This table lists the benchmark results for the high-res multi-view scenario. The following metrics are evaluated:

(*) For exact definitions, detailing how potentially incomplete ground truth is taken into account, see our paper.

The datasets are grouped into different categories, and result averages are computed for a category and method if results of the method are available for all datasets within the category. Note that the category "all" includes both the high-res multi-view and the low-res many-view scenarios.

Methods with suffix _ROB may participate in the Robust Vision Challenge.

Click a dataset result cell to show a visualization of the reconstruction. For training datasets, ground truth and accuracy / completeness visualizations are also available. The visualizations may not work with mobile browsers.




Method Infoallhigh-res
multi-view
indooroutdoorbotani.boulde.bridgedoorexhibi.lectur.living.loungeobserv.old co.statueterrac.
sorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
DeepC-MVS_fast98.69 199.49 1399.39 1599.77 3799.63 10999.59 4999.36 19599.46 13999.07 999.79 1999.82 4498.85 3399.92 6598.68 8599.87 3999.82 32
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepC-MVS98.35 299.30 4699.19 4899.64 6499.82 2999.23 9199.62 8299.55 5598.94 2699.63 5499.95 295.82 13999.94 4299.37 1799.97 399.73 66
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
DeepPCF-MVS98.18 398.81 11199.37 1797.12 30199.60 11991.75 32998.61 32099.44 15899.35 199.83 1299.85 2698.70 5199.81 13999.02 4899.91 1799.81 36
PLCcopyleft97.94 499.02 8798.85 9199.53 8199.66 10399.01 11999.24 23199.52 7696.85 21399.27 13699.48 19698.25 7599.91 7497.76 16499.62 10499.65 91
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
ACMM97.58 598.37 13998.34 13398.48 22999.41 15397.10 24599.56 11299.45 15098.53 5499.04 18999.85 2693.00 23599.71 17998.74 7697.45 22898.64 258
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
COLMAP_ROBcopyleft97.56 698.86 10298.75 10299.17 13399.88 1198.53 18999.34 20299.59 3897.55 15098.70 23699.89 1095.83 13899.90 8798.10 13499.90 2599.08 169
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
HY-MVS97.30 798.85 10898.64 11399.47 9399.42 15099.08 10599.62 8299.36 19497.39 16699.28 13299.68 12096.44 12199.92 6598.37 11898.22 18099.40 146
ACMH97.28 898.10 16697.99 15798.44 23699.41 15396.96 26099.60 9099.56 4898.09 8998.15 27199.91 590.87 29199.70 18598.88 5797.45 22898.67 242
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
3Dnovator97.25 999.24 5599.05 6099.81 2999.12 21599.66 3799.84 999.74 1099.09 898.92 20799.90 795.94 13499.98 598.95 5399.92 1299.79 46
ACMH+97.24 1097.92 19797.78 18298.32 24499.46 14496.68 27099.56 11299.54 6298.41 6397.79 28699.87 1990.18 29899.66 19298.05 14397.18 24198.62 266
ACMP97.20 1198.06 16997.94 16198.45 23399.37 16397.01 25499.44 15999.49 10597.54 15398.45 25799.79 7391.95 26999.72 17397.91 15097.49 22698.62 266
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
LTVRE_ROB97.16 1298.02 18097.90 16398.40 23999.23 19296.80 26699.70 4299.60 3597.12 18898.18 27099.70 10991.73 27999.72 17398.39 11597.45 22898.68 231
Andreas Kuhn, Heiko Hirschmüller, Daniel Scharstein, Helmut Mayer: A TV Prior for High-Quality Scalable Multi-View Stereo Reconstruction. International Journal of Computer Vision 2016
3Dnovator+97.12 1399.18 5998.97 7399.82 2699.17 20799.68 3399.81 1599.51 8599.20 498.72 22999.89 1095.68 14399.97 1198.86 6499.86 4999.81 36
PCF-MVS97.08 1497.66 23997.06 25799.47 9399.61 11799.09 10498.04 33899.25 24291.24 32798.51 25399.70 10994.55 19799.91 7492.76 31799.85 5399.42 144
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
TAPA-MVS97.07 1597.74 22697.34 24298.94 15999.70 8797.53 23499.25 22999.51 8591.90 32499.30 12499.63 14298.78 3999.64 19688.09 33199.87 3999.65 91
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
OpenMVScopyleft96.50 1698.47 13198.12 14599.52 8599.04 23099.53 5899.82 1399.72 1194.56 29598.08 27499.88 1494.73 18999.98 597.47 19499.76 7999.06 174
PVSNet96.02 1798.85 10898.84 9298.89 17799.73 7297.28 23798.32 33199.60 3597.86 11799.50 8499.57 16296.75 11499.86 10798.56 10199.70 9299.54 115
IB-MVS95.67 1896.22 28495.44 29298.57 22099.21 19596.70 26898.65 31997.74 33396.71 21997.27 29198.54 30686.03 32899.92 6598.47 11186.30 33999.10 164
Christian Sormann, Mattia Rossi, Andreas Kuhn and Friedrich Fraundorfer: IB-MVS: An Iterative Algorithm for Deep Multi-View Stereo based on Binary Decisions. BMVC 2021
PVSNet_094.43 1996.09 28895.47 29097.94 27599.31 17894.34 31397.81 33999.70 1597.12 18897.46 28898.75 29689.71 30199.79 14697.69 17481.69 34399.68 84
OpenMVS_ROBcopyleft92.34 2094.38 30493.70 30596.41 31297.38 32293.17 32399.06 26798.75 29686.58 33794.84 31398.26 31281.53 34199.32 24389.01 32897.87 20796.76 334
MVEpermissive76.82 2176.91 32674.31 32884.70 33385.38 35376.05 35296.88 34593.17 35467.39 34971.28 35089.01 35021.66 36387.69 35271.74 35072.29 34690.35 348
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVScopyleft70.75 2275.98 32774.97 32679.01 34070.98 35655.18 35793.37 34998.21 32465.08 35261.78 35393.83 34221.74 36292.53 34778.59 34591.12 32189.34 349
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
CMPMVSbinary69.68 2394.13 30594.90 29791.84 32597.24 32680.01 34698.52 32499.48 11489.01 33491.99 33299.67 12485.67 33099.13 27795.44 27397.03 24396.39 336
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
SMA-MVS99.47 2099.34 2499.86 1399.73 7299.85 699.56 11299.50 9997.61 14499.84 899.82 4499.28 399.91 7498.79 7299.91 1799.81 36
tfpn11197.81 21197.49 21698.78 20499.72 7697.86 22199.59 9298.74 29997.93 11299.26 14098.62 29991.75 27599.86 10793.57 30698.18 18498.61 275
conf0.0198.21 15397.89 16799.15 13699.76 4499.04 10999.67 5697.71 33497.10 19299.55 7299.54 17092.70 24799.79 14696.90 23298.12 19498.61 275
GSMVS99.52 120
test_part399.37 18997.97 10899.78 7899.95 3397.15 213
conf0.00298.21 15397.89 16799.15 13699.76 4499.04 10999.67 5697.71 33497.10 19299.55 7299.54 17092.70 24799.79 14696.90 23298.12 19498.61 275
thresconf0.0298.24 14697.89 16799.27 12199.76 4499.04 10999.67 5697.71 33497.10 19299.55 7299.54 17092.70 24799.79 14696.90 23298.12 19498.97 183
tfpn_n40098.24 14697.89 16799.27 12199.76 4499.04 10999.67 5697.71 33497.10 19299.55 7299.54 17092.70 24799.79 14696.90 23298.12 19498.97 183
tfpnconf98.24 14697.89 16799.27 12199.76 4499.04 10999.67 5697.71 33497.10 19299.55 7299.54 17092.70 24799.79 14696.90 23298.12 19498.97 183
tfpnview1198.24 14697.89 16799.27 12199.76 4499.04 10999.67 5697.71 33497.10 19299.55 7299.54 17092.70 24799.79 14696.90 23298.12 19498.97 183
tfpn100098.33 14098.02 15499.25 12599.78 3698.73 17099.70 4297.55 34297.48 15699.69 3799.53 17792.37 26599.85 11397.82 15798.26 17999.16 160
test_part299.81 3299.83 899.77 24
tfpn_ndepth98.17 15797.84 17599.15 13699.75 5698.76 16999.61 8897.39 34496.92 21099.61 5999.38 22392.19 26799.86 10797.57 18298.13 19298.82 200
test_part199.48 11498.96 2199.84 5899.83 23
conf200view1197.78 21897.45 22298.77 20599.72 7697.86 22199.59 9298.74 29997.93 11299.26 14098.62 29991.75 27599.83 12693.22 31098.18 18498.61 275
thres100view90097.76 22097.45 22298.69 21199.72 7697.86 22199.59 9298.74 29997.93 11299.26 14098.62 29991.75 27599.83 12693.22 31098.18 18498.37 299
tfpnnormal97.84 20597.47 21998.98 15399.20 19799.22 9299.64 7799.61 3296.32 24998.27 26899.70 10993.35 23199.44 22095.69 26895.40 26998.27 302
tfpn200view997.72 22997.38 23598.72 20999.69 8997.96 21699.50 13498.73 30897.83 12299.17 16798.45 30891.67 28199.83 12693.22 31098.18 18498.37 299
view60097.97 18897.66 19798.89 17799.75 5697.81 22599.69 4598.80 29198.02 10299.25 14498.88 28491.95 26999.89 9594.36 29398.29 17598.96 189
view80097.97 18897.66 19798.89 17799.75 5697.81 22599.69 4598.80 29198.02 10299.25 14498.88 28491.95 26999.89 9594.36 29398.29 17598.96 189
conf0.05thres100097.97 18897.66 19798.89 17799.75 5697.81 22599.69 4598.80 29198.02 10299.25 14498.88 28491.95 26999.89 9594.36 29398.29 17598.96 189
tfpn97.97 18897.66 19798.89 17799.75 5697.81 22599.69 4598.80 29198.02 10299.25 14498.88 28491.95 26999.89 9594.36 29398.29 17598.96 189
ESAPD99.31 4599.13 5399.87 699.81 3299.83 899.37 18999.48 11497.97 10899.77 2499.78 7898.96 2199.95 3397.15 21399.84 5899.83 23
CHOSEN 280x42099.12 6999.13 5399.08 14299.66 10397.89 21998.43 32799.71 1398.88 3099.62 5799.76 8896.63 11799.70 18599.46 1499.99 199.66 88
CANet99.25 5499.14 5299.59 7099.41 15399.16 9699.35 19999.57 4498.82 3599.51 8399.61 15096.46 12099.95 3399.59 299.98 299.65 91
Fast-Effi-MVS+-dtu98.77 11798.83 9598.60 21799.41 15396.99 25699.52 12599.49 10598.11 8699.24 14999.34 24196.96 10799.79 14697.95 14899.45 10799.02 178
Effi-MVS+-dtu98.78 11598.89 8498.47 23199.33 17096.91 26299.57 10599.30 22398.47 5799.41 10198.99 27796.78 11199.74 16198.73 7899.38 11198.74 213
CANet_DTU98.97 9498.87 8699.25 12599.33 17098.42 20199.08 26299.30 22399.16 599.43 9699.75 9395.27 15299.97 1198.56 10199.95 699.36 149
MVS_030499.06 8198.86 8999.66 5599.51 13299.36 7799.22 23699.51 8598.95 2499.58 6599.65 13193.74 22899.98 599.66 199.95 699.64 97
MP-MVS-pluss99.37 3899.20 4799.88 499.90 399.87 299.30 20999.52 7697.18 18299.60 6199.79 7398.79 3899.95 3398.83 6899.91 1799.83 23
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
HSP-MVS99.41 3399.26 4499.85 1999.89 899.80 1599.67 5699.37 19398.70 4599.77 2499.49 19098.21 7699.95 3398.46 11299.77 7799.81 36
sam_mvs194.86 17799.52 120
sam_mvs94.72 190
semantic-postprocess98.06 26799.57 12496.36 27999.49 10597.18 18298.71 23099.72 10592.70 24799.14 27497.44 19795.86 26298.67 242
TSAR-MVS + MP.99.58 399.50 799.81 2999.91 199.66 3799.63 7999.39 18098.91 2999.78 2399.85 2699.36 299.94 4298.84 6699.88 3599.82 32
xiu_mvs_v1_base_debu99.29 4899.27 4199.34 10799.63 10998.97 12699.12 25299.51 8598.86 3199.84 899.47 20098.18 7799.99 199.50 899.31 11699.08 169
OPM-MVS98.19 15698.10 14698.45 23398.88 26597.07 24999.28 21699.38 18698.57 5299.22 15699.81 5492.12 26899.66 19298.08 13997.54 22098.61 275
ACMMP_Plus99.47 2099.34 2499.88 499.87 1599.86 399.47 15199.48 11498.05 9899.76 2999.86 2298.82 3599.93 5798.82 7199.91 1799.84 12
ambc93.06 32092.68 34182.36 34398.47 32698.73 30895.09 31197.41 33155.55 35199.10 28296.42 25591.32 32097.71 329
zzz-MVS99.49 1399.36 1999.89 299.90 399.86 399.36 19599.47 13098.79 4099.68 3899.81 5498.43 6499.97 1198.88 5799.90 2599.83 23
MTGPAbinary99.47 130
mvs-test198.86 10298.84 9298.89 17799.33 17097.77 23099.44 15999.30 22398.47 5799.10 17799.43 20996.78 11199.95 3398.73 7899.02 13598.96 189
Effi-MVS+98.81 11198.59 12299.48 9099.46 14499.12 10298.08 33799.50 9997.50 15599.38 10899.41 21496.37 12399.81 13999.11 4198.54 16599.51 125
xiu_mvs_v2_base99.26 5399.25 4599.29 11899.53 12998.91 13999.02 27899.45 15098.80 3999.71 3299.26 25598.94 2799.98 599.34 2299.23 12098.98 182
xiu_mvs_v1_base99.29 4899.27 4199.34 10799.63 10998.97 12699.12 25299.51 8598.86 3199.84 899.47 20098.18 7799.99 199.50 899.31 11699.08 169
new-patchmatchnet94.48 30294.08 30395.67 31495.08 33492.41 32699.18 24399.28 23494.55 29693.49 32797.37 33387.86 32297.01 33491.57 32088.36 32897.61 330
pmmvs696.53 27196.09 27297.82 28598.69 29395.47 29699.37 18999.47 13093.46 31497.41 28999.78 7887.06 32699.33 24096.92 23092.70 31698.65 256
pmmvs597.52 24697.30 24798.16 26498.57 30396.73 26799.27 21998.90 28396.14 26798.37 26199.53 17791.54 28599.14 27497.51 18995.87 26198.63 264
test_post199.23 23265.14 35594.18 21299.71 17997.58 180
test_post65.99 35494.65 19499.73 169
Fast-Effi-MVS+98.70 12198.43 12899.51 8799.51 13299.28 8599.52 12599.47 13096.11 26999.01 19299.34 24196.20 12899.84 11997.88 15298.82 15299.39 147
patchmatchnet-post98.70 29794.79 18199.74 161
Anonymous2023121190.69 31489.39 31594.58 31694.25 33688.18 33499.29 21399.07 26282.45 34292.95 32997.65 32363.96 34997.79 32789.27 32785.63 34097.77 327
pmmvs-eth3d95.34 29794.73 29897.15 29995.53 33295.94 28799.35 19999.10 25795.13 28393.55 32697.54 33088.15 32197.91 32494.58 28789.69 32597.61 330
GG-mvs-BLEND98.45 23398.55 30498.16 20899.43 16493.68 35297.23 29298.46 30789.30 30599.22 26795.43 27498.22 18097.98 313
xiu_mvs_v1_base_debi99.29 4899.27 4199.34 10799.63 10998.97 12699.12 25299.51 8598.86 3199.84 899.47 20098.18 7799.99 199.50 899.31 11699.08 169
Anonymous2023120696.22 28496.03 27396.79 30897.31 32594.14 31499.63 7999.08 25996.17 26397.04 29699.06 27293.94 21997.76 32986.96 33595.06 27798.47 292
MTAPA99.52 1199.39 1599.89 299.90 399.86 399.66 6599.47 13098.79 4099.68 3899.81 5498.43 6499.97 1198.88 5799.90 2599.83 23
MTMP98.88 285
gm-plane-assit98.54 30592.96 32494.65 29199.15 26399.64 19697.56 184
test9_res97.49 19199.72 8699.75 56
MVP-Stereo97.81 21197.75 19297.99 27397.53 32096.60 27298.96 29398.85 28797.22 18097.23 29299.36 23495.28 15199.46 21495.51 27299.78 7597.92 317
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST999.67 9399.65 4099.05 26999.41 17096.22 25998.95 20399.49 19098.77 4299.91 74
train_agg99.02 8798.77 9999.77 3799.67 9399.65 4099.05 26999.41 17096.28 25298.95 20399.49 19098.76 4499.91 7497.63 17799.72 8699.75 56
gg-mvs-nofinetune96.17 28695.32 29398.73 20898.79 27798.14 20999.38 18794.09 35191.07 32998.07 27791.04 34789.62 30399.35 23696.75 24299.09 13098.68 231
Patchmatch-test198.16 15998.14 14398.22 25999.30 17995.55 29299.07 26398.97 27297.57 14899.43 9699.60 15392.72 24499.60 20497.38 20099.20 12299.50 128
Patchmatch-test97.93 19497.65 20298.77 20599.18 20297.07 24999.03 27599.14 25496.16 26498.74 22799.57 16294.56 19699.72 17393.36 30999.11 12799.52 120
test_899.67 9399.61 4599.03 27599.41 17096.28 25298.93 20699.48 19698.76 4499.91 74
MS-PatchMatch97.24 26197.32 24596.99 30298.45 30893.51 32298.82 30799.32 22097.41 16498.13 27299.30 24988.99 30799.56 20795.68 26999.80 7197.90 318
Patchmatch-RL test95.84 29095.81 27995.95 31395.61 33090.57 33198.24 33398.39 31995.10 28595.20 31098.67 29894.78 18297.77 32896.28 25890.02 32399.51 125
agg_prior398.97 9498.71 10599.75 4099.67 9399.60 4799.04 27499.41 17095.93 27498.87 21399.48 19698.61 5699.91 7497.63 17799.72 8699.75 56
cdsmvs_eth3d_5k24.64 33332.85 3340.00 3460.00 3600.00 3610.00 35299.51 850.00 3560.00 35799.56 16496.58 1180.00 3590.00 3560.00 3570.00 357
pcd_1.5k_mvsjas8.27 33511.03 3360.00 3460.00 3600.00 3610.00 3520.00 3620.00 3560.00 3570.27 35899.01 120.00 3590.00 3560.00 3570.00 357
pcd1.5k->3k40.85 32943.49 33132.93 34398.95 2480.00 3610.00 35299.53 720.00 3560.00 3570.27 35895.32 1500.00 3590.00 35697.30 23698.80 202
agg_prior199.01 9098.76 10199.76 3999.67 9399.62 4398.99 28499.40 17796.26 25598.87 21399.49 19098.77 4299.91 7497.69 17499.72 8699.75 56
agg_prior297.21 20799.73 8599.75 56
agg_prior99.67 9399.62 4399.40 17798.87 21399.91 74
tmp_tt82.80 32181.52 32186.66 33266.61 35768.44 35592.79 35097.92 32868.96 34880.04 34799.85 2685.77 32996.15 33997.86 15443.89 35295.39 340
canonicalmvs99.02 8798.86 8999.51 8799.42 15099.32 8099.80 1999.48 11498.63 4899.31 12398.81 29297.09 10399.75 16099.27 2997.90 20699.47 135
anonymousdsp98.44 13398.28 13898.94 15998.50 30698.96 13099.77 2499.50 9997.07 19998.87 21399.77 8594.76 18799.28 25298.66 8697.60 21498.57 286
alignmvs98.81 11198.56 12499.58 7399.43 14999.42 7299.51 12998.96 27498.61 5099.35 11798.92 28394.78 18299.77 15699.35 1898.11 20099.54 115
nrg03098.64 12798.42 12999.28 12099.05 22999.69 3299.81 1599.46 13998.04 9999.01 19299.82 4496.69 11699.38 22699.34 2294.59 29198.78 204
v14419297.92 19797.60 20698.87 18898.83 27498.65 17899.55 11899.34 20696.20 26099.32 12299.40 21894.36 20499.26 26096.37 25795.03 27898.70 221
FIs98.78 11598.63 11499.23 13099.18 20299.54 5599.83 1299.59 3898.28 7098.79 22399.81 5496.75 11499.37 22999.08 4396.38 25398.78 204
v192192097.80 21497.45 22298.84 19698.80 27598.53 18999.52 12599.34 20696.15 26699.24 14999.47 20093.98 21899.29 25195.40 27595.13 27698.69 226
UA-Net99.42 3099.29 3799.80 3199.62 11399.55 5499.50 13499.70 1598.79 4099.77 2499.96 197.45 9499.96 1998.92 5599.90 2599.89 2
v119297.81 21197.44 22798.91 17198.88 26598.68 17499.51 12999.34 20696.18 26299.20 16199.34 24194.03 21799.36 23395.32 27795.18 27398.69 226
FC-MVSNet-test98.75 11898.62 11799.15 13699.08 22399.45 6999.86 899.60 3598.23 7598.70 23699.82 4496.80 11099.22 26799.07 4496.38 25398.79 203
v114497.98 18597.69 19698.85 19598.87 26898.66 17799.54 12199.35 19896.27 25499.23 15499.35 23894.67 19299.23 26496.73 24395.16 27498.68 231
sosnet-low-res0.02 3360.03 3370.00 3460.00 3600.00 3610.00 3520.00 3620.00 3560.00 3570.27 3580.00 3640.00 3590.00 3560.00 3570.00 357
HFP-MVS99.49 1399.37 1799.86 1399.87 1599.80 1599.66 6599.67 2298.15 8099.68 3899.69 11599.06 999.96 1998.69 8399.87 3999.84 12
v14897.79 21697.55 20898.50 22698.74 28697.72 23399.54 12199.33 21496.26 25598.90 21099.51 18594.68 19199.14 27497.83 15693.15 31198.63 264
sosnet0.02 3360.03 3370.00 3460.00 3600.00 3610.00 3520.00 3620.00 3560.00 3570.27 3580.00 3640.00 3590.00 3560.00 3570.00 357
v74897.52 24697.23 25298.41 23898.69 29397.23 24299.87 499.45 15095.72 27798.51 25399.53 17794.13 21399.30 24996.78 24192.39 31898.70 221
uncertanet0.02 3360.03 3370.00 3460.00 3600.00 3610.00 3520.00 3620.00 3560.00 3570.27 3580.00 3640.00 3590.00 3560.00 3570.00 357
AllTest98.87 9998.72 10399.31 11299.86 2098.48 19799.56 11299.61 3297.85 11999.36 11499.85 2695.95 13299.85 11396.66 24899.83 6499.59 109
TestCases99.31 11299.86 2098.48 19799.61 3297.85 11999.36 11499.85 2695.95 13299.85 11396.66 24899.83 6499.59 109
v7n97.87 20197.52 21098.92 16798.76 28598.58 18699.84 999.46 13996.20 26098.91 20899.70 10994.89 17599.44 22096.03 26193.89 30498.75 210
v114198.05 17597.76 18998.91 17198.91 26098.78 16799.57 10599.35 19896.41 24599.23 15499.36 23494.93 17199.27 25597.38 20094.72 28598.68 231
region2R99.48 1799.35 2299.87 699.88 1199.80 1599.65 7599.66 2598.13 8299.66 4999.68 12098.96 2199.96 1998.62 9199.87 3999.84 12
testing_294.44 30392.93 30998.98 15394.16 33799.00 12199.42 17199.28 23496.60 22884.86 34096.84 33570.91 34399.27 25598.23 12796.08 25998.68 231
test_normal97.44 25496.77 26499.44 9997.75 31999.00 12199.10 26098.64 31297.71 13693.93 32398.82 29187.39 32499.83 12698.61 9398.97 13999.49 129
v1neww98.12 16397.84 17598.93 16298.97 24398.81 15899.66 6599.35 19896.49 23399.29 12899.37 22795.02 16499.32 24397.73 16894.73 28398.67 242
PS-MVSNAJss98.92 9798.92 7998.90 17598.78 28198.53 18999.78 2299.54 6298.07 9399.00 19999.76 8899.01 1299.37 22999.13 3997.23 23898.81 201
PS-MVSNAJ99.32 4399.32 2799.30 11599.57 12498.94 13498.97 29199.46 13998.92 2899.71 3299.24 25799.01 1299.98 599.35 1899.66 9898.97 183
jajsoiax98.43 13498.28 13898.88 18498.60 30198.43 19999.82 1399.53 7298.19 7698.63 24799.80 6593.22 23399.44 22099.22 3197.50 22398.77 207
mvs_tets98.40 13798.23 14098.91 17198.67 29698.51 19499.66 6599.53 7298.19 7698.65 24599.81 5492.75 24199.44 22099.31 2597.48 22798.77 207
#test#99.43 2899.29 3799.86 1399.87 1599.80 1599.55 11899.67 2297.83 12299.68 3899.69 11599.06 999.96 1998.39 11599.87 3999.84 12
EI-MVSNet-UG-set99.58 399.57 199.64 6499.78 3699.14 10099.60 9099.45 15099.01 1399.90 199.83 3798.98 1999.93 5799.59 299.95 699.86 5
EI-MVSNet-Vis-set99.58 399.56 399.64 6499.78 3699.15 9999.61 8899.45 15099.01 1399.89 299.82 4499.01 1299.92 6599.56 599.95 699.85 8
Regformer-399.57 699.53 599.68 5299.76 4499.29 8499.58 9999.44 15899.01 1399.87 699.80 6598.97 2099.91 7499.44 1699.92 1299.83 23
Regformer-499.59 299.54 499.73 4799.76 4499.41 7399.58 9999.49 10599.02 1099.88 399.80 6599.00 1899.94 4299.45 1599.92 1299.84 12
Regformer-199.53 999.47 899.72 4999.71 8299.44 7099.49 14299.46 13998.95 2499.83 1299.76 8899.01 1299.93 5799.17 3699.87 3999.80 42
Regformer-299.54 799.47 899.75 4099.71 8299.52 6199.49 14299.49 10598.94 2699.83 1299.76 8899.01 1299.94 4299.15 3899.87 3999.80 42
v7new98.12 16397.84 17598.93 16298.97 24398.81 15899.66 6599.35 19896.49 23399.29 12899.37 22795.02 16499.32 24397.73 16894.73 28398.67 242
HPM-MVS++copyleft99.39 3799.23 4699.87 699.75 5699.84 799.43 16499.51 8598.68 4799.27 13699.53 17798.64 5599.96 1998.44 11499.80 7199.79 46
test_prior499.56 5298.99 284
XVS99.53 999.42 1199.87 699.85 2399.83 899.69 4599.68 1998.98 1999.37 11099.74 9898.81 3699.94 4298.79 7299.86 4999.84 12
v124097.69 23397.32 24598.79 20298.85 27298.43 19999.48 14799.36 19496.11 26999.27 13699.36 23493.76 22699.24 26394.46 29095.23 27298.70 221
test_prior399.21 5699.05 6099.68 5299.67 9399.48 6598.96 29399.56 4898.34 6699.01 19299.52 18298.68 5299.83 12697.96 14699.74 8299.74 61
v1896.42 27495.80 28198.26 25098.95 24898.82 15699.76 2799.28 23494.58 29294.12 31597.70 31995.22 15798.16 31294.83 28487.80 32997.79 326
pm-mvs197.68 23597.28 24998.88 18499.06 22698.62 18299.50 13499.45 15096.32 24997.87 28299.79 7392.47 26099.35 23697.54 18693.54 30798.67 242
test_prior298.96 29398.34 6699.01 19299.52 18298.68 5297.96 14699.74 82
X-MVStestdata96.55 27095.45 29199.87 699.85 2399.83 899.69 4599.68 1998.98 1999.37 11064.01 35698.81 3699.94 4298.79 7299.86 4999.84 12
test_prior99.68 5299.67 9399.48 6599.56 4899.83 12699.74 61
v1796.42 27495.81 27998.25 25498.94 25198.80 16399.76 2799.28 23494.57 29394.18 31497.71 31895.23 15698.16 31294.86 28287.73 33197.80 321
v1696.39 27695.76 28298.26 25098.96 24698.81 15899.76 2799.28 23494.57 29394.10 31697.70 31995.04 16398.16 31294.70 28687.77 33097.80 321
divwei89l23v2f11298.06 16997.78 18298.91 17198.90 26198.77 16899.57 10599.35 19896.45 24099.24 14999.37 22794.92 17299.27 25597.50 19094.71 28798.68 231
v1596.28 27895.62 28498.25 25498.94 25198.83 14999.76 2799.29 22794.52 29794.02 31997.61 32695.02 16498.13 31694.53 28886.92 33497.80 321
旧先验298.96 29396.70 22099.47 8999.94 4298.19 128
新几何299.01 282
新几何199.75 4099.75 5699.59 4999.54 6296.76 21699.29 12899.64 13898.43 6499.94 4296.92 23099.66 9899.72 72
旧先验199.74 6799.59 4999.54 6299.69 11598.47 6199.68 9699.73 66
无先验98.99 28499.51 8596.89 21199.93 5797.53 18799.72 72
原ACMM298.95 297
原ACMM199.65 5999.73 7299.33 7999.47 13097.46 15799.12 17299.66 13098.67 5499.91 7497.70 17399.69 9399.71 79
v1396.24 28195.58 28698.25 25498.98 24098.83 14999.75 3499.29 22794.35 30293.89 32497.60 32795.17 15998.11 31894.27 30086.86 33797.81 319
v1296.24 28195.58 28698.23 25798.96 24698.81 15899.76 2799.29 22794.42 30193.85 32597.60 32795.12 16098.09 31994.32 29786.85 33897.80 321
test22299.75 5699.49 6498.91 30299.49 10596.42 24399.34 12099.65 13198.28 7499.69 9399.72 72
testdata299.95 3396.67 247
segment_acmp98.96 21
testdata99.54 7799.75 5698.95 13199.51 8597.07 19999.43 9699.70 10998.87 3199.94 4297.76 16499.64 10199.72 72
testdata198.85 30698.32 69
v897.95 19397.63 20498.93 16298.95 24898.81 15899.80 1999.41 17096.03 27399.10 17799.42 21194.92 17299.30 24996.94 22894.08 30098.66 253
131498.68 12398.54 12599.11 14198.89 26498.65 17899.27 21999.49 10596.89 21197.99 27999.56 16497.72 9099.83 12697.74 16799.27 11998.84 199
112199.09 7798.87 8699.75 4099.74 6799.60 4799.27 21999.48 11496.82 21599.25 14499.65 13198.38 6899.93 5797.53 18799.67 9799.73 66
LFMVS97.90 19997.35 23999.54 7799.52 13099.01 11999.39 18298.24 32397.10 19299.65 5299.79 7384.79 33499.91 7499.28 2798.38 17299.69 80
v798.05 17597.78 18298.87 18898.99 23698.67 17599.64 7799.34 20696.31 25199.29 12899.51 18594.78 18299.27 25597.03 22095.15 27598.66 253
v698.12 16397.84 17598.94 15998.94 25198.83 14999.66 6599.34 20696.49 23399.30 12499.37 22794.95 16899.34 23997.77 16394.74 28298.67 242
VDD-MVS97.73 22797.35 23998.88 18499.47 14397.12 24499.34 20298.85 28798.19 7699.67 4499.85 2682.98 33899.92 6599.49 1298.32 17499.60 105
v1196.23 28395.57 28998.21 26098.93 25698.83 14999.72 3999.29 22794.29 30394.05 31897.64 32494.88 17698.04 32092.89 31588.43 32797.77 327
VDDNet97.55 24397.02 25899.16 13499.49 13998.12 21199.38 18799.30 22395.35 28299.68 3899.90 782.62 34099.93 5799.31 2598.13 19299.42 144
v5297.79 21697.50 21498.66 21598.80 27598.62 18299.87 499.44 15895.87 27599.01 19299.46 20494.44 20399.33 24096.65 25093.96 30398.05 308
V1496.26 27995.60 28598.26 25098.94 25198.83 14999.76 2799.29 22794.49 29893.96 32197.66 32294.99 16798.13 31694.41 29186.90 33597.80 321
v1097.85 20397.52 21098.86 19298.99 23698.67 17599.75 3499.41 17095.70 27898.98 20199.41 21494.75 18899.23 26496.01 26294.63 29098.67 242
V497.80 21497.51 21298.67 21498.79 27798.63 18099.87 499.44 15895.87 27599.01 19299.46 20494.52 19999.33 24096.64 25193.97 30298.05 308
VPNet97.84 20597.44 22799.01 14999.21 19598.94 13499.48 14799.57 4498.38 6499.28 13299.73 10188.89 30899.39 22599.19 3393.27 30998.71 217
MVS97.28 25996.55 26699.48 9098.78 28198.95 13199.27 21999.39 18083.53 34098.08 27499.54 17096.97 10699.87 10494.23 30199.16 12499.63 101
v2v48298.06 16997.77 18698.92 16798.90 26198.82 15699.57 10599.36 19496.65 22399.19 16499.35 23894.20 20999.25 26197.72 17294.97 27998.69 226
v198.05 17597.76 18998.93 16298.92 25898.80 16399.57 10599.35 19896.39 24799.28 13299.36 23494.86 17799.32 24397.38 20094.72 28598.68 231
V4298.06 16997.79 18098.86 19298.98 24098.84 14699.69 4599.34 20696.53 23299.30 12499.37 22794.67 19299.32 24397.57 18294.66 28898.42 295
V996.25 28095.58 28698.26 25098.94 25198.83 14999.75 3499.29 22794.45 30093.96 32197.62 32594.94 16998.14 31594.40 29286.87 33697.81 319
SD-MVS99.41 3399.52 699.05 14699.74 6799.68 3399.46 15499.52 7699.11 799.88 399.91 599.43 197.70 33098.72 8099.93 1199.77 52
GA-MVS97.85 20397.47 21999.00 15199.38 16197.99 21498.57 32299.15 25297.04 20298.90 21099.30 24989.83 30099.38 22696.70 24598.33 17399.62 103
MSLP-MVS++99.46 2299.47 899.44 9999.60 11999.16 9699.41 17599.71 1398.98 1999.45 9299.78 7899.19 599.54 21099.28 2799.84 5899.63 101
APDe-MVS99.66 199.57 199.92 199.77 4199.89 199.75 3499.56 4899.02 1099.88 399.85 2699.18 699.96 1999.22 3199.92 1299.90 1
APD-MVS_3200maxsize99.48 1799.35 2299.85 1999.76 4499.83 899.63 7999.54 6298.36 6599.79 1999.82 4498.86 3299.95 3398.62 9199.81 6999.78 50
ADS-MVSNet298.02 18098.07 15197.87 28099.33 17095.19 30299.23 23299.08 25996.24 25799.10 17799.67 12494.11 21498.93 30196.81 23999.05 13399.48 131
EI-MVSNet98.67 12498.67 10998.68 21299.35 16697.97 21599.50 13499.38 18696.93 20999.20 16199.83 3797.87 8499.36 23398.38 11797.56 21898.71 217
Regformer0.02 3360.03 3370.00 3460.00 3600.00 3610.00 3520.00 3620.00 3560.00 3570.27 3580.00 3640.00 3590.00 3560.00 3570.00 357
CVMVSNet98.57 12998.67 10998.30 24699.35 16695.59 29199.50 13499.55 5598.60 5199.39 10699.83 3794.48 20099.45 21598.75 7598.56 16499.85 8
pmmvs498.13 16197.90 16398.81 19998.61 30098.87 14298.99 28499.21 24696.44 24199.06 18799.58 15895.90 13699.11 28097.18 21196.11 25898.46 294
EU-MVSNet97.98 18598.03 15397.81 28698.72 28996.65 27199.66 6599.66 2598.09 8998.35 26399.82 4495.25 15598.01 32297.41 19995.30 27198.78 204
VNet99.11 7398.90 8299.73 4799.52 13099.56 5299.41 17599.39 18099.01 1399.74 3199.78 7895.56 14499.92 6599.52 798.18 18499.72 72
test-LLR98.06 16997.90 16398.55 22498.79 27797.10 24598.67 31697.75 33197.34 16898.61 25098.85 28894.45 20199.45 21597.25 20599.38 11199.10 164
TESTMET0.1,197.55 24397.27 25198.40 23998.93 25696.53 27398.67 31697.61 34196.96 20698.64 24699.28 25288.63 31499.45 21597.30 20499.38 11199.21 158
test-mter97.49 25297.13 25598.55 22498.79 27797.10 24598.67 31697.75 33196.65 22398.61 25098.85 28888.23 31999.45 21597.25 20599.38 11199.10 164
VPA-MVSNet98.29 14397.95 16099.30 11599.16 20999.54 5599.50 13499.58 4398.27 7199.35 11799.37 22792.53 25899.65 19499.35 1894.46 29298.72 215
ACMMPR99.49 1399.36 1999.86 1399.87 1599.79 1999.66 6599.67 2298.15 8099.67 4499.69 11598.95 2699.96 1998.69 8399.87 3999.84 12
testgi97.65 24097.50 21498.13 26599.36 16596.45 27699.42 17199.48 11497.76 13097.87 28299.45 20791.09 28898.81 30494.53 28898.52 16699.13 163
test20.0396.12 28795.96 27696.63 30997.44 32195.45 29799.51 12999.38 18696.55 23196.16 30599.25 25693.76 22696.17 33887.35 33494.22 29798.27 302
thres600view797.86 20297.51 21298.92 16799.72 7697.95 21899.59 9298.74 29997.94 11199.27 13698.62 29991.75 27599.86 10793.73 30598.19 18398.96 189
111192.30 31192.21 31292.55 32293.30 33886.27 33599.15 24898.74 29991.94 32290.85 33597.82 31684.18 33595.21 34079.65 34394.27 29696.19 337
.test124583.42 31986.17 31775.15 34193.30 33886.27 33599.15 24898.74 29991.94 32290.85 33597.82 31684.18 33595.21 34079.65 34339.90 35343.98 354
ADS-MVSNet98.20 15598.08 14998.56 22299.33 17096.48 27599.23 23299.15 25296.24 25799.10 17799.67 12494.11 21499.71 17996.81 23999.05 13399.48 131
MP-MVScopyleft99.33 4299.15 5199.87 699.88 1199.82 1399.66 6599.46 13998.09 8999.48 8899.74 9898.29 7399.96 1997.93 14999.87 3999.82 32
testmvs39.17 33143.78 33025.37 34536.04 35916.84 36098.36 32826.56 35920.06 35438.51 35567.32 35229.64 35915.30 35837.59 35439.90 35343.98 354
thres40097.77 21997.38 23598.92 16799.69 8997.96 21699.50 13498.73 30897.83 12299.17 16798.45 30891.67 28199.83 12693.22 31098.18 18498.96 189
test12339.01 33242.50 33228.53 34439.17 35820.91 35998.75 31219.17 36119.83 35538.57 35466.67 35333.16 35715.42 35737.50 35529.66 35549.26 353
thres20097.61 24197.28 24998.62 21699.64 10698.03 21299.26 22798.74 29997.68 14099.09 18198.32 31091.66 28399.81 13992.88 31698.22 18098.03 311
test0.0.03 197.71 23297.42 23198.56 22298.41 30997.82 22498.78 30998.63 31397.34 16898.05 27898.98 28094.45 20198.98 29395.04 28197.15 24298.89 197
test1235691.74 31292.19 31390.37 33091.22 34282.41 34298.61 32098.28 32190.66 33091.82 33397.92 31484.90 33392.61 34681.64 34294.66 28896.09 338
testus94.61 30195.30 29492.54 32396.44 32884.18 33998.36 32899.03 26794.18 30496.49 30198.57 30588.74 30995.09 34287.41 33398.45 16998.36 301
pmmvs394.09 30693.25 30896.60 31094.76 33594.49 31098.92 30098.18 32689.66 33196.48 30298.06 31386.28 32797.33 33289.68 32687.20 33397.97 314
testmv87.91 31587.80 31688.24 33187.68 34977.50 34999.07 26397.66 34089.27 33286.47 33996.22 33868.35 34592.49 34876.63 34788.82 32694.72 341
EMVS80.02 32379.22 32482.43 33991.19 34376.40 35097.55 34392.49 35866.36 35183.01 34391.27 34564.63 34885.79 35465.82 35260.65 34885.08 351
E-PMN80.61 32279.88 32382.81 33790.75 34476.38 35197.69 34095.76 34866.44 35083.52 34192.25 34462.54 35087.16 35368.53 35161.40 34784.89 352
test235694.07 30794.46 30292.89 32195.18 33386.13 33797.60 34299.06 26493.61 31196.15 30798.28 31185.60 33193.95 34486.68 33798.00 20398.59 282
test123567892.91 31093.30 30791.71 32793.14 34083.01 34198.75 31298.58 31692.80 31992.45 33097.91 31588.51 31693.54 34582.26 34195.35 27098.59 282
PGM-MVS99.45 2399.31 3299.86 1399.87 1599.78 2399.58 9999.65 3097.84 12199.71 3299.80 6599.12 899.97 1198.33 12299.87 3999.83 23
LCM-MVSNet-Re97.83 20798.15 14296.87 30699.30 17992.25 32899.59 9298.26 32297.43 16196.20 30499.13 26596.27 12698.73 30698.17 13098.99 13799.64 97
LCM-MVSNet86.80 31785.22 32091.53 32887.81 34880.96 34598.23 33598.99 27071.05 34690.13 33796.51 33748.45 35496.88 33590.51 32285.30 34196.76 334
MCST-MVS99.43 2899.30 3499.82 2699.79 3599.74 2799.29 21399.40 17798.79 4099.52 8199.62 14798.91 2999.90 8798.64 8899.75 8099.82 32
mvs_anonymous99.03 8698.99 7099.16 13499.38 16198.52 19299.51 12999.38 18697.79 12799.38 10899.81 5497.30 9999.45 21599.35 1898.99 13799.51 125
MVS_Test99.10 7698.97 7399.48 9099.49 13999.14 10099.67 5699.34 20697.31 17199.58 6599.76 8897.65 9199.82 13598.87 6199.07 13299.46 138
MDA-MVSNet-bldmvs94.96 29993.98 30497.92 27798.24 31297.27 23899.15 24899.33 21493.80 30980.09 34699.03 27588.31 31897.86 32693.49 30894.36 29498.62 266
CDPH-MVS99.13 6498.91 8199.80 3199.75 5699.71 2999.15 24899.41 17096.60 22899.60 6199.55 16798.83 3499.90 8797.48 19299.83 6499.78 50
test1299.75 4099.64 10699.61 4599.29 22799.21 15898.38 6899.89 9599.74 8299.74 61
diffmvs98.72 12098.49 12699.43 10299.48 14299.19 9399.62 8299.42 16795.58 28099.37 11099.67 12496.14 12999.74 16198.14 13298.96 14099.37 148
YYNet195.36 29694.51 30197.92 27797.89 31597.10 24599.10 26099.23 24493.26 31680.77 34499.04 27492.81 24098.02 32194.30 29894.18 29898.64 258
PMMVS286.87 31685.37 31991.35 32990.21 34583.80 34098.89 30397.45 34383.13 34191.67 33495.03 33948.49 35394.70 34385.86 33877.62 34495.54 339
MDA-MVSNet_test_wron95.45 29494.60 29998.01 27198.16 31397.21 24399.11 25899.24 24393.49 31380.73 34598.98 28093.02 23498.18 31094.22 30294.45 29398.64 258
tpmvs97.98 18598.02 15497.84 28399.04 23094.73 30999.31 20799.20 24796.10 27298.76 22699.42 21194.94 16999.81 13996.97 22598.45 16998.97 183
PM-MVS92.96 30992.23 31195.14 31595.61 33089.98 33399.37 18998.21 32494.80 28895.04 31297.69 32165.06 34797.90 32594.30 29889.98 32497.54 333
HQP_MVS98.27 14598.22 14198.44 23699.29 18296.97 25899.39 18299.47 13098.97 2299.11 17499.61 15092.71 24599.69 18897.78 16197.63 21198.67 242
plane_prior799.29 18297.03 253
plane_prior699.27 18796.98 25792.71 245
plane_prior599.47 13099.69 18897.78 16197.63 21198.67 242
plane_prior499.61 150
plane_prior397.00 25598.69 4699.11 174
plane_prior299.39 18298.97 22
plane_prior199.26 189
plane_prior96.97 25899.21 23998.45 5997.60 214
PS-CasMVS97.93 19497.59 20798.95 15898.99 23699.06 10799.68 5499.52 7697.13 18698.31 26599.68 12092.44 26499.05 28598.51 10794.08 30098.75 210
UniMVSNet_NR-MVSNet98.22 15097.97 15898.96 15698.92 25898.98 12399.48 14799.53 7297.76 13098.71 23099.46 20496.43 12299.22 26798.57 9892.87 31498.69 226
PEN-MVS97.76 22097.44 22798.72 20998.77 28498.54 18899.78 2299.51 8597.06 20198.29 26799.64 13892.63 25598.89 30298.09 13593.16 31098.72 215
TransMVSNet (Re)97.15 26296.58 26598.86 19299.12 21598.85 14599.49 14298.91 28195.48 28197.16 29499.80 6593.38 23099.11 28094.16 30391.73 31998.62 266
DTE-MVSNet97.51 24997.19 25498.46 23298.63 29998.13 21099.84 999.48 11496.68 22197.97 28099.67 12492.92 23798.56 30896.88 23892.60 31798.70 221
DU-MVS98.08 16897.79 18098.96 15698.87 26898.98 12399.41 17599.45 15097.87 11698.71 23099.50 18794.82 17999.22 26798.57 9892.87 31498.68 231
UniMVSNet (Re)98.29 14398.00 15699.13 14099.00 23599.36 7799.49 14299.51 8597.95 11098.97 20299.13 26596.30 12599.38 22698.36 12093.34 30898.66 253
CP-MVSNet98.09 16797.78 18299.01 14998.97 24399.24 9099.67 5699.46 13997.25 17698.48 25699.64 13893.79 22499.06 28498.63 8994.10 29998.74 213
WR-MVS_H98.13 16197.87 17498.90 17599.02 23398.84 14699.70 4299.59 3897.27 17498.40 25999.19 26195.53 14599.23 26498.34 12193.78 30598.61 275
WR-MVS98.06 16997.73 19399.06 14498.86 27199.25 8999.19 24299.35 19897.30 17298.66 23999.43 20993.94 21999.21 27198.58 9694.28 29598.71 217
NR-MVSNet97.97 18897.61 20599.02 14898.87 26899.26 8899.47 15199.42 16797.63 14397.08 29599.50 18795.07 16299.13 27797.86 15493.59 30698.68 231
Baseline_NR-MVSNet97.76 22097.45 22298.68 21299.09 22298.29 20399.41 17598.85 28795.65 27998.63 24799.67 12494.82 17999.10 28298.07 14192.89 31398.64 258
TranMVSNet+NR-MVSNet97.93 19497.66 19798.76 20798.78 28198.62 18299.65 7599.49 10597.76 13098.49 25599.60 15394.23 20898.97 30098.00 14492.90 31298.70 221
TSAR-MVS + GP.99.36 3999.36 1999.36 10699.67 9398.61 18599.07 26399.33 21499.00 1799.82 1599.81 5499.06 999.84 11999.09 4299.42 10999.65 91
abl_699.44 2699.31 3299.83 2499.85 2399.75 2499.66 6599.59 3898.13 8299.82 1599.81 5498.60 5799.96 1998.46 11299.88 3599.79 46
n20.00 362
nn0.00 362
mPP-MVS99.44 2699.30 3499.86 1399.88 1199.79 1999.69 4599.48 11498.12 8499.50 8499.75 9398.78 3999.97 1198.57 9899.89 3399.83 23
door-mid98.05 327
DI_MVS_plusplus_test97.45 25396.79 26299.44 9997.76 31899.04 10999.21 23998.61 31597.74 13394.01 32098.83 29087.38 32599.83 12698.63 8998.90 14799.44 141
XVG-OURS-SEG-HR98.69 12298.62 11798.89 17799.71 8297.74 23199.12 25299.54 6298.44 6299.42 9999.71 10694.20 20999.92 6598.54 10698.90 14799.00 179
DWT-MVSNet_test97.53 24597.40 23397.93 27699.03 23294.86 30699.57 10598.63 31396.59 23098.36 26298.79 29389.32 30499.74 16198.14 13298.16 19199.20 159
MVSFormer99.17 6099.12 5599.29 11899.51 13298.94 13499.88 199.46 13997.55 15099.80 1799.65 13197.39 9599.28 25299.03 4699.85 5399.65 91
jason99.13 6499.03 6599.45 9699.46 14498.87 14299.12 25299.26 24098.03 10199.79 1999.65 13197.02 10599.85 11399.02 4899.90 2599.65 91
jason: jason.
lupinMVS99.13 6499.01 6999.46 9599.51 13298.94 13499.05 26999.16 25197.86 11799.80 1799.56 16497.39 9599.86 10798.94 5499.85 5399.58 111
test_djsdf98.67 12498.57 12398.98 15398.70 29298.91 13999.88 199.46 13997.55 15099.22 15699.88 1495.73 14299.28 25299.03 4697.62 21398.75 210
Test495.05 29893.67 30699.22 13196.07 32998.94 13499.20 24199.27 23997.71 13689.96 33897.59 32966.18 34699.25 26198.06 14298.96 14099.47 135
HPM-MVS_fast99.51 1299.40 1499.85 1999.91 199.79 1999.76 2799.56 4897.72 13599.76 2999.75 9399.13 799.92 6599.07 4499.92 1299.85 8
PatchFormer-LS_test98.01 18398.05 15297.87 28099.15 21294.76 30899.42 17198.93 27697.12 18898.84 21998.59 30493.74 22899.80 14398.55 10498.17 19099.06 174
testpf95.66 29296.02 27594.58 31698.35 31092.32 32797.25 34497.91 33092.83 31897.03 29798.99 27788.69 31198.61 30795.72 26797.40 23292.80 343
K. test v397.10 26496.79 26298.01 27198.72 28996.33 28099.87 497.05 34597.59 14596.16 30599.80 6588.71 31099.04 28696.69 24696.55 25098.65 256
lessismore_v097.79 28798.69 29395.44 29894.75 34995.71 30999.87 1988.69 31199.32 24395.89 26394.93 28198.62 266
SixPastTwentyTwo97.50 25097.33 24498.03 26898.65 29796.23 28399.77 2498.68 31197.14 18597.90 28199.93 490.45 29399.18 27397.00 22296.43 25298.67 242
OurMVSNet-221017-097.88 20097.77 18698.19 26298.71 29196.53 27399.88 199.00 26997.79 12798.78 22499.94 391.68 28099.35 23697.21 20796.99 24498.69 226
HPM-MVScopyleft99.42 3099.28 3999.83 2499.90 399.72 2899.81 1599.54 6297.59 14599.68 3899.63 14298.91 2999.94 4298.58 9699.91 1799.84 12
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS98.73 11998.68 10898.88 18499.70 8797.73 23298.92 30099.55 5598.52 5599.45 9299.84 3595.27 15299.91 7498.08 13998.84 15199.00 179
XVG-ACMP-BASELINE97.83 20797.71 19598.20 26199.11 21796.33 28099.41 17599.52 7698.06 9799.05 18899.50 18789.64 30299.73 16997.73 16897.38 23498.53 288
LPG-MVS_test98.22 15098.13 14498.49 22799.33 17097.05 25199.58 9999.55 5597.46 15799.24 14999.83 3792.58 25699.72 17398.09 13597.51 22198.68 231
LGP-MVS_train98.49 22799.33 17097.05 25199.55 5597.46 15799.24 14999.83 3792.58 25699.72 17398.09 13597.51 22198.68 231
test1199.35 198
door97.92 328
EPNet_dtu98.03 17897.96 15998.23 25798.27 31195.54 29499.23 23298.75 29699.02 1097.82 28499.71 10696.11 13099.48 21293.04 31499.65 10099.69 80
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268899.19 5799.10 5799.45 9699.89 898.52 19299.39 18299.94 198.73 4499.11 17499.89 1095.50 14699.94 4299.50 899.97 399.89 2
EPNet98.86 10298.71 10599.30 11597.20 32798.18 20799.62 8298.91 28199.28 298.63 24799.81 5495.96 13199.99 199.24 3099.72 8699.73 66
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS96.83 263
HQP-NCC99.19 19998.98 28898.24 7298.66 239
ACMP_Plane99.19 19998.98 28898.24 7298.66 239
APD-MVScopyleft99.27 5199.08 5899.84 2399.75 5699.79 1999.50 13499.50 9997.16 18499.77 2499.82 4498.78 3999.94 4297.56 18499.86 4999.80 42
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS97.19 209
HQP4-MVS98.66 23999.64 19698.64 258
HQP3-MVS99.39 18097.58 216
HQP2-MVS92.47 260
LP97.04 26596.80 26197.77 28898.90 26195.23 30098.97 29199.06 26494.02 30598.09 27399.41 21493.88 22198.82 30390.46 32398.42 17199.26 156
CNVR-MVS99.42 3099.30 3499.78 3599.62 11399.71 2999.26 22799.52 7698.82 3599.39 10699.71 10698.96 2199.85 11398.59 9599.80 7199.77 52
NCCC99.34 4199.19 4899.79 3499.61 11799.65 4099.30 20999.48 11498.86 3199.21 15899.63 14298.72 5099.90 8798.25 12699.63 10399.80 42
114514_t98.93 9698.67 10999.72 4999.85 2399.53 5899.62 8299.59 3892.65 32099.71 3299.78 7898.06 8199.90 8798.84 6699.91 1799.74 61
CP-MVS99.45 2399.32 2799.85 1999.83 2899.75 2499.69 4599.52 7698.07 9399.53 7999.63 14298.93 2899.97 1198.74 7699.91 1799.83 23
DSMNet-mixed97.25 26097.35 23996.95 30497.84 31693.61 32199.57 10596.63 34696.13 26898.87 21398.61 30394.59 19597.70 33095.08 28098.86 15099.55 113
tpm297.44 25497.34 24297.74 29099.15 21294.36 31299.45 15598.94 27593.45 31598.90 21099.44 20891.35 28699.59 20697.31 20398.07 20199.29 154
NP-MVS99.23 19296.92 26199.40 218
EG-PatchMatch MVS95.97 28995.69 28396.81 30797.78 31792.79 32599.16 24598.93 27696.16 26494.08 31799.22 25982.72 33999.47 21395.67 27097.50 22398.17 305
tpm cat197.39 25697.36 23797.50 29699.17 20793.73 31799.43 16499.31 22191.27 32698.71 23099.08 26994.31 20799.77 15696.41 25698.50 16799.00 179
SteuartSystems-ACMMP99.54 799.42 1199.87 699.82 2999.81 1499.59 9299.51 8598.62 4999.79 1999.83 3799.28 399.97 1198.48 10999.90 2599.84 12
Skip Steuart: Steuart Systems R&D Blog.
tpmp4_e2397.34 25797.29 24897.52 29499.25 19193.73 31799.58 9999.19 25094.00 30698.20 26999.41 21490.74 29299.74 16197.13 21598.07 20199.07 173
CostFormer97.72 22997.73 19397.71 29199.15 21294.02 31599.54 12199.02 26894.67 29099.04 18999.35 23892.35 26699.77 15698.50 10897.94 20599.34 151
CR-MVSNet98.17 15797.93 16298.87 18899.18 20298.49 19599.22 23699.33 21496.96 20699.56 6999.38 22394.33 20599.00 29194.83 28498.58 16199.14 161
JIA-IIPM97.50 25097.02 25898.93 16298.73 28797.80 22999.30 20998.97 27291.73 32598.91 20894.86 34195.10 16199.71 17997.58 18097.98 20499.28 155
Patchmtry97.75 22497.40 23398.81 19999.10 22098.87 14299.11 25899.33 21494.83 28798.81 22199.38 22394.33 20599.02 28996.10 25995.57 26798.53 288
PatchT97.03 26696.44 26798.79 20298.99 23698.34 20299.16 24599.07 26292.13 32199.52 8197.31 33494.54 19898.98 29388.54 32998.73 15799.03 176
tpmrst98.33 14098.48 12797.90 27999.16 20994.78 30799.31 20799.11 25697.27 17499.45 9299.59 15595.33 14999.84 11998.48 10998.61 15899.09 168
BH-w/o98.00 18497.89 16798.32 24499.35 16696.20 28499.01 28298.90 28396.42 24398.38 26099.00 27695.26 15499.72 17396.06 26098.61 15899.03 176
tpm97.67 23897.55 20898.03 26899.02 23395.01 30599.43 16498.54 31896.44 24199.12 17299.34 24191.83 27499.60 20497.75 16696.46 25199.48 131
DELS-MVS99.48 1799.42 1199.65 5999.72 7699.40 7599.05 26999.66 2599.14 699.57 6899.80 6598.46 6299.94 4299.57 499.84 5899.60 105
Christian Sormann, Emanuele Santellani, Mattia Rossi, Andreas Kuhn, Friedrich Fraundorfer: DELS-MVS: Deep Epipolar Line Search for Multi-View Stereo. Winter Conference on Applications of Computer Vision (WACV), 2023
BH-untuned98.42 13598.36 13198.59 21899.49 13996.70 26899.27 21999.13 25597.24 17898.80 22299.38 22395.75 14199.74 16197.07 21999.16 12499.33 152
RPMNet96.61 26995.85 27798.87 18899.18 20298.49 19599.22 23699.08 25988.72 33699.56 6997.38 33294.08 21699.00 29186.87 33698.58 16199.14 161
no-one83.04 32080.12 32291.79 32689.44 34785.65 33899.32 20498.32 32089.06 33379.79 34889.16 34944.86 35596.67 33684.33 34046.78 35193.05 342
MVSTER98.49 13098.32 13599.00 15199.35 16699.02 11799.54 12199.38 18697.41 16499.20 16199.73 10193.86 22399.36 23398.87 6197.56 21898.62 266
CPTT-MVS99.11 7398.90 8299.74 4599.80 3499.46 6899.59 9299.49 10597.03 20399.63 5499.69 11597.27 10099.96 1997.82 15799.84 5899.81 36
GBi-Net97.68 23597.48 21798.29 24799.51 13297.26 23999.43 16499.48 11496.49 23399.07 18399.32 24690.26 29598.98 29397.10 21696.65 24698.62 266
PVSNet_Blended_VisFu99.36 3999.28 3999.61 6899.86 2099.07 10699.47 15199.93 297.66 14299.71 3299.86 2297.73 8999.96 1999.47 1399.82 6899.79 46
PVSNet_BlendedMVS98.86 10298.80 9699.03 14799.76 4498.79 16599.28 21699.91 397.42 16399.67 4499.37 22797.53 9299.88 10298.98 5197.29 23798.42 295
UnsupCasMVSNet_eth96.44 27296.12 27197.40 29898.65 29795.65 28999.36 19599.51 8597.13 18696.04 30898.99 27788.40 31798.17 31196.71 24490.27 32298.40 297
UnsupCasMVSNet_bld93.53 30892.51 31096.58 31197.38 32293.82 31698.24 33399.48 11491.10 32893.10 32896.66 33674.89 34298.37 30994.03 30487.71 33297.56 332
PVSNet_Blended99.08 7998.97 7399.42 10399.76 4498.79 16598.78 30999.91 396.74 21799.67 4499.49 19097.53 9299.88 10298.98 5199.85 5399.60 105
FMVSNet596.43 27396.19 27097.15 29999.11 21795.89 28899.32 20499.52 7694.47 29998.34 26499.07 27087.54 32397.07 33392.61 31895.72 26498.47 292
test197.68 23597.48 21798.29 24799.51 13297.26 23999.43 16499.48 11496.49 23399.07 18399.32 24690.26 29598.98 29397.10 21696.65 24698.62 266
new_pmnet96.38 27796.03 27397.41 29798.13 31495.16 30499.05 26999.20 24793.94 30797.39 29098.79 29391.61 28499.04 28690.43 32495.77 26398.05 308
FMVSNet398.03 17897.76 18998.84 19699.39 16098.98 12399.40 18199.38 18696.67 22299.07 18399.28 25292.93 23698.98 29397.10 21696.65 24698.56 287
dp97.75 22497.80 17997.59 29399.10 22093.71 31999.32 20498.88 28596.48 23999.08 18299.55 16792.67 25499.82 13596.52 25298.58 16199.24 157
FMVSNet297.72 22997.36 23798.80 20199.51 13298.84 14699.45 15599.42 16796.49 23398.86 21899.29 25190.26 29598.98 29396.44 25496.56 24998.58 285
FMVSNet196.84 26796.36 26898.29 24799.32 17797.26 23999.43 16499.48 11495.11 28498.55 25299.32 24683.95 33798.98 29395.81 26596.26 25698.62 266
N_pmnet94.95 30095.83 27892.31 32498.47 30779.33 34799.12 25292.81 35693.87 30897.68 28799.13 26593.87 22299.01 29091.38 32196.19 25798.59 282
cascas97.69 23397.43 23098.48 22998.60 30197.30 23698.18 33699.39 18092.96 31798.41 25898.78 29593.77 22599.27 25598.16 13198.61 15898.86 198
BH-RMVSNet98.41 13698.08 14999.40 10499.41 15398.83 14999.30 20998.77 29597.70 13898.94 20599.65 13192.91 23999.74 16196.52 25299.55 10599.64 97
UGNet98.87 9998.69 10799.40 10499.22 19498.72 17299.44 15999.68 1999.24 399.18 16699.42 21192.74 24399.96 1999.34 2299.94 1099.53 119
Wanjuan Su, Qingshan Xu, Wenbing Tao: Uncertainty-guided Multi-view Stereo Network for Depth Estimation. IEEE Transactions on Circuits and Systems for Video Technology, 2022
WTY-MVS99.06 8198.88 8599.61 6899.62 11399.16 9699.37 18999.56 4898.04 9999.53 7999.62 14796.84 10999.94 4298.85 6598.49 16899.72 72
XXY-MVS98.38 13898.09 14899.24 12899.26 18999.32 8099.56 11299.55 5597.45 16098.71 23099.83 3793.23 23299.63 20198.88 5796.32 25598.76 209
sss99.17 6099.05 6099.53 8199.62 11398.97 12699.36 19599.62 3197.83 12299.67 4499.65 13197.37 9899.95 3399.19 3399.19 12399.68 84
Test_1112_low_res98.89 9898.66 11299.57 7499.69 8998.95 13199.03 27599.47 13096.98 20599.15 16999.23 25896.77 11399.89 9598.83 6898.78 15599.86 5
1112_ss98.98 9298.77 9999.59 7099.68 9299.02 11799.25 22999.48 11497.23 17999.13 17099.58 15896.93 10899.90 8798.87 6198.78 15599.84 12
ab-mvs-re8.30 33411.06 3350.00 3460.00 3600.00 3610.00 3520.00 3620.00 3560.00 35799.58 1580.00 3640.00 3590.00 3560.00 3570.00 357
ab-mvs98.86 10298.63 11499.54 7799.64 10699.19 9399.44 15999.54 6297.77 12999.30 12499.81 5494.20 20999.93 5799.17 3698.82 15299.49 129
TR-MVS97.76 22097.41 23298.82 19899.06 22697.87 22098.87 30598.56 31796.63 22598.68 23899.22 25992.49 25999.65 19495.40 27597.79 20898.95 196
MDTV_nov1_ep13_2view95.18 30399.35 19996.84 21499.58 6595.19 15897.82 15799.46 138
MDTV_nov1_ep1398.32 13599.11 21794.44 31199.27 21998.74 29997.51 15499.40 10599.62 14794.78 18299.76 15997.59 17998.81 154
MIMVSNet195.51 29395.04 29696.92 30597.38 32295.60 29099.52 12599.50 9993.65 31096.97 29999.17 26285.28 33296.56 33788.36 33095.55 26898.60 281
MIMVSNet97.73 22797.45 22298.57 22099.45 14897.50 23599.02 27898.98 27196.11 26999.41 10199.14 26490.28 29498.74 30595.74 26698.93 14399.47 135
IterMVS-LS98.46 13298.42 12998.58 21999.59 12198.00 21399.37 18999.43 16696.94 20899.07 18399.59 15597.87 8499.03 28898.32 12495.62 26698.71 217
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet99.09 7799.03 6599.25 12599.42 15098.73 17099.45 15599.46 13998.11 8699.46 9199.77 8598.01 8299.37 22998.70 8198.92 14599.66 88
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref97.19 240
IterMVS97.83 20797.77 18698.02 27099.58 12296.27 28299.02 27899.48 11497.22 18098.71 23099.70 10992.75 24199.13 27797.46 19596.00 26098.67 242
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon99.12 6998.95 7799.65 5999.74 6799.70 3199.27 21999.57 4496.40 24699.42 9999.68 12098.75 4799.80 14397.98 14599.72 8699.44 141
MVS_111021_LR99.41 3399.33 2699.65 5999.77 4199.51 6398.94 29999.85 698.82 3599.65 5299.74 9898.51 5999.80 14398.83 6899.89 3399.64 97
DP-MVS99.16 6298.95 7799.78 3599.77 4199.53 5899.41 17599.50 9997.03 20399.04 18999.88 1497.39 9599.92 6598.66 8699.90 2599.87 4
ACMMP++97.43 231
HQP-MVS98.02 18097.90 16398.37 24199.19 19996.83 26398.98 28899.39 18098.24 7298.66 23999.40 21892.47 26099.64 19697.19 20997.58 21698.64 258
QAPM98.67 12498.30 13799.80 3199.20 19799.67 3599.77 2499.72 1194.74 28998.73 22899.90 795.78 14099.98 596.96 22699.88 3599.76 55
Vis-MVSNetpermissive99.12 6998.97 7399.56 7699.78 3699.10 10399.68 5499.66 2598.49 5699.86 799.87 1994.77 18699.84 11999.19 3399.41 11099.74 61
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet95.75 29195.16 29597.51 29599.30 17993.69 32098.88 30495.78 34785.09 33998.78 22492.65 34391.29 28799.37 22994.85 28399.85 5399.46 138
IS-MVSNet99.05 8398.87 8699.57 7499.73 7299.32 8099.75 3499.20 24798.02 10299.56 6999.86 2296.54 11999.67 19098.09 13599.13 12699.73 66
HyFIR lowres test99.11 7398.92 7999.65 5999.90 399.37 7699.02 27899.91 397.67 14199.59 6499.75 9395.90 13699.73 16999.53 699.02 13599.86 5
EPMVS97.82 21097.65 20298.35 24298.88 26595.98 28699.49 14294.71 35097.57 14899.26 14099.48 19692.46 26399.71 17997.87 15399.08 13199.35 150
PAPM_NR99.04 8498.84 9299.66 5599.74 6799.44 7099.39 18299.38 18697.70 13899.28 13299.28 25298.34 7199.85 11396.96 22699.45 10799.69 80
TAMVS99.12 6999.08 5899.24 12899.46 14498.55 18799.51 12999.46 13998.09 8999.45 9299.82 4498.34 7199.51 21198.70 8198.93 14399.67 87
PAPR98.63 12898.34 13399.51 8799.40 15899.03 11698.80 30899.36 19496.33 24899.00 19999.12 26898.46 6299.84 11995.23 27899.37 11599.66 88
RPSCF98.22 15098.62 11796.99 30299.82 2991.58 33099.72 3999.44 15896.61 22699.66 4999.89 1095.92 13599.82 13597.46 19599.10 12999.57 112
Vis-MVSNet (Re-imp)98.87 9998.72 10399.31 11299.71 8298.88 14199.80 1999.44 15897.91 11599.36 11499.78 7895.49 14799.43 22497.91 15099.11 12799.62 103
test_040296.64 26896.24 26997.85 28298.85 27296.43 27799.44 15999.26 24093.52 31296.98 29899.52 18288.52 31599.20 27292.58 31997.50 22397.93 316
MVS_111021_HR99.41 3399.32 2799.66 5599.72 7699.47 6798.95 29799.85 698.82 3599.54 7899.73 10198.51 5999.74 16198.91 5699.88 3599.77 52
CSCG99.32 4399.32 2799.32 11199.85 2398.29 20399.71 4199.66 2598.11 8699.41 10199.80 6598.37 7099.96 1998.99 5099.96 599.72 72
PatchMatch-RL98.84 11098.62 11799.52 8599.71 8299.28 8599.06 26799.77 997.74 13399.50 8499.53 17795.41 14899.84 11997.17 21299.64 10199.44 141
API-MVS99.04 8499.03 6599.06 14499.40 15899.31 8399.55 11899.56 4898.54 5399.33 12199.39 22298.76 4499.78 15496.98 22499.78 7598.07 307
Test By Simon98.75 47
TDRefinement95.42 29594.57 30097.97 27489.83 34696.11 28599.48 14798.75 29696.74 21796.68 30099.88 1488.65 31399.71 17998.37 11882.74 34298.09 306
USDC97.34 25797.20 25397.75 28999.07 22495.20 30198.51 32599.04 26697.99 10798.31 26599.86 2289.02 30699.55 20995.67 27097.36 23598.49 290
EPP-MVSNet99.13 6498.99 7099.53 8199.65 10599.06 10799.81 1599.33 21497.43 16199.60 6199.88 1497.14 10299.84 11999.13 3998.94 14299.69 80
PMMVS98.80 11498.62 11799.34 10799.27 18798.70 17398.76 31199.31 22197.34 16899.21 15899.07 27097.20 10199.82 13598.56 10198.87 14999.52 120
PAPM97.59 24297.09 25699.07 14399.06 22698.26 20598.30 33299.10 25794.88 28698.08 27499.34 24196.27 12699.64 19689.87 32598.92 14599.31 153
ACMMPcopyleft99.45 2399.32 2799.82 2699.89 899.67 3599.62 8299.69 1898.12 8499.63 5499.84 3598.73 4999.96 1998.55 10499.83 6499.81 36
Qingshan Xu, Weihang Kong, Wenbing Tao, Marc Pollefeys: Multi-Scale Geometric Consistency Guided and Planar Prior Assisted Multi-View Stereo. IEEE Transactions on Pattern Analysis and Machine Intelligence
CNLPA99.14 6398.99 7099.59 7099.58 12299.41 7399.16 24599.44 15898.45 5999.19 16499.49 19098.08 8099.89 9597.73 16899.75 8099.48 131
PatchmatchNetpermissive98.31 14298.36 13198.19 26299.16 20995.32 29999.27 21998.92 27897.37 16799.37 11099.58 15894.90 17499.70 18597.43 19899.21 12199.54 115
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS99.30 4699.17 5099.70 5199.56 12799.52 6199.58 9999.80 897.12 18899.62 5799.73 10198.58 5899.90 8798.61 9399.91 1799.68 84
F-COLMAP99.19 5799.04 6399.64 6499.78 3699.27 8799.42 17199.54 6297.29 17399.41 10199.59 15598.42 6799.93 5798.19 12899.69 9399.73 66
ANet_high77.30 32574.86 32784.62 33575.88 35577.61 34897.63 34193.15 35588.81 33564.27 35189.29 34836.51 35683.93 35575.89 34852.31 35092.33 346
PNet_i23d79.43 32477.68 32584.67 33486.18 35171.69 35496.50 34693.68 35275.17 34471.33 34991.18 34632.18 35890.62 35078.57 34674.34 34591.71 347
wuyk23d40.18 33041.29 33336.84 34286.18 35149.12 35879.73 35122.81 36027.64 35325.46 35628.45 35721.98 36048.89 35655.80 35323.56 35612.51 356
OMC-MVS99.08 7999.04 6399.20 13299.67 9398.22 20699.28 21699.52 7698.07 9399.66 4999.81 5497.79 8799.78 15497.79 16099.81 6999.60 105
MG-MVS99.13 6499.02 6899.45 9699.57 12498.63 18099.07 26399.34 20698.99 1899.61 5999.82 4497.98 8399.87 10497.00 22299.80 7199.85 8
wuykxyi23d74.42 32871.19 32984.14 33676.16 35474.29 35396.00 34792.57 35769.57 34763.84 35287.49 35121.98 36088.86 35175.56 34957.50 34989.26 350
AdaColmapbinary99.01 9098.80 9699.66 5599.56 12799.54 5599.18 24399.70 1598.18 7999.35 11799.63 14296.32 12499.90 8797.48 19299.77 7799.55 113
uanet0.02 3360.03 3370.00 3460.00 3600.00 3610.00 3520.00 3620.00 3560.00 3570.27 3580.00 3640.00 3590.00 3560.00 3570.00 357
ITE_SJBPF98.08 26699.29 18296.37 27898.92 27898.34 6698.83 22099.75 9391.09 28899.62 20295.82 26497.40 23298.25 304
DeepMVS_CXcopyleft93.34 31999.29 18282.27 34499.22 24585.15 33896.33 30399.05 27390.97 29099.73 16993.57 30697.77 20998.01 312
TinyColmap97.12 26396.89 26097.83 28499.07 22495.52 29598.57 32298.74 29997.58 14797.81 28599.79 7388.16 32099.56 20795.10 27997.21 23998.39 298
MAR-MVS98.86 10298.63 11499.54 7799.37 16399.66 3799.45 15599.54 6296.61 22699.01 19299.40 21897.09 10399.86 10797.68 17699.53 10699.10 164
Zhenyu Xu, Yiguang Liu, Xuelei Shi, Ying Wang, Yunan Zheng: MARMVS: Matching Ambiguity Reduced Multiple View Stereo for Efficient Large Scale Scene Reconstruction. CVPR 2020
LF4IMVS97.52 24697.46 22197.70 29298.98 24095.55 29299.29 21398.82 29098.07 9398.66 23999.64 13889.97 29999.61 20397.01 22196.68 24597.94 315
MSDG98.98 9298.80 9699.53 8199.76 4499.19 9398.75 31299.55 5597.25 17699.47 8999.77 8597.82 8699.87 10496.93 22999.90 2599.54 115
LS3D99.27 5199.12 5599.74 4599.18 20299.75 2499.56 11299.57 4498.45 5999.49 8799.85 2697.77 8899.94 4298.33 12299.84 5899.52 120
CLD-MVS98.16 15998.10 14698.33 24399.29 18296.82 26598.75 31299.44 15897.83 12299.13 17099.55 16792.92 23799.67 19098.32 12497.69 21098.48 291
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS84.93 31885.65 31882.75 33886.77 35063.39 35698.35 33098.92 27874.11 34583.39 34298.98 28050.85 35292.40 34984.54 33994.97 27992.46 344
Gipumacopyleft90.99 31390.15 31493.51 31898.73 28790.12 33293.98 34899.45 15079.32 34392.28 33194.91 34069.61 34497.98 32387.42 33295.67 26592.45 345
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015