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.
sorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
DeepPCF-MVS80.84 188.10 1688.56 1786.73 5992.24 7769.03 11089.57 9993.39 3577.53 5389.79 2594.12 5678.98 1496.58 3985.66 5895.72 2894.58 47
DeepC-MVS79.81 287.08 4086.88 4587.69 3691.16 9172.32 4590.31 7993.94 1977.12 6782.82 13594.23 5072.13 5697.09 1984.83 6795.37 3593.65 106
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 4186.62 5087.76 2993.52 5072.37 4391.26 5993.04 4676.62 8384.22 10093.36 8471.44 6696.76 2980.82 11395.33 3794.16 72
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
3Dnovator+77.84 485.48 7384.47 9288.51 791.08 9373.49 1693.18 1693.78 2380.79 876.66 25493.37 8360.40 23696.75 3077.20 16293.73 7095.29 6
3Dnovator76.31 583.38 12382.31 13786.59 6187.94 20872.94 2890.64 6892.14 11077.21 6375.47 28092.83 9758.56 24894.72 11573.24 21392.71 8192.13 188
ACMP74.13 681.51 16680.57 16684.36 13889.42 13968.69 12689.97 8591.50 14274.46 15475.04 30290.41 17853.82 29394.54 12177.56 15882.91 26789.86 278
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PCF-MVS73.52 780.38 19778.84 21585.01 10587.71 22468.99 11383.65 31791.46 14363.00 38177.77 22990.28 18266.10 14895.09 9861.40 33488.22 16690.94 226
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
ACMM73.20 880.78 18579.84 18783.58 18789.31 14768.37 13489.99 8491.60 13670.28 26177.25 23889.66 20053.37 29893.53 17474.24 20282.85 26888.85 312
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TAPA-MVS73.13 979.15 22877.94 23482.79 22889.59 13062.99 29588.16 16591.51 13965.77 34277.14 24691.09 15760.91 22493.21 19750.26 41987.05 19092.17 186
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
OpenMVScopyleft72.83 1079.77 21078.33 22684.09 15985.17 30969.91 9390.57 6990.97 15566.70 32772.17 34491.91 12154.70 28493.96 14461.81 33190.95 11288.41 328
PLCcopyleft70.83 1178.05 25876.37 28083.08 20991.88 8367.80 15688.19 16389.46 20964.33 36569.87 37188.38 24153.66 29493.58 16658.86 35882.73 27087.86 339
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
HY-MVS69.67 1277.95 26177.15 25980.36 28987.57 24060.21 34283.37 32687.78 27766.11 33775.37 28787.06 28263.27 17590.48 31761.38 33582.43 27490.40 249
LTVRE_ROB69.57 1376.25 29974.54 30881.41 26188.60 17964.38 25679.24 38889.12 23370.76 24569.79 37387.86 25749.09 35793.20 20056.21 38680.16 30186.65 376
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
ACMH+68.96 1476.01 30374.01 31482.03 24888.60 17965.31 22488.86 13087.55 28170.25 26367.75 39387.47 26941.27 41993.19 20258.37 36475.94 35987.60 344
IB-MVS68.01 1575.85 30573.36 32583.31 19684.76 32166.03 19783.38 32585.06 33170.21 26469.40 37581.05 40345.76 38794.66 11865.10 29675.49 36589.25 296
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
ACMH67.68 1675.89 30473.93 31681.77 25388.71 17666.61 18988.62 14589.01 23769.81 27266.78 40786.70 29141.95 41691.51 28255.64 38778.14 32787.17 360
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
COLMAP_ROBcopyleft66.92 1773.01 34670.41 36380.81 28087.13 25465.63 21188.30 16084.19 34462.96 38263.80 43587.69 26138.04 43892.56 23146.66 43874.91 37984.24 414
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
PVSNet64.34 1872.08 36070.87 35775.69 37286.21 28256.44 39074.37 43780.73 39162.06 39570.17 36482.23 39442.86 40883.31 41054.77 39284.45 23887.32 355
OpenMVS_ROBcopyleft64.09 1970.56 37368.19 37977.65 35380.26 41059.41 35185.01 27982.96 36758.76 42365.43 42182.33 39137.63 44091.23 29345.34 44876.03 35882.32 436
PVSNet_057.27 2061.67 42559.27 42868.85 43379.61 42257.44 37668.01 46073.44 44855.93 44258.54 45470.41 46544.58 39677.55 44047.01 43735.91 47771.55 465
CMPMVSbinary51.72 2170.19 37868.16 38076.28 36773.15 46357.55 37479.47 38583.92 34648.02 46156.48 46184.81 34043.13 40686.42 37962.67 31981.81 28284.89 407
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PMVScopyleft37.38 2244.16 44840.28 45255.82 45840.82 49342.54 47565.12 47163.99 47334.43 47824.48 48457.12 4773.92 49376.17 45117.10 48555.52 46048.75 479
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVEpermissive26.22 2330.37 45425.89 45843.81 46644.55 49235.46 48328.87 48639.07 49018.20 48618.58 48840.18 4832.68 49447.37 48817.07 48623.78 48548.60 480
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
E5new84.22 9284.12 9584.51 12787.60 23165.36 22087.45 19092.31 8976.51 8583.53 11692.26 10869.25 10293.50 17779.88 12588.26 16194.69 33
FE-blended-shiyan772.94 34870.66 35879.79 30677.80 43661.03 32781.31 35787.15 29565.18 35268.09 38976.28 44851.32 32590.97 30763.06 31365.76 43387.35 352
E6new84.22 9284.12 9584.52 12587.60 23165.36 22087.45 19092.30 9176.51 8583.53 11692.26 10869.26 10093.49 17979.88 12588.26 16194.69 33
blended_shiyan673.38 33671.17 35280.01 30078.36 43261.48 32182.43 34087.27 29065.40 35068.56 38477.55 44051.94 31791.01 30463.27 31065.76 43387.55 347
usedtu_blend_shiyan573.29 34170.96 35580.25 29377.80 43662.16 31084.44 29787.38 28664.41 36268.09 38976.28 44851.32 32591.23 29363.21 31165.76 43387.35 352
blend_shiyan472.29 35669.65 36880.21 29578.24 43462.16 31082.29 34287.27 29065.41 34968.43 38876.42 44739.91 42791.23 29363.21 31165.66 43687.22 358
E684.22 9284.12 9584.52 12587.60 23165.36 22087.45 19092.30 9176.51 8583.53 11692.26 10869.26 10093.49 17979.88 12588.26 16194.69 33
E584.22 9284.12 9584.51 12787.60 23165.36 22087.45 19092.31 8976.51 8583.53 11692.26 10869.25 10293.50 17779.88 12588.26 16194.69 33
FE-MVSNET376.43 29575.32 29779.76 30783.00 36660.72 33281.74 34888.76 25168.99 29972.98 33184.19 35556.41 27190.27 31862.39 32179.40 31188.31 329
E484.10 9883.99 10184.45 13287.58 23964.99 23486.54 23092.25 9676.38 9483.37 12192.09 11969.88 9093.58 16679.78 13088.03 17194.77 25
E3new83.78 10883.60 11184.31 14287.76 22164.89 24286.24 24492.20 10375.15 13582.87 13291.23 14970.11 8493.52 17679.05 13687.79 17594.51 55
FE-MVSNET272.88 35071.28 34977.67 35178.30 43357.78 37084.43 29888.92 24369.56 27964.61 42781.67 39946.73 37588.54 35559.33 35167.99 42486.69 375
fmvsm_s_conf0.5_n_1186.06 5686.75 4784.00 17287.78 21866.09 19689.96 8690.80 16277.37 5786.72 6594.20 5272.51 5192.78 22489.08 2292.33 8793.13 137
E284.00 10183.87 10284.39 13587.70 22664.95 23586.40 23792.23 9775.85 10883.21 12391.78 12770.09 8593.55 17179.52 13388.05 16994.66 41
MED-MVS test87.86 2694.57 1771.43 6093.28 1294.36 375.24 12692.25 995.03 2097.39 1188.15 3995.96 1994.75 30
MED-MVS89.59 490.16 487.86 2694.57 1771.43 6093.28 1294.36 376.30 9892.25 995.03 2081.59 797.39 1188.15 3995.96 1994.75 30
E384.00 10183.87 10284.39 13587.70 22664.95 23586.40 23792.23 9775.85 10883.21 12391.78 12770.09 8593.55 17179.52 13388.05 16994.66 41
TestfortrainingZip a89.27 789.82 787.60 3994.57 1770.90 7793.28 1294.36 375.24 12692.25 995.03 2081.59 797.39 1186.12 5795.96 1994.52 54
TestfortrainingZip93.28 12
fmvsm_s_conf0.5_n_1086.38 5286.76 4685.24 9587.33 24667.30 17489.50 10190.98 15476.25 10190.56 2294.75 2968.38 11794.24 13590.80 792.32 8994.19 71
viewdifsd2359ckpt0782.83 13782.78 12982.99 21486.51 27762.58 29985.09 27790.83 16175.22 12882.28 14091.63 13569.43 9692.03 25377.71 15686.32 20294.34 64
viewdifsd2359ckpt0983.34 12482.55 13285.70 8187.64 23067.72 15988.43 15191.68 13171.91 21681.65 15490.68 17067.10 13494.75 11376.17 17787.70 17894.62 46
viewdifsd2359ckpt1382.91 13582.29 13884.77 11886.96 26366.90 18787.47 18791.62 13472.19 20981.68 15390.71 16966.92 13593.28 19075.90 18287.15 18894.12 75
viewcassd2359sk1183.89 10383.74 10784.34 14087.76 22164.91 24186.30 24192.22 10075.47 11983.04 12991.52 14070.15 8393.53 17479.26 13587.96 17294.57 49
viewdifsd2359ckpt1180.37 19979.73 19082.30 24283.70 34662.39 30384.20 30586.67 30573.22 19380.90 16790.62 17263.00 18591.56 27576.81 17178.44 32192.95 149
viewmacassd2359aftdt83.76 10983.66 11084.07 16186.59 27564.56 24786.88 21591.82 12475.72 11183.34 12292.15 11768.24 12192.88 21879.05 13689.15 14594.77 25
viewmsd2359difaftdt80.37 19979.73 19082.30 24283.70 34662.39 30384.20 30586.67 30573.22 19380.90 16790.62 17263.00 18591.56 27576.81 17178.44 32192.95 149
diffmvs_AUTHOR82.38 14382.27 13982.73 23383.26 35663.80 26783.89 31189.76 19773.35 18782.37 13990.84 16666.25 14590.79 31082.77 9387.93 17393.59 111
FE-MVSNET67.25 40365.33 40773.02 40675.86 44552.54 43080.26 37780.56 39463.80 37560.39 44679.70 42241.41 41884.66 40043.34 45262.62 44581.86 440
fmvsm_l_conf0.5_n_985.84 6686.63 4983.46 19087.12 25966.01 19988.56 14889.43 21075.59 11689.32 2894.32 4472.89 4691.21 29690.11 1192.33 8793.16 133
mamba_040879.37 22477.52 25184.93 11088.81 16767.96 14965.03 47288.66 25470.96 24079.48 18989.80 19458.69 24594.65 11970.35 24585.93 21392.18 183
icg_test_0407_278.92 23678.93 21378.90 32587.13 25463.59 27476.58 41989.33 21470.51 25277.82 22589.03 21961.84 20281.38 42372.56 22285.56 22091.74 196
SSM_0407277.67 27177.52 25178.12 34288.81 16767.96 14965.03 47288.66 25470.96 24079.48 18989.80 19458.69 24574.23 46470.35 24585.93 21392.18 183
SSM_040781.58 16180.48 16984.87 11388.81 16767.96 14987.37 19689.25 22471.06 23679.48 18990.39 17959.57 23994.48 12672.45 22685.93 21392.18 183
viewmambaseed2359dif80.41 19579.84 18782.12 24482.95 37162.50 30283.39 32488.06 26767.11 32280.98 16590.31 18166.20 14791.01 30474.62 19684.90 22892.86 152
IMVS_040780.61 18879.90 18582.75 23287.13 25463.59 27485.33 27089.33 21470.51 25277.82 22589.03 21961.84 20292.91 21672.56 22285.56 22091.74 196
viewmanbaseed2359cas83.66 11283.55 11284.00 17286.81 26764.53 24886.65 22591.75 12974.89 14283.15 12891.68 13168.74 11392.83 22279.02 13889.24 14294.63 44
IMVS_040477.16 28076.42 27879.37 31687.13 25463.59 27477.12 41789.33 21470.51 25266.22 41789.03 21950.36 33982.78 41372.56 22285.56 22091.74 196
SSM_040481.91 15180.84 16285.13 10189.24 15168.26 13787.84 17989.25 22471.06 23680.62 17390.39 17959.57 23994.65 11972.45 22687.19 18792.47 169
IMVS_040380.80 18180.12 18082.87 22187.13 25463.59 27485.19 27189.33 21470.51 25278.49 20989.03 21963.26 17693.27 19272.56 22285.56 22091.74 196
SD_040374.65 32074.77 30474.29 39286.20 28347.42 45683.71 31585.12 32969.30 28568.50 38687.95 25659.40 24186.05 38249.38 42383.35 26189.40 291
fmvsm_s_conf0.5_n_987.39 3387.95 2385.70 8189.48 13767.88 15388.59 14689.05 23480.19 1290.70 2095.40 1574.56 2893.92 15191.54 292.07 9295.31 5
ME-MVS88.98 1289.39 987.75 3094.54 2071.43 6091.61 4994.25 676.30 9890.62 2195.03 2078.06 1697.07 2088.15 3995.96 1994.75 30
NormalMVS86.29 5485.88 6587.52 4193.26 5672.47 3891.65 4792.19 10579.31 2484.39 9692.18 11364.64 16495.53 7180.70 11694.65 5294.56 51
lecture88.09 1788.59 1686.58 6293.26 5669.77 9693.70 694.16 977.13 6689.76 2695.52 1472.26 5396.27 4886.87 5094.65 5293.70 101
SymmetryMVS85.38 7884.81 8687.07 5091.47 8772.47 3891.65 4788.06 26779.31 2484.39 9692.18 11364.64 16495.53 7180.70 11690.91 11393.21 129
Elysia81.53 16280.16 17785.62 8485.51 30068.25 13988.84 13392.19 10571.31 22780.50 17589.83 19246.89 37194.82 10876.85 16789.57 13693.80 96
StellarMVS81.53 16280.16 17785.62 8485.51 30068.25 13988.84 13392.19 10571.31 22780.50 17589.83 19246.89 37194.82 10876.85 16789.57 13693.80 96
KinetiMVS83.31 12782.61 13185.39 9187.08 26067.56 16588.06 16891.65 13277.80 4482.21 14391.79 12657.27 26194.07 14277.77 15589.89 13294.56 51
LuminaMVS80.68 18679.62 19583.83 17985.07 31568.01 14886.99 20988.83 24470.36 25781.38 15787.99 25550.11 34292.51 23579.02 13886.89 19490.97 224
VortexMVS78.57 24577.89 23780.59 28485.89 29062.76 29885.61 25989.62 20472.06 21374.99 30385.38 32655.94 27390.77 31374.99 19376.58 34688.23 331
AstraMVS80.81 17880.14 17982.80 22586.05 28963.96 26286.46 23385.90 32173.71 17480.85 17090.56 17554.06 29191.57 27479.72 13183.97 24592.86 152
guyue81.13 17180.64 16582.60 23686.52 27663.92 26586.69 22487.73 27873.97 16680.83 17189.69 19856.70 26791.33 29078.26 15385.40 22492.54 163
sc_t172.19 35869.51 36980.23 29484.81 31961.09 32584.68 28680.22 40360.70 40471.27 35383.58 37036.59 44389.24 33960.41 34163.31 44390.37 250
tt0320-xc70.11 37967.45 39678.07 34485.33 30659.51 35083.28 32778.96 41658.77 42267.10 40380.28 41436.73 44287.42 36956.83 38159.77 45487.29 356
tt032070.49 37568.03 38377.89 34684.78 32059.12 35283.55 32180.44 39858.13 42867.43 39980.41 41239.26 43087.54 36855.12 38963.18 44486.99 367
fmvsm_s_conf0.5_n_886.56 4787.17 3884.73 12087.76 22165.62 21289.20 11492.21 10279.94 1789.74 2794.86 2668.63 11494.20 13690.83 591.39 10494.38 61
fmvsm_s_conf0.5_n_783.34 12484.03 10081.28 26685.73 29465.13 22885.40 26989.90 19374.96 14082.13 14493.89 6966.65 13787.92 36286.56 5391.05 10990.80 229
fmvsm_s_conf0.5_n_685.55 7286.20 5683.60 18587.32 24865.13 22888.86 13091.63 13375.41 12188.23 4093.45 8168.56 11592.47 23689.52 1892.78 7993.20 131
fmvsm_s_conf0.5_n_585.22 8185.55 7384.25 15186.26 28067.40 17089.18 11589.31 21972.50 20388.31 3793.86 7069.66 9391.96 25789.81 1391.05 10993.38 119
fmvsm_s_conf0.5_n_485.39 7785.75 7084.30 14486.70 27165.83 20588.77 13689.78 19575.46 12088.35 3693.73 7469.19 10493.06 21091.30 388.44 15994.02 81
SSC-MVS3.273.35 34073.39 32373.23 40185.30 30749.01 45274.58 43681.57 38275.21 13073.68 32285.58 32152.53 30182.05 41854.33 39577.69 33388.63 322
testing3-275.12 31775.19 29974.91 38490.40 10945.09 46780.29 37578.42 41978.37 4076.54 25987.75 25844.36 39887.28 37157.04 37783.49 25892.37 172
myMVS_eth3d2873.62 33273.53 32273.90 39788.20 19347.41 45778.06 40879.37 41174.29 16073.98 31884.29 35044.67 39483.54 40751.47 40987.39 18390.74 234
UWE-MVS-2865.32 41464.93 40866.49 44378.70 42938.55 48077.86 41264.39 47262.00 39664.13 43183.60 36941.44 41776.00 45231.39 47280.89 29084.92 406
fmvsm_l_conf0.5_n_386.02 5786.32 5385.14 9887.20 25168.54 13089.57 9990.44 17275.31 12587.49 5494.39 4272.86 4792.72 22589.04 2790.56 11894.16 72
fmvsm_s_conf0.5_n_386.36 5387.46 3283.09 20787.08 26065.21 22589.09 12390.21 18379.67 1989.98 2495.02 2473.17 4291.71 26991.30 391.60 9992.34 173
fmvsm_s_conf0.5_n_284.04 9984.11 9983.81 18186.17 28465.00 23386.96 21087.28 28874.35 15688.25 3994.23 5061.82 20492.60 22889.85 1288.09 16893.84 92
fmvsm_s_conf0.1_n_283.80 10683.79 10683.83 17985.62 29764.94 23887.03 20786.62 30974.32 15787.97 4794.33 4360.67 22892.60 22889.72 1487.79 17593.96 83
GDP-MVS83.52 11882.64 13086.16 6988.14 19768.45 13289.13 12192.69 7072.82 20283.71 11191.86 12555.69 27495.35 8680.03 12289.74 13494.69 33
BP-MVS184.32 9183.71 10886.17 6887.84 21367.85 15489.38 10989.64 20377.73 4583.98 10692.12 11856.89 26695.43 7784.03 8091.75 9895.24 7
reproduce_monomvs75.40 31374.38 31178.46 33783.92 34057.80 36983.78 31386.94 30073.47 18372.25 34384.47 34438.74 43389.27 33875.32 19170.53 41388.31 329
mmtdpeth74.16 32573.01 32977.60 35683.72 34561.13 32385.10 27685.10 33072.06 21377.21 24480.33 41343.84 40285.75 38577.14 16452.61 46685.91 390
reproduce_model87.28 3587.39 3386.95 5493.10 6271.24 6891.60 5093.19 4074.69 14888.80 3395.61 1170.29 8196.44 4386.20 5693.08 7593.16 133
reproduce-ours87.47 2787.61 2787.07 5093.27 5471.60 5591.56 5493.19 4074.98 13888.96 3095.54 1271.20 7096.54 4086.28 5493.49 7193.06 140
our_new_method87.47 2787.61 2787.07 5093.27 5471.60 5591.56 5493.19 4074.98 13888.96 3095.54 1271.20 7096.54 4086.28 5493.49 7193.06 140
mmdepth0.00 4620.00 4650.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 4950.00 4940.00 4980.00 4950.00 4940.00 4930.00 491
monomultidepth0.00 4620.00 4650.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 4950.00 4940.00 4980.00 4950.00 4940.00 4930.00 491
mvs5depth69.45 38567.45 39675.46 37873.93 45455.83 40079.19 39083.23 35866.89 32371.63 35083.32 37433.69 45185.09 39459.81 34755.34 46285.46 396
MVStest156.63 43152.76 43768.25 43861.67 48053.25 42871.67 44568.90 46238.59 47350.59 46983.05 37925.08 46570.66 47036.76 46638.56 47680.83 447
ttmdpeth59.91 42757.10 43168.34 43767.13 47446.65 46174.64 43567.41 46448.30 46062.52 44185.04 33720.40 47375.93 45342.55 45545.90 47582.44 435
WBMVS73.43 33572.81 33175.28 38087.91 20950.99 44478.59 40181.31 38765.51 34874.47 31384.83 33946.39 37686.68 37558.41 36377.86 32988.17 334
dongtai45.42 44645.38 44745.55 46573.36 46126.85 48967.72 46134.19 49154.15 44749.65 47156.41 47825.43 46462.94 48119.45 48228.09 48246.86 481
kuosan39.70 45040.40 45137.58 46864.52 47726.98 48765.62 46933.02 49246.12 46342.79 47548.99 48124.10 46946.56 48912.16 49026.30 48339.20 482
MVSMamba_PlusPlus85.99 5985.96 6486.05 7391.09 9267.64 16189.63 9792.65 7572.89 20184.64 9091.71 13071.85 5896.03 5584.77 6994.45 6094.49 56
MGCFI-Net85.06 8585.51 7483.70 18389.42 13963.01 29189.43 10492.62 7876.43 8987.53 5391.34 14772.82 4993.42 18781.28 10888.74 15394.66 41
testing9176.54 28975.66 28879.18 32188.43 18655.89 39981.08 35983.00 36573.76 17375.34 28884.29 35046.20 38290.07 32364.33 30184.50 23491.58 203
testing1175.14 31674.01 31478.53 33488.16 19556.38 39280.74 36680.42 39970.67 24672.69 33783.72 36643.61 40489.86 32662.29 32483.76 24989.36 293
testing9976.09 30275.12 30179.00 32288.16 19555.50 40580.79 36381.40 38573.30 18975.17 29684.27 35344.48 39790.02 32464.28 30284.22 24391.48 208
UBG73.08 34572.27 33875.51 37688.02 20451.29 44278.35 40577.38 42865.52 34673.87 32082.36 39045.55 38986.48 37855.02 39084.39 24088.75 317
UWE-MVS72.13 35971.49 34474.03 39586.66 27347.70 45481.40 35676.89 43363.60 37675.59 27784.22 35439.94 42685.62 38848.98 42686.13 20888.77 316
ETVMVS72.25 35771.05 35375.84 37087.77 22051.91 43479.39 38674.98 44069.26 28773.71 32182.95 38140.82 42386.14 38146.17 44284.43 23989.47 289
sasdasda85.91 6385.87 6786.04 7489.84 12569.44 10590.45 7693.00 5176.70 8188.01 4591.23 14973.28 4093.91 15281.50 10588.80 15094.77 25
testing22274.04 32772.66 33378.19 34087.89 21055.36 40681.06 36079.20 41471.30 22974.65 31083.57 37139.11 43288.67 35251.43 41185.75 21890.53 243
WB-MVSnew71.96 36171.65 34372.89 40784.67 32651.88 43582.29 34277.57 42462.31 39173.67 32383.00 38053.49 29781.10 42545.75 44582.13 27785.70 393
fmvsm_l_conf0.5_n_a84.13 9784.16 9484.06 16485.38 30468.40 13388.34 15886.85 30367.48 32087.48 5593.40 8270.89 7391.61 27088.38 3789.22 14392.16 187
fmvsm_l_conf0.5_n84.47 9084.54 8984.27 14885.42 30368.81 11688.49 15087.26 29268.08 31388.03 4493.49 7772.04 5791.77 26588.90 2989.14 14692.24 180
fmvsm_s_conf0.1_n_a83.32 12682.99 12384.28 14683.79 34268.07 14589.34 11182.85 36969.80 27387.36 5894.06 5968.34 11991.56 27587.95 4283.46 26093.21 129
fmvsm_s_conf0.1_n83.56 11783.38 11684.10 15584.86 31867.28 17589.40 10883.01 36470.67 24687.08 6093.96 6768.38 11791.45 28588.56 3484.50 23493.56 113
fmvsm_s_conf0.5_n_a83.63 11583.41 11584.28 14686.14 28568.12 14389.43 10482.87 36870.27 26287.27 5993.80 7369.09 10591.58 27288.21 3883.65 25493.14 136
fmvsm_s_conf0.5_n83.80 10683.71 10884.07 16186.69 27267.31 17389.46 10383.07 36371.09 23486.96 6393.70 7569.02 11091.47 28488.79 3084.62 23393.44 118
MM89.16 889.23 1088.97 490.79 10273.65 1092.66 2891.17 14986.57 187.39 5794.97 2571.70 6297.68 192.19 195.63 3295.57 1
WAC-MVS42.58 47339.46 461
Syy-MVS68.05 39767.85 38668.67 43584.68 32340.97 47878.62 39973.08 44966.65 33166.74 40879.46 42352.11 31182.30 41632.89 47076.38 35482.75 433
test_fmvsmconf0.1_n85.61 7185.65 7185.50 8882.99 36969.39 10789.65 9590.29 18173.31 18887.77 4994.15 5571.72 6193.23 19590.31 990.67 11793.89 89
test_fmvsmconf0.01_n84.73 8984.52 9185.34 9280.25 41169.03 11089.47 10289.65 20273.24 19286.98 6294.27 4766.62 13893.23 19590.26 1089.95 13093.78 98
myMVS_eth3d67.02 40466.29 40469.21 43084.68 32342.58 47378.62 39973.08 44966.65 33166.74 40879.46 42331.53 45682.30 41639.43 46276.38 35482.75 433
testing368.56 39367.67 39271.22 42287.33 24642.87 47283.06 33571.54 45270.36 25769.08 37984.38 34730.33 45985.69 38737.50 46575.45 36985.09 405
SSC-MVS53.88 43553.59 43554.75 46172.87 46419.59 49473.84 44060.53 47857.58 43449.18 47273.45 45946.34 38075.47 45816.20 48732.28 48069.20 467
test_fmvsmconf_n85.92 6286.04 6385.57 8785.03 31669.51 10089.62 9890.58 16773.42 18487.75 5094.02 6172.85 4893.24 19490.37 890.75 11593.96 83
WB-MVS54.94 43254.72 43355.60 45973.50 45820.90 49374.27 43861.19 47659.16 41850.61 46874.15 45647.19 36875.78 45517.31 48435.07 47870.12 466
test_fmvsmvis_n_192084.02 10083.87 10284.49 13184.12 33469.37 10888.15 16687.96 27070.01 26783.95 10793.23 8668.80 11291.51 28288.61 3289.96 12992.57 161
dmvs_re71.14 36570.58 35972.80 40881.96 38759.68 34675.60 42779.34 41268.55 30669.27 37880.72 40949.42 35176.54 44552.56 40477.79 33082.19 438
SDMVSNet80.38 19780.18 17680.99 27589.03 16164.94 23880.45 37289.40 21175.19 13276.61 25789.98 18860.61 23187.69 36676.83 17083.55 25690.33 252
dmvs_testset62.63 42264.11 41358.19 45378.55 43024.76 49175.28 42865.94 46867.91 31560.34 44776.01 45053.56 29573.94 46631.79 47167.65 42575.88 460
sd_testset77.70 26977.40 25478.60 33089.03 16160.02 34379.00 39385.83 32275.19 13276.61 25789.98 18854.81 27985.46 39162.63 32083.55 25690.33 252
test_fmvsm_n_192085.29 8085.34 7785.13 10186.12 28669.93 9288.65 14490.78 16369.97 26988.27 3893.98 6671.39 6791.54 27988.49 3590.45 12093.91 86
test_cas_vis1_n_192073.76 33173.74 32073.81 39875.90 44459.77 34580.51 37082.40 37358.30 42681.62 15585.69 31644.35 39976.41 44876.29 17578.61 31785.23 400
test_vis1_n_192075.52 30975.78 28474.75 38879.84 41757.44 37683.26 32885.52 32562.83 38579.34 19486.17 30845.10 39379.71 43078.75 14381.21 28787.10 366
test_vis1_n69.85 38369.21 37271.77 41572.66 46655.27 40981.48 35376.21 43652.03 45375.30 29383.20 37728.97 46076.22 45074.60 19778.41 32583.81 420
test_fmvs1_n70.86 36970.24 36572.73 40972.51 46755.28 40881.27 35879.71 40851.49 45678.73 20184.87 33827.54 46277.02 44276.06 17979.97 30585.88 391
mvsany_test162.30 42361.26 42765.41 44569.52 46954.86 41266.86 46449.78 48546.65 46268.50 38683.21 37649.15 35666.28 47756.93 37960.77 45075.11 461
APD_test153.31 43749.93 44263.42 44865.68 47550.13 44871.59 44666.90 46634.43 47840.58 47771.56 4638.65 48876.27 44934.64 46955.36 46163.86 472
test_vis1_rt60.28 42658.42 42965.84 44467.25 47355.60 40470.44 45260.94 47744.33 46659.00 45266.64 46724.91 46668.67 47462.80 31569.48 41673.25 463
test_vis3_rt49.26 44347.02 44556.00 45654.30 48545.27 46666.76 46648.08 48636.83 47544.38 47453.20 4797.17 49064.07 47956.77 38255.66 45958.65 475
test_fmvs268.35 39667.48 39570.98 42469.50 47051.95 43380.05 37976.38 43549.33 45974.65 31084.38 34723.30 47175.40 45974.51 19875.17 37785.60 394
test_fmvs170.93 36870.52 36072.16 41373.71 45655.05 41080.82 36178.77 41751.21 45778.58 20684.41 34631.20 45776.94 44375.88 18380.12 30484.47 412
test_fmvs363.36 42161.82 42467.98 43962.51 47946.96 46077.37 41574.03 44645.24 46467.50 39678.79 43112.16 48372.98 46872.77 21866.02 43183.99 418
mvsany_test353.99 43451.45 43961.61 45055.51 48444.74 46963.52 47545.41 48943.69 46758.11 45676.45 44517.99 47663.76 48054.77 39247.59 47176.34 459
testf145.72 44441.96 44857.00 45456.90 48245.32 46366.14 46759.26 47926.19 48230.89 48160.96 4734.14 49170.64 47126.39 47846.73 47355.04 477
APD_test245.72 44441.96 44857.00 45456.90 48245.32 46366.14 46759.26 47926.19 48230.89 48160.96 4734.14 49170.64 47126.39 47846.73 47355.04 477
test_f52.09 43950.82 44055.90 45753.82 48742.31 47659.42 47858.31 48136.45 47656.12 46370.96 46412.18 48257.79 48353.51 39956.57 45867.60 468
FE-MVS77.78 26575.68 28684.08 16088.09 20166.00 20083.13 33187.79 27668.42 31078.01 22285.23 33045.50 39195.12 9259.11 35585.83 21791.11 217
FA-MVS(test-final)80.96 17479.91 18484.10 15588.30 19165.01 23284.55 29290.01 18973.25 19179.61 18687.57 26458.35 25094.72 11571.29 23586.25 20592.56 162
balanced_conf0386.78 4286.99 4086.15 7091.24 9067.61 16290.51 7092.90 6177.26 6087.44 5691.63 13571.27 6996.06 5485.62 6095.01 4194.78 24
MonoMVSNet76.49 29475.80 28378.58 33181.55 39458.45 35686.36 23986.22 31574.87 14574.73 30883.73 36551.79 32188.73 35070.78 23872.15 40388.55 325
patch_mono-283.65 11384.54 8980.99 27590.06 12065.83 20584.21 30488.74 25271.60 22285.01 7992.44 10574.51 2983.50 40882.15 10192.15 9093.64 108
EGC-MVSNET52.07 44047.05 44467.14 44183.51 35160.71 33380.50 37167.75 4630.07 4910.43 49275.85 45324.26 46881.54 42128.82 47462.25 44659.16 474
test250677.30 27876.49 27579.74 30890.08 11652.02 43187.86 17863.10 47474.88 14380.16 18192.79 10038.29 43792.35 24368.74 26592.50 8494.86 19
test111179.43 21979.18 20880.15 29789.99 12153.31 42687.33 19977.05 43175.04 13680.23 18092.77 10248.97 35992.33 24568.87 26392.40 8694.81 22
ECVR-MVScopyleft79.61 21279.26 20580.67 28390.08 11654.69 41387.89 17677.44 42774.88 14380.27 17892.79 10048.96 36092.45 23768.55 26692.50 8494.86 19
test_blank0.00 4620.00 4650.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 4950.00 4940.00 4980.00 4950.00 4940.00 4930.00 491
tt080578.73 23977.83 23981.43 26085.17 30960.30 34089.41 10790.90 15771.21 23177.17 24588.73 22946.38 37793.21 19772.57 22078.96 31690.79 230
DVP-MVS++90.23 191.01 187.89 2494.34 3171.25 6495.06 194.23 778.38 3892.78 495.74 682.45 397.49 489.42 1996.68 294.95 12
FOURS195.00 1072.39 4195.06 193.84 2074.49 15391.30 18
MSC_two_6792asdad89.16 194.34 3175.53 292.99 5497.53 289.67 1596.44 994.41 58
PC_three_145268.21 31292.02 1594.00 6382.09 595.98 6184.58 7196.68 294.95 12
No_MVS89.16 194.34 3175.53 292.99 5497.53 289.67 1596.44 994.41 58
test_one_060195.07 771.46 5994.14 1078.27 4192.05 1495.74 680.83 13
eth-test20.00 499
eth-test0.00 499
GeoE81.71 15681.01 15983.80 18289.51 13464.45 25488.97 12688.73 25371.27 23078.63 20589.76 19766.32 14493.20 20069.89 25286.02 21093.74 99
test_method31.52 45229.28 45638.23 46727.03 4956.50 49820.94 48762.21 4754.05 48922.35 48752.50 48013.33 48047.58 48727.04 47734.04 47960.62 473
Anonymous2024052168.80 39067.22 39973.55 39974.33 45254.11 41883.18 32985.61 32458.15 42761.68 44280.94 40630.71 45881.27 42457.00 37873.34 39685.28 399
h-mvs3383.15 12982.19 14086.02 7690.56 10570.85 7988.15 16689.16 22976.02 10584.67 8791.39 14661.54 20995.50 7382.71 9675.48 36691.72 200
hse-mvs281.72 15580.94 16084.07 16188.72 17567.68 16085.87 25487.26 29276.02 10584.67 8788.22 24761.54 20993.48 18282.71 9673.44 39491.06 219
CL-MVSNet_self_test72.37 35471.46 34575.09 38279.49 42453.53 42280.76 36585.01 33369.12 29370.51 35882.05 39657.92 25384.13 40252.27 40566.00 43287.60 344
KD-MVS_2432*160066.22 41163.89 41473.21 40275.47 45053.42 42470.76 45084.35 33964.10 36866.52 41278.52 43234.55 44984.98 39550.40 41550.33 46981.23 444
KD-MVS_self_test68.81 38967.59 39472.46 41274.29 45345.45 46277.93 41087.00 29863.12 37863.99 43378.99 43042.32 41184.77 39856.55 38464.09 44187.16 362
AUN-MVS79.21 22777.60 24984.05 16788.71 17667.61 16285.84 25687.26 29269.08 29477.23 24088.14 25253.20 30093.47 18375.50 18973.45 39391.06 219
ZD-MVS94.38 2972.22 4692.67 7270.98 23987.75 5094.07 5874.01 3696.70 3184.66 7094.84 48
SR-MVS-dyc-post85.77 6785.61 7286.23 6693.06 6470.63 8291.88 4392.27 9373.53 18185.69 7394.45 3765.00 16295.56 6882.75 9491.87 9592.50 166
RE-MVS-def85.48 7593.06 6470.63 8291.88 4392.27 9373.53 18185.69 7394.45 3763.87 17082.75 9491.87 9592.50 166
SED-MVS90.08 290.85 287.77 2895.30 270.98 7193.57 894.06 1577.24 6193.10 195.72 882.99 197.44 789.07 2596.63 494.88 16
IU-MVS95.30 271.25 6492.95 6066.81 32492.39 688.94 2896.63 494.85 21
OPU-MVS89.06 394.62 1575.42 493.57 894.02 6182.45 396.87 2483.77 8296.48 894.88 16
test_241102_TWO94.06 1577.24 6192.78 495.72 881.26 1097.44 789.07 2596.58 694.26 69
test_241102_ONE95.30 270.98 7194.06 1577.17 6493.10 195.39 1682.99 197.27 15
SF-MVS88.46 1588.74 1587.64 3892.78 7071.95 5192.40 2994.74 275.71 11289.16 2995.10 1875.65 2496.19 5187.07 4996.01 1794.79 23
cl2278.07 25777.01 26181.23 26882.37 38461.83 31683.55 32187.98 26968.96 30075.06 30183.87 35961.40 21491.88 26273.53 20776.39 35189.98 273
miper_ehance_all_eth78.59 24477.76 24481.08 27382.66 37761.56 31983.65 31789.15 23068.87 30175.55 27983.79 36366.49 14192.03 25373.25 21276.39 35189.64 285
miper_enhance_ethall77.87 26476.86 26580.92 27881.65 39161.38 32282.68 33788.98 23865.52 34675.47 28082.30 39265.76 15592.00 25672.95 21576.39 35189.39 292
ZNCC-MVS87.94 2287.85 2488.20 1294.39 2873.33 1993.03 1993.81 2276.81 7585.24 7794.32 4471.76 6096.93 2385.53 6195.79 2694.32 66
dcpmvs_285.63 7086.15 6084.06 16491.71 8464.94 23886.47 23291.87 12173.63 17686.60 6793.02 9376.57 1891.87 26383.36 8492.15 9095.35 3
cl____77.72 26776.76 26980.58 28582.49 38160.48 33783.09 33287.87 27369.22 28974.38 31585.22 33162.10 19991.53 28071.09 23675.41 37089.73 284
DIV-MVS_self_test77.72 26776.76 26980.58 28582.48 38260.48 33783.09 33287.86 27469.22 28974.38 31585.24 32962.10 19991.53 28071.09 23675.40 37189.74 283
eth_miper_zixun_eth77.92 26276.69 27281.61 25783.00 36661.98 31383.15 33089.20 22869.52 28174.86 30684.35 34961.76 20592.56 23171.50 23372.89 39890.28 255
9.1488.26 1992.84 6991.52 5694.75 173.93 16988.57 3594.67 3075.57 2595.79 6386.77 5195.76 27
uanet_test0.00 4620.00 4650.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 4950.00 4940.00 4980.00 4950.00 4940.00 4930.00 491
DCPMVS0.00 4620.00 4650.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 4950.00 4940.00 4980.00 4950.00 4940.00 4930.00 491
save fliter93.80 4472.35 4490.47 7491.17 14974.31 158
ET-MVSNet_ETH3D78.63 24276.63 27484.64 12286.73 27069.47 10285.01 27984.61 33669.54 28066.51 41486.59 29550.16 34191.75 26676.26 17684.24 24292.69 158
UniMVSNet_ETH3D79.10 23078.24 22881.70 25486.85 26560.24 34187.28 20188.79 24674.25 16176.84 24890.53 17749.48 35091.56 27567.98 27082.15 27693.29 124
EIA-MVS83.31 12782.80 12784.82 11589.59 13065.59 21388.21 16292.68 7174.66 15078.96 19786.42 30269.06 10795.26 8775.54 18890.09 12693.62 109
miper_refine_blended66.22 41163.89 41473.21 40275.47 45053.42 42470.76 45084.35 33964.10 36866.52 41278.52 43234.55 44984.98 39550.40 41550.33 46981.23 444
miper_lstm_enhance74.11 32673.11 32877.13 36280.11 41359.62 34772.23 44386.92 30266.76 32670.40 36082.92 38256.93 26582.92 41269.06 26172.63 39988.87 311
ETV-MVS84.90 8884.67 8885.59 8689.39 14268.66 12788.74 14092.64 7779.97 1684.10 10385.71 31569.32 9895.38 8280.82 11391.37 10592.72 155
CS-MVS86.69 4486.95 4285.90 7890.76 10367.57 16492.83 2293.30 3779.67 1984.57 9392.27 10771.47 6595.02 10084.24 7793.46 7395.13 9
D2MVS74.82 31873.21 32679.64 31279.81 41862.56 30180.34 37487.35 28764.37 36468.86 38082.66 38746.37 37890.10 32267.91 27181.24 28686.25 380
DVP-MVScopyleft89.60 390.35 387.33 4595.27 571.25 6493.49 1092.73 6977.33 5892.12 1295.78 480.98 1197.40 989.08 2296.41 1293.33 123
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
test_0728_THIRD78.38 3892.12 1295.78 481.46 997.40 989.42 1996.57 794.67 38
test_0728_SECOND87.71 3595.34 171.43 6093.49 1094.23 797.49 489.08 2296.41 1294.21 70
test072695.27 571.25 6493.60 794.11 1177.33 5892.81 395.79 380.98 11
SR-MVS86.73 4386.67 4886.91 5594.11 4172.11 4992.37 3392.56 8074.50 15286.84 6494.65 3167.31 13195.77 6484.80 6892.85 7892.84 154
DPM-MVS84.93 8684.29 9386.84 5690.20 11373.04 2387.12 20493.04 4669.80 27382.85 13491.22 15273.06 4496.02 5776.72 17494.63 5491.46 210
GST-MVS87.42 3187.26 3487.89 2494.12 4072.97 2492.39 3193.43 3376.89 7384.68 8693.99 6570.67 7796.82 2684.18 7995.01 4193.90 88
test_yl81.17 16980.47 17083.24 20089.13 15663.62 27086.21 24589.95 19172.43 20781.78 15189.61 20257.50 25893.58 16670.75 23986.90 19292.52 164
thisisatest053079.40 22177.76 24484.31 14287.69 22865.10 23187.36 19784.26 34370.04 26577.42 23488.26 24649.94 34594.79 11270.20 24784.70 23293.03 143
Anonymous2024052980.19 20578.89 21484.10 15590.60 10464.75 24588.95 12790.90 15765.97 34180.59 17491.17 15549.97 34493.73 16469.16 26082.70 27293.81 94
Anonymous20240521178.25 25077.01 26181.99 24991.03 9460.67 33484.77 28483.90 34770.65 25080.00 18291.20 15341.08 42191.43 28665.21 29485.26 22593.85 90
DCV-MVSNet81.17 16980.47 17083.24 20089.13 15663.62 27086.21 24589.95 19172.43 20781.78 15189.61 20257.50 25893.58 16670.75 23986.90 19292.52 164
tttt051779.40 22177.91 23583.90 17888.10 20063.84 26688.37 15784.05 34571.45 22576.78 25189.12 21649.93 34794.89 10570.18 24883.18 26592.96 148
our_test_369.14 38767.00 40075.57 37479.80 41958.80 35377.96 40977.81 42259.55 41462.90 43978.25 43547.43 36583.97 40351.71 40767.58 42683.93 419
thisisatest051577.33 27775.38 29483.18 20385.27 30863.80 26782.11 34583.27 35765.06 35475.91 27283.84 36149.54 34994.27 13167.24 27886.19 20691.48 208
ppachtmachnet_test70.04 38067.34 39878.14 34179.80 41961.13 32379.19 39080.59 39359.16 41865.27 42279.29 42546.75 37487.29 37049.33 42466.72 42786.00 389
SMA-MVScopyleft89.08 1089.23 1088.61 694.25 3573.73 992.40 2993.63 2674.77 14792.29 795.97 274.28 3397.24 1688.58 3396.91 194.87 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
GSMVS88.96 308
DPE-MVScopyleft89.48 689.98 588.01 1694.80 1172.69 3191.59 5194.10 1375.90 10792.29 795.66 1081.67 697.38 1487.44 4896.34 1593.95 85
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part295.06 872.65 3291.80 16
thres100view90076.50 29175.55 29079.33 31789.52 13356.99 38185.83 25783.23 35873.94 16876.32 26487.12 27951.89 31891.95 25848.33 42983.75 25089.07 297
tfpnnormal74.39 32173.16 32778.08 34386.10 28858.05 36184.65 28987.53 28270.32 26071.22 35585.63 31954.97 27889.86 32643.03 45375.02 37886.32 379
tfpn200view976.42 29675.37 29579.55 31589.13 15657.65 37285.17 27283.60 35073.41 18576.45 26086.39 30352.12 30991.95 25848.33 42983.75 25089.07 297
c3_l78.75 23877.91 23581.26 26782.89 37261.56 31984.09 30989.13 23269.97 26975.56 27884.29 35066.36 14392.09 25273.47 20975.48 36690.12 261
CHOSEN 280x42066.51 40864.71 41071.90 41481.45 39663.52 27957.98 47968.95 46153.57 44862.59 44076.70 44346.22 38175.29 46055.25 38879.68 30676.88 458
CANet86.45 4886.10 6187.51 4290.09 11570.94 7589.70 9492.59 7981.78 481.32 15891.43 14570.34 7997.23 1784.26 7593.36 7494.37 62
Fast-Effi-MVS+-dtu78.02 25976.49 27582.62 23583.16 36266.96 18586.94 21287.45 28572.45 20471.49 35284.17 35654.79 28391.58 27267.61 27380.31 30089.30 295
Effi-MVS+-dtu80.03 20778.57 21984.42 13485.13 31368.74 12188.77 13688.10 26474.99 13774.97 30483.49 37257.27 26193.36 18873.53 20780.88 29191.18 215
CANet_DTU80.61 18879.87 18682.83 22285.60 29863.17 29087.36 19788.65 25676.37 9575.88 27388.44 24053.51 29693.07 20973.30 21189.74 13492.25 178
MGCNet87.69 2487.55 2988.12 1389.45 13871.76 5391.47 5789.54 20682.14 386.65 6694.28 4668.28 12097.46 690.81 695.31 3895.15 8
MP-MVS-pluss87.67 2587.72 2587.54 4093.64 4872.04 5089.80 9093.50 3075.17 13486.34 6895.29 1770.86 7496.00 5988.78 3196.04 1694.58 47
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS89.51 589.91 688.30 1094.28 3473.46 1792.90 2194.11 1180.27 1091.35 1794.16 5478.35 1596.77 2889.59 1794.22 6694.67 38
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
sam_mvs151.32 32588.96 308
sam_mvs50.01 343
IterMVS-SCA-FT75.43 31173.87 31880.11 29882.69 37664.85 24381.57 35283.47 35469.16 29270.49 35984.15 35751.95 31588.15 35969.23 25872.14 40487.34 354
TSAR-MVS + MP.88.02 2188.11 2087.72 3393.68 4772.13 4891.41 5892.35 8774.62 15188.90 3293.85 7175.75 2396.00 5987.80 4394.63 5495.04 10
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
xiu_mvs_v1_base_debu80.80 18179.72 19284.03 16987.35 24170.19 8885.56 26188.77 24769.06 29581.83 14788.16 24850.91 33192.85 21978.29 15087.56 17989.06 299
OPM-MVS83.50 11982.95 12485.14 9888.79 17270.95 7489.13 12191.52 13877.55 5280.96 16691.75 12960.71 22694.50 12479.67 13286.51 20089.97 274
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMMP_NAP88.05 2088.08 2187.94 1993.70 4573.05 2290.86 6593.59 2876.27 10088.14 4195.09 1971.06 7296.67 3387.67 4496.37 1494.09 77
ambc75.24 38173.16 46250.51 44763.05 47787.47 28464.28 42977.81 43817.80 47789.73 33057.88 36960.64 45185.49 395
MTGPAbinary92.02 111
SPE-MVS-test86.29 5486.48 5185.71 8091.02 9567.21 18092.36 3493.78 2378.97 3383.51 12091.20 15370.65 7895.15 9181.96 10294.89 4694.77 25
Effi-MVS+83.62 11683.08 12085.24 9588.38 18867.45 16788.89 12989.15 23075.50 11882.27 14188.28 24469.61 9494.45 12777.81 15487.84 17493.84 92
xiu_mvs_v2_base81.69 15781.05 15783.60 18589.15 15568.03 14784.46 29590.02 18870.67 24681.30 16186.53 30063.17 17994.19 13875.60 18788.54 15688.57 324
xiu_mvs_v1_base80.80 18179.72 19284.03 16987.35 24170.19 8885.56 26188.77 24769.06 29581.83 14788.16 24850.91 33192.85 21978.29 15087.56 17989.06 299
new-patchmatchnet61.73 42461.73 42561.70 44972.74 46524.50 49269.16 45778.03 42161.40 39956.72 46075.53 45438.42 43576.48 44745.95 44457.67 45584.13 416
pmmvs674.69 31973.39 32378.61 32981.38 39857.48 37586.64 22687.95 27164.99 35770.18 36386.61 29450.43 33889.52 33362.12 32770.18 41588.83 313
pmmvs571.55 36270.20 36675.61 37377.83 43556.39 39181.74 34880.89 38857.76 43167.46 39784.49 34349.26 35585.32 39357.08 37675.29 37485.11 404
test_post178.90 3965.43 49048.81 36285.44 39259.25 353
test_post5.46 48950.36 33984.24 401
Fast-Effi-MVS+80.81 17879.92 18383.47 18988.85 16364.51 25085.53 26689.39 21270.79 24378.49 20985.06 33567.54 12893.58 16667.03 28286.58 19892.32 175
patchmatchnet-post74.00 45751.12 33088.60 353
Anonymous2023121178.97 23477.69 24782.81 22490.54 10664.29 25790.11 8391.51 13965.01 35676.16 27188.13 25350.56 33693.03 21469.68 25577.56 33591.11 217
pmmvs-eth3d70.50 37467.83 38878.52 33577.37 44066.18 19581.82 34681.51 38358.90 42163.90 43480.42 41142.69 40986.28 38058.56 36165.30 43883.11 428
GG-mvs-BLEND75.38 37981.59 39355.80 40179.32 38769.63 45767.19 40173.67 45843.24 40588.90 34950.41 41484.50 23481.45 443
xiu_mvs_v1_base_debi80.80 18179.72 19284.03 16987.35 24170.19 8885.56 26188.77 24769.06 29581.83 14788.16 24850.91 33192.85 21978.29 15087.56 17989.06 299
Anonymous2023120668.60 39167.80 38971.02 42380.23 41250.75 44678.30 40680.47 39656.79 43866.11 41882.63 38846.35 37978.95 43343.62 45175.70 36183.36 425
MTAPA87.23 3687.00 3987.90 2294.18 3974.25 586.58 22892.02 11179.45 2285.88 7094.80 2768.07 12296.21 5086.69 5295.34 3693.23 126
MTMP92.18 3932.83 493
gm-plane-assit81.40 39753.83 42162.72 38880.94 40692.39 24063.40 308
test9_res84.90 6495.70 3092.87 151
MVP-Stereo76.12 30074.46 31081.13 27285.37 30569.79 9584.42 30087.95 27165.03 35567.46 39785.33 32753.28 29991.73 26858.01 36883.27 26381.85 441
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST993.26 5672.96 2588.75 13891.89 11968.44 30985.00 8093.10 8874.36 3295.41 80
train_agg86.43 4986.20 5687.13 4993.26 5672.96 2588.75 13891.89 11968.69 30485.00 8093.10 8874.43 3095.41 8084.97 6395.71 2993.02 144
gg-mvs-nofinetune69.95 38167.96 38475.94 36983.07 36354.51 41677.23 41670.29 45563.11 37970.32 36162.33 46943.62 40388.69 35153.88 39787.76 17784.62 411
SCA74.22 32472.33 33779.91 30284.05 33762.17 30979.96 38179.29 41366.30 33672.38 34180.13 41651.95 31588.60 35359.25 35377.67 33488.96 308
Patchmatch-test64.82 41763.24 41869.57 42879.42 42549.82 45063.49 47669.05 46051.98 45459.95 45080.13 41650.91 33170.98 46940.66 45973.57 39187.90 338
test_893.13 6072.57 3588.68 14391.84 12368.69 30484.87 8493.10 8874.43 3095.16 90
MS-PatchMatch73.83 33072.67 33277.30 36083.87 34166.02 19881.82 34684.66 33561.37 40168.61 38382.82 38547.29 36688.21 35859.27 35284.32 24177.68 456
Patchmatch-RL test70.24 37767.78 39077.61 35477.43 43959.57 34971.16 44770.33 45462.94 38368.65 38272.77 46050.62 33585.49 39069.58 25666.58 42987.77 341
cdsmvs_eth3d_5k19.96 45526.61 4570.00 4760.00 4990.00 5010.00 48889.26 2230.00 4940.00 49588.61 23461.62 2080.00 4950.00 4940.00 4930.00 491
pcd_1.5k_mvsjas5.26 4617.02 4640.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 4950.00 49463.15 1800.00 4950.00 4940.00 4930.00 491
agg_prior282.91 9195.45 3392.70 156
agg_prior92.85 6871.94 5291.78 12784.41 9594.93 101
tmp_tt18.61 45621.40 45910.23 4734.82 49610.11 49634.70 48430.74 4941.48 49023.91 48626.07 48728.42 46113.41 49227.12 47615.35 4897.17 487
canonicalmvs85.91 6385.87 6786.04 7489.84 12569.44 10590.45 7693.00 5176.70 8188.01 4591.23 14973.28 4093.91 15281.50 10588.80 15094.77 25
anonymousdsp78.60 24377.15 25982.98 21680.51 40967.08 18187.24 20289.53 20765.66 34475.16 29787.19 27752.52 30292.25 24777.17 16379.34 31389.61 286
alignmvs85.48 7385.32 7985.96 7789.51 13469.47 10289.74 9292.47 8176.17 10287.73 5291.46 14470.32 8093.78 15881.51 10488.95 14794.63 44
nrg03083.88 10483.53 11384.96 10786.77 26969.28 10990.46 7592.67 7274.79 14682.95 13091.33 14872.70 5093.09 20880.79 11579.28 31492.50 166
v14419279.47 21778.37 22482.78 22983.35 35363.96 26286.96 21090.36 17769.99 26877.50 23285.67 31860.66 22993.77 16074.27 20176.58 34690.62 238
FIs82.07 14882.42 13381.04 27488.80 17158.34 35888.26 16193.49 3176.93 7278.47 21191.04 15969.92 8992.34 24469.87 25384.97 22792.44 171
v192192079.22 22678.03 23282.80 22583.30 35563.94 26486.80 21890.33 17869.91 27177.48 23385.53 32258.44 24993.75 16273.60 20676.85 34390.71 236
UA-Net85.08 8484.96 8485.45 8992.07 7968.07 14589.78 9190.86 16082.48 284.60 9293.20 8769.35 9795.22 8871.39 23490.88 11493.07 139
v119279.59 21478.43 22383.07 21083.55 35064.52 24986.93 21390.58 16770.83 24277.78 22885.90 31159.15 24393.94 14773.96 20477.19 33890.76 232
FC-MVSNet-test81.52 16482.02 14580.03 29988.42 18755.97 39887.95 17293.42 3477.10 6877.38 23590.98 16569.96 8891.79 26468.46 26884.50 23492.33 174
v114480.03 20779.03 21083.01 21383.78 34364.51 25087.11 20590.57 16971.96 21578.08 22186.20 30761.41 21393.94 14774.93 19477.23 33690.60 240
sosnet-low-res0.00 4620.00 4650.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 4950.00 4940.00 4980.00 4950.00 4940.00 4930.00 491
HFP-MVS87.58 2687.47 3187.94 1994.58 1673.54 1593.04 1793.24 3876.78 7784.91 8294.44 3970.78 7596.61 3684.53 7294.89 4693.66 102
v14878.72 24077.80 24181.47 25982.73 37561.96 31486.30 24188.08 26573.26 19076.18 26885.47 32462.46 19292.36 24271.92 23073.82 39090.09 264
sosnet0.00 4620.00 4650.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 4950.00 4940.00 4980.00 4950.00 4940.00 4930.00 491
uncertanet0.00 4620.00 4650.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 4950.00 4940.00 4980.00 4950.00 4940.00 4930.00 491
AllTest70.96 36768.09 38279.58 31385.15 31163.62 27084.58 29179.83 40662.31 39160.32 44886.73 28532.02 45388.96 34750.28 41771.57 40886.15 383
TestCases79.58 31385.15 31163.62 27079.83 40662.31 39160.32 44886.73 28532.02 45388.96 34750.28 41771.57 40886.15 383
v7n78.97 23477.58 25083.14 20583.45 35265.51 21488.32 15991.21 14773.69 17572.41 34086.32 30557.93 25293.81 15769.18 25975.65 36290.11 262
region2R87.42 3187.20 3788.09 1494.63 1473.55 1393.03 1993.12 4576.73 8084.45 9494.52 3269.09 10596.70 3184.37 7494.83 4994.03 80
RRT-MVS82.60 14282.10 14284.10 15587.98 20762.94 29687.45 19091.27 14577.42 5679.85 18390.28 18256.62 26994.70 11779.87 12988.15 16794.67 38
mamv476.81 28678.23 23072.54 41186.12 28665.75 21078.76 39782.07 37764.12 36772.97 33291.02 16267.97 12368.08 47683.04 8978.02 32883.80 421
PS-MVSNAJss82.07 14881.31 15284.34 14086.51 27767.27 17689.27 11291.51 13971.75 21779.37 19290.22 18663.15 18094.27 13177.69 15782.36 27591.49 207
PS-MVSNAJ81.69 15781.02 15883.70 18389.51 13468.21 14284.28 30390.09 18770.79 24381.26 16285.62 32063.15 18094.29 12975.62 18688.87 14988.59 323
jajsoiax79.29 22577.96 23383.27 19884.68 32366.57 19089.25 11390.16 18569.20 29175.46 28289.49 20645.75 38893.13 20676.84 16980.80 29390.11 262
mvs_tets79.13 22977.77 24383.22 20284.70 32266.37 19289.17 11690.19 18469.38 28375.40 28589.46 20944.17 40093.15 20476.78 17380.70 29590.14 259
EI-MVSNet-UG-set83.81 10583.38 11685.09 10387.87 21167.53 16687.44 19589.66 20179.74 1882.23 14289.41 21370.24 8294.74 11479.95 12383.92 24692.99 147
EI-MVSNet-Vis-set84.19 9683.81 10585.31 9388.18 19467.85 15487.66 18289.73 20080.05 1582.95 13089.59 20470.74 7694.82 10880.66 11884.72 23193.28 125
HPM-MVS++copyleft89.02 1189.15 1288.63 595.01 976.03 192.38 3292.85 6480.26 1187.78 4894.27 4775.89 2296.81 2787.45 4796.44 993.05 142
test_prior472.60 3489.01 125
XVS87.18 3786.91 4488.00 1794.42 2473.33 1992.78 2392.99 5479.14 2683.67 11394.17 5367.45 12996.60 3783.06 8794.50 5794.07 78
v124078.99 23377.78 24282.64 23483.21 35863.54 27886.62 22790.30 18069.74 27877.33 23685.68 31757.04 26493.76 16173.13 21476.92 34090.62 238
pm-mvs177.25 27976.68 27378.93 32484.22 33258.62 35586.41 23488.36 26171.37 22673.31 32688.01 25461.22 21989.15 34264.24 30373.01 39789.03 303
test_prior288.85 13275.41 12184.91 8293.54 7674.28 3383.31 8595.86 24
X-MVStestdata80.37 19977.83 23988.00 1794.42 2473.33 1992.78 2392.99 5479.14 2683.67 11312.47 48867.45 12996.60 3783.06 8794.50 5794.07 78
test_prior86.33 6492.61 7469.59 9892.97 5995.48 7493.91 86
旧先验286.56 22958.10 42987.04 6188.98 34574.07 203
新几何286.29 243
新几何183.42 19293.13 6070.71 8085.48 32657.43 43581.80 15091.98 12063.28 17492.27 24664.60 30092.99 7687.27 357
旧先验191.96 8065.79 20886.37 31393.08 9269.31 9992.74 8088.74 319
无先验87.48 18688.98 23860.00 41094.12 14067.28 27788.97 307
原ACMM286.86 216
原ACMM184.35 13993.01 6668.79 11792.44 8263.96 37381.09 16391.57 13966.06 15095.45 7567.19 27994.82 5088.81 314
test22291.50 8668.26 13784.16 30783.20 36154.63 44679.74 18491.63 13558.97 24491.42 10386.77 372
testdata291.01 30462.37 323
segment_acmp73.08 43
testdata79.97 30190.90 9864.21 25884.71 33459.27 41785.40 7592.91 9462.02 20189.08 34368.95 26291.37 10586.63 377
testdata184.14 30875.71 112
v879.97 20979.02 21182.80 22584.09 33564.50 25287.96 17190.29 18174.13 16575.24 29586.81 28462.88 18793.89 15574.39 20075.40 37190.00 270
131476.53 29075.30 29880.21 29583.93 33962.32 30784.66 28788.81 24560.23 40870.16 36584.07 35855.30 27790.73 31467.37 27683.21 26487.59 346
LFMVS81.82 15481.23 15483.57 18891.89 8263.43 28389.84 8781.85 38077.04 7083.21 12393.10 8852.26 30793.43 18671.98 22989.95 13093.85 90
VDD-MVS83.01 13482.36 13684.96 10791.02 9566.40 19188.91 12888.11 26377.57 4984.39 9693.29 8552.19 30893.91 15277.05 16588.70 15494.57 49
VDDNet81.52 16480.67 16484.05 16790.44 10864.13 26089.73 9385.91 32071.11 23383.18 12693.48 7850.54 33793.49 17973.40 21088.25 16594.54 53
v1079.74 21178.67 21682.97 21784.06 33664.95 23587.88 17790.62 16673.11 19575.11 29986.56 29861.46 21294.05 14373.68 20575.55 36489.90 276
VPNet78.69 24178.66 21778.76 32788.31 19055.72 40284.45 29686.63 30876.79 7678.26 21590.55 17659.30 24289.70 33166.63 28377.05 33990.88 227
MVS78.19 25476.99 26381.78 25285.66 29566.99 18284.66 28790.47 17155.08 44572.02 34685.27 32863.83 17194.11 14166.10 28789.80 13384.24 414
v2v48280.23 20379.29 20483.05 21183.62 34864.14 25987.04 20689.97 19073.61 17778.18 21887.22 27561.10 22193.82 15676.11 17876.78 34591.18 215
V4279.38 22378.24 22882.83 22281.10 40365.50 21585.55 26489.82 19471.57 22378.21 21686.12 30960.66 22993.18 20375.64 18575.46 36889.81 281
SD-MVS88.06 1888.50 1886.71 6092.60 7572.71 2991.81 4693.19 4077.87 4290.32 2394.00 6374.83 2693.78 15887.63 4594.27 6593.65 106
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
GA-MVS76.87 28575.17 30081.97 25082.75 37462.58 29981.44 35586.35 31472.16 21274.74 30782.89 38346.20 38292.02 25568.85 26481.09 28891.30 213
MSLP-MVS++85.43 7585.76 6984.45 13291.93 8170.24 8590.71 6792.86 6377.46 5584.22 10092.81 9967.16 13392.94 21580.36 11994.35 6390.16 258
APDe-MVScopyleft89.15 989.63 887.73 3194.49 2271.69 5493.83 493.96 1875.70 11491.06 1996.03 176.84 1797.03 2189.09 2195.65 3194.47 57
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize85.97 6185.88 6586.22 6792.69 7269.53 9991.93 4292.99 5473.54 18085.94 6994.51 3565.80 15495.61 6783.04 8992.51 8393.53 116
ADS-MVSNet266.20 41363.33 41774.82 38679.92 41558.75 35467.55 46275.19 43953.37 44965.25 42375.86 45142.32 41180.53 42841.57 45768.91 42085.18 401
EI-MVSNet80.52 19479.98 18282.12 24484.28 33063.19 28986.41 23488.95 24174.18 16378.69 20287.54 26766.62 13892.43 23872.57 22080.57 29790.74 234
Regformer0.00 4620.00 4650.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 4950.00 4940.00 4980.00 4950.00 4940.00 4930.00 491
CVMVSNet72.99 34772.58 33474.25 39384.28 33050.85 44586.41 23483.45 35544.56 46573.23 32887.54 26749.38 35285.70 38665.90 28978.44 32186.19 382
pmmvs474.03 32971.91 34080.39 28881.96 38768.32 13581.45 35482.14 37559.32 41669.87 37185.13 33352.40 30588.13 36060.21 34474.74 38184.73 410
EU-MVSNet68.53 39467.61 39371.31 42178.51 43147.01 45984.47 29384.27 34242.27 46866.44 41584.79 34140.44 42483.76 40458.76 36068.54 42383.17 426
VNet82.21 14582.41 13481.62 25590.82 10060.93 32884.47 29389.78 19576.36 9684.07 10491.88 12364.71 16390.26 31970.68 24188.89 14893.66 102
test-LLR72.94 34872.43 33574.48 38981.35 39958.04 36278.38 40277.46 42566.66 32869.95 36979.00 42848.06 36379.24 43166.13 28584.83 22986.15 383
TESTMET0.1,169.89 38269.00 37472.55 41079.27 42756.85 38278.38 40274.71 44457.64 43268.09 38977.19 44237.75 43976.70 44463.92 30484.09 24484.10 417
test-mter71.41 36370.39 36474.48 38981.35 39958.04 36278.38 40277.46 42560.32 40769.95 36979.00 42836.08 44679.24 43166.13 28584.83 22986.15 383
VPA-MVSNet80.60 19080.55 16780.76 28188.07 20260.80 33186.86 21691.58 13775.67 11580.24 17989.45 21163.34 17390.25 32070.51 24379.22 31591.23 214
ACMMPR87.44 2987.23 3688.08 1594.64 1373.59 1293.04 1793.20 3976.78 7784.66 8994.52 3268.81 11196.65 3484.53 7294.90 4594.00 82
testgi66.67 40766.53 40367.08 44275.62 44841.69 47775.93 42276.50 43466.11 33765.20 42586.59 29535.72 44774.71 46143.71 45073.38 39584.84 408
test20.0367.45 40066.95 40168.94 43175.48 44944.84 46877.50 41377.67 42366.66 32863.01 43783.80 36247.02 36978.40 43542.53 45668.86 42283.58 423
thres600view776.50 29175.44 29179.68 31089.40 14157.16 37885.53 26683.23 35873.79 17276.26 26587.09 28051.89 31891.89 26148.05 43483.72 25390.00 270
ADS-MVSNet64.36 41862.88 42168.78 43479.92 41547.17 45867.55 46271.18 45353.37 44965.25 42375.86 45142.32 41173.99 46541.57 45768.91 42085.18 401
MP-MVScopyleft87.71 2387.64 2687.93 2194.36 3073.88 692.71 2792.65 7577.57 4983.84 10994.40 4172.24 5496.28 4785.65 5995.30 3993.62 109
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs6.04 4608.02 4630.10 4750.08 4970.03 50069.74 4530.04 4980.05 4920.31 4931.68 4920.02 4970.04 4930.24 4920.02 4910.25 490
thres40076.50 29175.37 29579.86 30389.13 15657.65 37285.17 27283.60 35073.41 18576.45 26086.39 30352.12 30991.95 25848.33 42983.75 25090.00 270
test1236.12 4598.11 4620.14 4740.06 4980.09 49971.05 4480.03 4990.04 4930.25 4941.30 4930.05 4960.03 4940.21 4930.01 4920.29 489
thres20075.55 30874.47 30978.82 32687.78 21857.85 36783.07 33483.51 35372.44 20675.84 27484.42 34552.08 31291.75 26647.41 43683.64 25586.86 370
test0.0.03 168.00 39867.69 39168.90 43277.55 43847.43 45575.70 42672.95 45166.66 32866.56 41082.29 39348.06 36375.87 45444.97 44974.51 38383.41 424
pmmvs357.79 42954.26 43468.37 43664.02 47856.72 38575.12 43265.17 46940.20 47052.93 46669.86 46620.36 47475.48 45745.45 44755.25 46372.90 464
EMVS30.81 45329.65 45534.27 47050.96 49025.95 49056.58 48146.80 48824.01 48515.53 49030.68 48612.47 48154.43 48612.81 48917.05 48722.43 486
E-PMN31.77 45130.64 45435.15 46952.87 48927.67 48657.09 48047.86 48724.64 48416.40 48933.05 48511.23 48454.90 48514.46 48818.15 48622.87 485
PGM-MVS86.68 4586.27 5587.90 2294.22 3773.38 1890.22 8193.04 4675.53 11783.86 10894.42 4067.87 12696.64 3582.70 9894.57 5693.66 102
LCM-MVSNet-Re77.05 28176.94 26477.36 35887.20 25151.60 43880.06 37880.46 39775.20 13167.69 39486.72 28762.48 19188.98 34563.44 30789.25 14191.51 205
LCM-MVSNet54.25 43349.68 44367.97 44053.73 48845.28 46566.85 46580.78 39035.96 47739.45 47862.23 4718.70 48778.06 43848.24 43251.20 46880.57 449
MCST-MVS87.37 3487.25 3587.73 3194.53 2172.46 4089.82 8893.82 2173.07 19684.86 8592.89 9576.22 2096.33 4584.89 6695.13 4094.40 60
mvs_anonymous79.42 22079.11 20980.34 29084.45 32957.97 36482.59 33887.62 28067.40 32176.17 27088.56 23768.47 11689.59 33270.65 24286.05 20993.47 117
MVS_Test83.15 12983.06 12183.41 19486.86 26463.21 28786.11 24892.00 11374.31 15882.87 13289.44 21270.03 8793.21 19777.39 16188.50 15893.81 94
MDA-MVSNet-bldmvs66.68 40663.66 41675.75 37179.28 42660.56 33673.92 43978.35 42064.43 36150.13 47079.87 42044.02 40183.67 40546.10 44356.86 45683.03 430
CDPH-MVS85.76 6885.29 8187.17 4893.49 5171.08 6988.58 14792.42 8568.32 31184.61 9193.48 7872.32 5296.15 5379.00 14095.43 3494.28 68
test1286.80 5892.63 7370.70 8191.79 12682.71 13771.67 6396.16 5294.50 5793.54 115
casdiffmvspermissive85.11 8385.14 8285.01 10587.20 25165.77 20987.75 18092.83 6577.84 4384.36 9992.38 10672.15 5593.93 15081.27 10990.48 11995.33 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
diffmvspermissive82.10 14681.88 14882.76 23183.00 36663.78 26983.68 31689.76 19772.94 19982.02 14689.85 19165.96 15390.79 31082.38 10087.30 18593.71 100
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
baseline275.70 30673.83 31981.30 26583.26 35661.79 31782.57 33980.65 39266.81 32466.88 40583.42 37357.86 25492.19 24963.47 30679.57 30789.91 275
baseline176.98 28376.75 27177.66 35288.13 19855.66 40385.12 27581.89 37873.04 19776.79 25088.90 22562.43 19387.78 36563.30 30971.18 41089.55 288
YYNet165.03 41562.91 42071.38 41775.85 44656.60 38869.12 45874.66 44557.28 43654.12 46477.87 43745.85 38574.48 46249.95 42061.52 44983.05 429
PMMVS240.82 44938.86 45346.69 46453.84 48616.45 49548.61 48249.92 48437.49 47431.67 47960.97 4728.14 48956.42 48428.42 47530.72 48167.19 469
MDA-MVSNet_test_wron65.03 41562.92 41971.37 41875.93 44356.73 38469.09 45974.73 44357.28 43654.03 46577.89 43645.88 38474.39 46349.89 42161.55 44882.99 431
tpmvs71.09 36669.29 37176.49 36682.04 38656.04 39778.92 39581.37 38664.05 37067.18 40278.28 43449.74 34889.77 32849.67 42272.37 40083.67 422
PM-MVS66.41 40964.14 41273.20 40473.92 45556.45 38978.97 39464.96 47163.88 37464.72 42680.24 41519.84 47583.44 40966.24 28464.52 44079.71 452
HQP_MVS83.64 11483.14 11985.14 9890.08 11668.71 12391.25 6092.44 8279.12 2878.92 19991.00 16360.42 23495.38 8278.71 14486.32 20291.33 211
plane_prior790.08 11668.51 131
plane_prior689.84 12568.70 12560.42 234
plane_prior592.44 8295.38 8278.71 14486.32 20291.33 211
plane_prior491.00 163
plane_prior368.60 12878.44 3678.92 199
plane_prior291.25 6079.12 28
plane_prior189.90 124
plane_prior68.71 12390.38 7877.62 4786.16 207
PS-CasMVS78.01 26078.09 23177.77 35087.71 22454.39 41788.02 16991.22 14677.50 5473.26 32788.64 23360.73 22588.41 35761.88 32973.88 38990.53 243
UniMVSNet_NR-MVSNet81.88 15281.54 15182.92 21888.46 18463.46 28187.13 20392.37 8680.19 1278.38 21289.14 21571.66 6493.05 21170.05 24976.46 34992.25 178
PEN-MVS77.73 26677.69 24777.84 34887.07 26253.91 42087.91 17591.18 14877.56 5173.14 32988.82 22861.23 21889.17 34159.95 34572.37 40090.43 247
TransMVSNet (Re)75.39 31474.56 30777.86 34785.50 30257.10 38086.78 22086.09 31972.17 21171.53 35187.34 27063.01 18489.31 33756.84 38061.83 44787.17 360
DTE-MVSNet76.99 28276.80 26777.54 35786.24 28153.06 42987.52 18590.66 16577.08 6972.50 33888.67 23260.48 23389.52 33357.33 37470.74 41290.05 269
DU-MVS81.12 17280.52 16882.90 21987.80 21563.46 28187.02 20891.87 12179.01 3178.38 21289.07 21765.02 16093.05 21170.05 24976.46 34992.20 181
UniMVSNet (Re)81.60 16081.11 15683.09 20788.38 18864.41 25587.60 18393.02 5078.42 3778.56 20788.16 24869.78 9193.26 19369.58 25676.49 34891.60 201
CP-MVSNet78.22 25178.34 22577.84 34887.83 21454.54 41587.94 17391.17 14977.65 4673.48 32588.49 23862.24 19788.43 35662.19 32574.07 38590.55 242
WR-MVS_H78.51 24678.49 22078.56 33288.02 20456.38 39288.43 15192.67 7277.14 6573.89 31987.55 26666.25 14589.24 33958.92 35773.55 39290.06 268
WR-MVS79.49 21679.22 20780.27 29288.79 17258.35 35785.06 27888.61 25878.56 3577.65 23088.34 24263.81 17290.66 31564.98 29777.22 33791.80 195
NR-MVSNet80.23 20379.38 20082.78 22987.80 21563.34 28486.31 24091.09 15379.01 3172.17 34489.07 21767.20 13292.81 22366.08 28875.65 36292.20 181
Baseline_NR-MVSNet78.15 25578.33 22677.61 35485.79 29256.21 39686.78 22085.76 32373.60 17877.93 22487.57 26465.02 16088.99 34467.14 28075.33 37387.63 343
TranMVSNet+NR-MVSNet80.84 17680.31 17382.42 23987.85 21262.33 30687.74 18191.33 14480.55 977.99 22389.86 19065.23 15892.62 22667.05 28175.24 37692.30 176
TSAR-MVS + GP.85.71 6985.33 7886.84 5691.34 8872.50 3689.07 12487.28 28876.41 9085.80 7190.22 18674.15 3595.37 8581.82 10391.88 9492.65 160
n20.00 500
nn0.00 500
mPP-MVS86.67 4686.32 5387.72 3394.41 2673.55 1392.74 2592.22 10076.87 7482.81 13694.25 4966.44 14296.24 4982.88 9294.28 6493.38 119
door-mid69.98 456
XVG-OURS-SEG-HR80.81 17879.76 18983.96 17685.60 29868.78 11883.54 32390.50 17070.66 24976.71 25391.66 13260.69 22791.26 29176.94 16681.58 28391.83 193
mvsmamba80.60 19079.38 20084.27 14889.74 12867.24 17887.47 18786.95 29970.02 26675.38 28688.93 22451.24 32892.56 23175.47 19089.22 14393.00 146
MVSFormer82.85 13682.05 14485.24 9587.35 24170.21 8690.50 7290.38 17468.55 30681.32 15889.47 20761.68 20693.46 18478.98 14190.26 12392.05 190
jason81.39 16780.29 17484.70 12186.63 27469.90 9485.95 25186.77 30463.24 37781.07 16489.47 20761.08 22292.15 25078.33 14990.07 12892.05 190
jason: jason.
lupinMVS81.39 16780.27 17584.76 11987.35 24170.21 8685.55 26486.41 31162.85 38481.32 15888.61 23461.68 20692.24 24878.41 14890.26 12391.83 193
test_djsdf80.30 20279.32 20383.27 19883.98 33865.37 21990.50 7290.38 17468.55 30676.19 26788.70 23056.44 27093.46 18478.98 14180.14 30390.97 224
HPM-MVS_fast85.35 7984.95 8586.57 6393.69 4670.58 8492.15 4091.62 13473.89 17082.67 13894.09 5762.60 18895.54 7080.93 11192.93 7793.57 112
K. test v371.19 36468.51 37679.21 32083.04 36557.78 37084.35 30276.91 43272.90 20062.99 43882.86 38439.27 42991.09 30261.65 33252.66 46588.75 317
lessismore_v078.97 32381.01 40457.15 37965.99 46761.16 44482.82 38539.12 43191.34 28959.67 34846.92 47288.43 327
SixPastTwentyTwo73.37 33771.26 35179.70 30985.08 31457.89 36685.57 26083.56 35271.03 23865.66 41985.88 31242.10 41492.57 23059.11 35563.34 44288.65 321
OurMVSNet-221017-074.26 32372.42 33679.80 30583.76 34459.59 34885.92 25386.64 30766.39 33566.96 40487.58 26339.46 42891.60 27165.76 29169.27 41888.22 332
HPM-MVScopyleft87.11 3886.98 4187.50 4393.88 4372.16 4792.19 3893.33 3676.07 10483.81 11093.95 6869.77 9296.01 5885.15 6294.66 5194.32 66
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS80.41 19579.23 20683.97 17585.64 29669.02 11283.03 33690.39 17371.09 23477.63 23191.49 14354.62 28691.35 28875.71 18483.47 25991.54 204
XVG-ACMP-BASELINE76.11 30174.27 31381.62 25583.20 35964.67 24683.60 32089.75 19969.75 27671.85 34787.09 28032.78 45292.11 25169.99 25180.43 29988.09 335
casdiffmvs_mvgpermissive85.99 5986.09 6285.70 8187.65 22967.22 17988.69 14293.04 4679.64 2185.33 7692.54 10473.30 3994.50 12483.49 8391.14 10895.37 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
LPG-MVS_test82.08 14781.27 15384.50 12989.23 15268.76 11990.22 8191.94 11775.37 12376.64 25591.51 14154.29 28794.91 10278.44 14683.78 24789.83 279
LGP-MVS_train84.50 12989.23 15268.76 11991.94 11775.37 12376.64 25591.51 14154.29 28794.91 10278.44 14683.78 24789.83 279
baseline84.93 8684.98 8384.80 11787.30 24965.39 21887.30 20092.88 6277.62 4784.04 10592.26 10871.81 5993.96 14481.31 10790.30 12295.03 11
test1192.23 97
door69.44 459
EPNet_dtu75.46 31074.86 30277.23 36182.57 37954.60 41486.89 21483.09 36271.64 21866.25 41685.86 31355.99 27288.04 36154.92 39186.55 19989.05 302
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268877.63 27275.69 28583.44 19189.98 12268.58 12978.70 39887.50 28356.38 44075.80 27586.84 28358.67 24791.40 28761.58 33385.75 21890.34 251
EPNet83.72 11182.92 12586.14 7284.22 33269.48 10191.05 6485.27 32781.30 676.83 24991.65 13366.09 14995.56 6876.00 18193.85 6893.38 119
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS66.98 183
HQP-NCC89.33 14489.17 11676.41 9077.23 240
ACMP_Plane89.33 14489.17 11676.41 9077.23 240
APD-MVScopyleft87.44 2987.52 3087.19 4794.24 3672.39 4191.86 4592.83 6573.01 19888.58 3494.52 3273.36 3896.49 4284.26 7595.01 4192.70 156
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS77.47 159
HQP4-MVS77.24 23995.11 9491.03 221
HQP3-MVS92.19 10585.99 211
HQP2-MVS60.17 237
CNVR-MVS88.93 1389.13 1388.33 894.77 1273.82 890.51 7093.00 5180.90 788.06 4394.06 5976.43 1996.84 2588.48 3695.99 1894.34 64
NCCC88.06 1888.01 2288.24 1194.41 2673.62 1191.22 6292.83 6581.50 585.79 7293.47 8073.02 4597.00 2284.90 6494.94 4494.10 76
114514_t80.68 18679.51 19784.20 15294.09 4267.27 17689.64 9691.11 15258.75 42474.08 31790.72 16858.10 25195.04 9969.70 25489.42 14090.30 254
CP-MVS87.11 3886.92 4387.68 3794.20 3873.86 793.98 392.82 6876.62 8383.68 11294.46 3667.93 12495.95 6284.20 7894.39 6193.23 126
DSMNet-mixed57.77 43056.90 43260.38 45167.70 47235.61 48269.18 45653.97 48332.30 48157.49 45879.88 41940.39 42568.57 47538.78 46372.37 40076.97 457
tpm273.26 34271.46 34578.63 32883.34 35456.71 38680.65 36880.40 40056.63 43973.55 32482.02 39751.80 32091.24 29256.35 38578.42 32487.95 336
NP-MVS89.62 12968.32 13590.24 184
EG-PatchMatch MVS74.04 32771.82 34180.71 28284.92 31767.42 16885.86 25588.08 26566.04 33964.22 43083.85 36035.10 44892.56 23157.44 37280.83 29282.16 439
tpm cat170.57 37268.31 37877.35 35982.41 38357.95 36578.08 40780.22 40352.04 45268.54 38577.66 43952.00 31487.84 36451.77 40672.07 40586.25 380
SteuartSystems-ACMMP88.72 1488.86 1488.32 992.14 7872.96 2593.73 593.67 2580.19 1288.10 4294.80 2773.76 3797.11 1887.51 4695.82 2594.90 15
Skip Steuart: Steuart Systems R&D Blog.
CostFormer75.24 31573.90 31779.27 31882.65 37858.27 35980.80 36282.73 37161.57 39875.33 29283.13 37855.52 27591.07 30364.98 29778.34 32688.45 326
CR-MVSNet73.37 33771.27 35079.67 31181.32 40165.19 22675.92 42380.30 40159.92 41172.73 33581.19 40152.50 30386.69 37459.84 34677.71 33187.11 364
JIA-IIPM66.32 41062.82 42276.82 36477.09 44161.72 31865.34 47075.38 43858.04 43064.51 42862.32 47042.05 41586.51 37751.45 41069.22 41982.21 437
Patchmtry70.74 37069.16 37375.49 37780.72 40554.07 41974.94 43480.30 40158.34 42570.01 36681.19 40152.50 30386.54 37653.37 40071.09 41185.87 392
PatchT68.46 39567.85 38670.29 42680.70 40643.93 47072.47 44274.88 44160.15 40970.55 35776.57 44449.94 34581.59 42050.58 41374.83 38085.34 398
tpmrst72.39 35272.13 33973.18 40580.54 40849.91 44979.91 38279.08 41563.11 37971.69 34979.95 41855.32 27682.77 41465.66 29273.89 38886.87 369
BH-w/o78.21 25277.33 25780.84 27988.81 16765.13 22884.87 28287.85 27569.75 27674.52 31284.74 34261.34 21593.11 20758.24 36685.84 21684.27 413
tpm72.37 35471.71 34274.35 39182.19 38552.00 43279.22 38977.29 42964.56 36072.95 33383.68 36851.35 32483.26 41158.33 36575.80 36087.81 340
DELS-MVS85.41 7685.30 8085.77 7988.49 18267.93 15285.52 26893.44 3278.70 3483.63 11589.03 21974.57 2795.71 6680.26 12194.04 6793.66 102
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
BH-untuned79.47 21778.60 21882.05 24789.19 15465.91 20386.07 24988.52 25972.18 21075.42 28487.69 26161.15 22093.54 17360.38 34286.83 19586.70 374
RPMNet73.51 33470.49 36182.58 23781.32 40165.19 22675.92 42392.27 9357.60 43372.73 33576.45 44552.30 30695.43 7748.14 43377.71 33187.11 364
MVSTER79.01 23277.88 23882.38 24083.07 36364.80 24484.08 31088.95 24169.01 29878.69 20287.17 27854.70 28492.43 23874.69 19580.57 29789.89 277
CPTT-MVS83.73 11083.33 11884.92 11193.28 5370.86 7892.09 4190.38 17468.75 30379.57 18792.83 9760.60 23293.04 21380.92 11291.56 10290.86 228
GBi-Net78.40 24777.40 25481.40 26287.60 23163.01 29188.39 15489.28 22071.63 21975.34 28887.28 27154.80 28091.11 29762.72 31679.57 30790.09 264
PVSNet_Blended_VisFu82.62 13981.83 14984.96 10790.80 10169.76 9788.74 14091.70 13069.39 28278.96 19788.46 23965.47 15694.87 10774.42 19988.57 15590.24 256
PVSNet_BlendedMVS80.60 19080.02 18182.36 24188.85 16365.40 21686.16 24792.00 11369.34 28478.11 21986.09 31066.02 15194.27 13171.52 23182.06 27887.39 350
UnsupCasMVSNet_eth67.33 40165.99 40571.37 41873.48 45951.47 44075.16 43085.19 32865.20 35160.78 44580.93 40842.35 41077.20 44157.12 37553.69 46485.44 397
UnsupCasMVSNet_bld63.70 42061.53 42670.21 42773.69 45751.39 44172.82 44181.89 37855.63 44357.81 45771.80 46238.67 43478.61 43449.26 42552.21 46780.63 448
PVSNet_Blended80.98 17380.34 17282.90 21988.85 16365.40 21684.43 29892.00 11367.62 31778.11 21985.05 33666.02 15194.27 13171.52 23189.50 13889.01 304
FMVSNet569.50 38467.96 38474.15 39482.97 37055.35 40780.01 38082.12 37662.56 38963.02 43681.53 40036.92 44181.92 41948.42 42874.06 38685.17 403
test178.40 24777.40 25481.40 26287.60 23163.01 29188.39 15489.28 22071.63 21975.34 28887.28 27154.80 28091.11 29762.72 31679.57 30790.09 264
new_pmnet50.91 44150.29 44152.78 46268.58 47134.94 48463.71 47456.63 48239.73 47144.95 47365.47 46821.93 47258.48 48234.98 46856.62 45764.92 470
FMVSNet377.88 26376.85 26680.97 27786.84 26662.36 30586.52 23188.77 24771.13 23275.34 28886.66 29354.07 29091.10 30062.72 31679.57 30789.45 290
dp66.80 40565.43 40670.90 42579.74 42148.82 45375.12 43274.77 44259.61 41364.08 43277.23 44142.89 40780.72 42748.86 42766.58 42983.16 427
FMVSNet278.20 25377.21 25881.20 26987.60 23162.89 29787.47 18789.02 23671.63 21975.29 29487.28 27154.80 28091.10 30062.38 32279.38 31289.61 286
FMVSNet177.44 27476.12 28281.40 26286.81 26763.01 29188.39 15489.28 22070.49 25674.39 31487.28 27149.06 35891.11 29760.91 33878.52 31990.09 264
N_pmnet52.79 43853.26 43651.40 46378.99 4287.68 49769.52 4543.89 49651.63 45557.01 45974.98 45540.83 42265.96 47837.78 46464.67 43980.56 450
cascas76.72 28874.64 30582.99 21485.78 29365.88 20482.33 34189.21 22760.85 40372.74 33481.02 40447.28 36793.75 16267.48 27585.02 22689.34 294
BH-RMVSNet79.61 21278.44 22283.14 20589.38 14365.93 20284.95 28187.15 29573.56 17978.19 21789.79 19656.67 26893.36 18859.53 35086.74 19690.13 260
UGNet80.83 17779.59 19684.54 12488.04 20368.09 14489.42 10688.16 26276.95 7176.22 26689.46 20949.30 35493.94 14768.48 26790.31 12191.60 201
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
WTY-MVS75.65 30775.68 28675.57 37486.40 27956.82 38377.92 41182.40 37365.10 35376.18 26887.72 25963.13 18380.90 42660.31 34381.96 27989.00 306
XXY-MVS75.41 31275.56 28974.96 38383.59 34957.82 36880.59 36983.87 34866.54 33474.93 30588.31 24363.24 17780.09 42962.16 32676.85 34386.97 368
EC-MVSNet86.01 5886.38 5284.91 11289.31 14766.27 19492.32 3593.63 2679.37 2384.17 10291.88 12369.04 10995.43 7783.93 8193.77 6993.01 145
sss73.60 33373.64 32173.51 40082.80 37355.01 41176.12 42181.69 38162.47 39074.68 30985.85 31457.32 26078.11 43760.86 33980.93 28987.39 350
Test_1112_low_res76.40 29775.44 29179.27 31889.28 14958.09 36081.69 35087.07 29759.53 41572.48 33986.67 29261.30 21689.33 33660.81 34080.15 30290.41 248
1112_ss77.40 27676.43 27780.32 29189.11 16060.41 33983.65 31787.72 27962.13 39473.05 33086.72 28762.58 19089.97 32562.11 32880.80 29390.59 241
ab-mvs-re7.23 4589.64 4610.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 49586.72 2870.00 4980.00 4950.00 4940.00 4930.00 491
ab-mvs79.51 21578.97 21281.14 27188.46 18460.91 32983.84 31289.24 22670.36 25779.03 19688.87 22763.23 17890.21 32165.12 29582.57 27392.28 177
TR-MVS77.44 27476.18 28181.20 26988.24 19263.24 28684.61 29086.40 31267.55 31877.81 22786.48 30154.10 28993.15 20457.75 37082.72 27187.20 359
MDTV_nov1_ep13_2view37.79 48175.16 43055.10 44466.53 41149.34 35353.98 39687.94 337
MDTV_nov1_ep1369.97 36783.18 36053.48 42377.10 41880.18 40560.45 40569.33 37780.44 41048.89 36186.90 37351.60 40878.51 320
MIMVSNet168.58 39266.78 40273.98 39680.07 41451.82 43680.77 36484.37 33864.40 36359.75 45182.16 39536.47 44483.63 40642.73 45470.33 41486.48 378
MIMVSNet70.69 37169.30 37074.88 38584.52 32756.35 39475.87 42579.42 41064.59 35967.76 39282.41 38941.10 42081.54 42146.64 44081.34 28486.75 373
IterMVS-LS80.06 20679.38 20082.11 24685.89 29063.20 28886.79 21989.34 21374.19 16275.45 28386.72 28766.62 13892.39 24072.58 21976.86 34290.75 233
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet79.07 23177.70 24683.17 20487.60 23168.23 14184.40 30186.20 31667.49 31976.36 26386.54 29961.54 20990.79 31061.86 33087.33 18490.49 245
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref81.95 280
IterMVS74.29 32272.94 33078.35 33881.53 39563.49 28081.58 35182.49 37268.06 31469.99 36883.69 36751.66 32385.54 38965.85 29071.64 40786.01 387
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon83.11 13282.09 14386.15 7094.44 2370.92 7688.79 13592.20 10370.53 25179.17 19591.03 16164.12 16896.03 5568.39 26990.14 12591.50 206
MVS_111021_LR82.61 14082.11 14184.11 15488.82 16671.58 5785.15 27486.16 31774.69 14880.47 17791.04 15962.29 19590.55 31680.33 12090.08 12790.20 257
DP-MVS76.78 28774.57 30683.42 19293.29 5269.46 10488.55 14983.70 34963.98 37270.20 36288.89 22654.01 29294.80 11146.66 43881.88 28186.01 387
ACMMP++81.25 285
HQP-MVS82.61 14082.02 14584.37 13789.33 14466.98 18389.17 11692.19 10576.41 9077.23 24090.23 18560.17 23795.11 9477.47 15985.99 21191.03 221
QAPM80.88 17579.50 19885.03 10488.01 20668.97 11491.59 5192.00 11366.63 33375.15 29892.16 11557.70 25595.45 7563.52 30588.76 15290.66 237
Vis-MVSNetpermissive83.46 12082.80 12785.43 9090.25 11268.74 12190.30 8090.13 18676.33 9780.87 16992.89 9561.00 22394.20 13672.45 22690.97 11193.35 122
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet59.14 42857.67 43063.57 44781.65 39143.50 47171.73 44465.06 47039.59 47251.43 46757.73 47538.34 43682.58 41539.53 46073.95 38764.62 471
IS-MVSNet83.15 12982.81 12684.18 15389.94 12363.30 28591.59 5188.46 26079.04 3079.49 18892.16 11565.10 15994.28 13067.71 27291.86 9794.95 12
HyFIR lowres test77.53 27375.40 29383.94 17789.59 13066.62 18880.36 37388.64 25756.29 44176.45 26085.17 33257.64 25693.28 19061.34 33683.10 26691.91 192
EPMVS69.02 38868.16 38071.59 41679.61 42249.80 45177.40 41466.93 46562.82 38670.01 36679.05 42645.79 38677.86 43956.58 38375.26 37587.13 363
PAPM_NR83.02 13382.41 13484.82 11592.47 7666.37 19287.93 17491.80 12573.82 17177.32 23790.66 17167.90 12594.90 10470.37 24489.48 13993.19 132
TAMVS78.89 23777.51 25383.03 21287.80 21567.79 15784.72 28585.05 33267.63 31676.75 25287.70 26062.25 19690.82 30958.53 36287.13 18990.49 245
PAPR81.66 15980.89 16183.99 17490.27 11164.00 26186.76 22291.77 12868.84 30277.13 24789.50 20567.63 12794.88 10667.55 27488.52 15793.09 138
RPSCF73.23 34371.46 34578.54 33382.50 38059.85 34482.18 34482.84 37058.96 42071.15 35689.41 21345.48 39284.77 39858.82 35971.83 40691.02 223
Vis-MVSNet (Re-imp)78.36 24978.45 22178.07 34488.64 17851.78 43786.70 22379.63 40974.14 16475.11 29990.83 16761.29 21789.75 32958.10 36791.60 9992.69 158
test_040272.79 35170.44 36279.84 30488.13 19865.99 20185.93 25284.29 34165.57 34567.40 40085.49 32346.92 37092.61 22735.88 46774.38 38480.94 446
MVS_111021_HR85.14 8284.75 8786.32 6591.65 8572.70 3085.98 25090.33 17876.11 10382.08 14591.61 13871.36 6894.17 13981.02 11092.58 8292.08 189
CSCG86.41 5186.19 5887.07 5092.91 6772.48 3790.81 6693.56 2973.95 16783.16 12791.07 15875.94 2195.19 8979.94 12494.38 6293.55 114
PatchMatch-RL72.38 35370.90 35676.80 36588.60 17967.38 17179.53 38476.17 43762.75 38769.36 37682.00 39845.51 39084.89 39753.62 39880.58 29678.12 455
API-MVS81.99 15081.23 15484.26 15090.94 9770.18 9191.10 6389.32 21871.51 22478.66 20488.28 24465.26 15795.10 9764.74 29991.23 10787.51 348
Test By Simon64.33 166
TDRefinement67.49 39964.34 41176.92 36373.47 46061.07 32684.86 28382.98 36659.77 41258.30 45585.13 33326.06 46387.89 36347.92 43560.59 45281.81 442
USDC70.33 37668.37 37776.21 36880.60 40756.23 39579.19 39086.49 31060.89 40261.29 44385.47 32431.78 45589.47 33553.37 40076.21 35782.94 432
EPP-MVSNet83.40 12283.02 12284.57 12390.13 11464.47 25392.32 3590.73 16474.45 15579.35 19391.10 15669.05 10895.12 9272.78 21787.22 18694.13 74
PMMVS69.34 38668.67 37571.35 42075.67 44762.03 31275.17 42973.46 44750.00 45868.68 38179.05 42652.07 31378.13 43661.16 33782.77 26973.90 462
PAPM77.68 27076.40 27981.51 25887.29 25061.85 31583.78 31389.59 20564.74 35871.23 35488.70 23062.59 18993.66 16552.66 40387.03 19189.01 304
ACMMPcopyleft85.89 6585.39 7687.38 4493.59 4972.63 3392.74 2593.18 4476.78 7780.73 17293.82 7264.33 16696.29 4682.67 9990.69 11693.23 126
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
CNLPA78.08 25676.79 26881.97 25090.40 10971.07 7087.59 18484.55 33766.03 34072.38 34189.64 20157.56 25786.04 38359.61 34983.35 26188.79 315
PatchmatchNetpermissive73.12 34471.33 34878.49 33683.18 36060.85 33079.63 38378.57 41864.13 36671.73 34879.81 42151.20 32985.97 38457.40 37376.36 35688.66 320
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS86.43 4986.17 5987.24 4690.88 9970.96 7392.27 3794.07 1472.45 20485.22 7891.90 12269.47 9596.42 4483.28 8695.94 2394.35 63
F-COLMAP76.38 29874.33 31282.50 23889.28 14966.95 18688.41 15389.03 23564.05 37066.83 40688.61 23446.78 37392.89 21757.48 37178.55 31887.67 342
ANet_high50.57 44246.10 44663.99 44648.67 49139.13 47970.99 44980.85 38961.39 40031.18 48057.70 47617.02 47873.65 46731.22 47315.89 48879.18 453
wuyk23d16.82 45715.94 46019.46 47258.74 48131.45 48539.22 4833.74 4976.84 4886.04 4912.70 4911.27 49524.29 49110.54 49114.40 4902.63 488
OMC-MVS82.69 13881.97 14784.85 11488.75 17467.42 16887.98 17090.87 15974.92 14179.72 18591.65 13362.19 19893.96 14475.26 19286.42 20193.16 133
MG-MVS83.41 12183.45 11483.28 19792.74 7162.28 30888.17 16489.50 20875.22 12881.49 15692.74 10366.75 13695.11 9472.85 21691.58 10192.45 170
AdaColmapbinary80.58 19379.42 19984.06 16493.09 6368.91 11589.36 11088.97 24069.27 28675.70 27689.69 19857.20 26395.77 6463.06 31388.41 16087.50 349
uanet0.00 4620.00 4650.00 4760.00 4990.00 5010.00 4880.00 5000.00 4940.00 4950.00 4940.00 4980.00 4950.00 4940.00 4930.00 491
ITE_SJBPF78.22 33981.77 39060.57 33583.30 35669.25 28867.54 39587.20 27636.33 44587.28 37154.34 39474.62 38286.80 371
DeepMVS_CXcopyleft27.40 47140.17 49426.90 48824.59 49517.44 48723.95 48548.61 4829.77 48526.48 49018.06 48324.47 48428.83 484
TinyColmap67.30 40264.81 40974.76 38781.92 38956.68 38780.29 37581.49 38460.33 40656.27 46283.22 37524.77 46787.66 36745.52 44669.47 41779.95 451
MAR-MVS81.84 15380.70 16385.27 9491.32 8971.53 5889.82 8890.92 15669.77 27578.50 20886.21 30662.36 19494.52 12365.36 29392.05 9389.77 282
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
LF4IMVS64.02 41962.19 42369.50 42970.90 46853.29 42776.13 42077.18 43052.65 45158.59 45380.98 40523.55 47076.52 44653.06 40266.66 42878.68 454
MSDG73.36 33970.99 35480.49 28784.51 32865.80 20780.71 36786.13 31865.70 34365.46 42083.74 36444.60 39590.91 30851.13 41276.89 34184.74 409
LS3D76.95 28474.82 30383.37 19590.45 10767.36 17289.15 12086.94 30061.87 39769.52 37490.61 17451.71 32294.53 12246.38 44186.71 19788.21 333
CLD-MVS82.31 14481.65 15084.29 14588.47 18367.73 15885.81 25892.35 8775.78 11078.33 21486.58 29764.01 16994.35 12876.05 18087.48 18290.79 230
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS53.68 43651.64 43859.81 45265.08 47651.03 44369.48 45569.58 45841.46 46940.67 47672.32 46116.46 47970.00 47324.24 48065.42 43758.40 476
Gipumacopyleft45.18 44741.86 45055.16 46077.03 44251.52 43932.50 48580.52 39532.46 48027.12 48335.02 4849.52 48675.50 45622.31 48160.21 45338.45 483
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015