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.
sort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysorted bysort bysort bysort bysort bysort by
test_blank8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
uanet_test8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
pcd_1.5k_mvsjas16.61 34422.14 3470.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 199.28 410.00 3780.00 3760.00 3760.00 374
sosnet-low-res8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
sosnet8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
uncertanet8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
Regformer8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
uanet8.33 34511.11 3480.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 378100.00 10.00 3820.00 3780.00 3760.00 3760.00 374
LCM-MVSNet99.95 199.95 199.95 199.99 199.99 199.95 299.97 299.99 1100.00 199.98 999.78 6100.00 199.92 1100.00 199.87 9
ANet_high99.88 499.87 499.91 299.99 199.91 299.65 50100.00 199.90 7100.00 199.97 1099.61 1799.97 1799.75 13100.00 199.84 14
MVS-HIRNet97.86 28298.22 25396.76 34299.28 28191.53 36998.38 27692.60 37399.13 15799.31 22799.96 1197.18 24999.68 32698.34 15499.83 13899.07 296
pmmvs699.86 699.86 699.83 2199.94 1099.90 599.83 699.91 1099.85 2499.94 1199.95 1299.73 899.90 13399.65 1699.97 3399.69 55
gg-mvs-nofinetune95.87 33295.17 33697.97 31798.19 36596.95 32399.69 3489.23 37899.89 1196.24 36699.94 1381.19 36999.51 36093.99 35398.20 34897.44 362
anonymousdsp99.80 1199.77 1299.90 499.96 499.88 999.73 2099.85 2699.70 5299.92 1899.93 1499.45 2399.97 1799.36 53100.00 199.85 13
mvs_tets99.90 299.90 299.90 499.96 499.79 3899.72 2399.88 1899.92 699.98 399.93 1499.94 199.98 799.77 12100.00 199.92 3
OurMVSNet-221017-099.75 1599.71 1699.84 1999.96 499.83 2499.83 699.85 2699.80 3699.93 1499.93 1498.54 13999.93 7199.59 2199.98 2499.76 39
PS-MVSNAJss99.84 899.82 899.89 799.96 499.77 4499.68 3799.85 2699.95 399.98 399.92 1799.28 4199.98 799.75 13100.00 199.94 2
test_djsdf99.84 899.81 999.91 299.94 1099.84 1999.77 1199.80 4999.73 4399.97 699.92 1799.77 799.98 799.43 41100.00 199.90 4
TDRefinement99.72 1799.70 1799.77 4099.90 1999.85 1499.86 599.92 799.69 5599.78 7099.92 1799.37 3199.88 16598.93 11699.95 5299.60 126
UA-Net99.78 1399.76 1499.86 1699.72 11099.71 7199.91 399.95 599.96 299.71 10399.91 2099.15 5599.97 1799.50 35100.00 199.90 4
v7n99.82 1099.80 1099.88 1199.96 499.84 1999.82 899.82 3999.84 2799.94 1199.91 2099.13 6099.96 3599.83 999.99 1299.83 18
Anonymous2023121199.62 3599.57 4099.76 4799.61 15099.60 11099.81 999.73 8399.82 3299.90 2299.90 2297.97 20099.86 19899.42 4699.96 4599.80 24
jajsoiax99.89 399.89 399.89 799.96 499.78 4199.70 2899.86 2299.89 1199.98 399.90 2299.94 199.98 799.75 13100.00 199.90 4
SixPastTwentyTwo99.42 7099.30 9099.76 4799.92 1499.67 8799.70 2899.14 30799.65 6799.89 2699.90 2296.20 27699.94 5799.42 4699.92 7799.67 68
DeepC-MVS98.90 499.62 3599.61 3199.67 9299.72 11099.44 14399.24 13699.71 9599.27 13099.93 1499.90 2299.70 1199.93 7198.99 10499.99 1299.64 95
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
UniMVSNet_ETH3D99.85 799.83 799.90 499.89 2199.91 299.89 499.71 9599.93 499.95 1099.89 2699.71 999.96 3599.51 3399.97 3399.84 14
TransMVSNet (Re)99.78 1399.77 1299.81 2699.91 1599.85 1499.75 1599.86 2299.70 5299.91 2099.89 2699.60 1999.87 17899.59 2199.74 18999.71 48
MIMVSNet199.66 2699.62 2799.80 2999.94 1099.87 1099.69 3499.77 6399.78 3999.93 1499.89 2697.94 20199.92 9199.65 1699.98 2499.62 111
Anonymous2024052199.44 6599.42 6599.49 16599.89 2198.96 22999.62 5399.76 6899.85 2499.82 5299.88 2996.39 27199.97 1799.59 2199.98 2499.55 152
Baseline_NR-MVSNet99.49 5299.37 7499.82 2399.91 1599.84 1998.83 22699.86 2299.68 5799.65 12499.88 2997.67 22299.87 17899.03 10199.86 11999.76 39
K. test v398.87 20398.60 21399.69 8899.93 1399.46 13699.74 1794.97 36799.78 3999.88 3299.88 2993.66 30599.97 1799.61 1999.95 5299.64 95
test111197.74 28798.16 26196.49 34899.60 15289.86 37799.71 2791.21 37499.89 1199.88 3299.87 3293.73 30499.90 13399.56 2699.99 1299.70 51
new-patchmatchnet99.35 9299.57 4098.71 29399.82 4696.62 33098.55 25999.75 7599.50 9399.88 3299.87 3299.31 3799.88 16599.43 41100.00 199.62 111
pm-mvs199.79 1299.79 1199.78 3799.91 1599.83 2499.76 1399.87 2099.73 4399.89 2699.87 3299.63 1499.87 17899.54 2899.92 7799.63 100
v1099.69 2199.69 1899.66 9999.81 5399.39 15799.66 4599.75 7599.60 8399.92 1899.87 3298.75 11299.86 19899.90 299.99 1299.73 44
JIA-IIPM98.06 27797.92 28098.50 29998.59 35597.02 32298.80 23498.51 33599.88 1697.89 34699.87 3291.89 32299.90 13398.16 17397.68 36098.59 329
LTVRE_ROB99.19 199.88 499.87 499.88 1199.91 1599.90 599.96 199.92 799.90 799.97 699.87 3299.81 599.95 4599.54 2899.99 1299.80 24
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
test250694.73 33894.59 34095.15 35499.59 15685.90 37999.75 1574.01 38099.89 1199.71 10399.86 3879.00 37899.90 13399.52 3299.99 1299.65 86
ECVR-MVScopyleft97.73 28898.04 26796.78 34199.59 15690.81 37399.72 2390.43 37699.89 1199.86 4099.86 3893.60 30699.89 15099.46 3899.99 1299.65 86
test_part198.63 22798.26 25099.75 5799.40 24399.49 12999.67 4199.68 10999.86 1999.88 3299.86 3886.73 36099.93 7199.34 5599.97 3399.81 23
KD-MVS_self_test99.63 3299.59 3499.76 4799.84 3599.90 599.37 9799.79 5599.83 3099.88 3299.85 4198.42 15799.90 13399.60 2099.73 19699.49 188
v899.68 2499.69 1899.65 10499.80 5899.40 15599.66 4599.76 6899.64 6999.93 1499.85 4198.66 12399.84 23499.88 699.99 1299.71 48
EU-MVSNet99.39 8299.62 2798.72 29199.88 2596.44 33299.56 7099.85 2699.90 799.90 2299.85 4198.09 18999.83 24599.58 2499.95 5299.90 4
DSMNet-mixed99.48 5499.65 2498.95 26499.71 11397.27 31699.50 7599.82 3999.59 8599.41 20599.85 4199.62 16100.00 199.53 3099.89 9599.59 135
ACMH98.42 699.59 3899.54 4599.72 7999.86 3199.62 10299.56 7099.79 5598.77 20299.80 6299.85 4199.64 1399.85 21798.70 13499.89 9599.70 51
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
XXY-MVS99.71 1899.67 2199.81 2699.89 2199.72 6899.59 6599.82 3999.39 11599.82 5299.84 4699.38 2999.91 11399.38 5099.93 7399.80 24
EGC-MVSNET89.05 34085.52 34399.64 11199.89 2199.78 4199.56 7099.52 21124.19 37449.96 37599.83 4799.15 5599.92 9197.71 21299.85 12399.21 260
FC-MVSNet-test99.70 1999.65 2499.86 1699.88 2599.86 1399.72 2399.78 6099.90 799.82 5299.83 4798.45 15499.87 17899.51 3399.97 3399.86 11
lessismore_v099.64 11199.86 3199.38 16090.66 37599.89 2699.83 4794.56 29599.97 1799.56 2699.92 7799.57 146
GBi-Net99.42 7099.31 8599.73 7399.49 21099.77 4499.68 3799.70 10099.44 10799.62 13899.83 4797.21 24599.90 13398.96 11099.90 8799.53 165
test199.42 7099.31 8599.73 7399.49 21099.77 4499.68 3799.70 10099.44 10799.62 13899.83 4797.21 24599.90 13398.96 11099.90 8799.53 165
FMVSNet199.66 2699.63 2699.73 7399.78 7499.77 4499.68 3799.70 10099.67 6199.82 5299.83 4798.98 7899.90 13399.24 7099.97 3399.53 165
TAMVS99.49 5299.45 5799.63 11699.48 21699.42 15099.45 8299.57 17799.66 6599.78 7099.83 4797.85 21099.86 19899.44 4099.96 4599.61 122
SD-MVS99.01 18099.30 9098.15 31399.50 20599.40 15598.94 21499.61 14799.22 14299.75 8399.82 5499.54 2295.51 37597.48 23399.87 11299.54 160
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
ab-mvs99.33 10199.28 9799.47 17199.57 17199.39 15799.78 1099.43 24398.87 18999.57 15499.82 5498.06 19299.87 17898.69 13699.73 19699.15 275
PMVScopyleft92.94 2198.82 20898.81 19798.85 27999.84 3597.99 29399.20 14699.47 23099.71 4799.42 19799.82 5498.09 18999.47 36293.88 35499.85 12399.07 296
Y. Furukawa, J. Ponce: Accurate, dense, and robust multiview stereopsis. PAMI (2010)
VPA-MVSNet99.66 2699.62 2799.79 3499.68 13399.75 5599.62 5399.69 10699.85 2499.80 6299.81 5798.81 9799.91 11399.47 3799.88 10399.70 51
UGNet99.38 8499.34 7999.49 16598.90 33198.90 23999.70 2899.35 26799.86 1998.57 31599.81 5798.50 14999.93 7199.38 5099.98 2499.66 78
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
ambc99.20 24099.35 25598.53 26099.17 15799.46 23499.67 11699.80 5998.46 15399.70 30997.92 19099.70 20899.38 226
VDDNet98.97 18698.82 19699.42 18699.71 11398.81 24399.62 5398.68 32799.81 3399.38 21299.80 5994.25 29799.85 21798.79 12599.32 29799.59 135
mvs_anonymous99.28 10999.39 6998.94 26599.19 29797.81 30199.02 19599.55 18899.78 3999.85 4299.80 5998.24 17699.86 19899.57 2599.50 27099.15 275
QAPM98.40 25797.99 27099.65 10499.39 24599.47 13299.67 4199.52 21191.70 36398.78 29999.80 5998.55 13799.95 4594.71 34399.75 18199.53 165
3Dnovator99.15 299.43 6699.36 7799.65 10499.39 24599.42 15099.70 2899.56 18299.23 13899.35 21699.80 5999.17 5399.95 4598.21 16599.84 12899.59 135
CMPMVSbinary77.52 2398.50 24598.19 25899.41 19498.33 36299.56 11999.01 19799.59 16695.44 34499.57 15499.80 5995.64 28499.46 36496.47 29599.92 7799.21 260
M. Jancosek, T. Pajdla: Multi-View Reconstruction Preserving Weakly-Supported Surfaces. CVPR 2011
FIs99.65 3199.58 3799.84 1999.84 3599.85 1499.66 4599.75 7599.86 1999.74 9299.79 6598.27 17499.85 21799.37 5299.93 7399.83 18
LCM-MVSNet-Re99.28 10999.15 11799.67 9299.33 27099.76 5199.34 10399.97 298.93 18199.91 2099.79 6598.68 11899.93 7196.80 27699.56 25399.30 244
CHOSEN 1792x268899.39 8299.30 9099.65 10499.88 2599.25 18998.78 23899.88 1898.66 21099.96 899.79 6597.45 23399.93 7199.34 5599.99 1299.78 32
CR-MVSNet98.35 26298.20 25598.83 28399.05 31898.12 28599.30 11599.67 11497.39 30499.16 25499.79 6591.87 32399.91 11398.78 12898.77 32998.44 340
Patchmtry98.78 21198.54 22399.49 16598.89 33499.19 20599.32 10899.67 11499.65 6799.72 9899.79 6591.87 32399.95 4598.00 18499.97 3399.33 238
wuyk23d97.58 29599.13 12192.93 35599.69 12499.49 12999.52 7399.77 6397.97 27299.96 899.79 6599.84 399.94 5795.85 32099.82 14779.36 371
Anonymous2024052999.42 7099.34 7999.65 10499.53 18899.60 11099.63 5299.39 25699.47 10099.76 7799.78 7198.13 18799.86 19898.70 13499.68 21699.49 188
DTE-MVSNet99.68 2499.61 3199.88 1199.80 5899.87 1099.67 4199.71 9599.72 4699.84 4599.78 7198.67 12199.97 1799.30 6399.95 5299.80 24
EG-PatchMatch MVS99.57 3999.56 4499.62 12599.77 8299.33 17399.26 12899.76 6899.32 12499.80 6299.78 7199.29 3999.87 17899.15 8799.91 8699.66 78
RPSCF99.18 14399.02 15899.64 11199.83 3999.85 1499.44 8599.82 3998.33 25199.50 18299.78 7197.90 20499.65 34296.78 27799.83 13899.44 209
3Dnovator+98.92 399.35 9299.24 10699.67 9299.35 25599.47 13299.62 5399.50 21999.44 10799.12 26199.78 7198.77 10999.94 5797.87 19699.72 20299.62 111
Gipumacopyleft99.57 3999.59 3499.49 16599.98 399.71 7199.72 2399.84 3299.81 3399.94 1199.78 7198.91 8799.71 30798.41 14899.95 5299.05 298
S. Galliani, K. Lasinger, K. Schindler: Massively Parallel Multiview Stereopsis by Surface Normal Diffusion. ICCV 2015
COLMAP_ROBcopyleft98.06 1299.45 6399.37 7499.70 8799.83 3999.70 7899.38 9399.78 6099.53 8999.67 11699.78 7199.19 5199.86 19897.32 24199.87 11299.55 152
Johannes L. Schönberger, Enliang Zheng, Marc Pollefeys, Jan-Michael Frahm: Pixelwise View Selection for Unstructured Multi-View Stereo. ECCV 2016
USDC98.96 18998.93 17899.05 25899.54 18397.99 29397.07 35799.80 4998.21 25899.75 8399.77 7898.43 15599.64 34497.90 19199.88 10399.51 177
EPP-MVSNet99.17 14799.00 16499.66 9999.80 5899.43 14799.70 2899.24 29399.48 9599.56 16199.77 7894.89 29099.93 7198.72 13399.89 9599.63 100
OpenMVScopyleft98.12 1098.23 27097.89 28499.26 23099.19 29799.26 18599.65 5099.69 10691.33 36498.14 33799.77 7898.28 17399.96 3595.41 33299.55 25798.58 331
PatchT98.45 25298.32 24698.83 28398.94 32998.29 27699.24 13698.82 32299.84 2799.08 26699.76 8191.37 32699.94 5798.82 12399.00 31898.26 347
MIMVSNet98.43 25398.20 25599.11 25099.53 18898.38 27399.58 6798.61 33198.96 17699.33 22199.76 8190.92 33399.81 27197.38 23999.76 17899.15 275
DP-MVS99.48 5499.39 6999.74 6399.57 17199.62 10299.29 12299.61 14799.87 1799.74 9299.76 8198.69 11799.87 17898.20 16699.80 16099.75 42
ACMH+98.40 899.50 5099.43 6299.71 8399.86 3199.76 5199.32 10899.77 6399.53 8999.77 7599.76 8199.26 4599.78 28297.77 20499.88 10399.60 126
RRT_MVS98.75 21598.54 22399.41 19498.14 36998.61 25798.98 20899.66 11899.31 12599.84 4599.75 8591.98 32099.98 799.20 7699.95 5299.62 111
v124099.56 4299.58 3799.51 15999.80 5899.00 22399.00 19999.65 12999.15 15599.90 2299.75 8599.09 6399.88 16599.90 299.96 4599.67 68
Vis-MVSNetpermissive99.75 1599.74 1599.79 3499.88 2599.66 8999.69 3499.92 799.67 6199.77 7599.75 8599.61 1799.98 799.35 5499.98 2499.72 45
Jingyang Zhang, Yao Yao, Shiwei Li, Zixin Luo, Tian Fang: Visibility-aware Multiview Stereo Network. BMVC 2020
RPMNet98.60 23198.53 22598.83 28399.05 31898.12 28599.30 11599.62 14099.86 1999.16 25499.74 8892.53 31699.92 9198.75 13098.77 32998.44 340
FMVSNet299.35 9299.28 9799.55 14899.49 21099.35 17099.45 8299.57 17799.44 10799.70 10699.74 8897.21 24599.87 17899.03 10199.94 6599.44 209
IterMVS98.97 18699.16 11498.42 30299.74 10395.64 34398.06 30599.83 3499.83 3099.85 4299.74 8896.10 27999.99 599.27 69100.00 199.63 100
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
OpenMVS_ROBcopyleft97.31 1797.36 30296.84 31398.89 27899.29 27899.45 14198.87 22099.48 22686.54 36999.44 19199.74 8897.34 24099.86 19891.61 35999.28 30197.37 364
IterMVS-SCA-FT99.00 18299.16 11498.51 29899.75 9795.90 34098.07 30399.84 3299.84 2799.89 2699.73 9296.01 28099.99 599.33 58100.00 199.63 100
ACMMP_NAP99.28 10999.11 12899.79 3499.75 9799.81 3198.95 21299.53 20398.27 25599.53 17399.73 9298.75 11299.87 17897.70 21599.83 13899.68 61
v114499.54 4799.53 4999.59 13299.79 6899.28 18199.10 18099.61 14799.20 14399.84 4599.73 9298.67 12199.84 23499.86 899.98 2499.64 95
PM-MVS99.36 9099.29 9599.58 13699.83 3999.66 8998.95 21299.86 2298.85 19199.81 5999.73 9298.40 16299.92 9198.36 15199.83 13899.17 271
PEN-MVS99.66 2699.59 3499.89 799.83 3999.87 1099.66 4599.73 8399.70 5299.84 4599.73 9298.56 13699.96 3599.29 6699.94 6599.83 18
PVSNet_Blended_VisFu99.40 7799.38 7199.44 18099.90 1998.66 25398.94 21499.91 1097.97 27299.79 6799.73 9299.05 7299.97 1799.15 8799.99 1299.68 61
Patchmatch-RL test98.60 23198.36 24099.33 21399.77 8299.07 22098.27 28499.87 2098.91 18499.74 9299.72 9890.57 34099.79 27998.55 14299.85 12399.11 283
v14419299.55 4599.54 4599.58 13699.78 7499.20 20499.11 17999.62 14099.18 14599.89 2699.72 9898.66 12399.87 17899.88 699.97 3399.66 78
v119299.57 3999.57 4099.57 14199.77 8299.22 19899.04 19299.60 15999.18 14599.87 3999.72 9899.08 6799.85 21799.89 599.98 2499.66 78
AllTest99.21 13499.07 14399.63 11699.78 7499.64 9699.12 17799.83 3498.63 21399.63 13099.72 9898.68 11899.75 29696.38 29999.83 13899.51 177
TestCases99.63 11699.78 7499.64 9699.83 3498.63 21399.63 13099.72 9898.68 11899.75 29696.38 29999.83 13899.51 177
casdiffmvs99.63 3299.61 3199.67 9299.79 6899.59 11399.13 17399.85 2699.79 3899.76 7799.72 9899.33 3699.82 25599.21 7399.94 6599.59 135
ACMM98.09 1199.46 6199.38 7199.72 7999.80 5899.69 8299.13 17399.65 12998.99 17199.64 12699.72 9899.39 2599.86 19898.23 16399.81 15599.60 126
Qingshan Xu and Wenbing Tao: Multi-Scale Geometric Consistency Guided Multi-View Stereo. CVPR 2019
v192192099.56 4299.57 4099.55 14899.75 9799.11 21299.05 19099.61 14799.15 15599.88 3299.71 10599.08 6799.87 17899.90 299.97 3399.66 78
APDe-MVS99.48 5499.36 7799.85 1899.55 18299.81 3199.50 7599.69 10698.99 17199.75 8399.71 10598.79 10499.93 7198.46 14699.85 12399.80 24
PS-CasMVS99.66 2699.58 3799.89 799.80 5899.85 1499.66 4599.73 8399.62 7399.84 4599.71 10598.62 12799.96 3599.30 6399.96 4599.86 11
XVG-ACMP-BASELINE99.23 12099.10 13699.63 11699.82 4699.58 11698.83 22699.72 9298.36 24199.60 14699.71 10598.92 8599.91 11397.08 26199.84 12899.40 221
PVSNet_BlendedMVS99.03 17499.01 16199.09 25299.54 18397.99 29398.58 25399.82 3997.62 29099.34 21999.71 10598.52 14699.77 29097.98 18599.97 3399.52 175
IS-MVSNet99.03 17498.85 19199.55 14899.80 5899.25 18999.73 2099.15 30699.37 11799.61 14499.71 10594.73 29399.81 27197.70 21599.88 10399.58 140
LS3D99.24 11999.11 12899.61 12898.38 36099.79 3899.57 6899.68 10999.61 7799.15 25699.71 10598.70 11699.91 11397.54 22999.68 21699.13 282
TSAR-MVS + MP.99.34 9799.24 10699.63 11699.82 4699.37 16399.26 12899.35 26798.77 20299.57 15499.70 11299.27 4499.88 16597.71 21299.75 18199.65 86
Zhenlong Yuan, Jiakai Cao, Zhaoqi Wang, Zhaoxin Li: TSAR-MVS: Textureless-aware Segmentation and Correlative Refinement Guided Multi-View Stereo. Pattern Recognition
V4299.56 4299.54 4599.63 11699.79 6899.46 13699.39 9199.59 16699.24 13699.86 4099.70 11298.55 13799.82 25599.79 1199.95 5299.60 126
MDA-MVSNet-bldmvs99.06 16799.05 14999.07 25699.80 5897.83 30098.89 21699.72 9299.29 12699.63 13099.70 11296.47 26699.89 15098.17 17299.82 14799.50 183
CDS-MVSNet99.22 12999.13 12199.50 16299.35 25599.11 21298.96 21199.54 19499.46 10499.61 14499.70 11296.31 27399.83 24599.34 5599.88 10399.55 152
Khang Truong Giang, Soohwan Song, Sungho Jo: Curvature-guided dynamic scale networks for Multi-view Stereo. ICLR 2022
DeepPCF-MVS98.42 699.18 14399.02 15899.67 9299.22 29099.75 5597.25 35199.47 23098.72 20799.66 12099.70 11299.29 3999.63 34598.07 17999.81 15599.62 111
TinyColmap98.97 18698.93 17899.07 25699.46 22698.19 28197.75 32899.75 7598.79 19999.54 16899.70 11298.97 8099.62 34696.63 28799.83 13899.41 219
D2MVS99.22 12999.19 11199.29 22399.69 12498.74 24798.81 23199.41 24698.55 22199.68 11199.69 11898.13 18799.87 17898.82 12399.98 2499.24 253
DPE-MVScopyleft99.14 15298.92 18299.82 2399.57 17199.77 4498.74 24299.60 15998.55 22199.76 7799.69 11898.23 17999.92 9196.39 29899.75 18199.76 39
Kehua Chen, Zhenlong Yuan, Tianlu Mao, Zhaoqi Wang: Dual-Level Precision Edges Guided Multi-View Stereo with Accurate Planarization. AAAI2025
tfpnnormal99.43 6699.38 7199.60 13099.87 2999.75 5599.59 6599.78 6099.71 4799.90 2299.69 11898.85 9599.90 13397.25 25199.78 17199.15 275
tmp_tt95.75 33495.42 33296.76 34289.90 37994.42 35298.86 22197.87 35078.01 37099.30 23299.69 11897.70 21795.89 37499.29 6698.14 35299.95 1
VDD-MVS99.20 13699.11 12899.44 18099.43 23498.98 22599.50 7598.32 34399.80 3699.56 16199.69 11896.99 25599.85 21798.99 10499.73 19699.50 183
WR-MVS_H99.61 3799.53 4999.87 1499.80 5899.83 2499.67 4199.75 7599.58 8699.85 4299.69 11898.18 18599.94 5799.28 6899.95 5299.83 18
LPG-MVS_test99.22 12999.05 14999.74 6399.82 4699.63 10099.16 16399.73 8397.56 29299.64 12699.69 11899.37 3199.89 15096.66 28499.87 11299.69 55
LGP-MVS_train99.74 6399.82 4699.63 10099.73 8397.56 29299.64 12699.69 11899.37 3199.89 15096.66 28499.87 11299.69 55
baseline99.63 3299.62 2799.66 9999.80 5899.62 10299.44 8599.80 4999.71 4799.72 9899.69 11899.15 5599.83 24599.32 6099.94 6599.53 165
FMVSNet597.80 28497.25 30099.42 18698.83 34098.97 22799.38 9399.80 4998.87 18999.25 23799.69 11880.60 37299.91 11398.96 11099.90 8799.38 226
ACMMPcopyleft99.25 11699.08 13999.74 6399.79 6899.68 8599.50 7599.65 12998.07 26699.52 17599.69 11898.57 13499.92 9197.18 25699.79 16599.63 100
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
MVS_030498.88 20198.71 20499.39 19998.85 33898.91 23899.45 8299.30 27998.56 21997.26 35999.68 12996.18 27799.96 3599.17 8399.94 6599.29 247
MVP-Stereo99.16 14899.08 13999.43 18499.48 21699.07 22099.08 18799.55 18898.63 21399.31 22799.68 12998.19 18399.78 28298.18 17099.58 25199.45 204
Qingsong Yan: MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.
nrg03099.70 1999.66 2299.82 2399.76 8699.84 1999.61 5899.70 10099.93 499.78 7099.68 12999.10 6199.78 28299.45 3999.96 4599.83 18
RRT_test8_iter0597.35 30397.25 30097.63 32798.81 34493.13 35999.26 12899.89 1599.51 9299.83 5099.68 12979.03 37799.88 16599.53 3099.72 20299.89 8
XVG-OURS99.21 13499.06 14599.65 10499.82 4699.62 10297.87 32499.74 8098.36 24199.66 12099.68 12999.71 999.90 13396.84 27499.88 10399.43 215
N_pmnet98.73 21998.53 22599.35 21099.72 11098.67 25198.34 27794.65 36898.35 24699.79 6799.68 12998.03 19399.93 7198.28 15999.92 7799.44 209
EI-MVSNet99.38 8499.44 5999.21 23899.58 16198.09 28999.26 12899.46 23499.62 7399.75 8399.67 13598.54 13999.85 21799.15 8799.92 7799.68 61
CVMVSNet98.61 22998.88 18897.80 32299.58 16193.60 35799.26 12899.64 13599.66 6599.72 9899.67 13593.26 30899.93 7199.30 6399.81 15599.87 9
MVS_Test99.28 10999.31 8599.19 24199.35 25598.79 24599.36 10099.49 22499.17 14999.21 24799.67 13598.78 10699.66 33599.09 9799.66 22799.10 285
SteuartSystems-ACMMP99.30 10699.14 11899.76 4799.87 2999.66 8999.18 15299.60 15998.55 22199.57 15499.67 13599.03 7499.94 5797.01 26399.80 16099.69 55
Skip Steuart: Steuart Systems R&D Blog.
pmmvs-eth3d99.48 5499.47 5399.51 15999.77 8299.41 15498.81 23199.66 11899.42 11499.75 8399.66 13999.20 5099.76 29298.98 10699.99 1299.36 232
EI-MVSNet-UG-set99.48 5499.50 5199.42 18699.57 17198.65 25699.24 13699.46 23499.68 5799.80 6299.66 13998.99 7799.89 15099.19 7899.90 8799.72 45
YYNet198.95 19298.99 16998.84 28199.64 14397.14 32098.22 28899.32 27298.92 18399.59 14999.66 13997.40 23599.83 24598.27 16099.90 8799.55 152
MDA-MVSNet_test_wron98.95 19298.99 16998.85 27999.64 14397.16 31998.23 28799.33 27098.93 18199.56 16199.66 13997.39 23799.83 24598.29 15899.88 10399.55 152
MVSTER98.47 25098.22 25399.24 23599.06 31798.35 27599.08 18799.46 23499.27 13099.75 8399.66 13988.61 35099.85 21799.14 9399.92 7799.52 175
test072699.69 12499.80 3699.24 13699.57 17799.16 15199.73 9699.65 14498.35 166
EI-MVSNet-Vis-set99.47 6099.49 5299.42 18699.57 17198.66 25399.24 13699.46 23499.67 6199.79 6799.65 14498.97 8099.89 15099.15 8799.89 9599.71 48
SR-MVS-dyc-post99.27 11399.11 12899.73 7399.54 18399.74 6199.26 12899.62 14099.16 15199.52 17599.64 14698.41 15899.91 11397.27 24699.61 24399.54 160
RE-MVS-def99.13 12199.54 18399.74 6199.26 12899.62 14099.16 15199.52 17599.64 14698.57 13497.27 24699.61 24399.54 160
SMA-MVScopyleft99.19 13999.00 16499.73 7399.46 22699.73 6499.13 17399.52 21197.40 30399.57 15499.64 14698.93 8499.83 24597.61 22599.79 16599.63 100
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
APD-MVS_3200maxsize99.31 10599.16 11499.74 6399.53 18899.75 5599.27 12699.61 14799.19 14499.57 15499.64 14698.76 11099.90 13397.29 24399.62 23699.56 149
ADS-MVSNet297.78 28597.66 29398.12 31599.14 30395.36 34599.22 14398.75 32596.97 31998.25 32999.64 14690.90 33499.94 5796.51 29299.56 25399.08 291
ADS-MVSNet97.72 29197.67 29297.86 32099.14 30394.65 35199.22 14398.86 31996.97 31998.25 32999.64 14690.90 33499.84 23496.51 29299.56 25399.08 291
CP-MVSNet99.54 4799.43 6299.87 1499.76 8699.82 2899.57 6899.61 14799.54 8799.80 6299.64 14697.79 21499.95 4599.21 7399.94 6599.84 14
FMVSNet398.80 21098.63 21299.32 21799.13 30598.72 24899.10 18099.48 22699.23 13899.62 13899.64 14692.57 31499.86 19898.96 11099.90 8799.39 224
IterMVS-LS99.41 7499.47 5399.25 23399.81 5398.09 28998.85 22399.76 6899.62 7399.83 5099.64 14698.54 13999.97 1799.15 8799.99 1299.68 61
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Marc Pollefeys: IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo.
DeepC-MVS_fast98.47 599.23 12099.12 12599.56 14599.28 28199.22 19898.99 20499.40 25399.08 16299.58 15199.64 14698.90 9099.83 24597.44 23599.75 18199.63 100
Andreas Kuhn, Christian Sormann, Mattia Rossi, Oliver Erdler, Friedrich Fraundorfer: DeepC-MVS: Deep Confidence Prediction for Multi-View Stereo Reconstruction. 3DV 2020
SED-MVS99.40 7799.28 9799.77 4099.69 12499.82 2899.20 14699.54 19499.13 15799.82 5299.63 15698.91 8799.92 9197.85 19999.70 20899.58 140
test_241102_TWO99.54 19499.13 15799.76 7799.63 15698.32 17199.92 9197.85 19999.69 21199.75 42
OPM-MVS99.26 11599.13 12199.63 11699.70 12199.61 10898.58 25399.48 22698.50 22799.52 17599.63 15699.14 5899.76 29297.89 19299.77 17599.51 177
Ray L. Khuboni, Hongjun Xu: Octagram Propagation Matching for Multi-Scale View Stereopsis (OPM-MVS).
zzz-MVS99.30 10699.14 11899.80 2999.81 5399.81 3198.73 24499.53 20399.27 13099.42 19799.63 15698.21 18099.95 4597.83 20299.79 16599.65 86
MTAPA99.35 9299.20 11099.80 2999.81 5399.81 3199.33 10599.53 20399.27 13099.42 19799.63 15698.21 18099.95 4597.83 20299.79 16599.65 86
abl_699.36 9099.23 10899.75 5799.71 11399.74 6199.33 10599.76 6899.07 16499.65 12499.63 15699.09 6399.92 9197.13 25999.76 17899.58 140
APD-MVScopyleft98.87 20398.59 21599.71 8399.50 20599.62 10299.01 19799.57 17796.80 32699.54 16899.63 15698.29 17299.91 11395.24 33599.71 20699.61 122
Yuesong Wang, Zhaojie Zeng and etc.: Adaptive Patch Deformation for Textureless-Resilient Multi-View Stereo. CVPR2023
MG-MVS98.52 24398.39 23798.94 26599.15 30297.39 31498.18 28999.21 30198.89 18899.23 24199.63 15697.37 23999.74 29894.22 34899.61 24399.69 55
FPMVS96.32 32395.50 33198.79 28799.60 15298.17 28398.46 27398.80 32397.16 31596.28 36499.63 15682.19 36899.09 36888.45 36698.89 32599.10 285
our_test_398.85 20599.09 13798.13 31499.66 13994.90 35097.72 32999.58 17599.07 16499.64 12699.62 16598.19 18399.93 7198.41 14899.95 5299.55 152
ppachtmachnet_test98.89 20099.12 12598.20 31299.66 13995.24 34797.63 33399.68 10999.08 16299.78 7099.62 16598.65 12599.88 16598.02 18099.96 4599.48 193
pmmvs599.19 13999.11 12899.42 18699.76 8698.88 24098.55 25999.73 8398.82 19599.72 9899.62 16596.56 26299.82 25599.32 6099.95 5299.56 149
patchmatchnet-post99.62 16590.58 33999.94 57
v2v48299.50 5099.47 5399.58 13699.78 7499.25 18999.14 16799.58 17599.25 13499.81 5999.62 16598.24 17699.84 23499.83 999.97 3399.64 95
test20.0399.55 4599.54 4599.58 13699.79 6899.37 16399.02 19599.89 1599.60 8399.82 5299.62 16598.81 9799.89 15099.43 4199.86 11999.47 198
TSAR-MVS + GP.99.12 15699.04 15599.38 20399.34 26599.16 20798.15 29299.29 28198.18 26199.63 13099.62 16599.18 5299.68 32698.20 16699.74 18999.30 244
EPNet98.13 27397.77 28899.18 24394.57 37797.99 29399.24 13697.96 34799.74 4297.29 35899.62 16593.13 31099.97 1798.59 14099.83 13899.58 140
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
OMC-MVS98.90 19798.72 20399.44 18099.39 24599.42 15098.58 25399.64 13597.31 30899.44 19199.62 16598.59 13199.69 31596.17 30899.79 16599.22 258
DVP-MVS++99.38 8499.25 10499.77 4099.03 32199.77 4499.74 1799.61 14799.18 14599.76 7799.61 17499.00 7599.92 9197.72 21099.60 24699.62 111
test_one_060199.63 14599.76 5199.55 18899.23 13899.31 22799.61 17498.59 131
xxxxxxxxxxxxxcwj99.11 16098.96 17599.54 15299.53 18899.25 18998.29 28299.76 6899.07 16499.42 19799.61 17498.86 9399.87 17896.45 29699.68 21699.49 188
SF-MVS99.10 16498.93 17899.62 12599.58 16199.51 12799.13 17399.65 12997.97 27299.42 19799.61 17498.86 9399.87 17896.45 29699.68 21699.49 188
DVP-MVScopyleft99.32 10399.17 11399.77 4099.69 12499.80 3699.14 16799.31 27699.16 15199.62 13899.61 17498.35 16699.91 11397.88 19399.72 20299.61 122
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_THIRD99.18 14599.62 13899.61 17498.58 13399.91 11397.72 21099.80 16099.77 35
v14899.40 7799.41 6699.39 19999.76 8698.94 23199.09 18499.59 16699.17 14999.81 5999.61 17498.41 15899.69 31599.32 6099.94 6599.53 165
DELS-MVS99.34 9799.30 9099.48 16999.51 19899.36 16698.12 29699.53 20399.36 11999.41 20599.61 17499.22 4899.87 17899.21 7399.68 21699.20 264
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
MDTV_nov1_ep1397.73 28998.70 35390.83 37299.15 16598.02 34698.51 22698.82 29399.61 17490.98 33299.66 33596.89 27098.92 322
Regformer-399.41 7499.41 6699.40 19699.52 19398.70 24999.17 15799.44 23999.62 7399.75 8399.60 18398.90 9099.85 21798.89 11899.84 12899.65 86
Regformer-499.45 6399.44 5999.50 16299.52 19398.94 23199.17 15799.53 20399.64 6999.76 7799.60 18398.96 8399.90 13398.91 11799.84 12899.67 68
PGM-MVS99.20 13699.01 16199.77 4099.75 9799.71 7199.16 16399.72 9297.99 27099.42 19799.60 18398.81 9799.93 7196.91 26899.74 18999.66 78
HyFIR lowres test98.91 19598.64 21099.73 7399.85 3499.47 13298.07 30399.83 3498.64 21299.89 2699.60 18392.57 314100.00 199.33 5899.97 3399.72 45
CSCG99.37 8799.29 9599.60 13099.71 11399.46 13699.43 8799.85 2698.79 19999.41 20599.60 18398.92 8599.92 9198.02 18099.92 7799.43 215
ACMP97.51 1499.05 17098.84 19399.67 9299.78 7499.55 12298.88 21799.66 11897.11 31899.47 18699.60 18399.07 6999.89 15096.18 30799.85 12399.58 140
Qingshan Xu and Wenbing Tao: Planar Prior Assisted PatchMatch Multi-View Stereo. AAAI 2020
dp96.86 31197.07 30596.24 35198.68 35490.30 37699.19 15198.38 34297.35 30698.23 33199.59 18987.23 35399.82 25596.27 30398.73 33598.59 329
EPMVS96.53 31996.32 31797.17 33998.18 36692.97 36199.39 9189.95 37798.21 25898.61 31199.59 18986.69 36299.72 30396.99 26499.23 30998.81 321
test117299.23 12099.05 14999.74 6399.52 19399.75 5599.20 14699.61 14798.97 17399.48 18499.58 19198.41 15899.91 11397.15 25899.55 25799.57 146
SR-MVS99.19 13999.00 16499.74 6399.51 19899.72 6899.18 15299.60 15998.85 19199.47 18699.58 19198.38 16399.92 9196.92 26799.54 26399.57 146
MP-MVS-pluss99.14 15298.92 18299.80 2999.83 3999.83 2498.61 24999.63 13796.84 32499.44 19199.58 19198.81 9799.91 11397.70 21599.82 14799.67 68
MP-MVS-pluss: MP-MVS-pluss. MP-MVS-pluss
MS-PatchMatch99.00 18298.97 17399.09 25299.11 31298.19 28198.76 24199.33 27098.49 22999.44 19199.58 19198.21 18099.69 31598.20 16699.62 23699.39 224
LFMVS98.46 25198.19 25899.26 23099.24 28898.52 26299.62 5396.94 35999.87 1799.31 22799.58 19191.04 33199.81 27198.68 13799.42 28399.45 204
VPNet99.46 6199.37 7499.71 8399.82 4699.59 11399.48 7999.70 10099.81 3399.69 10999.58 19197.66 22699.86 19899.17 8399.44 27899.67 68
PMMVS299.48 5499.45 5799.57 14199.76 8698.99 22498.09 30099.90 1498.95 17799.78 7099.58 19199.57 2099.93 7199.48 3699.95 5299.79 30
PatchmatchNetpermissive97.65 29297.80 28597.18 33898.82 34392.49 36299.17 15798.39 34198.12 26298.79 29799.58 19190.71 33899.89 15097.23 25299.41 28499.16 273
Fangjinhua Wang, Silvano Galliani, Christoph Vogel, Pablo Speciale, Marc Pollefeys: PatchmatchNet: Learned Multi-View Patchmatch Stereo.
SCA98.11 27498.36 24097.36 33399.20 29592.99 36098.17 29198.49 33798.24 25699.10 26499.57 19996.01 28099.94 5796.86 27199.62 23699.14 279
Patchmatch-test98.10 27597.98 27298.48 30099.27 28396.48 33199.40 8999.07 31098.81 19699.23 24199.57 19990.11 34499.87 17896.69 28199.64 23399.09 288
VNet99.18 14399.06 14599.56 14599.24 28899.36 16699.33 10599.31 27699.67 6199.47 18699.57 19996.48 26599.84 23499.15 8799.30 29999.47 198
GeoE99.69 2199.66 2299.78 3799.76 8699.76 5199.60 6399.82 3999.46 10499.75 8399.56 20299.63 1499.95 4599.43 4199.88 10399.62 111
9.1498.64 21099.45 22998.81 23199.60 15997.52 29799.28 23399.56 20298.53 14399.83 24595.36 33499.64 233
MSLP-MVS++99.05 17099.09 13798.91 27199.21 29298.36 27498.82 23099.47 23098.85 19198.90 28499.56 20298.78 10699.09 36898.57 14199.68 21699.26 250
TranMVSNet+NR-MVSNet99.54 4799.47 5399.76 4799.58 16199.64 9699.30 11599.63 13799.61 7799.71 10399.56 20298.76 11099.96 3599.14 9399.92 7799.68 61
114514_t98.49 24898.11 26499.64 11199.73 10699.58 11699.24 13699.76 6889.94 36699.42 19799.56 20297.76 21699.86 19897.74 20999.82 14799.47 198
Vis-MVSNet (Re-imp)98.77 21298.58 21899.34 21199.78 7498.88 24099.61 5899.56 18299.11 16199.24 24099.56 20293.00 31299.78 28297.43 23699.89 9599.35 235
test_040299.22 12999.14 11899.45 17899.79 6899.43 14799.28 12399.68 10999.54 8799.40 21099.56 20299.07 6999.82 25596.01 31299.96 4599.11 283
tpmvs97.39 30097.69 29096.52 34798.41 35991.76 36699.30 11598.94 31897.74 28597.85 34999.55 20992.40 31999.73 30196.25 30498.73 33598.06 355
MSDG99.08 16598.98 17299.37 20699.60 15299.13 21097.54 33799.74 8098.84 19499.53 17399.55 20999.10 6199.79 27997.07 26299.86 11999.18 269
bset_n11_16_dypcd98.69 22398.45 23099.42 18699.69 12498.52 26296.06 36596.80 36099.71 4799.73 9699.54 21195.14 28899.96 3599.39 4999.95 5299.79 30
tpmrst97.73 28898.07 26696.73 34498.71 35292.00 36499.10 18098.86 31998.52 22598.92 28199.54 21191.90 32199.82 25598.02 18099.03 31698.37 342
new_pmnet98.88 20198.89 18798.84 28199.70 12197.62 30798.15 29299.50 21997.98 27199.62 13899.54 21198.15 18699.94 5797.55 22899.84 12898.95 308
Anonymous2023120699.35 9299.31 8599.47 17199.74 10399.06 22299.28 12399.74 8099.23 13899.72 9899.53 21497.63 22899.88 16599.11 9599.84 12899.48 193
ITE_SJBPF99.38 20399.63 14599.44 14399.73 8398.56 21999.33 22199.53 21498.88 9299.68 32696.01 31299.65 23199.02 304
test_method91.72 33992.32 34289.91 35693.49 37870.18 38090.28 36999.56 18261.71 37395.39 37099.52 21693.90 29999.94 5798.76 12998.27 34799.62 111
CHOSEN 280x42098.41 25598.41 23598.40 30399.34 26595.89 34196.94 35999.44 23998.80 19899.25 23799.52 21693.51 30799.98 798.94 11599.98 2499.32 241
Regformer-199.32 10399.27 10099.47 17199.41 24098.95 23098.99 20499.48 22699.48 9599.66 12099.52 21698.78 10699.87 17898.36 15199.74 18999.60 126
Regformer-299.34 9799.27 10099.53 15499.41 24099.10 21698.99 20499.53 20399.47 10099.66 12099.52 21698.80 10199.89 15098.31 15799.74 18999.60 126
CANet_DTU98.91 19598.85 19199.09 25298.79 34698.13 28498.18 28999.31 27699.48 9598.86 28999.51 22096.56 26299.95 4599.05 10099.95 5299.19 267
pmmvs398.08 27697.80 28598.91 27199.41 24097.69 30697.87 32499.66 11895.87 33899.50 18299.51 22090.35 34299.97 1798.55 14299.47 27599.08 291
HY-MVS98.23 998.21 27297.95 27498.99 26199.03 32198.24 27799.61 5898.72 32696.81 32598.73 30399.51 22094.06 29899.86 19896.91 26898.20 34898.86 316
ETH3D-3000-0.198.77 21298.50 22799.59 13299.47 22199.53 12498.77 23999.60 15997.33 30799.23 24199.50 22397.91 20399.83 24595.02 33999.67 22399.41 219
miper_lstm_enhance98.65 22698.60 21398.82 28699.20 29597.33 31597.78 32799.66 11899.01 17099.59 14999.50 22394.62 29499.85 21798.12 17599.90 8799.26 250
Anonymous20240521198.75 21598.46 22999.63 11699.34 26599.66 8999.47 8197.65 35299.28 12999.56 16199.50 22393.15 30999.84 23498.62 13999.58 25199.40 221
mPP-MVS99.19 13999.00 16499.76 4799.76 8699.68 8599.38 9399.54 19498.34 25099.01 27299.50 22398.53 14399.93 7197.18 25699.78 17199.66 78
HPM-MVS_fast99.43 6699.30 9099.80 2999.83 3999.81 3199.52 7399.70 10098.35 24699.51 18099.50 22399.31 3799.88 16598.18 17099.84 12899.69 55
h-mvs3398.61 22998.34 24399.44 18099.60 15298.67 25199.27 12699.44 23999.68 5799.32 22399.49 22892.50 317100.00 199.24 7096.51 36799.65 86
test_241102_ONE99.69 12499.82 2899.54 19499.12 16099.82 5299.49 22898.91 8799.52 359
tttt051797.62 29397.20 30298.90 27799.76 8697.40 31399.48 7994.36 36999.06 16899.70 10699.49 22884.55 36699.94 5798.73 13299.65 23199.36 232
eth_miper_zixun_eth98.68 22498.71 20498.60 29599.10 31396.84 32797.52 34199.54 19498.94 17899.58 15199.48 23196.25 27599.76 29298.01 18399.93 7399.21 260
testtj98.56 23798.17 26099.72 7999.45 22999.60 11098.88 21799.50 21996.88 32199.18 25399.48 23197.08 25299.92 9193.69 35599.38 28799.63 100
c3_l98.72 22098.71 20498.72 29199.12 30797.22 31897.68 33299.56 18298.90 18599.54 16899.48 23196.37 27299.73 30197.88 19399.88 10399.21 260
MP-MVScopyleft99.06 16798.83 19599.76 4799.76 8699.71 7199.32 10899.50 21998.35 24698.97 27499.48 23198.37 16499.92 9195.95 31899.75 18199.63 100
Rongxuan Tan, Qing Wang, et al.: MP-MVS: Multi-Scale Windows PatchMatch and Planar Prior Multi-View Stereo.
MVS_111021_LR99.13 15499.03 15799.42 18699.58 16199.32 17597.91 32399.73 8398.68 20999.31 22799.48 23199.09 6399.66 33597.70 21599.77 17599.29 247
XVS99.27 11399.11 12899.75 5799.71 11399.71 7199.37 9799.61 14799.29 12698.76 30199.47 23698.47 15099.88 16597.62 22399.73 19699.67 68
EPNet_dtu97.62 29397.79 28797.11 34096.67 37492.31 36398.51 26598.04 34599.24 13695.77 36899.47 23693.78 30399.66 33598.98 10699.62 23699.37 229
Wanjuan Su, Wenbing Tao: Efficient Edge-Preserving Multi-View Stereo Network for Depth Estimation. AAAI 2023
MVS_111021_HR99.12 15699.02 15899.40 19699.50 20599.11 21297.92 32199.71 9598.76 20599.08 26699.47 23699.17 5399.54 35597.85 19999.76 17899.54 160
cl____98.54 24198.41 23598.92 26999.03 32197.80 30297.46 34399.59 16698.90 18599.60 14699.46 23993.85 30199.78 28297.97 18799.89 9599.17 271
DIV-MVS_self_test98.54 24198.42 23498.92 26999.03 32197.80 30297.46 34399.59 16698.90 18599.60 14699.46 23993.87 30099.78 28297.97 18799.89 9599.18 269
tpm cat196.78 31396.98 30896.16 35298.85 33890.59 37599.08 18799.32 27292.37 36197.73 35599.46 23991.15 33099.69 31596.07 31098.80 32698.21 350
PHI-MVS99.11 16098.95 17799.59 13299.13 30599.59 11399.17 15799.65 12997.88 27899.25 23799.46 23998.97 8099.80 27697.26 24899.82 14799.37 229
pmmvs499.13 15499.06 14599.36 20999.57 17199.10 21698.01 30899.25 29098.78 20199.58 15199.44 24398.24 17699.76 29298.74 13199.93 7399.22 258
XVG-OURS-SEG-HR99.16 14898.99 16999.66 9999.84 3599.64 9698.25 28699.73 8398.39 23899.63 13099.43 24499.70 1199.90 13397.34 24098.64 33799.44 209
CNVR-MVS98.99 18598.80 19999.56 14599.25 28699.43 14798.54 26299.27 28598.58 21898.80 29699.43 24498.53 14399.70 30997.22 25399.59 25099.54 160
PC_three_145297.56 29299.68 11199.41 24699.09 6397.09 37396.66 28499.60 24699.62 111
diffmvs99.34 9799.32 8499.39 19999.67 13898.77 24698.57 25799.81 4899.61 7799.48 18499.41 24698.47 15099.86 19898.97 10899.90 8799.53 165
LF4IMVS99.01 18098.92 18299.27 22899.71 11399.28 18198.59 25299.77 6398.32 25299.39 21199.41 24698.62 12799.84 23496.62 28899.84 12898.69 325
OPU-MVS99.29 22399.12 30799.44 14399.20 14699.40 24999.00 7598.84 37096.54 29099.60 24699.58 140
testdata99.42 18699.51 19898.93 23599.30 27996.20 33498.87 28899.40 24998.33 17099.89 15096.29 30299.28 30199.44 209
Test_1112_low_res98.95 19298.73 20299.63 11699.68 13399.15 20998.09 30099.80 4997.14 31699.46 18999.40 24996.11 27899.89 15099.01 10399.84 12899.84 14
PCF-MVS96.03 1896.73 31595.86 32699.33 21399.44 23199.16 20796.87 36099.44 23986.58 36898.95 27699.40 24994.38 29699.88 16587.93 36799.80 16098.95 308
Andreas Kuhn, Shan Lin, Oliver Erdler: Plane Completion and Filtering for Multi-View Stereo Reconstruction. GCPR 2019
旧先验199.49 21099.29 17999.26 28799.39 25397.67 22299.36 29299.46 202
DROMVSNet99.69 2199.69 1899.68 8999.71 11399.91 299.76 1399.96 499.86 1999.51 18099.39 25399.57 2099.93 7199.64 1899.86 11999.20 264
ACMMPR99.23 12099.06 14599.76 4799.74 10399.69 8299.31 11299.59 16698.36 24199.35 21699.38 25598.61 12999.93 7197.43 23699.75 18199.67 68
miper_ehance_all_eth98.59 23498.59 21598.59 29698.98 32797.07 32197.49 34299.52 21198.50 22799.52 17599.37 25696.41 27099.71 30797.86 19799.62 23699.00 306
HFP-MVS99.25 11699.08 13999.76 4799.73 10699.70 7899.31 11299.59 16698.36 24199.36 21499.37 25698.80 10199.91 11397.43 23699.75 18199.68 61
#test#99.12 15698.90 18699.76 4799.73 10699.70 7899.10 18099.59 16697.60 29199.36 21499.37 25698.80 10199.91 11396.84 27499.75 18199.68 61
CPTT-MVS98.74 21798.44 23299.64 11199.61 15099.38 16099.18 15299.55 18896.49 32999.27 23599.37 25697.11 25199.92 9195.74 32599.67 22399.62 111
DP-MVS Recon98.50 24598.23 25299.31 22099.49 21099.46 13698.56 25899.63 13794.86 35398.85 29099.37 25697.81 21299.59 35296.08 30999.44 27898.88 314
region2R99.23 12099.05 14999.77 4099.76 8699.70 7899.31 11299.59 16698.41 23599.32 22399.36 26198.73 11599.93 7197.29 24399.74 18999.67 68
DU-MVS99.33 10199.21 10999.71 8399.43 23499.56 11998.83 22699.53 20399.38 11699.67 11699.36 26197.67 22299.95 4599.17 8399.81 15599.63 100
UniMVSNet (Re)99.37 8799.26 10299.68 8999.51 19899.58 11698.98 20899.60 15999.43 11299.70 10699.36 26197.70 21799.88 16599.20 7699.87 11299.59 135
NR-MVSNet99.40 7799.31 8599.68 8999.43 23499.55 12299.73 2099.50 21999.46 10499.88 3299.36 26197.54 23099.87 17898.97 10899.87 11299.63 100
UnsupCasMVSNet_eth98.83 20698.57 21999.59 13299.68 13399.45 14198.99 20499.67 11499.48 9599.55 16699.36 26194.92 28999.86 19898.95 11496.57 36699.45 204
GST-MVS99.16 14898.96 17599.75 5799.73 10699.73 6499.20 14699.55 18898.22 25799.32 22399.35 26698.65 12599.91 11396.86 27199.74 18999.62 111
UnsupCasMVSNet_bld98.55 24098.27 24999.40 19699.56 18199.37 16397.97 31699.68 10997.49 29999.08 26699.35 26695.41 28799.82 25597.70 21598.19 35099.01 305
sss98.90 19798.77 20199.27 22899.48 21698.44 26798.72 24599.32 27297.94 27699.37 21399.35 26696.31 27399.91 11398.85 12099.63 23599.47 198
CostFormer96.71 31696.79 31596.46 34998.90 33190.71 37499.41 8898.68 32794.69 35698.14 33799.34 26986.32 36399.80 27697.60 22698.07 35498.88 314
ETH3D cwj APD-0.1698.50 24598.16 26199.51 15999.04 32099.39 15798.47 26899.47 23096.70 32898.78 29999.33 27097.62 22999.86 19894.69 34499.38 28799.28 249
原ACMM199.37 20699.47 22198.87 24299.27 28596.74 32798.26 32899.32 27197.93 20299.82 25595.96 31799.38 28799.43 215
tpm97.15 30596.95 30997.75 32498.91 33094.24 35399.32 10897.96 34797.71 28798.29 32699.32 27186.72 36199.92 9198.10 17896.24 36999.09 288
test22299.51 19899.08 21997.83 32699.29 28195.21 34898.68 30799.31 27397.28 24299.38 28799.43 215
BH-RMVSNet98.41 25598.14 26399.21 23899.21 29298.47 26498.60 25198.26 34498.35 24698.93 27899.31 27397.20 24899.66 33594.32 34699.10 31299.51 177
thisisatest053097.45 29896.95 30998.94 26599.68 13397.73 30499.09 18494.19 37198.61 21699.56 16199.30 27584.30 36799.93 7198.27 16099.54 26399.16 273
MVSFormer99.41 7499.44 5999.31 22099.57 17198.40 27099.77 1199.80 4999.73 4399.63 13099.30 27598.02 19599.98 799.43 4199.69 21199.55 152
jason99.16 14899.11 12899.32 21799.75 9798.44 26798.26 28599.39 25698.70 20899.74 9299.30 27598.54 13999.97 1798.48 14599.82 14799.55 152
jason: jason.
ZNCC-MVS99.22 12999.04 15599.77 4099.76 8699.73 6499.28 12399.56 18298.19 26099.14 25899.29 27898.84 9699.92 9197.53 23199.80 16099.64 95
112198.56 23798.24 25199.52 15699.49 21099.24 19499.30 11599.22 29795.77 34098.52 31899.29 27897.39 23799.85 21795.79 32399.34 29499.46 202
新几何199.52 15699.50 20599.22 19899.26 28795.66 34398.60 31299.28 28097.67 22299.89 15095.95 31899.32 29799.45 204
UniMVSNet_NR-MVSNet99.37 8799.25 10499.72 7999.47 22199.56 11998.97 21099.61 14799.43 11299.67 11699.28 28097.85 21099.95 4599.17 8399.81 15599.65 86
CL-MVSNet_self_test98.71 22198.56 22299.15 24699.22 29098.66 25397.14 35499.51 21598.09 26599.54 16899.27 28296.87 25899.74 29898.43 14798.96 31999.03 300
CP-MVS99.23 12099.05 14999.75 5799.66 13999.66 8999.38 9399.62 14098.38 23999.06 27099.27 28298.79 10499.94 5797.51 23299.82 14799.66 78
AdaColmapbinary98.60 23198.35 24299.38 20399.12 30799.22 19898.67 24899.42 24597.84 28398.81 29499.27 28297.32 24199.81 27195.14 33699.53 26599.10 285
NCCC98.82 20898.57 21999.58 13699.21 29299.31 17698.61 24999.25 29098.65 21198.43 32399.26 28597.86 20899.81 27196.55 28999.27 30499.61 122
TAPA-MVS97.92 1398.03 27897.55 29499.46 17499.47 22199.44 14398.50 26699.62 14086.79 36799.07 26999.26 28598.26 17599.62 34697.28 24599.73 19699.31 243
Andrea Romanoni, Matteo Matteucci: TAPA-MVS: Textureless-Aware PAtchMatch Multi-View Stereo. ICCV 2019
MCST-MVS99.02 17698.81 19799.65 10499.58 16199.49 12998.58 25399.07 31098.40 23799.04 27199.25 28798.51 14899.80 27697.31 24299.51 26899.65 86
HQP_MVS98.90 19798.68 20999.55 14899.58 16199.24 19498.80 23499.54 19498.94 17899.14 25899.25 28797.24 24399.82 25595.84 32199.78 17199.60 126
plane_prior499.25 287
HPM-MVScopyleft99.25 11699.07 14399.78 3799.81 5399.75 5599.61 5899.67 11497.72 28699.35 21699.25 28799.23 4799.92 9197.21 25499.82 14799.67 68
Chunlin Ren, Qingshan Xu, Shikun Zhang, Jiaqi Yang: Hierarchical Prior Mining for Non-local Multi-View Stereo. ICCV 2023
PatchMatch-RL98.68 22498.47 22899.30 22299.44 23199.28 18198.14 29499.54 19497.12 31799.11 26299.25 28797.80 21399.70 30996.51 29299.30 29998.93 310
Effi-MVS+-dtu99.07 16698.92 18299.52 15698.89 33499.78 4199.15 16599.66 11899.34 12098.92 28199.24 29297.69 21999.98 798.11 17699.28 30198.81 321
WTY-MVS98.59 23498.37 23999.26 23099.43 23498.40 27098.74 24299.13 30998.10 26399.21 24799.24 29294.82 29199.90 13397.86 19798.77 32999.49 188
cl2297.56 29697.28 29898.40 30398.37 36196.75 32897.24 35299.37 26397.31 30899.41 20599.22 29487.30 35299.37 36697.70 21599.62 23699.08 291
CANet99.11 16099.05 14999.28 22698.83 34098.56 25998.71 24799.41 24699.25 13499.23 24199.22 29497.66 22699.94 5799.19 7899.97 3399.33 238
baseline197.73 28897.33 29798.96 26399.30 27697.73 30499.40 8998.42 33999.33 12399.46 18999.21 29691.18 32999.82 25598.35 15391.26 37299.32 241
tpm296.35 32296.22 31996.73 34498.88 33791.75 36799.21 14598.51 33593.27 35997.89 34699.21 29684.83 36599.70 30996.04 31198.18 35198.75 324
ETH3 D test640097.76 28697.19 30399.50 16299.38 24899.26 18598.34 27799.49 22492.99 36098.54 31799.20 29895.92 28299.82 25591.14 36299.66 22799.40 221
WR-MVS99.11 16098.93 17899.66 9999.30 27699.42 15098.42 27499.37 26399.04 16999.57 15499.20 29896.89 25799.86 19898.66 13899.87 11299.70 51
F-COLMAP98.74 21798.45 23099.62 12599.57 17199.47 13298.84 22499.65 12996.31 33398.93 27899.19 30097.68 22199.87 17896.52 29199.37 29199.53 165
1112_ss99.05 17098.84 19399.67 9299.66 13999.29 17998.52 26499.82 3997.65 28999.43 19599.16 30196.42 26899.91 11399.07 9999.84 12899.80 24
ab-mvs-re8.26 35211.02 3550.00 3590.00 3820.00 3830.00 3700.00 3830.00 3770.00 37899.16 3010.00 3820.00 3780.00 3760.00 3760.00 374
cdsmvs_eth3d_5k24.88 34333.17 3450.00 3590.00 3820.00 3830.00 37099.62 1400.00 3770.00 37899.13 30399.82 40.00 3780.00 3760.00 3760.00 374
lupinMVS98.96 18998.87 18999.24 23599.57 17198.40 27098.12 29699.18 30398.28 25499.63 13099.13 30398.02 19599.97 1798.22 16499.69 21199.35 235
PVSNet97.47 1598.42 25498.44 23298.35 30599.46 22696.26 33496.70 36299.34 26997.68 28899.00 27399.13 30397.40 23599.72 30397.59 22799.68 21699.08 291
CLD-MVS98.76 21498.57 21999.33 21399.57 17198.97 22797.53 33999.55 18896.41 33099.27 23599.13 30399.07 6999.78 28296.73 28099.89 9599.23 256
Zhaoxin Li, Wangmeng Zuo, Zhaoqi Wang, Lei Zhang: Confidence-based Large-scale Dense Multi-view Stereo. IEEE Transaction on Image Processing, 2020
131498.00 28097.90 28398.27 31198.90 33197.45 31299.30 11599.06 31294.98 35097.21 36099.12 30798.43 15599.67 33195.58 32898.56 34097.71 360
E-PMN97.14 30797.43 29596.27 35098.79 34691.62 36895.54 36799.01 31699.44 10798.88 28599.12 30792.78 31399.68 32694.30 34799.03 31697.50 361
DPM-MVS98.28 26597.94 27899.32 21799.36 25399.11 21297.31 34998.78 32496.88 32198.84 29199.11 30997.77 21599.61 35094.03 35299.36 29299.23 256
CDPH-MVS98.56 23798.20 25599.61 12899.50 20599.46 13698.32 28099.41 24695.22 34799.21 24799.10 31098.34 16899.82 25595.09 33899.66 22799.56 149
MVS95.72 33594.63 33998.99 26198.56 35697.98 29899.30 11598.86 31972.71 37297.30 35799.08 31198.34 16899.74 29889.21 36498.33 34599.26 250
ZD-MVS99.43 23499.61 10899.43 24396.38 33199.11 26299.07 31297.86 20899.92 9194.04 35199.49 272
HPM-MVS++copyleft98.96 18998.70 20799.74 6399.52 19399.71 7198.86 22199.19 30298.47 23198.59 31399.06 31398.08 19199.91 11396.94 26699.60 24699.60 126
Fast-Effi-MVS+-dtu99.20 13699.12 12599.43 18499.25 28699.69 8299.05 19099.82 3999.50 9398.97 27499.05 31498.98 7899.98 798.20 16699.24 30798.62 327
test_prior398.62 22898.34 24399.46 17499.35 25599.22 19897.95 31799.39 25697.87 27998.05 33999.05 31497.90 20499.69 31595.99 31499.49 27299.48 193
test_prior297.95 31797.87 27998.05 33999.05 31497.90 20495.99 31499.49 272
hse-mvs298.52 24398.30 24799.16 24499.29 27898.60 25898.77 23999.02 31499.68 5799.32 22399.04 31792.50 31799.85 21799.24 7097.87 35899.03 300
KD-MVS_2432*160095.89 33095.41 33397.31 33694.96 37593.89 35497.09 35599.22 29797.23 31198.88 28599.04 31779.23 37499.54 35596.24 30596.81 36498.50 338
miper_refine_blended95.89 33095.41 33397.31 33694.96 37593.89 35497.09 35599.22 29797.23 31198.88 28599.04 31779.23 37499.54 35596.24 30596.81 36498.50 338
testgi99.29 10899.26 10299.37 20699.75 9798.81 24398.84 22499.89 1598.38 23999.75 8399.04 31799.36 3499.86 19899.08 9899.25 30599.45 204
AUN-MVS97.82 28397.38 29699.14 24799.27 28398.53 26098.72 24599.02 31498.10 26397.18 36199.03 32189.26 34999.85 21797.94 18997.91 35699.03 300
test_yl98.25 26797.95 27499.13 24899.17 30098.47 26499.00 19998.67 32998.97 17399.22 24599.02 32291.31 32799.69 31597.26 24898.93 32099.24 253
DCV-MVSNet98.25 26797.95 27499.13 24899.17 30098.47 26499.00 19998.67 32998.97 17399.22 24599.02 32291.31 32799.69 31597.26 24898.93 32099.24 253
MSP-MVS99.04 17398.79 20099.81 2699.78 7499.73 6499.35 10299.57 17798.54 22499.54 16898.99 32496.81 25999.93 7196.97 26599.53 26599.77 35
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
TEST999.35 25599.35 17098.11 29899.41 24694.83 35597.92 34498.99 32498.02 19599.85 217
train_agg98.35 26297.95 27499.57 14199.35 25599.35 17098.11 29899.41 24694.90 35197.92 34498.99 32498.02 19599.85 21795.38 33399.44 27899.50 183
agg_prior198.33 26497.92 28099.57 14199.35 25599.36 16697.99 31299.39 25694.85 35497.76 35398.98 32798.03 19399.85 21795.49 32999.44 27899.51 177
PVSNet_Blended98.70 22298.59 21599.02 26099.54 18397.99 29397.58 33699.82 3995.70 34299.34 21998.98 32798.52 14699.77 29097.98 18599.83 13899.30 244
CNLPA98.57 23698.34 24399.28 22699.18 29999.10 21698.34 27799.41 24698.48 23098.52 31898.98 32797.05 25399.78 28295.59 32799.50 27098.96 307
test_899.34 26599.31 17698.08 30299.40 25394.90 35197.87 34898.97 33098.02 19599.84 234
GA-MVS97.99 28197.68 29198.93 26899.52 19398.04 29297.19 35399.05 31398.32 25298.81 29498.97 33089.89 34799.41 36598.33 15599.05 31499.34 237
miper_enhance_ethall98.03 27897.94 27898.32 30798.27 36396.43 33396.95 35899.41 24696.37 33299.43 19598.96 33294.74 29299.69 31597.71 21299.62 23698.83 320
PLCcopyleft97.35 1698.36 25997.99 27099.48 16999.32 27199.24 19498.50 26699.51 21595.19 34998.58 31498.96 33296.95 25699.83 24595.63 32699.25 30599.37 229
Jie Liao, Yanping Fu, Qingan Yan, Chunxia xiao: Pyramid Multi-View Stereo with Local Consistency. Pacific Graphics 2019
xiu_mvs_v1_base_debu99.23 12099.34 7998.91 27199.59 15698.23 27898.47 26899.66 11899.61 7799.68 11198.94 33499.39 2599.97 1799.18 8099.55 25798.51 335
mvs-test198.83 20698.70 20799.22 23798.89 33499.65 9498.88 21799.66 11899.34 12098.29 32698.94 33497.69 21999.96 3598.11 17698.54 34198.04 356
Effi-MVS+99.06 16798.97 17399.34 21199.31 27298.98 22598.31 28199.91 1098.81 19698.79 29798.94 33499.14 5899.84 23498.79 12598.74 33399.20 264
xiu_mvs_v1_base99.23 12099.34 7998.91 27199.59 15698.23 27898.47 26899.66 11899.61 7799.68 11198.94 33499.39 2599.97 1799.18 8099.55 25798.51 335
xiu_mvs_v1_base_debi99.23 12099.34 7998.91 27199.59 15698.23 27898.47 26899.66 11899.61 7799.68 11198.94 33499.39 2599.97 1799.18 8099.55 25798.51 335
EIA-MVS99.12 15699.01 16199.45 17899.36 25399.62 10299.34 10399.79 5598.41 23598.84 29198.89 33998.75 11299.84 23498.15 17499.51 26898.89 313
CS-MVS-test99.43 6699.40 6899.53 15499.51 19899.84 1999.60 6399.94 699.52 9199.10 26498.89 33999.24 4699.90 13399.11 9599.66 22798.84 319
EMVS96.96 31097.28 29895.99 35398.76 35091.03 37195.26 36898.61 33199.34 12098.92 28198.88 34193.79 30299.66 33592.87 35699.05 31497.30 365
thisisatest051596.98 30996.42 31698.66 29499.42 23997.47 31097.27 35094.30 37097.24 31099.15 25698.86 34285.01 36499.87 17897.10 26099.39 28698.63 326
CS-MVS99.40 7799.43 6299.29 22399.44 23199.72 6899.36 10099.91 1099.71 4799.28 23398.83 34399.22 4899.86 19899.40 4899.77 17598.29 345
NP-MVS99.40 24399.13 21098.83 343
HQP-MVS98.36 25998.02 26999.39 19999.31 27298.94 23197.98 31399.37 26397.45 30098.15 33398.83 34396.67 26099.70 30994.73 34199.67 22399.53 165
MAR-MVS98.24 26997.92 28099.19 24198.78 34899.65 9499.17 15799.14 30795.36 34598.04 34198.81 34697.47 23299.72 30395.47 33199.06 31398.21 350
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
API-MVS98.38 25898.39 23798.35 30598.83 34099.26 18599.14 16799.18 30398.59 21798.66 30898.78 34798.61 12999.57 35494.14 34999.56 25396.21 368
BH-untuned98.22 27198.09 26598.58 29799.38 24897.24 31798.55 25998.98 31797.81 28499.20 25298.76 34897.01 25499.65 34294.83 34098.33 34598.86 316
Fast-Effi-MVS+99.02 17698.87 18999.46 17499.38 24899.50 12899.04 19299.79 5597.17 31498.62 31098.74 34999.34 3599.95 4598.32 15699.41 28498.92 311
MVEpermissive92.54 2296.66 31796.11 32198.31 30999.68 13397.55 30997.94 31995.60 36699.37 11790.68 37498.70 35096.56 26298.61 37286.94 37299.55 25798.77 323
Simon Fuhrmann, Fabian Langguth, Michael Goesele: MVE - A Multi-View Reconstruction Environment. EUROGRAPHICS Workshops on Graphics and Cultural Heritage (2014)
PAPM95.61 33694.71 33898.31 30999.12 30796.63 32996.66 36398.46 33890.77 36596.25 36598.68 35193.01 31199.69 31581.60 37397.86 35998.62 327
test-LLR97.15 30596.95 30997.74 32598.18 36695.02 34897.38 34596.10 36198.00 26897.81 35098.58 35290.04 34599.91 11397.69 22198.78 32798.31 343
test-mter96.23 32695.73 32997.74 32598.18 36695.02 34897.38 34596.10 36197.90 27797.81 35098.58 35279.12 37699.91 11397.69 22198.78 32798.31 343
PAPM_NR98.36 25998.04 26799.33 21399.48 21698.93 23598.79 23799.28 28497.54 29598.56 31698.57 35497.12 25099.69 31594.09 35098.90 32499.38 226
TESTMET0.1,196.24 32595.84 32797.41 33298.24 36493.84 35697.38 34595.84 36598.43 23297.81 35098.56 35579.77 37399.89 15097.77 20498.77 32998.52 334
ETV-MVS99.18 14399.18 11299.16 24499.34 26599.28 18199.12 17799.79 5599.48 9598.93 27898.55 35699.40 2499.93 7198.51 14499.52 26798.28 346
xiu_mvs_v2_base99.02 17699.11 12898.77 28899.37 25198.09 28998.13 29599.51 21599.47 10099.42 19798.54 35799.38 2999.97 1798.83 12199.33 29698.24 348
TR-MVS97.44 29997.15 30498.32 30798.53 35797.46 31198.47 26897.91 34996.85 32398.21 33298.51 35896.42 26899.51 36092.16 35897.29 36297.98 357
PS-MVSNAJ99.00 18299.08 13998.76 28999.37 25198.10 28898.00 31099.51 21599.47 10099.41 20598.50 35999.28 4199.97 1798.83 12199.34 29498.20 352
ET-MVSNet_ETH3D96.78 31396.07 32298.91 27199.26 28597.92 29997.70 33196.05 36497.96 27592.37 37398.43 36087.06 35499.90 13398.27 16097.56 36198.91 312
baseline296.83 31296.28 31898.46 30199.09 31596.91 32598.83 22693.87 37297.23 31196.23 36798.36 36188.12 35199.90 13396.68 28298.14 35298.57 332
gm-plane-assit97.59 37189.02 37893.47 35898.30 36299.84 23496.38 299
DeepMVS_CXcopyleft97.98 31699.69 12496.95 32399.26 28775.51 37195.74 36998.28 36396.47 26699.62 34691.23 36197.89 35797.38 363
PAPR97.56 29697.07 30599.04 25998.80 34598.11 28797.63 33399.25 29094.56 35798.02 34298.25 36497.43 23499.68 32690.90 36398.74 33399.33 238
PMMVS98.49 24898.29 24899.11 25098.96 32898.42 26997.54 33799.32 27297.53 29698.47 32298.15 36597.88 20799.82 25597.46 23499.24 30799.09 288
test0.0.03 197.37 30196.91 31298.74 29097.72 37097.57 30897.60 33597.36 35898.00 26899.21 24798.02 36690.04 34599.79 27998.37 15095.89 37098.86 316
BH-w/o97.20 30497.01 30797.76 32399.08 31695.69 34298.03 30798.52 33495.76 34197.96 34398.02 36695.62 28599.47 36292.82 35797.25 36398.12 354
alignmvs98.28 26597.96 27399.25 23399.12 30798.93 23599.03 19498.42 33999.64 6998.72 30497.85 36890.86 33699.62 34698.88 11999.13 31099.19 267
PVSNet_095.53 1995.85 33395.31 33597.47 33098.78 34893.48 35895.72 36699.40 25396.18 33597.37 35697.73 36995.73 28399.58 35395.49 32981.40 37399.36 232
canonicalmvs99.02 17699.00 16499.09 25299.10 31398.70 24999.61 5899.66 11899.63 7298.64 30997.65 37099.04 7399.54 35598.79 12598.92 32299.04 299
DWT-MVSNet_test96.03 32995.80 32896.71 34698.50 35891.93 36599.25 13597.87 35095.99 33796.81 36397.61 37181.02 37099.66 33597.20 25597.98 35598.54 333
cascas96.99 30896.82 31497.48 32997.57 37395.64 34396.43 36499.56 18291.75 36297.13 36297.61 37195.58 28698.63 37196.68 28299.11 31198.18 353
IB-MVS95.41 2095.30 33794.46 34197.84 32198.76 35095.33 34697.33 34896.07 36396.02 33695.37 37197.41 37376.17 37999.96 3597.54 22995.44 37198.22 349
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
thres600view796.60 31896.16 32097.93 31899.63 14596.09 33899.18 15297.57 35398.77 20298.72 30497.32 37487.04 35599.72 30388.57 36598.62 33897.98 357
thres100view90096.39 32196.03 32397.47 33099.63 14595.93 33999.18 15297.57 35398.75 20698.70 30697.31 37587.04 35599.67 33187.62 36898.51 34296.81 366
GG-mvs-BLEND97.36 33397.59 37196.87 32699.70 2888.49 37994.64 37297.26 37680.66 37199.12 36791.50 36096.50 36896.08 370
tfpn200view996.30 32495.89 32497.53 32899.58 16196.11 33699.00 19997.54 35698.43 23298.52 31896.98 37786.85 35799.67 33187.62 36898.51 34296.81 366
thres40096.40 32095.89 32497.92 31999.58 16196.11 33699.00 19997.54 35698.43 23298.52 31896.98 37786.85 35799.67 33187.62 36898.51 34297.98 357
thres20096.09 32795.68 33097.33 33599.48 21696.22 33598.53 26397.57 35398.06 26798.37 32596.73 37986.84 35999.61 35086.99 37198.57 33996.16 369
X-MVStestdata96.09 32794.87 33799.75 5799.71 11399.71 7199.37 9799.61 14799.29 12698.76 30161.30 38098.47 15099.88 16597.62 22399.73 19699.67 68
test_post52.41 38190.25 34399.86 198
test_post199.14 16751.63 38289.54 34899.82 25596.86 271
testmvs28.94 34233.33 34415.79 35826.03 3809.81 38296.77 36115.67 38111.55 37623.87 37750.74 38319.03 3818.53 37723.21 37533.07 37429.03 373
test12329.31 34133.05 34618.08 35725.93 38112.24 38197.53 33910.93 38211.78 37524.21 37650.08 38421.04 3808.60 37623.51 37432.43 37533.39 372
FOURS199.83 3999.89 899.74 1799.71 9599.69 5599.63 130
MSC_two_6792asdad99.74 6399.03 32199.53 12499.23 29499.92 9197.77 20499.69 21199.78 32
No_MVS99.74 6399.03 32199.53 12499.23 29499.92 9197.77 20499.69 21199.78 32
eth-test20.00 382
eth-test0.00 382
IU-MVS99.69 12499.77 4499.22 29797.50 29899.69 10997.75 20899.70 20899.77 35
save fliter99.53 18899.25 18998.29 28299.38 26299.07 164
test_0728_SECOND99.83 2199.70 12199.79 3899.14 16799.61 14799.92 9197.88 19399.72 20299.77 35
GSMVS99.14 279
test_part299.62 14999.67 8799.55 166
sam_mvs190.81 33799.14 279
sam_mvs90.52 341
MTGPAbinary99.53 203
MTMP99.09 18498.59 333
test9_res95.10 33799.44 27899.50 183
agg_prior294.58 34599.46 27799.50 183
agg_prior99.35 25599.36 16699.39 25697.76 35399.85 217
test_prior499.19 20598.00 310
test_prior99.46 17499.35 25599.22 19899.39 25699.69 31599.48 193
旧先验297.94 31995.33 34698.94 27799.88 16596.75 278
新几何298.04 306
无先验98.01 30899.23 29495.83 33999.85 21795.79 32399.44 209
原ACMM297.92 321
testdata299.89 15095.99 314
segment_acmp98.37 164
testdata197.72 32997.86 282
test1299.54 15299.29 27899.33 17399.16 30598.43 32397.54 23099.82 25599.47 27599.48 193
plane_prior799.58 16199.38 160
plane_prior699.47 22199.26 18597.24 243
plane_prior599.54 19499.82 25595.84 32199.78 17199.60 126
plane_prior399.31 17698.36 24199.14 258
plane_prior298.80 23498.94 178
plane_prior199.51 198
plane_prior99.24 19498.42 27497.87 27999.71 206
n20.00 383
nn0.00 383
door-mid99.83 34
test1199.29 281
door99.77 63
HQP5-MVS98.94 231
HQP-NCC99.31 27297.98 31397.45 30098.15 333
ACMP_Plane99.31 27297.98 31397.45 30098.15 333
BP-MVS94.73 341
HQP4-MVS98.15 33399.70 30999.53 165
HQP3-MVS99.37 26399.67 223
HQP2-MVS96.67 260
MDTV_nov1_ep13_2view91.44 37099.14 16797.37 30599.21 24791.78 32596.75 27899.03 300
ACMMP++_ref99.94 65
ACMMP++99.79 165
Test By Simon98.41 158