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|---|---|---|---|---|---|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
LDDMM-Face
|
https://arxiv.org/abs/2108.00690v1
|
NME (inter-ocular)
|
4.63
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
LDDMM-Face
|
https://arxiv.org/abs/2108.00690v1
|
AUC@10 (inter-ocular)
|
55.09
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
LDDMM-Face
|
https://arxiv.org/abs/2108.00690v1
|
FR@10 (inter-ocular)
|
3.68
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
GRegNet + LRefNet
|
http://openaccess.thecvf.com/content_CVPRW_2019/html/AMFG/Su_Efficient_and_Accurate_Face_Alignment_by_Global_Regression_and_Cascaded_CVPRW_2019_paper.html
|
NME (inter-ocular)
|
4.65
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
GRegNet + LRefNet
|
http://openaccess.thecvf.com/content_CVPRW_2019/html/AMFG/Su_Efficient_and_Accurate_Face_Alignment_by_Global_Regression_and_Cascaded_CVPRW_2019_paper.html
|
AUC@10 (inter-ocular)
|
58.4
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
GRegNet + LRefNet
|
http://openaccess.thecvf.com/content_CVPRW_2019/html/AMFG/Su_Efficient_and_Accurate_Face_Alignment_by_Global_Regression_and_Cascaded_CVPRW_2019_paper.html
|
FR@10 (inter-ocular)
|
4.88
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
3DDE
|
https://arxiv.org/abs/1902.01831v2
|
NME (inter-ocular)
|
4.68
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
3DDE
|
https://arxiv.org/abs/1902.01831v2
|
AUC@10 (inter-ocular)
|
55.44
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
3DDE
|
https://arxiv.org/abs/1902.01831v2
|
FR@10 (inter-ocular)
|
5.04
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
Wing
|
http://arxiv.org/abs/1711.06753v5
|
NME (inter-ocular)
|
5.11
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
Wing
|
http://arxiv.org/abs/1711.06753v5
|
AUC@10 (inter-ocular)
|
55.4
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
Wing
|
http://arxiv.org/abs/1711.06753v5
|
FR@10 (inter-ocular)
|
6.00
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
ATPN
|
https://arxiv.org/abs/2103.07615v3
|
NME (inter-ocular)
|
5.13
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
ATPN
|
https://arxiv.org/abs/2103.07615v3
|
AUC@10 (inter-ocular)
|
55.7
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
ATPN
|
https://arxiv.org/abs/2103.07615v3
|
FR@10 (inter-ocular)
|
6.27
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
LAB
|
http://arxiv.org/abs/1805.10483v1
|
NME (inter-ocular)
|
5.27
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
LAB
|
http://arxiv.org/abs/1805.10483v1
|
AUC@10 (inter-ocular)
|
53.2
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
LAB
|
http://arxiv.org/abs/1805.10483v1
|
FR@10 (inter-ocular)
|
7.56
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
SCAF
|
https://link.springer.com/chapter/10.1007/978-3-031-06427-2_36
|
NME (inter-ocular)
|
5.50
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
CFSS
|
https://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Zhu_Face_Alignment_by_2015_CVPR_paper.html
|
NME (inter-ocular)
|
9.07
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
CFSS
|
https://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Zhu_Face_Alignment_by_2015_CVPR_paper.html
|
AUC@10 (inter-ocular)
|
36.6
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
CFSS
|
https://www.cv-foundation.org/openaccess/content_cvpr_2015/html/Zhu_Face_Alignment_by_2015_CVPR_paper.html
|
FR@10 (inter-ocular)
|
20.56
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
MobileNetV2
|
https://arxiv.org/abs/2103.00119v3
|
NME (inter-ocular)
|
9.41
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
SDM
|
http://openaccess.thecvf.com/content_cvpr_2013/html/Xiong_Supervised_Descent_Method_2013_CVPR_paper.html
|
NME (inter-ocular)
|
10.29
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
SDM
|
http://openaccess.thecvf.com/content_cvpr_2013/html/Xiong_Supervised_Descent_Method_2013_CVPR_paper.html
|
AUC@10 (inter-ocular)
|
30.02
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
SDM
|
http://openaccess.thecvf.com/content_cvpr_2013/html/Xiong_Supervised_Descent_Method_2013_CVPR_paper.html
|
FR@10 (inter-ocular)
|
29.40
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
ASMNet
|
https://arxiv.org/abs/2103.00119v3
|
NME (inter-ocular)
|
10.77
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
DVLN
|
http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/html/Wu_Leveraging_Intra_and_CVPR_2017_paper.html
|
NME (inter-ocular)
|
10.84
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
DVLN
|
http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/html/Wu_Leveraging_Intra_and_CVPR_2017_paper.html
|
AUC@10 (inter-ocular)
|
45.6
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
DVLN
|
http://openaccess.thecvf.com/content_cvpr_2017_workshops/w33/html/Wu_Leveraging_Intra_and_CVPR_2017_paper.html
|
FR@10 (inter-ocular)
|
10.84
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
ESR
|
https://ieeexplore.ieee.org/document/6248015
|
NME (inter-ocular)
|
11.13
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
ESR
|
https://ieeexplore.ieee.org/document/6248015
|
AUC@10 (inter-ocular)
|
27.74
|
Facial Recognition and Modelling > Face Alignment
|
WFLW
|
ESR
|
https://ieeexplore.ieee.org/document/6248015
|
FR@10 (inter-ocular)
|
35.24
|
Facial Recognition and Modelling > Face Alignment
|
CelebA + AFLW Unaligned
|
Progressive Face SR
|
https://arxiv.org/abs/1908.08239v1
|
MOS
|
3.73
|
Facial Recognition and Modelling > Face Alignment
|
CelebA + AFLW Unaligned
|
Progressive Face SR
|
https://arxiv.org/abs/1908.08239v1
|
MS-SSIM
|
0.897
|
Facial Recognition and Modelling > Face Alignment
|
CelebA + AFLW Unaligned
|
Progressive Face SR
|
https://arxiv.org/abs/1908.08239v1
|
PSNR
|
22.96
|
Facial Recognition and Modelling > Face Alignment
|
CelebA + AFLW Unaligned
|
Progressive Face SR
|
https://arxiv.org/abs/1908.08239v1
|
SSIM
|
0.695
|
Facial Recognition and Modelling > Face Alignment
|
AFLW-PIFA (21 points)
|
Face alignment
|
https://www.adrianbulat.com/downloads/BMVC16/cale_bmvc16.pdf
|
NME
|
2.63%
|
Facial Recognition and Modelling > Face Alignment
|
AFLW-Full
|
Binary Face Alignment
|
http://arxiv.org/abs/1703.00862v2
|
Mean NME
|
2.85
|
Facial Recognition and Modelling > Face Alignment
|
AFLW-Full
|
AnchorFace
|
https://arxiv.org/abs/2007.03221v3
|
Mean NME
|
1.56
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
SPIGA
|
https://arxiv.org/abs/2210.07233v1
|
NME (box)
|
2.03
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
SPIGA
|
https://arxiv.org/abs/2210.07233v1
|
AUC@7 (box)
|
71.0
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
SPIGA
|
https://arxiv.org/abs/2210.07233v1
|
NME (inter-ocular)
|
3.43
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
SPIGA
|
https://arxiv.org/abs/2210.07233v1
|
AUC@8 (inter-ocular)
|
57.27
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
SPIGA
|
https://arxiv.org/abs/2210.07233v1
|
FR@8 (inter-ocular)
|
0.67
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
DTLD-s
|
https://arxiv.org/abs/2208.10808v1
|
NME (box)
|
2.05
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
DTLD-s
|
https://arxiv.org/abs/2208.10808v1
|
AUC@7 (box)
|
70.9
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
LUVLi
|
https://arxiv.org/abs/2004.02980v1
|
NME (box)
|
2.24
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
LUVLi
|
https://arxiv.org/abs/2004.02980v1
|
AUC@7 (box)
|
68.3
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
KDN
|
http://openaccess.thecvf.com/content_ICCV_2019/html/Chen_Face_Alignment_With_Kernel_Density_Deep_Neural_Network_ICCV_2019_paper.html
|
NME (box)
|
2.49
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
KDN
|
http://openaccess.thecvf.com/content_ICCV_2019/html/Chen_Face_Alignment_With_Kernel_Density_Deep_Neural_Network_ICCV_2019_paper.html
|
AUC@7 (box)
|
67.3
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
3DDE
|
https://arxiv.org/abs/1902.01831v2
|
NME (inter-ocular)
|
3.73
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
3DDE
|
https://arxiv.org/abs/1902.01831v2
|
AUC@8 (inter-ocular)
|
53.94
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
3DDE
|
https://arxiv.org/abs/1902.01831v2
|
FR@8 (inter-ocular)
|
2.33
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
DCFE
|
http://openaccess.thecvf.com/content_ECCV_2018/html/Roberto_Valle_A_Deeply-initialized_Coarse-to-fine_ECCV_2018_paper.html
|
NME (inter-ocular)
|
3.88
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
DCFE
|
http://openaccess.thecvf.com/content_ECCV_2018/html/Roberto_Valle_A_Deeply-initialized_Coarse-to-fine_ECCV_2018_paper.html
|
AUC@8 (inter-ocular)
|
52.42
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
DCFE
|
http://openaccess.thecvf.com/content_ECCV_2018/html/Roberto_Valle_A_Deeply-initialized_Coarse-to-fine_ECCV_2018_paper.html
|
FR@8 (inter-ocular)
|
1.83
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
DAN
|
http://arxiv.org/abs/1706.01789v2
|
NME (inter-ocular)
|
4.30
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
DAN
|
http://arxiv.org/abs/1706.01789v2
|
AUC@8 (inter-ocular)
|
47.00
|
Facial Recognition and Modelling > Face Alignment
|
300W Split 2
|
DAN
|
http://arxiv.org/abs/1706.01789v2
|
FR@8 (inter-ocular)
|
2.67
|
Facial Recognition and Modelling > Face Alignment
|
AFLW2000
|
MNN+ORB (Reannotated)
|
https://arxiv.org/abs/2202.02299v1
|
Error rate
|
2.58
|
Facial Recognition and Modelling > Face Alignment
|
AFLW2000
|
Nonlinear 3D Face Morphable Model
|
http://arxiv.org/abs/1804.03786v3
|
Error rate
|
4.70
|
Facial Recognition and Modelling > Face Alignment
|
AFLW2000
|
MCL
|
http://arxiv.org/abs/1808.01558v2
|
Error rate
|
5.38
|
Facial Recognition and Modelling > Face Alignment
|
AFLW2000
|
3DDFA
|
http://arxiv.org/abs/1511.07212v1
|
Error rate
|
5.42
|
Facial Recognition and Modelling > Face Alignment
|
AFLW2000
|
Dlib (68 points)
|
http://openaccess.thecvf.com/content_cvpr_2014/html/Kazemi_One_Millisecond_Face_2014_CVPR_paper.html
|
Error rate
|
10.545
|
Facial Recognition and Modelling > Face Alignment
|
IBUG
|
DenseU-Net + Dual Transformer
|
http://arxiv.org/abs/1812.01936v1
|
Mean Error Rate
|
6.73%
|
Facial Recognition and Modelling > Face Alignment
|
IBUG
|
DCFE (inter pupils normalization)
|
http://openaccess.thecvf.com/content_ECCV_2018/html/Roberto_Valle_A_Deeply-initialized_Coarse-to-fine_ECCV_2018_paper.html
|
Mean Error Rate
|
7.54%
|
Facial Recognition and Modelling > Face Alignment
|
FaceScape
|
ASM
|
https://arxiv.org/abs/2304.09423v3
|
NME
|
0.21
|
Facial Recognition and Modelling > Face Alignment
|
FaceScape
|
ImFace
|
https://arxiv.org/abs/2203.14510v2
|
NME
|
0.257
|
Facial Recognition and Modelling > Face Alignment
|
FaceScape
|
FLAME
|
http://flame.is.tue.mpg.de/
|
NME
|
0.341
|
Facial Recognition and Modelling > Face Alignment
|
FaceScape
|
CoMA
|
http://arxiv.org/abs/1807.10267v3
|
NME
|
1.088
|
Facial Recognition and Modelling > Face Alignment
|
AFLW-LFPA
|
FPN
|
http://arxiv.org/abs/1803.07835v1
|
Mean NME
|
2.93%
|
Facial Recognition and Modelling > Face Alignment
|
AFLW-LFPA
|
DeFA
|
http://arxiv.org/abs/1709.01442v1
|
Mean NME
|
3.86%
|
Facial Recognition and Modelling > Face Alignment
|
AFLW-LFPA
|
Ours
|
http://arxiv.org/abs/1808.04803v1
|
NME
|
3.02
|
Facial Recognition and Modelling > Age Estimation
|
LAGENDA
|
MiVOLO-V2
|
https://arxiv.org/abs/2403.02302v4
|
MAE
|
3.65
|
Facial Recognition and Modelling > Age Estimation
|
LAGENDA
|
MiVOLO-D1
|
https://arxiv.org/abs/2307.04616v2
|
MAE
|
3.99
|
Facial Recognition and Modelling > Age Estimation
|
AgeDB
|
MiVOLO-D1
|
https://arxiv.org/abs/2307.04616v2
|
MAE
|
5.55
|
Facial Recognition and Modelling > Age Estimation
|
AgeDB
|
FaRL+MLP
|
https://arxiv.org/abs/2307.04570v3
|
MAE
|
5.64
|
Facial Recognition and Modelling > Age Estimation
|
AgeDB
|
ResNet-50-OR-CNN
|
https://arxiv.org/abs/2307.04570v3
|
MAE
|
5.78
|
Facial Recognition and Modelling > Age Estimation
|
AgeDB
|
ResNet-50-DLDL
|
https://arxiv.org/abs/2307.04570v3
|
MAE
|
5.80
|
Facial Recognition and Modelling > Age Estimation
|
AgeDB
|
ResNet-50-DLDL-v2
|
https://arxiv.org/abs/2307.04570v3
|
MAE
|
5.80
|
Facial Recognition and Modelling > Age Estimation
|
AgeDB
|
ResNet-50-Cross-Entropy
|
https://arxiv.org/abs/2307.04570v3
|
MAE
|
5.81
|
Facial Recognition and Modelling > Age Estimation
|
AgeDB
|
ResNet-50-SORD
|
https://arxiv.org/abs/2307.04570v3
|
MAE
|
5.81
|
Facial Recognition and Modelling > Age Estimation
|
AgeDB
|
ResNet-50-Mean-Variance
|
https://arxiv.org/abs/2307.04570v3
|
MAE
|
5.85
|
Facial Recognition and Modelling > Age Estimation
|
AgeDB
|
ResNet-50-Unimodal-Concentrated
|
https://arxiv.org/abs/2307.04570v3
|
MAE
|
5.90
|
Facial Recognition and Modelling > Age Estimation
|
AgeDB
|
ResNet-50-Regression
|
https://arxiv.org/abs/2307.04570v3
|
MAE
|
6.23
|
Facial Recognition and Modelling > Age Estimation
|
MORPH album2 (Caucasian)
|
MWR
|
https://arxiv.org/abs/2203.13122v1
|
MAE
|
2.13
|
Facial Recognition and Modelling > Age Estimation
|
MORPH album2 (Caucasian)
|
MetaAge
|
https://arxiv.org/abs/2207.05288v1
|
MAE
|
2.23
|
Facial Recognition and Modelling > Age Estimation
|
MORPH album2 (Caucasian)
|
DRC-ORID
|
https://openreview.net/forum?id=Yz-XtK5RBxB
|
MAE
|
2.26
|
Facial Recognition and Modelling > Age Estimation
|
MORPH album2 (Caucasian)
|
OrdinalCLIP
|
https://arxiv.org/abs/2206.02338v2
|
MAE
|
2.32
|
Facial Recognition and Modelling > Age Estimation
|
MORPH album2 (Caucasian)
|
POE
|
https://arxiv.org/abs/2103.13629v1
|
MAE
|
2.35
|
Facial Recognition and Modelling > Age Estimation
|
MORPH album2 (Caucasian)
|
AVDL
|
https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/4328_ECCV_2020_paper.php
|
MAE
|
2.37
|
Facial Recognition and Modelling > Age Estimation
|
MORPH album2 (Caucasian)
|
BridgeNet
|
http://arxiv.org/abs/1904.03358v1
|
MAE
|
2.38
|
Facial Recognition and Modelling > Age Estimation
|
MORPH album2 (Caucasian)
|
OL
|
https://openreview.net/forum?id=HygsuaNFwr
|
MAE
|
2.41
|
Facial Recognition and Modelling > Age Estimation
|
MORPH album2 (Caucasian)
|
DEX
|
https://link.springer.com/article/10.1007/s11263-016-0940-3
|
MAE
|
2.68
|
Facial Recognition and Modelling > Age Estimation
|
MORPH album2 (Caucasian)
|
DRFs
|
http://arxiv.org/abs/1712.07195v1
|
MAE
|
2.91
|
Facial Recognition and Modelling > Age Estimation
|
MORPH album2 (Caucasian)
|
dLDLF
|
http://arxiv.org/abs/1702.06086v4
|
MAE
|
3.02
|
Facial Recognition and Modelling > Age Estimation
|
AFAD
|
CORAL
|
https://arxiv.org/abs/1901.07884v7
|
MAE
|
3.48
|
Facial Recognition and Modelling > Age Estimation
|
AFAD
|
ResNet-50-Unimodal-Concentrated
|
https://arxiv.org/abs/2307.04570v3
|
MAE
|
3.20
|
Facial Recognition and Modelling > Age Estimation
|
AFAD
|
ResNet-50-Regression
|
https://arxiv.org/abs/2307.04570v3
|
MAE
|
3.17
|
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