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_ROB99.19 199.88 499.87 499.88 1299.91 2199.90 499.96 199.92 799.90 699.97 699.87 3799.81 799.95 4199.54 4499.99 2099.80 25
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
3Dnovator99.15 299.43 8199.36 9099.65 9699.39 24499.42 12699.70 2999.56 17799.23 13499.35 20499.80 6399.17 5199.95 4198.21 16699.84 13399.59 134
3Dnovator+98.92 399.35 10299.24 11599.67 8499.35 25299.47 10599.62 5699.50 20499.44 10199.12 24199.78 7998.77 10399.94 5597.87 18899.72 20099.62 112
DeepC-MVS98.90 499.62 4399.61 4199.67 8499.72 13099.44 11699.24 14099.71 10499.27 12399.93 2699.90 2399.70 1299.93 6698.99 10899.99 2099.64 95
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepC-MVS_fast98.47 599.23 12899.12 13099.56 14299.28 27599.22 17998.99 19999.40 23399.08 15799.58 14699.64 15298.90 8399.83 22697.44 21599.75 18299.63 99
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepPCF-MVS98.42 699.18 14699.02 15999.67 8499.22 28299.75 4397.25 33599.47 21398.72 19599.66 11999.70 11899.29 3799.63 32998.07 17999.81 16099.62 112
ACMH98.42 699.59 4599.54 5399.72 6799.86 3599.62 8299.56 7099.79 6898.77 18799.80 7499.85 4599.64 1499.85 19498.70 13799.89 10699.70 53
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH+98.40 899.50 6699.43 7899.71 7199.86 3599.76 4199.32 11199.77 7399.53 8799.77 8699.76 8899.26 4599.78 26897.77 19499.88 11299.60 123
HY-MVS98.23 998.21 25697.95 25798.99 24699.03 30698.24 25999.61 6098.72 29896.81 29698.73 28199.51 21194.06 28199.86 17896.91 24398.20 33098.86 287
OpenMVScopyleft98.12 1098.23 25497.89 26399.26 21899.19 28799.26 16899.65 5499.69 11391.33 34398.14 31699.77 8598.28 16699.96 3395.41 30999.55 23498.58 300
ACMM98.09 1199.46 7799.38 8499.72 6799.80 6999.69 6299.13 17699.65 13298.99 16299.64 12799.72 10499.39 2499.86 17898.23 16499.81 16099.60 123
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
COLMAP_ROBcopyleft98.06 1299.45 7999.37 8799.70 7799.83 4699.70 5899.38 9299.78 7099.53 8799.67 11599.78 7999.19 4999.86 17897.32 22199.87 11999.55 146
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
TAPA-MVS97.92 1398.03 26397.55 27599.46 16799.47 22699.44 11698.50 25699.62 14386.79 34699.07 24799.26 26198.26 16899.62 33097.28 22599.73 19599.31 228
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP97.51 1499.05 16898.84 18899.67 8499.78 8899.55 9598.88 21399.66 12397.11 29199.47 17399.60 17699.07 6699.89 12496.18 27499.85 12999.58 138
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PVSNet97.47 1598.42 23998.44 21998.35 28799.46 23096.26 30796.70 34299.34 24797.68 26799.00 25299.13 27897.40 22299.72 28997.59 20899.68 20699.08 268
PLCcopyleft97.35 1698.36 24497.99 25399.48 16299.32 26799.24 17598.50 25699.51 20195.19 32698.58 29398.96 30696.95 24499.83 22695.63 30299.25 27699.37 215
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
OpenMVS_ROBcopyleft97.31 1797.36 27896.84 28898.89 25799.29 27399.45 11498.87 21599.48 20986.54 34899.44 17699.74 9497.34 22799.86 17891.61 33399.28 27297.37 340
PCF-MVS96.03 1896.73 30295.86 31399.33 20299.44 23499.16 18996.87 33999.44 22186.58 34798.95 26099.40 23094.38 27999.88 13987.93 34499.80 16598.95 280
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PVSNet_095.53 1995.85 32195.31 32097.47 31598.78 32793.48 33595.72 34599.40 23396.18 30997.37 33797.73 34595.73 26799.58 33695.49 30581.40 35199.36 218
IB-MVS95.41 2095.30 32594.46 32797.84 30698.76 32995.33 32697.33 33396.07 34096.02 31095.37 35097.41 34976.17 35799.96 3397.54 21095.44 35098.22 316
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
PMVScopyleft92.94 2198.82 20598.81 19398.85 25899.84 4297.99 27599.20 15099.47 21399.71 4799.42 18299.82 5898.09 17899.47 34293.88 32999.85 12999.07 272
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVEpermissive92.54 2296.66 30496.11 30798.31 29099.68 14997.55 29097.94 31295.60 34899.37 11390.68 35298.70 32396.56 25098.61 35286.94 35099.55 23498.77 293
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CMPMVSbinary77.52 2398.50 23098.19 24499.41 18598.33 34199.56 9299.01 19499.59 16595.44 32199.57 14899.80 6395.64 26899.46 34596.47 26799.92 8899.21 239
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
conf0.0197.19 28696.74 29298.51 27899.73 12098.35 25199.35 9995.78 34296.54 29999.39 19399.08 28586.57 33799.88 13995.69 29698.57 31397.30 341
GSMVS99.14 253
test_part398.74 23397.71 26499.57 19199.90 10994.47 321
conf0.00297.19 28696.74 29298.51 27899.73 12098.35 25199.35 9995.78 34296.54 29999.39 19399.08 28586.57 33799.88 13995.69 29698.57 31397.30 341
thresconf0.0297.25 28196.74 29298.75 26899.73 12098.35 25199.35 9995.78 34296.54 29999.39 19399.08 28586.57 33799.88 13995.69 29698.57 31398.02 324
tfpn_n40097.25 28196.74 29298.75 26899.73 12098.35 25199.35 9995.78 34296.54 29999.39 19399.08 28586.57 33799.88 13995.69 29698.57 31398.02 324
tfpnconf97.25 28196.74 29298.75 26899.73 12098.35 25199.35 9995.78 34296.54 29999.39 19399.08 28586.57 33799.88 13995.69 29698.57 31398.02 324
tfpnview1197.25 28196.74 29298.75 26899.73 12098.35 25199.35 9995.78 34296.54 29999.39 19399.08 28586.57 33799.88 13995.69 29698.57 31398.02 324
tfpn100097.28 28096.83 28998.64 27599.67 15397.68 28799.41 8395.47 34997.14 28899.43 18099.07 29285.87 34499.88 13996.78 25098.67 31098.34 310
test_part299.62 16499.67 6799.55 158
tfpn_ndepth96.93 29596.43 30398.42 28399.60 16797.72 28399.22 14695.16 35095.91 31299.26 22198.79 31885.56 34599.87 15896.03 28198.35 32697.68 336
test_part199.53 18998.40 15799.68 20699.66 79
conf200view1196.43 30796.03 30997.63 31299.63 16095.93 31399.18 15297.57 32998.75 19298.70 28497.31 35187.04 32999.67 31387.62 34598.51 32297.30 341
thres100view90096.39 30996.03 30997.47 31599.63 16095.93 31399.18 15297.57 32998.75 19298.70 28497.31 35187.04 32999.67 31387.62 34598.51 32296.81 345
tfpnnormal99.43 8199.38 8499.60 12499.87 3299.75 4399.59 6599.78 7099.71 4799.90 3599.69 12498.85 8899.90 10997.25 22799.78 17399.15 249
tfpn200view996.30 31295.89 31197.53 31399.58 17396.11 30999.00 19697.54 33398.43 21598.52 29696.98 35586.85 33299.67 31387.62 34598.51 32296.81 345
view60096.86 29696.52 29997.88 30199.69 14295.87 31799.39 8697.68 32599.11 15298.96 25697.82 34187.40 32499.79 26089.78 33798.83 29597.98 328
view80096.86 29696.52 29997.88 30199.69 14295.87 31799.39 8697.68 32599.11 15298.96 25697.82 34187.40 32499.79 26089.78 33798.83 29597.98 328
conf0.05thres100096.86 29696.52 29997.88 30199.69 14295.87 31799.39 8697.68 32599.11 15298.96 25697.82 34187.40 32499.79 26089.78 33798.83 29597.98 328
tfpn96.86 29696.52 29997.88 30199.69 14295.87 31799.39 8697.68 32599.11 15298.96 25697.82 34187.40 32499.79 26089.78 33798.83 29597.98 328
ESAPD98.87 20098.58 21099.74 5599.62 16499.67 6798.74 23399.53 18997.71 26499.55 15899.57 19198.40 15799.90 10994.47 32199.68 20699.66 79
CHOSEN 280x42098.41 24098.41 22498.40 28599.34 26295.89 31696.94 33899.44 22198.80 18399.25 22299.52 20793.51 28599.98 798.94 12099.98 3699.32 227
CANet99.11 16099.05 15299.28 21198.83 32098.56 23898.71 23899.41 22799.25 13099.23 22699.22 27297.66 21399.94 5599.19 8399.97 4799.33 223
Fast-Effi-MVS+-dtu99.20 14199.12 13099.43 17699.25 27899.69 6299.05 18799.82 4899.50 9098.97 25499.05 29498.98 7399.98 798.20 16799.24 27898.62 296
Effi-MVS+-dtu99.07 16498.92 17799.52 15298.89 31499.78 3599.15 16699.66 12399.34 11698.92 26499.24 26897.69 20699.98 798.11 17699.28 27298.81 291
CANet_DTU98.91 19498.85 18699.09 23698.79 32598.13 26698.18 28299.31 25499.48 9298.86 27099.51 21196.56 25099.95 4199.05 10499.95 6599.19 242
MVS_030499.17 14999.10 13999.38 19199.08 30198.86 22598.46 26399.73 9299.53 8799.35 20499.30 25397.11 23999.96 3399.33 6599.99 2099.33 223
MP-MVS-pluss99.14 15498.92 17799.80 2999.83 4699.83 2298.61 24099.63 14096.84 29599.44 17699.58 18498.81 9099.91 9297.70 19899.82 15299.67 69
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HSP-MVS99.01 17798.76 19799.76 4299.78 8899.73 4999.35 9999.31 25498.54 20899.54 16198.99 29896.81 24699.93 6696.97 24199.53 23999.61 117
sam_mvs190.81 31099.14 253
sam_mvs90.52 314
semantic-postprocess98.51 27899.75 11195.90 31599.84 3799.84 2399.89 3899.73 9895.96 26699.99 499.33 65100.00 199.63 99
TSAR-MVS + MP.99.34 10799.24 11599.63 10799.82 5399.37 14399.26 13499.35 24598.77 18799.57 14899.70 11899.27 4299.88 13997.71 19799.75 18299.65 89
xiu_mvs_v1_base_debu99.23 12899.34 9298.91 25299.59 17098.23 26098.47 25999.66 12399.61 7599.68 11298.94 30999.39 2499.97 1699.18 8599.55 23498.51 303
OPM-MVS99.26 12399.13 12799.63 10799.70 14099.61 8698.58 24499.48 20998.50 21199.52 16699.63 15999.14 5499.76 27697.89 18799.77 17799.51 167
ACMMP_Plus99.28 11799.11 13299.79 3499.75 11199.81 2898.95 20699.53 18998.27 23799.53 16499.73 9898.75 10799.87 15897.70 19899.83 14399.68 62
ambc99.20 22899.35 25298.53 24099.17 15899.46 21699.67 11599.80 6398.46 15199.70 29497.92 18599.70 20399.38 211
MPTG99.30 11499.14 12499.80 2999.81 6199.81 2898.73 23699.53 18999.27 12399.42 18299.63 15998.21 17299.95 4197.83 19199.79 16899.65 89
MTGPAbinary99.53 189
mvs-test198.83 20398.70 20099.22 22598.89 31499.65 7498.88 21399.66 12399.34 11698.29 30598.94 30997.69 20699.96 3398.11 17698.54 32198.04 323
Effi-MVS+99.06 16598.97 17199.34 20099.31 26898.98 20798.31 27599.91 1198.81 18198.79 27698.94 30999.14 5499.84 21098.79 12998.74 30699.20 240
xiu_mvs_v2_base99.02 17399.11 13298.77 26699.37 24998.09 27198.13 28899.51 20199.47 9699.42 18298.54 32999.38 2899.97 1698.83 12699.33 26798.24 315
xiu_mvs_v1_base99.23 12899.34 9298.91 25299.59 17098.23 26098.47 25999.66 12399.61 7599.68 11298.94 30999.39 2499.97 1699.18 8599.55 23498.51 303
new-patchmatchnet99.35 10299.57 4898.71 27499.82 5396.62 30398.55 24999.75 8499.50 9099.88 4699.87 3799.31 3599.88 13999.43 53100.00 199.62 112
pmmvs699.86 699.86 699.83 2499.94 1599.90 499.83 899.91 1199.85 1999.94 2099.95 1299.73 1099.90 10999.65 3599.97 4799.69 56
pmmvs599.19 14499.11 13299.42 17899.76 10398.88 22298.55 24999.73 9298.82 18099.72 10299.62 16696.56 25099.82 23399.32 6899.95 6599.56 143
test_post199.14 17151.63 36089.54 32199.82 23396.86 246
test_post52.41 35990.25 31699.86 178
Fast-Effi-MVS+99.02 17398.87 18399.46 16799.38 24799.50 9999.04 18999.79 6897.17 28698.62 28998.74 32299.34 3499.95 4198.32 15899.41 25898.92 283
patchmatchnet-post99.62 16690.58 31299.94 55
Anonymous2023121199.83 1199.81 1099.89 699.97 499.95 299.88 499.93 699.87 1399.94 2099.98 899.55 2199.95 4199.21 7999.98 3699.78 31
pmmvs-eth3d99.48 7099.47 6999.51 15599.77 9899.41 13098.81 22699.66 12399.42 10899.75 9099.66 14699.20 4899.76 27698.98 11099.99 2099.36 218
GG-mvs-BLEND97.36 31897.59 34896.87 30199.70 2988.49 35794.64 35197.26 35380.66 35399.12 34791.50 33496.50 34796.08 349
xiu_mvs_v1_base_debi99.23 12899.34 9298.91 25299.59 17098.23 26098.47 25999.66 12399.61 7599.68 11298.94 30999.39 2499.97 1699.18 8599.55 23498.51 303
Anonymous2023120699.35 10299.31 9699.47 16499.74 11799.06 20499.28 13099.74 8999.23 13499.72 10299.53 20597.63 21599.88 13999.11 10099.84 13399.48 180
MTAPA99.35 10299.20 12099.80 2999.81 6199.81 2899.33 10899.53 18999.27 12399.42 18299.63 15998.21 17299.95 4197.83 19199.79 16899.65 89
MTMP98.59 304
gm-plane-assit97.59 34889.02 35593.47 33898.30 33399.84 21096.38 268
test9_res95.10 31499.44 24999.50 173
MVP-Stereo99.16 15199.08 14299.43 17699.48 22199.07 20299.08 18499.55 18098.63 20199.31 21499.68 13698.19 17599.78 26898.18 17199.58 22799.45 190
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST999.35 25299.35 15098.11 29199.41 22794.83 33297.92 32398.99 29898.02 18499.85 194
train_agg98.35 24797.95 25799.57 13699.35 25299.35 15098.11 29199.41 22794.90 32897.92 32398.99 29898.02 18499.85 19495.38 31099.44 24999.50 173
gg-mvs-nofinetune95.87 32095.17 32397.97 29898.19 34396.95 29999.69 3889.23 35699.89 1096.24 34699.94 1381.19 35099.51 34093.99 32898.20 33097.44 338
Patchmatch-test198.13 25898.40 22597.31 32099.20 28692.99 33698.17 28498.49 30898.24 23899.10 24399.52 20796.01 26599.83 22697.22 22999.62 22099.12 257
Patchmatch-test98.10 26097.98 25598.48 28299.27 27796.48 30499.40 8599.07 28298.81 18199.23 22699.57 19190.11 31799.87 15896.69 25599.64 21899.09 265
test_899.34 26299.31 15698.08 29699.40 23394.90 32897.87 32798.97 30498.02 18499.84 210
MS-PatchMatch99.00 18098.97 17199.09 23699.11 29898.19 26398.76 23299.33 24898.49 21299.44 17699.58 18498.21 17299.69 30098.20 16799.62 22099.39 208
Patchmatch-RL test98.60 22198.36 23099.33 20299.77 9899.07 20298.27 27699.87 2098.91 17199.74 9899.72 10490.57 31399.79 26098.55 14599.85 12999.11 258
agg_prior398.24 25297.81 26599.53 15099.34 26299.26 16898.09 29399.39 23694.21 33697.77 33298.96 30697.74 20399.84 21095.38 31099.44 24999.50 173
cdsmvs_eth3d_5k24.88 33133.17 3310.00 3440.00 3580.00 3590.00 35099.62 1430.00 3540.00 35599.13 27899.82 60.00 3570.00 3540.00 3550.00 355
pcd_1.5k_mvsjas16.61 33222.14 3330.00 3440.00 3580.00 3590.00 3500.00 3600.00 3540.00 355100.00 199.28 390.00 3570.00 3540.00 3550.00 355
pcd1.5k->3k49.97 32855.52 32933.31 34199.95 130.00 3590.00 35099.81 560.00 3540.00 355100.00 199.96 10.00 3570.00 354100.00 199.92 3
agg_prior198.33 25097.92 25999.57 13699.35 25299.36 14697.99 30599.39 23694.85 33197.76 33398.98 30198.03 18299.85 19495.49 30599.44 24999.51 167
agg_prior294.58 32099.46 24899.50 173
agg_prior99.35 25299.36 14699.39 23697.76 33399.85 194
tmp_tt95.75 32295.42 31996.76 32489.90 35594.42 33198.86 21697.87 32378.01 34999.30 21899.69 12497.70 20495.89 35399.29 7498.14 33499.95 1
canonicalmvs99.02 17399.00 16499.09 23699.10 30098.70 23299.61 6099.66 12399.63 7098.64 28897.65 34699.04 7099.54 33898.79 12998.92 29199.04 275
anonymousdsp99.80 1399.77 1499.90 499.96 599.88 899.73 2199.85 2999.70 4999.92 3199.93 1499.45 2399.97 1699.36 61100.00 199.85 14
alignmvs98.28 25197.96 25699.25 22199.12 29598.93 21699.03 19198.42 31199.64 6798.72 28297.85 33990.86 30999.62 33098.88 12499.13 28299.19 242
nrg03099.70 2899.66 3399.82 2599.76 10399.84 1899.61 6099.70 10799.93 499.78 8299.68 13699.10 5999.78 26899.45 5199.96 5999.83 18
v14419299.55 5499.54 5399.58 13099.78 8899.20 18599.11 17899.62 14399.18 14099.89 3899.72 10498.66 12199.87 15899.88 1499.97 4799.66 79
FIs99.65 4199.58 4599.84 2199.84 4299.85 1399.66 4999.75 8499.86 1699.74 9899.79 7098.27 16799.85 19499.37 6099.93 8599.83 18
v192192099.56 5099.57 4899.55 14599.75 11199.11 19499.05 18799.61 14799.15 14799.88 4699.71 11199.08 6499.87 15899.90 999.97 4799.66 79
UA-Net99.78 1599.76 1899.86 1899.72 13099.71 5199.91 399.95 599.96 299.71 10699.91 2099.15 5399.97 1699.50 48100.00 199.90 5
v119299.57 4799.57 4899.57 13699.77 9899.22 17999.04 18999.60 16199.18 14099.87 5199.72 10499.08 6499.85 19499.89 1399.98 3699.66 79
FC-MVSNet-test99.70 2899.65 3499.86 1899.88 2899.86 1299.72 2599.78 7099.90 699.82 6599.83 5198.45 15299.87 15899.51 4799.97 4799.86 12
v114499.54 5999.53 6199.59 12699.79 8299.28 16299.10 17999.61 14799.20 13899.84 6099.73 9898.67 11999.84 21099.86 1999.98 3699.64 95
sosnet-low-res8.33 33311.11 3340.00 3440.00 3580.00 3590.00 3500.00 3600.00 3540.00 355100.00 10.00 3620.00 3570.00 3540.00 3550.00 355
HFP-MVS99.25 12499.08 14299.76 4299.73 12099.70 5899.31 11899.59 16598.36 22399.36 20299.37 23598.80 9499.91 9297.43 21699.75 18299.68 62
v14899.40 9099.41 8099.39 18999.76 10398.94 21299.09 18399.59 16599.17 14599.81 7199.61 17398.41 15599.69 30099.32 6899.94 7799.53 156
sosnet8.33 33311.11 3340.00 3440.00 3580.00 3590.00 3500.00 3600.00 3540.00 355100.00 10.00 3620.00 3570.00 3540.00 3550.00 355
v74899.76 1799.74 2199.84 2199.95 1399.83 2299.82 1099.80 6099.82 2799.95 1699.87 3798.72 11199.93 6699.72 3499.98 3699.75 40
uncertanet8.33 33311.11 3340.00 3440.00 3580.00 3590.00 3500.00 3600.00 3540.00 355100.00 10.00 3620.00 3570.00 3540.00 3550.00 355
AllTest99.21 13999.07 14699.63 10799.78 8899.64 7699.12 17799.83 4098.63 20199.63 13099.72 10498.68 11699.75 28296.38 26899.83 14399.51 167
TestCases99.63 10799.78 8899.64 7699.83 4098.63 20199.63 13099.72 10498.68 11699.75 28296.38 26899.83 14399.51 167
v7n99.82 1299.80 1299.88 1299.96 599.84 1899.82 1099.82 4899.84 2399.94 2099.91 2099.13 5799.96 3399.83 2099.99 2099.83 18
v114199.54 5999.52 6399.57 13699.78 8899.27 16699.15 16699.61 14799.26 12799.89 3899.69 12498.56 13399.82 23399.82 2399.97 4799.63 99
region2R99.23 12899.05 15299.77 3999.76 10399.70 5899.31 11899.59 16598.41 21899.32 21299.36 24098.73 11099.93 6697.29 22399.74 18999.67 69
testing_299.58 4699.56 5199.62 11599.81 6199.44 11699.14 17199.43 22499.69 5399.82 6599.79 7099.14 5499.79 26099.31 7099.95 6599.63 99
test_normal98.82 20598.67 20399.27 21399.56 19398.83 22798.22 28098.01 31899.03 16099.49 17299.24 26896.21 26099.76 27698.69 13899.56 22899.22 236
v1neww99.55 5499.54 5399.61 11899.80 6999.39 13499.32 11199.61 14799.18 14099.87 5199.69 12498.64 12599.82 23399.79 2699.94 7799.60 123
PS-MVSNAJss99.84 999.82 999.89 699.96 599.77 3799.68 4199.85 2999.95 399.98 399.92 1799.28 3999.98 799.75 31100.00 199.94 2
PS-MVSNAJ99.00 18099.08 14298.76 26799.37 24998.10 27098.00 30399.51 20199.47 9699.41 18898.50 33199.28 3999.97 1698.83 12699.34 26598.20 319
jajsoiax99.89 399.89 399.89 699.96 599.78 3599.70 2999.86 2299.89 1099.98 399.90 2399.94 299.98 799.75 31100.00 199.90 5
mvs_tets99.90 299.90 299.90 499.96 599.79 3399.72 2599.88 1899.92 599.98 399.93 1499.94 299.98 799.77 30100.00 199.92 3
#test#99.12 15798.90 18099.76 4299.73 12099.70 5899.10 17999.59 16597.60 27099.36 20299.37 23598.80 9499.91 9296.84 24799.75 18299.68 62
EI-MVSNet-UG-set99.48 7099.50 6799.42 17899.57 18298.65 23799.24 14099.46 21699.68 5699.80 7499.66 14698.99 7299.89 12499.19 8399.90 10099.72 46
EI-MVSNet-Vis-set99.47 7699.49 6899.42 17899.57 18298.66 23599.24 14099.46 21699.67 5899.79 7999.65 15198.97 7599.89 12499.15 9299.89 10699.71 49
Regformer-399.41 8799.41 8099.40 18699.52 20198.70 23299.17 15899.44 22199.62 7199.75 9099.60 17698.90 8399.85 19498.89 12399.84 13399.65 89
Regformer-499.45 7999.44 7599.50 15799.52 20198.94 21299.17 15899.53 18999.64 6799.76 8999.60 17698.96 7899.90 10998.91 12299.84 13399.67 69
Regformer-199.32 11299.27 11099.47 16499.41 24098.95 21198.99 19999.48 20999.48 9299.66 11999.52 20798.78 10099.87 15898.36 15499.74 18999.60 123
Regformer-299.34 10799.27 11099.53 15099.41 24099.10 19798.99 19999.53 18999.47 9699.66 11999.52 20798.80 9499.89 12498.31 15999.74 18999.60 123
v7new99.55 5499.54 5399.61 11899.80 6999.39 13499.32 11199.61 14799.18 14099.87 5199.69 12498.64 12599.82 23399.79 2699.94 7799.60 123
HPM-MVS++98.96 18698.70 20099.74 5599.52 20199.71 5198.86 21699.19 27498.47 21498.59 29299.06 29398.08 18099.91 9296.94 24299.60 22599.60 123
test_prior499.19 18798.00 303
XVS99.27 12299.11 13299.75 5199.71 13399.71 5199.37 9699.61 14799.29 12098.76 27999.47 21998.47 14999.88 13997.62 20599.73 19599.67 69
v124099.56 5099.58 4599.51 15599.80 6999.00 20599.00 19699.65 13299.15 14799.90 3599.75 9299.09 6199.88 13999.90 999.96 5999.67 69
test_prior398.62 21998.34 23299.46 16799.35 25299.22 17997.95 31099.39 23697.87 25598.05 31899.05 29497.90 19199.69 30095.99 28499.49 24499.48 180
v1899.68 3399.69 2999.65 9699.79 8299.40 13199.68 4199.83 4099.66 6299.93 2699.85 4598.65 12399.84 21099.87 1899.99 2099.71 49
pm-mvs199.79 1499.79 1399.78 3799.91 2199.83 2299.76 1699.87 2099.73 4299.89 3899.87 3799.63 1599.87 15899.54 4499.92 8899.63 99
test_prior297.95 31097.87 25598.05 31899.05 29497.90 19195.99 28499.49 244
X-MVStestdata96.09 31694.87 32499.75 5199.71 13399.71 5199.37 9699.61 14799.29 12098.76 27961.30 35898.47 14999.88 13997.62 20599.73 19599.67 69
test_prior99.46 16799.35 25299.22 17999.39 23699.69 30099.48 180
v1799.70 2899.71 2599.67 8499.81 6199.44 11699.70 2999.83 4099.69 5399.94 2099.87 3798.70 11299.84 21099.88 1499.99 2099.73 43
v1699.70 2899.71 2599.67 8499.81 6199.43 12299.70 2999.83 4099.70 4999.94 2099.87 3798.69 11499.84 21099.88 1499.99 2099.73 43
divwei89l23v2f11299.54 5999.52 6399.57 13699.78 8899.27 16699.15 16699.61 14799.26 12799.89 3899.69 12498.56 13399.82 23399.82 2399.96 5999.63 99
v1599.72 2599.73 2499.68 8199.82 5399.44 11699.70 2999.85 2999.72 4599.95 1699.88 3498.76 10499.84 21099.90 9100.00 199.75 40
旧先验297.94 31295.33 32398.94 26199.88 13996.75 252
新几何298.04 299
新几何199.52 15299.50 21099.22 17999.26 26495.66 32098.60 29199.28 25797.67 20999.89 12495.95 28899.32 26899.45 190
旧先验199.49 21599.29 16099.26 26499.39 23397.67 20999.36 26499.46 188
无先验98.01 30199.23 27195.83 31499.85 19495.79 29399.44 195
原ACMM297.92 314
原ACMM199.37 19599.47 22698.87 22499.27 26296.74 29898.26 30799.32 24897.93 19099.82 23395.96 28799.38 26199.43 201
v1399.76 1799.77 1499.73 6299.86 3599.55 9599.77 1399.86 2299.79 3399.96 899.91 2098.90 8399.87 15899.91 5100.00 199.78 31
v1299.75 1999.77 1499.72 6799.85 3999.53 9899.75 1799.86 2299.78 3499.96 899.90 2398.88 8699.86 17899.91 5100.00 199.77 34
test22299.51 20599.08 20097.83 31999.29 25895.21 32598.68 28699.31 25097.28 22999.38 26199.43 201
testdata299.89 12495.99 284
segment_acmp98.37 160
testdata99.42 17899.51 20598.93 21699.30 25796.20 30898.87 26999.40 23098.33 16499.89 12496.29 27199.28 27299.44 195
testdata197.72 32197.86 258
v899.68 3399.69 2999.65 9699.80 6999.40 13199.66 4999.76 7999.64 6799.93 2699.85 4598.66 12199.84 21099.88 1499.99 2099.71 49
131498.00 26497.90 26298.27 29298.90 31097.45 29299.30 12199.06 28494.98 32797.21 34099.12 28298.43 15399.67 31395.58 30498.56 32097.71 335
112198.56 22598.24 23799.52 15299.49 21599.24 17599.30 12199.22 27295.77 31698.52 29699.29 25697.39 22499.85 19495.79 29399.34 26599.46 188
LFMVS98.46 23598.19 24499.26 21899.24 28098.52 24199.62 5696.94 33699.87 1399.31 21499.58 18491.04 30499.81 25298.68 14099.42 25699.45 190
v799.56 5099.54 5399.61 11899.80 6999.39 13499.30 12199.59 16599.14 14999.82 6599.72 10498.75 10799.84 21099.83 2099.94 7799.61 117
v699.55 5499.54 5399.61 11899.80 6999.39 13499.32 11199.60 16199.18 14099.87 5199.68 13698.65 12399.82 23399.79 2699.95 6599.61 117
VDD-MVS99.20 14199.11 13299.44 17399.43 23698.98 20799.50 7498.32 31499.80 3199.56 15599.69 12496.99 24399.85 19498.99 10899.73 19599.50 173
v1199.75 1999.76 1899.71 7199.85 3999.49 10199.73 2199.84 3799.75 3999.95 1699.90 2398.93 7999.86 17899.92 3100.00 199.77 34
VDDNet98.97 18398.82 19299.42 17899.71 13398.81 22899.62 5698.68 30099.81 2899.38 20099.80 6394.25 28099.85 19498.79 12999.32 26899.59 134
v5299.85 799.84 799.89 699.96 599.89 699.87 599.81 5699.85 1999.96 899.90 2399.27 4299.95 4199.93 199.99 2099.82 23
V1499.73 2499.74 2199.69 7899.83 4699.48 10499.72 2599.85 2999.74 4099.96 899.89 3198.79 9799.85 19499.91 5100.00 199.76 37
v1099.69 3299.69 2999.66 9299.81 6199.39 13499.66 4999.75 8499.60 8099.92 3199.87 3798.75 10799.86 17899.90 999.99 2099.73 43
V499.85 799.84 799.88 1299.96 599.89 699.87 599.81 5699.85 1999.96 899.90 2399.27 4299.95 4199.93 1100.00 199.82 23
VPNet99.46 7799.37 8799.71 7199.82 5399.59 8799.48 7899.70 10799.81 2899.69 11099.58 18497.66 21399.86 17899.17 8899.44 24999.67 69
MVS95.72 32394.63 32698.99 24698.56 33697.98 28099.30 12198.86 29072.71 35197.30 33899.08 28598.34 16299.74 28689.21 34198.33 32799.26 233
v2v48299.50 6699.47 6999.58 13099.78 8899.25 17299.14 17199.58 17399.25 13099.81 7199.62 16698.24 16999.84 21099.83 2099.97 4799.64 95
v199.54 5999.52 6399.58 13099.77 9899.28 16299.15 16699.61 14799.26 12799.88 4699.68 13698.56 13399.82 23399.82 2399.97 4799.63 99
V4299.56 5099.54 5399.63 10799.79 8299.46 10999.39 8699.59 16599.24 13299.86 5699.70 11898.55 13799.82 23399.79 2699.95 6599.60 123
V999.74 2399.75 2099.71 7199.84 4299.50 9999.74 1999.86 2299.76 3899.96 899.90 2398.83 8999.85 19499.91 5100.00 199.77 34
SD-MVS99.01 17799.30 10198.15 29499.50 21099.40 13198.94 20999.61 14799.22 13799.75 9099.82 5899.54 2295.51 35497.48 21399.87 11999.54 153
GA-MVS97.99 26597.68 27298.93 25199.52 20198.04 27497.19 33699.05 28598.32 23498.81 27398.97 30489.89 32099.41 34698.33 15799.05 28699.34 222
MSLP-MVS++99.05 16899.09 14198.91 25299.21 28398.36 25098.82 22599.47 21398.85 17698.90 26799.56 19698.78 10099.09 34898.57 14399.68 20699.26 233
APDe-MVS99.48 7099.36 9099.85 2099.55 19599.81 2899.50 7499.69 11398.99 16299.75 9099.71 11198.79 9799.93 6698.46 14999.85 12999.80 25
APD-MVS_3200maxsize99.31 11399.16 12199.74 5599.53 19999.75 4399.27 13399.61 14799.19 13999.57 14899.64 15298.76 10499.90 10997.29 22399.62 22099.56 143
ADS-MVSNet297.78 26897.66 27498.12 29599.14 29195.36 32599.22 14698.75 29696.97 29298.25 30899.64 15290.90 30799.94 5596.51 26499.56 22899.08 268
EI-MVSNet99.38 9599.44 7599.21 22699.58 17398.09 27199.26 13499.46 21699.62 7199.75 9099.67 14298.54 13999.85 19499.15 9299.92 8899.68 62
Regformer8.33 33311.11 3340.00 3440.00 3580.00 3590.00 3500.00 3600.00 3540.00 355100.00 10.00 3620.00 3570.00 3540.00 3550.00 355
CVMVSNet98.61 22098.88 18297.80 30799.58 17393.60 33499.26 13499.64 13799.66 6299.72 10299.67 14293.26 28799.93 6699.30 7199.81 16099.87 10
pmmvs499.13 15599.06 14899.36 19899.57 18299.10 19798.01 30199.25 26798.78 18699.58 14699.44 22498.24 16999.76 27698.74 13499.93 8599.22 236
EU-MVSNet99.39 9399.62 3898.72 27399.88 2896.44 30599.56 7099.85 2999.90 699.90 3599.85 4598.09 17899.83 22699.58 4199.95 6599.90 5
VNet99.18 14699.06 14899.56 14299.24 28099.36 14699.33 10899.31 25499.67 5899.47 17399.57 19196.48 25399.84 21099.15 9299.30 27099.47 184
test-LLR97.15 28896.95 28597.74 31098.18 34495.02 32897.38 33096.10 33898.00 24697.81 32998.58 32590.04 31899.91 9297.69 20398.78 30098.31 311
TESTMET0.1,196.24 31395.84 31497.41 31798.24 34293.84 33397.38 33095.84 34198.43 21597.81 32998.56 32879.77 35599.89 12497.77 19498.77 30298.52 302
test-mter96.23 31495.73 31697.74 31098.18 34495.02 32897.38 33096.10 33897.90 25397.81 32998.58 32579.12 35699.91 9297.69 20398.78 30098.31 311
VPA-MVSNet99.66 3699.62 3899.79 3499.68 14999.75 4399.62 5699.69 11399.85 1999.80 7499.81 6198.81 9099.91 9299.47 5099.88 11299.70 53
ACMMPR99.23 12899.06 14899.76 4299.74 11799.69 6299.31 11899.59 16598.36 22399.35 20499.38 23498.61 12999.93 6697.43 21699.75 18299.67 69
testgi99.29 11699.26 11299.37 19599.75 11198.81 22898.84 22099.89 1598.38 22199.75 9099.04 29799.36 3399.86 17899.08 10299.25 27699.45 190
test20.0399.55 5499.54 5399.58 13099.79 8299.37 14399.02 19299.89 1599.60 8099.82 6599.62 16698.81 9099.89 12499.43 5399.86 12699.47 184
thres600view796.60 30596.16 30697.93 29999.63 16096.09 31199.18 15297.57 32998.77 18798.72 28297.32 35087.04 32999.72 28988.57 34298.62 31297.98 328
111197.29 27996.71 29899.04 24399.65 15697.72 28398.35 27099.80 6099.40 10999.66 11999.43 22575.10 35899.87 15898.98 11099.98 3699.52 164
.test124585.84 32789.27 32875.54 34099.65 15697.72 28398.35 27099.80 6099.40 10999.66 11999.43 22575.10 35899.87 15898.98 11033.07 35229.03 353
ADS-MVSNet97.72 27097.67 27397.86 30599.14 29194.65 33099.22 14698.86 29096.97 29298.25 30899.64 15290.90 30799.84 21096.51 26499.56 22899.08 268
MP-MVScopyleft99.06 16598.83 19199.76 4299.76 10399.71 5199.32 11199.50 20498.35 22898.97 25499.48 21698.37 16099.92 8395.95 28899.75 18299.63 99
testmvs28.94 33033.33 33015.79 34326.03 3569.81 35896.77 34015.67 35811.55 35323.87 35450.74 36119.03 3618.53 35623.21 35333.07 35229.03 353
thres40096.40 30895.89 31197.92 30099.58 17396.11 30999.00 19697.54 33398.43 21598.52 29696.98 35586.85 33299.67 31387.62 34598.51 32297.98 328
test12329.31 32933.05 33218.08 34225.93 35712.24 35797.53 32710.93 35911.78 35224.21 35350.08 36221.04 3608.60 35523.51 35232.43 35433.39 352
thres20096.09 31695.68 31797.33 31999.48 22196.22 30898.53 25397.57 32998.06 24598.37 30496.73 35786.84 33499.61 33486.99 34998.57 31396.16 348
test0.0.03 197.37 27796.91 28798.74 27297.72 34797.57 28997.60 32397.36 33598.00 24699.21 23098.02 33790.04 31899.79 26098.37 15395.89 34998.86 287
test1235698.43 23798.39 22698.55 27799.46 23096.36 30697.32 33499.81 5697.60 27099.62 13799.37 23594.57 27799.89 12497.80 19399.92 8899.40 206
testus98.15 25798.06 25098.40 28599.11 29895.95 31296.77 34099.89 1595.83 31499.23 22698.47 33297.50 21899.84 21096.58 26199.20 28199.39 208
pmmvs398.08 26197.80 26698.91 25299.41 24097.69 28697.87 31799.66 12395.87 31399.50 17099.51 21190.35 31599.97 1698.55 14599.47 24699.08 268
testmv99.53 6599.51 6699.59 12699.73 12099.31 15698.48 25899.92 799.57 8499.87 5199.79 7099.12 5899.91 9299.16 9199.99 2099.55 146
EMVS96.96 29397.28 27795.99 33698.76 32991.03 34895.26 34898.61 30299.34 11698.92 26498.88 31493.79 28299.66 31892.87 33099.05 28697.30 341
E-PMN97.14 29097.43 27696.27 33298.79 32591.62 34595.54 34699.01 28799.44 10198.88 26899.12 28292.78 29299.68 30894.30 32499.03 28897.50 337
test235695.99 31995.26 32298.18 29396.93 35295.53 32495.31 34798.71 29995.67 31998.48 30097.83 34080.72 35299.88 13995.47 30798.21 32999.11 258
test123567898.93 19398.84 18899.19 22999.46 23098.55 23997.53 32799.77 7398.76 19099.69 11099.48 21696.69 24799.90 10998.30 16099.91 9899.11 258
PGM-MVS99.20 14199.01 16299.77 3999.75 11199.71 5199.16 16499.72 10197.99 24899.42 18299.60 17698.81 9099.93 6696.91 24399.74 18999.66 79
LCM-MVSNet-Re99.28 11799.15 12399.67 8499.33 26699.76 4199.34 10699.97 398.93 16899.91 3399.79 7098.68 11699.93 6696.80 24999.56 22899.30 229
LCM-MVSNet99.95 199.95 199.95 199.99 199.99 199.95 299.97 399.99 1100.00 199.98 899.78 8100.00 199.92 3100.00 199.87 10
MCST-MVS99.02 17398.81 19399.65 9699.58 17399.49 10198.58 24499.07 28298.40 21999.04 24999.25 26398.51 14799.80 25797.31 22299.51 24199.65 89
mvs_anonymous99.28 11799.39 8298.94 24999.19 28797.81 28299.02 19299.55 18099.78 3499.85 5799.80 6398.24 16999.86 17899.57 4299.50 24299.15 249
MVS_Test99.28 11799.31 9699.19 22999.35 25298.79 23099.36 9899.49 20899.17 14599.21 23099.67 14298.78 10099.66 31899.09 10199.66 21599.10 262
MDA-MVSNet-bldmvs99.06 16599.05 15299.07 24099.80 6997.83 28198.89 21199.72 10199.29 12099.63 13099.70 11896.47 25499.89 12498.17 17399.82 15299.50 173
CDPH-MVS98.56 22598.20 24199.61 11899.50 21099.46 10998.32 27499.41 22795.22 32499.21 23099.10 28498.34 16299.82 23395.09 31599.66 21599.56 143
test1299.54 14999.29 27399.33 15399.16 27798.43 30297.54 21699.82 23399.47 24699.48 180
diffmvs98.94 19298.87 18399.13 23399.37 24998.90 21999.25 13899.64 13797.55 27499.04 24999.58 18497.23 23299.64 32798.73 13599.44 24998.86 287
YYNet198.95 18998.99 16798.84 26099.64 15897.14 29798.22 28099.32 25098.92 17099.59 14599.66 14697.40 22299.83 22698.27 16399.90 10099.55 146
PMMVS299.48 7099.45 7399.57 13699.76 10398.99 20698.09 29399.90 1498.95 16599.78 8299.58 18499.57 2099.93 6699.48 4999.95 6599.79 30
MDA-MVSNet_test_wron98.95 18998.99 16798.85 25899.64 15897.16 29698.23 27999.33 24898.93 16899.56 15599.66 14697.39 22499.83 22698.29 16199.88 11299.55 146
tpmvs97.39 27697.69 27196.52 33098.41 33991.76 34399.30 12198.94 28997.74 26297.85 32899.55 20192.40 29699.73 28896.25 27398.73 30898.06 322
PM-MVS99.36 10099.29 10699.58 13099.83 4699.66 7098.95 20699.86 2298.85 17699.81 7199.73 9898.40 15799.92 8398.36 15499.83 14399.17 247
HQP_MVS98.90 19698.68 20299.55 14599.58 17399.24 17598.80 22799.54 18498.94 16699.14 23999.25 26397.24 23099.82 23395.84 29199.78 17399.60 123
plane_prior799.58 17399.38 140
plane_prior699.47 22699.26 16897.24 230
plane_prior599.54 18499.82 23395.84 29199.78 17399.60 123
plane_prior499.25 263
plane_prior399.31 15698.36 22399.14 239
plane_prior298.80 22798.94 166
plane_prior199.51 205
plane_prior99.24 17598.42 26797.87 25599.71 201
PS-CasMVS99.66 3699.58 4599.89 699.80 6999.85 1399.66 4999.73 9299.62 7199.84 6099.71 11198.62 12799.96 3399.30 7199.96 5999.86 12
UniMVSNet_NR-MVSNet99.37 9799.25 11499.72 6799.47 22699.56 9298.97 20499.61 14799.43 10699.67 11599.28 25797.85 19699.95 4199.17 8899.81 16099.65 89
PEN-MVS99.66 3699.59 4399.89 699.83 4699.87 999.66 4999.73 9299.70 4999.84 6099.73 9898.56 13399.96 3399.29 7499.94 7799.83 18
TransMVSNet (Re)99.78 1599.77 1499.81 2799.91 2199.85 1399.75 1799.86 2299.70 4999.91 3399.89 3199.60 1999.87 15899.59 3999.74 18999.71 49
DTE-MVSNet99.68 3399.61 4199.88 1299.80 6999.87 999.67 4699.71 10499.72 4599.84 6099.78 7998.67 11999.97 1699.30 7199.95 6599.80 25
DU-MVS99.33 11099.21 11999.71 7199.43 23699.56 9298.83 22299.53 18999.38 11299.67 11599.36 24097.67 20999.95 4199.17 8899.81 16099.63 99
UniMVSNet (Re)99.37 9799.26 11299.68 8199.51 20599.58 8998.98 20399.60 16199.43 10699.70 10899.36 24097.70 20499.88 13999.20 8299.87 11999.59 134
CP-MVSNet99.54 5999.43 7899.87 1699.76 10399.82 2799.57 6899.61 14799.54 8599.80 7499.64 15297.79 20099.95 4199.21 7999.94 7799.84 15
WR-MVS_H99.61 4499.53 6199.87 1699.80 6999.83 2299.67 4699.75 8499.58 8399.85 5799.69 12498.18 17699.94 5599.28 7699.95 6599.83 18
WR-MVS99.11 16098.93 17499.66 9299.30 27299.42 12698.42 26799.37 24299.04 15999.57 14899.20 27496.89 24599.86 17898.66 14199.87 11999.70 53
NR-MVSNet99.40 9099.31 9699.68 8199.43 23699.55 9599.73 2199.50 20499.46 9999.88 4699.36 24097.54 21699.87 15898.97 11499.87 11999.63 99
Baseline_NR-MVSNet99.49 6899.37 8799.82 2599.91 2199.84 1898.83 22299.86 2299.68 5699.65 12599.88 3497.67 20999.87 15899.03 10599.86 12699.76 37
TranMVSNet+NR-MVSNet99.54 5999.47 6999.76 4299.58 17399.64 7699.30 12199.63 14099.61 7599.71 10699.56 19698.76 10499.96 3399.14 9899.92 8899.68 62
TSAR-MVS + GP.99.12 15799.04 15799.38 19199.34 26299.16 18998.15 28599.29 25898.18 24199.63 13099.62 16699.18 5099.68 30898.20 16799.74 18999.30 229
abl_699.36 10099.23 11799.75 5199.71 13399.74 4899.33 10899.76 7999.07 15899.65 12599.63 15999.09 6199.92 8397.13 23599.76 17999.58 138
n20.00 360
nn0.00 360
mPP-MVS99.19 14499.00 16499.76 4299.76 10399.68 6599.38 9299.54 18498.34 23299.01 25199.50 21498.53 14399.93 6697.18 23399.78 17399.66 79
door-mid99.83 40
DI_MVS_plusplus_test98.80 20898.65 20499.27 21399.57 18298.90 21998.44 26597.95 32199.02 16199.51 16899.23 27196.18 26299.76 27698.52 14799.42 25699.14 253
XVG-OURS-SEG-HR99.16 15198.99 16799.66 9299.84 4299.64 7698.25 27899.73 9298.39 22099.63 13099.43 22599.70 1299.90 10997.34 22098.64 31199.44 195
DWT-MVSNet_test96.03 31895.80 31596.71 32898.50 33891.93 34199.25 13897.87 32395.99 31196.81 34297.61 34781.02 35199.66 31897.20 23297.98 33898.54 301
MVSFormer99.41 8799.44 7599.31 20899.57 18298.40 24699.77 1399.80 6099.73 4299.63 13099.30 25398.02 18499.98 799.43 5399.69 20499.55 146
jason99.16 15199.11 13299.32 20699.75 11198.44 24398.26 27799.39 23698.70 19699.74 9899.30 25398.54 13999.97 1698.48 14899.82 15299.55 146
jason: jason.
lupinMVS98.96 18698.87 18399.24 22399.57 18298.40 24698.12 28999.18 27598.28 23699.63 13099.13 27898.02 18499.97 1698.22 16599.69 20499.35 220
test_djsdf99.84 999.81 1099.91 299.94 1599.84 1899.77 1399.80 6099.73 4299.97 699.92 1799.77 999.98 799.43 53100.00 199.90 5
Test498.65 21898.44 21999.27 21399.57 18298.86 22598.43 26699.41 22798.85 17699.57 14898.95 30893.05 28999.75 28298.57 14399.56 22899.19 242
HPM-MVS_fast99.43 8199.30 10199.80 2999.83 4699.81 2899.52 7299.70 10798.35 22899.51 16899.50 21499.31 3599.88 13998.18 17199.84 13399.69 56
PatchFormer-LS_test96.95 29497.07 28096.62 32998.76 32991.85 34299.18 15298.45 31097.29 28597.73 33597.22 35488.77 32299.76 27698.13 17598.04 33698.25 314
testpf94.48 32695.31 32091.99 33997.22 35189.64 35498.86 21696.52 33794.36 33596.09 34798.76 32082.21 34898.73 35097.05 23896.74 34587.60 350
K. test v398.87 20098.60 20799.69 7899.93 1899.46 10999.74 1994.97 35199.78 3499.88 4699.88 3493.66 28499.97 1699.61 3899.95 6599.64 95
lessismore_v099.64 10399.86 3599.38 14090.66 35499.89 3899.83 5194.56 27899.97 1699.56 4399.92 8899.57 142
SixPastTwentyTwo99.42 8499.30 10199.76 4299.92 1999.67 6799.70 2999.14 27999.65 6599.89 3899.90 2396.20 26199.94 5599.42 5799.92 8899.67 69
OurMVSNet-221017-099.75 1999.71 2599.84 2199.96 599.83 2299.83 899.85 2999.80 3199.93 2699.93 1498.54 13999.93 6699.59 3999.98 3699.76 37
HPM-MVS99.25 12499.07 14699.78 3799.81 6199.75 4399.61 6099.67 11997.72 26399.35 20499.25 26399.23 4699.92 8397.21 23199.82 15299.67 69
XVG-OURS99.21 13999.06 14899.65 9699.82 5399.62 8297.87 31799.74 8998.36 22399.66 11999.68 13699.71 1199.90 10996.84 24799.88 11299.43 201
XVG-ACMP-BASELINE99.23 12899.10 13999.63 10799.82 5399.58 8998.83 22299.72 10198.36 22399.60 14499.71 11198.92 8099.91 9297.08 23699.84 13399.40 206
LPG-MVS_test99.22 13699.05 15299.74 5599.82 5399.63 8099.16 16499.73 9297.56 27299.64 12799.69 12499.37 3099.89 12496.66 25799.87 11999.69 56
LGP-MVS_train99.74 5599.82 5399.63 8099.73 9297.56 27299.64 12799.69 12499.37 3099.89 12496.66 25799.87 11999.69 56
test1199.29 258
door99.77 73
EPNet_dtu97.62 27297.79 26897.11 32396.67 35392.31 33998.51 25598.04 31699.24 13295.77 34899.47 21993.78 28399.66 31898.98 11099.62 22099.37 215
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268899.39 9399.30 10199.65 9699.88 2899.25 17298.78 23199.88 1898.66 19899.96 899.79 7097.45 22099.93 6699.34 6399.99 2099.78 31
EPNet98.13 25897.77 26999.18 23294.57 35497.99 27599.24 14097.96 31999.74 4097.29 33999.62 16693.13 28899.97 1698.59 14299.83 14399.58 138
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS98.94 212
HQP-NCC99.31 26897.98 30697.45 27898.15 312
ACMP_Plane99.31 26897.98 30697.45 27898.15 312
APD-MVScopyleft98.87 20098.59 20899.71 7199.50 21099.62 8299.01 19499.57 17496.80 29799.54 16199.63 15998.29 16599.91 9295.24 31299.71 20199.61 117
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS94.73 317
HQP4-MVS98.15 31299.70 29499.53 156
HQP3-MVS99.37 24299.67 212
HQP2-MVS96.67 248
LP98.34 24998.44 21998.05 29698.88 31795.31 32799.28 13098.74 29799.12 15198.98 25399.79 7093.40 28699.93 6698.38 15299.41 25898.90 284
CNVR-MVS98.99 18298.80 19599.56 14299.25 27899.43 12298.54 25299.27 26298.58 20598.80 27599.43 22598.53 14399.70 29497.22 22999.59 22699.54 153
NCCC98.82 20598.57 21299.58 13099.21 28399.31 15698.61 24099.25 26798.65 19998.43 30299.26 26197.86 19599.81 25296.55 26299.27 27599.61 117
114514_t98.49 23298.11 24799.64 10399.73 12099.58 8999.24 14099.76 7989.94 34599.42 18299.56 19697.76 20299.86 17897.74 19699.82 15299.47 184
CP-MVS99.23 12899.05 15299.75 5199.66 15499.66 7099.38 9299.62 14398.38 22199.06 24899.27 25998.79 9799.94 5597.51 21299.82 15299.66 79
DSMNet-mixed99.48 7099.65 3498.95 24899.71 13397.27 29499.50 7499.82 4899.59 8299.41 18899.85 4599.62 16100.00 199.53 4699.89 10699.59 134
tpm296.35 31096.22 30596.73 32698.88 31791.75 34499.21 14998.51 30693.27 33997.89 32599.21 27384.83 34699.70 29496.04 28098.18 33398.75 294
NP-MVS99.40 24399.13 19298.83 315
EG-PatchMatch MVS99.57 4799.56 5199.62 11599.77 9899.33 15399.26 13499.76 7999.32 11999.80 7499.78 7999.29 3799.87 15899.15 9299.91 9899.66 79
tpm cat196.78 30196.98 28496.16 33598.85 31990.59 35299.08 18499.32 25092.37 34097.73 33599.46 22291.15 30399.69 30096.07 27898.80 29998.21 317
SteuartSystems-ACMMP99.30 11499.14 12499.76 4299.87 3299.66 7099.18 15299.60 16198.55 20799.57 14899.67 14299.03 7199.94 5597.01 23999.80 16599.69 56
Skip Steuart: Steuart Systems R&D Blog.
tpmp4_e2396.11 31596.06 30896.27 33298.90 31090.70 35199.34 10699.03 28693.72 33796.56 34399.31 25083.63 34799.75 28296.06 27998.02 33798.35 309
CostFormer96.71 30396.79 29196.46 33198.90 31090.71 35099.41 8398.68 30094.69 33398.14 31699.34 24786.32 34399.80 25797.60 20798.07 33598.88 285
CR-MVSNet98.35 24798.20 24198.83 26299.05 30498.12 26799.30 12199.67 11997.39 28199.16 23699.79 7091.87 29999.91 9298.78 13298.77 30298.44 306
JIA-IIPM98.06 26297.92 25998.50 28198.59 33597.02 29898.80 22798.51 30699.88 1297.89 32599.87 3791.89 29899.90 10998.16 17497.68 34298.59 298
Patchmtry98.78 21098.54 21599.49 15998.89 31499.19 18799.32 11199.67 11999.65 6599.72 10299.79 7091.87 29999.95 4198.00 18299.97 4799.33 223
PatchT98.45 23698.32 23498.83 26298.94 30898.29 25899.24 14098.82 29399.84 2399.08 24499.76 8891.37 30299.94 5598.82 12899.00 29098.26 313
tpmrst97.73 26998.07 24996.73 32698.71 33292.00 34099.10 17998.86 29098.52 20998.92 26499.54 20391.90 29799.82 23398.02 18099.03 28898.37 308
BH-w/o97.20 28597.01 28397.76 30899.08 30195.69 32198.03 30098.52 30595.76 31797.96 32298.02 33795.62 26999.47 34292.82 33197.25 34498.12 321
tpm97.15 28896.95 28597.75 30998.91 30994.24 33299.32 11197.96 31997.71 26498.29 30599.32 24886.72 33599.92 8398.10 17896.24 34899.09 265
DELS-MVS99.34 10799.30 10199.48 16299.51 20599.36 14698.12 28999.53 18999.36 11599.41 18899.61 17399.22 4799.87 15899.21 7999.68 20699.20 240
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-untuned98.22 25598.09 24898.58 27699.38 24797.24 29598.55 24998.98 28897.81 26199.20 23598.76 32097.01 24299.65 32594.83 31698.33 32798.86 287
RPMNet98.53 22898.44 21998.83 26299.05 30498.12 26799.30 12198.78 29599.86 1699.16 23699.74 9492.53 29599.91 9298.75 13398.77 30298.44 306
no-one99.28 11799.23 11799.45 17199.87 3299.08 20098.95 20699.52 19998.88 17399.77 8699.83 5197.78 20199.90 10998.46 14999.99 2099.38 211
MVSTER98.47 23498.22 23999.24 22399.06 30398.35 25199.08 18499.46 21699.27 12399.75 9099.66 14688.61 32399.85 19499.14 9899.92 8899.52 164
CPTT-MVS98.74 21398.44 21999.64 10399.61 16699.38 14099.18 15299.55 18096.49 30599.27 21999.37 23597.11 23999.92 8395.74 29599.67 21299.62 112
GBi-Net99.42 8499.31 9699.73 6299.49 21599.77 3799.68 4199.70 10799.44 10199.62 13799.83 5197.21 23399.90 10998.96 11599.90 10099.53 156
PVSNet_Blended_VisFu99.40 9099.38 8499.44 17399.90 2598.66 23598.94 20999.91 1197.97 25099.79 7999.73 9899.05 6999.97 1699.15 9299.99 2099.68 62
PVSNet_BlendedMVS99.03 17199.01 16299.09 23699.54 19697.99 27598.58 24499.82 4897.62 26999.34 20899.71 11198.52 14599.77 27497.98 18399.97 4799.52 164
UnsupCasMVSNet_eth98.83 20398.57 21299.59 12699.68 14999.45 11498.99 19999.67 11999.48 9299.55 15899.36 24094.92 27399.86 17898.95 11996.57 34699.45 190
UnsupCasMVSNet_bld98.55 22798.27 23699.40 18699.56 19399.37 14397.97 30999.68 11697.49 27799.08 24499.35 24595.41 27299.82 23397.70 19898.19 33299.01 278
PVSNet_Blended98.70 21698.59 20899.02 24599.54 19697.99 27597.58 32499.82 4895.70 31899.34 20898.98 30198.52 14599.77 27497.98 18399.83 14399.30 229
FMVSNet597.80 26797.25 27899.42 17898.83 32098.97 20999.38 9299.80 6098.87 17499.25 22299.69 12480.60 35499.91 9298.96 11599.90 10099.38 211
test199.42 8499.31 9699.73 6299.49 21599.77 3799.68 4199.70 10799.44 10199.62 13799.83 5197.21 23399.90 10998.96 11599.90 10099.53 156
new_pmnet98.88 19998.89 18198.84 26099.70 14097.62 28898.15 28599.50 20497.98 24999.62 13799.54 20398.15 17799.94 5597.55 20999.84 13398.95 280
FMVSNet398.80 20898.63 20699.32 20699.13 29398.72 23199.10 17999.48 20999.23 13499.62 13799.64 15292.57 29399.86 17898.96 11599.90 10099.39 208
dp96.86 29697.07 28096.24 33498.68 33490.30 35399.19 15198.38 31397.35 28398.23 31099.59 18287.23 32899.82 23396.27 27298.73 30898.59 298
FMVSNet299.35 10299.28 10899.55 14599.49 21599.35 15099.45 7999.57 17499.44 10199.70 10899.74 9497.21 23399.87 15899.03 10599.94 7799.44 195
FMVSNet199.66 3699.63 3799.73 6299.78 8899.77 3799.68 4199.70 10799.67 5899.82 6599.83 5198.98 7399.90 10999.24 7899.97 4799.53 156
N_pmnet98.73 21598.53 21699.35 19999.72 13098.67 23498.34 27294.65 35298.35 22899.79 7999.68 13698.03 18299.93 6698.28 16299.92 8899.44 195
cascas96.99 29296.82 29097.48 31497.57 35095.64 32296.43 34499.56 17791.75 34197.13 34197.61 34795.58 27098.63 35196.68 25699.11 28398.18 320
BH-RMVSNet98.41 24098.14 24699.21 22699.21 28398.47 24298.60 24298.26 31598.35 22898.93 26299.31 25097.20 23699.66 31894.32 32399.10 28499.51 167
UGNet99.38 9599.34 9299.49 15998.90 31098.90 21999.70 2999.35 24599.86 1698.57 29499.81 6198.50 14899.93 6699.38 5899.98 3699.66 79
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-MVS98.59 22398.37 22999.26 21899.43 23698.40 24698.74 23399.13 28198.10 24399.21 23099.24 26894.82 27599.90 10997.86 18998.77 30299.49 179
XXY-MVS99.71 2799.67 3299.81 2799.89 2799.72 5099.59 6599.82 4899.39 11199.82 6599.84 5099.38 2899.91 9299.38 5899.93 8599.80 25
sss98.90 19698.77 19699.27 21399.48 22198.44 24398.72 23799.32 25097.94 25299.37 20199.35 24596.31 25899.91 9298.85 12599.63 21999.47 184
Test_1112_low_res98.95 18998.73 19899.63 10799.68 14999.15 19198.09 29399.80 6097.14 28899.46 17599.40 23096.11 26399.89 12499.01 10799.84 13399.84 15
1112_ss99.05 16898.84 18899.67 8499.66 15499.29 16098.52 25499.82 4897.65 26899.43 18099.16 27696.42 25699.91 9299.07 10399.84 13399.80 25
ab-mvs-re8.26 33811.02 3390.00 3440.00 3580.00 3590.00 3500.00 3600.00 3540.00 35599.16 2760.00 3620.00 3570.00 3540.00 3550.00 355
ab-mvs99.33 11099.28 10899.47 16499.57 18299.39 13499.78 1299.43 22498.87 17499.57 14899.82 5898.06 18199.87 15898.69 13899.73 19599.15 249
TR-MVS97.44 27597.15 27998.32 28998.53 33797.46 29198.47 25997.91 32296.85 29498.21 31198.51 33096.42 25699.51 34092.16 33297.29 34397.98 328
MDTV_nov1_ep13_2view91.44 34799.14 17197.37 28299.21 23091.78 30196.75 25299.03 276
MDTV_nov1_ep1397.73 27098.70 33390.83 34999.15 16698.02 31798.51 21098.82 27299.61 17390.98 30599.66 31896.89 24598.92 291
MIMVSNet199.66 3699.62 3899.80 2999.94 1599.87 999.69 3899.77 7399.78 3499.93 2699.89 3197.94 18999.92 8399.65 3599.98 3699.62 112
MIMVSNet98.43 23798.20 24199.11 23499.53 19998.38 24999.58 6798.61 30298.96 16499.33 21099.76 8890.92 30699.81 25297.38 21999.76 17999.15 249
IterMVS-LS99.41 8799.47 6999.25 22199.81 6198.09 27198.85 21999.76 7999.62 7199.83 6499.64 15298.54 13999.97 1699.15 9299.99 2099.68 62
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet99.22 13699.13 12799.50 15799.35 25299.11 19498.96 20599.54 18499.46 9999.61 14299.70 11896.31 25899.83 22699.34 6399.88 11299.55 146
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref99.94 77
IterMVS98.97 18399.16 12198.42 28399.74 11795.64 32298.06 29899.83 4099.83 2699.85 5799.74 9496.10 26499.99 499.27 77100.00 199.63 99
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon98.50 23098.23 23899.31 20899.49 21599.46 10998.56 24899.63 14094.86 33098.85 27199.37 23597.81 19899.59 33596.08 27799.44 24998.88 285
MVS_111021_LR99.13 15599.03 15899.42 17899.58 17399.32 15597.91 31699.73 9298.68 19799.31 21499.48 21699.09 6199.66 31897.70 19899.77 17799.29 232
DP-MVS99.48 7099.39 8299.74 5599.57 18299.62 8299.29 12999.61 14799.87 1399.74 9899.76 8898.69 11499.87 15898.20 16799.80 16599.75 40
ACMMP++99.79 168
HQP-MVS98.36 24498.02 25299.39 18999.31 26898.94 21297.98 30699.37 24297.45 27898.15 31298.83 31596.67 24899.70 29494.73 31799.67 21299.53 156
QAPM98.40 24297.99 25399.65 9699.39 24499.47 10599.67 4699.52 19991.70 34298.78 27899.80 6398.55 13799.95 4194.71 31999.75 18299.53 156
Vis-MVSNetpermissive99.75 1999.74 2199.79 3499.88 2899.66 7099.69 3899.92 799.67 5899.77 8699.75 9299.61 1799.98 799.35 6299.98 3699.72 46
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet97.86 26698.22 23996.76 32499.28 27591.53 34698.38 26992.60 35399.13 15099.31 21499.96 1197.18 23799.68 30898.34 15699.83 14399.07 272
IS-MVSNet99.03 17198.85 18699.55 14599.80 6999.25 17299.73 2199.15 27899.37 11399.61 14299.71 11194.73 27699.81 25297.70 19899.88 11299.58 138
HyFIR lowres test98.91 19498.64 20599.73 6299.85 3999.47 10598.07 29799.83 4098.64 20099.89 3899.60 17692.57 293100.00 199.33 6599.97 4799.72 46
EPMVS96.53 30696.32 30497.17 32298.18 34492.97 33799.39 8689.95 35598.21 23998.61 29099.59 18286.69 33699.72 28996.99 24099.23 28098.81 291
PAPM_NR98.36 24498.04 25199.33 20299.48 22198.93 21698.79 23099.28 26197.54 27598.56 29598.57 32797.12 23899.69 30094.09 32798.90 29399.38 211
TAMVS99.49 6899.45 7399.63 10799.48 22199.42 12699.45 7999.57 17499.66 6299.78 8299.83 5197.85 19699.86 17899.44 5299.96 5999.61 117
PAPR97.56 27497.07 28099.04 24398.80 32498.11 26997.63 32299.25 26794.56 33498.02 32198.25 33597.43 22199.68 30890.90 33698.74 30699.33 223
RPSCF99.18 14699.02 15999.64 10399.83 4699.85 1399.44 8199.82 4898.33 23399.50 17099.78 7997.90 19199.65 32596.78 25099.83 14399.44 195
Vis-MVSNet (Re-imp)98.77 21198.58 21099.34 20099.78 8898.88 22299.61 6099.56 17799.11 15299.24 22599.56 19693.00 29199.78 26897.43 21699.89 10699.35 220
test_040299.22 13699.14 12499.45 17199.79 8299.43 12299.28 13099.68 11699.54 8599.40 19299.56 19699.07 6699.82 23396.01 28299.96 5999.11 258
MVS_111021_HR99.12 15799.02 15999.40 18699.50 21099.11 19497.92 31499.71 10498.76 19099.08 24499.47 21999.17 5199.54 33897.85 19099.76 17999.54 153
CSCG99.37 9799.29 10699.60 12499.71 13399.46 10999.43 8299.85 2998.79 18499.41 18899.60 17698.92 8099.92 8398.02 18099.92 8899.43 201
PatchMatch-RL98.68 21798.47 21799.30 21099.44 23499.28 16298.14 28799.54 18497.12 29099.11 24299.25 26397.80 19999.70 29496.51 26499.30 27098.93 282
API-MVS98.38 24398.39 22698.35 28798.83 32099.26 16899.14 17199.18 27598.59 20498.66 28798.78 31998.61 12999.57 33794.14 32699.56 22896.21 347
Test By Simon98.41 155
TDRefinement99.72 2599.70 2899.77 3999.90 2599.85 1399.86 799.92 799.69 5399.78 8299.92 1799.37 3099.88 13998.93 12199.95 6599.60 123
USDC98.96 18698.93 17499.05 24299.54 19697.99 27597.07 33799.80 6098.21 23999.75 9099.77 8598.43 15399.64 32797.90 18699.88 11299.51 167
EPP-MVSNet99.17 14999.00 16499.66 9299.80 6999.43 12299.70 2999.24 27099.48 9299.56 15599.77 8594.89 27499.93 6698.72 13699.89 10699.63 99
PMMVS98.49 23298.29 23599.11 23498.96 30798.42 24597.54 32599.32 25097.53 27698.47 30198.15 33697.88 19499.82 23397.46 21499.24 27899.09 265
PAPM95.61 32494.71 32598.31 29099.12 29596.63 30296.66 34398.46 30990.77 34496.25 34598.68 32493.01 29099.69 30081.60 35197.86 34098.62 296
ACMMPcopyleft99.25 12499.08 14299.74 5599.79 8299.68 6599.50 7499.65 13298.07 24499.52 16699.69 12498.57 13299.92 8397.18 23399.79 16899.63 99
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
CNLPA98.57 22498.34 23299.28 21199.18 28999.10 19798.34 27299.41 22798.48 21398.52 29698.98 30197.05 24199.78 26895.59 30399.50 24298.96 279
PatchmatchNetpermissive97.65 27197.80 26697.18 32198.82 32392.49 33899.17 15898.39 31298.12 24298.79 27699.58 18490.71 31199.89 12497.23 22899.41 25899.16 248
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS99.11 16098.95 17399.59 12699.13 29399.59 8799.17 15899.65 13297.88 25499.25 22299.46 22298.97 7599.80 25797.26 22699.82 15299.37 215
F-COLMAP98.74 21398.45 21899.62 11599.57 18299.47 10598.84 22099.65 13296.31 30798.93 26299.19 27597.68 20899.87 15896.52 26399.37 26399.53 156
ANet_high99.88 499.87 499.91 299.99 199.91 399.65 54100.00 199.90 6100.00 199.97 1099.61 1799.97 1699.75 31100.00 199.84 15
PNet_i23d97.02 29197.87 26494.49 33799.69 14284.81 35695.18 34999.85 2997.83 26099.32 21299.57 19195.53 27199.47 34296.09 27697.74 34199.18 245
wuyk23d97.58 27399.13 12792.93 33899.69 14299.49 10199.52 7299.77 7397.97 25099.96 899.79 7099.84 499.94 5595.85 29099.82 15279.36 351
OMC-MVS98.90 19698.72 19999.44 17399.39 24499.42 12698.58 24499.64 13797.31 28499.44 17699.62 16698.59 13199.69 30096.17 27599.79 16899.22 236
MG-MVS98.52 22998.39 22698.94 24999.15 29097.39 29398.18 28299.21 27398.89 17299.23 22699.63 15997.37 22699.74 28694.22 32599.61 22499.69 56
wuykxyi23d99.65 4199.64 3699.69 7899.92 1999.20 18598.89 21199.99 298.73 19499.95 1699.80 6399.84 499.99 499.64 3799.98 3699.89 9
AdaColmapbinary98.60 22198.35 23199.38 19199.12 29599.22 17998.67 23999.42 22697.84 25998.81 27399.27 25997.32 22899.81 25295.14 31399.53 23999.10 262
uanet8.33 33311.11 3340.00 3440.00 3580.00 3590.00 3500.00 3600.00 3540.00 355100.00 10.00 3620.00 3570.00 3540.00 3550.00 355
ITE_SJBPF99.38 19199.63 16099.44 11699.73 9298.56 20699.33 21099.53 20598.88 8699.68 30896.01 28299.65 21799.02 277
DeepMVS_CXcopyleft97.98 29799.69 14296.95 29999.26 26475.51 35095.74 34998.28 33496.47 25499.62 33091.23 33597.89 33997.38 339
TinyColmap98.97 18398.93 17499.07 24099.46 23098.19 26397.75 32099.75 8498.79 18499.54 16199.70 11898.97 7599.62 33096.63 25999.83 14399.41 205
MAR-MVS98.24 25297.92 25999.19 22998.78 32799.65 7499.17 15899.14 27995.36 32298.04 32098.81 31797.47 21999.72 28995.47 30799.06 28598.21 317
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
LF4IMVS99.01 17798.92 17799.27 21399.71 13399.28 16298.59 24399.77 7398.32 23499.39 19399.41 22998.62 12799.84 21096.62 26099.84 13398.69 295
MSDG99.08 16398.98 17099.37 19599.60 16799.13 19297.54 32599.74 8998.84 17999.53 16499.55 20199.10 5999.79 26097.07 23799.86 12699.18 245
LS3D99.24 12799.11 13299.61 11898.38 34099.79 3399.57 6899.68 11699.61 7599.15 23899.71 11198.70 11299.91 9297.54 21099.68 20699.13 256
CLD-MVS98.76 21298.57 21299.33 20299.57 18298.97 20997.53 32799.55 18096.41 30699.27 21999.13 27899.07 6699.78 26896.73 25499.89 10699.23 235
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS96.32 31195.50 31898.79 26599.60 16798.17 26598.46 26398.80 29497.16 28796.28 34499.63 15982.19 34999.09 34888.45 34398.89 29499.10 262
Gipumacopyleft99.57 4799.59 4399.49 15999.98 399.71 5199.72 2599.84 3799.81 2899.94 2099.78 7998.91 8299.71 29398.41 15199.95 6599.05 274
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015