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
DeepC-MVS_fast98.69 199.49 1399.39 1599.77 3699.63 10899.59 4899.36 19499.46 13899.07 999.79 1899.82 4498.85 3299.92 6598.68 8499.87 3899.82 32
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepC-MVS98.35 299.30 4599.19 4799.64 6399.82 2999.23 9099.62 8299.55 5598.94 2699.63 5399.95 295.82 13899.94 4299.37 1799.97 399.73 65
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepPCF-MVS98.18 398.81 11099.37 1797.12 30099.60 11891.75 32898.61 31999.44 15799.35 199.83 1199.85 2698.70 5099.81 13899.02 4899.91 1799.81 36
PLCcopyleft97.94 499.02 8698.85 9099.53 8099.66 10299.01 11899.24 23099.52 7696.85 21299.27 13599.48 19598.25 7499.91 7497.76 16399.62 10399.65 90
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
ACMM97.58 598.37 13898.34 13298.48 22899.41 15297.10 24499.56 11299.45 14998.53 5499.04 18899.85 2693.00 23499.71 17898.74 7597.45 22798.64 257
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
COLMAP_ROBcopyleft97.56 698.86 10198.75 10199.17 13299.88 1198.53 18899.34 20199.59 3897.55 14998.70 23599.89 1095.83 13799.90 8698.10 13399.90 2499.08 168
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
HY-MVS97.30 798.85 10798.64 11299.47 9299.42 14999.08 10499.62 8299.36 19397.39 16599.28 13199.68 11996.44 12099.92 6598.37 11798.22 17999.40 145
ACMH97.28 898.10 16597.99 15698.44 23599.41 15296.96 25999.60 9099.56 4898.09 8998.15 27099.91 590.87 29099.70 18498.88 5797.45 22798.67 241
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
3Dnovator97.25 999.24 5499.05 5999.81 2899.12 21499.66 3699.84 999.74 1099.09 898.92 20699.90 795.94 13399.98 598.95 5399.92 1299.79 45
ACMH+97.24 1097.92 19697.78 18198.32 24399.46 14396.68 26999.56 11299.54 6298.41 6397.79 28599.87 1990.18 29799.66 19198.05 14297.18 24098.62 265
ACMP97.20 1198.06 16897.94 16098.45 23299.37 16297.01 25399.44 15899.49 10497.54 15298.45 25699.79 7291.95 26899.72 17297.91 14997.49 22598.62 265
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
LTVRE_ROB97.16 1298.02 17997.90 16298.40 23899.23 19196.80 26599.70 4299.60 3597.12 18798.18 26999.70 10891.73 27899.72 17298.39 11497.45 22798.68 230
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+97.12 1399.18 5898.97 7299.82 2599.17 20699.68 3299.81 1599.51 8599.20 498.72 22899.89 1095.68 14299.97 1198.86 6499.86 4899.81 36
PCF-MVS97.08 1497.66 23897.06 25699.47 9299.61 11699.09 10398.04 33799.25 24191.24 32698.51 25299.70 10894.55 19699.91 7492.76 31699.85 5299.42 143
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
TAPA-MVS97.07 1597.74 22597.34 24198.94 15899.70 8697.53 23399.25 22899.51 8591.90 32399.30 12399.63 14198.78 3899.64 19588.09 33099.87 3899.65 90
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
OpenMVScopyleft96.50 1698.47 13098.12 14499.52 8499.04 22999.53 5799.82 1399.72 1194.56 29498.08 27399.88 1494.73 18899.98 597.47 19399.76 7899.06 173
PVSNet96.02 1798.85 10798.84 9198.89 17699.73 7297.28 23698.32 33099.60 3597.86 11799.50 8399.57 16196.75 11399.86 10698.56 10099.70 9199.54 114
IB-MVS95.67 1896.22 28395.44 29198.57 21999.21 19496.70 26798.65 31897.74 33296.71 21897.27 29098.54 30586.03 32799.92 6598.47 11086.30 33899.10 163
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
PVSNet_094.43 1996.09 28795.47 28997.94 27499.31 17794.34 31297.81 33899.70 1597.12 18797.46 28798.75 29589.71 30099.79 14597.69 17381.69 34299.68 83
OpenMVS_ROBcopyleft92.34 2094.38 30393.70 30496.41 31197.38 32193.17 32299.06 26698.75 29586.58 33694.84 31298.26 31181.53 34099.32 24289.01 32797.87 20696.76 333
MVEpermissive76.82 2176.91 32574.31 32784.70 33285.38 35276.05 35196.88 34493.17 35367.39 34871.28 34989.01 34921.66 36287.69 35171.74 34972.29 34590.35 347
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVScopyleft70.75 2275.98 32674.97 32579.01 33970.98 35555.18 35693.37 34898.21 32365.08 35161.78 35293.83 34121.74 36192.53 34678.59 34491.12 32089.34 348
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
CMPMVSbinary69.68 2394.13 30494.90 29691.84 32497.24 32580.01 34598.52 32399.48 11389.01 33391.99 33199.67 12385.67 32999.13 27695.44 27297.03 24296.39 335
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
tfpn11197.81 21097.49 21598.78 20399.72 7597.86 22099.59 9298.74 29897.93 11299.26 13998.62 29891.75 27499.86 10693.57 30598.18 18398.61 274
conf0.0198.21 15297.89 16699.15 13599.76 4499.04 10899.67 5697.71 33397.10 19199.55 7199.54 16992.70 24699.79 14596.90 23198.12 19398.61 274
GSMVS99.52 119
test_part399.37 18897.97 10899.78 7799.95 3397.15 212
conf0.00298.21 15297.89 16699.15 13599.76 4499.04 10899.67 5697.71 33397.10 19199.55 7199.54 16992.70 24699.79 14596.90 23198.12 19398.61 274
thresconf0.0298.24 14597.89 16699.27 12099.76 4499.04 10899.67 5697.71 33397.10 19199.55 7199.54 16992.70 24699.79 14596.90 23198.12 19398.97 182
tfpn_n40098.24 14597.89 16699.27 12099.76 4499.04 10899.67 5697.71 33397.10 19199.55 7199.54 16992.70 24699.79 14596.90 23198.12 19398.97 182
tfpnconf98.24 14597.89 16699.27 12099.76 4499.04 10899.67 5697.71 33397.10 19199.55 7199.54 16992.70 24699.79 14596.90 23198.12 19398.97 182
tfpnview1198.24 14597.89 16699.27 12099.76 4499.04 10899.67 5697.71 33397.10 19199.55 7199.54 16992.70 24699.79 14596.90 23198.12 19398.97 182
tfpn100098.33 13998.02 15399.25 12499.78 3698.73 16999.70 4297.55 34197.48 15599.69 3699.53 17692.37 26499.85 11297.82 15698.26 17899.16 159
test_part299.81 3299.83 799.77 23
tfpn_ndepth98.17 15697.84 17499.15 13599.75 5698.76 16899.61 8897.39 34396.92 20999.61 5899.38 22292.19 26699.86 10697.57 18198.13 19198.82 199
test_part199.48 11398.96 2099.84 5799.83 23
conf200view1197.78 21797.45 22198.77 20499.72 7597.86 22099.59 9298.74 29897.93 11299.26 13998.62 29891.75 27499.83 12593.22 30998.18 18398.61 274
thres100view90097.76 21997.45 22198.69 21099.72 7597.86 22099.59 9298.74 29897.93 11299.26 13998.62 29891.75 27499.83 12593.22 30998.18 18398.37 298
tfpnnormal97.84 20497.47 21898.98 15299.20 19699.22 9199.64 7799.61 3296.32 24898.27 26799.70 10893.35 23099.44 21995.69 26795.40 26898.27 301
tfpn200view997.72 22897.38 23498.72 20899.69 8897.96 21599.50 13398.73 30797.83 12299.17 16698.45 30791.67 28099.83 12593.22 30998.18 18398.37 298
view60097.97 18797.66 19698.89 17699.75 5697.81 22499.69 4598.80 29098.02 10299.25 14398.88 28391.95 26899.89 9494.36 29298.29 17498.96 188
view80097.97 18797.66 19698.89 17699.75 5697.81 22499.69 4598.80 29098.02 10299.25 14398.88 28391.95 26899.89 9494.36 29298.29 17498.96 188
conf0.05thres100097.97 18797.66 19698.89 17699.75 5697.81 22499.69 4598.80 29098.02 10299.25 14398.88 28391.95 26899.89 9494.36 29298.29 17498.96 188
tfpn97.97 18797.66 19698.89 17699.75 5697.81 22499.69 4598.80 29098.02 10299.25 14398.88 28391.95 26899.89 9494.36 29298.29 17498.96 188
ESAPD99.31 4499.13 5299.87 699.81 3299.83 799.37 18899.48 11397.97 10899.77 2399.78 7798.96 2099.95 3397.15 21299.84 5799.83 23
CHOSEN 280x42099.12 6899.13 5299.08 14199.66 10297.89 21898.43 32699.71 1398.88 3099.62 5699.76 8796.63 11699.70 18499.46 1499.99 199.66 87
CANet99.25 5399.14 5199.59 6999.41 15299.16 9599.35 19899.57 4498.82 3599.51 8299.61 14996.46 11999.95 3399.59 299.98 299.65 90
Fast-Effi-MVS+-dtu98.77 11698.83 9498.60 21699.41 15296.99 25599.52 12499.49 10498.11 8699.24 14899.34 24096.96 10699.79 14597.95 14799.45 10699.02 177
Effi-MVS+-dtu98.78 11498.89 8398.47 23099.33 16996.91 26199.57 10599.30 22298.47 5799.41 10098.99 27696.78 11099.74 16098.73 7799.38 11098.74 212
CANet_DTU98.97 9398.87 8599.25 12499.33 16998.42 20099.08 26199.30 22299.16 599.43 9599.75 9295.27 15199.97 1198.56 10099.95 699.36 148
MVS_030499.06 8098.86 8899.66 5499.51 13199.36 7699.22 23599.51 8598.95 2499.58 6499.65 13093.74 22799.98 599.66 199.95 699.64 96
MP-MVS-pluss99.37 3799.20 4699.88 499.90 399.87 299.30 20899.52 7697.18 18199.60 6099.79 7298.79 3799.95 3398.83 6899.91 1799.83 23
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HSP-MVS99.41 3299.26 4399.85 1899.89 899.80 1499.67 5699.37 19298.70 4599.77 2399.49 18998.21 7599.95 3398.46 11199.77 7699.81 36
sam_mvs194.86 17699.52 119
sam_mvs94.72 189
semantic-postprocess98.06 26699.57 12396.36 27899.49 10497.18 18198.71 22999.72 10492.70 24699.14 27397.44 19695.86 26198.67 241
TSAR-MVS + MP.99.58 399.50 799.81 2899.91 199.66 3699.63 7999.39 17998.91 2999.78 2299.85 2699.36 299.94 4298.84 6699.88 3499.82 32
xiu_mvs_v1_base_debu99.29 4799.27 4099.34 10699.63 10898.97 12599.12 25199.51 8598.86 3199.84 899.47 19998.18 7699.99 199.50 899.31 11599.08 168
OPM-MVS98.19 15598.10 14598.45 23298.88 26497.07 24899.28 21599.38 18598.57 5299.22 15599.81 5392.12 26799.66 19198.08 13897.54 21998.61 274
ACMMP_Plus99.47 2099.34 2499.88 499.87 1599.86 399.47 15099.48 11398.05 9899.76 2899.86 2298.82 3499.93 5798.82 7199.91 1799.84 12
ambc93.06 31992.68 34082.36 34298.47 32598.73 30795.09 31097.41 33055.55 35099.10 28196.42 25491.32 31997.71 328
MPTG99.49 1399.36 1999.89 299.90 399.86 399.36 19499.47 12998.79 4099.68 3799.81 5398.43 6399.97 1198.88 5799.90 2499.83 23
MTGPAbinary99.47 129
mvs-test198.86 10198.84 9198.89 17699.33 16997.77 22999.44 15899.30 22298.47 5799.10 17699.43 20896.78 11099.95 3398.73 7799.02 13498.96 188
Effi-MVS+98.81 11098.59 12199.48 8999.46 14399.12 10198.08 33699.50 9997.50 15499.38 10799.41 21396.37 12299.81 13899.11 4198.54 16499.51 124
xiu_mvs_v2_base99.26 5299.25 4499.29 11799.53 12898.91 13899.02 27799.45 14998.80 3999.71 3199.26 25498.94 2699.98 599.34 2299.23 11998.98 181
xiu_mvs_v1_base99.29 4799.27 4099.34 10699.63 10898.97 12599.12 25199.51 8598.86 3199.84 899.47 19998.18 7699.99 199.50 899.31 11599.08 168
new-patchmatchnet94.48 30194.08 30295.67 31395.08 33392.41 32599.18 24299.28 23394.55 29593.49 32697.37 33287.86 32197.01 33391.57 31988.36 32797.61 329
pmmvs696.53 27096.09 27197.82 28498.69 29295.47 29599.37 18899.47 12993.46 31397.41 28899.78 7787.06 32599.33 23996.92 22992.70 31598.65 255
pmmvs597.52 24597.30 24698.16 26398.57 30296.73 26699.27 21898.90 28296.14 26698.37 26099.53 17691.54 28499.14 27397.51 18895.87 26098.63 263
test_post199.23 23165.14 35494.18 21199.71 17897.58 179
test_post65.99 35394.65 19399.73 168
Fast-Effi-MVS+98.70 12098.43 12799.51 8699.51 13199.28 8499.52 12499.47 12996.11 26899.01 19199.34 24096.20 12799.84 11897.88 15198.82 15199.39 146
patchmatchnet-post98.70 29694.79 18099.74 160
Anonymous2023121190.69 31389.39 31494.58 31594.25 33588.18 33399.29 21299.07 26182.45 34192.95 32897.65 32263.96 34897.79 32689.27 32685.63 33997.77 326
pmmvs-eth3d95.34 29694.73 29797.15 29895.53 33195.94 28699.35 19899.10 25695.13 28293.55 32597.54 32988.15 32097.91 32394.58 28689.69 32497.61 329
GG-mvs-BLEND98.45 23298.55 30398.16 20799.43 16393.68 35197.23 29198.46 30689.30 30499.22 26695.43 27398.22 17997.98 312
xiu_mvs_v1_base_debi99.29 4799.27 4099.34 10699.63 10898.97 12599.12 25199.51 8598.86 3199.84 899.47 19998.18 7699.99 199.50 899.31 11599.08 168
Anonymous2023120696.22 28396.03 27296.79 30797.31 32494.14 31399.63 7999.08 25896.17 26297.04 29599.06 27193.94 21897.76 32886.96 33495.06 27698.47 291
MTAPA99.52 1199.39 1599.89 299.90 399.86 399.66 6599.47 12998.79 4099.68 3799.81 5398.43 6399.97 1198.88 5799.90 2499.83 23
MTMP98.88 284
gm-plane-assit98.54 30492.96 32394.65 29099.15 26299.64 19597.56 183
test9_res97.49 19099.72 8599.75 55
MVP-Stereo97.81 21097.75 19197.99 27297.53 31996.60 27198.96 29298.85 28697.22 17997.23 29199.36 23395.28 15099.46 21395.51 27199.78 7497.92 316
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST999.67 9299.65 3999.05 26899.41 16996.22 25898.95 20299.49 18998.77 4199.91 74
train_agg99.02 8698.77 9899.77 3699.67 9299.65 3999.05 26899.41 16996.28 25198.95 20299.49 18998.76 4399.91 7497.63 17699.72 8599.75 55
gg-mvs-nofinetune96.17 28595.32 29298.73 20798.79 27698.14 20899.38 18694.09 35091.07 32898.07 27691.04 34689.62 30299.35 23596.75 24199.09 12998.68 230
Patchmatch-test198.16 15898.14 14298.22 25899.30 17895.55 29199.07 26298.97 27197.57 14799.43 9599.60 15292.72 24399.60 20397.38 19999.20 12199.50 127
Patchmatch-test97.93 19397.65 20198.77 20499.18 20197.07 24899.03 27499.14 25396.16 26398.74 22699.57 16194.56 19599.72 17293.36 30899.11 12699.52 119
test_899.67 9299.61 4499.03 27499.41 16996.28 25198.93 20599.48 19598.76 4399.91 74
MS-PatchMatch97.24 26097.32 24496.99 30198.45 30793.51 32198.82 30699.32 21997.41 16398.13 27199.30 24888.99 30699.56 20695.68 26899.80 7097.90 317
Patchmatch-RL test95.84 28995.81 27895.95 31295.61 32990.57 33098.24 33298.39 31895.10 28495.20 30998.67 29794.78 18197.77 32796.28 25790.02 32299.51 124
agg_prior398.97 9398.71 10499.75 3999.67 9299.60 4699.04 27399.41 16995.93 27398.87 21299.48 19598.61 5599.91 7497.63 17699.72 8599.75 55
cdsmvs_eth3d_5k24.64 33232.85 3330.00 3450.00 3590.00 3600.00 35199.51 850.00 3550.00 35699.56 16396.58 1170.00 3580.00 3550.00 3560.00 356
pcd_1.5k_mvsjas8.27 33411.03 3350.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.27 35799.01 110.00 3580.00 3550.00 3560.00 356
pcd1.5k->3k40.85 32843.49 33032.93 34298.95 2470.00 3600.00 35199.53 720.00 3550.00 3560.27 35795.32 1490.00 3580.00 35597.30 23598.80 201
agg_prior199.01 8998.76 10099.76 3899.67 9299.62 4298.99 28399.40 17696.26 25498.87 21299.49 18998.77 4199.91 7497.69 17399.72 8599.75 55
agg_prior297.21 20699.73 8499.75 55
agg_prior99.67 9299.62 4299.40 17698.87 21299.91 74
tmp_tt82.80 32081.52 32086.66 33166.61 35668.44 35492.79 34997.92 32768.96 34780.04 34699.85 2685.77 32896.15 33897.86 15343.89 35195.39 339
canonicalmvs99.02 8698.86 8899.51 8699.42 14999.32 7999.80 1999.48 11398.63 4899.31 12298.81 29197.09 10299.75 15999.27 2997.90 20599.47 134
anonymousdsp98.44 13298.28 13798.94 15898.50 30598.96 12999.77 2499.50 9997.07 19898.87 21299.77 8494.76 18699.28 25198.66 8597.60 21398.57 285
alignmvs98.81 11098.56 12399.58 7299.43 14899.42 7199.51 12898.96 27398.61 5099.35 11698.92 28294.78 18199.77 15599.35 1898.11 19999.54 114
nrg03098.64 12698.42 12899.28 11999.05 22899.69 3199.81 1599.46 13898.04 9999.01 19199.82 4496.69 11599.38 22599.34 2294.59 29098.78 203
v14419297.92 19697.60 20598.87 18798.83 27398.65 17799.55 11799.34 20596.20 25999.32 12199.40 21794.36 20399.26 25996.37 25695.03 27798.70 220
FIs98.78 11498.63 11399.23 12999.18 20199.54 5499.83 1299.59 3898.28 7098.79 22299.81 5396.75 11399.37 22899.08 4396.38 25298.78 203
v192192097.80 21397.45 22198.84 19598.80 27498.53 18899.52 12499.34 20596.15 26599.24 14899.47 19993.98 21799.29 25095.40 27495.13 27598.69 225
UA-Net99.42 2999.29 3699.80 3099.62 11299.55 5399.50 13399.70 1598.79 4099.77 2399.96 197.45 9399.96 1998.92 5599.90 2499.89 2
v119297.81 21097.44 22698.91 17098.88 26498.68 17399.51 12899.34 20596.18 26199.20 16099.34 24094.03 21699.36 23295.32 27695.18 27298.69 225
FC-MVSNet-test98.75 11798.62 11699.15 13599.08 22299.45 6899.86 899.60 3598.23 7598.70 23599.82 4496.80 10999.22 26699.07 4496.38 25298.79 202
v114497.98 18497.69 19598.85 19498.87 26798.66 17699.54 12099.35 19796.27 25399.23 15399.35 23794.67 19199.23 26396.73 24295.16 27398.68 230
sosnet-low-res0.02 3350.03 3360.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.27 3570.00 3630.00 3580.00 3550.00 3560.00 356
HFP-MVS99.49 1399.37 1799.86 1399.87 1599.80 1499.66 6599.67 2298.15 8099.68 3799.69 11499.06 899.96 1998.69 8299.87 3899.84 12
v14897.79 21597.55 20798.50 22598.74 28597.72 23299.54 12099.33 21396.26 25498.90 20999.51 18494.68 19099.14 27397.83 15593.15 31098.63 263
sosnet0.02 3350.03 3360.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.27 3570.00 3630.00 3580.00 3550.00 3560.00 356
v74897.52 24597.23 25198.41 23798.69 29297.23 24199.87 499.45 14995.72 27698.51 25299.53 17694.13 21299.30 24896.78 24092.39 31798.70 220
uncertanet0.02 3350.03 3360.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.27 3570.00 3630.00 3580.00 3550.00 3560.00 356
AllTest98.87 9898.72 10299.31 11199.86 2098.48 19699.56 11299.61 3297.85 11999.36 11399.85 2695.95 13199.85 11296.66 24799.83 6399.59 108
TestCases99.31 11199.86 2098.48 19699.61 3297.85 11999.36 11399.85 2695.95 13199.85 11296.66 24799.83 6399.59 108
v7n97.87 20097.52 20998.92 16698.76 28498.58 18599.84 999.46 13896.20 25998.91 20799.70 10894.89 17499.44 21996.03 26093.89 30398.75 209
v114198.05 17497.76 18898.91 17098.91 25998.78 16699.57 10599.35 19796.41 24499.23 15399.36 23394.93 17099.27 25497.38 19994.72 28498.68 230
region2R99.48 1799.35 2299.87 699.88 1199.80 1499.65 7599.66 2598.13 8299.66 4899.68 11998.96 2099.96 1998.62 9099.87 3899.84 12
testing_294.44 30292.93 30898.98 15294.16 33699.00 12099.42 17099.28 23396.60 22784.86 33996.84 33470.91 34299.27 25498.23 12696.08 25898.68 230
test_normal97.44 25396.77 26399.44 9897.75 31899.00 12099.10 25998.64 31197.71 13693.93 32298.82 29087.39 32399.83 12598.61 9298.97 13899.49 128
v1neww98.12 16297.84 17498.93 16198.97 24298.81 15799.66 6599.35 19796.49 23299.29 12799.37 22695.02 16399.32 24297.73 16794.73 28298.67 241
PS-MVSNAJss98.92 9698.92 7898.90 17498.78 28098.53 18899.78 2299.54 6298.07 9399.00 19899.76 8799.01 1199.37 22899.13 3997.23 23798.81 200
PS-MVSNAJ99.32 4299.32 2699.30 11499.57 12398.94 13398.97 29099.46 13898.92 2899.71 3199.24 25699.01 1199.98 599.35 1899.66 9798.97 182
jajsoiax98.43 13398.28 13798.88 18398.60 30098.43 19899.82 1399.53 7298.19 7698.63 24699.80 6493.22 23299.44 21999.22 3197.50 22298.77 206
mvs_tets98.40 13698.23 13998.91 17098.67 29598.51 19399.66 6599.53 7298.19 7698.65 24499.81 5392.75 24099.44 21999.31 2597.48 22698.77 206
#test#99.43 2799.29 3699.86 1399.87 1599.80 1499.55 11799.67 2297.83 12299.68 3799.69 11499.06 899.96 1998.39 11499.87 3899.84 12
EI-MVSNet-UG-set99.58 399.57 199.64 6399.78 3699.14 9999.60 9099.45 14999.01 1399.90 199.83 3798.98 1899.93 5799.59 299.95 699.86 5
EI-MVSNet-Vis-set99.58 399.56 399.64 6399.78 3699.15 9899.61 8899.45 14999.01 1399.89 299.82 4499.01 1199.92 6599.56 599.95 699.85 8
Regformer-399.57 699.53 599.68 5199.76 4499.29 8399.58 9999.44 15799.01 1399.87 699.80 6498.97 1999.91 7499.44 1699.92 1299.83 23
Regformer-499.59 299.54 499.73 4699.76 4499.41 7299.58 9999.49 10499.02 1099.88 399.80 6499.00 1799.94 4299.45 1599.92 1299.84 12
Regformer-199.53 999.47 899.72 4899.71 8199.44 6999.49 14199.46 13898.95 2499.83 1199.76 8799.01 1199.93 5799.17 3699.87 3899.80 41
Regformer-299.54 799.47 899.75 3999.71 8199.52 6099.49 14199.49 10498.94 2699.83 1199.76 8799.01 1199.94 4299.15 3899.87 3899.80 41
v7new98.12 16297.84 17498.93 16198.97 24298.81 15799.66 6599.35 19796.49 23299.29 12799.37 22695.02 16399.32 24297.73 16794.73 28298.67 241
HPM-MVS++99.39 3699.23 4599.87 699.75 5699.84 699.43 16399.51 8598.68 4799.27 13599.53 17698.64 5499.96 1998.44 11399.80 7099.79 45
test_prior499.56 5198.99 283
XVS99.53 999.42 1199.87 699.85 2399.83 799.69 4599.68 1998.98 1999.37 10999.74 9798.81 3599.94 4298.79 7299.86 4899.84 12
v124097.69 23297.32 24498.79 20198.85 27198.43 19899.48 14699.36 19396.11 26899.27 13599.36 23393.76 22599.24 26294.46 28995.23 27198.70 220
test_prior399.21 5599.05 5999.68 5199.67 9299.48 6498.96 29299.56 4898.34 6699.01 19199.52 18198.68 5199.83 12597.96 14599.74 8199.74 60
v1896.42 27395.80 28098.26 24998.95 24798.82 15599.76 2799.28 23394.58 29194.12 31497.70 31895.22 15698.16 31194.83 28387.80 32897.79 325
pm-mvs197.68 23497.28 24898.88 18399.06 22598.62 18199.50 13399.45 14996.32 24897.87 28199.79 7292.47 25999.35 23597.54 18593.54 30698.67 241
test_prior298.96 29298.34 6699.01 19199.52 18198.68 5197.96 14599.74 81
X-MVStestdata96.55 26995.45 29099.87 699.85 2399.83 799.69 4599.68 1998.98 1999.37 10964.01 35598.81 3599.94 4298.79 7299.86 4899.84 12
test_prior99.68 5199.67 9299.48 6499.56 4899.83 12599.74 60
v1796.42 27395.81 27898.25 25398.94 25098.80 16299.76 2799.28 23394.57 29294.18 31397.71 31795.23 15598.16 31194.86 28187.73 33097.80 320
v1696.39 27595.76 28198.26 24998.96 24598.81 15799.76 2799.28 23394.57 29294.10 31597.70 31895.04 16298.16 31194.70 28587.77 32997.80 320
divwei89l23v2f11298.06 16897.78 18198.91 17098.90 26098.77 16799.57 10599.35 19796.45 23999.24 14899.37 22694.92 17199.27 25497.50 18994.71 28698.68 230
v1596.28 27795.62 28398.25 25398.94 25098.83 14899.76 2799.29 22694.52 29694.02 31897.61 32595.02 16398.13 31594.53 28786.92 33397.80 320
旧先验298.96 29296.70 21999.47 8899.94 4298.19 127
新几何299.01 281
新几何199.75 3999.75 5699.59 4899.54 6296.76 21599.29 12799.64 13798.43 6399.94 4296.92 22999.66 9799.72 71
旧先验199.74 6799.59 4899.54 6299.69 11498.47 6099.68 9599.73 65
无先验98.99 28399.51 8596.89 21099.93 5797.53 18699.72 71
原ACMM298.95 296
原ACMM199.65 5899.73 7299.33 7899.47 12997.46 15699.12 17199.66 12998.67 5399.91 7497.70 17299.69 9299.71 78
v1396.24 28095.58 28598.25 25398.98 23998.83 14899.75 3499.29 22694.35 30193.89 32397.60 32695.17 15898.11 31794.27 29986.86 33697.81 318
v1296.24 28095.58 28598.23 25698.96 24598.81 15799.76 2799.29 22694.42 30093.85 32497.60 32695.12 15998.09 31894.32 29686.85 33797.80 320
test22299.75 5699.49 6398.91 30199.49 10496.42 24299.34 11999.65 13098.28 7399.69 9299.72 71
testdata299.95 3396.67 246
segment_acmp98.96 20
testdata99.54 7699.75 5698.95 13099.51 8597.07 19899.43 9599.70 10898.87 3099.94 4297.76 16399.64 10099.72 71
testdata198.85 30598.32 69
v897.95 19297.63 20398.93 16198.95 24798.81 15799.80 1999.41 16996.03 27299.10 17699.42 21094.92 17199.30 24896.94 22794.08 29998.66 252
131498.68 12298.54 12499.11 14098.89 26398.65 17799.27 21899.49 10496.89 21097.99 27899.56 16397.72 8999.83 12597.74 16699.27 11898.84 198
112199.09 7698.87 8599.75 3999.74 6799.60 4699.27 21899.48 11396.82 21499.25 14399.65 13098.38 6799.93 5797.53 18699.67 9699.73 65
LFMVS97.90 19897.35 23899.54 7699.52 12999.01 11899.39 18198.24 32297.10 19199.65 5199.79 7284.79 33399.91 7499.28 2798.38 17199.69 79
v798.05 17497.78 18198.87 18798.99 23598.67 17499.64 7799.34 20596.31 25099.29 12799.51 18494.78 18199.27 25497.03 21995.15 27498.66 252
v698.12 16297.84 17498.94 15898.94 25098.83 14899.66 6599.34 20596.49 23299.30 12399.37 22694.95 16799.34 23897.77 16294.74 28198.67 241
VDD-MVS97.73 22697.35 23898.88 18399.47 14297.12 24399.34 20198.85 28698.19 7699.67 4399.85 2682.98 33799.92 6599.49 1298.32 17399.60 104
v1196.23 28295.57 28898.21 25998.93 25598.83 14899.72 3999.29 22694.29 30294.05 31797.64 32394.88 17598.04 31992.89 31488.43 32697.77 326
VDDNet97.55 24297.02 25799.16 13399.49 13898.12 21099.38 18699.30 22295.35 28199.68 3799.90 782.62 33999.93 5799.31 2598.13 19199.42 143
v5297.79 21597.50 21398.66 21498.80 27498.62 18199.87 499.44 15795.87 27499.01 19199.46 20394.44 20299.33 23996.65 24993.96 30298.05 307
V1496.26 27895.60 28498.26 24998.94 25098.83 14899.76 2799.29 22694.49 29793.96 32097.66 32194.99 16698.13 31594.41 29086.90 33497.80 320
v1097.85 20297.52 20998.86 19198.99 23598.67 17499.75 3499.41 16995.70 27798.98 20099.41 21394.75 18799.23 26396.01 26194.63 28998.67 241
V497.80 21397.51 21198.67 21398.79 27698.63 17999.87 499.44 15795.87 27499.01 19199.46 20394.52 19899.33 23996.64 25093.97 30198.05 307
VPNet97.84 20497.44 22699.01 14899.21 19498.94 13399.48 14699.57 4498.38 6499.28 13199.73 10088.89 30799.39 22499.19 3393.27 30898.71 216
MVS97.28 25896.55 26599.48 8998.78 28098.95 13099.27 21899.39 17983.53 33998.08 27399.54 16996.97 10599.87 10394.23 30099.16 12399.63 100
v2v48298.06 16897.77 18598.92 16698.90 26098.82 15599.57 10599.36 19396.65 22299.19 16399.35 23794.20 20899.25 26097.72 17194.97 27898.69 225
v198.05 17497.76 18898.93 16198.92 25798.80 16299.57 10599.35 19796.39 24699.28 13199.36 23394.86 17699.32 24297.38 19994.72 28498.68 230
V4298.06 16897.79 17998.86 19198.98 23998.84 14599.69 4599.34 20596.53 23199.30 12399.37 22694.67 19199.32 24297.57 18194.66 28798.42 294
V996.25 27995.58 28598.26 24998.94 25098.83 14899.75 3499.29 22694.45 29993.96 32097.62 32494.94 16898.14 31494.40 29186.87 33597.81 318
SD-MVS99.41 3299.52 699.05 14599.74 6799.68 3299.46 15399.52 7699.11 799.88 399.91 599.43 197.70 32998.72 7999.93 1199.77 51
GA-MVS97.85 20297.47 21899.00 15099.38 16097.99 21398.57 32199.15 25197.04 20198.90 20999.30 24889.83 29999.38 22596.70 24498.33 17299.62 102
MSLP-MVS++99.46 2199.47 899.44 9899.60 11899.16 9599.41 17499.71 1398.98 1999.45 9199.78 7799.19 499.54 20999.28 2799.84 5799.63 100
APDe-MVS99.66 199.57 199.92 199.77 4199.89 199.75 3499.56 4899.02 1099.88 399.85 2699.18 599.96 1999.22 3199.92 1299.90 1
APD-MVS_3200maxsize99.48 1799.35 2299.85 1899.76 4499.83 799.63 7999.54 6298.36 6599.79 1899.82 4498.86 3199.95 3398.62 9099.81 6899.78 49
ADS-MVSNet298.02 17998.07 15097.87 27999.33 16995.19 30199.23 23199.08 25896.24 25699.10 17699.67 12394.11 21398.93 30096.81 23899.05 13299.48 130
EI-MVSNet98.67 12398.67 10898.68 21199.35 16597.97 21499.50 13399.38 18596.93 20899.20 16099.83 3797.87 8399.36 23298.38 11697.56 21798.71 216
Regformer0.02 3350.03 3360.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.27 3570.00 3630.00 3580.00 3550.00 3560.00 356
CVMVSNet98.57 12898.67 10898.30 24599.35 16595.59 29099.50 13399.55 5598.60 5199.39 10599.83 3794.48 19999.45 21498.75 7498.56 16399.85 8
pmmvs498.13 16097.90 16298.81 19898.61 29998.87 14198.99 28399.21 24596.44 24099.06 18699.58 15795.90 13599.11 27997.18 21096.11 25798.46 293
EU-MVSNet97.98 18498.03 15297.81 28598.72 28896.65 27099.66 6599.66 2598.09 8998.35 26299.82 4495.25 15498.01 32197.41 19895.30 27098.78 203
VNet99.11 7298.90 8199.73 4699.52 12999.56 5199.41 17499.39 17999.01 1399.74 3099.78 7795.56 14399.92 6599.52 798.18 18399.72 71
test-LLR98.06 16897.90 16298.55 22398.79 27697.10 24498.67 31597.75 33097.34 16798.61 24998.85 28794.45 20099.45 21497.25 20499.38 11099.10 163
TESTMET0.1,197.55 24297.27 25098.40 23898.93 25596.53 27298.67 31597.61 34096.96 20598.64 24599.28 25188.63 31399.45 21497.30 20399.38 11099.21 157
test-mter97.49 25197.13 25498.55 22398.79 27697.10 24498.67 31597.75 33096.65 22298.61 24998.85 28788.23 31899.45 21497.25 20499.38 11099.10 163
VPA-MVSNet98.29 14297.95 15999.30 11499.16 20899.54 5499.50 13399.58 4398.27 7199.35 11699.37 22692.53 25799.65 19399.35 1894.46 29198.72 214
ACMMPR99.49 1399.36 1999.86 1399.87 1599.79 1899.66 6599.67 2298.15 8099.67 4399.69 11498.95 2599.96 1998.69 8299.87 3899.84 12
testgi97.65 23997.50 21398.13 26499.36 16496.45 27599.42 17099.48 11397.76 13097.87 28199.45 20691.09 28798.81 30394.53 28798.52 16599.13 162
test20.0396.12 28695.96 27596.63 30897.44 32095.45 29699.51 12899.38 18596.55 23096.16 30499.25 25593.76 22596.17 33787.35 33394.22 29698.27 301
thres600view797.86 20197.51 21198.92 16699.72 7597.95 21799.59 9298.74 29897.94 11199.27 13598.62 29891.75 27499.86 10693.73 30498.19 18298.96 188
111192.30 31092.21 31192.55 32193.30 33786.27 33499.15 24798.74 29891.94 32190.85 33497.82 31584.18 33495.21 33979.65 34294.27 29596.19 336
.test124583.42 31886.17 31675.15 34093.30 33786.27 33499.15 24798.74 29891.94 32190.85 33497.82 31584.18 33495.21 33979.65 34239.90 35243.98 353
ADS-MVSNet98.20 15498.08 14898.56 22199.33 16996.48 27499.23 23199.15 25196.24 25699.10 17699.67 12394.11 21399.71 17896.81 23899.05 13299.48 130
MP-MVScopyleft99.33 4199.15 5099.87 699.88 1199.82 1299.66 6599.46 13898.09 8999.48 8799.74 9798.29 7299.96 1997.93 14899.87 3899.82 32
testmvs39.17 33043.78 32925.37 34436.04 35816.84 35998.36 32726.56 35820.06 35338.51 35467.32 35129.64 35815.30 35737.59 35339.90 35243.98 353
thres40097.77 21897.38 23498.92 16699.69 8897.96 21599.50 13398.73 30797.83 12299.17 16698.45 30791.67 28099.83 12593.22 30998.18 18398.96 188
test12339.01 33142.50 33128.53 34339.17 35720.91 35898.75 31119.17 36019.83 35438.57 35366.67 35233.16 35615.42 35637.50 35429.66 35449.26 352
thres20097.61 24097.28 24898.62 21599.64 10598.03 21199.26 22698.74 29897.68 14099.09 18098.32 30991.66 28299.81 13892.88 31598.22 17998.03 310
test0.0.03 197.71 23197.42 23098.56 22198.41 30897.82 22398.78 30898.63 31297.34 16798.05 27798.98 27994.45 20098.98 29295.04 28097.15 24198.89 196
test1235691.74 31192.19 31290.37 32991.22 34182.41 34198.61 31998.28 32090.66 32991.82 33297.92 31384.90 33292.61 34581.64 34194.66 28796.09 337
testus94.61 30095.30 29392.54 32296.44 32784.18 33898.36 32799.03 26694.18 30396.49 30098.57 30488.74 30895.09 34187.41 33298.45 16898.36 300
pmmvs394.09 30593.25 30796.60 30994.76 33494.49 30998.92 29998.18 32589.66 33096.48 30198.06 31286.28 32697.33 33189.68 32587.20 33297.97 313
testmv87.91 31487.80 31588.24 33087.68 34877.50 34899.07 26297.66 33989.27 33186.47 33896.22 33768.35 34492.49 34776.63 34688.82 32594.72 340
EMVS80.02 32279.22 32382.43 33891.19 34276.40 34997.55 34292.49 35766.36 35083.01 34291.27 34464.63 34785.79 35365.82 35160.65 34785.08 350
E-PMN80.61 32179.88 32282.81 33690.75 34376.38 35097.69 33995.76 34766.44 34983.52 34092.25 34362.54 34987.16 35268.53 35061.40 34684.89 351
test235694.07 30694.46 30192.89 32095.18 33286.13 33697.60 34199.06 26393.61 31096.15 30698.28 31085.60 33093.95 34386.68 33698.00 20298.59 281
test123567892.91 30993.30 30691.71 32693.14 33983.01 34098.75 31198.58 31592.80 31892.45 32997.91 31488.51 31593.54 34482.26 34095.35 26998.59 281
PGM-MVS99.45 2299.31 3199.86 1399.87 1599.78 2299.58 9999.65 3097.84 12199.71 3199.80 6499.12 799.97 1198.33 12199.87 3899.83 23
LCM-MVSNet-Re97.83 20698.15 14196.87 30599.30 17892.25 32799.59 9298.26 32197.43 16096.20 30399.13 26496.27 12598.73 30598.17 12998.99 13699.64 96
LCM-MVSNet86.80 31685.22 31991.53 32787.81 34780.96 34498.23 33498.99 26971.05 34590.13 33696.51 33648.45 35396.88 33490.51 32185.30 34096.76 333
MCST-MVS99.43 2799.30 3399.82 2599.79 3599.74 2699.29 21299.40 17698.79 4099.52 8099.62 14698.91 2899.90 8698.64 8799.75 7999.82 32
mvs_anonymous99.03 8598.99 6999.16 13399.38 16098.52 19199.51 12899.38 18597.79 12799.38 10799.81 5397.30 9899.45 21499.35 1898.99 13699.51 124
MVS_Test99.10 7598.97 7299.48 8999.49 13899.14 9999.67 5699.34 20597.31 17099.58 6499.76 8797.65 9099.82 13498.87 6199.07 13199.46 137
MDA-MVSNet-bldmvs94.96 29893.98 30397.92 27698.24 31197.27 23799.15 24799.33 21393.80 30880.09 34599.03 27488.31 31797.86 32593.49 30794.36 29398.62 265
CDPH-MVS99.13 6398.91 8099.80 3099.75 5699.71 2899.15 24799.41 16996.60 22799.60 6099.55 16698.83 3399.90 8697.48 19199.83 6399.78 49
test1299.75 3999.64 10599.61 4499.29 22699.21 15798.38 6799.89 9499.74 8199.74 60
diffmvs98.72 11998.49 12599.43 10199.48 14199.19 9299.62 8299.42 16695.58 27999.37 10999.67 12396.14 12899.74 16098.14 13198.96 13999.37 147
YYNet195.36 29594.51 30097.92 27697.89 31497.10 24499.10 25999.23 24393.26 31580.77 34399.04 27392.81 23998.02 32094.30 29794.18 29798.64 257
PMMVS286.87 31585.37 31891.35 32890.21 34483.80 33998.89 30297.45 34283.13 34091.67 33395.03 33848.49 35294.70 34285.86 33777.62 34395.54 338
MDA-MVSNet_test_wron95.45 29394.60 29898.01 27098.16 31297.21 24299.11 25799.24 24293.49 31280.73 34498.98 27993.02 23398.18 30994.22 30194.45 29298.64 257
tpmvs97.98 18498.02 15397.84 28299.04 22994.73 30899.31 20699.20 24696.10 27198.76 22599.42 21094.94 16899.81 13896.97 22498.45 16898.97 182
PM-MVS92.96 30892.23 31095.14 31495.61 32989.98 33299.37 18898.21 32394.80 28795.04 31197.69 32065.06 34697.90 32494.30 29789.98 32397.54 332
HQP_MVS98.27 14498.22 14098.44 23599.29 18196.97 25799.39 18199.47 12998.97 2299.11 17399.61 14992.71 24499.69 18797.78 16097.63 21098.67 241
plane_prior799.29 18197.03 252
plane_prior699.27 18696.98 25692.71 244
plane_prior599.47 12999.69 18797.78 16097.63 21098.67 241
plane_prior499.61 149
plane_prior397.00 25498.69 4699.11 173
plane_prior299.39 18198.97 22
plane_prior199.26 188
plane_prior96.97 25799.21 23898.45 5997.60 213
PS-CasMVS97.93 19397.59 20698.95 15798.99 23599.06 10699.68 5499.52 7697.13 18598.31 26499.68 11992.44 26399.05 28498.51 10694.08 29998.75 209
UniMVSNet_NR-MVSNet98.22 14997.97 15798.96 15598.92 25798.98 12299.48 14699.53 7297.76 13098.71 22999.46 20396.43 12199.22 26698.57 9792.87 31398.69 225
PEN-MVS97.76 21997.44 22698.72 20898.77 28398.54 18799.78 2299.51 8597.06 20098.29 26699.64 13792.63 25498.89 30198.09 13493.16 30998.72 214
TransMVSNet (Re)97.15 26196.58 26498.86 19199.12 21498.85 14499.49 14198.91 28095.48 28097.16 29399.80 6493.38 22999.11 27994.16 30291.73 31898.62 265
DTE-MVSNet97.51 24897.19 25398.46 23198.63 29898.13 20999.84 999.48 11396.68 22097.97 27999.67 12392.92 23698.56 30796.88 23792.60 31698.70 220
DU-MVS98.08 16797.79 17998.96 15598.87 26798.98 12299.41 17499.45 14997.87 11698.71 22999.50 18694.82 17899.22 26698.57 9792.87 31398.68 230
UniMVSNet (Re)98.29 14298.00 15599.13 13999.00 23499.36 7699.49 14199.51 8597.95 11098.97 20199.13 26496.30 12499.38 22598.36 11993.34 30798.66 252
CP-MVSNet98.09 16697.78 18199.01 14898.97 24299.24 8999.67 5699.46 13897.25 17598.48 25599.64 13793.79 22399.06 28398.63 8894.10 29898.74 212
WR-MVS_H98.13 16097.87 17398.90 17499.02 23298.84 14599.70 4299.59 3897.27 17398.40 25899.19 26095.53 14499.23 26398.34 12093.78 30498.61 274
WR-MVS98.06 16897.73 19299.06 14398.86 27099.25 8899.19 24199.35 19797.30 17198.66 23899.43 20893.94 21899.21 27098.58 9594.28 29498.71 216
NR-MVSNet97.97 18797.61 20499.02 14798.87 26799.26 8799.47 15099.42 16697.63 14397.08 29499.50 18695.07 16199.13 27697.86 15393.59 30598.68 230
Baseline_NR-MVSNet97.76 21997.45 22198.68 21199.09 22198.29 20299.41 17498.85 28695.65 27898.63 24699.67 12394.82 17899.10 28198.07 14092.89 31298.64 257
TranMVSNet+NR-MVSNet97.93 19397.66 19698.76 20698.78 28098.62 18199.65 7599.49 10497.76 13098.49 25499.60 15294.23 20798.97 29998.00 14392.90 31198.70 220
TSAR-MVS + GP.99.36 3899.36 1999.36 10599.67 9298.61 18499.07 26299.33 21399.00 1799.82 1499.81 5399.06 899.84 11899.09 4299.42 10899.65 90
abl_699.44 2599.31 3199.83 2399.85 2399.75 2399.66 6599.59 3898.13 8299.82 1499.81 5398.60 5699.96 1998.46 11199.88 3499.79 45
n20.00 361
nn0.00 361
mPP-MVS99.44 2599.30 3399.86 1399.88 1199.79 1899.69 4599.48 11398.12 8499.50 8399.75 9298.78 3899.97 1198.57 9799.89 3299.83 23
door-mid98.05 326
DI_MVS_plusplus_test97.45 25296.79 26199.44 9897.76 31799.04 10899.21 23898.61 31497.74 13394.01 31998.83 28987.38 32499.83 12598.63 8898.90 14699.44 140
XVG-OURS-SEG-HR98.69 12198.62 11698.89 17699.71 8197.74 23099.12 25199.54 6298.44 6299.42 9899.71 10594.20 20899.92 6598.54 10598.90 14699.00 178
DWT-MVSNet_test97.53 24497.40 23297.93 27599.03 23194.86 30599.57 10598.63 31296.59 22998.36 26198.79 29289.32 30399.74 16098.14 13198.16 19099.20 158
MVSFormer99.17 5999.12 5499.29 11799.51 13198.94 13399.88 199.46 13897.55 14999.80 1699.65 13097.39 9499.28 25199.03 4699.85 5299.65 90
jason99.13 6399.03 6499.45 9599.46 14398.87 14199.12 25199.26 23998.03 10199.79 1899.65 13097.02 10499.85 11299.02 4899.90 2499.65 90
jason: jason.
lupinMVS99.13 6399.01 6899.46 9499.51 13198.94 13399.05 26899.16 25097.86 11799.80 1699.56 16397.39 9499.86 10698.94 5499.85 5299.58 110
test_djsdf98.67 12398.57 12298.98 15298.70 29198.91 13899.88 199.46 13897.55 14999.22 15599.88 1495.73 14199.28 25199.03 4697.62 21298.75 209
Test495.05 29793.67 30599.22 13096.07 32898.94 13399.20 24099.27 23897.71 13689.96 33797.59 32866.18 34599.25 26098.06 14198.96 13999.47 134
HPM-MVS_fast99.51 1299.40 1499.85 1899.91 199.79 1899.76 2799.56 4897.72 13599.76 2899.75 9299.13 699.92 6599.07 4499.92 1299.85 8
PatchFormer-LS_test98.01 18298.05 15197.87 27999.15 21194.76 30799.42 17098.93 27597.12 18798.84 21898.59 30393.74 22799.80 14298.55 10398.17 18999.06 173
testpf95.66 29196.02 27494.58 31598.35 30992.32 32697.25 34397.91 32992.83 31797.03 29698.99 27688.69 31098.61 30695.72 26697.40 23192.80 342
K. test v397.10 26396.79 26198.01 27098.72 28896.33 27999.87 497.05 34497.59 14496.16 30499.80 6488.71 30999.04 28596.69 24596.55 24998.65 255
lessismore_v097.79 28698.69 29295.44 29794.75 34895.71 30899.87 1988.69 31099.32 24295.89 26294.93 28098.62 265
SixPastTwentyTwo97.50 24997.33 24398.03 26798.65 29696.23 28299.77 2498.68 31097.14 18497.90 28099.93 490.45 29299.18 27297.00 22196.43 25198.67 241
OurMVSNet-221017-097.88 19997.77 18598.19 26198.71 29096.53 27299.88 199.00 26897.79 12798.78 22399.94 391.68 27999.35 23597.21 20696.99 24398.69 225
HPM-MVS99.42 2999.28 3899.83 2399.90 399.72 2799.81 1599.54 6297.59 14499.68 3799.63 14198.91 2899.94 4298.58 9599.91 1799.84 12
XVG-OURS98.73 11898.68 10798.88 18399.70 8697.73 23198.92 29999.55 5598.52 5599.45 9199.84 3595.27 15199.91 7498.08 13898.84 15099.00 178
XVG-ACMP-BASELINE97.83 20697.71 19498.20 26099.11 21696.33 27999.41 17499.52 7698.06 9799.05 18799.50 18689.64 30199.73 16897.73 16797.38 23398.53 287
LPG-MVS_test98.22 14998.13 14398.49 22699.33 16997.05 25099.58 9999.55 5597.46 15699.24 14899.83 3792.58 25599.72 17298.09 13497.51 22098.68 230
LGP-MVS_train98.49 22699.33 16997.05 25099.55 5597.46 15699.24 14899.83 3792.58 25599.72 17298.09 13497.51 22098.68 230
test1199.35 197
door97.92 327
EPNet_dtu98.03 17797.96 15898.23 25698.27 31095.54 29399.23 23198.75 29599.02 1097.82 28399.71 10596.11 12999.48 21193.04 31399.65 9999.69 79
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268899.19 5699.10 5699.45 9599.89 898.52 19199.39 18199.94 198.73 4499.11 17399.89 1095.50 14599.94 4299.50 899.97 399.89 2
EPNet98.86 10198.71 10499.30 11497.20 32698.18 20699.62 8298.91 28099.28 298.63 24699.81 5395.96 13099.99 199.24 3099.72 8599.73 65
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS96.83 262
HQP-NCC99.19 19898.98 28798.24 7298.66 238
ACMP_Plane99.19 19898.98 28798.24 7298.66 238
APD-MVScopyleft99.27 5099.08 5799.84 2299.75 5699.79 1899.50 13399.50 9997.16 18399.77 2399.82 4498.78 3899.94 4297.56 18399.86 4899.80 41
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS97.19 208
HQP4-MVS98.66 23899.64 19598.64 257
HQP3-MVS99.39 17997.58 215
HQP2-MVS92.47 259
LP97.04 26496.80 26097.77 28798.90 26095.23 29998.97 29099.06 26394.02 30498.09 27299.41 21393.88 22098.82 30290.46 32298.42 17099.26 155
CNVR-MVS99.42 2999.30 3399.78 3499.62 11299.71 2899.26 22699.52 7698.82 3599.39 10599.71 10598.96 2099.85 11298.59 9499.80 7099.77 51
NCCC99.34 4099.19 4799.79 3399.61 11699.65 3999.30 20899.48 11398.86 3199.21 15799.63 14198.72 4999.90 8698.25 12599.63 10299.80 41
114514_t98.93 9598.67 10899.72 4899.85 2399.53 5799.62 8299.59 3892.65 31999.71 3199.78 7798.06 8099.90 8698.84 6699.91 1799.74 60
CP-MVS99.45 2299.32 2699.85 1899.83 2899.75 2399.69 4599.52 7698.07 9399.53 7899.63 14198.93 2799.97 1198.74 7599.91 1799.83 23
DSMNet-mixed97.25 25997.35 23896.95 30397.84 31593.61 32099.57 10596.63 34596.13 26798.87 21298.61 30294.59 19497.70 32995.08 27998.86 14999.55 112
tpm297.44 25397.34 24197.74 28999.15 21194.36 31199.45 15498.94 27493.45 31498.90 20999.44 20791.35 28599.59 20597.31 20298.07 20099.29 153
NP-MVS99.23 19196.92 26099.40 217
EG-PatchMatch MVS95.97 28895.69 28296.81 30697.78 31692.79 32499.16 24498.93 27596.16 26394.08 31699.22 25882.72 33899.47 21295.67 26997.50 22298.17 304
tpm cat197.39 25597.36 23697.50 29599.17 20693.73 31699.43 16399.31 22091.27 32598.71 22999.08 26894.31 20699.77 15596.41 25598.50 16699.00 178
SteuartSystems-ACMMP99.54 799.42 1199.87 699.82 2999.81 1399.59 9299.51 8598.62 4999.79 1899.83 3799.28 399.97 1198.48 10899.90 2499.84 12
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tpmp4_e2397.34 25697.29 24797.52 29399.25 19093.73 31699.58 9999.19 24994.00 30598.20 26899.41 21390.74 29199.74 16097.13 21498.07 20099.07 172
CostFormer97.72 22897.73 19297.71 29099.15 21194.02 31499.54 12099.02 26794.67 28999.04 18899.35 23792.35 26599.77 15598.50 10797.94 20499.34 150
CR-MVSNet98.17 15697.93 16198.87 18799.18 20198.49 19499.22 23599.33 21396.96 20599.56 6899.38 22294.33 20499.00 29094.83 28398.58 16099.14 160
JIA-IIPM97.50 24997.02 25798.93 16198.73 28697.80 22899.30 20898.97 27191.73 32498.91 20794.86 34095.10 16099.71 17897.58 17997.98 20399.28 154
Patchmtry97.75 22397.40 23298.81 19899.10 21998.87 14199.11 25799.33 21394.83 28698.81 22099.38 22294.33 20499.02 28896.10 25895.57 26698.53 287
PatchT97.03 26596.44 26698.79 20198.99 23598.34 20199.16 24499.07 26192.13 32099.52 8097.31 33394.54 19798.98 29288.54 32898.73 15699.03 175
tpmrst98.33 13998.48 12697.90 27899.16 20894.78 30699.31 20699.11 25597.27 17399.45 9199.59 15495.33 14899.84 11898.48 10898.61 15799.09 167
BH-w/o98.00 18397.89 16698.32 24399.35 16596.20 28399.01 28198.90 28296.42 24298.38 25999.00 27595.26 15399.72 17296.06 25998.61 15799.03 175
tpm97.67 23797.55 20798.03 26799.02 23295.01 30499.43 16398.54 31796.44 24099.12 17199.34 24091.83 27399.60 20397.75 16596.46 25099.48 130
DELS-MVS99.48 1799.42 1199.65 5899.72 7599.40 7499.05 26899.66 2599.14 699.57 6799.80 6498.46 6199.94 4299.57 499.84 5799.60 104
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-untuned98.42 13498.36 13098.59 21799.49 13896.70 26799.27 21899.13 25497.24 17798.80 22199.38 22295.75 14099.74 16097.07 21899.16 12399.33 151
RPMNet96.61 26895.85 27698.87 18799.18 20198.49 19499.22 23599.08 25888.72 33599.56 6897.38 33194.08 21599.00 29086.87 33598.58 16099.14 160
no-one83.04 31980.12 32191.79 32589.44 34685.65 33799.32 20398.32 31989.06 33279.79 34789.16 34844.86 35496.67 33584.33 33946.78 35093.05 341
MVSTER98.49 12998.32 13499.00 15099.35 16599.02 11699.54 12099.38 18597.41 16399.20 16099.73 10093.86 22299.36 23298.87 6197.56 21798.62 265
CPTT-MVS99.11 7298.90 8199.74 4499.80 3499.46 6799.59 9299.49 10497.03 20299.63 5399.69 11497.27 9999.96 1997.82 15699.84 5799.81 36
GBi-Net97.68 23497.48 21698.29 24699.51 13197.26 23899.43 16399.48 11396.49 23299.07 18299.32 24590.26 29498.98 29297.10 21596.65 24598.62 265
PVSNet_Blended_VisFu99.36 3899.28 3899.61 6799.86 2099.07 10599.47 15099.93 297.66 14299.71 3199.86 2297.73 8899.96 1999.47 1399.82 6799.79 45
PVSNet_BlendedMVS98.86 10198.80 9599.03 14699.76 4498.79 16499.28 21599.91 397.42 16299.67 4399.37 22697.53 9199.88 10198.98 5197.29 23698.42 294
UnsupCasMVSNet_eth96.44 27196.12 27097.40 29798.65 29695.65 28899.36 19499.51 8597.13 18596.04 30798.99 27688.40 31698.17 31096.71 24390.27 32198.40 296
UnsupCasMVSNet_bld93.53 30792.51 30996.58 31097.38 32193.82 31598.24 33299.48 11391.10 32793.10 32796.66 33574.89 34198.37 30894.03 30387.71 33197.56 331
PVSNet_Blended99.08 7898.97 7299.42 10299.76 4498.79 16498.78 30899.91 396.74 21699.67 4399.49 18997.53 9199.88 10198.98 5199.85 5299.60 104
FMVSNet596.43 27296.19 26997.15 29899.11 21695.89 28799.32 20399.52 7694.47 29898.34 26399.07 26987.54 32297.07 33292.61 31795.72 26398.47 291
test197.68 23497.48 21698.29 24699.51 13197.26 23899.43 16399.48 11396.49 23299.07 18299.32 24590.26 29498.98 29297.10 21596.65 24598.62 265
new_pmnet96.38 27696.03 27297.41 29698.13 31395.16 30399.05 26899.20 24693.94 30697.39 28998.79 29291.61 28399.04 28590.43 32395.77 26298.05 307
FMVSNet398.03 17797.76 18898.84 19599.39 15998.98 12299.40 18099.38 18596.67 22199.07 18299.28 25192.93 23598.98 29297.10 21596.65 24598.56 286
dp97.75 22397.80 17897.59 29299.10 21993.71 31899.32 20398.88 28496.48 23899.08 18199.55 16692.67 25399.82 13496.52 25198.58 16099.24 156
FMVSNet297.72 22897.36 23698.80 20099.51 13198.84 14599.45 15499.42 16696.49 23298.86 21799.29 25090.26 29498.98 29296.44 25396.56 24898.58 284
FMVSNet196.84 26696.36 26798.29 24699.32 17697.26 23899.43 16399.48 11395.11 28398.55 25199.32 24583.95 33698.98 29295.81 26496.26 25598.62 265
N_pmnet94.95 29995.83 27792.31 32398.47 30679.33 34699.12 25192.81 35593.87 30797.68 28699.13 26493.87 22199.01 28991.38 32096.19 25698.59 281
cascas97.69 23297.43 22998.48 22898.60 30097.30 23598.18 33599.39 17992.96 31698.41 25798.78 29493.77 22499.27 25498.16 13098.61 15798.86 197
BH-RMVSNet98.41 13598.08 14899.40 10399.41 15298.83 14899.30 20898.77 29497.70 13898.94 20499.65 13092.91 23899.74 16096.52 25199.55 10499.64 96
UGNet98.87 9898.69 10699.40 10399.22 19398.72 17199.44 15899.68 1999.24 399.18 16599.42 21092.74 24299.96 1999.34 2299.94 1099.53 118
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-MVS99.06 8098.88 8499.61 6799.62 11299.16 9599.37 18899.56 4898.04 9999.53 7899.62 14696.84 10899.94 4298.85 6598.49 16799.72 71
XXY-MVS98.38 13798.09 14799.24 12799.26 18899.32 7999.56 11299.55 5597.45 15998.71 22999.83 3793.23 23199.63 20098.88 5796.32 25498.76 208
sss99.17 5999.05 5999.53 8099.62 11298.97 12599.36 19499.62 3197.83 12299.67 4399.65 13097.37 9799.95 3399.19 3399.19 12299.68 83
Test_1112_low_res98.89 9798.66 11199.57 7399.69 8898.95 13099.03 27499.47 12996.98 20499.15 16899.23 25796.77 11299.89 9498.83 6898.78 15499.86 5
1112_ss98.98 9198.77 9899.59 6999.68 9199.02 11699.25 22899.48 11397.23 17899.13 16999.58 15796.93 10799.90 8698.87 6198.78 15499.84 12
ab-mvs-re8.30 33311.06 3340.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 35699.58 1570.00 3630.00 3580.00 3550.00 3560.00 356
ab-mvs98.86 10198.63 11399.54 7699.64 10599.19 9299.44 15899.54 6297.77 12999.30 12399.81 5394.20 20899.93 5799.17 3698.82 15199.49 128
TR-MVS97.76 21997.41 23198.82 19799.06 22597.87 21998.87 30498.56 31696.63 22498.68 23799.22 25892.49 25899.65 19395.40 27497.79 20798.95 195
MDTV_nov1_ep13_2view95.18 30299.35 19896.84 21399.58 6495.19 15797.82 15699.46 137
MDTV_nov1_ep1398.32 13499.11 21694.44 31099.27 21898.74 29897.51 15399.40 10499.62 14694.78 18199.76 15897.59 17898.81 153
MIMVSNet195.51 29295.04 29596.92 30497.38 32195.60 28999.52 12499.50 9993.65 30996.97 29899.17 26185.28 33196.56 33688.36 32995.55 26798.60 280
MIMVSNet97.73 22697.45 22198.57 21999.45 14797.50 23499.02 27798.98 27096.11 26899.41 10099.14 26390.28 29398.74 30495.74 26598.93 14299.47 134
IterMVS-LS98.46 13198.42 12898.58 21899.59 12098.00 21299.37 18899.43 16596.94 20799.07 18299.59 15497.87 8399.03 28798.32 12395.62 26598.71 216
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet99.09 7699.03 6499.25 12499.42 14998.73 16999.45 15499.46 13898.11 8699.46 9099.77 8498.01 8199.37 22898.70 8098.92 14499.66 87
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref97.19 239
IterMVS97.83 20697.77 18598.02 26999.58 12196.27 28199.02 27799.48 11397.22 17998.71 22999.70 10892.75 24099.13 27697.46 19496.00 25998.67 241
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon99.12 6898.95 7699.65 5899.74 6799.70 3099.27 21899.57 4496.40 24599.42 9899.68 11998.75 4699.80 14297.98 14499.72 8599.44 140
MVS_111021_LR99.41 3299.33 2599.65 5899.77 4199.51 6298.94 29899.85 698.82 3599.65 5199.74 9798.51 5899.80 14298.83 6899.89 3299.64 96
DP-MVS99.16 6198.95 7699.78 3499.77 4199.53 5799.41 17499.50 9997.03 20299.04 18899.88 1497.39 9499.92 6598.66 8599.90 2499.87 4
ACMMP++97.43 230
HQP-MVS98.02 17997.90 16298.37 24099.19 19896.83 26298.98 28799.39 17998.24 7298.66 23899.40 21792.47 25999.64 19597.19 20897.58 21598.64 257
QAPM98.67 12398.30 13699.80 3099.20 19699.67 3499.77 2499.72 1194.74 28898.73 22799.90 795.78 13999.98 596.96 22599.88 3499.76 54
Vis-MVSNetpermissive99.12 6898.97 7299.56 7599.78 3699.10 10299.68 5499.66 2598.49 5699.86 799.87 1994.77 18599.84 11899.19 3399.41 10999.74 60
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet95.75 29095.16 29497.51 29499.30 17893.69 31998.88 30395.78 34685.09 33898.78 22392.65 34291.29 28699.37 22894.85 28299.85 5299.46 137
IS-MVSNet99.05 8298.87 8599.57 7399.73 7299.32 7999.75 3499.20 24698.02 10299.56 6899.86 2296.54 11899.67 18998.09 13499.13 12599.73 65
HyFIR lowres test99.11 7298.92 7899.65 5899.90 399.37 7599.02 27799.91 397.67 14199.59 6399.75 9295.90 13599.73 16899.53 699.02 13499.86 5
EPMVS97.82 20997.65 20198.35 24198.88 26495.98 28599.49 14194.71 34997.57 14799.26 13999.48 19592.46 26299.71 17897.87 15299.08 13099.35 149
PAPM_NR99.04 8398.84 9199.66 5499.74 6799.44 6999.39 18199.38 18597.70 13899.28 13199.28 25198.34 7099.85 11296.96 22599.45 10699.69 79
TAMVS99.12 6899.08 5799.24 12799.46 14398.55 18699.51 12899.46 13898.09 8999.45 9199.82 4498.34 7099.51 21098.70 8098.93 14299.67 86
PAPR98.63 12798.34 13299.51 8699.40 15799.03 11598.80 30799.36 19396.33 24799.00 19899.12 26798.46 6199.84 11895.23 27799.37 11499.66 87
RPSCF98.22 14998.62 11696.99 30199.82 2991.58 32999.72 3999.44 15796.61 22599.66 4899.89 1095.92 13499.82 13497.46 19499.10 12899.57 111
Vis-MVSNet (Re-imp)98.87 9898.72 10299.31 11199.71 8198.88 14099.80 1999.44 15797.91 11599.36 11399.78 7795.49 14699.43 22397.91 14999.11 12699.62 102
test_040296.64 26796.24 26897.85 28198.85 27196.43 27699.44 15899.26 23993.52 31196.98 29799.52 18188.52 31499.20 27192.58 31897.50 22297.93 315
MVS_111021_HR99.41 3299.32 2699.66 5499.72 7599.47 6698.95 29699.85 698.82 3599.54 7799.73 10098.51 5899.74 16098.91 5699.88 3499.77 51
CSCG99.32 4299.32 2699.32 11099.85 2398.29 20299.71 4199.66 2598.11 8699.41 10099.80 6498.37 6999.96 1998.99 5099.96 599.72 71
PatchMatch-RL98.84 10998.62 11699.52 8499.71 8199.28 8499.06 26699.77 997.74 13399.50 8399.53 17695.41 14799.84 11897.17 21199.64 10099.44 140
API-MVS99.04 8399.03 6499.06 14399.40 15799.31 8299.55 11799.56 4898.54 5399.33 12099.39 22198.76 4399.78 15396.98 22399.78 7498.07 306
Test By Simon98.75 46
TDRefinement95.42 29494.57 29997.97 27389.83 34596.11 28499.48 14698.75 29596.74 21696.68 29999.88 1488.65 31299.71 17898.37 11782.74 34198.09 305
USDC97.34 25697.20 25297.75 28899.07 22395.20 30098.51 32499.04 26597.99 10798.31 26499.86 2289.02 30599.55 20895.67 26997.36 23498.49 289
EPP-MVSNet99.13 6398.99 6999.53 8099.65 10499.06 10699.81 1599.33 21397.43 16099.60 6099.88 1497.14 10199.84 11899.13 3998.94 14199.69 79
PMMVS98.80 11398.62 11699.34 10699.27 18698.70 17298.76 31099.31 22097.34 16799.21 15799.07 26997.20 10099.82 13498.56 10098.87 14899.52 119
PAPM97.59 24197.09 25599.07 14299.06 22598.26 20498.30 33199.10 25694.88 28598.08 27399.34 24096.27 12599.64 19589.87 32498.92 14499.31 152
ACMMPcopyleft99.45 2299.32 2699.82 2599.89 899.67 3499.62 8299.69 1898.12 8499.63 5399.84 3598.73 4899.96 1998.55 10399.83 6399.81 36
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
CNLPA99.14 6298.99 6999.59 6999.58 12199.41 7299.16 24499.44 15798.45 5999.19 16399.49 18998.08 7999.89 9497.73 16799.75 7999.48 130
PatchmatchNetpermissive98.31 14198.36 13098.19 26199.16 20895.32 29899.27 21898.92 27797.37 16699.37 10999.58 15794.90 17399.70 18497.43 19799.21 12099.54 114
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS99.30 4599.17 4999.70 5099.56 12699.52 6099.58 9999.80 897.12 18799.62 5699.73 10098.58 5799.90 8698.61 9299.91 1799.68 83
F-COLMAP99.19 5699.04 6299.64 6399.78 3699.27 8699.42 17099.54 6297.29 17299.41 10099.59 15498.42 6699.93 5798.19 12799.69 9299.73 65
ANet_high77.30 32474.86 32684.62 33475.88 35477.61 34797.63 34093.15 35488.81 33464.27 35089.29 34736.51 35583.93 35475.89 34752.31 34992.33 345
PNet_i23d79.43 32377.68 32484.67 33386.18 35071.69 35396.50 34593.68 35175.17 34371.33 34891.18 34532.18 35790.62 34978.57 34574.34 34491.71 346
wuyk23d40.18 32941.29 33236.84 34186.18 35049.12 35779.73 35022.81 35927.64 35225.46 35528.45 35621.98 35948.89 35555.80 35223.56 35512.51 355
OMC-MVS99.08 7899.04 6299.20 13199.67 9298.22 20599.28 21599.52 7698.07 9399.66 4899.81 5397.79 8699.78 15397.79 15999.81 6899.60 104
MG-MVS99.13 6399.02 6799.45 9599.57 12398.63 17999.07 26299.34 20598.99 1899.61 5899.82 4497.98 8299.87 10397.00 22199.80 7099.85 8
wuykxyi23d74.42 32771.19 32884.14 33576.16 35374.29 35296.00 34692.57 35669.57 34663.84 35187.49 35021.98 35988.86 35075.56 34857.50 34889.26 349
AdaColmapbinary99.01 8998.80 9599.66 5499.56 12699.54 5499.18 24299.70 1598.18 7999.35 11699.63 14196.32 12399.90 8697.48 19199.77 7699.55 112
uanet0.02 3350.03 3360.00 3450.00 3590.00 3600.00 3510.00 3610.00 3550.00 3560.27 3570.00 3630.00 3580.00 3550.00 3560.00 356
ITE_SJBPF98.08 26599.29 18196.37 27798.92 27798.34 6698.83 21999.75 9291.09 28799.62 20195.82 26397.40 23198.25 303
DeepMVS_CXcopyleft93.34 31899.29 18182.27 34399.22 24485.15 33796.33 30299.05 27290.97 28999.73 16893.57 30597.77 20898.01 311
TinyColmap97.12 26296.89 25997.83 28399.07 22395.52 29498.57 32198.74 29897.58 14697.81 28499.79 7288.16 31999.56 20695.10 27897.21 23898.39 297
MAR-MVS98.86 10198.63 11399.54 7699.37 16299.66 3699.45 15499.54 6296.61 22599.01 19199.40 21797.09 10299.86 10697.68 17599.53 10599.10 163
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
LF4IMVS97.52 24597.46 22097.70 29198.98 23995.55 29199.29 21298.82 28998.07 9398.66 23899.64 13789.97 29899.61 20297.01 22096.68 24497.94 314
MSDG98.98 9198.80 9599.53 8099.76 4499.19 9298.75 31199.55 5597.25 17599.47 8899.77 8497.82 8599.87 10396.93 22899.90 2499.54 114
LS3D99.27 5099.12 5499.74 4499.18 20199.75 2399.56 11299.57 4498.45 5999.49 8699.85 2697.77 8799.94 4298.33 12199.84 5799.52 119
CLD-MVS98.16 15898.10 14598.33 24299.29 18196.82 26498.75 31199.44 15797.83 12299.13 16999.55 16692.92 23699.67 18998.32 12397.69 20998.48 290
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS84.93 31785.65 31782.75 33786.77 34963.39 35598.35 32998.92 27774.11 34483.39 34198.98 27950.85 35192.40 34884.54 33894.97 27892.46 343
Gipumacopyleft90.99 31290.15 31393.51 31798.73 28690.12 33193.98 34799.45 14979.32 34292.28 33094.91 33969.61 34397.98 32287.42 33195.67 26492.45 344
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015