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 1199.91 1599.90 499.96 199.92 599.90 799.97 699.87 3099.81 599.95 4299.54 2499.99 1299.80 23
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 6399.36 7299.65 9599.39 22899.42 13699.70 2299.56 17099.23 12599.35 20199.80 5199.17 5099.95 4298.21 15299.84 12099.59 124
3Dnovator+98.92 399.35 8699.24 10099.67 8399.35 23899.47 11799.62 4699.50 20499.44 9499.12 24299.78 6498.77 10499.94 5397.87 18299.72 19299.62 104
DeepC-MVS98.90 499.62 3299.61 2999.67 8399.72 10699.44 12899.24 12199.71 9099.27 11799.93 1499.90 2199.70 1199.93 6698.99 9299.99 1299.64 87
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 11399.12 11899.56 13699.28 26399.22 18498.99 18999.40 23799.08 14699.58 14199.64 13998.90 8599.83 22497.44 21799.75 17299.63 92
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 13599.02 15099.67 8399.22 27199.75 4797.25 33499.47 21598.72 19099.66 11199.70 10599.29 3899.63 32498.07 16699.81 14799.62 104
ACMH98.42 699.59 3599.54 4399.72 7199.86 2999.62 9099.56 6099.79 5298.77 18599.80 5899.85 3599.64 1399.85 19898.70 12199.89 9099.70 47
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
ACMH+98.40 899.50 4899.43 6099.71 7599.86 2999.76 4599.32 9699.77 5999.53 7899.77 7199.76 7499.26 4499.78 26297.77 19099.88 9899.60 115
HY-MVS98.23 998.21 26097.95 25998.99 24599.03 30198.24 25799.61 5098.72 30596.81 30398.73 28099.51 20594.06 28499.86 18096.91 24798.20 32898.86 295
OpenMVScopyleft98.12 1098.23 25897.89 26999.26 21699.19 27799.26 17199.65 4399.69 10091.33 34198.14 31499.77 7198.28 16399.96 3395.41 30899.55 24098.58 309
ACMM98.09 1199.46 5999.38 6699.72 7199.80 5599.69 7099.13 15899.65 12298.99 15599.64 11799.72 9199.39 2399.86 18098.23 15099.81 14799.60 115
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
COLMAP_ROBcopyleft98.06 1299.45 6199.37 6999.70 7999.83 3699.70 6699.38 8399.78 5699.53 7899.67 10799.78 6499.19 4899.86 18097.32 22399.87 10699.55 140
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 26697.55 27999.46 16399.47 20699.44 12898.50 24999.62 13386.79 34499.07 24899.26 26698.26 16599.62 32597.28 22799.73 18799.31 227
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMP97.51 1499.05 16398.84 18599.67 8399.78 7199.55 10998.88 20299.66 11197.11 29699.47 17199.60 17299.07 6599.89 13296.18 28399.85 11699.58 129
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
PVSNet97.47 1598.42 24298.44 22198.35 28999.46 21196.26 31496.70 34299.34 25397.68 26999.00 25299.13 28497.40 22499.72 28297.59 20999.68 20499.08 273
PLCcopyleft97.35 1698.36 24797.99 25599.48 15899.32 25499.24 18098.50 24999.51 20195.19 32698.58 29198.96 30896.95 24599.83 22495.63 30299.25 28799.37 213
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
OpenMVS_ROBcopyleft97.31 1797.36 28796.84 29798.89 26299.29 26199.45 12698.87 20599.48 21186.54 34699.44 17699.74 8197.34 22999.86 18091.61 33499.28 28397.37 340
PCF-MVS96.03 1896.73 30095.86 31099.33 20099.44 21799.16 19396.87 34099.44 22486.58 34598.95 25599.40 23294.38 28299.88 14787.93 34299.80 15298.95 287
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
PVSNet_095.53 1995.85 31695.31 31797.47 31498.78 32593.48 33695.72 34599.40 23796.18 31297.37 33497.73 34495.73 27099.58 33295.49 30581.40 34899.36 216
IB-MVS95.41 2095.30 32094.46 32297.84 30598.76 32795.33 32697.33 33196.07 34196.02 31395.37 34797.41 34876.17 35599.96 3397.54 21195.44 34698.22 325
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 20198.81 18998.85 26399.84 3397.99 27399.20 13199.47 21599.71 4099.42 18299.82 4698.09 17999.47 33993.88 32999.85 11699.07 278
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
MVEpermissive92.54 2296.66 30296.11 30598.31 29399.68 12797.55 28997.94 30295.60 34499.37 10490.68 35098.70 32496.56 25098.61 34986.94 34799.55 24098.77 301
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CMPMVSbinary77.52 2398.50 23398.19 24599.41 18198.33 33999.56 10699.01 18299.59 15495.44 32199.57 14499.80 5195.64 27199.46 34196.47 27399.92 7299.21 244
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
SED-MVS99.40 7399.28 9299.77 3999.69 11999.82 2499.20 13199.54 18099.13 14099.82 4899.63 14798.91 8299.92 8497.85 18599.70 19899.58 129
IU-MVS99.69 11999.77 3999.22 27997.50 27899.69 10197.75 19299.70 19899.77 31
OPU-MVS99.29 21099.12 28799.44 12899.20 13199.40 23299.00 7198.84 34796.54 26899.60 23199.58 129
test_241102_TWO99.54 18099.13 14099.76 7399.63 14798.32 16199.92 8497.85 18599.69 20199.75 38
test_241102_ONE99.69 11999.82 2499.54 18099.12 14399.82 4899.49 21398.91 8299.52 336
xxxxxxxxxxxxxcwj99.11 15298.96 16799.54 14399.53 17599.25 17598.29 26599.76 6499.07 14899.42 18299.61 16598.86 8899.87 16096.45 27499.68 20499.49 173
SF-MVS99.10 15698.93 17099.62 11599.58 15099.51 11299.13 15899.65 12297.97 25399.42 18299.61 16598.86 8899.87 16096.45 27499.68 20499.49 173
ETH3D cwj APD-0.1698.50 23398.16 24899.51 14999.04 30099.39 14398.47 25199.47 21596.70 30698.78 27699.33 25297.62 21899.86 18094.69 32099.38 26999.28 233
cl-mvsnet297.56 28197.28 28298.40 28798.37 33896.75 30897.24 33599.37 24797.31 28899.41 19099.22 27587.30 33299.37 34397.70 19799.62 22399.08 273
miper_ehance_all_eth98.59 22298.59 20798.59 28098.98 30497.07 30197.49 32599.52 19898.50 21099.52 16499.37 23896.41 25899.71 28697.86 18399.62 22399.00 285
miper_enhance_ethall98.03 26697.94 26398.32 29198.27 34096.43 31396.95 33899.41 23096.37 30999.43 18098.96 30894.74 27899.69 29497.71 19599.62 22398.83 298
ZNCC-MVS99.22 12199.04 14699.77 3999.76 8399.73 5399.28 11199.56 17098.19 24399.14 23999.29 26098.84 9199.92 8497.53 21399.80 15299.64 87
ETH3 D test640097.76 27397.19 28799.50 15299.38 23199.26 17198.34 26099.49 20992.99 33798.54 29499.20 27995.92 26999.82 23491.14 33799.66 21599.40 205
cl-mvsnet_98.54 22998.41 22598.92 25399.03 30197.80 28297.46 32699.59 15498.90 16899.60 13699.46 22393.85 28699.78 26297.97 17499.89 9099.17 253
cl-mvsnet198.54 22998.42 22498.92 25399.03 30197.80 28297.46 32699.59 15498.90 16899.60 13699.46 22393.87 28599.78 26297.97 17499.89 9099.18 251
eth_miper_zixun_eth98.68 21598.71 19698.60 27999.10 29396.84 30797.52 32499.54 18098.94 16199.58 14199.48 21596.25 26299.76 27298.01 17099.93 6899.21 244
9.1498.64 20299.45 21498.81 21699.60 14797.52 27799.28 21599.56 19098.53 13699.83 22495.36 31099.64 220
testtj98.56 22598.17 24799.72 7199.45 21499.60 9798.88 20299.50 20496.88 29999.18 23499.48 21597.08 24199.92 8493.69 33099.38 26999.63 92
uanet_test8.33 32511.11 3270.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 353100.00 10.00 3580.00 3540.00 3510.00 3510.00 350
ETH3D-3000-0.198.77 20598.50 21799.59 12399.47 20699.53 11198.77 22499.60 14797.33 28799.23 22299.50 20897.91 19399.83 22495.02 31599.67 21199.41 203
save fliter99.53 17599.25 17598.29 26599.38 24699.07 148
ET-MVSNet_ETH3D96.78 29896.07 30698.91 25599.26 26697.92 27997.70 31496.05 34297.96 25692.37 34998.43 33587.06 33499.90 11998.27 14797.56 33998.91 291
UniMVSNet_ETH3D99.85 799.83 799.90 499.89 2199.91 299.89 499.71 9099.93 499.95 1099.89 2599.71 999.96 3399.51 2899.97 2999.84 14
EIA-MVS99.12 14899.01 15399.45 16799.36 23699.62 9099.34 9199.79 5298.41 21898.84 26898.89 31598.75 10799.84 21398.15 16199.51 25098.89 292
miper_lstm_enhance98.65 21798.60 20598.82 27099.20 27597.33 29597.78 31099.66 11199.01 15499.59 13999.50 20894.62 28099.85 19898.12 16299.90 8299.26 234
ETV-MVS99.18 13599.18 10699.16 23199.34 24899.28 16799.12 16299.79 5299.48 8398.93 25798.55 33099.40 2299.93 6698.51 13199.52 24998.28 322
CS-MVS99.09 15799.03 14899.25 21999.45 21499.49 11499.41 7799.82 3699.10 14598.03 31998.48 33499.30 3799.89 13298.30 14499.41 26598.35 319
D2MVS99.22 12199.19 10599.29 21099.69 11998.74 23298.81 21699.41 23098.55 20499.68 10399.69 11198.13 17799.87 16098.82 11199.98 2199.24 237
MSP-MVS99.32 9799.17 10799.77 3999.69 11999.80 3299.14 15199.31 26099.16 13699.62 12899.61 16598.35 15699.91 10097.88 17999.72 19299.61 111
test_0728_THIRD99.18 13199.62 12899.61 16598.58 12799.91 10097.72 19499.80 15299.77 31
test_0728_SECOND99.83 2199.70 11699.79 3499.14 15199.61 13799.92 8497.88 17999.72 19299.77 31
test072699.69 11999.80 3299.24 12199.57 16599.16 13699.73 9099.65 13798.35 156
SR-MVS99.19 13199.00 15699.74 5999.51 18499.72 5799.18 13699.60 14798.85 17499.47 17199.58 18098.38 15399.92 8496.92 24699.54 24599.57 135
DPM-MVS98.28 25397.94 26399.32 20499.36 23699.11 19897.31 33298.78 30296.88 29998.84 26899.11 29097.77 20499.61 32994.03 32799.36 27499.23 240
GST-MVS99.16 14098.96 16799.75 5499.73 10299.73 5399.20 13199.55 17598.22 24099.32 20899.35 24898.65 12099.91 10096.86 25099.74 18099.62 104
test_yl98.25 25597.95 25999.13 23299.17 28098.47 24499.00 18498.67 30898.97 15799.22 22699.02 29891.31 30899.69 29497.26 22898.93 30199.24 237
thisisatest053097.45 28396.95 29398.94 24999.68 12797.73 28499.09 16994.19 34998.61 19999.56 15199.30 25784.30 34699.93 6698.27 14799.54 24599.16 255
Anonymous2024052999.42 6699.34 7499.65 9599.53 17599.60 9799.63 4599.39 24099.47 8899.76 7399.78 6498.13 17799.86 18098.70 12199.68 20499.49 173
Anonymous20240521198.75 20898.46 21999.63 10699.34 24899.66 7799.47 7097.65 33199.28 11699.56 15199.50 20893.15 29299.84 21398.62 12699.58 23499.40 205
DCV-MVSNet98.25 25597.95 25999.13 23299.17 28098.47 24499.00 18498.67 30898.97 15799.22 22699.02 29891.31 30899.69 29497.26 22898.93 30199.24 237
tttt051797.62 27897.20 28698.90 26199.76 8397.40 29399.48 6894.36 34799.06 15299.70 9899.49 21384.55 34599.94 5398.73 11999.65 21899.36 216
our_test_398.85 19899.09 12998.13 29899.66 13394.90 33097.72 31299.58 16399.07 14899.64 11799.62 15698.19 17399.93 6698.41 13499.95 4799.55 140
thisisatest051596.98 29496.42 30098.66 27899.42 22397.47 29097.27 33394.30 34897.24 29099.15 23798.86 31785.01 34399.87 16097.10 23999.39 26898.63 304
ppachtmachnet_test98.89 19399.12 11898.20 29699.66 13395.24 32797.63 31699.68 10399.08 14699.78 6699.62 15698.65 12099.88 14798.02 16799.96 4099.48 177
SMA-MVS99.19 13199.00 15699.73 6699.46 21199.73 5399.13 15899.52 19897.40 28399.57 14499.64 13998.93 7999.83 22497.61 20799.79 15799.63 92
GSMVS99.14 261
DPE-MVS99.14 14498.92 17499.82 2399.57 16099.77 3998.74 22699.60 14798.55 20499.76 7399.69 11198.23 16999.92 8496.39 27699.75 17299.76 35
test_part299.62 14299.67 7599.55 156
test_part10.00 3370.00 3570.00 34899.53 1890.00 3580.00 3540.00 3510.00 3510.00 350
thres100view90096.39 30696.03 30797.47 31499.63 13995.93 31999.18 13697.57 33298.75 18998.70 28397.31 35087.04 33599.67 31087.62 34398.51 32396.81 342
tfpnnormal99.43 6399.38 6699.60 12199.87 2799.75 4799.59 5599.78 5699.71 4099.90 2299.69 11198.85 9099.90 11997.25 23199.78 16399.15 257
tfpn200view996.30 30995.89 30897.53 31299.58 15096.11 31699.00 18497.54 33598.43 21598.52 29596.98 35286.85 33799.67 31087.62 34398.51 32396.81 342
cl_fuxian98.72 21398.71 19698.72 27599.12 28797.22 29897.68 31599.56 17098.90 16899.54 15899.48 21596.37 25999.73 28097.88 17999.88 9899.21 244
CHOSEN 280x42098.41 24398.41 22598.40 28799.34 24895.89 32196.94 33999.44 22498.80 18199.25 21899.52 20293.51 29099.98 698.94 10399.98 2199.32 225
CANet99.11 15299.05 14199.28 21298.83 31798.56 24198.71 23099.41 23099.25 12199.23 22299.22 27597.66 21599.94 5399.19 6799.97 2999.33 222
Fast-Effi-MVS+-dtu99.20 12899.12 11899.43 17299.25 26799.69 7099.05 17599.82 3699.50 8198.97 25399.05 29498.98 7399.98 698.20 15399.24 28998.62 305
Effi-MVS+-dtu99.07 15998.92 17499.52 14698.89 31199.78 3799.15 14999.66 11199.34 10798.92 26099.24 27397.69 20899.98 698.11 16399.28 28398.81 299
CANet_DTU98.91 18898.85 18399.09 23698.79 32398.13 26498.18 27299.31 26099.48 8398.86 26699.51 20596.56 25099.95 4299.05 8899.95 4799.19 249
MVS_030498.88 19498.71 19699.39 18698.85 31598.91 22399.45 7199.30 26398.56 20297.26 33799.68 12296.18 26499.96 3399.17 7299.94 6099.29 231
MP-MVS-pluss99.14 14498.92 17499.80 2999.83 3699.83 2098.61 23299.63 13096.84 30299.44 17699.58 18098.81 9299.91 10097.70 19799.82 13999.67 63
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
DVP-MVS99.04 16698.79 19299.81 2699.78 7199.73 5399.35 9099.57 16598.54 20799.54 15898.99 30096.81 24799.93 6696.97 24499.53 24799.77 31
sam_mvs190.81 31899.14 261
sam_mvs90.52 322
IterMVS-SCA-FT99.00 17599.16 10898.51 28299.75 9395.90 32098.07 28699.84 2999.84 2199.89 2699.73 8596.01 26799.99 499.33 48100.00 199.63 92
TSAR-MVS + MP.99.34 9199.24 10099.63 10699.82 4299.37 14999.26 11599.35 25198.77 18599.57 14499.70 10599.27 4399.88 14797.71 19599.75 17299.65 81
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
xiu_mvs_v1_base_debu99.23 11399.34 7498.91 25599.59 14798.23 25898.47 25199.66 11199.61 6699.68 10398.94 31099.39 2399.97 1699.18 6999.55 24098.51 313
OPM-MVS99.26 10899.13 11599.63 10699.70 11699.61 9698.58 23699.48 21198.50 21099.52 16499.63 14799.14 5499.76 27297.89 17899.77 16799.51 162
ACMMP_NAP99.28 10399.11 12199.79 3499.75 9399.81 2798.95 19799.53 18998.27 23899.53 16299.73 8598.75 10799.87 16097.70 19799.83 13099.68 56
ambc99.20 22799.35 23898.53 24299.17 14199.46 21999.67 10799.80 5198.46 14699.70 28897.92 17699.70 19899.38 210
zzz-MVS99.30 10099.14 11299.80 2999.81 4999.81 2798.73 22899.53 18999.27 11799.42 18299.63 14798.21 17099.95 4297.83 18899.79 15799.65 81
MTGPAbinary99.53 189
mvs-test198.83 19998.70 19999.22 22498.89 31199.65 8298.88 20299.66 11199.34 10798.29 30398.94 31097.69 20899.96 3398.11 16398.54 32298.04 332
Effi-MVS+99.06 16098.97 16599.34 19899.31 25598.98 21198.31 26499.91 898.81 17998.79 27498.94 31099.14 5499.84 21398.79 11398.74 31499.20 247
xiu_mvs_v2_base99.02 16999.11 12198.77 27299.37 23498.09 26998.13 27899.51 20199.47 8899.42 18298.54 33199.38 2799.97 1698.83 10999.33 27898.24 324
xiu_mvs_v1_base99.23 11399.34 7498.91 25599.59 14798.23 25898.47 25199.66 11199.61 6699.68 10398.94 31099.39 2399.97 1699.18 6999.55 24098.51 313
new-patchmatchnet99.35 8699.57 3798.71 27799.82 4296.62 31098.55 24299.75 7099.50 8199.88 3299.87 3099.31 3599.88 14799.43 35100.00 199.62 104
pmmvs699.86 699.86 699.83 2199.94 1099.90 499.83 699.91 899.85 1999.94 1199.95 1199.73 899.90 11999.65 1699.97 2999.69 50
pmmvs599.19 13199.11 12199.42 17499.76 8398.88 22598.55 24299.73 7898.82 17899.72 9199.62 15696.56 25099.82 23499.32 5099.95 4799.56 137
test_post199.14 15151.63 35789.54 32999.82 23496.86 250
test_post52.41 35690.25 32499.86 180
Fast-Effi-MVS+99.02 16998.87 18199.46 16399.38 23199.50 11399.04 17799.79 5297.17 29298.62 28798.74 32399.34 3399.95 4298.32 14299.41 26598.92 290
patchmatchnet-post99.62 15690.58 32099.94 53
Anonymous2023121199.62 3299.57 3799.76 4599.61 14399.60 9799.81 999.73 7899.82 2599.90 2299.90 2197.97 19099.86 18099.42 3999.96 4099.80 23
pmmvs-eth3d99.48 5299.47 5199.51 14999.77 7999.41 14098.81 21699.66 11199.42 10199.75 7899.66 13299.20 4799.76 27298.98 9499.99 1299.36 216
GG-mvs-BLEND97.36 31797.59 34896.87 30699.70 2288.49 35594.64 34897.26 35180.66 35099.12 34491.50 33596.50 34396.08 346
xiu_mvs_v1_base_debi99.23 11399.34 7498.91 25599.59 14798.23 25898.47 25199.66 11199.61 6699.68 10398.94 31099.39 2399.97 1699.18 6999.55 24098.51 313
Anonymous2023120699.35 8699.31 8099.47 16099.74 9999.06 20899.28 11199.74 7599.23 12599.72 9199.53 20097.63 21799.88 14799.11 8499.84 12099.48 177
MTAPA99.35 8699.20 10499.80 2999.81 4999.81 2799.33 9399.53 18999.27 11799.42 18299.63 14798.21 17099.95 4297.83 18899.79 15799.65 81
MTMP99.09 16998.59 312
gm-plane-assit97.59 34889.02 35493.47 33598.30 33799.84 21396.38 277
test9_res95.10 31399.44 25999.50 168
MVP-Stereo99.16 14099.08 13199.43 17299.48 20199.07 20699.08 17299.55 17598.63 19699.31 21099.68 12298.19 17399.78 26298.18 15799.58 23499.45 188
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST999.35 23899.35 15698.11 28199.41 23094.83 33297.92 32298.99 30098.02 18599.85 198
train_agg98.35 25097.95 25999.57 13299.35 23899.35 15698.11 28199.41 23094.90 32897.92 32298.99 30098.02 18599.85 19895.38 30999.44 25999.50 168
gg-mvs-nofinetune95.87 31595.17 31897.97 30198.19 34296.95 30399.69 2889.23 35499.89 1196.24 34399.94 1281.19 34899.51 33793.99 32898.20 32897.44 338
SCA98.11 26298.36 23097.36 31799.20 27592.99 33898.17 27498.49 31698.24 23999.10 24499.57 18796.01 26799.94 5396.86 25099.62 22399.14 261
Patchmatch-test98.10 26397.98 25798.48 28499.27 26596.48 31199.40 7999.07 29098.81 17999.23 22299.57 18790.11 32599.87 16096.69 26099.64 22099.09 270
test_899.34 24899.31 16298.08 28599.40 23794.90 32897.87 32698.97 30698.02 18599.84 213
MS-PatchMatch99.00 17598.97 16599.09 23699.11 29298.19 26198.76 22599.33 25498.49 21299.44 17699.58 18098.21 17099.69 29498.20 15399.62 22399.39 208
Patchmatch-RL test98.60 22098.36 23099.33 20099.77 7999.07 20698.27 26799.87 1798.91 16799.74 8699.72 9190.57 32199.79 25898.55 12999.85 11699.11 265
cdsmvs_eth3d_5k24.88 32333.17 3240.00 3370.00 3560.00 3570.00 34899.62 1330.00 3520.00 35399.13 28499.82 40.00 3540.00 3510.00 3510.00 350
pcd_1.5k_mvsjas16.61 32422.14 3260.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 353100.00 199.28 400.00 3540.00 3510.00 3510.00 350
agg_prior198.33 25297.92 26599.57 13299.35 23899.36 15297.99 29599.39 24094.85 33197.76 33198.98 30398.03 18399.85 19895.49 30599.44 25999.51 162
agg_prior294.58 32199.46 25899.50 168
agg_prior99.35 23899.36 15299.39 24097.76 33199.85 198
tmp_tt95.75 31795.42 31696.76 32389.90 35394.42 33298.86 20697.87 32978.01 34799.30 21499.69 11197.70 20695.89 35099.29 5798.14 33299.95 1
canonicalmvs99.02 16999.00 15699.09 23699.10 29398.70 23499.61 5099.66 11199.63 6198.64 28697.65 34599.04 6999.54 33498.79 11398.92 30399.04 281
anonymousdsp99.80 1199.77 1299.90 499.96 499.88 699.73 1699.85 2399.70 4399.92 1899.93 1399.45 2199.97 1699.36 44100.00 199.85 13
alignmvs98.28 25397.96 25899.25 21999.12 28798.93 22099.03 17998.42 31899.64 5898.72 28197.85 34390.86 31799.62 32598.88 10799.13 29299.19 249
nrg03099.70 1999.66 2199.82 2399.76 8399.84 1699.61 5099.70 9499.93 499.78 6699.68 12299.10 5899.78 26299.45 3399.96 4099.83 18
v14419299.55 4399.54 4399.58 12799.78 7199.20 19099.11 16499.62 13399.18 13199.89 2699.72 9198.66 11899.87 16099.88 699.97 2999.66 73
FIs99.65 2999.58 3499.84 1999.84 3399.85 1199.66 3899.75 7099.86 1699.74 8699.79 5798.27 16499.85 19899.37 4399.93 6899.83 18
v192192099.56 4099.57 3799.55 13999.75 9399.11 19899.05 17599.61 13799.15 13899.88 3299.71 9899.08 6399.87 16099.90 299.97 2999.66 73
UA-Net99.78 1399.76 1499.86 1699.72 10699.71 5999.91 399.95 499.96 299.71 9699.91 1999.15 5299.97 1699.50 30100.00 199.90 4
v119299.57 3799.57 3799.57 13299.77 7999.22 18499.04 17799.60 14799.18 13199.87 3699.72 9199.08 6399.85 19899.89 599.98 2199.66 73
FC-MVSNet-test99.70 1999.65 2299.86 1699.88 2399.86 1099.72 1999.78 5699.90 799.82 4899.83 4098.45 14799.87 16099.51 2899.97 2999.86 11
v114499.54 4599.53 4799.59 12399.79 6599.28 16799.10 16599.61 13799.20 12999.84 4199.73 8598.67 11699.84 21399.86 899.98 2199.64 87
sosnet-low-res8.33 32511.11 3270.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 353100.00 10.00 3580.00 3540.00 3510.00 3510.00 350
HFP-MVS99.25 10999.08 13199.76 4599.73 10299.70 6699.31 10099.59 15498.36 22499.36 19999.37 23898.80 9699.91 10097.43 21899.75 17299.68 56
v14899.40 7399.41 6299.39 18699.76 8398.94 21699.09 16999.59 15499.17 13499.81 5599.61 16598.41 15099.69 29499.32 5099.94 6099.53 150
sosnet8.33 32511.11 3270.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 353100.00 10.00 3580.00 3540.00 3510.00 3510.00 350
uncertanet8.33 32511.11 3270.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 353100.00 10.00 3580.00 3540.00 3510.00 3510.00 350
AllTest99.21 12699.07 13599.63 10699.78 7199.64 8499.12 16299.83 3198.63 19699.63 12199.72 9198.68 11399.75 27696.38 27799.83 13099.51 162
TestCases99.63 10699.78 7199.64 8499.83 3198.63 19699.63 12199.72 9198.68 11399.75 27696.38 27799.83 13099.51 162
v7n99.82 1099.80 1099.88 1199.96 499.84 1699.82 899.82 3699.84 2199.94 1199.91 1999.13 5799.96 3399.83 999.99 1299.83 18
region2R99.23 11399.05 14199.77 3999.76 8399.70 6699.31 10099.59 15498.41 21899.32 20899.36 24398.73 11099.93 6697.29 22599.74 18099.67 63
testing_299.58 3699.56 4199.62 11599.81 4999.44 12899.14 15199.43 22799.69 4699.82 4899.79 5799.14 5499.79 25899.31 5399.95 4799.63 92
RRT_MVS98.75 20898.54 21499.41 18198.14 34698.61 24098.98 19399.66 11199.31 11299.84 4199.75 7891.98 30199.98 699.20 6599.95 4799.62 104
PS-MVSNAJss99.84 899.82 899.89 799.96 499.77 3999.68 3199.85 2399.95 399.98 399.92 1699.28 4099.98 699.75 13100.00 199.94 2
PS-MVSNAJ99.00 17599.08 13198.76 27399.37 23498.10 26898.00 29399.51 20199.47 8899.41 19098.50 33399.28 4099.97 1698.83 10999.34 27698.20 328
jajsoiax99.89 399.89 399.89 799.96 499.78 3799.70 2299.86 1999.89 1199.98 399.90 2199.94 199.98 699.75 13100.00 199.90 4
mvs_tets99.90 299.90 299.90 499.96 499.79 3499.72 1999.88 1599.92 699.98 399.93 1399.94 199.98 699.77 12100.00 199.92 3
#test#99.12 14898.90 17899.76 4599.73 10299.70 6699.10 16599.59 15497.60 27299.36 19999.37 23898.80 9699.91 10096.84 25399.75 17299.68 56
EI-MVSNet-UG-set99.48 5299.50 4999.42 17499.57 16098.65 23999.24 12199.46 21999.68 4899.80 5899.66 13298.99 7299.89 13299.19 6799.90 8299.72 41
EI-MVSNet-Vis-set99.47 5899.49 5099.42 17499.57 16098.66 23799.24 12199.46 21999.67 5099.79 6399.65 13798.97 7599.89 13299.15 7699.89 9099.71 44
Regformer-399.41 7099.41 6299.40 18399.52 18098.70 23499.17 14199.44 22499.62 6299.75 7899.60 17298.90 8599.85 19898.89 10699.84 12099.65 81
Regformer-499.45 6199.44 5799.50 15299.52 18098.94 21699.17 14199.53 18999.64 5899.76 7399.60 17298.96 7899.90 11998.91 10599.84 12099.67 63
Regformer-199.32 9799.27 9599.47 16099.41 22498.95 21598.99 18999.48 21199.48 8399.66 11199.52 20298.78 10199.87 16098.36 13799.74 18099.60 115
Regformer-299.34 9199.27 9599.53 14599.41 22499.10 20298.99 18999.53 18999.47 8899.66 11199.52 20298.80 9699.89 13298.31 14399.74 18099.60 115
HPM-MVS++copyleft98.96 18298.70 19999.74 5999.52 18099.71 5998.86 20699.19 28298.47 21498.59 29099.06 29398.08 18199.91 10096.94 24599.60 23199.60 115
test_prior499.19 19198.00 293
XVS99.27 10799.11 12199.75 5499.71 10999.71 5999.37 8799.61 13799.29 11398.76 27899.47 22098.47 14399.88 14797.62 20599.73 18799.67 63
v124099.56 4099.58 3499.51 14999.80 5599.00 20999.00 18499.65 12299.15 13899.90 2299.75 7899.09 6099.88 14799.90 299.96 4099.67 63
test_prior398.62 21898.34 23399.46 16399.35 23899.22 18497.95 30099.39 24097.87 26098.05 31699.05 29497.90 19499.69 29495.99 29099.49 25499.48 177
pm-mvs199.79 1299.79 1199.78 3799.91 1599.83 2099.76 1399.87 1799.73 3699.89 2699.87 3099.63 1499.87 16099.54 2499.92 7299.63 92
test_prior297.95 30097.87 26098.05 31699.05 29497.90 19495.99 29099.49 254
X-MVStestdata96.09 31294.87 31999.75 5499.71 10999.71 5999.37 8799.61 13799.29 11398.76 27861.30 35598.47 14399.88 14797.62 20599.73 18799.67 63
test_prior99.46 16399.35 23899.22 18499.39 24099.69 29499.48 177
旧先验297.94 30295.33 32398.94 25699.88 14796.75 257
新几何298.04 289
新几何199.52 14699.50 19099.22 18499.26 27195.66 32098.60 28999.28 26297.67 21199.89 13295.95 29499.32 27999.45 188
旧先验199.49 19599.29 16599.26 27199.39 23697.67 21199.36 27499.46 186
无先验98.01 29199.23 27895.83 31699.85 19895.79 29999.44 193
原ACMM297.92 304
原ACMM199.37 19399.47 20698.87 22799.27 26996.74 30598.26 30599.32 25397.93 19299.82 23495.96 29399.38 26999.43 199
test22299.51 18499.08 20597.83 30999.29 26595.21 32598.68 28499.31 25597.28 23199.38 26999.43 199
testdata299.89 13295.99 290
segment_acmp98.37 154
testdata99.42 17499.51 18498.93 22099.30 26396.20 31198.87 26599.40 23298.33 16099.89 13296.29 28099.28 28399.44 193
testdata197.72 31297.86 263
v899.68 2299.69 1899.65 9599.80 5599.40 14199.66 3899.76 6499.64 5899.93 1499.85 3598.66 11899.84 21399.88 699.99 1299.71 44
131498.00 26897.90 26898.27 29598.90 30897.45 29299.30 10399.06 29294.98 32797.21 33899.12 28898.43 14899.67 31095.58 30498.56 32197.71 336
112198.56 22598.24 23899.52 14699.49 19599.24 18099.30 10399.22 27995.77 31798.52 29599.29 26097.39 22699.85 19895.79 29999.34 27699.46 186
LFMVS98.46 23998.19 24599.26 21699.24 26998.52 24399.62 4696.94 33899.87 1499.31 21099.58 18091.04 31299.81 25098.68 12499.42 26499.45 188
VDD-MVS99.20 12899.11 12199.44 16999.43 21998.98 21199.50 6498.32 32299.80 2999.56 15199.69 11196.99 24499.85 19898.99 9299.73 18799.50 168
VDDNet98.97 17998.82 18899.42 17499.71 10998.81 22899.62 4698.68 30699.81 2699.38 19799.80 5194.25 28399.85 19898.79 11399.32 27999.59 124
v1099.69 2199.69 1899.66 9099.81 4999.39 14399.66 3899.75 7099.60 7299.92 1899.87 3098.75 10799.86 18099.90 299.99 1299.73 40
VPNet99.46 5999.37 6999.71 7599.82 4299.59 10099.48 6899.70 9499.81 2699.69 10199.58 18097.66 21599.86 18099.17 7299.44 25999.67 63
MVS95.72 31894.63 32198.99 24598.56 33397.98 27899.30 10398.86 29772.71 34997.30 33599.08 29298.34 15899.74 27889.21 33998.33 32699.26 234
v2v48299.50 4899.47 5199.58 12799.78 7199.25 17599.14 15199.58 16399.25 12199.81 5599.62 15698.24 16699.84 21399.83 999.97 2999.64 87
V4299.56 4099.54 4399.63 10699.79 6599.46 12199.39 8199.59 15499.24 12399.86 3799.70 10598.55 13099.82 23499.79 1199.95 4799.60 115
SD-MVS99.01 17399.30 8598.15 29799.50 19099.40 14198.94 19999.61 13799.22 12899.75 7899.82 4699.54 2095.51 35197.48 21599.87 10699.54 147
Zhenlong Yuan, Jiakai Cao, Zhaoxin Li, Hao Jiang and Zhaoqi Wang: SD-MVS: Segmentation-driven Deformation Multi-View Stereo with Spherical Refinement and EM optimization. AAAI2024
GA-MVS97.99 26997.68 27698.93 25299.52 18098.04 27297.19 33699.05 29398.32 23598.81 27198.97 30689.89 32899.41 34298.33 14199.05 29699.34 221
MSLP-MVS++99.05 16399.09 12998.91 25599.21 27298.36 25498.82 21599.47 21598.85 17498.90 26399.56 19098.78 10199.09 34598.57 12899.68 20499.26 234
APDe-MVS99.48 5299.36 7299.85 1899.55 17199.81 2799.50 6499.69 10098.99 15599.75 7899.71 9898.79 9999.93 6698.46 13399.85 11699.80 23
APD-MVS_3200maxsize99.31 9999.16 10899.74 5999.53 17599.75 4799.27 11499.61 13799.19 13099.57 14499.64 13998.76 10599.90 11997.29 22599.62 22399.56 137
ADS-MVSNet297.78 27297.66 27898.12 29999.14 28395.36 32599.22 12898.75 30496.97 29798.25 30699.64 13990.90 31599.94 5396.51 27099.56 23699.08 273
EI-MVSNet99.38 7999.44 5799.21 22599.58 15098.09 26999.26 11599.46 21999.62 6299.75 7899.67 12898.54 13299.85 19899.15 7699.92 7299.68 56
Regformer8.33 32511.11 3270.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 353100.00 10.00 3580.00 3540.00 3510.00 3510.00 350
CVMVSNet98.61 21998.88 18097.80 30699.58 15093.60 33599.26 11599.64 12899.66 5499.72 9199.67 12893.26 29199.93 6699.30 5499.81 14799.87 9
pmmvs499.13 14699.06 13799.36 19699.57 16099.10 20298.01 29199.25 27498.78 18499.58 14199.44 22798.24 16699.76 27298.74 11899.93 6899.22 242
EU-MVSNet99.39 7799.62 2598.72 27599.88 2396.44 31299.56 6099.85 2399.90 799.90 2299.85 3598.09 17999.83 22499.58 2199.95 4799.90 4
VNet99.18 13599.06 13799.56 13699.24 26999.36 15299.33 9399.31 26099.67 5099.47 17199.57 18796.48 25399.84 21399.15 7699.30 28199.47 182
test-LLR97.15 29096.95 29397.74 30998.18 34395.02 32897.38 32896.10 33998.00 24997.81 32898.58 32690.04 32699.91 10097.69 20398.78 30898.31 320
TESTMET0.1,196.24 31095.84 31197.41 31698.24 34193.84 33497.38 32895.84 34398.43 21597.81 32898.56 32979.77 35299.89 13297.77 19098.77 31098.52 312
test-mter96.23 31195.73 31397.74 30998.18 34395.02 32897.38 32896.10 33997.90 25897.81 32898.58 32679.12 35399.91 10097.69 20398.78 30898.31 320
VPA-MVSNet99.66 2499.62 2599.79 3499.68 12799.75 4799.62 4699.69 10099.85 1999.80 5899.81 4998.81 9299.91 10099.47 3299.88 9899.70 47
ACMMPR99.23 11399.06 13799.76 4599.74 9999.69 7099.31 10099.59 15498.36 22499.35 20199.38 23798.61 12499.93 6697.43 21899.75 17299.67 63
testgi99.29 10299.26 9799.37 19399.75 9398.81 22898.84 20999.89 1298.38 22299.75 7899.04 29799.36 3299.86 18099.08 8699.25 28799.45 188
test20.0399.55 4399.54 4399.58 12799.79 6599.37 14999.02 18099.89 1299.60 7299.82 4899.62 15698.81 9299.89 13299.43 3599.86 11399.47 182
thres600view796.60 30396.16 30497.93 30299.63 13996.09 31899.18 13697.57 33298.77 18598.72 28197.32 34987.04 33599.72 28288.57 34098.62 31997.98 333
ADS-MVSNet97.72 27697.67 27797.86 30499.14 28394.65 33199.22 12898.86 29796.97 29798.25 30699.64 13990.90 31599.84 21396.51 27099.56 23699.08 273
MP-MVScopyleft99.06 16098.83 18799.76 4599.76 8399.71 5999.32 9699.50 20498.35 22998.97 25399.48 21598.37 15499.92 8495.95 29499.75 17299.63 92
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs28.94 32233.33 32315.79 33626.03 3549.81 35696.77 34115.67 35611.55 35123.87 35250.74 35819.03 3578.53 35323.21 35033.07 34929.03 349
thres40096.40 30595.89 30897.92 30399.58 15096.11 31699.00 18497.54 33598.43 21598.52 29596.98 35286.85 33799.67 31087.62 34398.51 32397.98 333
test12329.31 32133.05 32518.08 33525.93 35512.24 35597.53 32210.93 35711.78 35024.21 35150.08 35921.04 3568.60 35223.51 34932.43 35033.39 348
thres20096.09 31295.68 31497.33 31999.48 20196.22 31598.53 24697.57 33298.06 24898.37 30296.73 35486.84 33999.61 32986.99 34698.57 32096.16 345
test0.0.03 197.37 28696.91 29698.74 27497.72 34797.57 28897.60 31897.36 33798.00 24999.21 22898.02 34190.04 32699.79 25898.37 13695.89 34598.86 295
pmmvs398.08 26497.80 27098.91 25599.41 22497.69 28697.87 30799.66 11195.87 31599.50 16899.51 20590.35 32399.97 1698.55 12999.47 25699.08 273
EMVS96.96 29597.28 28295.99 33398.76 32791.03 34995.26 34798.61 31099.34 10798.92 26098.88 31693.79 28799.66 31492.87 33199.05 29697.30 341
E-PMN97.14 29297.43 28096.27 33098.79 32391.62 34695.54 34699.01 29499.44 9498.88 26499.12 28892.78 29699.68 30594.30 32399.03 29897.50 337
PGM-MVS99.20 12899.01 15399.77 3999.75 9399.71 5999.16 14799.72 8797.99 25199.42 18299.60 17298.81 9299.93 6696.91 24799.74 18099.66 73
LCM-MVSNet-Re99.28 10399.15 11199.67 8399.33 25399.76 4599.34 9199.97 298.93 16499.91 2099.79 5798.68 11399.93 6696.80 25599.56 23699.30 228
LCM-MVSNet99.95 199.95 199.95 199.99 199.99 199.95 299.97 299.99 1100.00 199.98 899.78 6100.00 199.92 1100.00 199.87 9
MCST-MVS99.02 16998.81 18999.65 9599.58 15099.49 11498.58 23699.07 29098.40 22099.04 25099.25 26898.51 14199.80 25597.31 22499.51 25099.65 81
mvs_anonymous99.28 10399.39 6498.94 24999.19 27797.81 28199.02 18099.55 17599.78 3299.85 3899.80 5198.24 16699.86 18099.57 2299.50 25299.15 257
MVS_Test99.28 10399.31 8099.19 22899.35 23898.79 23099.36 8999.49 20999.17 13499.21 22899.67 12898.78 10199.66 31499.09 8599.66 21599.10 267
MDA-MVSNet-bldmvs99.06 16099.05 14199.07 24099.80 5597.83 28098.89 20199.72 8799.29 11399.63 12199.70 10596.47 25499.89 13298.17 15999.82 13999.50 168
CDPH-MVS98.56 22598.20 24299.61 11999.50 19099.46 12198.32 26399.41 23095.22 32499.21 22899.10 29198.34 15899.82 23495.09 31499.66 21599.56 137
test1299.54 14399.29 26199.33 15999.16 28598.43 30097.54 21999.82 23499.47 25699.48 177
casdiffmvs99.63 3099.61 2999.67 8399.79 6599.59 10099.13 15899.85 2399.79 3199.76 7399.72 9199.33 3499.82 23499.21 6299.94 6099.59 124
diffmvs99.34 9199.32 7999.39 18699.67 13298.77 23198.57 24099.81 4599.61 6699.48 17099.41 23098.47 14399.86 18098.97 9699.90 8299.53 150
baseline296.83 29796.28 30298.46 28599.09 29596.91 30598.83 21193.87 35097.23 29196.23 34498.36 33688.12 33199.90 11996.68 26198.14 33298.57 310
baseline197.73 27497.33 28198.96 24799.30 25997.73 28499.40 7998.42 31899.33 11099.46 17499.21 27791.18 31099.82 23498.35 13991.26 34799.32 225
YYNet198.95 18598.99 16198.84 26599.64 13797.14 30098.22 27199.32 25698.92 16699.59 13999.66 13297.40 22499.83 22498.27 14799.90 8299.55 140
PMMVS299.48 5299.45 5599.57 13299.76 8398.99 21098.09 28399.90 1198.95 16099.78 6699.58 18099.57 1999.93 6699.48 3199.95 4799.79 29
MDA-MVSNet_test_wron98.95 18598.99 16198.85 26399.64 13797.16 29998.23 27099.33 25498.93 16499.56 15199.66 13297.39 22699.83 22498.29 14599.88 9899.55 140
tpmvs97.39 28597.69 27596.52 32898.41 33691.76 34499.30 10398.94 29697.74 26697.85 32799.55 19692.40 30099.73 28096.25 28298.73 31698.06 331
PM-MVS99.36 8499.29 9099.58 12799.83 3699.66 7798.95 19799.86 1998.85 17499.81 5599.73 8598.40 15299.92 8498.36 13799.83 13099.17 253
HQP_MVS98.90 19098.68 20199.55 13999.58 15099.24 18098.80 21999.54 18098.94 16199.14 23999.25 26897.24 23299.82 23495.84 29799.78 16399.60 115
plane_prior799.58 15099.38 146
plane_prior699.47 20699.26 17197.24 232
plane_prior599.54 18099.82 23495.84 29799.78 16399.60 115
plane_prior499.25 268
plane_prior399.31 16298.36 22499.14 239
plane_prior298.80 21998.94 161
plane_prior199.51 184
plane_prior99.24 18098.42 25797.87 26099.71 196
PS-CasMVS99.66 2499.58 3499.89 799.80 5599.85 1199.66 3899.73 7899.62 6299.84 4199.71 9898.62 12299.96 3399.30 5499.96 4099.86 11
UniMVSNet_NR-MVSNet99.37 8199.25 9999.72 7199.47 20699.56 10698.97 19599.61 13799.43 9999.67 10799.28 26297.85 19999.95 4299.17 7299.81 14799.65 81
PEN-MVS99.66 2499.59 3299.89 799.83 3699.87 799.66 3899.73 7899.70 4399.84 4199.73 8598.56 12999.96 3399.29 5799.94 6099.83 18
TransMVSNet (Re)99.78 1399.77 1299.81 2699.91 1599.85 1199.75 1499.86 1999.70 4399.91 2099.89 2599.60 1899.87 16099.59 1999.74 18099.71 44
DTE-MVSNet99.68 2299.61 2999.88 1199.80 5599.87 799.67 3599.71 9099.72 3999.84 4199.78 6498.67 11699.97 1699.30 5499.95 4799.80 23
DU-MVS99.33 9599.21 10399.71 7599.43 21999.56 10698.83 21199.53 18999.38 10399.67 10799.36 24397.67 21199.95 4299.17 7299.81 14799.63 92
UniMVSNet (Re)99.37 8199.26 9799.68 8199.51 18499.58 10398.98 19399.60 14799.43 9999.70 9899.36 24397.70 20699.88 14799.20 6599.87 10699.59 124
CP-MVSNet99.54 4599.43 6099.87 1499.76 8399.82 2499.57 5899.61 13799.54 7699.80 5899.64 13997.79 20399.95 4299.21 6299.94 6099.84 14
WR-MVS_H99.61 3499.53 4799.87 1499.80 5599.83 2099.67 3599.75 7099.58 7599.85 3899.69 11198.18 17599.94 5399.28 5999.95 4799.83 18
WR-MVS99.11 15298.93 17099.66 9099.30 25999.42 13698.42 25799.37 24799.04 15399.57 14499.20 27996.89 24699.86 18098.66 12599.87 10699.70 47
NR-MVSNet99.40 7399.31 8099.68 8199.43 21999.55 10999.73 1699.50 20499.46 9299.88 3299.36 24397.54 21999.87 16098.97 9699.87 10699.63 92
Baseline_NR-MVSNet99.49 5099.37 6999.82 2399.91 1599.84 1698.83 21199.86 1999.68 4899.65 11599.88 2897.67 21199.87 16099.03 8999.86 11399.76 35
TranMVSNet+NR-MVSNet99.54 4599.47 5199.76 4599.58 15099.64 8499.30 10399.63 13099.61 6699.71 9699.56 19098.76 10599.96 3399.14 8299.92 7299.68 56
TSAR-MVS + GP.99.12 14899.04 14699.38 19099.34 24899.16 19398.15 27599.29 26598.18 24499.63 12199.62 15699.18 4999.68 30598.20 15399.74 18099.30 228
abl_699.36 8499.23 10299.75 5499.71 10999.74 5299.33 9399.76 6499.07 14899.65 11599.63 14799.09 6099.92 8497.13 23899.76 16999.58 129
n20.00 358
nn0.00 358
mPP-MVS99.19 13199.00 15699.76 4599.76 8399.68 7399.38 8399.54 18098.34 23399.01 25199.50 20898.53 13699.93 6697.18 23699.78 16399.66 73
door-mid99.83 31
XVG-OURS-SEG-HR99.16 14098.99 16199.66 9099.84 3399.64 8498.25 26999.73 7898.39 22199.63 12199.43 22899.70 1199.90 11997.34 22298.64 31899.44 193
DWT-MVSNet_test96.03 31495.80 31296.71 32798.50 33591.93 34399.25 12097.87 32995.99 31496.81 34097.61 34681.02 34999.66 31497.20 23597.98 33598.54 311
MVSFormer99.41 7099.44 5799.31 20799.57 16098.40 25099.77 1199.80 4699.73 3699.63 12199.30 25798.02 18599.98 699.43 3599.69 20199.55 140
jason99.16 14099.11 12199.32 20499.75 9398.44 24798.26 26899.39 24098.70 19199.74 8699.30 25798.54 13299.97 1698.48 13299.82 13999.55 140
jason: jason.
lupinMVS98.96 18298.87 18199.24 22299.57 16098.40 25098.12 27999.18 28398.28 23799.63 12199.13 28498.02 18599.97 1698.22 15199.69 20199.35 219
test_djsdf99.84 899.81 999.91 299.94 1099.84 1699.77 1199.80 4699.73 3699.97 699.92 1699.77 799.98 699.43 35100.00 199.90 4
HPM-MVS_fast99.43 6399.30 8599.80 2999.83 3699.81 2799.52 6299.70 9498.35 22999.51 16799.50 20899.31 3599.88 14798.18 15799.84 12099.69 50
RRT_test8_iter0597.35 28897.25 28497.63 31198.81 32193.13 33799.26 11599.89 1299.51 8099.83 4699.68 12279.03 35499.88 14799.53 2699.72 19299.89 8
K. test v398.87 19698.60 20599.69 8099.93 1399.46 12199.74 1594.97 34599.78 3299.88 3299.88 2893.66 28999.97 1699.61 1899.95 4799.64 87
lessismore_v099.64 10299.86 2999.38 14690.66 35299.89 2699.83 4094.56 28199.97 1699.56 2399.92 7299.57 135
SixPastTwentyTwo99.42 6699.30 8599.76 4599.92 1499.67 7599.70 2299.14 28799.65 5699.89 2699.90 2196.20 26399.94 5399.42 3999.92 7299.67 63
OurMVSNet-221017-099.75 1599.71 1699.84 1999.96 499.83 2099.83 699.85 2399.80 2999.93 1499.93 1398.54 13299.93 6699.59 1999.98 2199.76 35
HPM-MVScopyleft99.25 10999.07 13599.78 3799.81 4999.75 4799.61 5099.67 10797.72 26799.35 20199.25 26899.23 4599.92 8497.21 23499.82 13999.67 63
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS99.21 12699.06 13799.65 9599.82 4299.62 9097.87 30799.74 7598.36 22499.66 11199.68 12299.71 999.90 11996.84 25399.88 9899.43 199
XVG-ACMP-BASELINE99.23 11399.10 12899.63 10699.82 4299.58 10398.83 21199.72 8798.36 22499.60 13699.71 9898.92 8099.91 10097.08 24099.84 12099.40 205
LPG-MVS_test99.22 12199.05 14199.74 5999.82 4299.63 8899.16 14799.73 7897.56 27399.64 11799.69 11199.37 2999.89 13296.66 26399.87 10699.69 50
LGP-MVS_train99.74 5999.82 4299.63 8899.73 7897.56 27399.64 11799.69 11199.37 2999.89 13296.66 26399.87 10699.69 50
baseline99.63 3099.62 2599.66 9099.80 5599.62 9099.44 7499.80 4699.71 4099.72 9199.69 11199.15 5299.83 22499.32 5099.94 6099.53 150
test1199.29 265
door99.77 59
EPNet_dtu97.62 27897.79 27297.11 32296.67 35192.31 34198.51 24898.04 32499.24 12395.77 34599.47 22093.78 28899.66 31498.98 9499.62 22399.37 213
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268899.39 7799.30 8599.65 9599.88 2399.25 17598.78 22399.88 1598.66 19399.96 899.79 5797.45 22299.93 6699.34 4699.99 1299.78 30
EPNet98.13 26197.77 27399.18 23094.57 35297.99 27399.24 12197.96 32699.74 3597.29 33699.62 15693.13 29399.97 1698.59 12799.83 13099.58 129
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS98.94 216
HQP-NCC99.31 25597.98 29697.45 28098.15 310
ACMP_Plane99.31 25597.98 29697.45 28098.15 310
APD-MVScopyleft98.87 19698.59 20799.71 7599.50 19099.62 9099.01 18299.57 16596.80 30499.54 15899.63 14798.29 16299.91 10095.24 31199.71 19699.61 111
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS94.73 317
HQP4-MVS98.15 31099.70 28899.53 150
HQP3-MVS99.37 24799.67 211
HQP2-MVS96.67 248
CNVR-MVS98.99 17898.80 19199.56 13699.25 26799.43 13398.54 24599.27 26998.58 20198.80 27399.43 22898.53 13699.70 28897.22 23399.59 23399.54 147
NCCC98.82 20198.57 21199.58 12799.21 27299.31 16298.61 23299.25 27498.65 19498.43 30099.26 26697.86 19899.81 25096.55 26799.27 28699.61 111
114514_t98.49 23698.11 25099.64 10299.73 10299.58 10399.24 12199.76 6489.94 34399.42 18299.56 19097.76 20599.86 18097.74 19399.82 13999.47 182
CP-MVS99.23 11399.05 14199.75 5499.66 13399.66 7799.38 8399.62 13398.38 22299.06 24999.27 26498.79 9999.94 5397.51 21499.82 13999.66 73
DSMNet-mixed99.48 5299.65 2298.95 24899.71 10997.27 29699.50 6499.82 3699.59 7499.41 19099.85 3599.62 15100.00 199.53 2699.89 9099.59 124
tpm296.35 30796.22 30396.73 32598.88 31491.75 34599.21 13098.51 31493.27 33697.89 32499.21 27784.83 34499.70 28896.04 28798.18 33198.75 302
NP-MVS99.40 22799.13 19698.83 318
EG-PatchMatch MVS99.57 3799.56 4199.62 11599.77 7999.33 15999.26 11599.76 6499.32 11199.80 5899.78 6499.29 3899.87 16099.15 7699.91 8199.66 73
tpm cat196.78 29896.98 29296.16 33298.85 31590.59 35299.08 17299.32 25692.37 33897.73 33399.46 22391.15 31199.69 29496.07 28698.80 30798.21 326
SteuartSystems-ACMMP99.30 10099.14 11299.76 4599.87 2799.66 7799.18 13699.60 14798.55 20499.57 14499.67 12899.03 7099.94 5397.01 24299.80 15299.69 50
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CostFormer96.71 30196.79 29996.46 32998.90 30890.71 35199.41 7798.68 30694.69 33398.14 31499.34 25186.32 34299.80 25597.60 20898.07 33498.88 293
CR-MVSNet98.35 25098.20 24298.83 26799.05 29898.12 26599.30 10399.67 10797.39 28499.16 23599.79 5791.87 30499.91 10098.78 11698.77 31098.44 316
JIA-IIPM98.06 26597.92 26598.50 28398.59 33297.02 30298.80 21998.51 31499.88 1397.89 32499.87 3091.89 30399.90 11998.16 16097.68 33898.59 307
Patchmtry98.78 20498.54 21499.49 15598.89 31199.19 19199.32 9699.67 10799.65 5699.72 9199.79 5791.87 30499.95 4298.00 17199.97 2999.33 222
PatchT98.45 24098.32 23598.83 26798.94 30698.29 25699.24 12198.82 30099.84 2199.08 24599.76 7491.37 30799.94 5398.82 11199.00 30098.26 323
tpmrst97.73 27498.07 25296.73 32598.71 32992.00 34299.10 16598.86 29798.52 20898.92 26099.54 19891.90 30299.82 23498.02 16799.03 29898.37 318
BH-w/o97.20 28997.01 29197.76 30799.08 29695.69 32298.03 29098.52 31395.76 31897.96 32198.02 34195.62 27299.47 33992.82 33297.25 34198.12 330
tpm97.15 29096.95 29397.75 30898.91 30794.24 33399.32 9697.96 32697.71 26898.29 30399.32 25386.72 34099.92 8498.10 16596.24 34499.09 270
DELS-MVS99.34 9199.30 8599.48 15899.51 18499.36 15298.12 27999.53 18999.36 10699.41 19099.61 16599.22 4699.87 16099.21 6299.68 20499.20 247
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 25998.09 25198.58 28199.38 23197.24 29798.55 24298.98 29597.81 26599.20 23398.76 32297.01 24399.65 32194.83 31698.33 32698.86 295
RPMNet98.53 23198.44 22198.83 26799.05 29898.12 26599.30 10398.78 30299.86 1699.16 23599.74 8192.53 29999.91 10098.75 11798.77 31098.44 316
MVSTER98.47 23898.22 24099.24 22299.06 29798.35 25599.08 17299.46 21999.27 11799.75 7899.66 13288.61 33099.85 19899.14 8299.92 7299.52 160
CPTT-MVS98.74 21098.44 22199.64 10299.61 14399.38 14699.18 13699.55 17596.49 30799.27 21699.37 23897.11 24099.92 8495.74 30199.67 21199.62 104
GBi-Net99.42 6699.31 8099.73 6699.49 19599.77 3999.68 3199.70 9499.44 9499.62 12899.83 4097.21 23499.90 11998.96 9899.90 8299.53 150
PVSNet_Blended_VisFu99.40 7399.38 6699.44 16999.90 1998.66 23798.94 19999.91 897.97 25399.79 6399.73 8599.05 6899.97 1699.15 7699.99 1299.68 56
PVSNet_BlendedMVS99.03 16799.01 15399.09 23699.54 17297.99 27398.58 23699.82 3697.62 27199.34 20499.71 9898.52 13999.77 27097.98 17299.97 2999.52 160
UnsupCasMVSNet_eth98.83 19998.57 21199.59 12399.68 12799.45 12698.99 18999.67 10799.48 8399.55 15699.36 24394.92 27599.86 18098.95 10296.57 34299.45 188
UnsupCasMVSNet_bld98.55 22898.27 23799.40 18399.56 17099.37 14997.97 29999.68 10397.49 27999.08 24599.35 24895.41 27499.82 23497.70 19798.19 33099.01 284
PVSNet_Blended98.70 21498.59 20799.02 24499.54 17297.99 27397.58 31999.82 3695.70 31999.34 20498.98 30398.52 13999.77 27097.98 17299.83 13099.30 228
FMVSNet597.80 27197.25 28499.42 17498.83 31798.97 21399.38 8399.80 4698.87 17299.25 21899.69 11180.60 35199.91 10098.96 9899.90 8299.38 210
test199.42 6699.31 8099.73 6699.49 19599.77 3999.68 3199.70 9499.44 9499.62 12899.83 4097.21 23499.90 11998.96 9899.90 8299.53 150
new_pmnet98.88 19498.89 17998.84 26599.70 11697.62 28798.15 27599.50 20497.98 25299.62 12899.54 19898.15 17699.94 5397.55 21099.84 12098.95 287
FMVSNet398.80 20398.63 20499.32 20499.13 28598.72 23399.10 16599.48 21199.23 12599.62 12899.64 13992.57 29799.86 18098.96 9899.90 8299.39 208
dp96.86 29697.07 28996.24 33198.68 33190.30 35399.19 13598.38 32197.35 28698.23 30899.59 17887.23 33399.82 23496.27 28198.73 31698.59 307
FMVSNet299.35 8699.28 9299.55 13999.49 19599.35 15699.45 7199.57 16599.44 9499.70 9899.74 8197.21 23499.87 16099.03 8999.94 6099.44 193
FMVSNet199.66 2499.63 2499.73 6699.78 7199.77 3999.68 3199.70 9499.67 5099.82 4899.83 4098.98 7399.90 11999.24 6199.97 2999.53 150
N_pmnet98.73 21298.53 21699.35 19799.72 10698.67 23698.34 26094.65 34698.35 22999.79 6399.68 12298.03 18399.93 6698.28 14699.92 7299.44 193
cascas96.99 29396.82 29897.48 31397.57 35095.64 32396.43 34499.56 17091.75 33997.13 33997.61 34695.58 27398.63 34896.68 26199.11 29398.18 329
BH-RMVSNet98.41 24398.14 24999.21 22599.21 27298.47 24498.60 23498.26 32398.35 22998.93 25799.31 25597.20 23799.66 31494.32 32299.10 29499.51 162
UGNet99.38 7999.34 7499.49 15598.90 30898.90 22499.70 2299.35 25199.86 1698.57 29299.81 4998.50 14299.93 6699.38 4199.98 2199.66 73
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 22298.37 22999.26 21699.43 21998.40 25098.74 22699.13 28998.10 24699.21 22899.24 27394.82 27799.90 11997.86 18398.77 31099.49 173
XXY-MVS99.71 1899.67 2099.81 2699.89 2199.72 5799.59 5599.82 3699.39 10299.82 4899.84 3999.38 2799.91 10099.38 4199.93 6899.80 23
sss98.90 19098.77 19399.27 21499.48 20198.44 24798.72 22999.32 25697.94 25799.37 19899.35 24896.31 26099.91 10098.85 10899.63 22299.47 182
Test_1112_low_res98.95 18598.73 19499.63 10699.68 12799.15 19598.09 28399.80 4697.14 29499.46 17499.40 23296.11 26599.89 13299.01 9199.84 12099.84 14
1112_ss99.05 16398.84 18599.67 8399.66 13399.29 16598.52 24799.82 3697.65 27099.43 18099.16 28296.42 25699.91 10099.07 8799.84 12099.80 23
ab-mvs-re8.26 33111.02 3330.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 35399.16 2820.00 3580.00 3540.00 3510.00 3510.00 350
ab-mvs99.33 9599.28 9299.47 16099.57 16099.39 14399.78 1099.43 22798.87 17299.57 14499.82 4698.06 18299.87 16098.69 12399.73 18799.15 257
TR-MVS97.44 28497.15 28898.32 29198.53 33497.46 29198.47 25197.91 32896.85 30198.21 30998.51 33296.42 25699.51 33792.16 33397.29 34097.98 333
MDTV_nov1_ep13_2view91.44 34899.14 15197.37 28599.21 22891.78 30696.75 25799.03 282
MDTV_nov1_ep1397.73 27498.70 33090.83 35099.15 14998.02 32598.51 20998.82 27099.61 16590.98 31399.66 31496.89 24998.92 303
MIMVSNet199.66 2499.62 2599.80 2999.94 1099.87 799.69 2899.77 5999.78 3299.93 1499.89 2597.94 19199.92 8499.65 1699.98 2199.62 104
MIMVSNet98.43 24198.20 24299.11 23499.53 17598.38 25399.58 5798.61 31098.96 15999.33 20699.76 7490.92 31499.81 25097.38 22199.76 16999.15 257
IterMVS-LS99.41 7099.47 5199.25 21999.81 4998.09 26998.85 20899.76 6499.62 6299.83 4699.64 13998.54 13299.97 1699.15 7699.99 1299.68 56
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet99.22 12199.13 11599.50 15299.35 23899.11 19898.96 19699.54 18099.46 9299.61 13499.70 10596.31 26099.83 22499.34 4699.88 9899.55 140
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref99.94 60
IterMVS98.97 17999.16 10898.42 28699.74 9995.64 32398.06 28899.83 3199.83 2499.85 3899.74 8196.10 26699.99 499.27 60100.00 199.63 92
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon98.50 23398.23 23999.31 20799.49 19599.46 12198.56 24199.63 13094.86 33098.85 26799.37 23897.81 20199.59 33196.08 28599.44 25998.88 293
MVS_111021_LR99.13 14699.03 14899.42 17499.58 15099.32 16197.91 30699.73 7898.68 19299.31 21099.48 21599.09 6099.66 31497.70 19799.77 16799.29 231
DP-MVS99.48 5299.39 6499.74 5999.57 16099.62 9099.29 11099.61 13799.87 1499.74 8699.76 7498.69 11299.87 16098.20 15399.80 15299.75 38
ACMMP++99.79 157
HQP-MVS98.36 24798.02 25499.39 18699.31 25598.94 21697.98 29699.37 24797.45 28098.15 31098.83 31896.67 24899.70 28894.73 31799.67 21199.53 150
QAPM98.40 24597.99 25599.65 9599.39 22899.47 11799.67 3599.52 19891.70 34098.78 27699.80 5198.55 13099.95 4294.71 31999.75 17299.53 150
Vis-MVSNetpermissive99.75 1599.74 1599.79 3499.88 2399.66 7799.69 2899.92 599.67 5099.77 7199.75 7899.61 1699.98 699.35 4599.98 2199.72 41
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet97.86 27098.22 24096.76 32399.28 26391.53 34798.38 25992.60 35199.13 14099.31 21099.96 1097.18 23899.68 30598.34 14099.83 13099.07 278
IS-MVSNet99.03 16798.85 18399.55 13999.80 5599.25 17599.73 1699.15 28699.37 10499.61 13499.71 9894.73 27999.81 25097.70 19799.88 9899.58 129
HyFIR lowres test98.91 18898.64 20299.73 6699.85 3299.47 11798.07 28699.83 3198.64 19599.89 2699.60 17292.57 297100.00 199.33 4899.97 2999.72 41
EPMVS96.53 30496.32 30197.17 32198.18 34392.97 33999.39 8189.95 35398.21 24198.61 28899.59 17886.69 34199.72 28296.99 24399.23 29198.81 299
PAPM_NR98.36 24798.04 25399.33 20099.48 20198.93 22098.79 22299.28 26897.54 27598.56 29398.57 32897.12 23999.69 29494.09 32698.90 30599.38 210
TAMVS99.49 5099.45 5599.63 10699.48 20199.42 13699.45 7199.57 16599.66 5499.78 6699.83 4097.85 19999.86 18099.44 3499.96 4099.61 111
PAPR97.56 28197.07 28999.04 24398.80 32298.11 26797.63 31699.25 27494.56 33498.02 32098.25 33997.43 22399.68 30590.90 33898.74 31499.33 222
RPSCF99.18 13599.02 15099.64 10299.83 3699.85 1199.44 7499.82 3698.33 23499.50 16899.78 6497.90 19499.65 32196.78 25699.83 13099.44 193
Vis-MVSNet (Re-imp)98.77 20598.58 21099.34 19899.78 7198.88 22599.61 5099.56 17099.11 14499.24 22199.56 19093.00 29599.78 26297.43 21899.89 9099.35 219
test_040299.22 12199.14 11299.45 16799.79 6599.43 13399.28 11199.68 10399.54 7699.40 19599.56 19099.07 6599.82 23496.01 28899.96 4099.11 265
MVS_111021_HR99.12 14899.02 15099.40 18399.50 19099.11 19897.92 30499.71 9098.76 18899.08 24599.47 22099.17 5099.54 33497.85 18599.76 16999.54 147
CSCG99.37 8199.29 9099.60 12199.71 10999.46 12199.43 7699.85 2398.79 18299.41 19099.60 17298.92 8099.92 8498.02 16799.92 7299.43 199
PatchMatch-RL98.68 21598.47 21899.30 20999.44 21799.28 16798.14 27799.54 18097.12 29599.11 24399.25 26897.80 20299.70 28896.51 27099.30 28198.93 289
API-MVS98.38 24698.39 22798.35 28998.83 31799.26 17199.14 15199.18 28398.59 20098.66 28598.78 32198.61 12499.57 33394.14 32599.56 23696.21 344
Test By Simon98.41 150
TDRefinement99.72 1799.70 1799.77 3999.90 1999.85 1199.86 599.92 599.69 4699.78 6699.92 1699.37 2999.88 14798.93 10499.95 4799.60 115
USDC98.96 18298.93 17099.05 24299.54 17297.99 27397.07 33799.80 4698.21 24199.75 7899.77 7198.43 14899.64 32397.90 17799.88 9899.51 162
EPP-MVSNet99.17 13999.00 15699.66 9099.80 5599.43 13399.70 2299.24 27799.48 8399.56 15199.77 7194.89 27699.93 6698.72 12099.89 9099.63 92
PMMVS98.49 23698.29 23699.11 23498.96 30598.42 24997.54 32099.32 25697.53 27698.47 29998.15 34097.88 19799.82 23497.46 21699.24 28999.09 270
PAPM95.61 31994.71 32098.31 29399.12 28796.63 30996.66 34398.46 31790.77 34296.25 34298.68 32593.01 29499.69 29481.60 34897.86 33798.62 305
ACMMPcopyleft99.25 10999.08 13199.74 5999.79 6599.68 7399.50 6499.65 12298.07 24799.52 16499.69 11198.57 12899.92 8497.18 23699.79 15799.63 92
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 23399.28 21299.18 27999.10 20298.34 26099.41 23098.48 21398.52 29598.98 30397.05 24299.78 26295.59 30399.50 25298.96 286
PatchmatchNetpermissive97.65 27797.80 27097.18 32098.82 32092.49 34099.17 14198.39 32098.12 24598.79 27499.58 18090.71 31999.89 13297.23 23299.41 26599.16 255
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS99.11 15298.95 16999.59 12399.13 28599.59 10099.17 14199.65 12297.88 25999.25 21899.46 22398.97 7599.80 25597.26 22899.82 13999.37 213
F-COLMAP98.74 21098.45 22099.62 11599.57 16099.47 11798.84 20999.65 12296.31 31098.93 25799.19 28197.68 21099.87 16096.52 26999.37 27399.53 150
ANet_high99.88 499.87 499.91 299.99 199.91 299.65 43100.00 199.90 7100.00 199.97 999.61 1699.97 1699.75 13100.00 199.84 14
wuyk23d97.58 28099.13 11592.93 33499.69 11999.49 11499.52 6299.77 5997.97 25399.96 899.79 5799.84 399.94 5395.85 29699.82 13979.36 347
OMC-MVS98.90 19098.72 19599.44 16999.39 22899.42 13698.58 23699.64 12897.31 28899.44 17699.62 15698.59 12699.69 29496.17 28499.79 15799.22 242
MG-MVS98.52 23298.39 22798.94 24999.15 28297.39 29498.18 27299.21 28198.89 17199.23 22299.63 14797.37 22899.74 27894.22 32499.61 23099.69 50
AdaColmapbinary98.60 22098.35 23299.38 19099.12 28799.22 18498.67 23199.42 22997.84 26498.81 27199.27 26497.32 23099.81 25095.14 31299.53 24799.10 267
uanet8.33 32511.11 3270.00 3370.00 3560.00 3570.00 3480.00 3580.00 3520.00 353100.00 10.00 3580.00 3540.00 3510.00 3510.00 350
ITE_SJBPF99.38 19099.63 13999.44 12899.73 7898.56 20299.33 20699.53 20098.88 8799.68 30596.01 28899.65 21899.02 283
DeepMVS_CXcopyleft97.98 30099.69 11996.95 30399.26 27175.51 34895.74 34698.28 33896.47 25499.62 32591.23 33697.89 33697.38 339
TinyColmap98.97 17998.93 17099.07 24099.46 21198.19 26197.75 31199.75 7098.79 18299.54 15899.70 10598.97 7599.62 32596.63 26599.83 13099.41 203
MAR-MVS98.24 25797.92 26599.19 22898.78 32599.65 8299.17 14199.14 28795.36 32298.04 31898.81 32097.47 22199.72 28295.47 30799.06 29598.21 326
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 17398.92 17499.27 21499.71 10999.28 16798.59 23599.77 5998.32 23599.39 19699.41 23098.62 12299.84 21396.62 26699.84 12098.69 303
MSDG99.08 15898.98 16499.37 19399.60 14599.13 19697.54 32099.74 7598.84 17799.53 16299.55 19699.10 5899.79 25897.07 24199.86 11399.18 251
LS3D99.24 11299.11 12199.61 11998.38 33799.79 3499.57 5899.68 10399.61 6699.15 23799.71 9898.70 11199.91 10097.54 21199.68 20499.13 264
CLD-MVS98.76 20798.57 21199.33 20099.57 16098.97 21397.53 32299.55 17596.41 30899.27 21699.13 28499.07 6599.78 26296.73 25999.89 9099.23 240
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS96.32 30895.50 31598.79 27199.60 14598.17 26398.46 25698.80 30197.16 29396.28 34199.63 14782.19 34799.09 34588.45 34198.89 30699.10 267
Gipumacopyleft99.57 3799.59 3299.49 15599.98 399.71 5999.72 1999.84 2999.81 2699.94 1199.78 6498.91 8299.71 28698.41 13499.95 4799.05 280
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015