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 1599.39 1799.77 4799.63 12099.59 6899.36 19499.46 16899.07 1399.79 2699.82 4998.85 4199.92 8098.68 10899.87 4099.82 36
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 5699.19 6199.64 7799.82 3799.23 11499.62 6699.55 6498.94 3399.63 7399.95 295.82 17299.94 5499.37 2199.97 399.73 81
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 13199.37 1997.12 31599.60 13491.75 35098.61 32799.44 18999.35 199.83 1799.85 2998.70 6299.81 15699.02 5799.91 1699.81 41
PLCcopyleft97.94 499.02 10498.85 10999.53 9899.66 11099.01 14199.24 23399.52 8896.85 23899.27 15799.48 23098.25 9499.91 9197.76 19899.62 12499.65 113
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
ACMM97.58 598.37 16298.34 15798.48 24199.41 18097.10 25899.56 9899.45 18098.53 6499.04 20799.85 2993.00 25799.71 19598.74 9797.45 24198.64 273
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
COLMAP_ROBcopyleft97.56 698.86 11998.75 12199.17 15599.88 1198.53 19299.34 20399.59 4397.55 17198.70 25999.89 1095.83 17199.90 10698.10 16999.90 2399.08 197
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 12798.64 13299.47 11499.42 17799.08 13399.62 6699.36 22797.39 19299.28 15499.68 14696.44 15199.92 8098.37 14998.22 20499.40 174
ACMH97.28 898.10 18697.99 18498.44 25099.41 18096.96 27599.60 7399.56 5698.09 11298.15 30099.91 590.87 30899.70 20198.88 7297.45 24198.67 261
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
3Dnovator97.25 999.24 6699.05 7499.81 3899.12 25199.66 5499.84 699.74 1099.09 1098.92 22699.90 795.94 16699.98 698.95 6399.92 1199.79 53
ACMH+97.24 1097.92 21397.78 20798.32 26199.46 17096.68 28599.56 9899.54 7198.41 7597.79 31499.87 2090.18 31599.66 20998.05 17897.18 25398.62 283
ACMP97.20 1198.06 19097.94 19298.45 24799.37 19197.01 26999.44 15599.49 12897.54 17498.45 28399.79 8891.95 28799.72 18997.91 18597.49 23998.62 283
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
LTVRE_ROB97.16 1298.02 19897.90 19598.40 25499.23 22596.80 28199.70 3599.60 4097.12 21598.18 29999.70 13391.73 29399.72 18998.39 14597.45 24198.68 254
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 7198.97 9199.82 3599.17 24499.68 4999.81 1299.51 10199.20 498.72 25299.89 1095.68 17799.97 1198.86 7999.86 5199.81 41
PCF-MVS97.08 1497.66 25897.06 27999.47 11499.61 13099.09 13298.04 35099.25 26891.24 34398.51 27999.70 13394.55 22399.91 9192.76 33699.85 5899.42 171
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
TAPA-MVS97.07 1597.74 24397.34 26398.94 18099.70 9397.53 24499.25 23199.51 10191.90 34099.30 14999.63 17298.78 4899.64 21688.09 35199.87 4099.65 113
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
OpenMVScopyleft96.50 1698.47 15298.12 17099.52 10499.04 26799.53 8099.82 1099.72 1194.56 32298.08 30299.88 1594.73 21499.98 697.47 22999.76 9699.06 203
PVSNet96.02 1798.85 12798.84 11098.89 19399.73 7597.28 25098.32 34399.60 4097.86 13599.50 10399.57 19596.75 14199.86 12598.56 12999.70 10999.54 143
IB-MVS95.67 1896.22 29695.44 30698.57 23199.21 23196.70 28398.65 32597.74 34996.71 24697.27 32298.54 33386.03 34599.92 8098.47 14086.30 34699.10 192
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 30195.47 30497.94 28699.31 20794.34 33597.81 35299.70 1597.12 21597.46 31898.75 32789.71 31999.79 16497.69 20881.69 35299.68 103
OpenMVS_ROBcopyleft92.34 2094.38 31793.70 32196.41 32797.38 34193.17 34599.06 26698.75 32086.58 35094.84 34598.26 34081.53 35599.32 26689.01 34797.87 21996.76 349
MVEpermissive76.82 2176.91 33174.31 33584.70 34185.38 36576.05 36496.88 35693.17 36567.39 36071.28 36289.01 36121.66 37287.69 36171.74 36072.29 35890.35 357
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PMVScopyleft70.75 2275.98 33274.97 33379.01 34670.98 36755.18 36893.37 35998.21 34065.08 36361.78 36493.83 35521.74 37192.53 35978.59 35891.12 33889.34 358
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
CMPMVSbinary69.68 2394.13 31894.90 31091.84 33697.24 34580.01 35998.52 33399.48 14089.01 34791.99 35199.67 15285.67 34799.13 29595.44 30197.03 25696.39 351
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
GeoE98.85 12798.62 13899.53 9899.61 13099.08 13399.80 1799.51 10197.10 21999.31 14799.78 9595.23 19499.77 17098.21 15999.03 16499.75 69
test_method91.10 32291.36 32590.31 33995.85 35173.72 36594.89 35799.25 26868.39 35995.82 34099.02 31280.50 35698.95 32493.64 32594.89 30598.25 324
Anonymous2024052196.20 29895.89 29997.13 31497.72 33894.96 32799.79 2199.29 26393.01 33697.20 32599.03 31089.69 32098.36 33491.16 34196.13 27398.07 330
hse-mvs397.70 25197.28 26998.97 17699.70 9397.27 25199.36 19499.45 18098.94 3399.66 6499.64 16694.93 19999.99 199.48 1484.36 34899.65 113
hse-mvs297.50 26997.14 27698.59 22799.49 16097.05 26499.28 21599.22 27298.94 3399.66 6499.42 24494.93 19999.65 21399.48 1483.80 35099.08 197
CL-MVSNet_2432*160094.49 31593.97 31896.08 32896.16 35093.67 34298.33 34299.38 21795.13 30997.33 32198.15 34192.69 27096.57 35488.67 34879.87 35497.99 337
KD-MVS_2432*160094.62 31393.72 31997.31 31097.19 34795.82 30698.34 34099.20 27695.00 31497.57 31698.35 33787.95 33998.10 33792.87 33477.00 35698.01 334
DIV-MVS_2432*160095.00 31094.34 31596.96 31897.07 34995.39 31899.56 9899.44 18995.11 31197.13 32797.32 34891.86 28997.27 35090.35 34481.23 35398.23 326
AUN-MVS96.88 28596.31 29098.59 22799.48 16797.04 26799.27 22099.22 27297.44 18698.51 27999.41 24891.97 28699.66 20997.71 20583.83 34999.07 202
ZD-MVS99.71 8699.79 3099.61 3596.84 23999.56 9199.54 20798.58 7099.96 1996.93 26499.75 97
test117299.43 3399.29 4599.85 2599.75 6299.82 2099.60 7399.56 5698.28 8999.74 4199.79 8898.53 7299.95 4398.55 13299.78 8999.79 53
SR-MVS-dyc-post99.45 2699.31 3899.85 2599.76 5299.82 2099.63 6099.52 8898.38 7799.76 3799.82 4998.53 7299.95 4398.61 11899.81 8099.77 63
RE-MVS-def99.34 2699.76 5299.82 2099.63 6099.52 8898.38 7799.76 3799.82 4998.75 5698.61 11899.81 8099.77 63
SED-MVS99.61 299.52 699.88 699.84 3299.90 199.60 7399.48 14099.08 1199.91 199.81 6299.20 599.96 1998.91 6999.85 5899.79 53
IU-MVS99.84 3299.88 799.32 25198.30 8899.84 1398.86 7999.85 5899.89 2
OPU-MVS99.64 7799.56 14499.72 4299.60 7399.70 13399.27 499.42 24698.24 15899.80 8499.79 53
test_241102_TWO99.48 14099.08 1199.88 599.81 6298.94 3199.96 1998.91 6999.84 6599.88 5
test_241102_ONE99.84 3299.90 199.48 14099.07 1399.91 199.74 11799.20 599.76 175
xxxxxxxxxxxxxcwj99.43 3399.32 3199.75 5199.76 5299.59 6899.14 25199.53 8299.00 2299.71 4699.80 7698.95 2899.93 6998.19 16199.84 6599.74 74
SF-MVS99.38 4799.24 5699.79 4399.79 4299.68 4999.57 9199.54 7197.82 14599.71 4699.80 7698.95 2899.93 6998.19 16199.84 6599.74 74
ETH3D cwj APD-0.1699.06 9898.84 11099.72 6199.51 15199.60 6599.23 23499.44 18997.04 22499.39 13099.67 15298.30 9199.92 8097.27 23999.69 11099.64 120
cl-mvsnet297.85 22197.64 22498.48 24199.09 25897.87 23298.60 32999.33 24397.11 21898.87 23499.22 29092.38 28299.17 29098.21 15995.99 27798.42 313
miper_ehance_all_eth98.18 17798.10 17198.41 25299.23 22597.72 24098.72 31999.31 25496.60 25798.88 23299.29 28097.29 12399.13 29597.60 21395.99 27798.38 318
miper_enhance_ethall98.16 17998.08 17598.41 25298.96 27997.72 24098.45 33699.32 25196.95 23298.97 21999.17 29597.06 13099.22 28197.86 18995.99 27798.29 321
ZNCC-MVS99.47 2299.33 2899.87 1199.87 1599.81 2499.64 5899.67 2298.08 11699.55 9599.64 16698.91 3699.96 1998.72 10199.90 2399.82 36
ETH3 D test640098.70 14098.35 15699.73 5899.69 9699.60 6599.16 24599.45 18095.42 30799.27 15799.60 18597.39 11799.91 9195.36 30599.83 7299.70 96
cl-mvsnet____98.01 20197.84 20298.55 23599.25 22397.97 22598.71 32099.34 23696.47 26998.59 27699.54 20795.65 17999.21 28697.21 24395.77 28398.46 310
cl-mvsnet198.01 20197.85 20198.48 24199.24 22497.95 22998.71 32099.35 23296.50 26298.60 27599.54 20795.72 17699.03 30897.21 24395.77 28398.46 310
eth_miper_zixun_eth98.05 19597.96 18898.33 25999.26 21997.38 24898.56 33299.31 25496.65 25198.88 23299.52 21496.58 14599.12 29997.39 23695.53 29198.47 306
9.1499.10 6999.72 8099.40 17899.51 10197.53 17699.64 7299.78 9598.84 4299.91 9197.63 21199.82 78
testtj99.12 8598.87 10499.86 1899.72 8099.79 3099.44 15599.51 10197.29 19999.59 8699.74 11798.15 10099.96 1996.74 27299.69 11099.81 41
uanet_test0.02 3390.03 3420.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 3680.27 3680.00 3730.00 3680.00 3660.00 3660.00 364
ETH3D-3000-0.199.21 6799.02 8299.77 4799.73 7599.69 4799.38 18799.51 10197.45 18399.61 7999.75 11198.51 7599.91 9197.45 23299.83 7299.71 94
save fliter99.76 5299.59 6899.14 25199.40 20799.00 22
ET-MVSNet_ETH3D96.49 29295.64 30399.05 16599.53 14798.82 17098.84 30797.51 35197.63 16484.77 35499.21 29392.09 28598.91 32698.98 6092.21 33599.41 173
UniMVSNet_ETH3D97.32 27796.81 28398.87 20099.40 18597.46 24699.51 12099.53 8295.86 30398.54 27899.77 10282.44 35499.66 20998.68 10897.52 23399.50 157
EIA-MVS99.18 7199.09 7199.45 11799.49 16099.18 11899.67 4499.53 8297.66 16299.40 12899.44 23998.10 10199.81 15698.94 6499.62 12499.35 177
miper_refine_blended94.62 31393.72 31997.31 31097.19 34795.82 30698.34 34099.20 27695.00 31497.57 31698.35 33787.95 33998.10 33792.87 33477.00 35698.01 334
miper_lstm_enhance98.00 20397.91 19498.28 26799.34 19897.43 24798.88 30399.36 22796.48 26798.80 24499.55 20295.98 16298.91 32697.27 23995.50 29298.51 302
ETV-MVS99.26 6399.21 5999.40 12399.46 17099.30 10699.56 9899.52 8898.52 6599.44 11599.27 28598.41 8599.86 12599.10 5099.59 12699.04 204
CS-MVS99.37 4899.33 2899.51 10699.47 16899.51 8599.81 1299.57 5098.37 8099.65 6999.56 19898.21 9599.77 17099.54 599.77 9299.27 184
D2MVS98.41 15898.50 14898.15 27499.26 21996.62 28799.40 17899.61 3597.71 15598.98 21799.36 26296.04 16199.67 20698.70 10397.41 24598.15 328
DVP-MVS99.57 799.47 999.88 699.85 2599.89 399.57 9199.37 22699.10 899.81 2299.80 7698.94 3199.96 1998.93 6699.86 5199.81 41
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_THIRD98.99 2599.81 2299.80 7699.09 1299.96 1998.85 8199.90 2399.88 5
test_0728_SECOND99.91 299.84 3299.89 399.57 9199.51 10199.96 1998.93 6699.86 5199.88 5
test072699.85 2599.89 399.62 6699.50 12099.10 899.86 1199.82 4998.94 31
SR-MVS99.43 3399.29 4599.86 1899.75 6299.83 1499.59 7999.62 3398.21 9899.73 4399.79 8898.68 6399.96 1998.44 14399.77 9299.79 53
DPM-MVS98.95 11298.71 12499.66 6899.63 12099.55 7598.64 32699.10 28797.93 13199.42 11999.55 20298.67 6699.80 16195.80 29499.68 11599.61 128
GST-MVS99.40 4599.24 5699.85 2599.86 2199.79 3099.60 7399.67 2297.97 12899.63 7399.68 14698.52 7499.95 4398.38 14799.86 5199.81 41
test_yl98.86 11998.63 13399.54 9299.49 16099.18 11899.50 12699.07 29298.22 9699.61 7999.51 21895.37 18699.84 13698.60 12198.33 19899.59 134
thisisatest053098.35 16398.03 18099.31 13499.63 12098.56 18999.54 11096.75 35697.53 17699.73 4399.65 15991.25 30499.89 11498.62 11599.56 12799.48 159
Anonymous2024052998.09 18797.68 21999.34 12899.66 11098.44 20499.40 17899.43 19793.67 32999.22 17099.89 1090.23 31499.93 6999.26 3598.33 19899.66 109
Anonymous20240521198.30 16797.98 18599.26 14699.57 14098.16 21699.41 17098.55 33596.03 30199.19 17999.74 11791.87 28899.92 8099.16 4598.29 20399.70 96
DCV-MVSNet98.86 11998.63 13399.54 9299.49 16099.18 11899.50 12699.07 29298.22 9699.61 7999.51 21895.37 18699.84 13698.60 12198.33 19899.59 134
tttt051798.42 15698.14 16899.28 14499.66 11098.38 20899.74 3196.85 35497.68 15899.79 2699.74 11791.39 30199.89 11498.83 8699.56 12799.57 139
our_test_397.65 25997.68 21997.55 30598.62 31894.97 32698.84 30799.30 25896.83 24198.19 29899.34 26897.01 13299.02 31095.00 31196.01 27598.64 273
thisisatest051598.14 18297.79 20499.19 15399.50 15898.50 19998.61 32796.82 35596.95 23299.54 9699.43 24191.66 29799.86 12598.08 17499.51 13199.22 186
ppachtmachnet_test97.49 27297.45 24397.61 30298.62 31895.24 32098.80 31199.46 16896.11 29698.22 29799.62 17896.45 15098.97 32293.77 32395.97 28098.61 292
SMA-MVScopyleft99.44 3099.30 4199.85 2599.73 7599.83 1499.56 9899.47 15897.45 18399.78 3199.82 4999.18 899.91 9198.79 9299.89 3399.81 41
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
GSMVS99.52 148
DPE-MVScopyleft99.46 2499.32 3199.91 299.78 4499.88 799.36 19499.51 10198.73 5399.88 599.84 3898.72 6099.96 1998.16 16699.87 4099.88 5
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
test_part299.81 4099.83 1499.77 33
test_part197.75 24097.24 27399.29 14199.59 13699.63 6099.65 5599.49 12896.17 28998.44 28499.69 14089.80 31899.47 23398.68 10893.66 32198.78 225
thres100view90097.76 23697.45 24398.69 22299.72 8097.86 23499.59 7998.74 32397.93 13199.26 16298.62 33091.75 29199.83 14593.22 32998.18 20898.37 319
tfpnnormal97.84 22497.47 24098.98 17499.20 23399.22 11599.64 5899.61 3596.32 27698.27 29699.70 13393.35 25299.44 24195.69 29695.40 29398.27 322
tfpn200view997.72 24697.38 25698.72 22099.69 9697.96 22799.50 12698.73 32897.83 14099.17 18398.45 33591.67 29599.83 14593.22 32998.18 20898.37 319
cl_fuxian98.12 18598.04 17998.38 25699.30 20897.69 24398.81 31099.33 24396.67 24998.83 24099.34 26897.11 12798.99 31497.58 21595.34 29498.48 304
CHOSEN 280x42099.12 8599.13 6699.08 16199.66 11097.89 23198.43 33799.71 1398.88 3999.62 7799.76 10696.63 14499.70 20199.46 1799.99 199.66 109
CANet99.25 6599.14 6599.59 8499.41 18099.16 12199.35 20099.57 5098.82 4499.51 10299.61 18296.46 14999.95 4399.59 199.98 299.65 113
Fast-Effi-MVS+-dtu98.77 13798.83 11498.60 22699.41 18096.99 27199.52 11699.49 12898.11 10999.24 16599.34 26896.96 13499.79 16497.95 18399.45 13299.02 207
Effi-MVS+-dtu98.78 13598.89 10298.47 24599.33 19996.91 27799.57 9199.30 25898.47 6899.41 12398.99 31496.78 13899.74 17898.73 9999.38 13698.74 237
CANet_DTU98.97 11198.87 10499.25 14799.33 19998.42 20799.08 26299.30 25899.16 599.43 11699.75 11195.27 19099.97 1198.56 12999.95 699.36 176
MVS_030496.79 28796.52 28797.59 30399.22 22994.92 32899.04 27399.59 4396.49 26398.43 28598.99 31480.48 35799.39 24897.15 25199.27 14498.47 306
MP-MVS-pluss99.37 4899.20 6099.88 699.90 399.87 999.30 20999.52 8897.18 20999.60 8399.79 8898.79 4799.95 4398.83 8699.91 1699.83 29
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MSP-MVS99.42 3899.27 5199.88 699.89 899.80 2699.67 4499.50 12098.70 5599.77 3399.49 22498.21 9599.95 4398.46 14199.77 9299.88 5
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_mvs194.86 20499.52 148
sam_mvs94.72 215
IterMVS-SCA-FT97.82 22997.75 21398.06 27899.57 14096.36 29599.02 27799.49 12897.18 20998.71 25399.72 12892.72 26699.14 29297.44 23395.86 28298.67 261
TSAR-MVS + MP.99.58 499.50 899.81 3899.91 199.66 5499.63 6099.39 21198.91 3899.78 3199.85 2999.36 299.94 5498.84 8399.88 3699.82 36
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_debu99.29 5899.27 5199.34 12899.63 12098.97 14699.12 25399.51 10198.86 4099.84 1399.47 23398.18 9799.99 199.50 999.31 14199.08 197
OPM-MVS98.19 17598.10 17198.45 24798.88 28597.07 26299.28 21599.38 21798.57 6299.22 17099.81 6292.12 28499.66 20998.08 17497.54 23298.61 292
ACMMP_NAP99.47 2299.34 2699.88 699.87 1599.86 1099.47 14799.48 14098.05 12299.76 3799.86 2398.82 4499.93 6998.82 9099.91 1699.84 18
ambc93.06 33492.68 35782.36 35698.47 33598.73 32895.09 34397.41 34555.55 36399.10 30296.42 28391.32 33797.71 344
zzz-MVS99.49 1599.36 2199.89 499.90 399.86 1099.36 19499.47 15898.79 4999.68 5399.81 6298.43 8199.97 1198.88 7299.90 2399.83 29
MTGPAbinary99.47 158
mvs-test198.86 11998.84 11098.89 19399.33 19997.77 23799.44 15599.30 25898.47 6899.10 19499.43 24196.78 13899.95 4398.73 9999.02 16698.96 214
Effi-MVS+98.81 13198.59 14499.48 11199.46 17099.12 13098.08 34999.50 12097.50 17999.38 13399.41 24896.37 15399.81 15699.11 4998.54 19299.51 154
xiu_mvs_v2_base99.26 6399.25 5599.29 14199.53 14798.91 15999.02 27799.45 18098.80 4899.71 4699.26 28698.94 3199.98 699.34 2699.23 14698.98 211
xiu_mvs_v1_base99.29 5899.27 5199.34 12899.63 12098.97 14699.12 25399.51 10198.86 4099.84 1399.47 23398.18 9799.99 199.50 999.31 14199.08 197
new-patchmatchnet94.48 31694.08 31695.67 33095.08 35592.41 34899.18 24399.28 26594.55 32393.49 34897.37 34787.86 34197.01 35291.57 33988.36 34397.61 345
pmmvs696.53 29196.09 29497.82 29598.69 31295.47 31599.37 19099.47 15893.46 33397.41 31999.78 9587.06 34399.33 26596.92 26692.70 33398.65 271
pmmvs597.52 26697.30 26898.16 27398.57 32396.73 28299.27 22098.90 31196.14 29498.37 28999.53 21191.54 30099.14 29297.51 22595.87 28198.63 281
test_post199.23 23465.14 36594.18 23699.71 19597.58 215
test_post65.99 36494.65 21999.73 185
Fast-Effi-MVS+98.70 14098.43 15199.51 10699.51 15199.28 10899.52 11699.47 15896.11 29699.01 21099.34 26896.20 15899.84 13697.88 18798.82 17999.39 175
patchmatchnet-post98.70 32894.79 20799.74 178
Anonymous2023121197.88 21697.54 23398.90 19099.71 8698.53 19299.48 14299.57 5094.16 32598.81 24299.68 14693.23 25399.42 24698.84 8394.42 31198.76 231
pmmvs-eth3d95.34 30994.73 31197.15 31295.53 35495.94 30499.35 20099.10 28795.13 30993.55 34797.54 34488.15 33797.91 34294.58 31489.69 34297.61 345
GG-mvs-BLEND98.45 24798.55 32498.16 21699.43 16193.68 36497.23 32398.46 33489.30 32499.22 28195.43 30298.22 20497.98 338
xiu_mvs_v1_base_debi99.29 5899.27 5199.34 12899.63 12098.97 14699.12 25399.51 10198.86 4099.84 1399.47 23398.18 9799.99 199.50 999.31 14199.08 197
Anonymous2023120696.22 29696.03 29596.79 32397.31 34494.14 33699.63 6099.08 29096.17 28997.04 32999.06 30793.94 24297.76 34686.96 35495.06 30098.47 306
MTAPA99.52 1399.39 1799.89 499.90 399.86 1099.66 4899.47 15898.79 4999.68 5399.81 6298.43 8199.97 1198.88 7299.90 2399.83 29
MTMP99.54 11098.88 313
gm-plane-assit98.54 32592.96 34694.65 32199.15 29899.64 21697.56 220
test9_res97.49 22699.72 10499.75 69
MVP-Stereo97.81 23197.75 21397.99 28497.53 33996.60 28898.96 29298.85 31597.22 20797.23 32399.36 26295.28 18999.46 23595.51 30099.78 8997.92 342
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
TEST999.67 10199.65 5799.05 26899.41 20196.22 28598.95 22199.49 22498.77 5199.91 91
train_agg99.02 10498.77 11899.77 4799.67 10199.65 5799.05 26899.41 20196.28 27898.95 22199.49 22498.76 5399.91 9197.63 21199.72 10499.75 69
gg-mvs-nofinetune96.17 29995.32 30798.73 21898.79 29798.14 21899.38 18794.09 36391.07 34598.07 30591.04 35989.62 32299.35 26196.75 27199.09 15998.68 254
SCA98.19 17598.16 16698.27 26899.30 20895.55 31199.07 26398.97 30097.57 16999.43 11699.57 19592.72 26699.74 17897.58 21599.20 14899.52 148
Patchmatch-test97.93 21097.65 22298.77 21699.18 23897.07 26299.03 27499.14 28496.16 29198.74 25099.57 19594.56 22299.72 18993.36 32899.11 15599.52 148
test_899.67 10199.61 6399.03 27499.41 20196.28 27898.93 22599.48 23098.76 5399.91 91
MS-PatchMatch97.24 28097.32 26696.99 31698.45 32893.51 34498.82 30999.32 25197.41 19098.13 30199.30 27888.99 32699.56 22795.68 29799.80 8497.90 343
Patchmatch-RL test95.84 30395.81 30195.95 32995.61 35290.57 35298.24 34598.39 33795.10 31395.20 34298.67 32994.78 20897.77 34596.28 28690.02 34099.51 154
cdsmvs_eth3d_5k24.64 33632.85 3390.00 3500.00 3710.00 3720.00 36299.51 1010.00 3670.00 36899.56 19896.58 1450.00 3680.00 3660.00 3660.00 364
pcd_1.5k_mvsjas8.27 33811.03 3410.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 3680.27 36899.01 160.00 3680.00 3660.00 3660.00 364
agg_prior199.01 10798.76 12099.76 5099.67 10199.62 6198.99 28499.40 20796.26 28198.87 23499.49 22498.77 5199.91 9197.69 20899.72 10499.75 69
agg_prior297.21 24399.73 10399.75 69
agg_prior99.67 10199.62 6199.40 20798.87 23499.91 91
tmp_tt82.80 32781.52 33086.66 34066.61 36868.44 36692.79 36097.92 34568.96 35880.04 36199.85 2985.77 34696.15 35797.86 18943.89 36295.39 353
canonicalmvs99.02 10498.86 10899.51 10699.42 17799.32 10299.80 1799.48 14098.63 5899.31 14798.81 32397.09 12899.75 17799.27 3497.90 21899.47 164
anonymousdsp98.44 15498.28 16298.94 18098.50 32698.96 15099.77 2499.50 12097.07 22198.87 23499.77 10294.76 21299.28 27198.66 11197.60 22698.57 298
alignmvs98.81 13198.56 14699.58 8799.43 17699.42 9599.51 12098.96 30298.61 6099.35 14198.92 32094.78 20899.77 17099.35 2298.11 21499.54 143
nrg03098.64 14798.42 15299.28 14499.05 26699.69 4799.81 1299.46 16898.04 12399.01 21099.82 4996.69 14399.38 25099.34 2694.59 30898.78 225
v14419297.92 21397.60 22798.87 20098.83 29598.65 18299.55 10799.34 23696.20 28699.32 14699.40 25194.36 22899.26 27596.37 28595.03 30198.70 245
FIs98.78 13598.63 13399.23 15199.18 23899.54 7799.83 999.59 4398.28 8998.79 24699.81 6296.75 14199.37 25399.08 5296.38 26898.78 225
v192192097.80 23397.45 24398.84 20798.80 29698.53 19299.52 11699.34 23696.15 29399.24 16599.47 23393.98 24199.29 27095.40 30395.13 29998.69 249
UA-Net99.42 3899.29 4599.80 4099.62 12699.55 7599.50 12699.70 1598.79 4999.77 3399.96 197.45 11699.96 1998.92 6899.90 2399.89 2
v119297.81 23197.44 24898.91 18898.88 28598.68 17999.51 12099.34 23696.18 28899.20 17699.34 26894.03 24099.36 25795.32 30695.18 29798.69 249
FC-MVSNet-test98.75 13898.62 13899.15 15899.08 26099.45 9299.86 599.60 4098.23 9598.70 25999.82 4996.80 13799.22 28199.07 5396.38 26898.79 224
v114497.98 20597.69 21898.85 20698.87 28998.66 18199.54 11099.35 23296.27 28099.23 16999.35 26594.67 21799.23 27896.73 27395.16 29898.68 254
sosnet-low-res0.02 3390.03 3420.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 3680.27 3680.00 3730.00 3680.00 3660.00 3660.00 364
HFP-MVS99.49 1599.37 1999.86 1899.87 1599.80 2699.66 4899.67 2298.15 10399.68 5399.69 14099.06 1399.96 1998.69 10699.87 4099.84 18
v14897.79 23497.55 23098.50 23898.74 30597.72 24099.54 11099.33 24396.26 28198.90 22999.51 21894.68 21699.14 29297.83 19293.15 32898.63 281
sosnet0.02 3390.03 3420.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 3680.27 3680.00 3730.00 3680.00 3660.00 3660.00 364
uncertanet0.02 3390.03 3420.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 3680.27 3680.00 3730.00 3680.00 3660.00 3660.00 364
AllTest98.87 11698.72 12299.31 13499.86 2198.48 20299.56 9899.61 3597.85 13799.36 13899.85 2995.95 16499.85 13196.66 27899.83 7299.59 134
TestCases99.31 13499.86 2198.48 20299.61 3597.85 13799.36 13899.85 2995.95 16499.85 13196.66 27899.83 7299.59 134
v7n97.87 21897.52 23498.92 18498.76 30498.58 18899.84 699.46 16896.20 28698.91 22799.70 13394.89 20399.44 24196.03 28993.89 31998.75 233
region2R99.48 1999.35 2499.87 1199.88 1199.80 2699.65 5599.66 2798.13 10599.66 6499.68 14698.96 2599.96 1998.62 11599.87 4099.84 18
bset_n11_16_dypcd98.16 17997.97 18698.73 21898.26 33198.28 21297.99 35198.01 34497.68 15899.10 19499.63 17295.68 17799.15 29198.78 9596.55 26398.75 233
RRT_MVS98.60 14998.44 15099.05 16598.88 28599.14 12699.49 13699.38 21797.76 14999.29 15299.86 2395.38 18599.36 25798.81 9197.16 25498.64 273
PS-MVSNAJss98.92 11498.92 9798.90 19098.78 30098.53 19299.78 2299.54 7198.07 11799.00 21599.76 10699.01 1699.37 25399.13 4797.23 25098.81 222
PS-MVSNAJ99.32 5499.32 3199.30 13899.57 14098.94 15598.97 29199.46 16898.92 3799.71 4699.24 28899.01 1699.98 699.35 2299.66 11898.97 212
jajsoiax98.43 15598.28 16298.88 19698.60 32198.43 20599.82 1099.53 8298.19 9998.63 27099.80 7693.22 25599.44 24199.22 3797.50 23698.77 229
mvs_tets98.40 16098.23 16498.91 18898.67 31498.51 19899.66 4899.53 8298.19 9998.65 26899.81 6292.75 26399.44 24199.31 2997.48 24098.77 229
#test#99.43 3399.29 4599.86 1899.87 1599.80 2699.55 10799.67 2297.83 14099.68 5399.69 14099.06 1399.96 1998.39 14599.87 4099.84 18
EI-MVSNet-UG-set99.58 499.57 199.64 7799.78 4499.14 12699.60 7399.45 18099.01 1899.90 399.83 4298.98 2399.93 6999.59 199.95 699.86 11
EI-MVSNet-Vis-set99.58 499.56 399.64 7799.78 4499.15 12599.61 7299.45 18099.01 1899.89 499.82 4999.01 1699.92 8099.56 499.95 699.85 14
Regformer-399.57 799.53 599.68 6599.76 5299.29 10799.58 8699.44 18999.01 1899.87 1099.80 7698.97 2499.91 9199.44 2099.92 1199.83 29
Regformer-499.59 399.54 499.73 5899.76 5299.41 9699.58 8699.49 12899.02 1599.88 599.80 7699.00 2299.94 5499.45 1899.92 1199.84 18
Regformer-199.53 1199.47 999.72 6199.71 8699.44 9399.49 13699.46 16898.95 3299.83 1799.76 10699.01 1699.93 6999.17 4399.87 4099.80 49
Regformer-299.54 999.47 999.75 5199.71 8699.52 8399.49 13699.49 12898.94 3399.83 1799.76 10699.01 1699.94 5499.15 4699.87 4099.80 49
HPM-MVS++copyleft99.39 4699.23 5899.87 1199.75 6299.84 1399.43 16199.51 10198.68 5799.27 15799.53 21198.64 6899.96 1998.44 14399.80 8499.79 53
test_prior499.56 7398.99 284
XVS99.53 1199.42 1399.87 1199.85 2599.83 1499.69 3799.68 1998.98 2799.37 13599.74 11798.81 4599.94 5498.79 9299.86 5199.84 18
v124097.69 25297.32 26698.79 21498.85 29398.43 20599.48 14299.36 22796.11 29699.27 15799.36 26293.76 24899.24 27794.46 31695.23 29698.70 245
test_prior399.21 6799.05 7499.68 6599.67 10199.48 8898.96 29299.56 5698.34 8399.01 21099.52 21498.68 6399.83 14597.96 18199.74 10099.74 74
pm-mvs197.68 25497.28 26998.88 19699.06 26398.62 18599.50 12699.45 18096.32 27697.87 31099.79 8892.47 27799.35 26197.54 22293.54 32398.67 261
test_prior298.96 29298.34 8399.01 21099.52 21498.68 6397.96 18199.74 100
X-MVStestdata96.55 29095.45 30599.87 1199.85 2599.83 1499.69 3799.68 1998.98 2799.37 13564.01 36698.81 4599.94 5498.79 9299.86 5199.84 18
test_prior99.68 6599.67 10199.48 8899.56 5699.83 14599.74 74
旧先验298.96 29296.70 24799.47 10899.94 5498.19 161
新几何299.01 282
新几何199.75 5199.75 6299.59 6899.54 7196.76 24399.29 15299.64 16698.43 8199.94 5496.92 26699.66 11899.72 87
旧先验199.74 7099.59 6899.54 7199.69 14098.47 7899.68 11599.73 81
无先验98.99 28499.51 10196.89 23699.93 6997.53 22399.72 87
原ACMM298.95 296
原ACMM199.65 7299.73 7599.33 10199.47 15897.46 18099.12 18999.66 15898.67 6699.91 9197.70 20799.69 11099.71 94
test22299.75 6299.49 8798.91 30199.49 12896.42 27299.34 14499.65 15998.28 9399.69 11099.72 87
testdata299.95 4396.67 277
segment_acmp98.96 25
testdata99.54 9299.75 6298.95 15299.51 10197.07 22199.43 11699.70 13398.87 3999.94 5497.76 19899.64 12199.72 87
testdata198.85 30698.32 87
v897.95 20997.63 22598.93 18298.95 28098.81 17299.80 1799.41 20196.03 30199.10 19499.42 24494.92 20199.30 26996.94 26394.08 31798.66 269
131498.68 14398.54 14799.11 16098.89 28498.65 18299.27 22099.49 12896.89 23697.99 30799.56 19897.72 11299.83 14597.74 20199.27 14498.84 221
112199.09 9498.87 10499.75 5199.74 7099.60 6599.27 22099.48 14096.82 24299.25 16499.65 15998.38 8699.93 6997.53 22399.67 11799.73 81
LFMVS97.90 21597.35 26099.54 9299.52 14999.01 14199.39 18298.24 33997.10 21999.65 6999.79 8884.79 34999.91 9199.28 3298.38 19799.69 99
VDD-MVS97.73 24497.35 26098.88 19699.47 16897.12 25799.34 20398.85 31598.19 9999.67 5999.85 2982.98 35199.92 8099.49 1398.32 20299.60 130
VDDNet97.55 26397.02 28099.16 15699.49 16098.12 22099.38 18799.30 25895.35 30899.68 5399.90 782.62 35399.93 6999.31 2998.13 21399.42 171
v1097.85 22197.52 23498.86 20398.99 27398.67 18099.75 2899.41 20195.70 30498.98 21799.41 24894.75 21399.23 27896.01 29094.63 30798.67 261
VPNet97.84 22497.44 24899.01 17099.21 23198.94 15599.48 14299.57 5098.38 7799.28 15499.73 12488.89 32799.39 24899.19 4093.27 32698.71 241
MVS97.28 27896.55 28699.48 11198.78 30098.95 15299.27 22099.39 21183.53 35398.08 30299.54 20796.97 13399.87 12294.23 31999.16 15099.63 124
v2v48298.06 19097.77 20998.92 18498.90 28398.82 17099.57 9199.36 22796.65 25199.19 17999.35 26594.20 23399.25 27697.72 20494.97 30298.69 249
V4298.06 19097.79 20498.86 20398.98 27698.84 16699.69 3799.34 23696.53 26199.30 14999.37 25994.67 21799.32 26697.57 21994.66 30698.42 313
SD-MVS99.41 4299.52 699.05 16599.74 7099.68 4999.46 15099.52 8899.11 799.88 599.91 599.43 197.70 34798.72 10199.93 1099.77 63
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-MVS97.85 22197.47 24099.00 17299.38 18997.99 22498.57 33099.15 28297.04 22498.90 22999.30 27889.83 31799.38 25096.70 27598.33 19899.62 126
MSLP-MVS++99.46 2499.47 999.44 12199.60 13499.16 12199.41 17099.71 1398.98 2799.45 11199.78 9599.19 799.54 23099.28 3299.84 6599.63 124
APDe-MVS99.66 199.57 199.92 199.77 4999.89 399.75 2899.56 5699.02 1599.88 599.85 2999.18 899.96 1999.22 3799.92 1199.90 1
APD-MVS_3200maxsize99.48 1999.35 2499.85 2599.76 5299.83 1499.63 6099.54 7198.36 8199.79 2699.82 4998.86 4099.95 4398.62 11599.81 8099.78 61
ADS-MVSNet298.02 19898.07 17897.87 29199.33 19995.19 32299.23 23499.08 29096.24 28399.10 19499.67 15294.11 23798.93 32596.81 26999.05 16299.48 159
EI-MVSNet98.67 14498.67 12898.68 22399.35 19497.97 22599.50 12699.38 21796.93 23599.20 17699.83 4297.87 10699.36 25798.38 14797.56 23098.71 241
Regformer0.02 3390.03 3420.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 3680.27 3680.00 3730.00 3680.00 3660.00 3660.00 364
CVMVSNet98.57 15098.67 12898.30 26399.35 19495.59 31099.50 12699.55 6498.60 6199.39 13099.83 4294.48 22599.45 23698.75 9698.56 19199.85 14
pmmvs498.13 18397.90 19598.81 21198.61 32098.87 16298.99 28499.21 27596.44 27099.06 20599.58 19195.90 16999.11 30097.18 24996.11 27498.46 310
EU-MVSNet97.98 20598.03 18097.81 29698.72 30896.65 28699.66 4899.66 2798.09 11298.35 29199.82 4995.25 19398.01 34097.41 23595.30 29598.78 225
VNet99.11 9098.90 10099.73 5899.52 14999.56 7399.41 17099.39 21199.01 1899.74 4199.78 9595.56 18099.92 8099.52 798.18 20899.72 87
test-LLR98.06 19097.90 19598.55 23598.79 29797.10 25898.67 32297.75 34797.34 19498.61 27398.85 32194.45 22699.45 23697.25 24199.38 13699.10 192
TESTMET0.1,197.55 26397.27 27298.40 25498.93 28196.53 28998.67 32297.61 35096.96 23098.64 26999.28 28288.63 33199.45 23697.30 23899.38 13699.21 187
test-mter97.49 27297.13 27798.55 23598.79 29797.10 25898.67 32297.75 34796.65 25198.61 27398.85 32188.23 33599.45 23697.25 24199.38 13699.10 192
VPA-MVSNet98.29 16897.95 19099.30 13899.16 24699.54 7799.50 12699.58 4998.27 9199.35 14199.37 25992.53 27599.65 21399.35 2294.46 30998.72 239
ACMMPR99.49 1599.36 2199.86 1899.87 1599.79 3099.66 4899.67 2298.15 10399.67 5999.69 14098.95 2899.96 1998.69 10699.87 4099.84 18
testgi97.65 25997.50 23798.13 27599.36 19396.45 29299.42 16899.48 14097.76 14997.87 31099.45 23891.09 30598.81 32994.53 31598.52 19399.13 191
test20.0396.12 30095.96 29796.63 32497.44 34095.45 31699.51 12099.38 21796.55 26096.16 33799.25 28793.76 24896.17 35687.35 35394.22 31498.27 322
thres600view797.86 22097.51 23698.92 18499.72 8097.95 22999.59 7998.74 32397.94 13099.27 15798.62 33091.75 29199.86 12593.73 32498.19 20798.96 214
ADS-MVSNet98.20 17498.08 17598.56 23399.33 19996.48 29199.23 23499.15 28296.24 28399.10 19499.67 15294.11 23799.71 19596.81 26999.05 16299.48 159
MP-MVScopyleft99.33 5399.15 6499.87 1199.88 1199.82 2099.66 4899.46 16898.09 11299.48 10799.74 11798.29 9299.96 1997.93 18499.87 4099.82 36
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
testmvs39.17 33443.78 33625.37 34936.04 37016.84 37198.36 33826.56 36920.06 36538.51 36667.32 36229.64 36915.30 36737.59 36439.90 36343.98 362
thres40097.77 23597.38 25698.92 18499.69 9697.96 22799.50 12698.73 32897.83 14099.17 18398.45 33591.67 29599.83 14593.22 32998.18 20898.96 214
test12339.01 33542.50 33728.53 34839.17 36920.91 37098.75 31619.17 37119.83 36638.57 36566.67 36333.16 36815.42 36637.50 36529.66 36449.26 361
thres20097.61 26197.28 26998.62 22599.64 11798.03 22199.26 22998.74 32397.68 15899.09 19998.32 33991.66 29799.81 15692.88 33398.22 20498.03 333
test0.0.03 197.71 25097.42 25298.56 23398.41 32997.82 23598.78 31398.63 33297.34 19498.05 30698.98 31794.45 22698.98 31595.04 31097.15 25598.89 218
pmmvs394.09 31993.25 32296.60 32594.76 35694.49 33298.92 29998.18 34289.66 34696.48 33498.06 34286.28 34497.33 34989.68 34687.20 34597.97 339
EMVS80.02 32979.22 33282.43 34591.19 35876.40 36297.55 35592.49 36866.36 36283.01 35791.27 35864.63 36185.79 36365.82 36260.65 36085.08 359
E-PMN80.61 32879.88 33182.81 34390.75 35976.38 36397.69 35395.76 36066.44 36183.52 35592.25 35762.54 36287.16 36268.53 36161.40 35984.89 360
PGM-MVS99.45 2699.31 3899.86 1899.87 1599.78 3799.58 8699.65 3297.84 13999.71 4699.80 7699.12 1199.97 1198.33 15399.87 4099.83 29
LCM-MVSNet-Re97.83 22698.15 16796.87 32199.30 20892.25 34999.59 7998.26 33897.43 18796.20 33699.13 30096.27 15698.73 33198.17 16598.99 16899.64 120
LCM-MVSNet86.80 32585.22 32991.53 33787.81 36280.96 35898.23 34798.99 29871.05 35790.13 35396.51 35148.45 36696.88 35390.51 34285.30 34796.76 349
MCST-MVS99.43 3399.30 4199.82 3599.79 4299.74 4199.29 21399.40 20798.79 4999.52 10099.62 17898.91 3699.90 10698.64 11399.75 9799.82 36
mvs_anonymous99.03 10398.99 8799.16 15699.38 18998.52 19699.51 12099.38 21797.79 14699.38 13399.81 6297.30 12299.45 23699.35 2298.99 16899.51 154
MVS_Test99.10 9398.97 9199.48 11199.49 16099.14 12699.67 4499.34 23697.31 19799.58 8899.76 10697.65 11399.82 15298.87 7699.07 16199.46 166
MDA-MVSNet-bldmvs94.96 31193.98 31797.92 28898.24 33297.27 25199.15 24999.33 24393.80 32880.09 36099.03 31088.31 33497.86 34493.49 32794.36 31298.62 283
CDPH-MVS99.13 7998.91 9999.80 4099.75 6299.71 4499.15 24999.41 20196.60 25799.60 8399.55 20298.83 4399.90 10697.48 22799.83 7299.78 61
test1299.75 5199.64 11799.61 6399.29 26399.21 17398.38 8699.89 11499.74 10099.74 74
casdiffmvs99.13 7998.98 9099.56 9099.65 11599.16 12199.56 9899.50 12098.33 8699.41 12399.86 2395.92 16799.83 14599.45 1899.16 15099.70 96
diffmvs99.14 7799.02 8299.51 10699.61 13098.96 15099.28 21599.49 12898.46 7099.72 4599.71 12996.50 14899.88 11999.31 2999.11 15599.67 106
baseline297.87 21897.55 23098.82 20999.18 23898.02 22299.41 17096.58 35896.97 22996.51 33399.17 29593.43 25099.57 22697.71 20599.03 16498.86 219
baseline198.31 16597.95 19099.38 12699.50 15898.74 17599.59 7998.93 30498.41 7599.14 18699.60 18594.59 22099.79 16498.48 13793.29 32599.61 128
YYNet195.36 30894.51 31497.92 28897.89 33597.10 25899.10 26199.23 27193.26 33580.77 35899.04 30992.81 26298.02 33994.30 31794.18 31598.64 273
PMMVS286.87 32485.37 32891.35 33890.21 36083.80 35598.89 30297.45 35283.13 35491.67 35295.03 35248.49 36594.70 35885.86 35677.62 35595.54 352
MDA-MVSNet_test_wron95.45 30694.60 31298.01 28298.16 33397.21 25699.11 25999.24 27093.49 33280.73 35998.98 31793.02 25698.18 33594.22 32094.45 31098.64 273
tpmvs97.98 20598.02 18297.84 29399.04 26794.73 33199.31 20799.20 27696.10 30098.76 24999.42 24494.94 19899.81 15696.97 26098.45 19698.97 212
PM-MVS92.96 32192.23 32495.14 33195.61 35289.98 35499.37 19098.21 34094.80 31895.04 34497.69 34365.06 36097.90 34394.30 31789.98 34197.54 348
HQP_MVS98.27 17098.22 16598.44 25099.29 21296.97 27399.39 18299.47 15898.97 3099.11 19199.61 18292.71 26899.69 20497.78 19697.63 22398.67 261
plane_prior799.29 21297.03 268
plane_prior699.27 21796.98 27292.71 268
plane_prior599.47 15899.69 20497.78 19697.63 22398.67 261
plane_prior499.61 182
plane_prior397.00 27098.69 5699.11 191
plane_prior299.39 18298.97 30
plane_prior199.26 219
plane_prior96.97 27399.21 24198.45 7197.60 226
PS-CasMVS97.93 21097.59 22998.95 17998.99 27399.06 13699.68 4299.52 8897.13 21398.31 29399.68 14692.44 28199.05 30598.51 13594.08 31798.75 233
UniMVSNet_NR-MVSNet98.22 17197.97 18698.96 17798.92 28298.98 14399.48 14299.53 8297.76 14998.71 25399.46 23796.43 15299.22 28198.57 12692.87 33198.69 249
PEN-MVS97.76 23697.44 24898.72 22098.77 30398.54 19199.78 2299.51 10197.06 22398.29 29599.64 16692.63 27298.89 32898.09 17093.16 32798.72 239
TransMVSNet (Re)97.15 28196.58 28598.86 20399.12 25198.85 16599.49 13698.91 30995.48 30697.16 32699.80 7693.38 25199.11 30094.16 32191.73 33698.62 283
DTE-MVSNet97.51 26897.19 27598.46 24698.63 31798.13 21999.84 699.48 14096.68 24897.97 30899.67 15292.92 25998.56 33296.88 26892.60 33498.70 245
DU-MVS98.08 18997.79 20498.96 17798.87 28998.98 14399.41 17099.45 18097.87 13498.71 25399.50 22194.82 20599.22 28198.57 12692.87 33198.68 254
UniMVSNet (Re)98.29 16898.00 18399.13 15999.00 27299.36 10099.49 13699.51 10197.95 12998.97 21999.13 30096.30 15599.38 25098.36 15193.34 32498.66 269
CP-MVSNet98.09 18797.78 20799.01 17098.97 27899.24 11399.67 4499.46 16897.25 20398.48 28299.64 16693.79 24699.06 30498.63 11494.10 31698.74 237
WR-MVS_H98.13 18397.87 20098.90 19099.02 27098.84 16699.70 3599.59 4397.27 20198.40 28799.19 29495.53 18199.23 27898.34 15293.78 32098.61 292
WR-MVS98.06 19097.73 21599.06 16398.86 29299.25 11299.19 24299.35 23297.30 19898.66 26299.43 24193.94 24299.21 28698.58 12494.28 31398.71 241
NR-MVSNet97.97 20897.61 22699.02 16998.87 28999.26 11199.47 14799.42 19997.63 16497.08 32899.50 22195.07 19799.13 29597.86 18993.59 32298.68 254
Baseline_NR-MVSNet97.76 23697.45 24398.68 22399.09 25898.29 21099.41 17098.85 31595.65 30598.63 27099.67 15294.82 20599.10 30298.07 17792.89 33098.64 273
TranMVSNet+NR-MVSNet97.93 21097.66 22198.76 21798.78 30098.62 18599.65 5599.49 12897.76 14998.49 28199.60 18594.23 23298.97 32298.00 17992.90 32998.70 245
TSAR-MVS + GP.99.36 5099.36 2199.36 12799.67 10198.61 18799.07 26399.33 24399.00 2299.82 2099.81 6299.06 1399.84 13699.09 5199.42 13499.65 113
abl_699.44 3099.31 3899.83 3399.85 2599.75 3899.66 4899.59 4398.13 10599.82 2099.81 6298.60 6999.96 1998.46 14199.88 3699.79 53
n20.00 372
nn0.00 372
mPP-MVS99.44 3099.30 4199.86 1899.88 1199.79 3099.69 3799.48 14098.12 10799.50 10399.75 11198.78 4899.97 1198.57 12699.89 3399.83 29
door-mid98.05 343
XVG-OURS-SEG-HR98.69 14298.62 13898.89 19399.71 8697.74 23899.12 25399.54 7198.44 7499.42 11999.71 12994.20 23399.92 8098.54 13498.90 17599.00 208
DWT-MVSNet_test97.53 26597.40 25497.93 28799.03 26994.86 32999.57 9198.63 33296.59 25998.36 29098.79 32489.32 32399.74 17898.14 16898.16 21299.20 188
MVSFormer99.17 7399.12 6799.29 14199.51 15198.94 15599.88 199.46 16897.55 17199.80 2499.65 15997.39 11799.28 27199.03 5599.85 5899.65 113
jason99.13 7999.03 7999.45 11799.46 17098.87 16299.12 25399.26 26698.03 12599.79 2699.65 15997.02 13199.85 13199.02 5799.90 2399.65 113
jason: jason.
lupinMVS99.13 7999.01 8699.46 11699.51 15198.94 15599.05 26899.16 28197.86 13599.80 2499.56 19897.39 11799.86 12598.94 6499.85 5899.58 138
test_djsdf98.67 14498.57 14598.98 17498.70 31198.91 15999.88 199.46 16897.55 17199.22 17099.88 1595.73 17599.28 27199.03 5597.62 22598.75 233
HPM-MVS_fast99.51 1499.40 1699.85 2599.91 199.79 3099.76 2799.56 5697.72 15499.76 3799.75 11199.13 1099.92 8099.07 5399.92 1199.85 14
RRT_test8_iter0597.72 24697.60 22798.08 27699.23 22596.08 30299.63 6099.49 12897.54 17498.94 22399.81 6287.99 33899.35 26199.21 3996.51 26598.81 222
K. test v397.10 28396.79 28498.01 28298.72 30896.33 29699.87 497.05 35397.59 16696.16 33799.80 7688.71 32899.04 30696.69 27696.55 26398.65 271
lessismore_v097.79 29798.69 31295.44 31794.75 36195.71 34199.87 2088.69 32999.32 26695.89 29194.93 30498.62 283
SixPastTwentyTwo97.50 26997.33 26598.03 27998.65 31596.23 29999.77 2498.68 33197.14 21297.90 30999.93 490.45 30999.18 28997.00 25796.43 26798.67 261
OurMVSNet-221017-097.88 21697.77 20998.19 27198.71 31096.53 28999.88 199.00 29797.79 14698.78 24799.94 391.68 29499.35 26197.21 24396.99 25798.69 249
HPM-MVScopyleft99.42 3899.28 4999.83 3399.90 399.72 4299.81 1299.54 7197.59 16699.68 5399.63 17298.91 3699.94 5498.58 12499.91 1699.84 18
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
XVG-OURS98.73 13998.68 12798.88 19699.70 9397.73 23998.92 29999.55 6498.52 6599.45 11199.84 3895.27 19099.91 9198.08 17498.84 17899.00 208
XVG-ACMP-BASELINE97.83 22697.71 21798.20 27099.11 25396.33 29699.41 17099.52 8898.06 12199.05 20699.50 22189.64 32199.73 18597.73 20297.38 24798.53 300
LPG-MVS_test98.22 17198.13 16998.49 23999.33 19997.05 26499.58 8699.55 6497.46 18099.24 16599.83 4292.58 27399.72 18998.09 17097.51 23498.68 254
LGP-MVS_train98.49 23999.33 19997.05 26499.55 6497.46 18099.24 16599.83 4292.58 27399.72 18998.09 17097.51 23498.68 254
baseline99.15 7699.02 8299.53 9899.66 11099.14 12699.72 3299.48 14098.35 8299.42 11999.84 3896.07 16099.79 16499.51 899.14 15399.67 106
test1199.35 232
door97.92 345
EPNet_dtu98.03 19697.96 18898.23 26998.27 33095.54 31399.23 23498.75 32099.02 1597.82 31299.71 12996.11 15999.48 23293.04 33299.65 12099.69 99
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
CHOSEN 1792x268899.19 6999.10 6999.45 11799.89 898.52 19699.39 18299.94 198.73 5399.11 19199.89 1095.50 18299.94 5499.50 999.97 399.89 2
EPNet98.86 11998.71 12499.30 13897.20 34698.18 21599.62 6698.91 30999.28 298.63 27099.81 6295.96 16399.99 199.24 3699.72 10499.73 81
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
HQP5-MVS96.83 278
HQP-NCC99.19 23598.98 28898.24 9298.66 262
ACMP_Plane99.19 23598.98 28898.24 9298.66 262
APD-MVScopyleft99.27 6199.08 7299.84 3299.75 6299.79 3099.50 12699.50 12097.16 21199.77 3399.82 4998.78 4899.94 5497.56 22099.86 5199.80 49
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
BP-MVS97.19 247
HQP4-MVS98.66 26299.64 21698.64 273
HQP3-MVS99.39 21197.58 228
HQP2-MVS92.47 277
CNVR-MVS99.42 3899.30 4199.78 4599.62 12699.71 4499.26 22999.52 8898.82 4499.39 13099.71 12998.96 2599.85 13198.59 12399.80 8499.77 63
NCCC99.34 5299.19 6199.79 4399.61 13099.65 5799.30 20999.48 14098.86 4099.21 17399.63 17298.72 6099.90 10698.25 15799.63 12399.80 49
114514_t98.93 11398.67 12899.72 6199.85 2599.53 8099.62 6699.59 4392.65 33899.71 4699.78 9598.06 10399.90 10698.84 8399.91 1699.74 74
CP-MVS99.45 2699.32 3199.85 2599.83 3699.75 3899.69 3799.52 8898.07 11799.53 9899.63 17298.93 3599.97 1198.74 9799.91 1699.83 29
DSMNet-mixed97.25 27997.35 26096.95 31997.84 33693.61 34399.57 9196.63 35796.13 29598.87 23498.61 33294.59 22097.70 34795.08 30998.86 17799.55 141
tpm297.44 27497.34 26397.74 29999.15 24994.36 33499.45 15198.94 30393.45 33498.90 22999.44 23991.35 30299.59 22597.31 23798.07 21599.29 182
NP-MVS99.23 22596.92 27699.40 251
EG-PatchMatch MVS95.97 30295.69 30296.81 32297.78 33792.79 34799.16 24598.93 30496.16 29194.08 34699.22 29082.72 35299.47 23395.67 29897.50 23698.17 327
tpm cat197.39 27597.36 25897.50 30799.17 24493.73 33999.43 16199.31 25491.27 34298.71 25399.08 30494.31 23199.77 17096.41 28498.50 19499.00 208
SteuartSystems-ACMMP99.54 999.42 1399.87 1199.82 3799.81 2499.59 7999.51 10198.62 5999.79 2699.83 4299.28 399.97 1198.48 13799.90 2399.84 18
Skip Steuart: Steuart Systems R&D Blog.
CostFormer97.72 24697.73 21597.71 30099.15 24994.02 33799.54 11099.02 29694.67 32099.04 20799.35 26592.35 28399.77 17098.50 13697.94 21799.34 179
CR-MVSNet98.17 17897.93 19398.87 20099.18 23898.49 20099.22 23999.33 24396.96 23099.56 9199.38 25694.33 22999.00 31394.83 31398.58 18899.14 189
JIA-IIPM97.50 26997.02 28098.93 18298.73 30697.80 23699.30 20998.97 30091.73 34198.91 22794.86 35495.10 19699.71 19597.58 21597.98 21699.28 183
Patchmtry97.75 24097.40 25498.81 21199.10 25698.87 16299.11 25999.33 24394.83 31798.81 24299.38 25694.33 22999.02 31096.10 28795.57 28998.53 300
PatchT97.03 28496.44 28898.79 21498.99 27398.34 20999.16 24599.07 29292.13 33999.52 10097.31 34994.54 22498.98 31588.54 34998.73 18499.03 205
tpmrst98.33 16498.48 14997.90 29099.16 24694.78 33099.31 20799.11 28697.27 20199.45 11199.59 18895.33 18899.84 13698.48 13798.61 18599.09 196
BH-w/o98.00 20397.89 19998.32 26199.35 19496.20 30099.01 28298.90 31196.42 27298.38 28899.00 31395.26 19299.72 18996.06 28898.61 18599.03 205
tpm97.67 25797.55 23098.03 27999.02 27095.01 32599.43 16198.54 33696.44 27099.12 18999.34 26891.83 29099.60 22497.75 20096.46 26699.48 159
DELS-MVS99.48 1999.42 1399.65 7299.72 8099.40 9899.05 26899.66 2799.14 699.57 9099.80 7698.46 7999.94 5499.57 399.84 6599.60 130
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 15698.36 15498.59 22799.49 16096.70 28399.27 22099.13 28597.24 20598.80 24499.38 25695.75 17499.74 17897.07 25599.16 15099.33 180
RPMNet96.72 28895.90 29899.19 15399.18 23898.49 20099.22 23999.52 8888.72 34999.56 9197.38 34694.08 23999.95 4386.87 35598.58 18899.14 189
MVSTER98.49 15198.32 15999.00 17299.35 19499.02 13999.54 11099.38 21797.41 19099.20 17699.73 12493.86 24599.36 25798.87 7697.56 23098.62 283
CPTT-MVS99.11 9098.90 10099.74 5699.80 4199.46 9199.59 7999.49 12897.03 22699.63 7399.69 14097.27 12499.96 1997.82 19399.84 6599.81 41
GBi-Net97.68 25497.48 23898.29 26499.51 15197.26 25399.43 16199.48 14096.49 26399.07 20199.32 27590.26 31198.98 31597.10 25296.65 25998.62 283
PVSNet_Blended_VisFu99.36 5099.28 4999.61 8299.86 2199.07 13599.47 14799.93 297.66 16299.71 4699.86 2397.73 11199.96 1999.47 1699.82 7899.79 53
PVSNet_BlendedMVS98.86 11998.80 11599.03 16899.76 5298.79 17399.28 21599.91 397.42 18999.67 5999.37 25997.53 11499.88 11998.98 6097.29 24998.42 313
UnsupCasMVSNet_eth96.44 29396.12 29397.40 30998.65 31595.65 30899.36 19499.51 10197.13 21396.04 33998.99 31488.40 33398.17 33696.71 27490.27 33998.40 316
UnsupCasMVSNet_bld93.53 32092.51 32396.58 32697.38 34193.82 33898.24 34599.48 14091.10 34493.10 34996.66 35074.89 35898.37 33394.03 32287.71 34497.56 347
PVSNet_Blended99.08 9698.97 9199.42 12299.76 5298.79 17398.78 31399.91 396.74 24499.67 5999.49 22497.53 11499.88 11998.98 6099.85 5899.60 130
FMVSNet596.43 29496.19 29297.15 31299.11 25395.89 30599.32 20599.52 8894.47 32498.34 29299.07 30587.54 34297.07 35192.61 33795.72 28698.47 306
test197.68 25497.48 23898.29 26499.51 15197.26 25399.43 16199.48 14096.49 26399.07 20199.32 27590.26 31198.98 31597.10 25296.65 25998.62 283
new_pmnet96.38 29596.03 29597.41 30898.13 33495.16 32499.05 26899.20 27693.94 32697.39 32098.79 32491.61 29999.04 30690.43 34395.77 28398.05 332
FMVSNet398.03 19697.76 21298.84 20799.39 18898.98 14399.40 17899.38 21796.67 24999.07 20199.28 28292.93 25898.98 31597.10 25296.65 25998.56 299
dp97.75 24097.80 20397.59 30399.10 25693.71 34099.32 20598.88 31396.48 26799.08 20099.55 20292.67 27199.82 15296.52 28098.58 18899.24 185
FMVSNet297.72 24697.36 25898.80 21399.51 15198.84 16699.45 15199.42 19996.49 26398.86 23999.29 28090.26 31198.98 31596.44 28296.56 26298.58 297
FMVSNet196.84 28696.36 28998.29 26499.32 20697.26 25399.43 16199.48 14095.11 31198.55 27799.32 27583.95 35098.98 31595.81 29396.26 27198.62 283
N_pmnet94.95 31295.83 30092.31 33598.47 32779.33 36099.12 25392.81 36793.87 32797.68 31599.13 30093.87 24499.01 31291.38 34096.19 27298.59 296
cascas97.69 25297.43 25198.48 24198.60 32197.30 24998.18 34899.39 21192.96 33798.41 28698.78 32693.77 24799.27 27498.16 16698.61 18598.86 219
BH-RMVSNet98.41 15898.08 17599.40 12399.41 18098.83 16999.30 20998.77 31997.70 15698.94 22399.65 15992.91 26199.74 17896.52 28099.55 12999.64 120
UGNet98.87 11698.69 12699.40 12399.22 22998.72 17799.44 15599.68 1999.24 399.18 18299.42 24492.74 26599.96 1999.34 2699.94 999.53 147
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 9898.88 10399.61 8299.62 12699.16 12199.37 19099.56 5698.04 12399.53 9899.62 17896.84 13699.94 5498.85 8198.49 19599.72 87
XXY-MVS98.38 16198.09 17499.24 14999.26 21999.32 10299.56 9899.55 6497.45 18398.71 25399.83 4293.23 25399.63 22198.88 7296.32 27098.76 231
sss99.17 7399.05 7499.53 9899.62 12698.97 14699.36 19499.62 3397.83 14099.67 5999.65 15997.37 12199.95 4399.19 4099.19 14999.68 103
Test_1112_low_res98.89 11598.66 13199.57 8899.69 9698.95 15299.03 27499.47 15896.98 22899.15 18599.23 28996.77 14099.89 11498.83 8698.78 18299.86 11
1112_ss98.98 10998.77 11899.59 8499.68 10099.02 13999.25 23199.48 14097.23 20699.13 18799.58 19196.93 13599.90 10698.87 7698.78 18299.84 18
ab-mvs-re8.30 33711.06 3400.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 36899.58 1910.00 3730.00 3680.00 3660.00 3660.00 364
ab-mvs98.86 11998.63 13399.54 9299.64 11799.19 11699.44 15599.54 7197.77 14899.30 14999.81 6294.20 23399.93 6999.17 4398.82 17999.49 158
TR-MVS97.76 23697.41 25398.82 20999.06 26397.87 23298.87 30598.56 33496.63 25498.68 26199.22 29092.49 27699.65 21395.40 30397.79 22098.95 217
MDTV_nov1_ep13_2view95.18 32399.35 20096.84 23999.58 8895.19 19597.82 19399.46 166
MDTV_nov1_ep1398.32 15999.11 25394.44 33399.27 22098.74 32397.51 17899.40 12899.62 17894.78 20899.76 17597.59 21498.81 181
MIMVSNet195.51 30595.04 30996.92 32097.38 34195.60 30999.52 11699.50 12093.65 33096.97 33199.17 29585.28 34896.56 35588.36 35095.55 29098.60 295
MIMVSNet97.73 24497.45 24398.57 23199.45 17597.50 24599.02 27798.98 29996.11 29699.41 12399.14 29990.28 31098.74 33095.74 29598.93 17199.47 164
IterMVS-LS98.46 15398.42 15298.58 23099.59 13698.00 22399.37 19099.43 19796.94 23499.07 20199.59 18897.87 10699.03 30898.32 15595.62 28898.71 241
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
CDS-MVSNet99.09 9499.03 7999.25 14799.42 17798.73 17699.45 15199.46 16898.11 10999.46 11099.77 10298.01 10499.37 25398.70 10398.92 17399.66 109
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
ACMMP++_ref97.19 252
IterMVS97.83 22697.77 20998.02 28199.58 13896.27 29899.02 27799.48 14097.22 20798.71 25399.70 13392.75 26399.13 29597.46 23096.00 27698.67 261
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DP-MVS Recon99.12 8598.95 9599.65 7299.74 7099.70 4699.27 22099.57 5096.40 27499.42 11999.68 14698.75 5699.80 16197.98 18099.72 10499.44 169
MVS_111021_LR99.41 4299.33 2899.65 7299.77 4999.51 8598.94 29899.85 698.82 4499.65 6999.74 11798.51 7599.80 16198.83 8699.89 3399.64 120
DP-MVS99.16 7598.95 9599.78 4599.77 4999.53 8099.41 17099.50 12097.03 22699.04 20799.88 1597.39 11799.92 8098.66 11199.90 2399.87 10
ACMMP++97.43 244
HQP-MVS98.02 19897.90 19598.37 25799.19 23596.83 27898.98 28899.39 21198.24 9298.66 26299.40 25192.47 27799.64 21697.19 24797.58 22898.64 273
QAPM98.67 14498.30 16199.80 4099.20 23399.67 5299.77 2499.72 1194.74 31998.73 25199.90 795.78 17399.98 696.96 26199.88 3699.76 68
Vis-MVSNetpermissive99.12 8598.97 9199.56 9099.78 4499.10 13199.68 4299.66 2798.49 6799.86 1199.87 2094.77 21199.84 13699.19 4099.41 13599.74 74
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
MVS-HIRNet95.75 30495.16 30897.51 30699.30 20893.69 34198.88 30395.78 35985.09 35298.78 24792.65 35691.29 30399.37 25394.85 31299.85 5899.46 166
IS-MVSNet99.05 10098.87 10499.57 8899.73 7599.32 10299.75 2899.20 27698.02 12699.56 9199.86 2396.54 14799.67 20698.09 17099.13 15499.73 81
HyFIR lowres test99.11 9098.92 9799.65 7299.90 399.37 9999.02 27799.91 397.67 16199.59 8699.75 11195.90 16999.73 18599.53 699.02 16699.86 11
EPMVS97.82 22997.65 22298.35 25898.88 28595.98 30399.49 13694.71 36297.57 16999.26 16299.48 23092.46 28099.71 19597.87 18899.08 16099.35 177
PAPM_NR99.04 10198.84 11099.66 6899.74 7099.44 9399.39 18299.38 21797.70 15699.28 15499.28 28298.34 8999.85 13196.96 26199.45 13299.69 99
TAMVS99.12 8599.08 7299.24 14999.46 17098.55 19099.51 12099.46 16898.09 11299.45 11199.82 4998.34 8999.51 23198.70 10398.93 17199.67 106
PAPR98.63 14898.34 15799.51 10699.40 18599.03 13898.80 31199.36 22796.33 27599.00 21599.12 30398.46 7999.84 13695.23 30799.37 14099.66 109
RPSCF98.22 17198.62 13896.99 31699.82 3791.58 35199.72 3299.44 18996.61 25599.66 6499.89 1095.92 16799.82 15297.46 23099.10 15899.57 139
Vis-MVSNet (Re-imp)98.87 11698.72 12299.31 13499.71 8698.88 16199.80 1799.44 18997.91 13399.36 13899.78 9595.49 18399.43 24597.91 18599.11 15599.62 126
test_040296.64 28996.24 29197.85 29298.85 29396.43 29399.44 15599.26 26693.52 33196.98 33099.52 21488.52 33299.20 28892.58 33897.50 23697.93 341
MVS_111021_HR99.41 4299.32 3199.66 6899.72 8099.47 9098.95 29699.85 698.82 4499.54 9699.73 12498.51 7599.74 17898.91 6999.88 3699.77 63
CSCG99.32 5499.32 3199.32 13399.85 2598.29 21099.71 3499.66 2798.11 10999.41 12399.80 7698.37 8899.96 1998.99 5999.96 599.72 87
PatchMatch-RL98.84 13098.62 13899.52 10499.71 8699.28 10899.06 26699.77 997.74 15399.50 10399.53 21195.41 18499.84 13697.17 25099.64 12199.44 169
API-MVS99.04 10199.03 7999.06 16399.40 18599.31 10599.55 10799.56 5698.54 6399.33 14599.39 25598.76 5399.78 16896.98 25999.78 8998.07 330
Test By Simon98.75 56
TDRefinement95.42 30794.57 31397.97 28589.83 36196.11 30199.48 14298.75 32096.74 24496.68 33299.88 1588.65 33099.71 19598.37 14982.74 35198.09 329
USDC97.34 27697.20 27497.75 29899.07 26195.20 32198.51 33499.04 29597.99 12798.31 29399.86 2389.02 32599.55 22995.67 29897.36 24898.49 303
EPP-MVSNet99.13 7998.99 8799.53 9899.65 11599.06 13699.81 1299.33 24397.43 18799.60 8399.88 1597.14 12699.84 13699.13 4798.94 17099.69 99
PMMVS98.80 13498.62 13899.34 12899.27 21798.70 17898.76 31599.31 25497.34 19499.21 17399.07 30597.20 12599.82 15298.56 12998.87 17699.52 148
PAPM97.59 26297.09 27899.07 16299.06 26398.26 21398.30 34499.10 28794.88 31698.08 30299.34 26896.27 15699.64 21689.87 34598.92 17399.31 181
ACMMPcopyleft99.45 2699.32 3199.82 3599.89 899.67 5299.62 6699.69 1898.12 10799.63 7399.84 3898.73 5999.96 1998.55 13299.83 7299.81 41
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 7798.99 8799.59 8499.58 13899.41 9699.16 24599.44 18998.45 7199.19 17999.49 22498.08 10299.89 11497.73 20299.75 9799.48 159
PatchmatchNetpermissive98.31 16598.36 15498.19 27199.16 24695.32 31999.27 22098.92 30697.37 19399.37 13599.58 19194.90 20299.70 20197.43 23499.21 14799.54 143
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
PHI-MVS99.30 5699.17 6399.70 6499.56 14499.52 8399.58 8699.80 897.12 21599.62 7799.73 12498.58 7099.90 10698.61 11899.91 1699.68 103
F-COLMAP99.19 6999.04 7799.64 7799.78 4499.27 11099.42 16899.54 7197.29 19999.41 12399.59 18898.42 8499.93 6998.19 16199.69 11099.73 81
ANet_high77.30 33074.86 33484.62 34275.88 36677.61 36197.63 35493.15 36688.81 34864.27 36389.29 36036.51 36783.93 36475.89 35952.31 36192.33 356
wuyk23d40.18 33341.29 33836.84 34786.18 36449.12 36979.73 36122.81 37027.64 36425.46 36728.45 36721.98 37048.89 36555.80 36323.56 36512.51 363
OMC-MVS99.08 9699.04 7799.20 15299.67 10198.22 21499.28 21599.52 8898.07 11799.66 6499.81 6297.79 10999.78 16897.79 19599.81 8099.60 130
MG-MVS99.13 7999.02 8299.45 11799.57 14098.63 18499.07 26399.34 23698.99 2599.61 7999.82 4997.98 10599.87 12297.00 25799.80 8499.85 14
AdaColmapbinary99.01 10798.80 11599.66 6899.56 14499.54 7799.18 24399.70 1598.18 10299.35 14199.63 17296.32 15499.90 10697.48 22799.77 9299.55 141
uanet0.02 3390.03 3420.00 3500.00 3710.00 3720.00 3620.00 3720.00 3670.00 3680.27 3680.00 3730.00 3680.00 3660.00 3660.00 364
ITE_SJBPF98.08 27699.29 21296.37 29498.92 30698.34 8398.83 24099.75 11191.09 30599.62 22295.82 29297.40 24698.25 324
DeepMVS_CXcopyleft93.34 33399.29 21282.27 35799.22 27285.15 35196.33 33599.05 30890.97 30799.73 18593.57 32697.77 22198.01 334
TinyColmap97.12 28296.89 28297.83 29499.07 26195.52 31498.57 33098.74 32397.58 16897.81 31399.79 8888.16 33699.56 22795.10 30897.21 25198.39 317
MAR-MVS98.86 11998.63 13399.54 9299.37 19199.66 5499.45 15199.54 7196.61 25599.01 21099.40 25197.09 12899.86 12597.68 21099.53 13099.10 192
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 26697.46 24297.70 30198.98 27695.55 31199.29 21398.82 31898.07 11798.66 26299.64 16689.97 31699.61 22397.01 25696.68 25897.94 340
MSDG98.98 10998.80 11599.53 9899.76 5299.19 11698.75 31699.55 6497.25 20399.47 10899.77 10297.82 10899.87 12296.93 26499.90 2399.54 143
LS3D99.27 6199.12 6799.74 5699.18 23899.75 3899.56 9899.57 5098.45 7199.49 10699.85 2997.77 11099.94 5498.33 15399.84 6599.52 148
CLD-MVS98.16 17998.10 17198.33 25999.29 21296.82 28098.75 31699.44 18997.83 14099.13 18799.55 20292.92 25999.67 20698.32 15597.69 22298.48 304
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
FPMVS84.93 32685.65 32782.75 34486.77 36363.39 36798.35 33998.92 30674.11 35683.39 35698.98 31750.85 36492.40 36084.54 35794.97 30292.46 354
Gipumacopyleft90.99 32390.15 32693.51 33298.73 30690.12 35393.98 35899.45 18079.32 35592.28 35094.91 35369.61 35997.98 34187.42 35295.67 28792.45 355
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015