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_fast98.92 199.75 2699.67 3399.99 1399.99 5299.96 2999.73 38399.52 7799.06 15100.00 1100.00 198.80 137100.00 199.95 111100.00 1100.00 1
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
PLCcopyleft98.56 299.70 3999.74 1999.58 173100.00 198.79 231100.00 199.54 7698.58 9399.96 151100.00 199.59 24100.00 1100.00 1100.00 199.94 154
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
PCF-MVS98.23 398.69 21098.37 24099.62 16399.78 16699.02 21099.23 44699.06 42896.43 31098.08 376100.00 194.72 26899.95 18298.16 31399.91 14599.90 182
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
DeepPCF-MVS98.03 498.54 23699.72 2294.98 43699.99 5284.94 477100.00 199.42 15299.98 1100.00 1100.00 198.11 162100.00 1100.00 1100.00 1100.00 1
DeepC-MVS97.84 599.00 16298.80 16899.60 16799.93 11299.03 208100.00 199.40 20598.61 9299.33 278100.00 192.23 32799.95 18299.74 15699.96 12599.83 224
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
ACMM97.17 697.37 30797.40 29697.29 37699.01 35594.64 411100.00 199.25 31598.07 13198.44 35599.98 24487.38 41099.55 29999.25 25195.19 34597.69 408
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
COLMAP_ROBcopyleft97.10 798.29 25898.17 25798.65 28599.94 11097.39 33899.30 43599.40 20595.64 34697.75 396100.00 192.69 32199.95 18298.89 27499.92 14098.62 333
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
ACMP97.00 897.19 31597.16 31297.27 37998.97 36594.58 416100.00 199.32 25897.97 13997.45 40799.98 24485.79 42699.56 29499.70 17095.24 34297.67 414
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
HY-MVS96.53 999.50 7899.35 9199.96 5299.81 14399.93 5299.64 396100.00 197.97 13999.84 20699.85 30898.94 12399.99 10799.86 12798.23 26099.95 149
TAPA-MVS96.40 1097.64 28997.37 29898.45 29899.94 11095.70 382100.00 199.40 20597.65 16899.53 257100.00 199.31 7599.66 28080.48 482100.00 1100.00 1
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
ACMH96.25 1196.77 33496.62 32897.21 38098.96 36694.43 42099.64 39699.33 25597.43 20296.55 42899.97 25683.52 44099.54 30299.07 26695.13 34997.66 415
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
IB-MVS96.24 1297.54 29996.95 31699.33 22599.67 19498.10 301100.00 199.47 8497.42 20399.26 28299.69 34098.83 13499.89 22099.43 23678.77 475100.00 1
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
ACMH+96.20 1396.49 35196.33 34397.00 38799.06 35093.80 42999.81 35799.31 26797.32 21295.89 44199.97 25682.62 44599.54 30298.34 30594.63 36097.65 420
3Dnovator95.63 1499.06 14798.76 17499.96 5298.86 37899.90 7099.98 29099.93 3598.95 4298.49 351100.00 192.91 314100.00 199.71 166100.00 1100.00 1
3Dnovator+95.58 1599.03 15398.71 18499.96 5298.99 36399.89 77100.00 199.51 8198.96 3998.32 364100.00 192.78 316100.00 199.87 126100.00 1100.00 1
LTVRE_ROB95.29 1696.32 36196.10 35196.99 38898.55 39093.88 42899.45 41899.28 29094.50 38496.46 42999.52 37784.86 43199.48 31597.26 35295.03 35297.59 430
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
OpenMVScopyleft95.20 1798.76 19898.41 22899.78 13398.89 37299.81 9999.99 25899.76 5498.02 13398.02 382100.00 191.44 335100.00 199.63 19799.97 12199.55 311
PVSNet94.91 1899.30 11499.25 10499.44 192100.00 198.32 278100.00 199.86 4398.04 132100.00 1100.00 196.10 234100.00 199.55 21499.73 172100.00 1
PVSNet_093.57 1996.41 35395.74 37098.41 30399.84 13095.22 391100.00 1100.00 198.08 13097.55 40599.78 32884.40 433100.00 1100.00 181.99 465100.00 1
OpenMVS_ROBcopyleft88.34 2091.89 42991.12 43194.19 44795.55 46587.63 47299.26 43798.03 47386.61 47290.65 47296.82 47170.14 48198.78 37286.54 47096.50 32596.15 466
MVEpermissive68.59 2167.22 46364.68 46774.84 47774.67 50362.32 50295.84 49090.87 50250.98 49758.72 49981.05 49912.20 50678.95 49761.06 49756.75 49483.24 495
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
CMPMVSbinary66.12 2290.65 43892.04 42686.46 46796.18 45766.87 49798.03 48599.38 22483.38 47885.49 48499.55 37377.59 46198.80 37194.44 41494.31 36393.72 482
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
PMVScopyleft60.66 2365.98 46565.05 46668.75 48355.06 50638.40 50888.19 49396.98 48848.30 50044.82 50188.52 49212.22 50586.49 49467.58 49483.79 45881.35 496
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
gbinet_0.2-2-1-0.0293.73 41092.69 42296.84 39794.91 47694.62 412100.00 199.28 29087.02 46998.53 34598.45 45089.72 37798.15 42996.65 37269.64 48797.74 376
0.3-1-1-0.01597.60 29397.19 30998.83 27499.13 33996.55 369100.00 199.40 20594.19 39599.83 20999.81 31899.18 9199.97 14999.70 17083.50 45999.98 127
0.4-1-1-0.197.56 29697.15 31398.79 27999.01 35596.44 372100.00 199.40 20594.11 39899.81 22499.81 31899.09 9999.97 14999.65 19183.48 46199.98 127
0.4-1-1-0.297.60 29397.18 31098.86 27299.05 35296.62 367100.00 199.40 20594.24 39099.82 21899.81 31899.09 9999.97 14999.70 17083.50 45999.98 127
wanda-best-256-51293.76 40892.74 41996.84 39795.22 46894.54 417100.00 199.22 33187.22 46398.54 34098.56 44290.48 35798.22 42495.67 39269.73 48397.75 349
usedtu_dtu_shiyan285.34 44983.22 45591.71 45588.10 49383.34 48098.75 47697.59 48576.21 48791.11 46696.80 47258.14 48894.30 48375.00 49367.24 48997.49 436
usedtu_dtu_shiyan197.34 30996.97 31498.43 30097.82 42598.91 223100.00 199.29 28294.70 37598.46 35398.89 42693.95 29098.64 38595.86 38793.75 36597.74 376
blended_shiyan893.73 41092.69 42296.84 39795.17 47294.40 421100.00 199.20 36087.05 46698.60 33598.54 44690.15 36498.39 41195.54 39969.93 48297.74 376
E5new98.63 21998.41 22899.31 23299.51 27098.21 29099.79 36399.21 35096.62 29499.67 248100.00 193.15 30999.91 20799.46 23298.26 25599.81 244
FE-blended-shiyan793.76 40892.74 41996.84 39795.22 46894.54 417100.00 199.22 33187.22 46398.54 34098.56 44290.48 35798.22 42495.67 39269.73 48397.75 349
E6new98.64 21498.41 22899.30 23699.46 29798.19 29399.79 36399.21 35096.62 29499.68 243100.00 193.24 30599.91 20799.47 22998.26 25599.81 244
blended_shiyan693.70 41292.67 42496.78 40795.17 47294.38 424100.00 199.22 33187.03 46898.54 34098.56 44290.14 36598.22 42495.62 39669.73 48397.75 349
usedtu_blend_shiyan592.75 42291.39 42796.82 40395.22 46894.40 42199.05 46998.64 46175.98 48998.54 34098.56 44290.48 35798.31 41696.31 37869.73 48397.75 349
blend_shiyan495.76 38495.40 38996.82 40395.50 46694.40 421100.00 199.22 33187.12 46598.67 33098.59 43999.09 9998.31 41696.31 37884.14 45597.75 349
E698.64 21498.41 22899.30 23699.46 29798.19 29399.79 36399.21 35096.62 29499.68 243100.00 193.24 30599.91 20799.47 22998.26 25599.81 244
E598.63 21998.41 22899.31 23299.51 27098.21 29099.79 36399.21 35096.62 29499.67 248100.00 193.15 30999.91 20799.46 23298.26 25599.81 244
FE-MVSNET397.34 30996.97 31498.43 30097.82 42598.91 223100.00 199.29 28294.70 37598.46 35398.89 42693.95 29098.64 38595.88 38593.75 36597.74 376
E498.68 21298.46 22299.33 22599.51 27098.27 28499.96 30699.21 35096.66 28699.68 243100.00 193.38 30099.91 20799.49 22698.27 25399.81 244
E3new98.95 17698.80 16899.41 19999.57 23898.50 257100.00 199.22 33196.84 25499.89 199100.00 195.70 24299.93 19999.57 21298.39 22899.82 230
FE-MVSNET291.15 43590.00 44194.58 44090.74 48892.52 44699.56 40698.87 45190.82 44488.96 47595.40 47876.26 46895.56 47887.84 46681.59 46895.66 475
fmvsm_s_conf0.5_n_1198.92 18098.63 19599.80 12399.85 12899.86 89100.00 199.24 32198.91 55100.00 1100.00 189.69 37899.99 107100.00 199.98 11799.54 312
E298.77 19598.57 20599.37 21199.53 25198.38 26899.98 29099.22 33196.77 26299.75 232100.00 194.03 28699.91 20799.53 22098.35 23699.82 230
MED-MVS test99.99 13100.00 199.98 18100.00 199.95 1999.10 1099.99 127100.00 1100.00 1100.00 1100.00 1100.00 1
MED-MVS99.88 299.84 399.99 13100.00 199.98 18100.00 199.95 1999.05 1799.99 127100.00 199.58 27100.00 1100.00 1100.00 1100.00 1
E398.77 19598.57 20599.36 21399.47 29098.36 27299.98 29099.22 33196.76 26399.75 232100.00 194.10 28499.91 20799.53 22098.35 23699.82 230
TestfortrainingZip a99.86 499.81 699.99 13100.00 199.98 18100.00 199.95 1999.10 1099.99 127100.00 199.58 27100.00 199.68 180100.00 1100.00 1
TestfortrainingZip100.00 199.99 52100.00 1100.00 199.95 1999.03 25100.00 1100.00 199.59 24100.00 1100.00 1100.00 1
fmvsm_s_conf0.5_n_1099.08 14398.78 17099.97 4099.84 13099.92 59100.00 199.28 29098.93 49100.00 1100.00 191.07 34299.99 107100.00 199.95 127100.00 1
viewdifsd2359ckpt0798.72 20298.52 21399.34 21799.47 29098.28 28299.99 25899.20 36096.98 23999.60 253100.00 193.45 29999.93 19999.58 20998.36 23499.82 230
viewdifsd2359ckpt0998.78 19498.60 20199.31 23299.53 25198.37 269100.00 199.20 36096.85 25299.32 279100.00 194.68 26999.74 27099.46 23298.36 23499.81 244
viewdifsd2359ckpt1398.72 20298.52 21399.34 21799.55 24598.46 25999.99 25899.22 33196.50 30799.05 302100.00 194.54 27399.73 27399.46 23298.35 23699.81 244
viewcassd2359sk1198.90 18498.73 17899.40 20499.57 23898.47 25899.99 25899.22 33196.79 25999.82 218100.00 195.24 25099.91 20799.54 21798.38 23199.82 230
viewdifsd2359ckpt1197.98 27497.89 27498.26 31699.47 29094.98 39699.99 25899.22 33196.74 26999.24 283100.00 190.14 36599.90 21899.49 22696.73 31999.90 182
viewmacassd2359aftdt98.57 23098.31 24599.33 22599.49 28298.31 28099.89 34299.21 35096.87 25199.10 295100.00 192.48 32599.88 22899.50 22498.28 25099.81 244
viewmsd2359difaftdt97.98 27497.89 27498.27 31399.47 29094.99 39599.99 25899.22 33196.74 26999.24 283100.00 190.14 36599.90 21899.49 22696.73 31999.90 182
diffmvs_AUTHOR98.92 18098.73 17899.49 18599.48 28598.81 22999.94 32399.14 39297.24 21899.96 151100.00 194.85 26299.87 23099.67 18498.31 24699.79 276
FE-MVSNET89.50 44188.33 44793.00 45388.89 49190.24 46199.96 30696.86 49088.23 45888.46 47695.47 47777.03 46593.37 48878.54 48681.56 46995.39 477
fmvsm_l_conf0.5_n_999.35 10199.15 12399.95 6199.83 13499.84 95100.00 199.30 27398.92 52100.00 1100.00 194.32 281100.00 1100.00 199.93 137100.00 1
mamba_040898.63 21998.40 23399.34 21799.53 25198.52 25399.24 43999.16 38096.43 31098.95 30799.98 24494.47 27599.76 26599.21 25798.62 21299.75 284
icg_test_0407_298.30 25598.45 22397.85 35699.38 31895.36 38599.99 25899.18 37096.72 27599.58 254100.00 195.17 25598.45 40797.84 32798.15 26799.74 291
SSM_0407298.59 22698.40 23399.15 25199.53 25198.52 25399.24 43999.16 38096.43 31098.95 30799.98 24494.47 27599.19 34199.21 25798.62 21299.75 284
SSM_040798.72 20298.52 21399.33 22599.53 25198.52 25399.88 34599.15 38596.53 30198.95 307100.00 194.38 27899.72 27599.64 19298.62 21299.75 284
viewmambaseed2359dif98.57 23098.34 24499.28 24199.46 29798.23 287100.00 199.16 38096.26 32599.11 294100.00 193.12 31299.79 25599.61 20298.33 24399.80 270
IMVS_040798.36 25398.42 22698.19 32399.38 31895.36 38599.73 38399.18 37096.72 27599.58 254100.00 195.17 25599.47 31797.84 32798.15 26799.74 291
viewmanbaseed2359cas98.86 18898.68 19099.40 20499.51 27098.51 25699.98 29099.22 33197.05 23499.72 239100.00 194.77 26599.89 22099.58 20998.31 24699.81 244
IMVS_040497.87 27997.89 27497.81 35899.38 31895.36 38599.84 35199.18 37096.72 27598.41 356100.00 191.43 33698.32 41597.84 32798.15 26799.74 291
SSM_040498.76 19898.56 20899.35 21599.53 25198.65 24299.80 36299.15 38596.53 30199.47 264100.00 194.38 27899.76 26599.64 19298.59 21599.64 309
IMVS_040398.37 25198.39 23698.29 31199.38 31895.36 38599.97 29999.18 37096.72 27599.68 243100.00 194.61 27199.77 26197.84 32798.15 26799.74 291
SD_040397.92 27898.43 22596.39 41499.68 18689.74 46599.92 33199.34 25296.75 26699.39 27499.93 29193.54 29899.51 31099.11 26398.21 26199.92 167
fmvsm_s_conf0.5_n_999.04 15098.78 17099.81 11799.86 12699.44 164100.00 199.32 25898.94 45100.00 1100.00 191.00 34599.99 107100.00 199.94 133100.00 1
ME-MVS99.87 399.83 499.99 1399.99 5299.98 18100.00 199.95 1999.05 17100.00 1100.00 199.50 44100.00 1100.00 1100.00 1100.00 1
NormalMVS99.47 8499.48 7699.43 19599.99 5298.55 24899.94 32399.28 29098.39 103100.00 1100.00 198.44 15399.98 14099.36 24099.92 14099.75 284
lecture99.64 5499.53 6599.98 2899.99 5299.93 52100.00 199.47 8498.53 94100.00 1100.00 197.88 171100.00 199.98 9199.92 140100.00 1
SymmetryMVS99.30 11499.25 10499.45 19099.79 16198.55 24899.94 32399.47 8498.39 103100.00 1100.00 198.44 15399.98 14099.36 24097.83 29199.83 224
Elysia98.12 26797.72 28599.34 21799.30 32898.96 22099.95 31599.28 29096.64 28999.75 23299.99 23688.71 39499.81 25095.99 38399.84 16299.26 321
StellarMVS98.12 26797.72 28599.34 21799.30 32898.96 22099.95 31599.28 29096.64 28999.75 23299.99 23688.71 39499.81 25095.99 38399.84 16299.26 321
KinetiMVS98.61 22398.26 24899.65 15999.46 29799.24 18899.96 30699.44 12497.54 18599.99 12799.99 23690.83 35099.95 18297.18 35399.92 14099.75 284
LuminaMVS99.07 14698.92 15699.50 18198.87 37699.12 20199.92 33199.22 33197.45 19999.82 21899.98 24496.29 23299.85 23899.71 16699.05 20299.52 314
VortexMVS98.23 26398.11 26098.59 29099.56 24499.37 17299.95 31599.03 43696.47 30898.69 32799.55 37395.91 23598.66 38299.01 26994.80 35797.73 387
AstraMVS99.03 15399.01 13899.09 25499.46 29797.66 329100.00 199.23 32697.83 15099.95 182100.00 195.52 24699.86 23199.74 15699.39 19299.74 291
guyue99.21 13199.07 13299.62 16399.55 24599.29 179100.00 199.32 25897.66 16699.96 151100.00 195.84 23899.84 24299.63 19799.67 17899.75 284
sc_t192.52 42491.34 42896.09 42297.80 42789.86 46498.61 47999.12 40477.73 48396.09 43699.79 32768.64 48298.94 35896.94 35987.31 44199.46 318
tt0320-xc91.69 43290.50 43695.26 43098.04 41690.12 46398.60 48098.70 45976.63 48694.66 45099.52 37768.57 48397.99 44694.61 41185.18 45197.66 415
tt032092.36 42691.28 42995.58 42898.30 40290.65 45898.69 47799.14 39276.73 48496.07 43799.50 38072.28 47798.39 41193.29 42987.56 43997.70 403
fmvsm_s_conf0.5_n_899.34 10599.14 12599.91 8399.83 13499.74 111100.00 199.38 22498.94 45100.00 1100.00 194.25 28399.99 107100.00 199.91 145100.00 1
fmvsm_s_conf0.5_n_798.98 17098.85 16399.37 21199.67 19498.34 275100.00 199.31 26798.97 37100.00 1100.00 191.70 33399.97 14999.99 7699.97 12199.80 270
fmvsm_s_conf0.5_n_699.30 11499.12 12899.84 10999.24 33499.56 137100.00 199.31 26798.90 59100.00 1100.00 194.75 26799.97 14999.98 9199.88 151100.00 1
fmvsm_s_conf0.5_n_599.00 16298.70 18699.88 9599.81 14399.64 127100.00 199.26 31198.78 8399.97 144100.00 190.65 35299.99 107100.00 199.89 14899.99 124
fmvsm_s_conf0.5_n_498.98 17098.74 17799.68 15399.81 14399.50 151100.00 199.26 31198.91 55100.00 1100.00 190.87 34999.97 14999.99 7699.81 16799.57 310
SSC-MVS3.295.32 39194.97 39796.37 41698.29 40492.75 441100.00 199.30 27395.46 35898.36 35999.42 38678.92 45898.63 38793.28 43091.72 39897.72 394
testing3-299.45 8699.31 9499.86 10099.70 17899.73 113100.00 199.47 8497.46 19799.97 14499.97 25699.48 51100.00 199.78 14897.99 27799.85 219
myMVS_eth3d2899.41 9199.28 9699.80 12399.69 18199.53 144100.00 199.43 13397.12 22899.98 13899.97 25699.41 65100.00 199.81 14198.07 27499.88 203
UWE-MVS-2899.29 11799.23 11199.48 18699.73 17498.86 226100.00 199.43 13396.97 24199.99 12799.83 31199.43 5999.77 26199.35 24398.31 24699.80 270
fmvsm_l_conf0.5_n_399.38 9699.20 11799.92 8299.80 15699.78 103100.00 199.35 24598.94 45100.00 1100.00 194.77 26599.99 10799.99 7699.92 140100.00 1
fmvsm_s_conf0.5_n_398.99 16698.69 18899.89 9099.70 17899.69 122100.00 199.39 22198.93 49100.00 1100.00 190.20 36399.99 107100.00 199.95 127100.00 1
fmvsm_s_conf0.5_n_298.90 18498.57 20599.90 8799.79 16199.78 103100.00 199.25 31598.97 37100.00 1100.00 189.22 38699.99 107100.00 199.88 15199.92 167
fmvsm_s_conf0.1_n_298.95 17698.69 18899.73 14399.61 22299.74 111100.00 199.23 32698.95 4299.97 144100.00 190.92 34899.97 149100.00 199.58 18699.47 317
GDP-MVS99.39 9399.26 10299.77 13699.53 25199.55 139100.00 199.11 40697.14 22499.96 151100.00 199.83 599.89 22098.47 29999.26 19499.87 214
BP-MVS199.56 7199.48 7699.79 12899.48 28599.61 130100.00 199.32 25897.34 20999.94 185100.00 199.74 1399.89 22099.75 15599.72 17399.87 214
reproduce_monomvs98.61 22398.54 21098.82 27599.97 9799.28 181100.00 199.33 25598.51 9797.87 39099.24 39799.98 399.45 32399.02 26892.93 37797.74 376
mmtdpeth94.58 39894.18 40095.81 42698.82 38391.09 45699.99 25898.61 46296.38 317100.00 197.23 46876.52 46699.85 23899.82 13980.22 47196.48 461
reproduce_model99.76 2199.69 2599.98 2899.96 10399.93 52100.00 199.42 15298.81 76100.00 1100.00 198.98 115100.00 1100.00 1100.00 1100.00 1
reproduce-ours99.76 2199.69 2599.98 2899.96 10399.94 46100.00 199.42 15298.82 72100.00 1100.00 198.99 112100.00 1100.00 1100.00 1100.00 1
our_new_method99.76 2199.69 2599.98 2899.96 10399.94 46100.00 199.42 15298.82 72100.00 1100.00 198.99 112100.00 1100.00 1100.00 1100.00 1
mmdepth0.01 4710.02 4740.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.14 5040.00 5070.00 5040.00 5020.00 5020.00 500
monomultidepth0.01 4710.02 4740.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.14 5040.00 5070.00 5040.00 5020.00 5020.00 500
mvs5depth93.81 40793.00 41496.23 42094.25 47893.33 43597.43 48898.07 47293.47 41494.15 45699.58 36777.52 46298.97 35593.64 42488.92 42896.39 464
MVStest194.27 40193.30 41097.19 38198.83 38197.18 35099.93 32998.79 45686.80 47084.88 48799.04 41094.32 28198.25 42290.55 45086.57 44896.12 468
ttmdpeth96.24 36595.88 36197.32 37497.80 42796.61 36899.95 31598.77 45797.80 15493.42 45999.28 39586.42 41999.01 34997.63 33791.84 39596.33 465
WBMVS98.19 26598.10 26398.47 29699.63 21399.03 208100.00 199.32 25895.46 35898.39 35899.40 38899.69 1798.61 38998.64 28992.39 38597.76 338
dongtai98.29 25898.25 24998.42 30299.58 23495.86 379100.00 199.44 12493.46 41599.69 24299.97 25697.53 19099.51 31096.28 38098.27 25399.89 190
kuosan98.55 23398.53 21298.62 28799.66 20396.16 374100.00 199.44 12493.93 40299.81 22499.98 24497.58 18599.81 25098.08 31598.28 25099.89 190
MVSMamba_PlusPlus99.39 9399.25 10499.80 12399.68 18699.59 13399.99 25899.30 27396.66 28699.96 15199.97 25697.89 17099.92 20599.76 151100.00 199.90 182
MGCFI-Net99.01 16198.70 18699.93 7899.74 17399.94 46100.00 199.29 28297.60 180100.00 1100.00 195.10 25799.96 16999.74 15696.85 31899.91 171
testing9199.18 13499.10 12999.41 19999.60 22598.43 260100.00 199.43 13396.76 26399.82 21899.92 29299.05 10699.98 14099.62 19997.67 30299.81 244
testing1199.26 12299.19 11899.46 18899.64 21198.61 244100.00 199.43 13396.94 24399.92 19199.94 28699.43 5999.97 14999.67 18497.79 29699.82 230
testing9999.18 13499.10 12999.41 19999.60 22598.43 260100.00 199.43 13396.76 26399.84 20699.92 29299.06 10499.98 14099.62 19997.67 30299.81 244
UBG99.36 10099.27 9899.63 16199.63 21399.01 212100.00 199.43 13396.99 238100.00 199.92 29299.69 1799.99 10799.74 15698.06 27599.88 203
UWE-MVS99.18 13499.06 13399.51 17899.67 19498.80 230100.00 199.43 13396.80 25899.93 19099.86 30399.79 899.94 19597.78 33298.33 24399.80 270
ETVMVS99.16 13798.98 14499.69 15099.67 19499.56 137100.00 199.45 11096.36 31999.98 13899.95 28098.65 14399.64 28199.11 26397.63 30599.88 203
sasdasda99.03 15398.73 17899.94 7499.75 17199.95 37100.00 199.30 27397.64 170100.00 1100.00 195.22 25199.97 14999.76 15196.90 31699.91 171
testing22299.14 13998.94 15299.73 14399.67 19499.51 149100.00 199.43 13396.90 24999.99 12799.90 29798.55 14999.86 23198.85 27697.18 30999.81 244
WB-MVSnew97.02 32797.24 30696.37 41699.44 30597.36 340100.00 199.43 13396.12 33399.35 27799.89 29893.60 29698.42 40988.91 46598.39 22893.33 484
fmvsm_l_conf0.5_n_a99.63 5899.55 6299.86 10099.83 13499.58 135100.00 199.36 23498.98 35100.00 1100.00 197.85 17399.99 107100.00 199.94 133100.00 1
fmvsm_l_conf0.5_n99.63 5899.56 6099.86 10099.81 14399.59 133100.00 199.36 23498.98 35100.00 1100.00 197.92 16899.99 107100.00 199.95 127100.00 1
fmvsm_s_conf0.1_n_a98.71 20698.36 24299.78 13399.09 34499.42 166100.00 199.26 31197.42 203100.00 1100.00 189.78 37499.96 16999.82 13999.85 16099.97 137
fmvsm_s_conf0.1_n98.77 19598.42 22699.82 11299.47 29099.52 148100.00 199.27 30597.53 188100.00 1100.00 189.73 37699.96 16999.84 13399.93 13799.97 137
fmvsm_s_conf0.5_n_a99.32 11099.15 12399.81 11799.80 15699.47 160100.00 199.35 24598.22 116100.00 1100.00 195.21 25399.99 10799.96 10599.86 15799.98 127
fmvsm_s_conf0.5_n99.21 13199.01 13899.83 11099.84 13099.53 144100.00 199.38 22498.29 115100.00 1100.00 193.62 29599.99 10799.99 7699.93 13799.98 127
MM99.63 5899.52 6899.94 7499.99 5299.82 98100.00 199.97 1799.11 8100.00 1100.00 196.65 224100.00 1100.00 199.97 121100.00 1
WAC-MVS97.98 31095.74 389
Syy-MVS96.17 37096.57 33095.00 43499.50 27887.37 473100.00 199.57 7396.23 32698.07 377100.00 192.41 32697.81 45285.34 47297.96 28099.82 230
test_fmvsmconf0.1_n99.25 12699.05 13499.82 11298.92 36999.55 139100.00 199.23 32698.91 5599.75 23299.97 25694.79 26499.94 19599.94 11399.99 10799.97 137
test_fmvsmconf0.01_n98.60 22598.24 25299.67 15496.90 45299.21 19299.99 25899.04 43398.80 7799.57 25699.96 27390.12 36899.91 20799.89 12199.89 14899.90 182
myMVS_eth3d98.52 23898.51 21898.53 29399.50 27897.98 310100.00 199.57 7396.23 32698.07 377100.00 199.09 9997.81 45296.17 38197.96 28099.82 230
testing398.44 24398.37 24098.65 28599.51 27098.32 278100.00 199.62 7196.43 31097.93 38699.99 23699.11 9797.81 45294.88 40997.80 29499.82 230
SSC-MVS87.61 44689.47 44382.04 47490.63 48968.77 49499.99 25898.66 46090.34 44986.70 48298.08 45992.72 32084.12 49659.41 49888.71 43293.22 487
test_fmvsmconf_n99.56 7199.46 7999.86 10099.68 18699.58 135100.00 199.31 26798.92 5299.88 202100.00 197.35 20099.99 10799.98 9199.99 107100.00 1
WB-MVS88.24 44590.09 43982.68 47391.56 48569.51 493100.00 198.73 45890.72 44687.29 48198.12 45892.87 31585.01 49562.19 49589.34 42493.54 483
test_fmvsmvis_n_192099.46 8599.37 8699.73 14398.88 37399.18 196100.00 199.26 31198.85 6699.79 226100.00 197.70 181100.00 199.98 9199.86 157100.00 1
dmvs_re97.54 29997.88 27796.54 41199.55 24590.35 46099.86 34899.46 10297.00 23799.41 272100.00 190.78 35199.30 33599.60 20495.24 34299.96 143
SDMVSNet98.49 24198.08 26499.73 14399.82 13799.53 14499.99 25899.45 11097.62 17399.38 27599.86 30390.06 37199.88 22899.92 11696.61 32399.79 276
dmvs_testset93.27 41795.48 38486.65 46698.74 38468.42 49599.92 33198.91 44896.19 33193.28 460100.00 191.06 34491.67 49189.64 45891.54 40099.86 218
sd_testset97.81 28397.48 29298.79 27999.82 13796.80 36199.32 43199.45 11097.62 17399.38 27599.86 30385.56 42899.77 26199.72 16296.61 32399.79 276
test_fmvsm_n_192099.55 7399.49 7399.73 14399.85 12899.19 194100.00 199.41 20198.87 64100.00 1100.00 197.34 201100.00 199.98 9199.90 147100.00 1
test_cas_vis1_n_192098.63 21998.25 24999.77 13699.69 18199.32 176100.00 199.31 26798.84 6899.96 151100.00 187.42 40999.99 10799.14 25999.86 157100.00 1
test_vis1_n_192097.77 28597.24 30699.34 21799.79 16198.04 307100.00 199.25 31598.88 61100.00 1100.00 177.52 462100.00 199.88 12399.85 160100.00 1
test_vis1_n96.69 34095.81 36499.32 23099.14 33897.98 31099.97 29998.98 44398.45 100100.00 1100.00 166.44 48599.99 10799.78 14899.57 188100.00 1
test_fmvs1_n97.43 30496.86 31999.15 25199.68 18697.48 33599.99 25898.98 44398.82 72100.00 1100.00 174.85 47199.96 16999.67 18499.70 175100.00 1
mvsany_test199.57 7099.48 7699.85 10499.86 12699.54 142100.00 199.36 23498.94 45100.00 1100.00 197.97 165100.00 199.88 12399.28 193100.00 1
APD_test193.07 42094.14 40189.85 46099.18 33672.49 48899.76 37598.90 45092.86 43096.35 43099.94 28675.56 46999.91 20786.73 46997.98 27897.15 449
test_vis1_rt93.10 41992.93 41593.58 45099.63 21385.07 47699.99 25893.71 49897.49 19490.96 46897.10 46960.40 48799.95 18299.24 25397.90 28595.72 472
test_vis3_rt79.61 45478.19 45983.86 47088.68 49269.56 49299.81 35782.19 50686.78 47168.57 49484.51 49725.06 50298.26 42189.18 46378.94 47483.75 494
test_fmvs295.17 39695.23 39195.01 43398.95 36888.99 46999.99 25897.77 48097.79 15598.58 33799.70 33773.36 47399.34 33395.88 38595.03 35296.70 458
test_fmvs198.37 25198.04 26899.34 21799.84 13098.07 303100.00 199.00 44098.85 66100.00 1100.00 185.11 43099.96 16999.69 17999.88 151100.00 1
test_fmvs387.19 44787.02 45087.71 46492.69 48076.64 48599.96 30697.27 48693.55 41190.82 47094.03 48538.00 49892.19 49093.49 42783.35 46394.32 479
mvsany_test389.36 44388.96 44690.56 45891.95 48178.97 48399.74 37896.59 49496.84 25489.25 47396.07 47452.59 49097.11 46195.17 40582.44 46495.58 476
testf184.40 45184.79 45283.23 47195.71 46158.71 50498.79 47497.75 48181.58 47984.94 48598.07 46045.33 49497.73 45677.09 49083.85 45693.24 485
APD_test284.40 45184.79 45283.23 47195.71 46158.71 50498.79 47497.75 48181.58 47984.94 48598.07 46045.33 49497.73 45677.09 49083.85 45693.24 485
test_f86.87 44886.06 45189.28 46191.45 48676.37 48699.87 34797.11 48791.10 44188.46 47693.05 48738.31 49796.66 46691.77 44183.46 46294.82 478
FE-MVS99.16 13798.99 14399.66 15799.65 20599.18 19699.58 40499.43 13395.24 36399.91 19499.59 36599.37 6999.97 14998.31 30699.81 16799.83 224
FA-MVS(test-final)99.00 16298.75 17599.73 14399.63 21399.43 16599.83 35399.43 13395.84 34399.52 25899.37 39097.84 17599.96 16997.63 33799.68 17699.79 276
balanced_conf0399.43 8999.28 9699.85 10499.68 18699.68 12399.97 29999.28 29097.03 23599.96 15199.97 25697.90 16999.93 19999.77 150100.00 199.94 154
MonoMVSNet98.55 23398.64 19498.26 31698.21 40995.76 38199.94 32399.16 38096.23 32699.47 26499.24 39796.75 22199.22 33999.61 20299.17 19599.81 244
patch_mono-299.04 15099.79 996.81 40599.92 11590.47 459100.00 199.41 20198.95 42100.00 1100.00 199.78 9100.00 1100.00 1100.00 199.95 149
EGC-MVSNET79.46 45574.04 46395.72 42796.00 45992.73 44299.09 46499.04 4335.08 50216.72 50298.71 43473.03 47498.74 37882.05 47996.64 32295.69 473
test250699.48 8299.38 8399.75 13999.89 12199.51 14999.45 418100.00 198.38 10599.83 209100.00 198.86 13099.81 25099.25 25198.78 20799.94 154
test111198.42 24698.12 25999.29 23899.88 12398.15 29699.46 416100.00 198.36 10999.42 267100.00 187.91 40299.79 25599.31 24898.78 20799.94 154
ECVR-MVScopyleft98.43 24498.14 25899.32 23099.89 12198.21 29099.46 416100.00 198.38 10599.47 264100.00 187.91 40299.80 25499.35 24398.78 20799.94 154
test_blank0.07 4700.09 4730.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.79 5030.00 5070.00 5040.00 5020.00 5020.00 500
tt080596.52 34696.23 34697.40 36899.30 32893.55 43199.32 43199.45 11096.75 26697.88 38999.99 23679.99 45499.59 28597.39 34895.98 32699.06 328
DVP-MVS++99.81 1499.75 17100.00 1100.00 199.99 6100.00 199.42 15298.79 80100.00 1100.00 199.54 33100.00 1100.00 1100.00 1100.00 1
FOURS1100.00 199.97 26100.00 199.42 15298.52 96100.00 1
MSC_two_6792asdad100.00 1100.00 1100.00 199.42 152100.00 1100.00 1100.00 1100.00 1
PC_three_145298.80 77100.00 1100.00 199.54 33100.00 1100.00 1100.00 1100.00 1
No_MVS100.00 1100.00 1100.00 199.42 152100.00 1100.00 1100.00 1100.00 1
test_one_0601100.00 199.99 699.42 15298.72 85100.00 1100.00 199.60 21
eth-test20.00 508
eth-test0.00 508
GeoE98.06 27097.65 28999.29 23899.47 29098.41 262100.00 199.19 36394.85 37098.88 314100.00 191.21 33899.59 28597.02 35798.19 26499.88 203
test_method91.04 43791.10 43290.85 45798.34 39777.63 484100.00 198.93 44776.69 48596.25 43398.52 44870.44 47997.98 44789.02 46491.74 39696.92 454
Anonymous2024052193.29 41692.76 41894.90 43895.64 46491.27 45499.97 29998.82 45487.04 46794.71 44898.19 45783.86 43996.80 46384.04 47592.56 38496.64 459
h-mvs3397.03 32596.53 33198.51 29499.79 16195.90 37899.45 41899.45 11098.21 117100.00 199.78 32897.49 19299.99 10799.72 16274.92 47799.65 308
hse-mvs296.79 33396.38 33998.04 34499.68 18695.54 38499.81 35799.42 15298.21 117100.00 199.80 32497.49 19299.46 32299.72 16273.27 48099.12 326
CL-MVSNet_self_test91.07 43690.35 43893.24 45193.27 47989.16 46899.55 40899.25 31592.34 43395.23 44497.05 47088.86 39393.59 48680.67 48166.95 49096.96 453
KD-MVS_2432*160094.15 40393.08 41297.35 37299.53 25197.83 32399.63 39899.19 36392.88 42896.29 43197.68 46498.84 13296.70 46489.73 45663.92 49197.53 434
KD-MVS_self_test91.16 43490.09 43994.35 44394.44 47791.27 45499.74 37899.08 41590.82 44494.53 45294.91 48386.11 42194.78 48182.67 47768.52 48896.99 452
AUN-MVS96.26 36495.67 37698.06 33899.68 18695.60 38399.82 35699.42 15296.78 26199.88 20299.80 32494.84 26399.47 31797.48 34373.29 47999.12 326
ZD-MVS100.00 199.98 1899.80 4897.31 214100.00 1100.00 199.32 7399.99 107100.00 1100.00 1
SR-MVS-dyc-post99.63 5899.52 6899.97 4099.99 5299.91 63100.00 199.42 15297.62 173100.00 1100.00 198.65 14399.99 10799.99 76100.00 1100.00 1
RE-MVS-def99.55 6299.99 5299.91 63100.00 199.42 15297.62 173100.00 1100.00 198.94 12399.99 76100.00 1100.00 1
SED-MVS99.83 1099.77 12100.00 1100.00 199.99 6100.00 199.42 15299.03 25100.00 1100.00 199.50 44100.00 1100.00 1100.00 1100.00 1
IU-MVS100.00 199.99 699.42 15299.12 7100.00 1100.00 1100.00 1100.00 1
OPU-MVS100.00 1100.00 1100.00 1100.00 1100.00 199.54 33100.00 1100.00 1100.00 1100.00 1
test_241102_TWO99.42 15299.03 25100.00 1100.00 199.56 30100.00 1100.00 1100.00 1100.00 1
test_241102_ONE100.00 199.99 699.42 15299.03 25100.00 1100.00 199.50 44100.00 1
SF-MVS99.66 5199.57 5599.95 6199.99 5299.85 93100.00 199.42 15297.67 165100.00 1100.00 199.05 10699.99 107100.00 1100.00 1100.00 1
cl2298.23 26398.11 26098.58 29299.82 13799.01 212100.00 199.28 29096.92 24698.33 36399.21 40098.09 16498.97 35598.72 28492.61 38097.76 338
miper_ehance_all_eth97.81 28397.66 28898.23 31999.49 28298.37 26999.99 25899.11 40694.78 37198.25 37199.21 40098.18 16098.57 39797.35 35092.61 38097.76 338
miper_enhance_ethall98.33 25498.27 24798.51 29499.66 20399.04 207100.00 199.22 33197.53 18898.51 34999.38 38999.49 4798.75 37798.02 31992.61 38097.76 338
ZNCC-MVS99.71 3699.62 4799.97 4099.99 5299.90 70100.00 199.79 5097.97 13999.97 144100.00 198.97 117100.00 199.94 113100.00 1100.00 1
dcpmvs_298.87 18799.53 6596.90 39399.87 12590.88 45799.94 32399.07 42098.20 119100.00 1100.00 198.69 14299.86 231100.00 1100.00 199.95 149
cl____97.54 29997.32 30098.18 32499.47 29098.14 298100.00 199.10 40994.16 39797.60 40399.63 35797.52 19198.65 38496.47 37391.97 39397.76 338
DIV-MVS_self_test97.52 30297.35 29998.05 34299.46 29798.11 299100.00 199.10 40994.21 39397.62 40199.63 35797.65 18398.29 41996.47 37391.98 39297.76 338
eth_miper_zixun_eth97.47 30397.28 30298.06 33899.41 30997.94 31599.62 40099.08 41594.46 38698.19 37499.56 37296.91 21698.50 40296.78 36891.49 40297.74 376
9.1499.57 5599.99 52100.00 199.42 15297.54 185100.00 1100.00 199.15 9599.99 107100.00 1100.00 1
uanet_test0.01 4710.02 4740.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.14 5040.00 5070.00 5040.00 5020.00 5020.00 500
DCPMVS0.01 4710.02 4740.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.14 5040.00 5070.00 5040.00 5020.00 5020.00 500
save fliter99.99 5299.93 52100.00 199.42 15298.93 49
ET-MVSNet_ETH3D96.41 35395.48 38499.20 24999.81 14399.75 108100.00 199.02 43797.30 21678.33 490100.00 197.73 17997.94 44999.70 17087.41 44099.92 167
UniMVSNet_ETH3D95.28 39394.41 39997.89 35498.91 37095.14 39299.13 45999.35 24592.11 43497.17 41499.66 34770.28 48099.36 33097.88 32595.18 34699.16 324
EIA-MVS99.26 12299.19 11899.45 19099.63 21398.75 233100.00 199.27 30596.93 24499.95 182100.00 197.47 19499.79 25599.74 15699.72 17399.82 230
miper_refine_blended94.15 40393.08 41297.35 37299.53 25197.83 32399.63 39899.19 36392.88 42896.29 43197.68 46498.84 13296.70 46489.73 45663.92 49197.53 434
miper_lstm_enhance97.40 30697.28 30297.75 36099.48 28597.52 333100.00 199.07 42094.08 39998.01 38399.61 36397.38 19997.98 44796.44 37691.47 40497.76 338
ETV-MVS99.34 10599.24 10899.64 16099.58 23499.33 175100.00 199.25 31597.57 18399.96 151100.00 197.44 19799.79 25599.70 17099.65 18199.81 244
CS-MVS99.33 10899.27 9899.50 18199.99 5299.00 215100.00 199.13 39897.26 21799.96 151100.00 197.79 17899.64 28199.64 19299.67 17899.87 214
D2MVS97.63 29297.83 27997.05 38498.83 38194.60 413100.00 199.82 4596.89 25098.28 36799.03 41394.05 28599.47 31798.58 29694.97 35597.09 450
DVP-MVScopyleft99.83 1099.78 10100.00 1100.00 199.99 6100.00 199.42 15299.04 20100.00 1100.00 199.53 36100.00 1100.00 1100.00 1100.00 1
Zhenlong Yuan, Jinguo Luo, Fei Shen, Zhaoxin Li, Cong Liu, Tianlu Mao, Zhaoqi Wang: DVP-MVS: Synergize Depth-Edge and Visibility Prior for Multi-View Stereo. AAAI2025
test_0728_THIRD98.79 80100.00 1100.00 199.61 20100.00 1100.00 1100.00 1100.00 1
test_0728_SECOND100.00 199.99 5299.99 6100.00 199.42 152100.00 1100.00 1100.00 1100.00 1
test0726100.00 199.99 6100.00 199.42 15299.04 20100.00 1100.00 199.53 36
SR-MVS99.68 4699.58 5299.98 28100.00 199.95 37100.00 199.64 6997.59 181100.00 1100.00 198.99 11299.99 107100.00 1100.00 1100.00 1
DPM-MVS99.63 5899.51 70100.00 199.90 119100.00 1100.00 199.43 13399.00 32100.00 1100.00 199.58 27100.00 197.64 336100.00 1100.00 1
GST-MVS99.64 5499.53 6599.95 61100.00 199.86 89100.00 199.79 5097.72 16099.95 182100.00 198.39 156100.00 199.96 10599.99 107100.00 1
test_yl99.51 7599.37 8699.95 6199.82 13799.90 70100.00 199.47 8497.48 195100.00 1100.00 199.80 6100.00 199.98 9197.75 29899.94 154
thisisatest053099.37 9999.27 9899.69 15099.59 22999.41 167100.00 199.46 10296.46 30999.90 196100.00 199.44 5599.85 23898.97 27099.58 18699.80 270
Anonymous2024052996.93 33096.22 34799.05 25799.79 16197.30 34599.16 45599.47 8488.51 45798.69 327100.00 183.50 441100.00 199.83 13497.02 31399.83 224
Anonymous20240521197.87 27997.53 29198.90 26999.81 14396.70 36499.35 42999.46 10292.98 42698.83 32199.99 23690.63 354100.00 199.70 17097.03 312100.00 1
DCV-MVSNet99.51 7599.37 8699.95 6199.82 13799.90 70100.00 199.47 8497.48 195100.00 1100.00 199.80 6100.00 199.98 9197.75 29899.94 154
tttt051799.34 10599.23 11199.67 15499.57 23899.38 169100.00 199.46 10296.33 32299.89 199100.00 199.44 5599.84 24298.93 27299.46 19099.78 280
our_test_396.51 34896.35 34196.98 38997.61 43595.05 39399.98 29099.01 43994.68 37796.77 42599.06 40795.87 23798.14 43191.81 44092.37 38697.75 349
thisisatest051599.42 9099.31 9499.74 14099.59 22999.55 139100.00 199.46 10296.65 28899.92 191100.00 199.44 5599.85 23899.09 26599.63 18499.81 244
ppachtmachnet_test96.17 37095.89 36097.02 38697.61 43595.24 39099.99 25899.24 32193.31 42096.71 42699.62 36194.34 28098.07 44089.87 45592.30 38897.75 349
SMA-MVScopyleft99.69 4299.59 5099.98 2899.99 5299.93 52100.00 199.43 13397.50 193100.00 1100.00 199.43 59100.00 1100.00 1100.00 1100.00 1
Yufeng Yin; Xiaoyan Liu; Zichao Zhang: SMA-MVS: Segmentation-Guided Multi-Scale Anchor Deformation Patch Multi-View Stereo. IEEE Transactions on Circuits and Systems for Video Technology
GSMVS99.91 171
DPE-MVScopyleft99.79 1799.73 2099.99 1399.99 5299.98 18100.00 199.42 15298.91 55100.00 1100.00 199.22 87100.00 1100.00 1100.00 1100.00 1
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part2100.00 199.99 6100.00 1
thres100view90099.25 12699.01 13899.95 6199.81 14399.87 86100.00 199.94 2797.13 22699.83 20999.96 27397.01 208100.00 199.59 20697.85 28899.98 127
tfpnnormal96.36 35895.69 37598.37 30698.55 39098.71 23799.69 39199.45 11093.16 42496.69 42799.71 33488.44 40198.99 35294.17 41791.38 40597.41 441
tfpn200view999.26 12299.03 13699.96 5299.81 14399.89 77100.00 199.94 2797.23 22099.83 20999.96 27397.04 204100.00 199.59 20697.85 28899.98 127
c3_l97.58 29597.42 29498.06 33899.48 28598.16 29599.96 30699.10 40994.54 38298.13 37599.20 40297.87 17298.25 42297.28 35191.20 40797.75 349
CHOSEN 280x42099.85 699.87 199.80 12399.99 5299.97 2699.97 29999.98 1698.96 39100.00 1100.00 199.96 499.42 327100.00 1100.00 1100.00 1
CANet99.40 9299.24 10899.89 9099.99 5299.76 107100.00 199.73 6198.40 10299.78 228100.00 195.28 24899.96 169100.00 199.99 10799.96 143
Fast-Effi-MVS+-dtu98.38 25098.56 20897.82 35799.58 23494.44 419100.00 199.16 38096.75 26699.51 25999.63 35795.03 25999.60 28397.71 33499.67 17899.42 319
Effi-MVS+-dtu98.51 24098.86 16297.47 36799.77 16894.21 426100.00 198.94 44597.61 17799.91 19498.75 43395.89 23699.51 31099.36 24099.48 18998.68 331
CANet_DTU99.02 15998.90 16099.41 19999.88 12398.71 237100.00 199.29 28298.84 68100.00 1100.00 194.02 288100.00 198.08 31599.96 12599.52 314
MGCNet99.72 3299.65 3799.93 7899.99 5299.79 102100.00 199.91 4099.17 6100.00 1100.00 197.84 175100.00 1100.00 199.95 127100.00 1
MP-MVS-pluss99.61 6599.50 7199.97 4099.98 9399.92 59100.00 199.42 15297.53 18899.77 229100.00 198.77 138100.00 199.99 76100.00 199.99 124
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS99.81 1499.77 1299.94 74100.00 199.86 89100.00 199.42 15298.87 64100.00 1100.00 199.65 1999.96 169100.00 1100.00 1100.00 1
Zhenlong Yuan, Cong Liu, Fei Shen, Zhaoxin Li, Jingguo luo, Tianlu Mao and Zhaoqi Wang: MSP-MVS: Multi-granularity Segmentation Prior Guided Multi-View Stereo. AAAI2025
sam_mvs199.29 8199.91 171
sam_mvs99.33 70
IterMVS-SCA-FT96.72 33896.42 33897.62 36399.40 31496.83 36099.99 25899.14 39294.65 37997.55 40599.72 33289.65 38098.31 41695.62 39692.05 39097.73 387
TSAR-MVS + MP.99.82 1299.77 1299.99 13100.00 199.96 29100.00 199.43 13399.05 17100.00 1100.00 199.45 5499.99 107100.00 1100.00 1100.00 1
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_debu99.35 10199.21 11399.79 12899.67 19499.71 11699.78 36899.36 23498.13 125100.00 1100.00 197.00 211100.00 199.83 13499.07 19999.66 305
OPM-MVS97.21 31497.18 31097.32 37498.08 41594.66 409100.00 199.28 29098.65 9098.92 31199.98 24486.03 42499.56 29498.28 31095.41 33397.72 394
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
ACMMP_NAP99.67 4999.57 5599.97 4099.98 9399.92 59100.00 199.42 15297.83 150100.00 1100.00 198.89 129100.00 199.98 91100.00 1100.00 1
ambc88.45 46286.84 49470.76 49197.79 48798.02 47590.91 46995.14 47938.69 49698.51 40194.97 40784.23 45496.09 469
MTGPAbinary99.42 152
SPE-MVS-test99.31 11299.27 9899.43 19599.99 5298.77 232100.00 199.19 36397.24 21899.96 151100.00 197.56 18999.70 27899.68 18099.81 16799.82 230
Effi-MVS+98.58 22898.24 25299.61 16599.60 22599.26 18497.85 48699.10 40996.22 32999.97 14499.89 29893.75 29299.77 26199.43 23698.34 24099.81 244
xiu_mvs_v2_base99.51 7599.41 8099.82 11299.70 17899.73 11399.92 33199.40 20598.15 123100.00 1100.00 198.50 151100.00 199.85 13099.13 19799.74 291
xiu_mvs_v1_base99.35 10199.21 11399.79 12899.67 19499.71 11699.78 36899.36 23498.13 125100.00 1100.00 197.00 211100.00 199.83 13499.07 19999.66 305
new-patchmatchnet90.30 44089.46 44492.84 45490.77 48788.55 47199.83 35398.80 45590.07 45287.86 47995.00 48178.77 45994.30 48384.86 47379.15 47395.68 474
pmmvs693.64 41392.87 41695.94 42597.47 44591.41 45398.92 47099.02 43787.84 46295.01 44699.61 36377.24 46498.77 37594.33 41586.41 44997.63 424
pmmvs595.94 38195.61 37796.95 39097.42 44694.66 409100.00 198.08 47193.60 41097.05 41599.43 38587.02 41398.46 40695.76 38892.12 38997.72 394
test_post199.32 43188.24 49399.33 7099.59 28598.31 306
test_post89.05 49199.49 4799.59 285
Fast-Effi-MVS+98.40 24998.02 27099.55 17799.63 21399.06 205100.00 199.15 38595.07 36599.42 26799.95 28093.26 30499.73 27397.44 34498.24 25999.87 214
patchmatchnet-post97.79 46399.41 6599.54 302
Anonymous2023121196.29 36295.70 37298.07 33499.80 15697.49 33499.15 45799.40 20589.11 45497.75 39699.45 38488.93 39198.98 35398.26 31189.47 42297.73 387
pmmvs-eth3d91.73 43190.67 43594.92 43791.63 48492.71 44399.90 33898.54 46391.19 44088.08 47895.50 47679.31 45796.13 47390.55 45081.32 47095.91 471
GG-mvs-BLEND99.59 16999.54 24899.49 15599.17 45499.52 7799.96 15199.68 344100.00 199.33 33499.71 16699.99 10799.96 143
xiu_mvs_v1_base_debi99.35 10199.21 11399.79 12899.67 19499.71 11699.78 36899.36 23498.13 125100.00 1100.00 197.00 211100.00 199.83 13499.07 19999.66 305
Anonymous2023120693.45 41593.17 41194.30 44495.00 47489.69 46699.98 29098.43 46493.30 42194.50 45398.59 43990.52 35595.73 47777.46 48990.73 41397.48 439
MTAPA99.68 4699.59 5099.97 4099.99 5299.91 63100.00 199.42 15298.32 11399.94 185100.00 198.65 143100.00 199.96 105100.00 1100.00 1
MTMP100.00 199.18 370
gm-plane-assit99.52 26597.26 34795.86 340100.00 199.43 32598.76 282
test9_res100.00 1100.00 1100.00 1
MVP-Stereo96.51 34896.48 33596.60 41095.65 46394.25 42598.84 47398.16 46795.85 34295.23 44499.04 41092.54 32499.13 34392.98 43299.98 11796.43 463
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST9100.00 199.95 37100.00 199.42 15297.65 168100.00 1100.00 199.53 3699.97 149
train_agg99.71 3699.63 4499.97 40100.00 199.95 37100.00 199.42 15297.70 162100.00 1100.00 199.51 4099.97 149100.00 1100.00 1100.00 1
gg-mvs-nofinetune96.95 32996.10 35199.50 18199.41 30999.36 17499.07 46799.52 7783.69 47799.96 15183.60 498100.00 199.20 34099.68 18099.99 10799.96 143
SCA98.30 25597.98 27299.23 24799.41 30998.25 28699.99 25899.45 11096.91 24799.76 23199.58 36789.65 38099.54 30298.31 30698.79 20699.91 171
Patchmatch-test97.83 28297.42 29499.06 25599.08 34597.66 32998.66 47899.21 35093.65 40898.25 37199.58 36799.47 5299.57 29090.25 45498.59 21599.95 149
test_8100.00 199.91 63100.00 199.42 15297.70 162100.00 1100.00 199.51 4099.98 140
MS-PatchMatch95.66 38795.87 36295.05 43297.80 42789.25 46798.88 47299.30 27396.35 32096.86 42099.01 41581.35 45099.43 32593.30 42899.98 11796.46 462
Patchmatch-RL test93.49 41493.63 40693.05 45291.78 48283.41 47998.21 48496.95 48991.58 43891.05 46797.64 46699.40 6795.83 47694.11 42081.95 46699.91 171
cdsmvs_eth3d_5k24.41 46732.55 4690.00 4850.00 5080.00 5100.00 49699.39 2210.00 5030.00 504100.00 193.55 2970.00 5040.00 5020.00 5020.00 500
pcd_1.5k_mvsjas8.24 46910.99 4720.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.14 50498.75 1390.00 5040.00 5020.00 5020.00 500
agg_prior2100.00 1100.00 1100.00 1
agg_prior100.00 199.88 8499.42 152100.00 199.97 149
tmp_tt75.80 46074.26 46280.43 47552.91 50753.67 50687.42 49497.98 47661.80 49467.04 497100.00 176.43 46796.40 46996.47 37328.26 49991.23 489
canonicalmvs99.03 15398.73 17899.94 7499.75 17199.95 37100.00 199.30 27397.64 170100.00 1100.00 195.22 25199.97 14999.76 15196.90 31699.91 171
anonymousdsp97.16 31796.88 31898.00 34697.08 45198.06 30599.81 35799.15 38594.58 38097.84 39299.62 36190.49 35698.60 39297.98 32095.32 33697.33 445
alignmvs99.38 9699.21 11399.91 8399.73 17499.92 59100.00 199.51 8197.61 177100.00 1100.00 199.06 10499.93 19999.83 13497.12 31099.90 182
nrg03097.64 28997.27 30498.75 28298.34 39799.53 144100.00 199.22 33196.21 33098.27 36999.95 28094.40 27798.98 35399.23 25489.78 41997.75 349
v14419296.40 35695.81 36498.17 32697.89 42398.11 29999.99 25899.06 42893.39 41798.75 32599.09 40590.43 36198.66 38293.10 43190.55 41497.75 349
FIs97.95 27797.73 28498.62 28798.53 39299.24 188100.00 199.43 13396.74 26997.87 39099.82 31595.27 24998.89 36498.78 28093.07 37497.74 376
v192192096.16 37295.50 38098.14 32897.88 42497.96 31399.99 25899.07 42093.33 41998.60 33599.24 39789.37 38498.71 37991.28 44390.74 41297.75 349
UA-Net99.06 14798.83 16499.74 14099.52 26599.40 16899.08 46599.45 11097.64 17099.83 209100.00 195.80 23999.94 19598.35 30499.80 17099.88 203
v119296.18 36895.49 38298.26 31698.01 41898.15 29699.99 25899.08 41593.36 41898.54 34098.97 42089.47 38398.89 36491.15 44590.82 41097.75 349
FC-MVSNet-test97.84 28197.63 29098.45 29898.30 40299.05 206100.00 199.43 13396.63 29397.61 40299.82 31595.19 25498.57 39798.64 28993.05 37597.73 387
v114496.51 34895.97 35898.13 33197.98 42098.04 30799.99 25899.08 41593.51 41398.62 33498.98 41790.98 34798.62 38893.79 42390.79 41197.74 376
sosnet-low-res0.01 4710.02 4740.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.14 5040.00 5070.00 5040.00 5020.00 5020.00 500
HFP-MVS99.74 2899.67 3399.96 52100.00 199.89 77100.00 199.76 5497.95 143100.00 1100.00 199.31 75100.00 199.99 76100.00 1100.00 1
v14896.29 36295.84 36397.63 36197.74 43096.53 370100.00 199.07 42093.52 41298.01 38399.42 38691.22 33798.60 39296.37 37787.22 44397.75 349
sosnet0.01 4710.02 4740.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.14 5040.00 5070.00 5040.00 5020.00 5020.00 500
uncertanet0.01 4710.02 4740.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.14 5040.00 5070.00 5040.00 5020.00 5020.00 500
AllTest98.55 23398.40 23398.99 26299.93 11297.35 341100.00 199.40 20597.08 23199.09 29799.98 24493.37 30199.95 18296.94 35999.84 16299.68 303
TestCases98.99 26299.93 11297.35 34199.40 20597.08 23199.09 29799.98 24493.37 30199.95 18296.94 35999.84 16299.68 303
v7n96.06 37895.42 38897.99 34897.58 43897.35 34199.86 34899.11 40692.81 43197.91 38899.49 38190.99 34698.92 36092.51 43588.49 43397.70 403
region2R99.72 3299.64 4099.97 40100.00 199.90 70100.00 199.74 6097.86 149100.00 1100.00 199.19 90100.00 199.99 76100.00 1100.00 1
RRT-MVS98.75 20198.52 21399.44 19299.65 20598.57 24799.90 33899.08 41596.51 30599.96 15199.95 28092.59 32299.96 16999.60 20499.45 19199.81 244
balanced_ft_v198.70 20898.61 19898.94 26699.67 19496.90 35799.91 33799.30 27396.73 27399.96 15199.97 25692.18 32899.93 19999.86 12799.95 127100.00 1
PS-MVSNAJss98.03 27298.06 26797.94 35097.63 43397.33 34499.89 34299.23 32696.27 32498.03 38099.59 36598.75 13998.78 37298.52 29794.61 36197.70 403
PS-MVSNAJ99.64 5499.57 5599.85 10499.78 16699.81 9999.95 31599.42 15298.38 105100.00 1100.00 198.75 139100.00 199.88 12399.99 10799.74 291
jajsoiax97.07 32296.79 32397.89 35497.28 44997.12 35299.95 31599.19 36396.55 29997.31 41099.69 34087.35 41298.91 36198.70 28595.12 35097.66 415
mvs_tets97.00 32896.69 32597.94 35097.41 44897.27 34699.60 40299.18 37096.51 30597.35 40999.69 34086.53 41898.91 36198.84 27795.09 35197.65 420
EI-MVSNet-UG-set99.69 4299.63 4499.87 9799.99 5299.64 12799.95 31599.44 12498.35 111100.00 1100.00 198.98 11599.97 14999.98 91100.00 1100.00 1
EI-MVSNet-Vis-set99.70 3999.64 4099.87 97100.00 199.64 12799.98 29099.44 12498.35 11199.99 127100.00 199.04 10999.96 16999.98 91100.00 1100.00 1
HPM-MVS++copyleft99.82 1299.76 1599.99 1399.99 5299.98 18100.00 199.83 4498.88 6199.96 151100.00 199.21 88100.00 1100.00 1100.00 199.99 124
test_prior499.93 52100.00 1
XVS99.79 1799.73 2099.98 28100.00 199.94 46100.00 199.75 5798.67 88100.00 1100.00 199.16 93100.00 1100.00 1100.00 1100.00 1
v124095.96 38095.25 39098.07 33497.91 42297.87 32199.96 30699.07 42093.24 42298.64 33398.96 42188.98 39098.61 38989.58 45990.92 40997.75 349
pm-mvs195.76 38495.01 39598.00 34698.23 40897.45 33699.24 43999.04 43393.13 42595.93 44099.72 33286.28 42098.84 36995.62 39687.92 43697.72 394
test_prior2100.00 198.82 72100.00 1100.00 199.47 52100.00 1100.00 1
X-MVStestdata97.04 32496.06 35399.98 28100.00 199.94 46100.00 199.75 5798.67 88100.00 166.97 50199.16 93100.00 1100.00 1100.00 1100.00 1
test_prior99.90 87100.00 199.75 10899.73 6199.97 149100.00 1
旧先验2100.00 198.11 129100.00 1100.00 199.67 184
新几何2100.00 1
新几何199.99 13100.00 199.96 2999.81 4797.89 146100.00 1100.00 199.20 89100.00 197.91 324100.00 1100.00 1
旧先验199.99 5299.88 8499.82 45100.00 199.27 84100.00 1100.00 1
无先验100.00 199.80 4897.98 137100.00 199.33 246100.00 1
原ACMM2100.00 1
原ACMM199.93 78100.00 199.80 10199.66 6898.18 120100.00 1100.00 199.43 59100.00 199.50 224100.00 1100.00 1
test22299.99 5299.90 70100.00 199.69 6797.66 166100.00 1100.00 199.30 80100.00 1100.00 1
testdata2100.00 197.36 349
segment_acmp99.55 32
testdata99.66 15799.99 5298.97 21999.73 6197.96 142100.00 1100.00 199.42 63100.00 199.28 250100.00 1100.00 1
testdata1100.00 198.77 84
v896.35 35995.73 37198.21 32298.11 41498.23 28799.94 32399.07 42092.66 43298.29 36699.00 41691.46 33498.77 37594.17 41788.83 43197.62 426
131499.38 9699.19 11899.96 5298.88 37399.89 7799.24 43999.93 3598.88 6198.79 324100.00 197.02 207100.00 1100.00 1100.00 1100.00 1
LFMVS97.42 30596.62 32899.81 11799.80 15699.50 15199.16 45599.56 7594.48 385100.00 1100.00 179.35 456100.00 199.89 12197.37 30799.94 154
VDD-MVS96.58 34595.99 35698.34 30899.52 26595.33 38999.18 44999.38 22496.64 28999.77 229100.00 172.51 476100.00 1100.00 196.94 31599.70 301
VDDNet96.39 35795.55 37998.90 26999.27 33197.45 33699.15 45799.92 3991.28 43999.98 138100.00 173.55 472100.00 199.85 13096.98 31499.24 323
v1096.14 37495.50 38098.07 33498.19 41197.96 31399.83 35399.07 42092.10 43598.07 37798.94 42291.07 34298.61 38992.41 43889.82 41897.63 424
VPNet96.41 35395.76 36998.33 30998.61 38898.30 28199.48 41599.45 11096.98 23998.87 31699.88 30081.57 44898.93 35999.22 25687.82 43797.76 338
MVS99.22 13098.96 14799.98 2899.00 36099.95 3799.24 43999.94 2798.14 12498.88 314100.00 195.63 244100.00 199.85 130100.00 1100.00 1
v2v48296.70 33996.18 34898.27 31398.04 41698.39 265100.00 199.13 39894.19 39598.58 33799.08 40690.48 35798.67 38195.69 39190.44 41597.75 349
V4296.65 34196.16 35098.11 33398.17 41398.23 28799.99 25899.09 41493.97 40098.74 32699.05 40991.09 34198.82 37095.46 40089.90 41797.27 446
SD-MVS99.81 1499.75 1799.99 1399.99 5299.96 29100.00 199.42 15299.01 31100.00 1100.00 199.33 70100.00 1100.00 1100.00 1100.00 1
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-MVS97.72 28797.27 30499.06 25599.24 33497.93 316100.00 199.24 32195.80 34498.99 30699.64 35389.77 37599.36 33095.12 40697.62 30699.89 190
MSLP-MVS++99.89 199.85 299.99 13100.00 199.96 29100.00 199.95 1999.11 8100.00 1100.00 199.60 21100.00 1100.00 1100.00 1100.00 1
APDe-MVScopyleft99.84 999.78 1099.99 13100.00 199.98 18100.00 199.44 12499.06 15100.00 1100.00 199.56 3099.99 107100.00 1100.00 1100.00 1
Zhaojie Zeng, Yuesong Wang, Tao Guan: Matching Ambiguity-Resilient Multi-View Stereo via Adaptive Patch Deformation. Pattern Recognition
APD-MVS_3200maxsize99.65 5299.55 6299.97 4099.99 5299.91 63100.00 199.48 8397.54 185100.00 1100.00 198.97 11799.99 10799.98 91100.00 1100.00 1
ADS-MVSNet298.28 26098.51 21897.62 36399.51 27095.03 39499.24 43999.41 20195.52 35399.96 15199.70 33797.57 18797.94 44997.11 35598.54 21799.88 203
EI-MVSNet97.98 27497.93 27398.16 32799.11 34197.84 32299.74 37899.29 28294.39 38898.65 331100.00 197.21 20298.88 36797.62 34095.31 33797.75 349
Regformer0.01 4710.02 4740.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.14 5040.00 5070.00 5040.00 5020.00 5020.00 500
CVMVSNet98.56 23298.47 22198.82 27599.11 34197.67 32899.74 37899.47 8497.57 18399.06 301100.00 195.72 24198.97 35598.21 31297.33 30899.83 224
pmmvs497.17 31696.80 32198.27 31397.68 43298.64 243100.00 199.18 37094.22 39298.55 33999.71 33493.67 29398.47 40595.66 39492.57 38397.71 402
EU-MVSNet96.63 34296.53 33196.94 39197.59 43796.87 35999.76 37599.47 8496.35 32096.85 42199.78 32892.57 32396.27 47295.33 40191.08 40897.68 410
VNet99.04 15098.75 17599.90 8799.81 14399.75 10899.50 41499.47 8498.36 109100.00 199.99 23694.66 270100.00 199.90 11997.09 31199.96 143
test-LLR99.03 15398.91 15799.40 20499.40 31499.28 181100.00 199.45 11096.70 28199.42 26799.12 40399.31 7599.01 34996.82 36599.99 10799.91 171
TESTMET0.1,199.08 14398.96 14799.44 19299.63 21399.38 169100.00 199.45 11095.53 35199.48 261100.00 199.71 1599.02 34896.84 36499.99 10799.91 171
test-mter98.96 17398.82 16599.40 20499.40 31499.28 181100.00 199.45 11095.44 36299.42 26799.12 40399.70 1699.01 34996.82 36599.99 10799.91 171
VPA-MVSNet97.03 32596.43 33798.82 27598.64 38799.32 17699.38 42699.47 8496.73 27398.91 31398.94 42287.00 41499.40 32899.23 25489.59 42097.76 338
ACMMPR99.74 2899.67 3399.96 52100.00 199.89 77100.00 199.76 5497.95 143100.00 1100.00 199.29 81100.00 199.99 76100.00 1100.00 1
testgi96.18 36895.93 35996.93 39298.98 36494.20 427100.00 199.07 42097.16 22396.06 43899.86 30384.08 43897.79 45590.38 45397.80 29498.81 330
test20.0393.11 41892.85 41793.88 44995.19 47191.83 449100.00 198.87 45193.68 40792.76 46298.88 42889.20 38792.71 48977.88 48789.19 42697.09 450
thres600view799.24 12999.00 14199.95 6199.81 14399.87 86100.00 199.94 2797.13 22699.83 20999.96 27397.01 208100.00 199.54 21797.77 29799.97 137
ADS-MVSNet98.70 20898.51 21899.28 24199.51 27098.39 26599.24 43999.44 12495.52 35399.96 15199.70 33797.57 18799.58 28997.11 35598.54 21799.88 203
MP-MVScopyleft99.61 6599.49 7399.98 2899.99 5299.94 46100.00 199.42 15297.82 15299.99 127100.00 198.20 159100.00 199.99 76100.00 1100.00 1
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs80.17 45381.95 45674.80 47858.54 50559.58 503100.00 187.14 50476.09 48899.61 252100.00 167.06 48474.19 50198.84 27750.30 49590.64 490
thres40099.26 12299.03 13699.95 6199.81 14399.89 77100.00 199.94 2797.23 22099.83 20999.96 27397.04 204100.00 199.59 20697.85 28899.97 137
test12379.44 45679.23 45880.05 47680.03 49971.72 489100.00 177.93 50762.52 49394.81 44799.69 34078.21 46074.53 50092.57 43427.33 50093.90 480
thres20099.27 12099.04 13599.96 5299.81 14399.90 70100.00 199.94 2797.31 21499.83 20999.96 27397.04 204100.00 199.62 19997.88 28699.98 127
test0.0.03 198.12 26798.03 26998.39 30499.11 34198.07 303100.00 199.93 3596.70 28196.91 41999.95 28099.31 7598.19 42791.93 43998.44 22398.91 329
pmmvs390.62 43989.36 44594.40 44290.53 49091.49 452100.00 196.73 49184.21 47693.65 45896.65 47382.56 44694.83 48082.28 47877.62 47696.89 455
EMVS69.88 46269.09 46572.24 48284.70 49565.82 49999.96 30687.08 50549.82 49971.51 49384.74 49649.30 49175.32 49950.97 50043.71 49775.59 497
E-PMN70.72 46170.06 46472.69 48183.92 49665.48 50099.95 31592.72 50049.88 49872.30 49286.26 49547.17 49377.43 49853.83 49944.49 49675.17 498
PGM-MVS99.69 4299.61 4899.95 6199.99 5299.85 93100.00 199.58 7297.69 164100.00 1100.00 199.44 55100.00 199.79 142100.00 1100.00 1
LCM-MVSNet-Re96.52 34697.21 30894.44 44199.27 33185.80 47599.85 35096.61 49395.98 33592.75 46398.48 44993.97 28997.55 45999.58 20998.43 22499.98 127
LCM-MVSNet79.01 45876.93 46185.27 46878.28 50068.01 49696.57 48998.03 47355.10 49682.03 48993.27 48631.99 50193.95 48582.72 47674.37 47893.84 481
MCST-MVS99.85 699.80 7100.00 1100.00 199.99 6100.00 199.73 6199.19 5100.00 1100.00 199.31 75100.00 1100.00 1100.00 1100.00 1
mvs_anonymous98.80 19398.60 20199.38 21099.57 23899.24 188100.00 199.21 35095.87 33898.92 31199.82 31596.39 23199.03 34799.13 26198.50 21999.88 203
MVS_Test98.93 17998.65 19299.77 13699.62 22099.50 15199.99 25899.19 36395.52 35399.96 15199.86 30396.54 22899.98 14098.65 28898.48 22199.82 230
MDA-MVSNet-bldmvs91.65 43389.94 44296.79 40696.72 45396.70 36499.42 42398.94 44588.89 45566.97 49898.37 45481.43 44995.91 47589.24 46289.46 42397.75 349
CDPH-MVS99.73 3199.64 4099.99 13100.00 199.97 26100.00 199.42 15298.02 133100.00 1100.00 199.32 7399.99 107100.00 1100.00 1100.00 1
test1299.95 6199.99 5299.89 7799.42 152100.00 199.24 8699.97 149100.00 1100.00 1
casdiffmvspermissive98.65 21398.38 23899.46 18899.52 26598.74 236100.00 199.15 38596.91 24799.05 302100.00 192.75 31799.83 24499.70 17098.38 23199.81 244
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
diffmvspermissive98.96 17398.73 17899.63 16199.54 24899.16 198100.00 199.18 37097.33 21199.96 151100.00 194.60 27299.91 20799.66 18998.33 24399.82 230
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
baseline298.99 16698.93 15499.18 25099.26 33399.15 199100.00 199.46 10296.71 28096.79 423100.00 199.42 6399.25 33898.75 28399.94 13399.15 325
baseline198.91 18298.61 19899.81 11799.71 17699.77 10699.78 36899.44 12497.51 19298.81 32299.99 23698.25 15899.76 26598.60 29495.41 33399.89 190
YYNet192.44 42590.92 43497.03 38596.20 45697.06 35599.99 25899.14 39288.21 46067.93 49598.43 45388.63 39696.28 47190.64 44789.08 42797.74 376
PMMVS279.15 45777.28 46084.76 46982.34 49772.66 48799.70 38995.11 49771.68 49184.78 48890.87 48832.05 50089.99 49275.53 49263.45 49391.64 488
MDA-MVSNet_test_wron92.61 42391.09 43397.19 38196.71 45497.26 347100.00 199.14 39288.61 45667.90 49698.32 45689.03 38896.57 46790.47 45289.59 42097.74 376
tpmvs98.59 22698.38 23899.23 24799.69 18197.90 31799.31 43499.47 8494.52 38399.68 24399.28 39597.64 18499.89 22097.71 33498.17 26699.89 190
PM-MVS88.39 44487.41 44991.31 45691.73 48382.02 48299.79 36396.62 49291.06 44290.71 47195.73 47548.60 49295.96 47490.56 44981.91 46795.97 470
HQP_MVS97.71 28897.82 28097.37 37099.00 36094.80 403100.00 199.40 20599.00 3299.08 29999.97 25688.58 39999.55 29999.79 14295.57 33197.76 338
plane_prior799.00 36094.78 407
plane_prior699.06 35094.80 40388.58 399
plane_prior599.40 20599.55 29999.79 14295.57 33197.76 338
plane_prior499.97 256
plane_prior394.79 40699.03 2599.08 299
plane_prior2100.00 199.00 32
plane_prior199.02 354
plane_prior94.80 403100.00 199.03 2595.58 327
PS-CasMVS96.34 36095.78 36898.03 34598.18 41298.27 28499.71 38799.32 25894.75 37296.82 42299.65 34986.98 41598.15 42997.74 33388.85 43097.66 415
UniMVSNet_NR-MVSNet97.16 31796.80 32198.22 32098.38 39698.41 262100.00 199.45 11096.14 33297.76 39399.64 35395.05 25898.50 40297.98 32086.84 44497.75 349
PEN-MVS96.01 37995.48 38497.58 36597.74 43097.26 34799.90 33899.29 28294.55 38196.79 42399.55 37387.38 41097.84 45196.92 36287.24 44297.65 420
TransMVSNet (Re)94.78 39793.72 40497.93 35298.34 39797.88 31999.23 44697.98 47691.60 43794.55 45199.71 33487.89 40498.36 41389.30 46184.92 45297.56 432
DTE-MVSNet95.52 38894.99 39697.08 38397.49 44396.45 371100.00 199.25 31593.82 40396.17 43499.57 37187.81 40597.18 46094.57 41286.26 45097.62 426
DU-MVS96.93 33096.49 33498.22 32098.31 40098.41 262100.00 199.37 22896.41 31597.76 39399.65 34992.14 32998.50 40297.98 32086.84 44497.75 349
UniMVSNet (Re)97.29 31396.85 32098.59 29098.49 39399.13 200100.00 199.42 15296.52 30498.24 37398.90 42594.93 26098.89 36497.54 34187.61 43897.75 349
CP-MVSNet96.73 33696.25 34598.18 32498.21 40998.67 24099.77 37399.32 25895.06 36697.20 41399.65 34990.10 36998.19 42798.06 31888.90 42997.66 415
WR-MVS_H96.73 33696.32 34497.95 34998.26 40697.88 31999.72 38699.43 13395.06 36696.99 41698.68 43693.02 31398.53 40097.43 34588.33 43497.43 440
WR-MVS97.09 32096.64 32698.46 29798.43 39499.09 20299.97 29999.33 25595.62 34897.76 39399.67 34591.17 34098.56 39998.49 29889.28 42597.74 376
NR-MVSNet96.63 34296.04 35498.38 30598.31 40098.98 21799.22 44899.35 24595.87 33894.43 45499.65 34992.73 31998.40 41096.78 36888.05 43597.75 349
Baseline_NR-MVSNet96.16 37295.70 37297.56 36698.28 40596.79 362100.00 197.86 47991.93 43697.63 39999.47 38392.14 32998.35 41497.13 35486.83 44697.54 433
TranMVSNet+NR-MVSNet96.45 35296.01 35597.79 35998.00 41997.62 331100.00 199.35 24595.98 33597.31 41099.64 35390.09 37098.00 44596.89 36386.80 44797.75 349
TSAR-MVS + GP.99.61 6599.69 2599.35 21599.99 5298.06 305100.00 199.36 23499.83 2100.00 1100.00 198.95 12199.99 107100.00 199.11 198100.00 1
n20.00 509
nn0.00 509
mPP-MVS99.69 4299.60 4999.97 40100.00 199.91 63100.00 199.42 15297.91 145100.00 1100.00 199.04 109100.00 1100.00 1100.00 1100.00 1
door-mid96.32 495
XVG-OURS-SEG-HR98.27 26198.31 24598.14 32899.59 22995.92 376100.00 199.36 23498.48 9899.21 286100.00 189.27 38599.94 19599.76 15199.17 19598.56 334
mvsmamba99.05 14998.98 14499.27 24499.57 23898.10 301100.00 199.28 29095.92 33799.96 15199.97 25696.73 22299.89 22099.72 16299.65 18199.81 244
MVSFormer98.94 17898.82 16599.28 24199.45 30399.49 155100.00 199.13 39895.46 35899.97 144100.00 196.76 21998.59 39498.63 291100.00 199.74 291
jason99.11 14198.96 14799.59 16999.17 33799.31 178100.00 199.13 39897.38 20599.83 209100.00 195.54 24599.72 27599.57 21299.97 12199.74 291
jason: jason.
lupinMVS99.29 11799.16 12299.69 15099.45 30399.49 155100.00 199.15 38597.45 19999.97 144100.00 196.76 21999.76 26599.67 184100.00 199.81 244
test_djsdf97.55 29897.38 29798.07 33497.50 44197.99 309100.00 199.13 39895.46 35898.47 35299.85 30892.01 33298.59 39498.63 29195.36 33597.62 426
HPM-MVS_fast99.60 6899.49 7399.91 8399.99 5299.78 103100.00 199.42 15297.09 229100.00 1100.00 198.95 12199.96 16999.98 91100.00 1100.00 1
K. test v395.46 39095.14 39396.40 41397.53 44093.40 43499.99 25899.23 32695.49 35692.70 46499.73 33184.26 43498.12 43393.94 42293.38 37297.68 410
lessismore_v096.05 42397.55 43991.80 45099.22 33191.87 46599.91 29583.50 44198.68 38092.48 43690.42 41697.68 410
SixPastTwentyTwo95.71 38695.49 38296.38 41597.42 44693.01 43799.84 35198.23 46694.75 37295.98 43999.97 25685.35 42998.43 40894.71 41093.17 37397.69 408
OurMVSNet-221017-096.14 37495.98 35796.62 40997.49 44393.44 43399.92 33198.16 46795.86 34097.65 39899.95 28085.71 42798.78 37294.93 40894.18 36497.64 423
HPM-MVScopyleft99.59 6999.50 7199.89 90100.00 199.70 120100.00 199.42 15297.46 197100.00 1100.00 198.60 14699.96 16999.99 76100.00 1100.00 1
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS98.30 25598.36 24298.13 33199.58 23495.91 377100.00 199.36 23498.69 8699.23 285100.00 191.20 33999.92 20599.34 24597.82 29298.56 334
XVG-ACMP-BASELINE96.60 34496.52 33396.84 39798.41 39593.29 43699.99 25899.32 25897.76 15998.51 34999.29 39481.95 44799.54 30298.40 30195.03 35297.68 410
casdiffmvs_mvgpermissive98.64 21498.39 23699.40 20499.50 27898.60 245100.00 199.22 33196.85 25299.10 295100.00 192.75 31799.78 26099.71 16698.35 23699.81 244
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys: Lightweight and Accurate Multi-View Stereo With Confidence-Aware Diffusion Model. IEEE T-PAMI 2025
LPG-MVS_test97.31 31197.32 30097.28 37798.85 37994.60 413100.00 199.37 22897.35 20798.85 31799.98 24486.66 41699.56 29499.55 21495.26 33997.70 403
LGP-MVS_train97.28 37798.85 37994.60 41399.37 22897.35 20798.85 31799.98 24486.66 41699.56 29499.55 21495.26 33997.70 403
baseline98.69 21098.45 22399.41 19999.52 26598.67 240100.00 199.17 37997.03 23599.13 292100.00 193.17 30799.74 27099.70 17098.34 24099.81 244
test1199.42 152
door96.13 496
EPNet_dtu98.53 23798.23 25599.43 19599.92 11599.01 21299.96 30699.47 8498.80 7799.96 15199.96 27398.56 14899.30 33587.78 46799.68 176100.00 1
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268899.00 16298.91 15799.25 24699.90 11997.79 325100.00 199.99 1398.79 8098.28 367100.00 193.63 29499.95 18299.66 18999.95 127100.00 1
EPNet99.62 6399.69 2599.42 19899.99 5298.37 269100.00 199.89 4298.83 70100.00 1100.00 198.97 117100.00 199.90 11999.61 18599.89 190
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS94.82 400
HQP-NCC99.07 346100.00 199.04 2099.17 287
ACMP_Plane99.07 346100.00 199.04 2099.17 287
APD-MVScopyleft99.68 4699.58 5299.97 4099.99 5299.96 29100.00 199.42 15297.53 188100.00 1100.00 199.27 8499.97 149100.00 1100.00 1100.00 1
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS99.79 142
HQP4-MVS99.17 28799.57 29097.77 336
HQP3-MVS99.40 20595.58 327
HQP2-MVS88.61 397
CNVR-MVS99.85 699.80 7100.00 1100.00 199.99 6100.00 199.77 5399.07 13100.00 1100.00 199.39 68100.00 1100.00 1100.00 1100.00 1
NCCC99.86 499.82 5100.00 1100.00 199.99 6100.00 199.71 6699.07 13100.00 1100.00 199.59 24100.00 1100.00 1100.00 1100.00 1
114514_t99.39 9399.25 10499.81 11799.97 9799.48 159100.00 199.42 15295.53 351100.00 1100.00 198.37 15799.95 18299.97 103100.00 1100.00 1
CP-MVS99.67 4999.58 5299.95 61100.00 199.84 95100.00 199.42 15297.77 157100.00 1100.00 199.07 103100.00 1100.00 1100.00 1100.00 1
DSMNet-mixed95.18 39595.21 39295.08 43196.03 45890.21 46299.65 39593.64 49992.91 42798.34 36297.40 46790.05 37295.51 47991.02 44697.86 28799.51 316
tpm298.64 21498.58 20498.81 27899.42 30797.12 35299.69 39199.37 22893.63 40999.94 18599.67 34598.96 12099.47 31798.62 29397.95 28299.83 224
NP-MVS99.07 34694.81 40299.97 256
EG-PatchMatch MVS92.94 42192.49 42594.29 44595.87 46087.07 47499.07 46798.11 47093.19 42388.98 47498.66 43770.89 47899.08 34592.43 43795.21 34496.72 457
tpm cat198.05 27197.76 28198.92 26899.50 27897.10 35499.77 37399.30 27390.20 45199.72 23998.71 43497.71 18099.86 23196.75 37198.20 26399.81 244
SteuartSystems-ACMMP99.78 1999.71 2399.98 2899.76 16999.95 37100.00 199.42 15298.69 86100.00 1100.00 199.52 3999.99 107100.00 1100.00 1100.00 1
Skip Steuart: Steuart Systems R&D Blog.
CostFormer98.84 19098.77 17399.04 25999.41 30997.58 33299.67 39499.35 24594.66 37899.96 15199.36 39199.28 8399.74 27099.41 23897.81 29399.81 244
CR-MVSNet98.02 27397.71 28798.93 26799.31 32598.86 22699.13 45999.00 44096.53 30199.96 15198.98 41796.94 21498.10 43891.18 44498.40 22699.84 221
JIA-IIPM97.09 32096.34 34299.36 21398.88 37398.59 24699.81 35799.43 13384.81 47599.96 15190.34 49098.55 14999.52 30897.00 35898.28 25099.98 127
Patchmtry96.81 33296.37 34098.14 32899.31 32598.55 24898.91 47199.00 44090.45 44797.92 38798.98 41796.94 21498.12 43394.27 41691.53 40197.75 349
PatchT95.90 38294.95 39898.75 28299.03 35398.39 26599.08 46599.32 25885.52 47399.96 15194.99 48297.94 16698.05 44480.20 48398.47 22299.81 244
tpmrst98.98 17098.93 15499.14 25399.61 22297.74 32699.52 41299.36 23496.05 33499.98 13899.64 35399.04 10999.86 23198.94 27198.19 26499.82 230
BH-w/o98.82 19298.81 16798.88 27199.62 22096.71 363100.00 199.28 29097.09 22998.81 322100.00 194.91 26199.96 16999.54 217100.00 199.96 143
tpm98.24 26298.22 25698.32 31099.13 33995.79 38099.53 41199.12 40495.20 36499.96 15199.36 39197.58 18599.28 33797.41 34696.67 32199.88 203
DELS-MVS99.62 6399.56 6099.82 11299.92 11599.45 161100.00 199.78 5298.92 5299.73 238100.00 197.70 181100.00 199.93 115100.00 1100.00 1
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-untuned98.64 21498.65 19298.60 28999.59 22996.17 373100.00 199.28 29096.67 28598.41 356100.00 194.52 27499.83 24499.41 238100.00 199.81 244
RPMNet95.26 39493.82 40399.56 17699.31 32598.86 22699.13 45999.42 15279.82 48299.96 15195.13 48095.69 24399.98 14077.54 48898.40 22699.84 221
MVSTER98.58 22898.52 21398.77 28199.65 20599.68 123100.00 199.29 28295.63 34798.65 33199.80 32499.78 998.88 36798.59 29595.31 33797.73 387
CPTT-MVS99.49 8099.38 8399.85 104100.00 199.54 142100.00 199.42 15297.58 18299.98 138100.00 197.43 198100.00 199.99 76100.00 1100.00 1
GBi-Net96.07 37695.80 36696.89 39499.53 25194.87 39799.18 44999.27 30593.71 40498.53 34598.81 43084.23 43598.07 44095.31 40293.60 36897.72 394
PVSNet_Blended_VisFu99.33 10899.18 12199.78 13399.82 13799.49 155100.00 199.95 1997.36 20699.63 251100.00 196.45 23099.95 18299.79 14299.65 18199.89 190
PVSNet_BlendedMVS98.71 20698.62 19798.98 26499.98 9399.60 131100.00 1100.00 197.23 220100.00 199.03 41396.57 22699.99 107100.00 194.75 35897.35 444
UnsupCasMVSNet_eth94.25 40293.89 40295.34 42997.63 43392.13 44799.73 38399.36 23494.88 36992.78 46198.63 43882.72 44396.53 46894.57 41284.73 45397.36 443
UnsupCasMVSNet_bld89.50 44188.00 44893.99 44895.30 46788.86 47098.52 48199.28 29085.50 47487.80 48094.11 48461.63 48696.96 46290.63 44879.26 47296.15 466
PVSNet_Blended99.48 8299.36 8999.83 11099.98 9399.60 131100.00 1100.00 197.79 155100.00 1100.00 196.57 22699.99 107100.00 199.88 15199.90 182
FMVSNet595.32 39195.43 38794.99 43599.39 31792.99 43999.25 43899.24 32190.45 44797.44 40898.45 45095.78 24094.39 48287.02 46891.88 39497.59 430
test196.07 37695.80 36696.89 39499.53 25194.87 39799.18 44999.27 30593.71 40498.53 34598.81 43084.23 43598.07 44095.31 40293.60 36897.72 394
new_pmnet94.11 40693.47 40896.04 42496.60 45592.82 44099.97 29998.91 44890.21 45095.26 44398.05 46285.89 42598.14 43184.28 47492.01 39197.16 448
FMVSNet397.30 31296.95 31698.37 30699.65 20599.25 18699.71 38799.28 29094.23 39198.53 34598.91 42493.30 30398.11 43595.31 40293.60 36897.73 387
dp98.72 20298.61 19899.03 26099.53 25197.39 33899.45 41899.39 22195.62 34899.94 18599.52 37798.83 13499.82 24796.77 37098.42 22599.89 190
FMVSNet296.22 36695.60 37898.06 33899.53 25198.33 27699.45 41899.27 30593.71 40498.03 38098.84 42984.23 43598.10 43893.97 42193.40 37197.73 387
FMVSNet194.45 39993.63 40696.89 39498.87 37694.87 39799.18 44999.27 30590.95 44397.31 41098.81 43072.89 47598.07 44092.61 43392.81 37897.72 394
N_pmnet91.88 43093.37 40987.40 46597.24 45066.33 49899.90 33891.05 50189.77 45395.65 44298.58 44190.05 37298.11 43585.39 47192.72 37997.75 349
cascas98.43 24498.07 26699.50 18199.65 20599.02 210100.00 199.22 33194.21 39399.72 23999.98 24492.03 33199.93 19999.68 18098.12 27199.54 312
BH-RMVSNet98.46 24298.08 26499.59 16999.61 22299.19 194100.00 199.28 29097.06 23398.95 307100.00 188.99 38999.82 24798.83 279100.00 199.77 281
UGNet98.41 24898.11 26099.31 23299.54 24898.55 24899.18 449100.00 198.64 9199.79 22699.04 41087.61 407100.00 199.30 24999.89 14899.40 320
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-MVS99.54 7499.40 8199.95 6199.81 14399.93 52100.00 1100.00 197.98 13799.84 206100.00 198.94 12399.98 14099.86 12798.21 26199.94 154
XXY-MVS97.14 31996.63 32798.67 28498.65 38698.92 22299.54 41099.29 28295.57 35097.63 39999.83 31187.79 40699.35 33298.39 30292.95 37697.75 349
EC-MVSNet99.19 13399.09 13199.48 18699.42 30799.07 203100.00 199.21 35096.95 24299.96 151100.00 196.88 21799.48 31599.64 19299.79 17199.88 203
sss99.45 8699.34 9399.80 12399.76 16999.50 151100.00 199.91 4097.72 16099.98 13899.94 28698.45 152100.00 199.53 22098.75 21099.89 190
Test_1112_low_res98.83 19198.60 20199.51 17899.69 18198.75 23399.99 25899.14 39296.81 25798.84 31999.06 40797.45 19599.89 22098.66 28697.75 29899.89 190
1112_ss98.91 18298.71 18499.51 17899.69 18198.75 23399.99 25899.15 38596.82 25698.84 319100.00 197.45 19599.89 22098.66 28697.75 29899.89 190
ab-mvs-re8.33 46811.11 4710.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 504100.00 10.00 5070.00 5040.00 5020.00 5020.00 500
ab-mvs98.42 24698.02 27099.61 16599.71 17699.00 21599.10 46299.64 6996.70 28199.04 30499.81 31890.64 35399.98 14099.64 19297.93 28399.84 221
TR-MVS98.14 26697.74 28299.33 22599.59 22998.28 28299.27 43699.21 35096.42 31499.15 29199.94 28688.87 39299.79 25598.88 27598.29 24999.93 165
MDTV_nov1_ep13_2view99.24 18899.56 40696.31 32399.96 15198.86 13098.92 27399.89 190
MDTV_nov1_ep1398.94 15299.53 25198.36 27299.39 42599.46 10296.54 30099.99 12799.63 35798.92 12699.86 23198.30 30998.71 211
MIMVSNet191.96 42791.20 43094.23 44694.94 47591.69 45199.34 43099.22 33188.23 45894.18 45598.45 45075.52 47093.41 48779.37 48491.49 40297.60 429
MIMVSNet97.06 32396.73 32498.05 34299.38 31896.64 36698.47 48299.35 24593.41 41699.48 26198.53 44789.66 37997.70 45894.16 41998.11 27299.80 270
IterMVS-LS97.56 29697.44 29397.92 35399.38 31897.90 31799.89 34299.10 40994.41 38798.32 36499.54 37697.21 20298.11 43597.50 34291.62 39997.75 349
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet98.96 17398.95 15199.01 26199.48 28598.36 27299.93 32999.37 22896.79 25999.31 28099.83 31199.77 1198.91 36198.07 31797.98 27899.77 281
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref94.58 362
IterMVS96.76 33596.46 33697.63 36199.41 30996.89 35899.99 25899.13 39894.74 37497.59 40499.66 34789.63 38298.28 42095.71 39092.31 38797.72 394
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon99.76 2199.69 2599.98 28100.00 199.95 37100.00 199.52 7797.99 13599.99 127100.00 199.72 14100.00 199.96 105100.00 1100.00 1
MVS_111021_LR99.70 3999.65 3799.88 9599.96 10399.70 120100.00 199.97 1798.96 39100.00 1100.00 197.93 16799.95 18299.99 76100.00 1100.00 1
DP-MVS98.86 18898.54 21099.81 11799.97 9799.45 16199.52 41299.40 20594.35 38998.36 359100.00 196.13 23399.97 14999.12 262100.00 1100.00 1
ACMMP++95.17 347
HQP-MVS97.73 28697.85 27897.39 36999.07 34694.82 400100.00 199.40 20599.04 2099.17 28799.97 25688.61 39799.57 29099.79 14295.58 32797.77 336
QAPM98.99 16698.66 19199.96 5299.01 35599.87 8699.88 34599.93 3597.99 13598.68 329100.00 193.17 307100.00 199.32 247100.00 1100.00 1
Vis-MVSNetpermissive98.52 23898.25 24999.34 21799.68 18698.55 24899.68 39399.41 20197.34 20999.94 185100.00 190.38 36299.70 27899.03 26798.84 20599.76 283
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet94.12 40592.73 42198.29 31199.33 32495.95 37599.38 42699.19 36374.54 49098.26 37086.34 49486.07 42299.06 34691.60 44299.87 15699.85 219
IS-MVSNet99.08 14398.91 15799.59 16999.65 20599.38 16999.78 36899.24 32196.70 28199.51 259100.00 198.44 15399.52 30898.47 29998.39 22899.88 203
HyFIR lowres test99.32 11099.24 10899.58 17399.95 10799.26 184100.00 199.99 1396.72 27599.29 28199.91 29599.49 4799.47 31799.74 15698.08 273100.00 1
EPMVS99.25 12699.13 12699.60 16799.60 22599.20 19399.60 402100.00 196.93 24499.92 19199.36 39199.05 10699.71 27798.77 28198.94 20499.90 182
PAPM_NR99.74 2899.66 3699.99 13100.00 199.96 29100.00 199.47 8497.87 148100.00 1100.00 199.60 21100.00 1100.00 1100.00 1100.00 1
TAMVS98.76 19898.73 17898.86 27299.44 30597.69 32799.57 40599.34 25296.57 29899.12 29399.81 31898.83 13499.16 34297.97 32397.91 28499.73 300
PAPR99.76 2199.68 3199.99 13100.00 199.96 29100.00 199.47 8498.16 121100.00 1100.00 199.51 40100.00 1100.00 1100.00 1100.00 1
RPSCF97.37 30798.24 25294.76 43999.80 15684.57 47899.99 25899.05 43094.95 36899.82 218100.00 194.03 286100.00 198.15 31498.38 23199.70 301
Vis-MVSNet (Re-imp)98.99 16698.89 16199.29 23899.64 21198.89 22599.98 29099.31 26796.74 26999.48 261100.00 198.11 16299.10 34498.39 30298.34 24099.89 190
test_040294.35 40093.70 40596.32 41897.92 42193.60 43099.61 40198.85 45388.19 46194.68 44999.48 38280.01 45398.58 39689.39 46095.15 34896.77 456
MVS_111021_HR99.71 3699.63 4499.93 7899.95 10799.83 97100.00 1100.00 198.89 60100.00 1100.00 197.85 17399.95 182100.00 1100.00 1100.00 1
CSCG99.28 11999.35 9199.05 25799.99 5297.15 351100.00 199.47 8497.44 20199.42 267100.00 197.83 177100.00 199.99 76100.00 1100.00 1
PatchMatch-RL99.02 15998.78 17099.74 14099.99 5299.29 179100.00 1100.00 198.38 10599.89 19999.81 31893.14 31199.99 10797.85 32699.98 11799.95 149
API-MVS99.72 3299.70 2499.79 12899.97 9799.37 17299.96 30699.94 2798.48 98100.00 1100.00 198.92 126100.00 1100.00 1100.00 1100.00 1
Test By Simon99.10 98
TDRefinement91.93 42890.48 43796.27 41981.60 49892.65 44499.10 46297.61 48493.96 40193.77 45799.85 30880.03 45299.53 30797.82 33170.59 48196.63 460
USDC95.90 38295.70 37296.50 41298.60 38992.56 445100.00 198.30 46597.77 15796.92 41799.94 28681.25 45199.45 32393.54 42694.96 35697.49 436
EPP-MVSNet99.10 14299.00 14199.40 20499.51 27098.68 23999.92 33199.43 13395.47 35799.65 250100.00 199.51 4099.76 26599.53 22098.00 27699.75 284
PMMVS99.12 14098.97 14699.58 17399.57 23898.98 217100.00 199.30 27397.14 22499.96 151100.00 196.53 22999.82 24799.70 17098.49 22099.94 154
PAPM99.78 1999.76 1599.85 10499.01 35599.95 37100.00 199.75 5799.37 399.99 127100.00 199.76 1299.60 283100.00 1100.00 1100.00 1
ACMMPcopyleft99.65 5299.57 5599.89 9099.99 5299.66 12599.75 37799.73 6198.16 12199.75 232100.00 198.90 128100.00 199.96 10599.88 151100.00 1
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
CNLPA99.72 3299.65 3799.91 8399.97 9799.72 115100.00 199.47 8498.43 10199.88 202100.00 199.14 96100.00 199.97 103100.00 1100.00 1
PatchmatchNetpermissive99.03 15398.96 14799.26 24599.49 28298.33 27699.38 42699.45 11096.64 28999.96 15199.58 36799.49 4799.50 31397.63 33799.00 20399.93 165
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS99.50 7899.39 8299.82 112100.00 199.45 161100.00 199.94 2796.38 317100.00 1100.00 198.18 160100.00 1100.00 1100.00 1100.00 1
F-COLMAP99.64 5499.64 4099.67 15499.99 5299.07 203100.00 199.44 12498.30 11499.90 196100.00 199.18 9199.99 10799.91 118100.00 199.94 154
ANet_high66.05 46463.44 46873.88 47961.14 50463.45 50195.68 49187.18 50379.93 48147.35 50080.68 50022.35 50372.33 50261.24 49635.42 49885.88 493
wuyk23d28.28 46629.73 47023.92 48475.89 50232.61 50966.50 49512.88 50816.09 50114.59 50316.59 50212.35 50432.36 50339.36 50113.36 5016.79 499
OMC-MVS99.27 12099.38 8398.96 26599.95 10797.06 355100.00 199.40 20598.83 7099.88 202100.00 197.01 20899.86 23199.47 22999.84 16299.97 137
MG-MVS99.75 2699.68 3199.97 40100.00 199.91 6399.98 29099.47 8499.09 12100.00 1100.00 198.59 147100.00 199.95 111100.00 1100.00 1
AdaColmapbinary99.44 8899.26 10299.95 61100.00 199.86 8999.70 38999.99 1398.53 9499.90 196100.00 195.34 247100.00 199.92 116100.00 1100.00 1
uanet0.01 4710.02 4740.00 4850.00 5080.00 5100.00 4960.00 5090.00 5030.00 5040.14 5040.00 5070.00 5040.00 5020.00 5020.00 500
ITE_SJBPF96.84 39798.96 36693.49 43298.12 46998.12 12898.35 36199.97 25684.45 43299.56 29495.63 39595.25 34197.49 436
DeepMVS_CXcopyleft89.98 45998.90 37171.46 49099.18 37097.61 17796.92 41799.83 31186.07 42299.83 24496.02 38297.65 30498.65 332
TinyColmap95.50 38995.12 39496.64 40898.69 38593.00 43899.40 42497.75 48196.40 31696.14 43599.87 30179.47 45599.50 31393.62 42594.72 35997.40 442
MAR-MVS99.49 8099.36 8999.89 9099.97 9799.66 12599.74 37899.95 1997.89 146100.00 1100.00 196.71 223100.00 1100.00 1100.00 1100.00 1
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
LF4IMVS96.19 36796.18 34896.23 42098.26 40692.09 448100.00 197.89 47897.82 15297.94 38599.87 30182.71 44499.38 32997.41 34693.71 36797.20 447
MSDG98.90 18498.63 19599.70 14999.92 11599.25 186100.00 199.37 22895.71 34599.40 273100.00 196.58 22599.95 18296.80 36799.94 13399.91 171
LS3D99.31 11299.13 12699.87 9799.99 5299.71 11699.55 40899.46 10297.32 21299.82 218100.00 196.85 21899.97 14999.14 259100.00 199.92 167
CLD-MVS97.64 28997.74 28297.36 37199.01 35594.76 408100.00 199.34 25299.30 499.00 30599.97 25687.49 40899.57 29099.96 10595.58 32797.75 349
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS77.92 45979.45 45773.34 48076.87 50146.81 50798.24 48399.05 43059.89 49573.55 49198.34 45536.81 49986.55 49380.96 48091.35 40686.65 492
Gipumacopyleft84.73 45083.50 45488.40 46397.50 44182.21 48188.87 49299.05 43065.81 49285.71 48390.49 48953.70 48996.31 47078.64 48591.74 39686.67 491
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015