984.03 15687.35 22770.19 8485.56 24688.77 23269.06 28081.83 13488.16 23450.91 31492.85 20678.29 13787.56 16589.06 285
xiu_mvs_v1_base_debi80.80 16879.72 17984.03 15687.35 22770.19 8485.56 24688.77 23269.06 28081.83 13488.16 23450.91 31492.85 20678.29 13787.56 16589.06 285
ACMM73.20 880.78 17279.84 17483.58 17389.31 14368.37 13089.99 7991.60 12370.28 24777.25 22489.66 18653.37 28493.53 16674.24 18882.85 25488.85 298
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
LuminaMVS80.68 17379.62 18283.83 16585.07 30168.01 14486.99 19888.83 22970.36 24381.38 14387.99 24150.11 32592.51 22179.02 12586.89 18090.97 210
114514_t80.68 17379.51 18484.20 13994.09 3867.27 17189.64 9091.11 13958.75 40474.08 30390.72 15558.10 23895.04 9569.70 24089.42 13590.30 240
IMVS_040780.61 17579.90 17282.75 21887.13 24063.59 26085.33 25589.33 20070.51 23877.82 21189.03 20561.84 18992.91 20372.56 20885.56 20691.74 182
CANet_DTU80.61 17579.87 17382.83 20885.60 28463.17 27687.36 18688.65 24076.37 8975.88 25988.44 22653.51 28293.07 19673.30 19789.74 12992.25 164
VPA-MVSNet80.60 17780.55 15480.76 26788.07 19860.80 31386.86 20591.58 12475.67 10580.24 16589.45 19763.34 16090.25 30170.51 22979.22 30091.23 200
mvsmamba80.60 17779.38 18784.27 13589.74 12467.24 17387.47 18086.95 27970.02 25275.38 27288.93 21051.24 31192.56 21775.47 17689.22 13893.00 132
PVSNet_BlendedMVS80.60 17780.02 16882.36 22788.85 15965.40 21086.16 23292.00 10169.34 26978.11 20586.09 29666.02 13894.27 12671.52 21782.06 26487.39 334
AdaColmapbinary80.58 18079.42 18684.06 15193.09 5968.91 11189.36 10488.97 22669.27 27175.70 26289.69 18457.20 25095.77 6063.06 29688.41 15587.50 333
EI-MVSNet80.52 18179.98 16982.12 23084.28 31663.19 27586.41 22288.95 22774.18 15078.69 18887.54 25366.62 12592.43 22472.57 20680.57 28390.74 220
viewmambaseed2359dif80.41 18279.84 17482.12 23082.95 35662.50 28883.39 30788.06 25167.11 30680.98 15190.31 16766.20 13491.01 28874.62 18284.90 21492.86 138
XVG-OURS80.41 18279.23 19383.97 16185.64 28269.02 10883.03 31990.39 15971.09 22077.63 21791.49 13154.62 27291.35 27475.71 17083.47 24591.54 190
SDMVSNet80.38 18480.18 16380.99 26189.03 15764.94 22580.45 35189.40 19775.19 12076.61 24389.98 17460.61 21887.69 34676.83 15783.55 24290.33 238
PCF-MVS73.52 780.38 18478.84 20285.01 10087.71 21868.99 10983.65 30091.46 13063.00 36177.77 21590.28 16866.10 13595.09 9461.40 31588.22 15790.94 212
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
viewdifsd2359ckpt1180.37 18679.73 17782.30 22883.70 33262.39 28984.20 28886.67 28573.22 18080.90 15390.62 15863.00 17291.56 26176.81 15878.44 30692.95 135
viewmsd2359difaftdt80.37 18679.73 17782.30 22883.70 33262.39 28984.20 28886.67 28573.22 18080.90 15390.62 15863.00 17291.56 26176.81 15878.44 30692.95 135
X-MVStestdata80.37 18677.83 22688.00 1794.42 2073.33 1992.78 1992.99 5079.14 2683.67 10812.47 46867.45 11796.60 3383.06 8294.50 5394.07 65
test_djsdf80.30 18979.32 19083.27 18483.98 32465.37 21390.50 6790.38 16068.55 29076.19 25388.70 21656.44 25793.46 17178.98 12880.14 28990.97 210
v2v48280.23 19079.29 19183.05 19783.62 33464.14 24587.04 19589.97 17673.61 16478.18 20487.22 26161.10 20893.82 15176.11 16476.78 33091.18 201
NR-MVSNet80.23 19079.38 18782.78 21587.80 21163.34 27086.31 22691.09 14079.01 3172.17 32989.07 20367.20 12092.81 21066.08 27475.65 34792.20 167
Anonymous2024052980.19 19278.89 20184.10 14290.60 10064.75 23188.95 12190.90 14465.97 32580.59 16091.17 14249.97 32793.73 15969.16 24682.70 25893.81 81
IterMVS-LS80.06 19379.38 18782.11 23285.89 27663.20 27486.79 20889.34 19974.19 14975.45 26986.72 27366.62 12592.39 22672.58 20576.86 32790.75 219
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
Effi-MVS+-dtu80.03 19478.57 20684.42 12485.13 29968.74 11788.77 13088.10 24874.99 12474.97 29083.49 35757.27 24893.36 17573.53 19380.88 27791.18 201
v114480.03 19479.03 19783.01 19983.78 32964.51 23687.11 19490.57 15571.96 20278.08 20786.20 29361.41 20093.94 14274.93 18077.23 32190.60 226
v879.97 19679.02 19882.80 21184.09 32164.50 23887.96 16490.29 16774.13 15275.24 28186.81 27062.88 17493.89 15074.39 18675.40 35690.00 256
OpenMVScopyleft72.83 1079.77 19778.33 21384.09 14685.17 29569.91 8990.57 6490.97 14266.70 31172.17 32991.91 11154.70 27093.96 13961.81 31290.95 10788.41 314
v1079.74 19878.67 20382.97 20384.06 32264.95 22487.88 17090.62 15273.11 18275.11 28586.56 28461.46 19994.05 13873.68 19175.55 34989.90 262
ECVR-MVScopyleft79.61 19979.26 19280.67 26990.08 11254.69 39387.89 16977.44 40774.88 13080.27 16492.79 9548.96 34392.45 22368.55 25292.50 8094.86 19
BH-RMVSNet79.61 19978.44 20983.14 19189.38 13965.93 19684.95 26687.15 27673.56 16678.19 20389.79 18256.67 25593.36 17559.53 33186.74 18290.13 246
v119279.59 20178.43 21083.07 19683.55 33664.52 23586.93 20290.58 15370.83 22877.78 21485.90 29759.15 23093.94 14273.96 19077.19 32390.76 218
ab-mvs79.51 20278.97 19981.14 25788.46 18060.91 31183.84 29589.24 21270.36 24379.03 18288.87 21363.23 16590.21 30265.12 28182.57 25992.28 163
WR-MVS79.49 20379.22 19480.27 27888.79 16858.35 33885.06 26388.61 24278.56 3577.65 21688.34 22863.81 15990.66 29764.98 28377.22 32291.80 181
v14419279.47 20478.37 21182.78 21583.35 33963.96 24886.96 19990.36 16369.99 25477.50 21885.67 30460.66 21693.77 15574.27 18776.58 33190.62 224
BH-untuned79.47 20478.60 20582.05 23389.19 15065.91 19786.07 23488.52 24372.18 19775.42 27087.69 24761.15 20793.54 16560.38 32386.83 18186.70 355
test111179.43 20679.18 19580.15 28189.99 11753.31 40687.33 18877.05 41175.04 12380.23 16692.77 9748.97 34292.33 23168.87 24992.40 8294.81 22
mvs_anonymous79.42 20779.11 19680.34 27684.45 31557.97 34582.59 32187.62 26467.40 30576.17 25688.56 22368.47 10489.59 31370.65 22886.05 19593.47 104
thisisatest053079.40 20877.76 23184.31 13087.69 22065.10 22187.36 18684.26 32370.04 25177.42 22088.26 23249.94 32894.79 10870.20 23384.70 21893.03 129
tttt051779.40 20877.91 22283.90 16488.10 19663.84 25288.37 15084.05 32571.45 21176.78 23789.12 20249.93 33094.89 10170.18 23483.18 25192.96 134
V4279.38 21078.24 21582.83 20881.10 38865.50 20985.55 24989.82 18071.57 20978.21 20286.12 29560.66 21693.18 19075.64 17175.46 35389.81 267
mamba_040879.37 21177.52 23884.93 10588.81 16367.96 14565.03 45188.66 23870.96 22679.48 17589.80 18058.69 23294.65 11470.35 23185.93 19992.18 169
jajsoiax79.29 21277.96 22083.27 18484.68 30966.57 18589.25 10790.16 17169.20 27675.46 26889.49 19245.75 37093.13 19376.84 15680.80 27990.11 248
v192192079.22 21378.03 21982.80 21183.30 34163.94 25086.80 20790.33 16469.91 25777.48 21985.53 30858.44 23693.75 15773.60 19276.85 32890.71 222
AUN-MVS79.21 21477.60 23684.05 15488.71 17267.61 15785.84 24187.26 27369.08 27977.23 22688.14 23853.20 28693.47 17075.50 17573.45 37891.06 205
TAPA-MVS73.13 979.15 21577.94 22182.79 21489.59 12662.99 28188.16 15891.51 12665.77 32677.14 23291.09 14460.91 21193.21 18450.26 39987.05 17692.17 172
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
mvs_tets79.13 21677.77 23083.22 18884.70 30866.37 18789.17 11090.19 17069.38 26875.40 27189.46 19544.17 38293.15 19176.78 16080.70 28190.14 245
UniMVSNet_ETH3D79.10 21778.24 21581.70 24086.85 25160.24 32287.28 19088.79 23174.25 14876.84 23490.53 16349.48 33391.56 26167.98 25682.15 26293.29 111
CDS-MVSNet79.07 21877.70 23383.17 19087.60 22268.23 13784.40 28486.20 29667.49 30376.36 24986.54 28561.54 19690.79 29261.86 31187.33 17090.49 231
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
MVSTER79.01 21977.88 22582.38 22683.07 34964.80 23084.08 29388.95 22769.01 28378.69 18887.17 26454.70 27092.43 22474.69 18180.57 28389.89 263
v124078.99 22077.78 22982.64 22083.21 34463.54 26486.62 21690.30 16669.74 26477.33 22285.68 30357.04 25193.76 15673.13 20076.92 32590.62 224
Anonymous2023121178.97 22177.69 23482.81 21090.54 10264.29 24390.11 7891.51 12665.01 33776.16 25788.13 23950.56 31993.03 20169.68 24177.56 32091.11 203
v7n78.97 22177.58 23783.14 19183.45 33865.51 20888.32 15291.21 13473.69 16272.41 32586.32 29157.93 23993.81 15269.18 24575.65 34790.11 248
icg_test_0407_278.92 22378.93 20078.90 30687.13 24063.59 26076.58 39889.33 20070.51 23877.82 21189.03 20561.84 18981.38 40372.56 20885.56 20691.74 182
TAMVS78.89 22477.51 24083.03 19887.80 21167.79 15384.72 27085.05 31267.63 30076.75 23887.70 24662.25 18390.82 29158.53 34287.13 17590.49 231
c3_l78.75 22577.91 22281.26 25382.89 35761.56 30384.09 29289.13 21869.97 25575.56 26484.29 33666.36 13092.09 23873.47 19575.48 35190.12 247
tt080578.73 22677.83 22681.43 24685.17 29560.30 32189.41 10190.90 14471.21 21777.17 23188.73 21546.38 35993.21 18472.57 20678.96 30190.79 216
v14878.72 22777.80 22881.47 24582.73 36061.96 29886.30 22788.08 24973.26 17776.18 25485.47 31062.46 17992.36 22871.92 21673.82 37590.09 250
VPNet78.69 22878.66 20478.76 30888.31 18655.72 38284.45 28186.63 28876.79 7578.26 20190.55 16259.30 22989.70 31266.63 26977.05 32490.88 213
ET-MVSNet_ETH3D78.63 22976.63 26184.64 11786.73 25669.47 9885.01 26484.61 31669.54 26566.51 39586.59 28150.16 32491.75 25276.26 16384.24 22892.69 144
anonymousdsp78.60 23077.15 24682.98 20280.51 39467.08 17687.24 19189.53 19365.66 32875.16 28387.19 26352.52 28892.25 23377.17 15079.34 29889.61 272
miper_ehance_all_eth78.59 23177.76 23181.08 25982.66 36261.56 30383.65 30089.15 21668.87 28575.55 26583.79 34866.49 12892.03 23973.25 19876.39 33689.64 271
VortexMVS78.57 23277.89 22480.59 27085.89 27662.76 28485.61 24489.62 19072.06 20074.99 28985.38 31255.94 25990.77 29574.99 17976.58 33188.23 316
WR-MVS_H78.51 23378.49 20778.56 31388.02 20056.38 37288.43 14592.67 6877.14 6473.89 30587.55 25266.25 13289.24 32058.92 33773.55 37790.06 254
GBi-Net78.40 23477.40 24181.40 24887.60 22263.01 27788.39 14789.28 20671.63 20575.34 27487.28 25754.80 26691.11 28162.72 29879.57 29390.09 250
test178.40 23477.40 24181.40 24887.60 22263.01 27788.39 14789.28 20671.63 20575.34 27487.28 25754.80 26691.11 28162.72 29879.57 29390.09 250
Vis-MVSNet (Re-imp)78.36 23678.45 20878.07 32588.64 17451.78 41786.70 21279.63 38974.14 15175.11 28590.83 15461.29 20489.75 31058.10 34791.60 9492.69 144
Anonymous20240521178.25 23777.01 24881.99 23591.03 9060.67 31584.77 26983.90 32770.65 23680.00 16891.20 14041.08 40391.43 27265.21 28085.26 21193.85 77
CP-MVSNet78.22 23878.34 21277.84 32987.83 21054.54 39587.94 16691.17 13677.65 4673.48 31188.49 22462.24 18488.43 33662.19 30674.07 37090.55 228
BH-w/o78.21 23977.33 24480.84 26588.81 16365.13 21884.87 26787.85 25969.75 26274.52 29884.74 32861.34 20293.11 19458.24 34685.84 20284.27 393
FMVSNet278.20 24077.21 24581.20 25587.60 22262.89 28387.47 18089.02 22271.63 20575.29 28087.28 25754.80 26691.10 28462.38 30379.38 29789.61 272
MVS78.19 24176.99 25081.78 23885.66 28166.99 17784.66 27290.47 15755.08 42572.02 33185.27 31463.83 15894.11 13666.10 27389.80 12884.24 394
Baseline_NR-MVSNet78.15 24278.33 21377.61 33485.79 27856.21 37686.78 20985.76 30373.60 16577.93 21087.57 25065.02 14788.99 32567.14 26675.33 35887.63 328
CNLPA78.08 24376.79 25581.97 23690.40 10571.07 6787.59 17784.55 31766.03 32472.38 32689.64 18757.56 24486.04 36359.61 33083.35 24788.79 301
cl2278.07 24477.01 24881.23 25482.37 36961.83 30083.55 30487.98 25368.96 28475.06 28783.87 34461.40 20191.88 24873.53 19376.39 33689.98 259
PLCcopyleft70.83 1178.05 24576.37 26783.08 19591.88 7967.80 15288.19 15689.46 19564.33 34569.87 35688.38 22753.66 28093.58 16158.86 33882.73 25687.86 324
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
Fast-Effi-MVS+-dtu78.02 24676.49 26282.62 22183.16 34866.96 18086.94 20187.45 26972.45 19171.49 33784.17 34154.79 26991.58 25867.61 25980.31 28689.30 281
PS-CasMVS78.01 24778.09 21877.77 33187.71 21854.39 39788.02 16291.22 13377.50 5473.26 31388.64 21960.73 21288.41 33761.88 31073.88 37490.53 229
HY-MVS69.67 1277.95 24877.15 24680.36 27587.57 22660.21 32383.37 30987.78 26166.11 32175.37 27387.06 26863.27 16290.48 29961.38 31682.43 26090.40 235
eth_miper_zixun_eth77.92 24976.69 25981.61 24383.00 35261.98 29783.15 31389.20 21469.52 26674.86 29284.35 33561.76 19292.56 21771.50 21972.89 38390.28 241
FMVSNet377.88 25076.85 25380.97 26386.84 25262.36 29186.52 21988.77 23271.13 21875.34 27486.66 27954.07 27691.10 28462.72 29879.57 29389.45 276
miper_enhance_ethall77.87 25176.86 25280.92 26481.65 37661.38 30582.68 32088.98 22465.52 33075.47 26682.30 37765.76 14292.00 24272.95 20176.39 33689.39 278
FE-MVS77.78 25275.68 27384.08 14788.09 19766.00 19483.13 31487.79 26068.42 29478.01 20885.23 31645.50 37395.12 8859.11 33585.83 20391.11 203
PEN-MVS77.73 25377.69 23477.84 32987.07 24853.91 40087.91 16891.18 13577.56 5173.14 31588.82 21461.23 20589.17 32259.95 32672.37 38590.43 233
cl____77.72 25476.76 25680.58 27182.49 36660.48 31883.09 31587.87 25769.22 27474.38 30185.22 31762.10 18691.53 26671.09 22275.41 35589.73 270
DIV-MVS_self_test77.72 25476.76 25680.58 27182.48 36760.48 31883.09 31587.86 25869.22 27474.38 30185.24 31562.10 18691.53 26671.09 22275.40 35689.74 269
sd_testset77.70 25677.40 24178.60 31189.03 15760.02 32479.00 37285.83 30275.19 12076.61 24389.98 17454.81 26585.46 37162.63 30283.55 24290.33 238
PAPM77.68 25776.40 26681.51 24487.29 23661.85 29983.78 29689.59 19164.74 33971.23 33988.70 21662.59 17693.66 16052.66 38387.03 17789.01 290
SSM_0407277.67 25877.52 23878.12 32388.81 16367.96 14565.03 45188.66 23870.96 22679.48 17589.80 18058.69 23274.23 44470.35 23185.93 19992.18 169
CHOSEN 1792x268877.63 25975.69 27283.44 17789.98 11868.58 12578.70 37787.50 26756.38 42075.80 26186.84 26958.67 23491.40 27361.58 31485.75 20490.34 237
HyFIR lowres test77.53 26075.40 28083.94 16389.59 12666.62 18380.36 35288.64 24156.29 42176.45 24685.17 31857.64 24393.28 17761.34 31783.10 25291.91 178
FMVSNet177.44 26176.12 26981.40 24886.81 25363.01 27788.39 14789.28 20670.49 24274.39 30087.28 25749.06 34191.11 28160.91 31978.52 30490.09 250
TR-MVS77.44 26176.18 26881.20 25588.24 18863.24 27284.61 27586.40 29267.55 30277.81 21386.48 28754.10 27593.15 19157.75 35082.72 25787.20 340
1112_ss77.40 26376.43 26480.32 27789.11 15660.41 32083.65 30087.72 26362.13 37473.05 31686.72 27362.58 17789.97 30662.11 30980.80 27990.59 227
thisisatest051577.33 26475.38 28183.18 18985.27 29463.80 25382.11 32683.27 33765.06 33575.91 25883.84 34649.54 33294.27 12667.24 26486.19 19291.48 194
test250677.30 26576.49 26279.74 28990.08 11252.02 41187.86 17163.10 45474.88 13080.16 16792.79 9538.29 41892.35 22968.74 25192.50 8094.86 19
pm-mvs177.25 26676.68 26078.93 30584.22 31858.62 33686.41 22288.36 24571.37 21273.31 31288.01 24061.22 20689.15 32364.24 28973.01 38289.03 289
IMVS_040477.16 26776.42 26579.37 29787.13 24063.59 26077.12 39689.33 20070.51 23866.22 39889.03 20550.36 32282.78 39372.56 20885.56 20691.74 182
LCM-MVSNet-Re77.05 26876.94 25177.36 33887.20 23751.60 41880.06 35780.46 37775.20 11967.69 37586.72 27362.48 17888.98 32663.44 29389.25 13691.51 191
DTE-MVSNet76.99 26976.80 25477.54 33786.24 26753.06 40987.52 17890.66 15177.08 6872.50 32388.67 21860.48 22089.52 31457.33 35470.74 39790.05 255
baseline176.98 27076.75 25877.66 33288.13 19455.66 38385.12 26081.89 35873.04 18476.79 23688.90 21162.43 18087.78 34563.30 29571.18 39589.55 274
LS3D76.95 27174.82 28983.37 18190.45 10367.36 16789.15 11486.94 28061.87 37769.52 35990.61 16051.71 30794.53 11746.38 42186.71 18388.21 318
GA-MVS76.87 27275.17 28681.97 23682.75 35962.58 28581.44 33586.35 29472.16 19974.74 29382.89 36846.20 36492.02 24168.85 25081.09 27491.30 199
mamv476.81 27378.23 21772.54 39186.12 27265.75 20478.76 37682.07 35764.12 34772.97 31791.02 14967.97 11168.08 45683.04 8478.02 31383.80 401
DP-MVS76.78 27474.57 29283.42 17893.29 4869.46 10088.55 14383.70 32963.98 35270.20 34788.89 21254.01 27894.80 10746.66 41881.88 26786.01 367
cascas76.72 27574.64 29182.99 20085.78 27965.88 19882.33 32389.21 21360.85 38372.74 31981.02 38847.28 35093.75 15767.48 26185.02 21289.34 280
testing9176.54 27675.66 27579.18 30288.43 18255.89 37981.08 33883.00 34573.76 16075.34 27484.29 33646.20 36490.07 30464.33 28784.50 22091.58 189
131476.53 27775.30 28480.21 28083.93 32562.32 29384.66 27288.81 23060.23 38870.16 35084.07 34355.30 26390.73 29667.37 26283.21 25087.59 331
thres100view90076.50 27875.55 27779.33 29889.52 12956.99 36185.83 24283.23 33873.94 15576.32 25087.12 26551.89 30391.95 24448.33 40983.75 23689.07 283
thres600view776.50 27875.44 27879.68 29189.40 13757.16 35885.53 25183.23 33873.79 15976.26 25187.09 26651.89 30391.89 24748.05 41483.72 23990.00 256
thres40076.50 27875.37 28279.86 28689.13 15257.65 35285.17 25783.60 33073.41 17276.45 24686.39 28952.12 29591.95 24448.33 40983.75 23690.00 256
MonoMVSNet76.49 28175.80 27078.58 31281.55 37958.45 33786.36 22586.22 29574.87 13274.73 29483.73 35051.79 30688.73 33170.78 22472.15 38888.55 311
tfpn200view976.42 28275.37 28279.55 29689.13 15257.65 35285.17 25783.60 33073.41 17276.45 24686.39 28952.12 29591.95 24448.33 40983.75 23689.07 283
Test_1112_low_res76.40 28375.44 27879.27 29989.28 14558.09 34181.69 33087.07 27759.53 39572.48 32486.67 27861.30 20389.33 31760.81 32180.15 28890.41 234
F-COLMAP76.38 28474.33 29882.50 22489.28 14566.95 18188.41 14689.03 22164.05 35066.83 38788.61 22046.78 35692.89 20457.48 35178.55 30387.67 327
LTVRE_ROB69.57 1376.25 28574.54 29481.41 24788.60 17564.38 24279.24 36789.12 21970.76 23169.79 35887.86 24349.09 34093.20 18756.21 36680.16 28786.65 356
Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
MVP-Stereo76.12 28674.46 29681.13 25885.37 29169.79 9184.42 28387.95 25565.03 33667.46 37885.33 31353.28 28591.73 25458.01 34883.27 24981.85 421
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
XVG-ACMP-BASELINE76.11 28774.27 29981.62 24183.20 34564.67 23283.60 30389.75 18569.75 26271.85 33287.09 26632.78 43392.11 23769.99 23780.43 28588.09 320
testing9976.09 28875.12 28779.00 30388.16 19155.50 38580.79 34281.40 36573.30 17675.17 28284.27 33944.48 37990.02 30564.28 28884.22 22991.48 194
ACMH+68.96 1476.01 28974.01 30082.03 23488.60 17565.31 21488.86 12487.55 26570.25 24967.75 37487.47 25541.27 40193.19 18958.37 34475.94 34487.60 329
ACMH67.68 1675.89 29073.93 30281.77 23988.71 17266.61 18488.62 13989.01 22369.81 25866.78 38886.70 27741.95 39891.51 26855.64 36778.14 31287.17 341
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IB-MVS68.01 1575.85 29173.36 31183.31 18284.76 30766.03 19183.38 30885.06 31170.21 25069.40 36081.05 38745.76 36994.66 11365.10 28275.49 35089.25 282
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
baseline275.70 29273.83 30581.30 25183.26 34261.79 30182.57 32280.65 37266.81 30866.88 38683.42 35857.86 24192.19 23563.47 29279.57 29389.91 261
WTY-MVS75.65 29375.68 27375.57 35486.40 26556.82 36377.92 39082.40 35365.10 33476.18 25487.72 24563.13 17080.90 40660.31 32481.96 26589.00 292
thres20075.55 29474.47 29578.82 30787.78 21457.85 34883.07 31783.51 33372.44 19375.84 26084.42 33152.08 29891.75 25247.41 41683.64 24186.86 351
test_vis1_n_192075.52 29575.78 27174.75 36879.84 40257.44 35683.26 31185.52 30562.83 36579.34 18086.17 29445.10 37579.71 41078.75 13081.21 27387.10 347
EPNet_dtu75.46 29674.86 28877.23 34182.57 36454.60 39486.89 20383.09 34271.64 20466.25 39785.86 29955.99 25888.04 34154.92 37186.55 18589.05 288
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
IterMVS-SCA-FT75.43 29773.87 30480.11 28282.69 36164.85 22981.57 33283.47 33469.16 27770.49 34484.15 34251.95 30188.15 33969.23 24472.14 38987.34 336
XXY-MVS75.41 29875.56 27674.96 36383.59 33557.82 34980.59 34883.87 32866.54 31874.93 29188.31 22963.24 16480.09 40962.16 30776.85 32886.97 349
reproduce_monomvs75.40 29974.38 29778.46 31883.92 32657.80 35083.78 29686.94 28073.47 17072.25 32884.47 33038.74 41489.27 31975.32 17770.53 39888.31 315
TransMVSNet (Re)75.39 30074.56 29377.86 32885.50 28857.10 36086.78 20986.09 29972.17 19871.53 33687.34 25663.01 17189.31 31856.84 36061.83 42787.17 341
CostFormer75.24 30173.90 30379.27 29982.65 36358.27 34080.80 34182.73 35161.57 37875.33 27883.13 36355.52 26191.07 28764.98 28378.34 31188.45 312
testing1175.14 30274.01 30078.53 31588.16 19156.38 37280.74 34580.42 37970.67 23272.69 32283.72 35143.61 38689.86 30762.29 30583.76 23589.36 279
testing3-275.12 30375.19 28574.91 36490.40 10545.09 44780.29 35478.42 39978.37 4076.54 24587.75 24444.36 38087.28 35157.04 35783.49 24492.37 158
D2MVS74.82 30473.21 31279.64 29379.81 40362.56 28780.34 35387.35 27064.37 34468.86 36582.66 37246.37 36090.10 30367.91 25781.24 27286.25 360
pmmvs674.69 30573.39 30978.61 31081.38 38357.48 35586.64 21587.95 25564.99 33870.18 34886.61 28050.43 32189.52 31462.12 30870.18 40088.83 299
SD_040374.65 30674.77 29074.29 37286.20 26947.42 43683.71 29885.12 30969.30 27068.50 37087.95 24259.40 22886.05 36249.38 40383.35 24789.40 277
tfpnnormal74.39 30773.16 31378.08 32486.10 27458.05 34284.65 27487.53 26670.32 24671.22 34085.63 30554.97 26489.86 30743.03 43375.02 36386.32 359
IterMVS74.29 30872.94 31678.35 31981.53 38063.49 26681.58 33182.49 35268.06 29869.99 35383.69 35251.66 30885.54 36965.85 27671.64 39286.01 367
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
OurMVSNet-221017-074.26 30972.42 32279.80 28883.76 33059.59 32985.92 23886.64 28766.39 31966.96 38587.58 24939.46 40991.60 25765.76 27769.27 40388.22 317
SCA74.22 31072.33 32379.91 28584.05 32362.17 29579.96 36079.29 39366.30 32072.38 32680.13 40051.95 30188.60 33459.25 33377.67 31988.96 294
mmtdpeth74.16 31173.01 31577.60 33683.72 33161.13 30685.10 26185.10 31072.06 20077.21 23080.33 39743.84 38485.75 36577.14 15152.61 44685.91 370
miper_lstm_enhance74.11 31273.11 31477.13 34280.11 39859.62 32872.23 42286.92 28266.76 31070.40 34582.92 36756.93 25282.92 39269.06 24772.63 38488.87 297
testing22274.04 31372.66 31978.19 32187.89 20655.36 38681.06 33979.20 39471.30 21574.65 29683.57 35639.11 41388.67 33351.43 39185.75 20490.53 229
EG-PatchMatch MVS74.04 31371.82 32780.71 26884.92 30367.42 16385.86 24088.08 24966.04 32364.22 41083.85 34535.10 42992.56 21757.44 35280.83 27882.16 419
pmmvs474.03 31571.91 32680.39 27481.96 37268.32 13181.45 33482.14 35559.32 39669.87 35685.13 31952.40 29188.13 34060.21 32574.74 36684.73 390
MS-PatchMatch73.83 31672.67 31877.30 34083.87 32766.02 19281.82 32784.66 31561.37 38168.61 36882.82 37047.29 34988.21 33859.27 33284.32 22777.68 436
test_cas_vis1_n_192073.76 31773.74 30673.81 37875.90 42459.77 32680.51 34982.40 35358.30 40681.62 14185.69 30244.35 38176.41 42876.29 16278.61 30285.23 380
myMVS_eth3d2873.62 31873.53 30873.90 37788.20 18947.41 43778.06 38779.37 39174.29 14773.98 30484.29 33644.67 37683.54 38751.47 38987.39 16990.74 220
sss73.60 31973.64 30773.51 38082.80 35855.01 39176.12 40081.69 36162.47 37074.68 29585.85 30057.32 24778.11 41760.86 32080.93 27587.39 334
RPMNet73.51 32070.49 34382.58 22381.32 38665.19 21675.92 40292.27 8557.60 41372.73 32076.45 42852.30 29295.43 7348.14 41377.71 31687.11 345
WBMVS73.43 32172.81 31775.28 36087.91 20550.99 42478.59 38081.31 36765.51 33274.47 29984.83 32546.39 35886.68 35558.41 34377.86 31488.17 319
SixPastTwentyTwo73.37 32271.26 33679.70 29085.08 30057.89 34785.57 24583.56 33271.03 22465.66 40085.88 29842.10 39692.57 21659.11 33563.34 42288.65 307
CR-MVSNet73.37 32271.27 33579.67 29281.32 38665.19 21675.92 40280.30 38159.92 39172.73 32081.19 38552.50 28986.69 35459.84 32777.71 31687.11 345
MSDG73.36 32470.99 33880.49 27384.51 31465.80 20180.71 34686.13 29865.70 32765.46 40183.74 34944.60 37790.91 29051.13 39276.89 32684.74 389
SSC-MVS3.273.35 32573.39 30973.23 38185.30 29349.01 43274.58 41581.57 36275.21 11873.68 30885.58 30752.53 28782.05 39854.33 37577.69 31888.63 308
tpm273.26 32671.46 33178.63 30983.34 34056.71 36680.65 34780.40 38056.63 41973.55 31082.02 38251.80 30591.24 27856.35 36578.42 30987.95 321
RPSCF73.23 32771.46 33178.54 31482.50 36559.85 32582.18 32582.84 35058.96 40071.15 34189.41 19945.48 37484.77 37858.82 33971.83 39191.02 209
PatchmatchNetpermissive73.12 32871.33 33478.49 31783.18 34660.85 31279.63 36278.57 39864.13 34671.73 33379.81 40551.20 31285.97 36457.40 35376.36 34188.66 306
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
UBG73.08 32972.27 32475.51 35688.02 20051.29 42278.35 38477.38 40865.52 33073.87 30682.36 37545.55 37186.48 35855.02 37084.39 22688.75 303
COLMAP_ROBcopyleft66.92 1773.01 33070.41 34580.81 26687.13 24065.63 20588.30 15384.19 32462.96 36263.80 41587.69 24738.04 41992.56 21746.66 41874.91 36484.24 394
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
CVMVSNet72.99 33172.58 32074.25 37384.28 31650.85 42586.41 22283.45 33544.56 44573.23 31487.54 25349.38 33585.70 36665.90 27578.44 30686.19 362
test-LLR72.94 33272.43 32174.48 36981.35 38458.04 34378.38 38177.46 40566.66 31269.95 35479.00 41248.06 34679.24 41166.13 27184.83 21586.15 363
test_040272.79 33370.44 34479.84 28788.13 19465.99 19585.93 23784.29 32165.57 32967.40 38185.49 30946.92 35392.61 21335.88 44774.38 36980.94 426
tpmrst72.39 33472.13 32573.18 38580.54 39349.91 42979.91 36179.08 39563.11 35971.69 33479.95 40255.32 26282.77 39465.66 27873.89 37386.87 350
PatchMatch-RL72.38 33570.90 33976.80 34588.60 17567.38 16679.53 36376.17 41762.75 36769.36 36182.00 38345.51 37284.89 37753.62 37880.58 28278.12 435
CL-MVSNet_self_test72.37 33671.46 33175.09 36279.49 40953.53 40280.76 34485.01 31369.12 27870.51 34382.05 38157.92 24084.13 38252.27 38566.00 41687.60 329
tpm72.37 33671.71 32874.35 37182.19 37052.00 41279.22 36877.29 40964.56 34172.95 31883.68 35351.35 30983.26 39158.33 34575.80 34587.81 325
ETVMVS72.25 33871.05 33775.84 35087.77 21551.91 41479.39 36574.98 42069.26 27273.71 30782.95 36640.82 40586.14 36146.17 42284.43 22589.47 275
sc_t172.19 33969.51 35080.23 27984.81 30561.09 30884.68 27180.22 38360.70 38471.27 33883.58 35536.59 42489.24 32060.41 32263.31 42390.37 236
UWE-MVS72.13 34071.49 33074.03 37586.66 25947.70 43481.40 33676.89 41363.60 35675.59 26384.22 34039.94 40885.62 36848.98 40686.13 19488.77 302
PVSNet64.34 1872.08 34170.87 34075.69 35286.21 26856.44 37074.37 41680.73 37162.06 37570.17 34982.23 37942.86 39083.31 39054.77 37284.45 22487.32 337
WB-MVSnew71.96 34271.65 32972.89 38784.67 31251.88 41582.29 32477.57 40462.31 37173.67 30983.00 36553.49 28381.10 40545.75 42582.13 26385.70 373
pmmvs571.55 34370.20 34875.61 35377.83 41756.39 37181.74 32980.89 36857.76 41167.46 37884.49 32949.26 33885.32 37357.08 35675.29 35985.11 384
test-mter71.41 34470.39 34674.48 36981.35 38458.04 34378.38 38177.46 40560.32 38769.95 35479.00 41236.08 42779.24 41166.13 27184.83 21586.15 363
K. test v371.19 34568.51 35779.21 30183.04 35157.78 35184.35 28576.91 41272.90 18762.99 41882.86 36939.27 41091.09 28661.65 31352.66 44588.75 303
dmvs_re71.14 34670.58 34172.80 38881.96 37259.68 32775.60 40679.34 39268.55 29069.27 36380.72 39349.42 33476.54 42552.56 38477.79 31582.19 418
tpmvs71.09 34769.29 35276.49 34682.04 37156.04 37778.92 37481.37 36664.05 35067.18 38378.28 41849.74 33189.77 30949.67 40272.37 38583.67 402
AllTest70.96 34868.09 36379.58 29485.15 29763.62 25684.58 27679.83 38662.31 37160.32 42886.73 27132.02 43488.96 32850.28 39771.57 39386.15 363
test_fmvs170.93 34970.52 34272.16 39373.71 43655.05 39080.82 34078.77 39751.21 43778.58 19284.41 33231.20 43876.94 42375.88 16980.12 29084.47 392
test_fmvs1_n70.86 35070.24 34772.73 38972.51 44755.28 38881.27 33779.71 38851.49 43678.73 18784.87 32427.54 44377.02 42276.06 16579.97 29185.88 371
Patchmtry70.74 35169.16 35475.49 35780.72 39054.07 39974.94 41380.30 38158.34 40570.01 35181.19 38552.50 28986.54 35653.37 38071.09 39685.87 372
MIMVSNet70.69 35269.30 35174.88 36584.52 31356.35 37475.87 40479.42 39064.59 34067.76 37382.41 37441.10 40281.54 40146.64 42081.34 27086.75 354
tpm cat170.57 35368.31 35977.35 33982.41 36857.95 34678.08 38680.22 38352.04 43268.54 36977.66 42352.00 30087.84 34451.77 38672.07 39086.25 360
OpenMVS_ROBcopyleft64.09 1970.56 35468.19 36077.65 33380.26 39559.41 33285.01 26482.96 34758.76 40365.43 40282.33 37637.63 42191.23 27945.34 42876.03 34382.32 416
pmmvs-eth3d70.50 35567.83 36978.52 31677.37 42066.18 19081.82 32781.51 36358.90 40163.90 41480.42 39542.69 39186.28 36058.56 34165.30 41883.11 408
tt032070.49 35668.03 36477.89 32784.78 30659.12 33383.55 30480.44 37858.13 40867.43 38080.41 39639.26 41187.54 34855.12 36963.18 42486.99 348
USDC70.33 35768.37 35876.21 34880.60 39256.23 37579.19 36986.49 29060.89 38261.29 42385.47 31031.78 43689.47 31653.37 38076.21 34282.94 412
Patchmatch-RL test70.24 35867.78 37177.61 33477.43 41959.57 33071.16 42670.33 43462.94 36368.65 36772.77 44050.62 31885.49 37069.58 24266.58 41387.77 326
CMPMVSbinary51.72 2170.19 35968.16 36176.28 34773.15 44357.55 35479.47 36483.92 32648.02 44156.48 44184.81 32643.13 38886.42 35962.67 30181.81 26884.89 387
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
tt0320-xc70.11 36067.45 37778.07 32585.33 29259.51 33183.28 31078.96 39658.77 40267.10 38480.28 39836.73 42387.42 34956.83 36159.77 43487.29 338
ppachtmachnet_test70.04 36167.34 37978.14 32279.80 40461.13 30679.19 36980.59 37359.16 39865.27 40379.29 40946.75 35787.29 35049.33 40466.72 41186.00 369
gg-mvs-nofinetune69.95 36267.96 36575.94 34983.07 34954.51 39677.23 39570.29 43563.11 35970.32 34662.33 44943.62 38588.69 33253.88 37787.76 16484.62 391
TESTMET0.1,169.89 36369.00 35572.55 39079.27 41256.85 36278.38 38174.71 42457.64 41268.09 37277.19 42537.75 42076.70 42463.92 29084.09 23084.10 397
test_vis1_n69.85 36469.21 35371.77 39572.66 44655.27 38981.48 33376.21 41652.03 43375.30 27983.20 36228.97 44176.22 43074.60 18378.41 31083.81 400
FMVSNet569.50 36567.96 36574.15 37482.97 35555.35 38780.01 35982.12 35662.56 36963.02 41681.53 38436.92 42281.92 39948.42 40874.06 37185.17 383
mvs5depth69.45 36667.45 37775.46 35873.93 43455.83 38079.19 36983.23 33866.89 30771.63 33583.32 35933.69 43285.09 37459.81 32855.34 44285.46 376
PMMVS69.34 36768.67 35671.35 40075.67 42762.03 29675.17 40873.46 42750.00 43868.68 36679.05 41052.07 29978.13 41661.16 31882.77 25573.90 442
our_test_369.14 36867.00 38175.57 35479.80 40458.80 33477.96 38877.81 40259.55 39462.90 41978.25 41947.43 34883.97 38351.71 38767.58 41083.93 399
EPMVS69.02 36968.16 36171.59 39679.61 40749.80 43177.40 39366.93 44562.82 36670.01 35179.05 41045.79 36877.86 41956.58 36375.26 36087.13 344
KD-MVS_self_test68.81 37067.59 37572.46 39274.29 43345.45 44277.93 38987.00 27863.12 35863.99 41378.99 41442.32 39384.77 37856.55 36464.09 42187.16 343
Anonymous2024052168.80 37167.22 38073.55 37974.33 43254.11 39883.18 31285.61 30458.15 40761.68 42280.94 39030.71 43981.27 40457.00 35873.34 38185.28 379
Anonymous2023120668.60 37267.80 37071.02 40380.23 39750.75 42678.30 38580.47 37656.79 41866.11 39982.63 37346.35 36178.95 41343.62 43175.70 34683.36 405
MIMVSNet168.58 37366.78 38373.98 37680.07 39951.82 41680.77 34384.37 31864.40 34359.75 43182.16 38036.47 42583.63 38642.73 43470.33 39986.48 358
testing368.56 37467.67 37371.22 40287.33 23242.87 45283.06 31871.54 43270.36 24369.08 36484.38 33330.33 44085.69 36737.50 44575.45 35485.09 385
EU-MVSNet68.53 37567.61 37471.31 40178.51 41647.01 43984.47 27884.27 32242.27 44866.44 39684.79 32740.44 40683.76 38458.76 34068.54 40883.17 406
PatchT68.46 37667.85 36770.29 40680.70 39143.93 45072.47 42174.88 42160.15 38970.55 34276.57 42749.94 32881.59 40050.58 39374.83 36585.34 378
test_fmvs268.35 37767.48 37670.98 40469.50 45051.95 41380.05 35876.38 41549.33 43974.65 29684.38 33323.30 45275.40 43974.51 18475.17 36285.60 374
Syy-MVS68.05 37867.85 36768.67 41584.68 30940.97 45878.62 37873.08 42966.65 31566.74 38979.46 40752.11 29782.30 39632.89 45076.38 33982.75 413
test0.0.03 168.00 37967.69 37268.90 41277.55 41847.43 43575.70 40572.95 43166.66 31266.56 39182.29 37848.06 34675.87 43444.97 42974.51 36883.41 404
TDRefinement67.49 38064.34 39276.92 34373.47 44061.07 30984.86 26882.98 34659.77 39258.30 43585.13 31926.06 44487.89 34347.92 41560.59 43281.81 422
test20.0367.45 38166.95 38268.94 41175.48 42944.84 44877.50 39277.67 40366.66 31263.01 41783.80 34747.02 35278.40 41542.53 43668.86 40783.58 403
UnsupCasMVSNet_eth67.33 38265.99 38671.37 39873.48 43951.47 42075.16 40985.19 30865.20 33360.78 42580.93 39242.35 39277.20 42157.12 35553.69 44485.44 377
TinyColmap67.30 38364.81 39074.76 36781.92 37456.68 36780.29 35481.49 36460.33 38656.27 44283.22 36024.77 44887.66 34745.52 42669.47 40279.95 431
FE-MVSNET67.25 38465.33 38873.02 38675.86 42552.54 41080.26 35680.56 37463.80 35560.39 42679.70 40641.41 40084.66 38043.34 43262.62 42581.86 420
myMVS_eth3d67.02 38566.29 38569.21 41084.68 30942.58 45378.62 37873.08 42966.65 31566.74 38979.46 40731.53 43782.30 39639.43 44276.38 33982.75 413
dp66.80 38665.43 38770.90 40579.74 40648.82 43375.12 41174.77 42259.61 39364.08 41277.23 42442.89 38980.72 40748.86 40766.58 41383.16 407
MDA-MVSNet-bldmvs66.68 38763.66 39775.75 35179.28 41160.56 31773.92 41878.35 40064.43 34250.13 45079.87 40444.02 38383.67 38546.10 42356.86 43683.03 410
testgi66.67 38866.53 38467.08 42275.62 42841.69 45775.93 40176.50 41466.11 32165.20 40686.59 28135.72 42874.71 44143.71 43073.38 38084.84 388
CHOSEN 280x42066.51 38964.71 39171.90 39481.45 38163.52 26557.98 45868.95 44153.57 42862.59 42076.70 42646.22 36375.29 44055.25 36879.68 29276.88 438
PM-MVS66.41 39064.14 39373.20 38473.92 43556.45 36978.97 37364.96 45163.88 35464.72 40780.24 39919.84 45683.44 38966.24 27064.52 42079.71 432
JIA-IIPM66.32 39162.82 40376.82 34477.09 42161.72 30265.34 44975.38 41858.04 41064.51 40862.32 45042.05 39786.51 35751.45 39069.22 40482.21 417
KD-MVS_2432*160066.22 39263.89 39573.21 38275.47 43053.42 40470.76 42984.35 31964.10 34866.52 39378.52 41634.55 43084.98 37550.40 39550.33 44981.23 424
miper_refine_blended66.22 39263.89 39573.21 38275.47 43053.42 40470.76 42984.35 31964.10 34866.52 39378.52 41634.55 43084.98 37550.40 39550.33 44981.23 424
ADS-MVSNet266.20 39463.33 39874.82 36679.92 40058.75 33567.55 44175.19 41953.37 42965.25 40475.86 43142.32 39380.53 40841.57 43768.91 40585.18 381
UWE-MVS-2865.32 39564.93 38966.49 42378.70 41438.55 46077.86 39164.39 45262.00 37664.13 41183.60 35441.44 39976.00 43231.39 45280.89 27684.92 386
YYNet165.03 39662.91 40171.38 39775.85 42656.60 36869.12 43774.66 42557.28 41654.12 44477.87 42145.85 36774.48 44249.95 40061.52 42983.05 409
MDA-MVSNet_test_wron65.03 39662.92 40071.37 39875.93 42356.73 36469.09 43874.73 42357.28 41654.03 44577.89 42045.88 36674.39 44349.89 40161.55 42882.99 411
Patchmatch-test64.82 39863.24 39969.57 40879.42 41049.82 43063.49 45569.05 44051.98 43459.95 43080.13 40050.91 31470.98 44940.66 43973.57 37687.90 323
ADS-MVSNet64.36 39962.88 40268.78 41479.92 40047.17 43867.55 44171.18 43353.37 42965.25 40475.86 43142.32 39373.99 44541.57 43768.91 40585.18 381
LF4IMVS64.02 40062.19 40469.50 40970.90 44853.29 40776.13 39977.18 41052.65 43158.59 43380.98 38923.55 45176.52 42653.06 38266.66 41278.68 434
UnsupCasMVSNet_bld63.70 40161.53 40770.21 40773.69 43751.39 42172.82 42081.89 35855.63 42357.81 43771.80 44238.67 41578.61 41449.26 40552.21 44780.63 428
test_fmvs363.36 40261.82 40567.98 41962.51 45946.96 44077.37 39474.03 42645.24 44467.50 37778.79 41512.16 46472.98 44872.77 20466.02 41583.99 398
dmvs_testset62.63 40364.11 39458.19 43378.55 41524.76 47175.28 40765.94 44867.91 29960.34 42776.01 43053.56 28173.94 44631.79 45167.65 40975.88 440
mvsany_test162.30 40461.26 40865.41 42569.52 44954.86 39266.86 44349.78 46546.65 44268.50 37083.21 36149.15 33966.28 45756.93 35960.77 43075.11 441
new-patchmatchnet61.73 40561.73 40661.70 42972.74 44524.50 47269.16 43678.03 40161.40 37956.72 44075.53 43438.42 41676.48 42745.95 42457.67 43584.13 396
PVSNet_057.27 2061.67 40659.27 40968.85 41379.61 40757.44 35668.01 43973.44 42855.93 42258.54 43470.41 44544.58 37877.55 42047.01 41735.91 45771.55 445
test_vis1_rt60.28 40758.42 41065.84 42467.25 45355.60 38470.44 43160.94 45744.33 44659.00 43266.64 44724.91 44768.67 45462.80 29769.48 40173.25 443
ttmdpeth59.91 40857.10 41268.34 41767.13 45446.65 44174.64 41467.41 44448.30 44062.52 42185.04 32320.40 45475.93 43342.55 43545.90 45582.44 415
MVS-HIRNet59.14 40957.67 41163.57 42781.65 37643.50 45171.73 42365.06 45039.59 45251.43 44757.73 45538.34 41782.58 39539.53 44073.95 37264.62 451
pmmvs357.79 41054.26 41568.37 41664.02 45856.72 36575.12 41165.17 44940.20 45052.93 44669.86 44620.36 45575.48 43745.45 42755.25 44372.90 444
DSMNet-mixed57.77 41156.90 41360.38 43167.70 45235.61 46269.18 43553.97 46332.30 46157.49 43879.88 40340.39 40768.57 45538.78 44372.37 38576.97 437
MVStest156.63 41252.76 41868.25 41861.67 46053.25 40871.67 42468.90 44238.59 45350.59 44983.05 36425.08 44670.66 45036.76 44638.56 45680.83 427
WB-MVS54.94 41354.72 41455.60 43973.50 43820.90 47374.27 41761.19 45659.16 39850.61 44874.15 43647.19 35175.78 43517.31 46435.07 45870.12 446
LCM-MVSNet54.25 41449.68 42467.97 42053.73 46845.28 44566.85 44480.78 37035.96 45739.45 45862.23 4518.70 46878.06 41848.24 41251.20 44880.57 429
mvsany_test353.99 41551.45 42061.61 43055.51 46444.74 44963.52 45445.41 46943.69 44758.11 43676.45 42817.99 45763.76 46054.77 37247.59 45176.34 439
SSC-MVS53.88 41653.59 41654.75 44172.87 44419.59 47473.84 41960.53 45857.58 41449.18 45273.45 43946.34 36275.47 43816.20 46732.28 46069.20 447
FPMVS53.68 41751.64 41959.81 43265.08 45651.03 42369.48 43469.58 43841.46 44940.67 45672.32 44116.46 46070.00 45324.24 46065.42 41758.40 456
APD_test153.31 41849.93 42363.42 42865.68 45550.13 42871.59 42566.90 44634.43 45840.58 45771.56 4438.65 46976.27 42934.64 44955.36 44163.86 452
N_pmnet52.79 41953.26 41751.40 44378.99 4137.68 47769.52 4333.89 47651.63 43557.01 43974.98 43540.83 40465.96 45837.78 44464.67 41980.56 430
test_f52.09 42050.82 42155.90 43753.82 46742.31 45659.42 45758.31 46136.45 45656.12 44370.96 44412.18 46357.79 46353.51 37956.57 43867.60 448
EGC-MVSNET52.07 42147.05 42567.14 42183.51 33760.71 31480.50 35067.75 4430.07 4710.43 47275.85 43324.26 44981.54 40128.82 45462.25 42659.16 454
new_pmnet50.91 42250.29 42252.78 44268.58 45134.94 46463.71 45356.63 46239.73 45144.95 45365.47 44821.93 45358.48 46234.98 44856.62 43764.92 450
ANet_high50.57 42346.10 42763.99 42648.67 47139.13 45970.99 42880.85 36961.39 38031.18 46057.70 45617.02 45973.65 44731.22 45315.89 46879.18 433
test_vis3_rt49.26 42447.02 42656.00 43654.30 46545.27 44666.76 44548.08 46636.83 45544.38 45453.20 4597.17 47164.07 45956.77 36255.66 43958.65 455
testf145.72 42541.96 42957.00 43456.90 46245.32 44366.14 44659.26 45926.19 46230.89 46160.96 4534.14 47270.64 45126.39 45846.73 45355.04 457
APD_test245.72 42541.96 42957.00 43456.90 46245.32 44366.14 44659.26 45926.19 46230.89 46160.96 4534.14 47270.64 45126.39 45846.73 45355.04 457
dongtai45.42 42745.38 42845.55 44573.36 44126.85 46967.72 44034.19 47154.15 42749.65 45156.41 45825.43 44562.94 46119.45 46228.09 46246.86 461
Gipumacopyleft45.18 42841.86 43155.16 44077.03 42251.52 41932.50 46480.52 37532.46 46027.12 46335.02 4649.52 46775.50 43622.31 46160.21 43338.45 463
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
PMVScopyleft37.38 2244.16 42940.28 43355.82 43840.82 47342.54 45565.12 45063.99 45334.43 45824.48 46457.12 4573.92 47476.17 43117.10 46555.52 44048.75 459
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PMMVS240.82 43038.86 43446.69 44453.84 46616.45 47548.61 46149.92 46437.49 45431.67 45960.97 4528.14 47056.42 46428.42 45530.72 46167.19 449
kuosan39.70 43140.40 43237.58 44864.52 45726.98 46765.62 44833.02 47246.12 44342.79 45548.99 46124.10 45046.56 46912.16 47026.30 46339.20 462
E-PMN31.77 43230.64 43535.15 44952.87 46927.67 46657.09 45947.86 46724.64 46416.40 46933.05 46511.23 46554.90 46514.46 46818.15 46622.87 465
test_method31.52 43329.28 43738.23 44727.03 4756.50 47820.94 46662.21 4554.05 46922.35 46752.50 46013.33 46147.58 46727.04 45734.04 45960.62 453
EMVS30.81 43429.65 43634.27 45050.96 47025.95 47056.58 46046.80 46824.01 46515.53 47030.68 46612.47 46254.43 46612.81 46917.05 46722.43 466
MVEpermissive26.22 2330.37 43525.89 43943.81 44644.55 47235.46 46328.87 46539.07 47018.20 46618.58 46840.18 4632.68 47547.37 46817.07 46623.78 46548.60 460
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
cdsmvs_eth3d_5k19.96 43626.61 4380.00 4560.00 4790.00 4810.00 46789.26 2090.00 4740.00 47588.61 22061.62 1950.00 4750.00 4740.00 4730.00 471
tmp_tt18.61 43721.40 44010.23 4534.82 47610.11 47634.70 46330.74 4741.48 47023.91 46626.07 46728.42 44213.41 47227.12 45615.35 4697.17 467
wuyk23d16.82 43815.94 44119.46 45258.74 46131.45 46539.22 4623.74 4776.84 4686.04 4712.70 4711.27 47624.29 47110.54 47114.40 4702.63 468
ab-mvs-re7.23 4399.64 4420.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 47586.72 2730.00 4790.00 4750.00 4740.00 4730.00 471
test1236.12 4408.11 4430.14 4540.06 4780.09 47971.05 4270.03 4790.04 4730.25 4741.30 4730.05 4770.03 4740.21 4730.01 4720.29 469
testmvs6.04 4418.02 4440.10 4550.08 4770.03 48069.74 4320.04 4780.05 4720.31 4731.68 4720.02 4780.04 4730.24 4720.02 4710.25 470
pcd_1.5k_mvsjas5.26 4427.02 4450.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 4750.00 47463.15 1670.00 4750.00 4740.00 4730.00 471
mmdepth0.00 4430.00 4460.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 4750.00 4740.00 4790.00 4750.00 4740.00 4730.00 471
monomultidepth0.00 4430.00 4460.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 4750.00 4740.00 4790.00 4750.00 4740.00 4730.00 471
test_blank0.00 4430.00 4460.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 4750.00 4740.00 4790.00 4750.00 4740.00 4730.00 471
uanet_test0.00 4430.00 4460.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 4750.00 4740.00 4790.00 4750.00 4740.00 4730.00 471
DCPMVS0.00 4430.00 4460.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 4750.00 4740.00 4790.00 4750.00 4740.00 4730.00 471
sosnet-low-res0.00 4430.00 4460.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 4750.00 4740.00 4790.00 4750.00 4740.00 4730.00 471
sosnet0.00 4430.00 4460.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 4750.00 4740.00 4790.00 4750.00 4740.00 4730.00 471
uncertanet0.00 4430.00 4460.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 4750.00 4740.00 4790.00 4750.00 4740.00 4730.00 471
Regformer0.00 4430.00 4460.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 4750.00 4740.00 4790.00 4750.00 4740.00 4730.00 471
uanet0.00 4430.00 4460.00 4560.00 4790.00 4810.00 4670.00 4800.00 4740.00 4750.00 4740.00 4790.00 4750.00 4740.00 4730.00 471
WAC-MVS42.58 45339.46 441
FOURS195.00 1072.39 4195.06 193.84 1674.49 14091.30 15
MSC_two_6792asdad89.16 194.34 2775.53 292.99 5097.53 289.67 1596.44 994.41 45
PC_three_145268.21 29692.02 1294.00 5882.09 595.98 5784.58 6696.68 294.95 12
No_MVS89.16 194.34 2775.53 292.99 5097.53 289.67 1596.44 994.41 45
test_one_060195.07 771.46 5994.14 678.27 4192.05 1195.74 680.83 11
eth-test20.00 479
eth-test0.00 479
ZD-MVS94.38 2572.22 4692.67 6870.98 22587.75 4694.07 5374.01 3396.70 2784.66 6594.84 44
RE-MVS-def85.48 7193.06 6070.63 7891.88 3992.27 8573.53 16885.69 6894.45 3363.87 15782.75 8991.87 9092.50 152
IU-MVS95.30 271.25 6192.95 5666.81 30892.39 688.94 2796.63 494.85 21
OPU-MVS89.06 394.62 1575.42 493.57 894.02 5682.45 396.87 2083.77 7796.48 894.88 16
test_241102_TWO94.06 1177.24 6092.78 495.72 881.26 897.44 789.07 2496.58 694.26 56
test_241102_ONE95.30 270.98 6894.06 1177.17 6393.10 195.39 1682.99 197.27 12
9.1488.26 1692.84 6591.52 5194.75 173.93 15688.57 3194.67 2675.57 2295.79 5986.77 4795.76 23
save fliter93.80 4072.35 4490.47 6991.17 13674.31 145
test_0728_THIRD78.38 3892.12 995.78 481.46 797.40 989.42 1996.57 794.67 30
test_0728_SECOND87.71 3295.34 171.43 6093.49 1094.23 397.49 489.08 2296.41 1294.21 57
test072695.27 571.25 6193.60 794.11 777.33 5792.81 395.79 380.98 9
GSMVS88.96 294
test_part295.06 872.65 3291.80 13
sam_mvs151.32 31088.96 294
sam_mvs50.01 326
ambc75.24 36173.16 44250.51 42763.05 45687.47 26864.28 40977.81 42217.80 45889.73 31157.88 34960.64 43185.49 375
MTGPAbinary92.02 99
test_post178.90 3755.43 47048.81 34585.44 37259.25 333
test_post5.46 46950.36 32284.24 381
patchmatchnet-post74.00 43751.12 31388.60 334
GG-mvs-BLEND75.38 35981.59 37855.80 38179.32 36669.63 43767.19 38273.67 43843.24 38788.90 33050.41 39484.50 22081.45 423
MTMP92.18 3532.83 473
gm-plane-assit81.40 38253.83 40162.72 36880.94 39092.39 22663.40 294
test9_res84.90 5995.70 2692.87 137
TEST993.26 5272.96 2588.75 13291.89 10768.44 29385.00 7593.10 8374.36 2995.41 76
test_893.13 5672.57 3588.68 13791.84 11168.69 28884.87 7993.10 8374.43 2795.16 86
agg_prior282.91 8695.45 2992.70 142
agg_prior92.85 6471.94 5291.78 11584.41 9094.93 97
TestCases79.58 29485.15 29763.62 25679.83 38662.31 37160.32 42886.73 27132.02 43488.96 32850.28 39771.57 39386.15 363
test_prior472.60 3489.01 119
test_prior288.85 12675.41 11184.91 7793.54 7174.28 3083.31 8095.86 20
test_prior86.33 6092.61 7069.59 9492.97 5595.48 7093.91 73
旧先验286.56 21858.10 40987.04 5788.98 32674.07 189
新几何286.29 229
新几何183.42 17893.13 5670.71 7685.48 30657.43 41581.80 13791.98 11063.28 16192.27 23264.60 28692.99 7287.27 339
旧先验191.96 7665.79 20286.37 29393.08 8769.31 9192.74 7688.74 305
无先验87.48 17988.98 22460.00 39094.12 13567.28 26388.97 293
原ACMM286.86 205
原ACMM184.35 12793.01 6268.79 11392.44 7863.96 35381.09 14991.57 12766.06 13795.45 7167.19 26594.82 4688.81 300
test22291.50 8268.26 13384.16 29083.20 34154.63 42679.74 17091.63 12358.97 23191.42 9886.77 353
testdata291.01 28862.37 304
segment_acmp73.08 40
testdata79.97 28490.90 9464.21 24484.71 31459.27 39785.40 7092.91 8962.02 18889.08 32468.95 24891.37 10086.63 357
testdata184.14 29175.71 102
test1286.80 5492.63 6970.70 7791.79 11482.71 12471.67 5996.16 4894.50 5393.54 102
plane_prior790.08 11268.51 127
plane_prior689.84 12168.70 12160.42 221
plane_prior592.44 7895.38 7878.71 13186.32 18891.33 197
plane_prior491.00 150
plane_prior368.60 12478.44 3678.92 185
plane_prior291.25 5579.12 28
plane_prior189.90 120
plane_prior68.71 11990.38 7377.62 4786.16 193
n20.00 480
nn0.00 480
door-mid69.98 436
lessismore_v078.97 30481.01 38957.15 35965.99 44761.16 42482.82 37039.12 41291.34 27559.67 32946.92 45288.43 313
LGP-MVS_train84.50 12089.23 14868.76 11591.94 10575.37 11376.64 24191.51 12954.29 27394.91 9878.44 13383.78 23389.83 265
test1192.23 88
door69.44 439
HQP5-MVS66.98 178
HQP-NCC89.33 14089.17 11076.41 8577.23 226
ACMP_Plane89.33 14089.17 11076.41 8577.23 226
BP-MVS77.47 146
HQP4-MVS77.24 22595.11 9091.03 207
HQP3-MVS92.19 9385.99 197
HQP2-MVS60.17 224
NP-MVS89.62 12568.32 13190.24 170
MDTV_nov1_ep13_2view37.79 46175.16 40955.10 42466.53 39249.34 33653.98 37687.94 322
MDTV_nov1_ep1369.97 34983.18 34653.48 40377.10 39780.18 38560.45 38569.33 36280.44 39448.89 34486.90 35351.60 38878.51 305
ACMMP++_ref81.95 266
ACMMP++81.25 271
Test By Simon64.33 153
ITE_SJBPF78.22 32081.77 37560.57 31683.30 33669.25 27367.54 37687.20 26236.33 42687.28 35154.34 37474.62 36786.80 352
DeepMVS_CXcopyleft27.40 45140.17 47426.90 46824.59 47517.44 46723.95 46548.61 4629.77 46626.48 47018.06 46324.47 46428.83 464