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_ROB98.40 199.67 399.71 299.56 1899.85 1899.11 4199.90 199.78 599.63 1299.78 1099.67 2199.48 699.81 14299.30 3199.97 2399.77 16
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
3Dnovator98.27 298.81 6898.73 6799.05 10298.76 24297.81 13799.25 3299.30 13898.57 10398.55 17899.33 7297.95 7399.90 4797.16 13499.67 14799.44 134
3Dnovator+97.89 398.69 8798.51 9799.24 7798.81 23898.40 8799.02 5499.19 16998.99 7598.07 20199.28 7597.11 12699.84 10396.84 15299.32 21199.47 124
DeepC-MVS97.60 498.97 5498.93 5199.10 9299.35 12597.98 11898.01 14999.46 8297.56 16299.54 3599.50 4698.97 1899.84 10398.06 9399.92 4999.49 110
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepPCF-MVS96.93 598.32 13798.01 15799.23 7898.39 28498.97 5095.03 32199.18 17396.88 20999.33 7298.78 17198.16 5799.28 32896.74 15899.62 15599.44 134
DeepC-MVS_fast96.85 698.30 13998.15 14498.75 14498.61 26697.23 16597.76 17399.09 19297.31 18698.75 15798.66 18897.56 9099.64 25996.10 19899.55 18199.39 150
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
OpenMVScopyleft96.65 797.09 22496.68 22998.32 20298.32 28897.16 17298.86 7199.37 10789.48 33196.29 30199.15 10296.56 16399.90 4792.90 28199.20 22797.89 290
ACMH96.65 799.25 3099.24 3599.26 7599.72 3398.38 8999.07 5299.55 5498.30 11599.65 2399.45 5699.22 1099.76 19798.44 7699.77 10499.64 40
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH+96.62 999.08 4299.00 4999.33 6699.71 3498.83 5698.60 8399.58 3699.11 6199.53 3799.18 9298.81 2399.67 24496.71 16299.77 10499.50 103
COLMAP_ROBcopyleft96.50 1098.99 4998.85 5499.41 5299.58 5799.10 4298.74 7599.56 4999.09 6899.33 7299.19 9098.40 4399.72 22695.98 20299.76 11399.42 142
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TAPA-MVS96.21 1196.63 24495.95 25198.65 15398.93 21098.09 10496.93 23799.28 14183.58 34698.13 19897.78 26296.13 17999.40 31293.52 27099.29 21798.45 273
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMM96.08 1298.91 5998.73 6799.48 4499.55 7399.14 3498.07 13699.37 10797.62 15499.04 11698.96 14198.84 2199.79 17497.43 12599.65 15299.49 110
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
HY-MVS95.94 1395.90 25995.35 26497.55 24697.95 30494.79 24898.81 7496.94 30192.28 30795.17 32698.57 20589.90 27799.75 20391.20 31197.33 32198.10 285
OpenMVS_ROBcopyleft95.38 1495.84 26195.18 27097.81 23098.41 28397.15 17397.37 20998.62 25883.86 34598.65 16298.37 22494.29 23899.68 23888.41 32598.62 27496.60 330
ACMP95.32 1598.41 12998.09 15099.36 5699.51 8498.79 5997.68 18099.38 10395.76 24898.81 15298.82 16798.36 4599.82 12994.75 23399.77 10499.48 116
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PLCcopyleft94.65 1696.51 24895.73 25498.85 12998.75 24397.91 12596.42 26899.06 19590.94 32395.59 31497.38 28694.41 23599.59 27390.93 31498.04 30799.05 221
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PVSNet93.40 1795.67 26395.70 25595.57 30998.83 23388.57 32492.50 34397.72 28492.69 30196.49 29896.44 30693.72 25199.43 31093.61 26799.28 21898.71 260
PCF-MVS92.86 1894.36 29393.00 31198.42 19198.70 25297.56 15293.16 34199.11 19079.59 34997.55 24597.43 28392.19 26699.73 21779.85 34999.45 19797.97 289
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
IB-MVS91.63 1992.24 32090.90 32396.27 28697.22 33191.24 31894.36 33193.33 33792.37 30592.24 34494.58 34266.20 35699.89 5693.16 27794.63 34297.66 303
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
PMVScopyleft91.26 2097.86 17497.94 16297.65 23999.71 3497.94 12498.52 9198.68 25498.99 7597.52 24899.35 6897.41 10398.18 34891.59 30299.67 14796.82 327
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
PVSNet_089.98 2191.15 32590.30 32593.70 32997.72 31184.34 34690.24 34797.42 28890.20 32893.79 34093.09 34990.90 27398.89 34386.57 33172.76 35297.87 292
MVEpermissive83.40 2292.50 31791.92 31994.25 32398.83 23391.64 30492.71 34283.52 35595.92 24586.46 35395.46 32695.20 21295.40 35280.51 34898.64 27295.73 340
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CMPMVSbinary75.91 2396.29 25395.44 26298.84 13096.25 34598.69 6697.02 23299.12 18888.90 33497.83 22098.86 15989.51 27998.90 34291.92 29599.51 18998.92 237
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
tfpn11194.33 29493.78 29895.96 29999.06 18491.35 31398.03 14194.24 33098.33 11197.40 25794.98 33479.84 32799.68 23883.94 34098.22 28896.86 323
conf0.0194.82 28294.07 28897.06 26399.21 15094.53 25698.47 10392.69 33895.61 25097.81 22395.54 31977.71 33999.80 15491.49 30498.11 29596.86 323
GSMVS98.81 249
test_part397.25 21696.66 22098.71 17999.86 7793.00 279
conf0.00294.82 28294.07 28897.06 26399.21 15094.53 25698.47 10392.69 33895.61 25097.81 22395.54 31977.71 33999.80 15491.49 30498.11 29596.86 323
thresconf0.0294.70 28694.07 28896.58 27799.21 15094.53 25698.47 10392.69 33895.61 25097.81 22395.54 31977.71 33999.80 15491.49 30498.11 29595.42 342
tfpn_n40094.70 28694.07 28896.58 27799.21 15094.53 25698.47 10392.69 33895.61 25097.81 22395.54 31977.71 33999.80 15491.49 30498.11 29595.42 342
tfpnconf94.70 28694.07 28896.58 27799.21 15094.53 25698.47 10392.69 33895.61 25097.81 22395.54 31977.71 33999.80 15491.49 30498.11 29595.42 342
tfpnview1194.70 28694.07 28896.58 27799.21 15094.53 25698.47 10392.69 33895.61 25097.81 22395.54 31977.71 33999.80 15491.49 30498.11 29595.42 342
tfpn100094.81 28494.25 28796.47 28499.01 19893.47 28698.56 8792.30 34796.17 23597.90 21096.29 30876.70 34599.77 19293.02 27898.29 28496.16 334
test_part299.36 12199.10 4299.05 113
tfpn_ndepth94.12 30193.51 30595.94 30098.86 22593.60 28598.16 12791.90 34994.66 27497.41 25695.24 32976.24 34699.73 21791.21 31097.88 31094.50 347
test_part199.28 14197.56 9099.57 17299.53 91
conf200view1194.24 29793.67 30295.94 30099.06 18491.35 31398.03 14194.24 33098.33 11197.40 25794.98 33479.84 32799.62 26283.05 34298.08 30396.86 323
thres100view90094.19 29893.67 30295.75 30599.06 18491.35 31398.03 14194.24 33098.33 11197.40 25794.98 33479.84 32799.62 26283.05 34298.08 30396.29 331
tfpnnormal98.90 6098.90 5298.91 12199.67 4497.82 13599.00 5999.44 8899.45 2999.51 4399.24 8298.20 5599.86 7795.92 20499.69 13799.04 222
tfpn200view994.03 30393.44 30695.78 30498.93 21091.44 30797.60 19294.29 32897.94 12897.10 26894.31 34379.67 33199.62 26283.05 34298.08 30396.29 331
view60094.87 27794.41 27996.26 28799.22 14491.37 30998.49 9794.45 32398.75 8997.85 21595.98 31280.38 32299.75 20386.06 33398.49 27897.66 303
view80094.87 27794.41 27996.26 28799.22 14491.37 30998.49 9794.45 32398.75 8997.85 21595.98 31280.38 32299.75 20386.06 33398.49 27897.66 303
conf0.05thres100094.87 27794.41 27996.26 28799.22 14491.37 30998.49 9794.45 32398.75 8997.85 21595.98 31280.38 32299.75 20386.06 33398.49 27897.66 303
tfpn94.87 27794.41 27996.26 28799.22 14491.37 30998.49 9794.45 32398.75 8997.85 21595.98 31280.38 32299.75 20386.06 33398.49 27897.66 303
ESAPD98.25 14797.83 17099.50 4199.36 12199.10 4297.25 21699.28 14196.66 22099.05 11398.71 17997.56 9099.86 7793.00 27999.57 17299.53 91
CHOSEN 280x42095.51 26895.47 26095.65 30798.25 29088.27 32793.25 34098.88 22793.53 29294.65 33097.15 29386.17 29199.93 2697.41 12699.93 3998.73 259
CANet97.87 17397.76 17298.19 21297.75 31095.51 23496.76 24899.05 19997.74 14796.93 27598.21 23895.59 20299.89 5697.86 10499.93 3999.19 206
Fast-Effi-MVS+-dtu98.27 14398.09 15098.81 13398.43 28298.11 10397.61 19199.50 6598.64 9597.39 26097.52 27698.12 6099.95 1396.90 14898.71 26898.38 278
Effi-MVS+-dtu98.26 14597.90 16699.35 6198.02 30299.49 398.02 14899.16 18298.29 11897.64 23797.99 25396.44 17099.95 1396.66 16598.93 25998.60 267
CANet_DTU97.26 21397.06 20997.84 22997.57 31794.65 25396.19 28098.79 24397.23 19695.14 32798.24 23593.22 25399.84 10397.34 12899.84 7399.04 222
MVS_030498.02 16197.88 16898.46 18798.22 29596.39 20196.50 26299.49 7198.03 12697.24 26698.33 22994.80 22699.90 4798.31 8499.95 3099.08 217
MP-MVS-pluss98.57 10898.23 13499.60 1299.69 4299.35 997.16 22899.38 10394.87 27098.97 12698.99 13398.01 6699.88 6397.29 13099.70 13099.58 65
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HSP-MVS98.34 13597.94 16299.54 2599.57 6299.25 1898.57 8698.84 23497.55 16399.31 7997.71 26594.61 23199.88 6396.14 19799.19 23199.48 116
sam_mvs184.74 30398.81 249
sam_mvs84.29 309
semantic-postprocess96.87 27199.27 13491.16 31999.25 15299.10 6599.41 5899.35 6892.91 25999.96 898.65 6699.94 3399.49 110
TSAR-MVS + MP.98.63 9898.49 10299.06 10199.64 5097.90 12798.51 9598.94 21696.96 20599.24 9098.89 15597.83 7699.81 14296.88 14999.49 19599.48 116
xiu_mvs_v1_base_debu97.86 17498.17 13996.92 26898.98 20293.91 27496.45 26599.17 17997.85 14498.41 18797.14 29498.47 3999.92 3498.02 9599.05 24696.92 320
OPM-MVS98.56 10998.32 13099.25 7699.41 11598.73 6397.13 23099.18 17397.10 20398.75 15798.92 14698.18 5699.65 25796.68 16499.56 17999.37 157
ACMMP_Plus98.75 7598.48 10399.57 1699.58 5799.29 1397.82 16899.25 15296.94 20698.78 15399.12 10698.02 6599.84 10397.13 13899.67 14799.59 58
ambc98.24 20998.82 23695.97 21898.62 8199.00 21499.27 8299.21 8796.99 13399.50 29996.55 17599.50 19499.26 189
MPTG98.79 6998.52 9699.61 999.67 4499.36 797.33 21199.20 16398.83 8798.89 13898.90 15096.98 13499.92 3497.16 13499.70 13099.56 75
MTGPAbinary99.20 163
mvs-test197.83 18097.48 19098.89 12498.02 30299.20 2397.20 22299.16 18298.29 11896.46 29997.17 29196.44 17099.92 3496.66 16597.90 30997.54 313
Effi-MVS+98.02 16197.82 17198.62 15898.53 27697.19 16997.33 21199.68 1697.30 18796.68 28897.46 28198.56 3699.80 15496.63 16798.20 28998.86 244
xiu_mvs_v2_base97.16 22197.49 18796.17 29398.54 27492.46 29595.45 31298.84 23497.25 19197.48 25196.49 30398.31 4799.90 4796.34 18798.68 27096.15 336
xiu_mvs_v1_base97.86 17498.17 13996.92 26898.98 20293.91 27496.45 26599.17 17997.85 14498.41 18797.14 29498.47 3999.92 3498.02 9599.05 24696.92 320
new-patchmatchnet98.35 13498.74 6697.18 25999.24 13892.23 29996.42 26899.48 7498.30 11599.69 1799.53 4497.44 10199.82 12998.84 5899.77 10499.49 110
pmmvs699.67 399.70 399.60 1299.90 599.27 1699.53 999.76 799.64 1099.84 999.83 399.50 599.87 7299.36 2899.92 4999.64 40
pmmvs597.64 18897.49 18798.08 21999.14 17195.12 24496.70 25299.05 19993.77 28998.62 16898.83 16493.23 25299.75 20398.33 8399.76 11399.36 163
test_post197.59 19420.48 35683.07 31599.66 25294.16 249
test_post21.25 35583.86 31199.70 229
Fast-Effi-MVS+97.67 18697.38 19698.57 16898.71 24897.43 15997.23 21899.45 8594.82 27296.13 30396.51 30298.52 3899.91 4396.19 19298.83 26198.37 280
patchmatchnet-post98.77 17384.37 30699.85 88
Anonymous2023121199.71 299.70 399.74 299.97 299.52 299.74 499.82 499.73 699.91 499.89 299.27 999.94 2099.02 4999.94 3399.75 21
pmmvs-eth3d98.47 12498.34 12698.86 12899.30 13297.76 14097.16 22899.28 14195.54 25799.42 5799.19 9097.27 11299.63 26097.89 10099.97 2399.20 201
GG-mvs-BLEND94.76 31794.54 35192.13 30099.31 2080.47 35788.73 35191.01 35167.59 35398.16 34982.30 34794.53 34393.98 348
xiu_mvs_v1_base_debi97.86 17498.17 13996.92 26898.98 20293.91 27496.45 26599.17 17997.85 14498.41 18797.14 29498.47 3999.92 3498.02 9599.05 24696.92 320
Anonymous2023120698.21 15098.21 13598.20 21199.51 8495.43 23798.13 12899.32 12996.16 23898.93 13498.82 16796.00 18599.83 11797.32 12999.73 11899.36 163
MTAPA98.88 6198.64 8499.61 999.67 4499.36 798.43 11199.20 16398.83 8798.89 13898.90 15096.98 13499.92 3497.16 13499.70 13099.56 75
MTMP91.91 348
gm-plane-assit94.83 35081.97 35188.07 33794.99 33399.60 26991.76 297
test9_res93.28 27699.15 23799.38 156
MVP-Stereo98.08 15997.92 16498.57 16898.96 20596.79 18497.90 16099.18 17396.41 22898.46 18298.95 14295.93 19199.60 26996.51 17898.98 25699.31 178
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST998.71 24898.08 10795.96 28999.03 20391.40 31895.85 31097.53 27496.52 16599.76 197
train_agg97.10 22396.45 24199.07 9698.71 24898.08 10795.96 28999.03 20391.64 31295.85 31097.53 27496.47 16899.76 19793.67 26599.16 23499.36 163
gg-mvs-nofinetune92.37 31891.20 32295.85 30395.80 34992.38 29799.31 2081.84 35699.75 491.83 34599.74 868.29 35299.02 33787.15 32997.12 32396.16 334
Patchmatch-test196.44 25296.72 22595.60 30898.24 29288.35 32695.85 29896.88 30496.11 23997.67 23698.57 20593.10 25699.69 23394.79 23299.22 22498.77 255
Patchmatch-test96.55 24796.34 24497.17 26098.35 28693.06 28998.40 11397.79 28197.33 18398.41 18798.67 18683.68 31299.69 23395.16 22699.31 21398.77 255
test_898.67 25898.01 11395.91 29599.02 20791.64 31295.79 31297.50 27796.47 16899.76 197
MS-PatchMatch97.68 18597.75 17397.45 25198.23 29493.78 28097.29 21498.84 23496.10 24098.64 16498.65 19096.04 18299.36 31796.84 15299.14 23899.20 201
Patchmatch-RL test97.26 21397.02 21097.99 22699.52 8195.53 23396.13 28199.71 1297.47 16999.27 8299.16 9884.30 30899.62 26297.89 10099.77 10498.81 249
agg_prior396.95 23396.27 24699.00 11198.68 25597.91 12595.96 28999.01 21090.74 32495.60 31397.45 28296.14 17899.74 21293.67 26599.16 23499.36 163
cdsmvs_eth3d_5k24.66 33032.88 3310.00 3450.00 3590.00 3600.00 35199.10 1910.00 3550.00 35697.58 27299.21 110.00 3580.00 3550.00 3560.00 356
pcd_1.5k_mvsjas8.17 33310.90 3340.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.00 35798.07 610.00 3580.00 3550.00 3560.00 356
pcd1.5k->3k41.59 32944.35 33033.30 34299.87 120.00 3600.00 35199.58 360.00 3550.00 3560.00 35799.70 20.00 3580.00 35599.99 1199.91 2
agg_prior197.06 22696.40 24299.03 10598.68 25597.99 11495.76 30099.01 21091.73 31195.59 31497.50 27796.49 16799.77 19293.71 26499.14 23899.34 169
agg_prior292.50 29199.16 23499.37 157
agg_prior98.68 25597.99 11499.01 21095.59 31499.77 192
tmp_tt78.77 32878.73 32978.90 34058.45 35674.76 35694.20 33278.26 35839.16 35286.71 35292.82 35080.50 32175.19 35586.16 33292.29 34886.74 350
canonicalmvs98.34 13598.26 13398.58 16698.46 27997.82 13598.96 6399.46 8299.19 5497.46 25295.46 32698.59 3299.46 30698.08 9298.71 26898.46 272
anonymousdsp99.51 1299.47 1599.62 699.88 899.08 4699.34 1599.69 1598.93 8399.65 2399.72 1198.93 2099.95 1399.11 44100.00 199.82 10
alignmvs97.35 20696.88 21798.78 13898.54 27498.09 10497.71 17797.69 28699.20 5097.59 24195.90 31688.12 28699.55 28698.18 8998.96 25798.70 262
nrg03099.40 2199.35 2299.54 2599.58 5799.13 3798.98 6299.48 7499.68 799.46 5099.26 7998.62 3099.73 21799.17 4399.92 4999.76 19
v14419298.54 11698.57 9398.45 18999.21 15095.98 21797.63 18899.36 11197.15 20299.32 7799.18 9295.84 19699.84 10399.50 2299.91 5499.54 86
FIs99.14 3799.09 4599.29 6999.70 4098.28 9299.13 4699.52 6399.48 2599.24 9099.41 6196.79 14999.82 12998.69 6599.88 6499.76 19
v192192098.54 11698.60 9198.38 19899.20 15995.76 22797.56 19799.36 11197.23 19699.38 6299.17 9796.02 18399.84 10399.57 1899.90 5799.54 86
UA-Net99.47 1399.40 1799.70 399.49 9299.29 1399.80 399.72 1199.82 299.04 11699.81 498.05 6499.96 898.85 5699.99 1199.86 8
v119298.60 10598.66 8298.41 19299.27 13495.88 22397.52 20199.36 11197.41 17799.33 7299.20 8996.37 17499.82 12999.57 1899.92 4999.55 83
FC-MVSNet-test99.27 2999.25 3499.34 6499.77 2598.37 9099.30 2499.57 4399.61 1899.40 6099.50 4697.12 12499.85 8899.02 4999.94 3399.80 13
v114498.60 10598.66 8298.41 19299.36 12195.90 22297.58 19599.34 12197.51 16599.27 8299.15 10296.34 17599.80 15499.47 2499.93 3999.51 98
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-MVS98.71 8098.44 11299.51 3999.49 9299.16 2898.52 9199.31 13197.47 16998.58 17598.50 21697.97 7199.85 8896.57 17199.59 16299.53 91
v14898.45 12698.60 9198.00 22599.44 10994.98 24597.44 20799.06 19598.30 11599.32 7798.97 13896.65 15799.62 26298.37 8099.85 7199.39 150
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
v74899.44 1599.48 1399.33 6699.88 898.43 8699.42 1199.53 5999.63 1299.69 1799.60 3497.99 6999.91 4399.60 1499.96 2899.66 33
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
AllTest98.44 12798.20 13699.16 8499.50 8698.55 7698.25 11999.58 3696.80 21298.88 14199.06 11797.65 8499.57 28094.45 24299.61 15999.37 157
TestCases99.16 8499.50 8698.55 7699.58 3696.80 21298.88 14199.06 11797.65 8499.57 28094.45 24299.61 15999.37 157
v7n99.53 1099.57 1099.41 5299.88 898.54 7999.45 1099.61 3099.66 999.68 2099.66 2298.44 4299.95 1399.73 899.96 2899.75 21
v114198.63 9898.70 7498.41 19299.39 11795.96 21997.64 18599.21 15997.92 13099.35 6899.08 11196.61 16199.78 18399.25 3499.90 5799.50 103
region2R98.69 8798.40 11799.54 2599.53 7999.17 2698.52 9199.31 13197.46 17498.44 18498.51 21397.83 7699.88 6396.46 18199.58 16899.58 65
testing_298.93 5798.99 5098.76 14299.57 6297.03 17697.85 16599.13 18698.46 10799.44 5499.44 5798.22 5299.74 21298.85 5699.94 3399.51 98
test_normal97.58 19297.41 19298.10 21599.03 19495.72 22896.21 27797.05 29696.71 21798.65 16298.12 24493.87 24499.69 23397.68 11699.35 20698.88 242
v1neww98.70 8298.76 6398.52 17899.47 9996.30 20698.03 14199.18 17397.92 13099.26 8799.08 11196.91 13799.78 18399.19 4099.82 8299.47 124
PS-MVSNAJss99.46 1499.49 1299.35 6199.90 598.15 10099.20 3599.65 2099.48 2599.92 399.71 1498.07 6199.96 899.53 21100.00 199.93 1
PS-MVSNAJ97.08 22597.39 19596.16 29598.56 27192.46 29595.24 31798.85 23397.25 19197.49 25095.99 31198.07 6199.90 4796.37 18598.67 27196.12 337
jajsoiax99.58 899.61 799.48 4499.87 1298.61 7199.28 2999.66 1999.09 6899.89 899.68 1999.53 499.97 399.50 2299.99 1199.87 6
mvs_tets99.63 599.67 599.49 4399.88 898.61 7199.34 1599.71 1299.27 4599.90 599.74 899.68 399.97 399.55 2099.99 1199.88 5
#test#98.50 12198.16 14299.51 3999.49 9299.16 2898.03 14199.31 13196.30 23298.58 17598.50 21697.97 7199.85 8895.68 21899.59 16299.53 91
EI-MVSNet-UG-set98.69 8798.71 7198.62 15899.10 17496.37 20297.23 21898.87 22899.20 5099.19 9598.99 13397.30 10999.85 8898.77 6299.79 9699.65 37
EI-MVSNet-Vis-set98.68 9098.70 7498.63 15699.09 17796.40 20097.23 21898.86 23299.20 5099.18 9898.97 13897.29 11199.85 8898.72 6499.78 10099.64 40
Regformer-398.61 10498.61 8998.63 15699.02 19696.53 19397.17 22698.84 23499.13 6099.10 10598.85 16197.24 11799.79 17498.41 7999.70 13099.57 70
Regformer-498.73 7898.68 7998.89 12499.02 19697.22 16797.17 22699.06 19599.21 4799.17 9998.85 16197.45 10099.86 7798.48 7599.70 13099.60 52
Regformer-198.55 11398.44 11298.87 12698.85 22897.29 16296.91 24098.99 21598.97 7898.99 12298.64 19397.26 11599.81 14297.79 10599.57 17299.51 98
Regformer-298.60 10598.46 10899.02 10898.85 22897.71 14596.91 24099.09 19298.98 7799.01 11998.64 19397.37 10699.84 10397.75 11199.57 17299.52 96
v7new98.70 8298.76 6398.52 17899.47 9996.30 20698.03 14199.18 17397.92 13099.26 8799.08 11196.91 13799.78 18399.19 4099.82 8299.47 124
HPM-MVS++98.10 15797.64 18099.48 4499.09 17799.13 3797.52 20198.75 24897.46 17496.90 28097.83 26096.01 18499.84 10395.82 21299.35 20699.46 128
test_prior497.97 11995.86 296
XVS98.72 7998.45 11099.53 3299.46 10399.21 2198.65 7899.34 12198.62 9797.54 24698.63 19797.50 9599.83 11796.79 15499.53 18699.56 75
v124098.55 11398.62 8698.32 20299.22 14495.58 23197.51 20399.45 8597.16 20099.45 5399.24 8296.12 18099.85 8899.60 1499.88 6499.55 83
test_prior397.48 20097.00 21198.95 11598.69 25397.95 12295.74 30299.03 20396.48 22596.11 30497.63 27095.92 19299.59 27394.16 24999.20 22799.30 181
v1899.02 4699.17 3998.57 16899.45 10696.31 20498.94 6499.58 3699.06 7099.43 5599.58 3896.91 13799.80 15499.60 1499.97 2399.59 58
pm-mvs199.44 1599.48 1399.33 6699.80 2298.63 6899.29 2599.63 2599.30 4299.65 2399.60 3499.16 1699.82 12999.07 4699.83 7999.56 75
test_prior295.74 30296.48 22596.11 30497.63 27095.92 19294.16 24999.20 227
X-MVStestdata94.32 29592.59 31299.53 3299.46 10399.21 2198.65 7899.34 12198.62 9797.54 24645.85 35297.50 9599.83 11796.79 15499.53 18699.56 75
test_prior98.95 11598.69 25397.95 12299.03 20399.59 27399.30 181
v1799.07 4399.22 3698.61 16199.50 8696.42 19899.01 5599.60 3299.15 5699.48 4699.61 3097.05 12799.81 14299.64 1299.98 1999.61 49
v1699.07 4399.22 3698.61 16199.50 8696.42 19899.01 5599.60 3299.15 5699.46 5099.61 3097.04 12899.81 14299.64 1299.97 2399.61 49
divwei89l23v2f11298.63 9898.70 7498.41 19299.39 11795.96 21997.64 18599.21 15997.92 13099.35 6899.08 11196.61 16199.78 18399.25 3499.90 5799.50 103
v1599.11 4199.27 3398.62 15899.52 8196.43 19799.01 5599.63 2599.18 5599.59 3299.64 2697.13 12399.81 14299.71 10100.00 199.64 40
旧先验295.76 30088.56 33697.52 24899.66 25294.48 240
新几何295.93 293
新几何198.91 12198.94 20897.76 14098.76 24587.58 33996.75 28798.10 24694.80 22699.78 18392.73 28899.00 25399.20 201
旧先验198.82 23697.45 15898.76 24598.34 22795.50 20699.01 25299.23 195
无先验95.74 30298.74 25089.38 33299.73 21792.38 29399.22 199
原ACMM295.53 309
原ACMM198.35 20098.90 21896.25 20998.83 23992.48 30396.07 30798.10 24695.39 20999.71 22792.61 29098.99 25499.08 217
v1399.24 3199.39 1898.77 14099.63 5296.79 18499.24 3399.65 2099.39 3399.62 2799.70 1697.50 9599.84 10399.78 5100.00 199.67 31
v1299.21 3299.37 2098.74 14899.60 5596.72 18999.19 3999.65 2099.35 3999.62 2799.69 1797.43 10299.83 11799.76 6100.00 199.66 33
test22298.92 21496.93 18195.54 30898.78 24485.72 34396.86 28398.11 24594.43 23499.10 24599.23 195
testdata299.79 17492.80 286
segment_acmp97.02 131
testdata98.09 21698.93 21095.40 23898.80 24290.08 32997.45 25398.37 22495.26 21199.70 22993.58 26998.95 25899.17 211
testdata195.44 31396.32 230
v899.01 4799.16 4198.57 16899.47 9996.31 20498.90 6799.47 8099.03 7299.52 3999.57 3996.93 13699.81 14299.60 1499.98 1999.60 52
131495.74 26295.60 25996.17 29397.53 32092.75 29298.07 13698.31 26991.22 32094.25 33496.68 30095.53 20399.03 33691.64 30097.18 32296.74 328
112196.73 24196.00 24998.91 12198.95 20797.76 14098.07 13698.73 25187.65 33896.54 29298.13 24094.52 23399.73 21792.38 29399.02 25099.24 194
LFMVS97.20 21896.72 22598.64 15498.72 24696.95 18098.93 6694.14 33499.74 598.78 15399.01 13084.45 30599.73 21797.44 12499.27 21999.25 191
v798.67 9298.73 6798.50 18399.43 11396.21 21098.00 15099.31 13197.58 15899.17 9999.18 9296.63 15899.80 15499.42 2799.88 6499.48 116
v698.70 8298.76 6398.52 17899.47 9996.30 20698.03 14199.18 17397.92 13099.27 8299.08 11196.91 13799.78 18399.19 4099.82 8299.48 116
VDD-MVS98.56 10998.39 11999.07 9699.13 17298.07 10998.59 8597.01 29799.59 1999.11 10399.27 7794.82 22399.79 17498.34 8199.63 15499.34 169
v1199.12 4099.31 2898.53 17799.59 5696.11 21299.08 4999.65 2099.15 5699.60 3099.69 1797.26 11599.83 11799.81 3100.00 199.66 33
VDDNet98.21 15097.95 16099.01 10999.58 5797.74 14399.01 5597.29 29299.67 898.97 12699.50 4690.45 27599.80 15497.88 10299.20 22799.48 116
v5299.59 699.60 899.55 2099.87 1299.00 4799.59 799.56 4999.56 2299.68 2099.72 1198.57 3499.93 2699.85 199.99 1199.72 24
V1499.14 3799.30 3198.66 15299.56 6996.53 19399.08 4999.63 2599.24 4699.60 3099.66 2297.23 11999.82 12999.73 8100.00 199.65 37
v1098.97 5499.11 4498.55 17399.44 10996.21 21098.90 6799.55 5498.73 9399.48 4699.60 3496.63 15899.83 11799.70 1199.99 1199.61 49
V499.59 699.60 899.55 2099.87 1299.00 4799.59 799.56 4999.56 2299.68 2099.72 1198.57 3499.93 2699.85 199.99 1199.72 24
VPNet98.87 6298.83 5599.01 10999.70 4097.62 15198.43 11199.35 11799.47 2799.28 8099.05 12296.72 15499.82 12998.09 9199.36 20499.59 58
MVS93.19 31392.09 31796.50 28396.91 33594.03 27098.07 13698.06 27768.01 35094.56 33296.48 30495.96 19099.30 32583.84 34196.89 32796.17 333
v2v48298.56 10998.62 8698.37 19999.42 11495.81 22697.58 19599.16 18297.90 13899.28 8099.01 13095.98 18999.79 17499.33 2999.90 5799.51 98
v198.63 9898.70 7498.41 19299.39 11795.96 21997.64 18599.20 16397.92 13099.36 6699.07 11696.63 15899.78 18399.25 3499.90 5799.50 103
V4298.78 7298.78 6098.76 14299.44 10997.04 17598.27 11899.19 16997.87 14299.25 8999.16 9896.84 14499.78 18399.21 3899.84 7399.46 128
V999.18 3499.34 2498.70 14999.58 5796.63 19299.14 4499.64 2499.30 4299.61 2999.68 1997.33 10799.83 11799.75 7100.00 199.65 37
SD-MVS98.40 13198.68 7997.54 24798.96 20597.99 11497.88 16199.36 11198.20 12199.63 2699.04 12498.76 2495.33 35396.56 17499.74 11599.31 178
GA-MVS95.86 26095.32 26597.49 24998.60 26894.15 26893.83 33797.93 27995.49 25896.68 28897.42 28483.21 31399.30 32596.22 19098.55 27799.01 226
MSLP-MVS++98.02 16198.14 14697.64 24198.58 26995.19 24197.48 20499.23 15897.47 16997.90 21098.62 19997.04 12898.81 34597.55 11799.41 20098.94 235
APDe-MVS98.99 4998.79 5999.60 1299.21 15099.15 3398.87 6999.48 7497.57 16099.35 6899.24 8297.83 7699.89 5697.88 10299.70 13099.75 21
APD-MVS_3200maxsize98.84 6598.61 8999.53 3299.19 16099.27 1698.49 9799.33 12698.64 9599.03 11898.98 13697.89 7499.85 8896.54 17699.42 19999.46 128
ADS-MVSNet295.43 26994.98 27496.76 27598.14 29891.74 30297.92 15797.76 28290.23 32596.51 29598.91 14785.61 29799.85 8892.88 28296.90 32598.69 263
EI-MVSNet98.40 13198.51 9798.04 22399.10 17494.73 24997.20 22298.87 22898.97 7899.06 10899.02 12896.00 18599.80 15498.58 6899.82 8299.60 52
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
CVMVSNet96.25 25597.21 20393.38 33399.10 17480.56 35397.20 22298.19 27496.94 20699.00 12199.02 12889.50 28099.80 15496.36 18699.59 16299.78 15
pmmvs497.58 19297.28 20198.51 18298.84 23196.93 18195.40 31498.52 26193.60 29198.61 17098.65 19095.10 21599.60 26996.97 14499.79 9698.99 228
EU-MVSNet97.66 18798.50 9995.13 31399.63 5285.84 33598.35 11598.21 27198.23 12099.54 3599.46 5295.02 21699.68 23898.24 8599.87 6899.87 6
VNet98.42 12898.30 13198.79 13598.79 24197.29 16298.23 12098.66 25599.31 4198.85 14498.80 16994.80 22699.78 18398.13 9099.13 24199.31 178
test-LLR93.90 30693.85 29694.04 32496.53 34084.62 34394.05 33392.39 34596.17 23594.12 33695.07 33082.30 31799.67 24495.87 20898.18 29097.82 294
TESTMET0.1,192.19 32191.77 32093.46 33196.48 34282.80 35094.05 33391.52 35094.45 27994.00 33994.88 33866.65 35599.56 28395.78 21398.11 29598.02 288
test-mter92.33 31991.76 32194.04 32496.53 34084.62 34394.05 33392.39 34594.00 28894.12 33695.07 33065.63 35899.67 24495.87 20898.18 29097.82 294
VPA-MVSNet99.30 2899.30 3199.28 7099.49 9298.36 9199.00 5999.45 8599.63 1299.52 3999.44 5798.25 4899.88 6399.09 4599.84 7399.62 45
ACMMPR98.70 8298.42 11599.54 2599.52 8199.14 3498.52 9199.31 13197.47 16998.56 17798.54 21197.75 8199.88 6396.57 17199.59 16299.58 65
testgi98.32 13798.39 11998.13 21499.57 6295.54 23297.78 16999.49 7197.37 18099.19 9597.65 26998.96 1999.49 30096.50 17998.99 25499.34 169
test20.0398.78 7298.77 6298.78 13899.46 10397.20 16897.78 16999.24 15699.04 7199.41 5898.90 15097.65 8499.76 19797.70 11299.79 9699.39 150
thres600view794.45 29293.83 29796.29 28599.06 18491.53 30597.99 15194.24 33098.34 11097.44 25495.01 33279.84 32799.67 24484.33 33998.23 28697.66 303
111193.99 30493.72 30094.80 31699.33 12885.20 33995.97 28599.39 10097.88 14098.64 16498.56 20857.79 35999.80 15496.02 19999.87 6899.40 149
.test124579.71 32784.30 32865.96 34199.33 12885.20 33995.97 28599.39 10097.88 14098.64 16498.56 20857.79 35999.80 15496.02 19915.07 35312.86 354
ADS-MVSNet95.24 27194.93 27596.18 29298.14 29890.10 32197.92 15797.32 29190.23 32596.51 29598.91 14785.61 29799.74 21292.88 28296.90 32598.69 263
MP-MVScopyleft98.46 12598.09 15099.54 2599.57 6299.22 2098.50 9699.19 16997.61 15697.58 24298.66 18897.40 10499.88 6394.72 23699.60 16199.54 86
testmvs17.12 33120.53 3326.87 34412.05 3574.20 35993.62 3386.73 3594.62 35410.41 35424.33 3538.28 3623.56 3579.69 35415.07 35312.86 354
thres40094.14 30093.44 30696.24 29198.93 21091.44 30797.60 19294.29 32897.94 12897.10 26894.31 34379.67 33199.62 26283.05 34298.08 30397.66 303
test12317.04 33220.11 3337.82 34310.25 3584.91 35894.80 3254.47 3604.93 35310.00 35524.28 3549.69 3613.64 35610.14 35312.43 35514.92 353
thres20093.72 30893.14 30995.46 31098.66 26391.29 31796.61 25994.63 32297.39 17996.83 28493.71 34679.88 32699.56 28382.40 34698.13 29495.54 341
test0.0.03 194.51 29193.69 30196.99 26696.05 34693.61 28494.97 32293.49 33596.17 23597.57 24494.88 33882.30 31799.01 33993.60 26894.17 34698.37 280
test1235694.85 28195.12 27194.03 32698.25 29083.12 34893.85 33699.33 12694.17 28697.28 26497.20 28985.83 29599.75 20390.85 31799.33 20999.22 199
testus95.52 26695.32 26596.13 29797.91 30789.49 32393.62 33899.61 3092.41 30497.38 26295.42 32894.72 23099.63 26088.06 32798.72 26599.26 189
pmmvs395.03 27494.40 28396.93 26797.70 31492.53 29495.08 32097.71 28588.57 33597.71 23398.08 24979.39 33399.82 12996.19 19299.11 24498.43 275
testmv98.51 12098.47 10598.61 16199.24 13896.53 19396.66 25599.73 1098.56 10599.50 4499.23 8697.24 11799.87 7296.16 19599.93 3999.44 134
EMVS93.83 30794.02 29493.23 33496.83 33884.96 34189.77 34996.32 31397.92 13097.43 25596.36 30786.17 29198.93 34187.68 32897.73 31295.81 339
E-PMN94.17 29994.37 28493.58 33096.86 33685.71 33790.11 34897.07 29598.17 12497.82 22297.19 29084.62 30498.94 34089.77 32197.68 31396.09 338
test235691.64 32490.19 32796.00 29894.30 35289.58 32290.84 34696.68 30791.76 31095.48 32393.69 34767.05 35499.52 29384.83 33897.08 32498.91 239
test123567897.06 22696.84 22097.73 23598.55 27394.46 26294.80 32599.36 11196.85 21198.83 14798.26 23392.72 26299.82 12992.49 29299.70 13098.91 239
PGM-MVS98.66 9398.37 12299.55 2099.53 7999.18 2598.23 12099.49 7197.01 20498.69 16098.88 15698.00 6799.89 5695.87 20899.59 16299.58 65
LCM-MVSNet-Re98.64 9698.48 10399.11 9098.85 22898.51 8198.49 9799.83 398.37 10899.69 1799.46 5298.21 5499.92 3494.13 25399.30 21498.91 239
LCM-MVSNet99.93 199.92 199.94 199.99 199.97 199.90 199.89 299.98 199.99 199.96 199.77 1100.00 199.81 3100.00 199.85 9
MCST-MVS98.00 16497.63 18199.10 9299.24 13898.17 9996.89 24298.73 25195.66 24997.92 20797.70 26697.17 12299.66 25296.18 19499.23 22399.47 124
mvs_anonymous97.83 18098.16 14296.87 27198.18 29791.89 30197.31 21398.90 22597.37 18098.83 14799.46 5296.28 17699.79 17498.90 5398.16 29298.95 233
MVS_Test98.18 15398.36 12397.67 23798.48 27794.73 24998.18 12499.02 20797.69 15098.04 20499.11 10797.22 12199.56 28398.57 7098.90 26098.71 260
MDA-MVSNet-bldmvs97.94 16897.91 16598.06 22199.44 10994.96 24696.63 25799.15 18598.35 10998.83 14799.11 10794.31 23799.85 8896.60 16898.72 26599.37 157
CDPH-MVS97.26 21396.66 23299.07 9699.00 19998.15 10096.03 28399.01 21091.21 32197.79 22997.85 25996.89 14299.69 23392.75 28799.38 20399.39 150
test1298.93 11898.58 26997.83 13298.66 25596.53 29395.51 20599.69 23399.13 24199.27 186
diffmvs97.49 19797.36 19797.91 22798.38 28595.70 23097.95 15599.31 13194.87 27096.14 30298.78 17194.84 22299.43 31097.69 11498.26 28598.59 268
YYNet197.60 19097.67 17597.39 25599.04 19193.04 29195.27 31598.38 26797.25 19198.92 13598.95 14295.48 20799.73 21796.99 14398.74 26499.41 144
PMMVS298.07 16098.08 15398.04 22399.41 11594.59 25594.59 32999.40 9897.50 16698.82 15098.83 16496.83 14599.84 10397.50 12199.81 8899.71 27
MDA-MVSNet_test_wron97.60 19097.66 17897.41 25499.04 19193.09 28895.27 31598.42 26597.26 19098.88 14198.95 14295.43 20899.73 21797.02 14298.72 26599.41 144
tpmvs95.02 27595.25 26794.33 32196.39 34485.87 33498.08 13496.83 30595.46 25995.51 32298.69 18285.91 29499.53 28994.16 24996.23 33397.58 311
PM-MVS98.82 6698.72 7099.12 8999.64 5098.54 7997.98 15299.68 1697.62 15499.34 7199.18 9297.54 9399.77 19297.79 10599.74 11599.04 222
HQP_MVS97.99 16697.67 17598.93 11899.19 16097.65 14897.77 17199.27 14698.20 12197.79 22997.98 25494.90 21899.70 22994.42 24499.51 18999.45 132
plane_prior799.19 16097.87 129
plane_prior698.99 20197.70 14694.90 218
plane_prior599.27 14699.70 22994.42 24499.51 18999.45 132
plane_prior497.98 254
plane_prior397.78 13997.41 17797.79 229
plane_prior297.77 17198.20 121
plane_prior199.05 189
plane_prior97.65 14897.07 23196.72 21599.36 204
PS-CasMVS99.40 2199.33 2699.62 699.71 3499.10 4299.29 2599.53 5999.53 2499.46 5099.41 6198.23 5099.95 1398.89 5599.95 3099.81 12
UniMVSNet_NR-MVSNet98.86 6498.68 7999.40 5499.17 16598.74 6097.68 18099.40 9899.14 5999.06 10898.59 20396.71 15599.93 2698.57 7099.77 10499.53 91
PEN-MVS99.41 2099.34 2499.62 699.73 2899.14 3499.29 2599.54 5899.62 1699.56 3399.42 5998.16 5799.96 898.78 5999.93 3999.77 16
TransMVSNet (Re)99.44 1599.47 1599.36 5699.80 2298.58 7499.27 3199.57 4399.39 3399.75 1299.62 2899.17 1499.83 11799.06 4799.62 15599.66 33
DTE-MVSNet99.43 1899.35 2299.66 499.71 3499.30 1299.31 2099.51 6499.64 1099.56 3399.46 5298.23 5099.97 398.78 5999.93 3999.72 24
DU-MVS98.82 6698.63 8599.39 5599.16 16798.74 6097.54 20099.25 15298.84 8699.06 10898.76 17596.76 15299.93 2698.57 7099.77 10499.50 103
UniMVSNet (Re)98.87 6298.71 7199.35 6199.24 13898.73 6397.73 17699.38 10398.93 8399.12 10298.73 17796.77 15099.86 7798.63 6799.80 9299.46 128
CP-MVSNet99.21 3299.09 4599.56 1899.65 4798.96 5399.13 4699.34 12199.42 3199.33 7299.26 7997.01 13299.94 2098.74 6399.93 3999.79 14
WR-MVS_H99.33 2799.22 3699.65 599.71 3499.24 1999.32 1799.55 5499.46 2899.50 4499.34 7097.30 10999.93 2698.90 5399.93 3999.77 16
WR-MVS98.40 13198.19 13899.03 10599.00 19997.65 14896.85 24498.94 21698.57 10398.89 13898.50 21695.60 20199.85 8897.54 11899.85 7199.59 58
NR-MVSNet98.95 5698.82 5699.36 5699.16 16798.72 6599.22 3499.20 16399.10 6599.72 1398.76 17596.38 17399.86 7798.00 9899.82 8299.50 103
Baseline_NR-MVSNet98.98 5398.86 5399.36 5699.82 2098.55 7697.47 20699.57 4399.37 3699.21 9499.61 3096.76 15299.83 11798.06 9399.83 7999.71 27
TranMVSNet+NR-MVSNet99.17 3599.07 4799.46 4999.37 12098.87 5598.39 11499.42 9699.42 3199.36 6699.06 11798.38 4499.95 1398.34 8199.90 5799.57 70
TSAR-MVS + GP.98.18 15397.98 15898.77 14098.71 24897.88 12896.32 27298.66 25596.33 22999.23 9398.51 21397.48 9999.40 31297.16 13499.46 19699.02 225
abl_698.99 4998.78 6099.61 999.45 10699.46 498.60 8399.50 6598.59 9999.24 9099.04 12498.54 3799.89 5696.45 18299.62 15599.50 103
n20.00 361
nn0.00 361
mPP-MVS98.64 9698.34 12699.54 2599.54 7799.17 2698.63 8099.24 15697.47 16998.09 20098.68 18497.62 8899.89 5696.22 19099.62 15599.57 70
door-mid99.57 43
DI_MVS_plusplus_test97.57 19497.40 19398.07 22099.06 18495.71 22996.58 26096.96 29896.71 21798.69 16098.13 24093.81 24799.68 23897.45 12399.19 23198.80 252
XVG-OURS-SEG-HR98.49 12298.28 13299.14 8799.49 9298.83 5696.54 26199.48 7497.32 18599.11 10398.61 20199.33 899.30 32596.23 18998.38 28399.28 185
DWT-MVSNet_test92.75 31692.05 31894.85 31596.48 34287.21 33197.83 16794.99 31992.22 30892.72 34394.11 34570.75 35099.46 30695.01 22894.33 34597.87 292
MVSFormer98.26 14598.43 11497.77 23298.88 22393.89 27799.39 1399.56 4999.11 6198.16 19598.13 24093.81 24799.97 399.26 3299.57 17299.43 139
jason97.45 20297.35 19997.76 23399.24 13893.93 27395.86 29698.42 26594.24 28498.50 18198.13 24094.82 22399.91 4397.22 13299.73 11899.43 139
jason: jason.
lupinMVS97.06 22696.86 21897.65 23998.88 22393.89 27795.48 31197.97 27893.53 29298.16 19597.58 27293.81 24799.91 4396.77 15699.57 17299.17 211
test_djsdf99.52 1199.51 1199.53 3299.86 1698.74 6099.39 1399.56 4999.11 6199.70 1599.73 1099.00 1799.97 399.26 3299.98 1999.89 3
Test497.43 20397.18 20498.18 21399.05 18996.02 21696.62 25899.09 19296.25 23398.63 16797.70 26690.49 27499.68 23897.50 12199.30 21498.83 246
HPM-MVS_fast99.01 4798.82 5699.57 1699.71 3499.35 999.00 5999.50 6597.33 18398.94 13398.86 15998.75 2599.82 12997.53 11999.71 12799.56 75
PatchFormer-LS_test94.08 30293.91 29594.59 31996.93 33486.86 33297.55 19996.57 31094.27 28394.38 33393.64 34880.96 31999.59 27396.44 18394.48 34497.31 317
testpf89.08 32690.27 32685.50 33994.03 35382.85 34996.87 24391.09 35191.61 31490.96 34894.86 34166.15 35795.83 35094.58 23892.27 34977.82 351
K. test v398.00 16497.66 17899.03 10599.79 2497.56 15299.19 3992.47 34499.62 1699.52 3999.66 2289.61 27899.96 899.25 3499.81 8899.56 75
lessismore_v098.97 11399.73 2897.53 15486.71 35399.37 6499.52 4589.93 27699.92 3498.99 5199.72 12399.44 134
SixPastTwentyTwo98.75 7598.62 8699.16 8499.83 1997.96 12199.28 2998.20 27299.37 3699.70 1599.65 2592.65 26399.93 2699.04 4899.84 7399.60 52
OurMVSNet-221017-099.37 2499.31 2899.53 3299.91 498.98 4999.63 699.58 3699.44 3099.78 1099.76 696.39 17299.92 3499.44 2699.92 4999.68 30
HPM-MVS98.79 6998.53 9599.59 1599.65 4799.29 1399.16 4299.43 9396.74 21498.61 17098.38 22398.62 3099.87 7296.47 18099.67 14799.59 58
XVG-OURS98.53 11898.34 12699.11 9099.50 8698.82 5895.97 28599.50 6597.30 18799.05 11398.98 13699.35 799.32 32295.72 21599.68 14299.18 207
XVG-ACMP-BASELINE98.56 10998.34 12699.22 7999.54 7798.59 7397.71 17799.46 8297.25 19198.98 12498.99 13397.54 9399.84 10395.88 20599.74 11599.23 195
LPG-MVS_test98.71 8098.46 10899.47 4799.57 6298.97 5098.23 12099.48 7496.60 22399.10 10599.06 11798.71 2799.83 11795.58 22299.78 10099.62 45
LGP-MVS_train99.47 4799.57 6298.97 5099.48 7496.60 22399.10 10599.06 11798.71 2799.83 11795.58 22299.78 10099.62 45
test1198.87 228
door99.41 97
EPNet_dtu94.93 27694.78 27795.38 31193.58 35487.68 32996.78 24695.69 31897.35 18289.14 35098.09 24888.15 28599.49 30094.95 23199.30 21498.98 229
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268897.49 19797.14 20898.54 17699.68 4396.09 21596.50 26299.62 2891.58 31598.84 14698.97 13892.36 26599.88 6396.76 15799.95 3099.67 31
EPNet96.14 25695.44 26298.25 20890.76 35595.50 23597.92 15794.65 32198.97 7892.98 34298.85 16189.12 28299.87 7295.99 20199.68 14299.39 150
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS96.79 184
HQP-NCC98.67 25896.29 27396.05 24195.55 318
ACMP_Plane98.67 25896.29 27396.05 24195.55 318
APD-MVScopyleft98.10 15797.67 17599.42 5099.11 17398.93 5497.76 17399.28 14194.97 26798.72 15998.77 17397.04 12899.85 8893.79 26399.54 18299.49 110
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS92.82 284
HQP4-MVS95.56 31799.54 28799.32 174
HQP3-MVS99.04 20199.26 221
HQP2-MVS93.84 245
LP96.60 24696.57 23796.68 27697.64 31691.70 30398.11 13197.74 28397.29 18997.91 20999.24 8288.35 28499.85 8897.11 14095.76 33698.49 271
CNVR-MVS98.17 15597.87 16999.07 9698.67 25898.24 9497.01 23398.93 21997.25 19197.62 23898.34 22797.27 11299.57 28096.42 18499.33 20999.39 150
NCCC97.86 17497.47 19199.05 10298.61 26698.07 10996.98 23498.90 22597.63 15397.04 27297.93 25795.99 18899.66 25295.31 22598.82 26299.43 139
114514_t96.50 25095.77 25398.69 15099.48 9797.43 15997.84 16699.55 5481.42 34896.51 29598.58 20495.53 20399.67 24493.41 27499.58 16898.98 229
CP-MVS98.70 8298.42 11599.52 3799.36 12199.12 3998.72 7799.36 11197.54 16498.30 19298.40 22297.86 7599.89 5696.53 17799.72 12399.56 75
DSMNet-mixed97.42 20497.60 18396.87 27199.15 17091.46 30698.54 9099.12 18892.87 29997.58 24299.63 2796.21 17799.90 4795.74 21499.54 18299.27 186
tpm293.09 31492.58 31394.62 31897.56 31886.53 33397.66 18295.79 31786.15 34294.07 33898.23 23775.95 34799.53 28990.91 31596.86 32897.81 296
NP-MVS98.84 23197.39 16196.84 297
EG-PatchMatch MVS98.99 4999.01 4898.94 11799.50 8697.47 15698.04 14099.59 3498.15 12599.40 6099.36 6798.58 3399.76 19798.78 5999.68 14299.59 58
tpm cat193.29 31293.13 31093.75 32897.39 32784.74 34297.39 20897.65 28783.39 34794.16 33598.41 22182.86 31699.39 31491.56 30395.35 33997.14 319
SteuartSystems-ACMMP98.79 6998.54 9499.54 2599.73 2899.16 2898.23 12099.31 13197.92 13098.90 13698.90 15098.00 6799.88 6396.15 19699.72 12399.58 65
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tpmp4_e2392.91 31592.45 31494.29 32297.41 32585.62 33897.95 15596.77 30687.55 34091.33 34798.57 20574.21 34999.59 27391.62 30196.64 32997.65 310
CostFormer93.97 30593.78 29894.51 32097.53 32085.83 33697.98 15295.96 31589.29 33394.99 32998.63 19778.63 33599.62 26294.54 23996.50 33098.09 286
CR-MVSNet96.28 25495.95 25197.28 25697.71 31294.22 26498.11 13198.92 22292.31 30696.91 27899.37 6585.44 30099.81 14297.39 12797.36 31997.81 296
JIA-IIPM95.52 26695.03 27397.00 26596.85 33794.03 27096.93 23795.82 31699.20 5094.63 33199.71 1483.09 31499.60 26994.42 24494.64 34197.36 316
Patchmtry97.35 20696.97 21298.50 18397.31 32996.47 19698.18 12498.92 22298.95 8298.78 15399.37 6585.44 30099.85 8895.96 20399.83 7999.17 211
PatchT96.65 24396.35 24397.54 24797.40 32695.32 23997.98 15296.64 30999.33 4096.89 28199.42 5984.32 30799.81 14297.69 11497.49 31497.48 314
tpmrst95.07 27395.46 26193.91 32797.11 33284.36 34597.62 18996.96 29894.98 26696.35 30098.80 16985.46 29999.59 27395.60 22096.23 33397.79 299
BH-w/o95.13 27294.89 27695.86 30298.20 29691.31 31695.65 30597.37 28993.64 29096.52 29495.70 31793.04 25799.02 33788.10 32695.82 33597.24 318
tpm94.67 29094.34 28595.66 30697.68 31588.42 32597.88 16194.90 32094.46 27796.03 30998.56 20878.66 33499.79 17495.88 20595.01 34098.78 254
DELS-MVS98.27 14398.20 13698.48 18598.86 22596.70 19095.60 30799.20 16397.73 14898.45 18398.71 17997.50 9599.82 12998.21 8799.59 16298.93 236
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-untuned96.83 23696.75 22497.08 26198.74 24493.33 28796.71 25198.26 27096.72 21598.44 18497.37 28795.20 21299.47 30491.89 29697.43 31698.44 274
RPMNet96.82 23896.66 23297.28 25697.71 31294.22 26498.11 13196.90 30399.37 3696.91 27899.34 7086.72 28899.81 14297.53 11997.36 31997.81 296
no-one97.98 16798.10 14997.61 24299.55 7393.82 27996.70 25298.94 21696.18 23499.52 3999.41 6195.90 19499.81 14296.72 15999.99 1199.20 201
MVSTER96.86 23596.55 23897.79 23197.91 30794.21 26697.56 19798.87 22897.49 16899.06 10899.05 12280.72 32099.80 15498.44 7699.82 8299.37 157
CPTT-MVS97.84 17997.36 19799.27 7399.31 13098.46 8498.29 11699.27 14694.90 26997.83 22098.37 22494.90 21899.84 10393.85 26299.54 18299.51 98
GBi-Net98.65 9498.47 10599.17 8198.90 21898.24 9499.20 3599.44 8898.59 9998.95 12999.55 4194.14 24099.86 7797.77 10799.69 13799.41 144
PVSNet_Blended_VisFu98.17 15598.15 14498.22 21099.73 2895.15 24297.36 21099.68 1694.45 27998.99 12299.27 7796.87 14399.94 2097.13 13899.91 5499.57 70
PVSNet_BlendedMVS97.55 19597.53 18597.60 24398.92 21493.77 28196.64 25699.43 9394.49 27597.62 23899.18 9296.82 14699.67 24494.73 23499.93 3999.36 163
UnsupCasMVSNet_eth97.89 17097.60 18398.75 14499.31 13097.17 17197.62 18999.35 11798.72 9498.76 15698.68 18492.57 26499.74 21297.76 11095.60 33799.34 169
UnsupCasMVSNet_bld97.30 21096.92 21498.45 18999.28 13396.78 18896.20 27999.27 14695.42 26098.28 19398.30 23193.16 25499.71 22794.99 22997.37 31798.87 243
PVSNet_Blended96.88 23496.68 22997.47 25098.92 21493.77 28194.71 32799.43 9390.98 32297.62 23897.36 28896.82 14699.67 24494.73 23499.56 17998.98 229
FMVSNet596.01 25895.20 26998.41 19297.53 32096.10 21398.74 7599.50 6597.22 19998.03 20599.04 12469.80 35199.88 6397.27 13199.71 12799.25 191
test198.65 9498.47 10599.17 8198.90 21898.24 9499.20 3599.44 8898.59 9998.95 12999.55 4194.14 24099.86 7797.77 10799.69 13799.41 144
new_pmnet96.99 23196.76 22397.67 23798.72 24694.89 24795.95 29298.20 27292.62 30298.55 17898.54 21194.88 22199.52 29393.96 25799.44 19898.59 268
FMVSNet397.50 19697.24 20298.29 20698.08 30095.83 22597.86 16498.91 22497.89 13998.95 12998.95 14287.06 28799.81 14297.77 10799.69 13799.23 195
dp93.47 31093.59 30493.13 33596.64 33981.62 35297.66 18296.42 31292.80 30096.11 30498.64 19378.55 33699.59 27393.31 27592.18 35098.16 283
FMVSNet298.49 12298.40 11798.75 14498.90 21897.14 17498.61 8299.13 18698.59 9999.19 9599.28 7594.14 24099.82 12997.97 9999.80 9299.29 184
FMVSNet199.17 3599.17 3999.17 8199.55 7398.24 9499.20 3599.44 8899.21 4799.43 5599.55 4197.82 7999.86 7798.42 7899.89 6399.41 144
N_pmnet97.63 18997.17 20598.99 11299.27 13497.86 13095.98 28493.41 33695.25 26299.47 4998.90 15095.63 20099.85 8896.91 14699.73 11899.27 186
cascas94.79 28594.33 28696.15 29696.02 34892.36 29892.34 34599.26 15185.34 34495.08 32894.96 33792.96 25898.53 34694.41 24798.59 27597.56 312
BH-RMVSNet96.83 23696.58 23697.58 24598.47 27894.05 26996.67 25497.36 29096.70 21997.87 21297.98 25495.14 21499.44 30990.47 31998.58 27699.25 191
UGNet98.53 11898.45 11098.79 13597.94 30596.96 17999.08 4998.54 26099.10 6596.82 28599.47 5196.55 16499.84 10398.56 7399.94 3399.55 83
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-MVS96.67 24296.27 24697.87 22898.81 23894.61 25496.77 24797.92 28094.94 26897.12 26797.74 26491.11 27299.82 12993.89 25998.15 29399.18 207
XXY-MVS99.14 3799.15 4399.10 9299.76 2697.74 14398.85 7299.62 2898.48 10699.37 6499.49 4998.75 2599.86 7798.20 8899.80 9299.71 27
sss97.21 21796.93 21398.06 22198.83 23395.22 24096.75 24998.48 26394.49 27597.27 26597.90 25892.77 26199.80 15496.57 17199.32 21199.16 214
Test_1112_low_res96.99 23196.55 23898.31 20499.35 12595.47 23695.84 29999.53 5991.51 31796.80 28698.48 21991.36 27199.83 11796.58 16999.53 18699.62 45
1112_ss97.29 21296.86 21898.58 16699.34 12796.32 20396.75 24999.58 3693.14 29696.89 28197.48 27992.11 26899.86 7796.91 14699.54 18299.57 70
ab-mvs-re8.12 33410.83 3350.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 35697.48 2790.00 3630.00 3580.00 3550.00 3560.00 356
ab-mvs98.41 12998.36 12398.59 16599.19 16097.23 16599.32 1798.81 24097.66 15198.62 16899.40 6496.82 14699.80 15495.88 20599.51 18998.75 258
TR-MVS95.55 26595.12 27196.86 27497.54 31993.94 27296.49 26496.53 31194.36 28297.03 27396.61 30194.26 23999.16 33386.91 33096.31 33297.47 315
MDTV_nov1_ep13_2view74.92 35597.69 17990.06 33097.75 23285.78 29693.52 27098.69 263
MDTV_nov1_ep1395.22 26897.06 33383.20 34797.74 17596.16 31494.37 28196.99 27498.83 16483.95 31099.53 28993.90 25897.95 308
MIMVSNet199.38 2399.32 2799.55 2099.86 1699.19 2499.41 1299.59 3499.59 1999.71 1499.57 3997.12 12499.90 4799.21 3899.87 6899.54 86
MIMVSNet96.62 24596.25 24897.71 23699.04 19194.66 25299.16 4296.92 30297.23 19697.87 21299.10 10986.11 29399.65 25791.65 29999.21 22698.82 248
IterMVS-LS98.55 11398.70 7498.09 21699.48 9794.73 24997.22 22199.39 10098.97 7899.38 6299.31 7496.00 18599.93 2698.58 6899.97 2399.60 52
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet97.69 18497.35 19998.69 15098.73 24597.02 17896.92 23998.75 24895.89 24698.59 17398.67 18692.08 26999.74 21296.72 15999.81 8899.32 174
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref99.77 104
IterMVS97.73 18298.11 14896.57 28199.24 13890.28 32095.52 31099.21 15998.86 8599.33 7299.33 7293.11 25599.94 2098.49 7499.94 3399.48 116
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon97.33 20896.92 21498.57 16899.09 17797.99 11496.79 24599.35 11793.18 29597.71 23398.07 25095.00 21799.31 32393.97 25699.13 24198.42 276
MVS_111021_LR98.30 13998.12 14798.83 13199.16 16798.03 11296.09 28299.30 13897.58 15898.10 19998.24 23598.25 4899.34 31996.69 16399.65 15299.12 216
DP-MVS98.93 5798.81 5899.28 7099.21 15098.45 8598.46 10999.33 12699.63 1299.48 4699.15 10297.23 11999.75 20397.17 13399.66 15199.63 44
ACMMP++99.68 142
HQP-MVS97.00 23096.49 24098.55 17398.67 25896.79 18496.29 27399.04 20196.05 24195.55 31896.84 29793.84 24599.54 28792.82 28499.26 22199.32 174
QAPM97.31 20996.81 22198.82 13298.80 24097.49 15599.06 5399.19 16990.22 32797.69 23599.16 9896.91 13799.90 4790.89 31699.41 20099.07 219
Vis-MVSNetpermissive99.34 2699.36 2199.27 7399.73 2898.26 9399.17 4199.78 599.11 6199.27 8299.48 5098.82 2299.95 1398.94 5299.93 3999.59 58
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet94.32 29595.62 25890.42 33798.46 27975.36 35496.29 27389.13 35295.25 26295.38 32499.75 792.88 26099.19 33194.07 25599.39 20296.72 329
IS-MVSNet98.19 15297.90 16699.08 9599.57 6297.97 11999.31 2098.32 26899.01 7498.98 12499.03 12791.59 27099.79 17495.49 22499.80 9299.48 116
HyFIR lowres test97.19 21996.60 23598.96 11499.62 5497.28 16495.17 31899.50 6594.21 28599.01 11998.32 23086.61 28999.99 297.10 14199.84 7399.60 52
EPMVS93.72 30893.27 30895.09 31496.04 34787.76 32898.13 12885.01 35494.69 27396.92 27698.64 19378.47 33799.31 32395.04 22796.46 33198.20 282
PAPM_NR96.82 23896.32 24598.30 20599.07 18196.69 19197.48 20498.76 24595.81 24796.61 29196.47 30594.12 24399.17 33290.82 31897.78 31199.06 220
TAMVS98.24 14998.05 15598.80 13499.07 18197.18 17097.88 16198.81 24096.66 22099.17 9999.21 8794.81 22599.77 19296.96 14599.88 6499.44 134
PAPR95.29 27094.47 27897.75 23497.50 32495.14 24394.89 32498.71 25391.39 31995.35 32595.48 32594.57 23299.14 33584.95 33797.37 31798.97 232
RPSCF98.62 10398.36 12399.42 5099.65 4799.42 598.55 8999.57 4397.72 14998.90 13699.26 7996.12 18099.52 29395.72 21599.71 12799.32 174
Vis-MVSNet (Re-imp)97.46 20197.16 20698.34 20199.55 7396.10 21398.94 6498.44 26498.32 11498.16 19598.62 19988.76 28399.73 21793.88 26099.79 9699.18 207
test_040298.76 7498.71 7198.93 11899.56 6998.14 10298.45 11099.34 12199.28 4498.95 12998.91 14798.34 4699.79 17495.63 21999.91 5498.86 244
MVS_111021_HR98.25 14798.08 15398.75 14499.09 17797.46 15795.97 28599.27 14697.60 15797.99 20698.25 23498.15 5999.38 31696.87 15099.57 17299.42 142
CSCG98.68 9098.50 9999.20 8099.45 10698.63 6898.56 8799.57 4397.87 14298.85 14498.04 25197.66 8399.84 10396.72 15999.81 8899.13 215
PatchMatch-RL97.24 21696.78 22298.61 16199.03 19497.83 13296.36 27099.06 19593.49 29497.36 26397.78 26295.75 19799.49 30093.44 27398.77 26398.52 270
API-MVS97.04 22996.91 21697.42 25397.88 30998.23 9898.18 12498.50 26297.57 16097.39 26096.75 29996.77 15099.15 33490.16 32099.02 25094.88 346
Test By Simon96.52 165
TDRefinement99.42 1999.38 1999.55 2099.76 2699.33 1199.68 599.71 1299.38 3599.53 3799.61 3098.64 2999.80 15498.24 8599.84 7399.52 96
USDC97.41 20597.40 19397.44 25298.94 20893.67 28395.17 31899.53 5994.03 28798.97 12699.10 10995.29 21099.34 31995.84 21199.73 11899.30 181
EPP-MVSNet98.30 13998.04 15699.07 9699.56 6997.83 13299.29 2598.07 27699.03 7298.59 17399.13 10592.16 26799.90 4796.87 15099.68 14299.49 110
PMMVS96.51 24895.98 25098.09 21697.53 32095.84 22494.92 32398.84 23491.58 31596.05 30895.58 31895.68 19999.66 25295.59 22198.09 30298.76 257
PAPM91.88 32290.34 32496.51 28298.06 30192.56 29392.44 34497.17 29386.35 34190.38 34996.01 31086.61 28999.21 33070.65 35295.43 33897.75 300
ACMMPcopyleft98.75 7598.50 9999.52 3799.56 6999.16 2898.87 6999.37 10797.16 20098.82 15099.01 13097.71 8299.87 7296.29 18899.69 13799.54 86
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
CNLPA97.17 22096.71 22798.55 17398.56 27198.05 11196.33 27198.93 21996.91 20897.06 27197.39 28594.38 23699.45 30891.66 29899.18 23398.14 284
PatchmatchNetpermissive95.58 26495.67 25795.30 31297.34 32887.32 33097.65 18496.65 30895.30 26197.07 27098.69 18284.77 30299.75 20394.97 23098.64 27298.83 246
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS98.29 14297.95 16099.34 6498.44 28199.16 2898.12 13099.38 10396.01 24498.06 20298.43 22097.80 8099.67 24495.69 21799.58 16899.20 201
F-COLMAP97.30 21096.68 22999.14 8799.19 16098.39 8897.27 21599.30 13892.93 29796.62 29098.00 25295.73 19899.68 23892.62 28998.46 28299.35 168
ANet_high99.57 999.67 599.28 7099.89 798.09 10499.14 4499.93 199.82 299.93 299.81 499.17 1499.94 2099.31 30100.00 199.82 10
PNet_i23d91.80 32392.35 31590.14 33898.65 26473.10 35789.22 35099.02 20795.23 26497.87 21297.82 26178.45 33898.89 34388.73 32486.14 35198.42 276
wuyk23d96.06 25797.62 18291.38 33698.65 26498.57 7598.85 7296.95 30096.86 21099.90 599.16 9899.18 1298.40 34789.23 32399.77 10477.18 352
OMC-MVS97.88 17297.49 18799.04 10498.89 22298.63 6896.94 23699.25 15295.02 26598.53 18098.51 21397.27 11299.47 30493.50 27299.51 18999.01 226
MG-MVS96.77 24096.61 23497.26 25898.31 28993.06 28995.93 29398.12 27596.45 22797.92 20798.73 17793.77 25099.39 31491.19 31299.04 24999.33 173
wuykxyi23d99.36 2599.31 2899.50 4199.81 2198.67 6798.08 13499.75 898.03 12699.90 599.60 3499.18 1299.94 2099.46 2599.98 1999.89 3
AdaColmapbinary97.14 22296.71 22798.46 18798.34 28797.80 13896.95 23598.93 21995.58 25696.92 27697.66 26895.87 19599.53 28990.97 31399.14 23898.04 287
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_SJBPF98.87 12699.22 14498.48 8399.35 11797.50 16698.28 19398.60 20297.64 8799.35 31893.86 26199.27 21998.79 253
DeepMVS_CXcopyleft93.44 33298.24 29294.21 26694.34 32764.28 35191.34 34694.87 34089.45 28192.77 35477.54 35193.14 34793.35 349
TinyColmap97.89 17097.98 15897.60 24398.86 22594.35 26396.21 27799.44 8897.45 17699.06 10898.88 15697.99 6999.28 32894.38 24899.58 16899.18 207
MAR-MVS96.47 25195.70 25598.79 13597.92 30699.12 3998.28 11798.60 25992.16 30995.54 32196.17 30994.77 22999.52 29389.62 32298.23 28697.72 302
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
LF4IMVS97.90 16997.69 17498.52 17899.17 16597.66 14797.19 22599.47 8096.31 23197.85 21598.20 23996.71 15599.52 29394.62 23799.72 12398.38 278
MSDG97.71 18397.52 18698.28 20798.91 21796.82 18394.42 33099.37 10797.65 15298.37 19198.29 23297.40 10499.33 32194.09 25499.22 22498.68 266
LS3D98.63 9898.38 12199.36 5697.25 33099.38 699.12 4899.32 12999.21 4798.44 18498.88 15697.31 10899.80 15496.58 16999.34 20898.92 237
CLD-MVS97.49 19797.16 20698.48 18599.07 18197.03 17694.71 32799.21 15994.46 27798.06 20297.16 29297.57 8999.48 30394.46 24199.78 10098.95 233
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS93.44 31192.23 31697.08 26199.25 13797.86 13095.61 30697.16 29492.90 29893.76 34198.65 19075.94 34895.66 35179.30 35097.49 31497.73 301
Gipumacopyleft99.03 4599.16 4198.64 15499.94 398.51 8199.32 1799.75 899.58 2198.60 17299.62 2898.22 5299.51 29897.70 11299.73 11897.89 290
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015