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
LTVRE_ROB93.87 197.93 298.16 397.26 2398.81 2393.86 2799.07 298.98 397.01 1198.92 598.78 1495.22 3298.61 15796.85 499.77 1299.31 38
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
3Dnovator+92.74 295.86 5195.77 6096.13 4896.81 13090.79 6696.30 4397.82 6196.13 2394.74 14997.23 8291.33 10499.16 6593.25 6498.30 16398.46 113
3Dnovator92.54 394.80 9194.90 8994.47 10995.47 22587.06 12096.63 2497.28 11491.82 10394.34 16097.41 7390.60 12698.65 15592.47 8598.11 18397.70 161
DeepC-MVS91.39 495.43 6095.33 7695.71 6697.67 9590.17 6793.86 12498.02 4287.35 19896.22 8997.99 4794.48 5099.05 8192.73 7799.68 1897.93 143
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
COLMAP_ROBcopyleft91.06 596.75 1796.62 2497.13 2698.38 5094.31 1296.79 2198.32 1396.69 1596.86 6197.56 6595.48 2298.77 13790.11 13199.44 5498.31 119
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
DeepPCF-MVS90.46 694.20 11493.56 13596.14 4795.96 20192.96 4089.48 26897.46 9385.14 22596.23 8895.42 17993.19 6998.08 20890.37 12198.76 12697.38 181
DeepC-MVS_fast89.96 793.73 12293.44 13894.60 10296.14 18387.90 10893.36 13497.14 12185.53 22293.90 17195.45 17791.30 10698.59 16189.51 14198.62 13397.31 184
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OpenMVScopyleft89.45 892.27 17292.13 16592.68 17394.53 26084.10 16195.70 5997.03 12682.44 25491.14 23796.42 12488.47 15598.38 18685.95 19697.47 21795.55 251
ACMM88.83 996.30 4296.07 4696.97 3198.39 4992.95 4194.74 8998.03 4090.82 12597.15 5196.85 10196.25 1499.00 9193.10 6899.33 6898.95 77
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
TAPA-MVS88.58 1092.49 16791.75 17394.73 9596.50 14989.69 7292.91 15097.68 7178.02 28692.79 19994.10 22690.85 11797.96 21284.76 21098.16 17796.54 207
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMH+88.43 1196.48 3096.82 1895.47 7498.54 3989.06 8395.65 6198.61 796.10 2498.16 2497.52 6896.90 898.62 15690.30 12599.60 3298.72 100
ACMH88.36 1296.59 2697.43 594.07 12198.56 3585.33 14996.33 3998.30 1694.66 3598.72 998.30 3697.51 598.00 21094.87 2199.59 3498.86 85
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMP88.15 1395.71 5395.43 7296.54 4298.17 6491.73 5594.24 10998.08 3289.46 14996.61 7296.47 12095.85 1799.12 7390.45 11799.56 4198.77 95
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PMVScopyleft87.21 1494.97 8195.33 7693.91 12898.97 1497.16 295.54 6595.85 19296.47 1893.40 18297.46 7195.31 2895.47 30186.18 19598.78 12489.11 335
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PLCcopyleft85.34 1590.40 20288.92 21894.85 9196.53 14890.02 6891.58 20796.48 16380.16 26886.14 30592.18 27085.73 21198.25 19776.87 28494.61 28696.30 224
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
OpenMVS_ROBcopyleft85.12 1689.52 21789.05 21490.92 22794.58 25981.21 19191.10 22093.41 24677.03 29293.41 18093.99 23283.23 22497.80 23079.93 25594.80 28293.74 293
PCF-MVS84.52 1789.12 22287.71 24093.34 14396.06 18785.84 14286.58 31197.31 10968.46 33193.61 17693.89 23387.51 17798.52 17367.85 32998.11 18395.66 244
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
HY-MVS82.50 1886.81 27285.93 27589.47 25393.63 27677.93 25394.02 11391.58 27475.68 29583.64 32193.64 23777.40 26497.42 24871.70 31592.07 31993.05 305
IB-MVS77.21 1983.11 29381.05 30589.29 26291.15 30575.85 27685.66 31586.00 30979.70 27182.02 33386.61 32848.26 35198.39 18477.84 27592.22 31793.63 295
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
PVSNet76.22 2082.89 29682.37 29584.48 31593.96 26964.38 34078.60 34088.61 28771.50 31784.43 31786.36 33274.27 27694.60 31269.87 32693.69 30094.46 274
PVSNet_070.34 2174.58 32372.96 32579.47 33090.63 31266.24 33373.26 34383.40 33263.67 34478.02 34478.35 34872.53 27889.59 34256.68 34560.05 35182.57 346
CMPMVSbinary68.83 2287.28 25885.67 27792.09 19588.77 33385.42 14890.31 24294.38 22870.02 32688.00 29093.30 24773.78 27794.03 32175.96 29196.54 24596.83 203
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
MVEpermissive59.87 2373.86 32572.65 32677.47 33387.00 34474.35 29361.37 35060.93 35567.27 33569.69 35186.49 33081.24 24672.33 35356.45 34683.45 34085.74 341
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
tfpn11187.60 25287.12 24989.04 26796.14 18373.09 30693.00 14585.31 31792.13 9093.26 18890.96 28863.42 31498.48 17872.87 30796.98 23195.56 247
conf0.0186.95 26886.04 26889.70 24995.99 19475.66 27993.28 13582.70 33488.81 16291.26 22788.01 31958.77 33397.89 21578.93 26396.60 23995.56 247
GSMVS94.75 267
test_part393.92 12191.83 10196.39 13099.44 2489.00 153
conf0.00286.95 26886.04 26889.70 24995.99 19475.66 27993.28 13582.70 33488.81 16291.26 22788.01 31958.77 33397.89 21578.93 26396.60 23995.56 247
thresconf0.0286.69 27386.04 26888.64 27695.99 19475.66 27993.28 13582.70 33488.81 16291.26 22788.01 31958.77 33397.89 21578.93 26396.60 23992.36 315
tfpn_n40086.69 27386.04 26888.64 27695.99 19475.66 27993.28 13582.70 33488.81 16291.26 22788.01 31958.77 33397.89 21578.93 26396.60 23992.36 315
tfpnconf86.69 27386.04 26888.64 27695.99 19475.66 27993.28 13582.70 33488.81 16291.26 22788.01 31958.77 33397.89 21578.93 26396.60 23992.36 315
tfpnview1186.69 27386.04 26888.64 27695.99 19475.66 27993.28 13582.70 33488.81 16291.26 22788.01 31958.77 33397.89 21578.93 26396.60 23992.36 315
tfpn100086.83 27186.23 26788.64 27695.53 22375.25 28693.57 12982.28 34189.27 15491.46 22389.24 31057.22 34197.86 22480.63 24696.88 23392.81 308
test_part298.21 6189.41 7696.72 66
tfpn_ndepth85.85 28085.15 28187.98 28695.19 23775.36 28592.79 15383.18 33386.97 20589.92 25886.43 33157.44 34097.85 22778.18 27296.22 25390.72 330
test_part198.14 2894.69 4499.10 9098.17 127
conf200view1187.41 25586.89 25388.97 26896.14 18373.09 30693.00 14585.31 31792.13 9093.26 18890.96 28863.42 31498.28 19271.27 31996.54 24595.56 247
thres100view90087.35 25786.89 25388.72 27396.14 18373.09 30693.00 14585.31 31792.13 9093.26 18890.96 28863.42 31498.28 19271.27 31996.54 24594.79 265
tfpnnormal94.27 11194.87 9192.48 18397.71 9080.88 19494.55 10195.41 20793.70 5296.67 6997.72 5991.40 10298.18 20487.45 17699.18 8398.36 115
tfpn200view987.05 26686.52 26288.67 27495.77 20972.94 30991.89 19086.00 30990.84 12392.61 20289.80 30263.93 31198.28 19271.27 31996.54 24594.79 265
view60088.32 23687.94 23589.46 25496.49 15073.31 30093.95 11784.46 32793.02 6494.18 16192.68 25863.33 31898.56 16575.87 29297.50 21296.51 209
view80088.32 23687.94 23589.46 25496.49 15073.31 30093.95 11784.46 32793.02 6494.18 16192.68 25863.33 31898.56 16575.87 29297.50 21296.51 209
conf0.05thres100088.32 23687.94 23589.46 25496.49 15073.31 30093.95 11784.46 32793.02 6494.18 16192.68 25863.33 31898.56 16575.87 29297.50 21296.51 209
tfpn88.32 23687.94 23589.46 25496.49 15073.31 30093.95 11784.46 32793.02 6494.18 16192.68 25863.33 31898.56 16575.87 29297.50 21296.51 209
ESAPD95.42 6295.34 7495.68 6898.21 6189.41 7693.92 12198.14 2891.83 10196.72 6696.39 13094.69 4499.44 2489.00 15399.10 9098.17 127
CHOSEN 280x42080.04 31777.97 32186.23 30390.13 31974.53 29172.87 34589.59 28466.38 33776.29 34685.32 33556.96 34295.36 30469.49 32794.72 28388.79 337
CANet92.38 16991.99 16793.52 14193.82 27483.46 16791.14 21897.00 12889.81 14586.47 30394.04 22887.90 17299.21 6289.50 14298.27 16597.90 147
Fast-Effi-MVS+-dtu92.77 15892.16 16394.58 10594.66 25588.25 10392.05 18296.65 15489.62 14890.08 25391.23 28392.56 8198.60 15986.30 19496.27 25296.90 198
Effi-MVS+-dtu93.90 12092.60 15797.77 494.74 24996.67 494.00 11495.41 20789.94 14291.93 21992.13 27190.12 13398.97 9687.68 17397.48 21697.67 164
CANet_DTU89.85 21389.17 21291.87 20092.20 29880.02 21390.79 22795.87 19186.02 21582.53 32891.77 27680.01 25198.57 16485.66 19897.70 20497.01 193
MVS_030492.99 15192.54 15894.35 11594.67 25486.06 13991.16 21797.92 5590.01 14188.33 28694.41 21387.02 18999.22 6190.36 12299.00 10097.76 157
MP-MVS-pluss96.08 4795.92 5396.57 4199.06 991.21 5993.25 14198.32 1387.89 19096.86 6197.38 7595.55 2199.39 4195.47 1399.47 4899.11 52
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HSP-MVS95.18 7494.49 10197.23 2498.67 2794.05 1896.41 3797.00 12891.26 11695.12 13495.15 18686.60 20299.50 1893.43 5896.81 23498.13 132
sam_mvs166.64 29994.75 267
sam_mvs66.41 300
semantic-postprocess91.94 19893.89 27179.22 23793.51 24491.53 11395.37 12596.62 11377.17 26698.90 10391.89 9994.95 27897.70 161
TSAR-MVS + MP.94.96 8294.75 9295.57 7198.86 2088.69 9096.37 3896.81 14685.23 22394.75 14897.12 8991.85 9499.40 3693.45 5698.33 15898.62 106
xiu_mvs_v1_base_debu91.47 18491.52 17691.33 21695.69 21481.56 18689.92 25696.05 18583.22 24291.26 22790.74 29291.55 9998.82 12389.29 14595.91 25793.62 296
OPM-MVS95.61 5695.45 6996.08 4998.49 4691.00 6192.65 15797.33 10890.05 14096.77 6596.85 10195.04 3698.56 16592.77 7499.06 9398.70 101
ACMMP_Plus96.21 4396.12 4296.49 4598.90 1791.42 5794.57 9898.03 4090.42 13596.37 7897.35 7995.68 1999.25 5994.44 3199.34 6698.80 92
ambc92.98 15596.88 12683.01 17495.92 5396.38 17096.41 7697.48 7088.26 15997.80 23089.96 13698.93 10598.12 133
MPTG96.47 3196.14 4097.47 1198.95 1594.05 1893.69 12897.62 7494.46 4096.29 8396.94 9493.56 5799.37 4594.29 3599.42 5698.99 70
MTGPAbinary97.62 74
mvs-test193.07 14991.80 17196.89 3594.74 24995.83 792.17 17995.41 20789.94 14289.85 26190.59 29890.12 13398.88 10987.68 17395.66 26295.97 234
Effi-MVS+92.79 15692.74 15392.94 15995.10 23883.30 16994.00 11497.53 8691.36 11589.35 27090.65 29794.01 5498.66 15387.40 17895.30 27296.88 200
xiu_mvs_v2_base89.00 22489.19 21188.46 28294.86 24374.63 28986.97 30495.60 19880.88 26387.83 29288.62 31391.04 11598.81 12882.51 22994.38 28891.93 322
xiu_mvs_v1_base91.47 18491.52 17691.33 21695.69 21481.56 18689.92 25696.05 18583.22 24291.26 22790.74 29291.55 9998.82 12389.29 14595.91 25793.62 296
new-patchmatchnet88.97 22590.79 19683.50 32094.28 26555.83 35085.34 31793.56 24386.18 21295.47 12195.73 16683.10 22596.51 27985.40 20098.06 18798.16 129
pmmvs696.80 1497.36 995.15 8599.12 787.82 11196.68 2397.86 5796.10 2498.14 2599.28 397.94 498.21 19991.38 11299.69 1599.42 27
pmmvs587.87 24487.14 24890.07 24493.26 28276.97 26788.89 28392.18 26573.71 30788.36 28593.89 23376.86 27196.73 27380.32 24796.81 23496.51 209
test_post190.21 2445.85 35665.36 30496.00 29379.61 258
test_post6.07 35565.74 30395.84 295
Fast-Effi-MVS+91.28 19090.86 19392.53 18295.45 22682.53 17789.25 27796.52 16185.00 22989.91 25988.55 31492.94 7398.84 12184.72 21195.44 26996.22 227
patchmatchnet-post91.71 27766.22 30297.59 243
Anonymous2023121197.78 398.31 296.16 4699.55 289.37 8098.40 598.89 498.75 299.48 399.62 298.70 299.40 3691.60 10599.84 599.71 3
pmmvs-eth3d91.54 18190.73 19893.99 12295.76 21187.86 11090.83 22693.98 23678.23 28594.02 16996.22 14682.62 23296.83 27086.57 18998.33 15897.29 185
GG-mvs-BLEND83.24 32185.06 35071.03 31794.99 8365.55 35474.09 34975.51 34944.57 35394.46 31459.57 34387.54 33484.24 342
xiu_mvs_v1_base_debi91.47 18491.52 17691.33 21695.69 21481.56 18689.92 25696.05 18583.22 24291.26 22790.74 29291.55 9998.82 12389.29 14595.91 25793.62 296
Anonymous2023120688.77 23088.29 22590.20 24396.31 17078.81 24589.56 26793.49 24574.26 30392.38 20895.58 17182.21 23395.43 30372.07 31198.75 12896.34 222
MTAPA96.65 2296.38 3197.47 1198.95 1594.05 1895.88 5597.62 7494.46 4096.29 8396.94 9493.56 5799.37 4594.29 3599.42 5698.99 70
MTMP54.62 356
gm-plane-assit87.08 34359.33 34671.22 31883.58 34097.20 25773.95 300
test9_res88.16 16898.40 14997.83 153
MVP-Stereo90.07 21288.92 21893.54 13996.31 17086.49 12790.93 22495.59 20179.80 26991.48 22295.59 16880.79 24897.39 25178.57 27191.19 32496.76 205
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST996.45 15689.46 7390.60 23396.92 13779.09 27990.49 24794.39 21691.31 10598.88 109
train_agg92.71 16091.83 16995.35 7696.45 15689.46 7390.60 23396.92 13779.37 27590.49 24794.39 21691.20 11198.88 10988.66 16198.43 14797.72 159
gg-mvs-nofinetune82.10 30281.02 30685.34 30887.46 34071.04 31694.74 8967.56 35396.44 1979.43 34298.99 645.24 35296.15 29067.18 33192.17 31888.85 336
Patchmatch-test187.28 25887.30 24487.22 29492.01 30271.98 31489.43 26988.11 29482.26 25688.71 28192.20 26978.65 25695.81 29680.99 24493.30 30393.87 290
Patchmatch-test86.10 27986.01 27486.38 30190.63 31274.22 29589.57 26686.69 30385.73 22189.81 26392.83 25265.24 30691.04 33577.82 27795.78 26193.88 289
test_896.37 15989.14 8290.51 23796.89 14179.37 27590.42 24994.36 21891.20 11198.82 123
MS-PatchMatch88.05 24287.75 23988.95 26993.28 28077.93 25387.88 29392.49 26275.42 29792.57 20493.59 24080.44 25094.24 32081.28 23892.75 31194.69 269
Patchmatch-RL test88.81 22988.52 22289.69 25195.33 23479.94 21686.22 31292.71 25878.46 28395.80 11294.18 22366.25 30195.33 30689.22 15098.53 14093.78 291
agg_prior392.56 16691.62 17495.35 7696.39 15889.45 7590.61 23296.82 14578.82 28290.03 25594.14 22590.72 12398.88 10988.66 16198.43 14797.72 159
cdsmvs_eth3d_5k23.35 33031.13 3310.00 3450.00 3590.00 3600.00 35195.58 2020.00 3550.00 35691.15 28493.43 610.00 3580.00 3550.00 3560.00 356
pcd_1.5k_mvsjas7.56 33310.09 3340.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.00 35790.77 1180.00 3580.00 3550.00 3560.00 356
pcd1.5k->3k41.03 32843.65 33033.18 34198.74 260.00 3600.00 35197.57 810.00 3550.00 3560.00 35797.01 60.00 3580.00 35599.52 4599.53 17
agg_prior192.60 16391.76 17295.10 8696.20 17888.89 8790.37 23996.88 14279.67 27290.21 25094.41 21391.30 10698.78 13388.46 16498.37 15697.64 166
agg_prior287.06 18298.36 15797.98 139
agg_prior96.20 17888.89 8796.88 14290.21 25098.78 133
tmp_tt37.97 32944.33 32918.88 34211.80 35621.54 35763.51 34945.66 3584.23 35251.34 35350.48 35159.08 33222.11 35544.50 35168.35 35013.00 352
canonicalmvs94.59 10094.69 9494.30 11695.60 22187.03 12195.59 6298.24 2291.56 11295.21 13392.04 27394.95 4198.66 15391.45 11097.57 21097.20 188
anonymousdsp96.74 1896.42 2997.68 798.00 7594.03 2196.97 1697.61 7787.68 19598.45 2198.77 1594.20 5299.50 1896.70 599.40 6199.53 17
alignmvs93.26 14192.85 14994.50 10795.70 21387.45 11393.45 13295.76 19491.58 11195.25 13092.42 26681.96 23798.72 14391.61 10497.87 19897.33 183
nrg03096.32 4096.55 2795.62 6997.83 8288.55 9695.77 5898.29 1892.68 7098.03 2797.91 5295.13 3398.95 9993.85 4399.49 4799.36 35
v14419293.20 14693.54 13692.16 19396.05 18878.26 25191.95 18597.14 12184.98 23095.96 10196.11 15187.08 18899.04 8493.79 4498.84 11399.17 46
FIs94.90 8595.35 7393.55 13798.28 5781.76 18495.33 7098.14 2893.05 6397.07 5397.18 8587.65 17499.29 5491.72 10199.69 1599.61 12
v192192093.26 14193.61 13392.19 19196.04 19178.31 25091.88 19297.24 11685.17 22496.19 9396.19 14886.76 19899.05 8194.18 3998.84 11399.22 43
UA-Net97.35 597.24 1397.69 598.22 6093.87 2698.42 498.19 2496.95 1295.46 12399.23 493.45 5999.57 1395.34 1799.89 499.63 10
v119293.49 13093.78 12392.62 17696.16 18279.62 22691.83 20197.22 11886.07 21496.10 9796.38 13387.22 18499.02 8894.14 4098.88 10899.22 43
FC-MVSNet-test95.32 6695.88 5593.62 13498.49 4681.77 18395.90 5498.32 1393.93 4897.53 3997.56 6588.48 15499.40 3692.91 7399.83 899.68 5
v114493.50 12993.81 12192.57 17896.28 17279.61 22791.86 19796.96 13286.95 20795.91 10896.32 13687.65 17498.96 9793.51 5298.88 10899.13 50
sosnet-low-res0.00 3350.00 3360.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.00 3570.00 3630.00 3580.00 3550.00 3560.00 356
HFP-MVS96.39 3896.17 3997.04 2898.51 4393.37 3596.30 4397.98 4592.35 8195.63 11796.47 12095.37 2499.27 5793.78 4599.14 8698.48 111
v14892.87 15593.29 14091.62 20796.25 17677.72 25791.28 21595.05 21189.69 14695.93 10596.04 15387.34 18298.38 18690.05 13497.99 19298.78 94
sosnet0.00 3350.00 3360.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.00 3570.00 3630.00 3580.00 3550.00 3560.00 356
v74896.51 2897.05 1594.89 9098.35 5585.82 14396.58 2797.47 9296.25 2198.46 1998.35 3393.27 6799.33 5295.13 1999.59 3499.52 20
uncertanet0.00 3350.00 3360.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.00 3570.00 3630.00 3580.00 3550.00 3560.00 356
AllTest94.88 8794.51 10096.00 5098.02 7392.17 4595.26 7398.43 990.48 13295.04 14096.74 10892.54 8297.86 22485.11 20598.98 10197.98 139
TestCases96.00 5098.02 7392.17 4598.43 990.48 13295.04 14096.74 10892.54 8297.86 22485.11 20598.98 10197.98 139
v7n96.82 1197.31 1095.33 7898.54 3986.81 12496.83 1998.07 3596.59 1798.46 1998.43 3292.91 7499.52 1796.25 899.76 1399.65 9
v114193.42 13493.76 12592.40 18796.37 15979.24 23391.84 19896.38 17088.33 18195.86 11096.23 14387.41 18098.89 10592.61 8198.82 11999.08 59
region2R96.41 3696.09 4497.38 1998.62 2993.81 3196.32 4097.96 4992.26 8495.28 12896.57 11695.02 3899.41 3293.63 4999.11 8998.94 78
testing_294.03 11794.38 10393.00 15496.79 13281.41 18992.87 15296.96 13285.88 21897.06 5697.92 5091.18 11498.71 14891.72 10199.04 9898.87 84
test_normal91.49 18391.44 18091.62 20795.21 23579.44 22990.08 25193.84 23882.60 25094.37 15994.74 20586.66 20098.46 18188.58 16396.92 23296.95 196
v1neww93.58 12793.92 11892.56 17996.64 14179.77 22192.50 16496.41 16588.55 17495.93 10596.24 14188.08 16598.87 11592.45 8798.50 14499.05 63
PS-MVSNAJss96.01 4996.04 4895.89 5798.82 2288.51 9895.57 6397.88 5688.72 16998.81 798.86 1090.77 11899.60 895.43 1499.53 4399.57 15
PS-MVSNAJ88.86 22888.99 21788.48 28194.88 24174.71 28786.69 30895.60 19880.88 26387.83 29287.37 32690.77 11898.82 12382.52 22894.37 28991.93 322
jajsoiax96.59 2696.42 2997.12 2798.76 2592.49 4496.44 3597.42 9586.96 20698.71 1098.72 1795.36 2699.56 1695.92 1099.45 5299.32 37
mvs_tets96.83 1096.71 2197.17 2598.83 2192.51 4396.58 2797.61 7787.57 19698.80 898.90 996.50 1199.59 1296.15 999.47 4899.40 31
#test#95.89 5095.51 6697.04 2898.51 4393.37 3595.14 7597.98 4589.34 15195.63 11796.47 12095.37 2499.27 5791.99 9599.14 8698.48 111
EI-MVSNet-UG-set94.35 10894.27 11094.59 10392.46 29285.87 14192.42 16994.69 22293.67 5696.13 9595.84 16191.20 11198.86 11893.78 4598.23 17099.03 66
EI-MVSNet-Vis-set94.36 10794.28 10894.61 9892.55 29185.98 14092.44 16894.69 22293.70 5296.12 9695.81 16291.24 10898.86 11893.76 4898.22 17298.98 75
Regformer-394.28 11094.23 11294.46 11092.78 28986.28 13492.39 17094.70 22193.69 5595.97 10095.56 17391.34 10398.48 17893.45 5698.14 17998.62 106
Regformer-494.90 8594.67 9695.59 7092.78 28989.02 8492.39 17095.91 18994.50 3896.41 7695.56 17392.10 8899.01 9094.23 3798.14 17998.74 97
Regformer-194.55 10294.33 10695.19 8392.83 28788.54 9791.87 19395.84 19393.99 4595.95 10295.04 19392.00 9098.79 13093.14 6798.31 16098.23 123
Regformer-294.86 8894.55 9995.77 6292.83 28789.98 6991.87 19396.40 16794.38 4296.19 9395.04 19392.47 8599.04 8493.49 5398.31 16098.28 121
v7new93.58 12793.92 11892.56 17996.64 14179.77 22192.50 16496.41 16588.55 17495.93 10596.24 14188.08 16598.87 11592.45 8798.50 14499.05 63
HPM-MVS++95.02 7994.39 10296.91 3497.88 8093.58 3394.09 11296.99 13091.05 12192.40 20795.22 18591.03 11699.25 5992.11 9098.69 13197.90 147
test_prior489.91 7090.74 228
XVS96.49 2996.18 3897.44 1398.56 3593.99 2296.50 3197.95 5194.58 3694.38 15796.49 11894.56 4799.39 4193.57 5099.05 9598.93 79
v124093.29 13893.71 12992.06 19696.01 19277.89 25591.81 20297.37 9985.12 22696.69 6896.40 12686.67 19999.07 7894.51 2998.76 12699.22 43
test_prior393.29 13892.85 14994.61 9895.95 20287.23 11690.21 24497.36 10589.33 15290.77 24094.81 20090.41 12998.68 15188.21 16598.55 13797.93 143
v1894.63 9995.26 8192.74 16996.60 14479.81 21994.64 9497.37 9991.87 9797.26 4997.91 5288.13 16399.04 8494.30 3499.24 7699.38 32
pm-mvs195.43 6095.94 5193.93 12798.38 5085.08 15195.46 6797.12 12491.84 9997.28 4798.46 2895.30 2997.71 23890.17 12999.42 5698.99 70
test_prior290.21 24489.33 15290.77 24094.81 20090.41 12988.21 16598.55 137
X-MVStestdata90.70 19688.45 22397.44 1398.56 3593.99 2296.50 3197.95 5194.58 3694.38 15726.89 35294.56 4799.39 4193.57 5099.05 9598.93 79
test_prior94.61 9895.95 20287.23 11697.36 10598.68 15197.93 143
v1794.80 9195.46 6892.83 16596.76 13380.02 21394.85 8597.40 9792.23 8697.45 4398.04 4288.46 15699.06 7994.56 2799.40 6199.41 28
v1694.79 9395.44 7192.83 16596.73 13480.03 21194.85 8597.41 9692.23 8697.41 4698.04 4288.40 15899.06 7994.56 2799.30 7099.41 28
divwei89l23v2f11293.42 13493.76 12592.41 18596.37 15979.24 23391.84 19896.38 17088.33 18195.86 11096.23 14387.41 18098.89 10592.61 8198.83 11699.09 56
v1594.93 8395.62 6592.86 16496.83 12880.01 21594.84 8797.48 9192.36 7997.76 3598.20 3988.61 15299.11 7494.86 2299.62 2999.46 25
旧先验290.00 25468.65 33092.71 20196.52 27885.15 203
新几何290.02 253
新几何193.17 14997.16 11287.29 11594.43 22667.95 33291.29 22694.94 19786.97 19298.23 19881.06 24397.75 20093.98 286
旧先验196.20 17884.17 16094.82 21695.57 17289.57 14297.89 19796.32 223
无先验89.94 25595.75 19570.81 32398.59 16181.17 24194.81 264
原ACMM289.34 272
原ACMM192.87 16396.91 12584.22 15997.01 12776.84 29389.64 26694.46 21288.00 16998.70 14981.53 23698.01 19195.70 243
v1395.39 6396.12 4293.18 14897.22 10980.81 19695.55 6497.57 8193.42 5898.02 2998.49 2689.62 14199.18 6495.54 1299.68 1899.54 16
v1295.29 6996.02 5093.10 15097.14 11580.63 19795.39 6897.55 8593.19 6197.98 3098.44 3089.40 14499.16 6595.38 1699.67 2199.52 20
test22296.95 12185.27 15088.83 28493.61 24165.09 34190.74 24294.85 19984.62 21997.36 22193.91 287
testdata298.03 20980.24 250
segment_acmp92.14 87
testdata91.03 22396.87 12782.01 18094.28 23071.55 31692.46 20595.42 17985.65 21397.38 25382.64 22797.27 22393.70 294
testdata188.96 28288.44 178
v894.65 9895.29 7892.74 16996.65 13779.77 22194.59 9597.17 12091.86 9897.47 4297.93 4988.16 16299.08 7694.32 3299.47 4899.38 32
131486.46 27786.33 26586.87 29791.65 30374.54 29091.94 18794.10 23374.28 30284.78 31487.33 32783.03 22695.00 31078.72 26991.16 32591.06 328
112190.26 20889.23 21093.34 14397.15 11487.40 11491.94 18794.39 22767.88 33391.02 23894.91 19886.91 19598.59 16181.17 24197.71 20394.02 285
LFMVS91.33 18991.16 18991.82 20196.27 17379.36 23195.01 8185.61 31496.04 2794.82 14697.06 9272.03 28198.46 18184.96 20898.70 13097.65 165
v793.66 12393.97 11592.73 17196.55 14780.15 20492.54 15996.99 13087.36 19795.99 9996.48 11988.18 16098.94 10293.35 6198.31 16099.09 56
v693.59 12693.93 11692.56 17996.65 13779.77 22192.50 16496.40 16788.55 17495.94 10496.23 14388.13 16398.87 11592.46 8698.50 14499.06 62
VDD-MVS94.37 10694.37 10494.40 11397.49 10386.07 13893.97 11693.28 24794.49 3996.24 8797.78 5687.99 17098.79 13088.92 15599.14 8698.34 116
v1195.10 7795.88 5592.76 16896.98 12079.64 22595.12 7697.60 7992.64 7398.03 2798.44 3089.06 14999.15 6795.42 1599.67 2199.50 22
VDDNet94.03 11794.27 11093.31 14598.87 1982.36 17895.51 6691.78 27397.19 1096.32 8098.60 2084.24 22098.75 13887.09 18198.83 11698.81 91
v5296.93 897.29 1195.86 5898.12 6688.48 9997.69 797.74 6794.90 3398.55 1598.72 1793.39 6399.49 2196.92 299.62 2999.61 12
V1495.05 7895.75 6192.94 15996.94 12280.21 20295.03 8097.50 9092.62 7497.84 3398.28 3788.87 15199.13 7195.03 2099.64 2699.48 24
v1094.68 9795.27 8092.90 16296.57 14680.15 20494.65 9397.57 8190.68 12897.43 4498.00 4688.18 16099.15 6794.84 2499.55 4299.41 28
V496.93 897.29 1195.86 5898.11 6788.47 10097.69 797.74 6794.91 3198.55 1598.72 1793.37 6499.49 2196.92 299.62 2999.61 12
VPNet93.08 14793.76 12591.03 22398.60 3275.83 27891.51 20995.62 19791.84 9995.74 11497.10 9089.31 14598.32 19085.07 20799.06 9398.93 79
MVS84.98 28684.30 28587.01 29591.03 30677.69 25891.94 18794.16 23259.36 34784.23 31887.50 32585.66 21296.80 27171.79 31393.05 30986.54 340
v2v48293.29 13893.63 13292.29 18896.35 16778.82 24491.77 20596.28 17588.45 17795.70 11696.26 13986.02 20998.90 10393.02 7198.81 12299.14 49
v193.43 13293.77 12492.41 18596.37 15979.24 23391.84 19896.38 17088.33 18195.87 10996.22 14687.45 17898.89 10592.61 8198.83 11699.09 56
V4293.43 13293.58 13492.97 15695.34 23281.22 19092.67 15696.49 16287.25 20096.20 9196.37 13487.32 18398.85 12092.39 8998.21 17398.85 88
V995.17 7595.89 5493.02 15397.04 11880.42 19995.22 7497.53 8692.92 6897.90 3198.35 3389.15 14899.14 6995.21 1899.65 2599.50 22
SD-MVS95.19 7395.73 6293.55 13796.62 14388.88 8994.67 9198.05 3791.26 11697.25 5096.40 12695.42 2394.36 31792.72 7899.19 8197.40 178
GA-MVS87.70 24886.82 25590.31 23693.27 28177.22 26384.72 32292.79 25685.11 22789.82 26290.07 29966.80 29697.76 23584.56 21294.27 29295.96 235
MSLP-MVS++93.25 14393.88 12091.37 21596.34 16882.81 17593.11 14397.74 6789.37 15094.08 16795.29 18490.40 13196.35 28890.35 12398.25 16894.96 262
APDe-MVS96.46 3296.64 2395.93 5597.68 9489.38 7996.90 1898.41 1192.52 7697.43 4497.92 5095.11 3499.50 1894.45 3099.30 7098.92 82
APD-MVS_3200maxsize96.82 1196.65 2297.32 2297.95 7993.82 2996.31 4198.25 1995.51 3096.99 5997.05 9395.63 2099.39 4193.31 6298.88 10898.75 96
ADS-MVSNet284.01 29182.20 29789.41 25989.04 33076.37 27087.57 29590.98 27972.71 31384.46 31592.45 26268.08 28996.48 28070.58 32483.97 33795.38 254
EI-MVSNet92.99 15193.26 14492.19 19192.12 30079.21 23892.32 17394.67 22491.77 10695.24 13195.85 15987.14 18798.49 17591.99 9598.26 16698.86 85
Regformer0.00 3350.00 3360.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.00 3570.00 3630.00 3580.00 3550.00 3560.00 356
CVMVSNet85.16 28484.72 28286.48 29992.12 30070.19 31892.32 17388.17 29356.15 34990.64 24495.85 15967.97 29196.69 27488.78 15890.52 32792.56 312
pmmvs488.95 22687.70 24192.70 17294.30 26485.60 14687.22 30192.16 26774.62 29989.75 26594.19 22277.97 26196.41 28482.71 22696.36 25196.09 230
EU-MVSNet87.39 25686.71 25889.44 25893.40 27976.11 27394.93 8490.00 28357.17 34895.71 11597.37 7664.77 30897.68 24092.67 7994.37 28994.52 272
VNet92.67 16192.96 14691.79 20296.27 17380.15 20491.95 18594.98 21292.19 8994.52 15596.07 15287.43 17997.39 25184.83 20998.38 15197.83 153
test-LLR83.58 29283.17 29284.79 31389.68 32366.86 33083.08 32784.52 32583.07 24682.85 32684.78 33762.86 32393.49 32482.85 22494.86 27994.03 283
TESTMET0.1,179.09 31978.04 32082.25 32587.52 33864.03 34283.08 32780.62 34670.28 32580.16 34183.22 34244.13 35490.56 33879.95 25393.36 30192.15 320
test-mter81.21 30980.01 31584.79 31389.68 32366.86 33083.08 32784.52 32573.85 30682.85 32684.78 33743.66 35593.49 32482.85 22494.86 27994.03 283
VPA-MVSNet95.14 7695.67 6493.58 13697.76 8483.15 17194.58 9797.58 8093.39 5997.05 5798.04 4293.25 6898.51 17489.75 13899.59 3499.08 59
ACMMPR96.46 3296.14 4097.41 1798.60 3293.82 2996.30 4397.96 4992.35 8195.57 11996.61 11494.93 4299.41 3293.78 4599.15 8599.00 68
testgi90.38 20391.34 18487.50 29297.49 10371.54 31589.43 26995.16 21088.38 17994.54 15494.68 20892.88 7693.09 32771.60 31697.85 19997.88 149
test20.0390.80 19490.85 19490.63 23095.63 21979.24 23389.81 26292.87 25389.90 14494.39 15696.40 12685.77 21095.27 30873.86 30199.05 9597.39 179
thres600view787.66 25087.10 25189.36 26196.05 18873.17 30492.72 15485.31 31791.89 9693.29 18590.97 28763.42 31498.39 18473.23 30496.99 23096.51 209
111180.36 31581.32 30377.48 33294.61 25744.56 35381.59 33390.66 28186.78 20990.60 24593.52 24230.37 35890.67 33666.36 33397.42 21997.20 188
.test124564.72 32770.88 32846.22 34094.61 25744.56 35381.59 33390.66 28186.78 20990.60 24593.52 24230.37 35890.67 33666.36 3333.45 3543.44 354
ADS-MVSNet82.25 30081.55 30184.34 31689.04 33065.30 33487.57 29585.13 32372.71 31384.46 31592.45 26268.08 28992.33 33170.58 32483.97 33795.38 254
MP-MVScopyleft96.14 4595.68 6397.51 1098.81 2394.06 1696.10 4797.78 6692.73 6993.48 17996.72 11094.23 5199.42 2891.99 9599.29 7299.05 63
testmvs9.02 33211.42 3331.81 3442.77 3581.13 35979.44 3381.90 3591.18 3542.65 3556.80 3531.95 3620.87 3572.62 3543.45 3543.44 354
thres40087.20 26286.52 26289.24 26595.77 20972.94 30991.89 19086.00 30990.84 12392.61 20289.80 30263.93 31198.28 19271.27 31996.54 24596.51 209
test1239.49 33112.01 3321.91 3432.87 3571.30 35882.38 3301.34 3601.36 3532.84 3546.56 3542.45 3610.97 3562.73 3535.56 3533.47 353
thres20085.85 28085.18 28087.88 28994.44 26172.52 31189.08 27986.21 30688.57 17391.44 22488.40 31564.22 30998.00 21068.35 32895.88 26093.12 304
test0.0.03 182.48 29981.47 30285.48 30689.70 32273.57 29884.73 32081.64 34383.07 24688.13 28986.61 32862.86 32389.10 34566.24 33590.29 32893.77 292
test1235676.35 32177.41 32273.19 33790.70 31038.86 35674.56 34291.14 27674.55 30080.54 34088.18 31752.36 34890.49 34052.38 34992.26 31690.21 333
testus82.09 30381.78 29883.03 32292.35 29364.37 34179.44 33893.27 24873.08 31087.06 30085.21 33676.80 27289.27 34353.30 34795.48 26795.46 253
pmmvs380.83 31178.96 31886.45 30087.23 34177.48 25984.87 31982.31 34063.83 34385.03 31189.50 30949.66 34993.10 32673.12 30695.10 27688.78 338
testmv88.46 23388.11 23289.48 25296.00 19376.14 27286.20 31393.75 23984.48 23593.57 17795.52 17580.91 24795.09 30963.97 33898.61 13497.22 187
EMVS80.35 31680.28 31380.54 32884.73 35169.07 32272.54 34680.73 34587.80 19281.66 33581.73 34462.89 32289.84 34175.79 29694.65 28582.71 345
E-PMN80.72 31380.86 30880.29 32985.11 34968.77 32372.96 34481.97 34287.76 19383.25 32583.01 34362.22 32689.17 34477.15 28394.31 29182.93 344
test235675.58 32273.13 32482.95 32386.10 34666.42 33275.07 34184.87 32470.91 32180.85 33880.66 34538.02 35788.98 34649.32 35092.35 31593.44 300
test123567884.54 28783.85 28986.59 29893.81 27573.41 29982.38 33091.79 27279.43 27389.50 26791.61 28070.59 28492.94 32958.14 34497.40 22093.44 300
PGM-MVS96.32 4095.94 5197.43 1598.59 3493.84 2895.33 7098.30 1691.40 11495.76 11396.87 10095.26 3099.45 2392.77 7499.21 8099.00 68
LCM-MVSNet-Re94.20 11494.58 9893.04 15195.91 20583.13 17293.79 12599.19 292.00 9398.84 698.04 4293.64 5699.02 8881.28 23898.54 13996.96 195
LCM-MVSNet99.43 199.49 199.24 199.95 198.13 199.37 199.57 199.82 199.86 199.85 199.52 199.73 197.58 199.94 199.85 1
MCST-MVS92.91 15392.51 15994.10 12097.52 10185.72 14591.36 21497.13 12380.33 26792.91 19894.24 22091.23 10998.72 14389.99 13597.93 19597.86 151
mvs_anonymous90.37 20491.30 18587.58 29192.17 29968.00 32489.84 26194.73 22083.82 24093.22 19297.40 7487.54 17697.40 25087.94 17095.05 27797.34 182
MVS_Test92.57 16593.29 14090.40 23493.53 27875.85 27692.52 16196.96 13288.73 16892.35 20996.70 11190.77 11898.37 18992.53 8495.49 26696.99 194
MDA-MVSNet-bldmvs91.04 19190.88 19291.55 21094.68 25380.16 20385.49 31692.14 26890.41 13694.93 14495.79 16385.10 21596.93 26685.15 20394.19 29497.57 169
CDPH-MVS92.67 16191.83 16995.18 8496.94 12288.46 10190.70 23097.07 12577.38 28992.34 21195.08 19092.67 8098.88 10985.74 19798.57 13698.20 126
test1294.43 11295.95 20286.75 12596.24 17889.76 26489.79 14098.79 13097.95 19497.75 158
diffmvs90.45 20090.49 20090.34 23592.25 29577.09 26491.80 20495.96 18882.68 24985.83 30795.07 19187.01 19097.09 26089.68 13994.10 29596.83 203
YYNet188.17 24088.24 22787.93 28792.21 29773.62 29780.75 33688.77 28682.51 25394.99 14295.11 18982.70 23093.70 32283.33 22093.83 29796.48 217
PMMVS281.31 30783.44 29074.92 33590.52 31446.49 35269.19 34885.23 32284.30 23687.95 29194.71 20776.95 27084.36 35064.07 33798.09 18593.89 288
MDA-MVSNet_test_wron88.16 24188.23 22887.93 28792.22 29673.71 29680.71 33788.84 28582.52 25294.88 14595.14 18782.70 23093.61 32383.28 22193.80 29896.46 218
tpmvs84.22 29083.97 28784.94 31187.09 34265.18 33591.21 21688.35 28982.87 24885.21 30990.96 28865.24 30696.75 27279.60 25985.25 33692.90 307
PM-MVS93.33 13792.67 15595.33 7896.58 14594.06 1692.26 17692.18 26585.92 21796.22 8996.61 11485.64 21495.99 29490.35 12398.23 17095.93 236
HQP_MVS94.26 11293.93 11695.23 8297.71 9088.12 10594.56 9997.81 6291.74 10893.31 18395.59 16886.93 19398.95 9989.26 14898.51 14298.60 108
plane_prior797.71 9088.68 91
plane_prior697.21 11088.23 10486.93 193
plane_prior597.81 6298.95 9989.26 14898.51 14298.60 108
plane_prior495.59 168
plane_prior388.43 10290.35 13793.31 183
plane_prior294.56 9991.74 108
plane_prior197.38 105
plane_prior88.12 10593.01 14488.98 15798.06 187
PS-CasMVS96.69 2097.43 594.49 10899.13 584.09 16296.61 2597.97 4897.91 598.64 1398.13 4095.24 3199.65 393.39 5999.84 599.72 2
UniMVSNet_NR-MVSNet95.35 6595.21 8295.76 6397.69 9388.59 9492.26 17697.84 6094.91 3196.80 6395.78 16590.42 12899.41 3291.60 10599.58 3999.29 39
PEN-MVS96.69 2097.39 894.61 9899.16 384.50 15596.54 2998.05 3798.06 498.64 1398.25 3895.01 3999.65 392.95 7299.83 899.68 5
TransMVSNet (Re)95.27 7296.04 4892.97 15698.37 5281.92 18295.07 7896.76 15093.97 4797.77 3498.57 2195.72 1897.90 21388.89 15699.23 7899.08 59
DTE-MVSNet96.74 1897.43 594.67 9699.13 584.68 15496.51 3097.94 5498.14 398.67 1298.32 3595.04 3699.69 293.27 6399.82 1099.62 11
DU-MVS95.28 7095.12 8695.75 6497.75 8588.59 9492.58 15897.81 6293.99 4596.80 6395.90 15790.10 13699.41 3291.60 10599.58 3999.26 40
UniMVSNet (Re)95.32 6695.15 8495.80 6197.79 8388.91 8692.91 15098.07 3593.46 5796.31 8195.97 15690.14 13299.34 4992.11 9099.64 2699.16 47
CP-MVSNet96.19 4496.80 1994.38 11498.99 1383.82 16496.31 4197.53 8697.60 698.34 2297.52 6891.98 9299.63 693.08 7099.81 1199.70 4
WR-MVS_H96.60 2597.05 1595.24 8199.02 1186.44 13096.78 2298.08 3297.42 798.48 1897.86 5591.76 9699.63 694.23 3799.84 599.66 7
WR-MVS93.49 13093.72 12892.80 16797.57 9980.03 21190.14 24895.68 19693.70 5296.62 7195.39 18287.21 18599.04 8487.50 17599.64 2699.33 36
NR-MVSNet95.28 7095.28 7995.26 8097.75 8587.21 11895.08 7797.37 9993.92 4997.65 3795.90 15790.10 13699.33 5290.11 13199.66 2399.26 40
Baseline_NR-MVSNet94.47 10595.09 8792.60 17798.50 4580.82 19592.08 18196.68 15393.82 5096.29 8398.56 2290.10 13697.75 23690.10 13399.66 2399.24 42
TranMVSNet+NR-MVSNet96.07 4896.26 3595.50 7398.26 5887.69 11293.75 12697.86 5795.96 2897.48 4197.14 8795.33 2799.44 2490.79 11599.76 1399.38 32
TSAR-MVS + GP.93.07 14992.41 16195.06 8795.82 20790.87 6590.97 22292.61 26088.04 18794.61 15293.79 23688.08 16597.81 22989.41 14398.39 15096.50 216
abl_697.31 697.12 1497.86 398.54 3995.32 896.61 2598.35 1295.81 2997.55 3897.44 7296.51 1099.40 3694.06 4199.23 7898.85 88
n20.00 361
nn0.00 361
mPP-MVS96.46 3296.05 4797.69 598.62 2994.65 996.45 3397.74 6792.59 7595.47 12196.68 11294.50 4999.42 2893.10 6899.26 7498.99 70
door-mid92.13 269
DI_MVS_plusplus_test91.42 18791.41 18191.46 21295.34 23279.06 24090.58 23593.74 24082.59 25194.69 15194.76 20486.54 20398.44 18387.93 17196.49 25096.87 201
XVG-OURS-SEG-HR95.38 6495.00 8896.51 4398.10 6994.07 1592.46 16798.13 3190.69 12793.75 17396.25 14098.03 397.02 26392.08 9295.55 26498.45 114
DWT-MVSNet_test80.74 31279.18 31785.43 30787.51 33966.87 32989.87 26086.01 30874.20 30480.86 33780.62 34648.84 35096.68 27681.54 23583.14 34292.75 310
MVSFormer92.18 17392.23 16292.04 19794.74 24980.06 20997.15 1397.37 9988.98 15788.83 27492.79 25377.02 26899.60 896.41 696.75 23796.46 218
jason89.17 22188.32 22491.70 20595.73 21280.07 20888.10 29193.22 24971.98 31590.09 25292.79 25378.53 25798.56 16587.43 17797.06 22796.46 218
jason: jason.
lupinMVS88.34 23587.31 24391.45 21394.74 24980.06 20987.23 30092.27 26471.10 31988.83 27491.15 28477.02 26898.53 17286.67 18796.75 23795.76 240
test_djsdf96.62 2396.49 2897.01 3098.55 3891.77 5497.15 1397.37 9988.98 15798.26 2398.86 1093.35 6699.60 896.41 699.45 5299.66 7
Test491.41 18891.25 18691.89 19995.35 23180.32 20090.97 22296.92 13781.96 25795.11 13593.81 23581.34 24298.48 17888.71 16097.08 22696.87 201
HPM-MVS_fast97.01 796.89 1797.39 1899.12 793.92 2497.16 1298.17 2693.11 6296.48 7597.36 7896.92 799.34 4994.31 3399.38 6498.92 82
PatchFormer-LS_test82.62 29881.71 29985.32 30987.92 33467.31 32689.03 28088.20 29277.58 28883.79 32080.50 34760.96 33096.42 28383.86 21883.59 33992.23 319
testpf74.01 32476.37 32366.95 33880.56 35460.00 34588.43 29075.07 35181.54 26075.75 34883.73 33938.93 35683.09 35184.01 21579.32 34757.75 350
K. test v393.37 13693.27 14393.66 13398.05 7182.62 17694.35 10686.62 30496.05 2697.51 4098.85 1276.59 27399.65 393.21 6598.20 17598.73 99
lessismore_v093.87 13098.05 7183.77 16580.32 34797.13 5297.91 5277.49 26399.11 7492.62 8098.08 18698.74 97
SixPastTwentyTwo94.91 8495.21 8293.98 12398.52 4283.19 17095.93 5294.84 21594.86 3498.49 1798.74 1681.45 24099.60 894.69 2599.39 6399.15 48
OurMVSNet-221017-096.80 1496.75 2096.96 3299.03 1091.85 5297.98 698.01 4394.15 4498.93 499.07 588.07 16899.57 1395.86 1199.69 1599.46 25
HPM-MVS96.81 1396.62 2497.36 2098.89 1893.53 3497.51 998.44 892.35 8195.95 10296.41 12596.71 999.42 2893.99 4299.36 6599.13 50
XVG-OURS94.72 9594.12 11396.50 4498.00 7594.23 1391.48 21098.17 2690.72 12695.30 12796.47 12087.94 17196.98 26491.41 11197.61 20998.30 120
XVG-ACMP-BASELINE95.68 5495.34 7496.69 3998.40 4893.04 3894.54 10298.05 3790.45 13496.31 8196.76 10692.91 7498.72 14391.19 11399.42 5698.32 117
LPG-MVS_test96.38 3996.23 3696.84 3698.36 5392.13 4795.33 7098.25 1991.78 10497.07 5397.22 8396.38 1299.28 5592.07 9399.59 3499.11 52
LGP-MVS_train96.84 3698.36 5392.13 4798.25 1991.78 10497.07 5397.22 8396.38 1299.28 5592.07 9399.59 3499.11 52
test1196.65 154
door91.26 275
EPNet_dtu85.63 28284.37 28489.40 26086.30 34574.33 29491.64 20688.26 29084.84 23372.96 35089.85 30071.27 28397.69 23976.60 28697.62 20896.18 228
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268887.19 26385.92 27691.00 22697.13 11679.41 23084.51 32395.60 19864.14 34290.07 25494.81 20078.26 25997.14 25973.34 30395.38 27196.46 218
EPNet89.80 21488.25 22694.45 11183.91 35286.18 13693.87 12387.07 30291.16 12080.64 33994.72 20678.83 25498.89 10585.17 20198.89 10698.28 121
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS84.89 152
HQP-NCC96.36 16491.37 21187.16 20188.81 276
ACMP_Plane96.36 16491.37 21187.16 20188.81 276
APD-MVScopyleft95.00 8094.69 9495.93 5597.38 10590.88 6494.59 9597.81 6289.22 15595.46 12396.17 15093.42 6299.34 4989.30 14498.87 11197.56 171
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS86.55 190
HQP4-MVS88.81 27698.61 15798.15 130
HQP3-MVS97.31 10997.73 201
HQP2-MVS84.76 217
LP86.29 27885.35 27989.10 26687.80 33576.21 27189.92 25690.99 27884.86 23287.66 29492.32 26770.40 28596.48 28081.94 23182.24 34494.63 270
CNVR-MVS94.58 10194.29 10795.46 7596.94 12289.35 8191.81 20296.80 14789.66 14793.90 17195.44 17892.80 7898.72 14392.74 7698.52 14198.32 117
NCCC94.08 11693.54 13695.70 6796.49 15089.90 7192.39 17096.91 14090.64 12992.33 21294.60 20990.58 12798.96 9790.21 12897.70 20498.23 123
114514_t90.51 19889.80 20892.63 17598.00 7582.24 17993.40 13397.29 11265.84 33989.40 26994.80 20386.99 19198.75 13883.88 21798.61 13496.89 199
CP-MVS96.44 3596.08 4597.54 998.29 5694.62 1096.80 2098.08 3292.67 7295.08 13996.39 13094.77 4399.42 2893.17 6699.44 5498.58 110
DSMNet-mixed82.21 30181.56 30084.16 31789.57 32570.00 32090.65 23177.66 35054.99 35083.30 32497.57 6477.89 26290.50 33966.86 33295.54 26591.97 321
tpm281.46 30680.35 31284.80 31289.90 32165.14 33690.44 23885.36 31665.82 34082.05 33292.44 26457.94 33996.69 27470.71 32388.49 33292.56 312
NP-MVS96.82 12987.10 11993.40 245
EG-PatchMatch MVS94.54 10394.67 9694.14 11997.87 8186.50 12692.00 18496.74 15188.16 18696.93 6097.61 6393.04 7297.90 21391.60 10598.12 18298.03 136
tpm cat180.61 31479.46 31684.07 31888.78 33265.06 33889.26 27588.23 29162.27 34581.90 33489.66 30862.70 32595.29 30771.72 31480.60 34691.86 324
SteuartSystems-ACMMP96.40 3796.30 3396.71 3898.63 2891.96 5095.70 5998.01 4393.34 6096.64 7096.57 11694.99 4099.36 4793.48 5499.34 6698.82 90
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tpmp4_e2381.87 30580.41 31086.27 30289.29 32867.84 32591.58 20787.61 29867.42 33478.60 34392.71 25656.42 34496.87 26871.44 31788.63 33194.10 279
CostFormer83.09 29482.21 29685.73 30489.27 32967.01 32790.35 24086.47 30570.42 32483.52 32393.23 24861.18 32796.85 26977.21 28288.26 33393.34 303
CR-MVSNet87.89 24387.12 24990.22 24091.01 30778.93 24192.52 16192.81 25473.08 31089.10 27196.93 9667.11 29397.64 24188.80 15792.70 31294.08 280
JIA-IIPM85.08 28583.04 29391.19 22287.56 33786.14 13789.40 27184.44 33188.98 15782.20 33097.95 4856.82 34396.15 29076.55 28783.45 34091.30 326
Patchmtry90.11 21189.92 20790.66 22990.35 31877.00 26692.96 14892.81 25490.25 13894.74 14996.93 9667.11 29397.52 24485.17 20198.98 10197.46 174
PatchT87.51 25388.17 23085.55 30590.64 31166.91 32892.02 18386.09 30792.20 8889.05 27397.16 8664.15 31096.37 28789.21 15192.98 31093.37 302
tpmrst82.85 29782.93 29482.64 32487.65 33658.99 34790.14 24887.90 29575.54 29683.93 31991.63 27966.79 29895.36 30481.21 24081.54 34593.57 299
BH-w/o87.21 26187.02 25287.79 29094.77 24777.27 26287.90 29293.21 25181.74 25989.99 25788.39 31683.47 22296.93 26671.29 31892.43 31489.15 334
tpm84.38 28984.08 28685.30 31090.47 31563.43 34389.34 27285.63 31377.24 29187.62 29595.03 19561.00 32997.30 25479.26 26091.09 32695.16 256
DELS-MVS92.05 17592.16 16391.72 20494.44 26180.13 20787.62 29497.25 11587.34 19992.22 21493.18 24989.54 14398.73 14289.67 14098.20 17596.30 224
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-untuned90.68 19790.90 19190.05 24595.98 20079.57 22890.04 25294.94 21487.91 18894.07 16893.00 25087.76 17397.78 23279.19 26195.17 27592.80 309
RPMNet89.30 21989.00 21690.22 24091.01 30778.93 24192.52 16187.85 29691.91 9589.10 27196.89 9968.84 28897.64 24190.17 12992.70 31294.08 280
no-one87.84 24587.21 24689.74 24793.58 27778.64 24981.28 33592.69 25974.36 30192.05 21797.14 8781.86 23996.07 29272.03 31299.90 294.52 272
MVSTER89.32 21888.75 22191.03 22390.10 32076.62 26890.85 22594.67 22482.27 25595.24 13195.79 16361.09 32898.49 17590.49 11698.26 16697.97 142
CPTT-MVS94.74 9494.12 11396.60 4098.15 6593.01 3995.84 5697.66 7289.21 15693.28 18695.46 17688.89 15098.98 9289.80 13798.82 11997.80 156
GBi-Net93.21 14492.96 14693.97 12495.40 22784.29 15695.99 4896.56 15788.63 17095.10 13698.53 2381.31 24398.98 9286.74 18498.38 15198.65 102
PVSNet_Blended_VisFu91.63 17991.20 18792.94 15997.73 8983.95 16392.14 18097.46 9378.85 28192.35 20994.98 19684.16 22199.08 7686.36 19396.77 23695.79 239
PVSNet_BlendedMVS90.35 20589.96 20691.54 21194.81 24578.80 24690.14 24896.93 13579.43 27388.68 28395.06 19286.27 20698.15 20580.27 24898.04 18997.68 163
UnsupCasMVSNet_eth90.33 20690.34 20290.28 23794.64 25680.24 20189.69 26495.88 19085.77 22093.94 17095.69 16781.99 23692.98 32884.21 21491.30 32397.62 167
UnsupCasMVSNet_bld88.50 23288.03 23389.90 24695.52 22478.88 24387.39 29994.02 23579.32 27893.06 19394.02 23080.72 24994.27 31875.16 29893.08 30896.54 207
PVSNet_Blended88.74 23188.16 23190.46 23394.81 24578.80 24686.64 30996.93 13574.67 29888.68 28389.18 31186.27 20698.15 20580.27 24896.00 25594.44 275
FMVSNet587.82 24786.56 26091.62 20792.31 29479.81 21993.49 13194.81 21883.26 24191.36 22596.93 9652.77 34797.49 24676.07 28998.03 19097.55 172
test193.21 14492.96 14693.97 12495.40 22784.29 15695.99 4896.56 15788.63 17095.10 13698.53 2381.31 24398.98 9286.74 18498.38 15198.65 102
new_pmnet81.22 30881.01 30781.86 32690.92 30970.15 31984.03 32580.25 34870.83 32285.97 30689.78 30567.93 29284.65 34967.44 33091.90 32190.78 329
FMVSNet390.78 19590.32 20392.16 19393.03 28579.92 21792.54 15994.95 21386.17 21395.10 13696.01 15469.97 28798.75 13886.74 18498.38 15197.82 155
dp79.28 31878.62 31981.24 32785.97 34756.45 34986.91 30585.26 32172.97 31281.45 33689.17 31256.01 34695.45 30273.19 30576.68 34891.82 325
FMVSNet292.78 15792.73 15492.95 15895.40 22781.98 18194.18 11195.53 20488.63 17096.05 9897.37 7681.31 24398.81 12887.38 17998.67 13298.06 134
FMVSNet194.84 8995.13 8593.97 12497.60 9784.29 15695.99 4896.56 15792.38 7897.03 5898.53 2390.12 13398.98 9288.78 15899.16 8498.65 102
N_pmnet88.90 22787.25 24593.83 13194.40 26393.81 3184.73 32087.09 30179.36 27793.26 18892.43 26579.29 25391.68 33377.50 28097.22 22496.00 233
cascas87.02 26786.28 26689.25 26491.56 30476.45 26984.33 32496.78 14871.01 32086.89 30285.91 33381.35 24196.94 26583.09 22395.60 26394.35 277
BH-RMVSNet90.47 19990.44 20190.56 23195.21 23578.65 24889.15 27893.94 23788.21 18492.74 20094.22 22186.38 20497.88 22178.67 27095.39 27095.14 258
UGNet93.08 14792.50 16094.79 9493.87 27287.99 10795.07 7894.26 23190.64 12987.33 29897.67 6186.89 19698.49 17588.10 16998.71 12997.91 146
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-MVS86.93 27086.50 26488.24 28494.96 24074.64 28887.19 30292.07 27078.29 28488.32 28791.59 28178.06 26094.27 31874.88 29993.15 30695.80 238
XXY-MVS92.58 16493.16 14590.84 22897.75 8579.84 21891.87 19396.22 18185.94 21695.53 12097.68 6092.69 7994.48 31383.21 22297.51 21198.21 125
sss87.23 26086.82 25588.46 28293.96 26977.94 25286.84 30692.78 25777.59 28787.61 29691.83 27578.75 25591.92 33277.84 27594.20 29395.52 252
Test_1112_low_res87.50 25486.58 25990.25 23996.80 13177.75 25687.53 29896.25 17769.73 32786.47 30393.61 23975.67 27497.88 22179.95 25393.20 30495.11 259
1112_ss88.42 23487.41 24291.45 21396.69 13680.99 19389.72 26396.72 15273.37 30887.00 30190.69 29577.38 26598.20 20181.38 23793.72 29995.15 257
ab-mvs-re7.56 33310.08 3350.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 35690.69 2950.00 3630.00 3580.00 3550.00 3560.00 356
ab-mvs92.40 16892.62 15691.74 20397.02 11981.65 18595.84 5695.50 20586.95 20792.95 19797.56 6590.70 12497.50 24579.63 25797.43 21896.06 232
TR-MVS87.70 24887.17 24789.27 26394.11 26879.26 23288.69 28691.86 27181.94 25890.69 24389.79 30482.82 22997.42 24872.65 30991.98 32091.14 327
MDTV_nov1_ep13_2view42.48 35588.45 28967.22 33683.56 32266.80 29672.86 30894.06 282
MDTV_nov1_ep1383.88 28889.42 32761.52 34488.74 28587.41 29973.99 30584.96 31394.01 23165.25 30595.53 29878.02 27393.16 305
MIMVSNet195.52 5895.45 6995.72 6599.14 489.02 8496.23 4696.87 14493.73 5197.87 3298.49 2690.73 12299.05 8186.43 19299.60 3299.10 55
MIMVSNet87.13 26586.54 26188.89 27096.05 18876.11 27394.39 10488.51 28881.37 26188.27 28896.75 10772.38 27995.52 29965.71 33695.47 26895.03 260
IterMVS-LS93.78 12194.28 10892.27 18996.27 17379.21 23891.87 19396.78 14891.77 10696.57 7497.07 9187.15 18698.74 14191.99 9599.03 9998.86 85
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet89.55 21588.22 22993.53 14095.37 23086.49 12789.26 27593.59 24279.76 27091.15 23692.31 26877.12 26798.38 18677.51 27997.92 19695.71 242
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref98.82 119
IterMVS90.18 20990.16 20490.21 24293.15 28375.98 27587.56 29792.97 25286.43 21194.09 16696.40 12678.32 25897.43 24787.87 17294.69 28497.23 186
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon92.31 17091.88 16893.60 13597.18 11186.87 12391.10 22097.37 9984.92 23192.08 21694.08 22788.59 15398.20 20183.50 21998.14 17995.73 241
MVS_111021_LR93.66 12393.28 14294.80 9396.25 17690.95 6290.21 24495.43 20687.91 18893.74 17594.40 21592.88 7696.38 28690.39 11998.28 16497.07 191
DP-MVS95.62 5595.84 5794.97 8897.16 11288.62 9394.54 10297.64 7396.94 1396.58 7397.32 8093.07 7198.72 14390.45 11798.84 11397.57 169
ACMMP++99.25 75
HQP-MVS92.09 17491.49 17993.88 12996.36 16484.89 15291.37 21197.31 10987.16 20188.81 27693.40 24584.76 21798.60 15986.55 19097.73 20198.14 131
QAPM92.88 15492.77 15193.22 14795.82 20783.31 16896.45 3397.35 10783.91 23893.75 17396.77 10489.25 14698.88 10984.56 21297.02 22997.49 173
Vis-MVSNetpermissive95.50 5995.48 6795.56 7298.11 6789.40 7895.35 6998.22 2392.36 7994.11 16598.07 4192.02 8999.44 2493.38 6097.67 20697.85 152
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet78.83 32080.60 30973.51 33693.07 28447.37 35187.10 30378.00 34968.94 32977.53 34597.26 8171.45 28294.62 31163.28 34088.74 33078.55 348
IS-MVSNet94.49 10494.35 10594.92 8998.25 5986.46 12997.13 1594.31 22996.24 2296.28 8696.36 13582.88 22799.35 4888.19 16799.52 4598.96 76
HyFIR lowres test87.19 26385.51 27892.24 19097.12 11780.51 19885.03 31896.06 18466.11 33891.66 22192.98 25170.12 28699.14 6975.29 29795.23 27497.07 191
EPMVS81.17 31080.37 31183.58 31985.58 34865.08 33790.31 24271.34 35277.31 29085.80 30891.30 28259.38 33192.70 33079.99 25282.34 34392.96 306
PAPM_NR91.03 19290.81 19591.68 20696.73 13481.10 19293.72 12796.35 17488.19 18588.77 28092.12 27285.09 21697.25 25582.40 23093.90 29696.68 206
TAMVS90.16 21089.05 21493.49 14296.49 15086.37 13290.34 24192.55 26180.84 26592.99 19594.57 21181.94 23898.20 20173.51 30298.21 17395.90 237
PAPR87.65 25186.77 25790.27 23892.85 28677.38 26088.56 28896.23 17976.82 29484.98 31289.75 30686.08 20897.16 25872.33 31093.35 30296.26 226
RPSCF95.58 5794.89 9097.62 897.58 9896.30 595.97 5197.53 8692.42 7793.41 18097.78 5691.21 11097.77 23391.06 11497.06 22798.80 92
Vis-MVSNet (Re-imp)90.42 20190.16 20491.20 22197.66 9677.32 26194.33 10787.66 29791.20 11892.99 19595.13 18875.40 27598.28 19277.86 27499.19 8197.99 138
test_040295.73 5296.22 3794.26 11798.19 6385.77 14493.24 14297.24 11696.88 1497.69 3697.77 5894.12 5399.13 7191.54 10999.29 7297.88 149
MVS_111021_HR93.63 12593.42 13994.26 11796.65 13786.96 12289.30 27496.23 17988.36 18093.57 17794.60 20993.45 5997.77 23390.23 12798.38 15198.03 136
CSCG94.69 9694.75 9294.52 10697.55 10087.87 10995.01 8197.57 8192.68 7096.20 9193.44 24491.92 9398.78 13389.11 15299.24 7696.92 197
PatchMatch-RL89.18 22088.02 23492.64 17495.90 20692.87 4288.67 28791.06 27780.34 26690.03 25591.67 27883.34 22394.42 31576.35 28894.84 28190.64 331
API-MVS91.52 18291.61 17591.26 21994.16 26686.26 13594.66 9294.82 21691.17 11992.13 21591.08 28690.03 13997.06 26279.09 26297.35 22290.45 332
Test By Simon90.61 125
TDRefinement97.68 497.60 497.93 299.02 1195.95 698.61 398.81 597.41 897.28 4798.46 2894.62 4698.84 12194.64 2699.53 4398.99 70
USDC89.02 22389.08 21388.84 27195.07 23974.50 29288.97 28196.39 16973.21 30993.27 18796.28 13882.16 23496.39 28577.55 27898.80 12395.62 246
EPP-MVSNet93.91 11993.68 13194.59 10398.08 7085.55 14797.44 1094.03 23494.22 4394.94 14396.19 14882.07 23599.57 1387.28 18098.89 10698.65 102
PMMVS83.00 29581.11 30488.66 27583.81 35386.44 13082.24 33285.65 31261.75 34682.07 33185.64 33479.75 25291.59 33475.99 29093.09 30787.94 339
PAPM81.91 30480.11 31487.31 29393.87 27272.32 31384.02 32693.22 24969.47 32876.13 34789.84 30172.15 28097.23 25653.27 34889.02 32992.37 314
ACMMPcopyleft96.61 2496.34 3297.43 1598.61 3193.88 2596.95 1798.18 2592.26 8496.33 7996.84 10395.10 3599.40 3693.47 5599.33 6899.02 67
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
CNLPA91.72 17891.20 18793.26 14696.17 18191.02 6091.14 21895.55 20390.16 13990.87 23993.56 24186.31 20594.40 31679.92 25697.12 22594.37 276
PatchmatchNetpermissive85.22 28384.64 28386.98 29689.51 32669.83 32190.52 23687.34 30078.87 28087.22 29992.74 25566.91 29596.53 27781.77 23386.88 33594.58 271
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS94.34 10993.80 12295.95 5295.65 21791.67 5694.82 8897.86 5787.86 19193.04 19494.16 22491.58 9898.78 13390.27 12698.96 10497.41 176
F-COLMAP92.28 17191.06 19095.95 5297.52 10191.90 5193.53 13097.18 11983.98 23788.70 28294.04 22888.41 15798.55 17180.17 25195.99 25697.39 179
ANet_high94.83 9096.28 3490.47 23296.65 13773.16 30594.33 10798.74 696.39 2098.09 2698.93 893.37 6498.70 14990.38 12099.68 1899.53 17
PNet_i23d72.03 32670.91 32775.38 33490.46 31657.84 34871.73 34781.53 34483.86 23982.21 32983.49 34129.97 36087.80 34760.78 34154.12 35280.51 347
wuyk23d87.83 24690.79 19678.96 33190.46 31688.63 9292.72 15490.67 28091.65 11098.68 1197.64 6296.06 1577.53 35259.84 34299.41 6070.73 349
OMC-MVS94.22 11393.69 13095.81 6097.25 10891.27 5892.27 17597.40 9787.10 20494.56 15395.42 17993.74 5598.11 20786.62 18898.85 11298.06 134
MG-MVS89.54 21689.80 20888.76 27294.88 24172.47 31289.60 26592.44 26385.82 21989.48 26895.98 15582.85 22897.74 23781.87 23295.27 27396.08 231
wuykxyi23d96.76 1696.57 2697.34 2197.75 8596.73 394.37 10596.48 16391.00 12299.72 298.99 696.06 1598.21 19994.86 2299.90 297.09 190
AdaColmapbinary91.63 17991.36 18392.47 18495.56 22286.36 13392.24 17896.27 17688.88 16189.90 26092.69 25791.65 9798.32 19077.38 28197.64 20792.72 311
uanet0.00 3350.00 3360.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.00 3570.00 3630.00 3580.00 3550.00 3560.00 356
ITE_SJBPF95.95 5297.34 10793.36 3796.55 16091.93 9494.82 14695.39 18291.99 9197.08 26185.53 19997.96 19397.41 176
DeepMVS_CXcopyleft53.83 33970.38 35564.56 33948.52 35733.01 35165.50 35274.21 35056.19 34546.64 35438.45 35270.07 34950.30 351
TinyColmap92.00 17692.76 15289.71 24895.62 22077.02 26590.72 22996.17 18387.70 19495.26 12996.29 13792.54 8296.45 28281.77 23398.77 12595.66 244
MAR-MVS90.32 20788.87 22094.66 9794.82 24491.85 5294.22 11094.75 21980.91 26287.52 29788.07 31886.63 20197.87 22376.67 28596.21 25494.25 278
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
LF4IMVS92.72 15992.02 16694.84 9295.65 21791.99 4992.92 14996.60 15685.08 22892.44 20693.62 23886.80 19796.35 28886.81 18398.25 16896.18 228
MSDG90.82 19390.67 19991.26 21994.16 26683.08 17386.63 31096.19 18290.60 13191.94 21891.89 27489.16 14795.75 29780.96 24594.51 28794.95 263
LS3D96.11 4695.83 5896.95 3394.75 24894.20 1497.34 1197.98 4597.31 995.32 12696.77 10493.08 7099.20 6391.79 10098.16 17797.44 175
CLD-MVS91.82 17791.41 18193.04 15196.37 15983.65 16686.82 30797.29 11284.65 23492.27 21389.67 30792.20 8697.85 22783.95 21699.47 4897.62 167
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS84.50 28883.28 29188.16 28596.32 16994.49 1185.76 31485.47 31583.09 24585.20 31094.26 21963.79 31386.58 34863.72 33991.88 32283.40 343
Gipumacopyleft95.31 6895.80 5993.81 13297.99 7890.91 6396.42 3697.95 5196.69 1591.78 22098.85 1291.77 9595.49 30091.72 10199.08 9295.02 261
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015