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|---|---|---|---|---|---|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER+
|
Local Learning Deep + BOW
|
https://arxiv.org/abs/1804.10892v7
|
Accuracy
|
87.76
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER+
|
Ensemble with Shared Representations (ESR-9)
|
https://arxiv.org/abs/2001.06338v1
|
Accuracy
|
87.15
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
Aff-Wild2
|
GReFEL
|
https://arxiv.org/abs/2410.15927v1
|
Accuracy
|
72.48
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
Aff-Wild2
|
EmoAffectNet LSTM
|
https://www.sciencedirect.com/science/article/abs/pii/S0925231222012656
|
UAR
|
52.9
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FERG
|
DeepEmotion
|
http://arxiv.org/abs/1902.01019v1
|
Accuracy
|
99.3
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FERG
|
GReFEL
|
https://arxiv.org/abs/2410.15927v1
|
Accuracy
|
98.18
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
BP4D
|
Norface
|
https://arxiv.org/abs/2407.15617v1
|
ICC
|
0.74
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
BP4D
|
Ours (VGG-F)
|
https://arxiv.org/abs/2103.16554v2
|
ICC
|
0.719
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
Cohn-Kanade
|
Sequential forward selection
|
http://arxiv.org/abs/1701.01879v2
|
Accuracy
|
88.7%
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
JAFFE
|
TL
|
https://www.mdpi.com/2079-9292/10/9/1036
|
Accuracy
|
99.52
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
JAFFE
|
GReFEL
|
https://arxiv.org/abs/2410.15927v1
|
Accuracy
|
96.67
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
JAFFE
|
ViT
|
https://arxiv.org/abs/2107.03107v4
|
Accuracy
|
94.83
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
JAFFE
|
DeepEmotion
|
http://arxiv.org/abs/1902.01019v1
|
Accuracy
|
92.8
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
EfficientFER
|
https://ieeexplore.ieee.org/document/11017006
|
Accuracy
|
82.47
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
FERNeXt-SDAFE
|
https://ieeexplore.ieee.org/abstract/document/10888031
|
Accuracy
|
81.33
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
ResEmoteNet
|
https://arxiv.org/abs/2409.10545v2
|
Accuracy
|
79.79
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
Ensemble ResMaskingNet with 6 other CNNs
|
https://ieeexplore.ieee.org/document/9411919
|
Accuracy
|
76.82
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
Mini-ResEmoteNet (A)
|
https://arxiv.org/abs/2501.18538v1
|
Accuracy
|
76.33
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
EmoNeXt
|
https://arxiv.org/abs/2501.08199v1
|
Accuracy
|
76.12
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
Segmentation VGG-19
|
https://link.springer.com/article/10.1007/s41870-023-01184-z
|
Accuracy
|
75.97
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
Local Learning Deep+BOW
|
https://arxiv.org/abs/1804.10892v7
|
Accuracy
|
75.42
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
LHC-Net
|
https://arxiv.org/abs/2111.07224v2
|
Accuracy
|
74.42
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
Residual Masking Network
|
https://ieeexplore.ieee.org/document/9411919
|
Accuracy
|
74.14
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
ResNet18 With Tricks
|
https://github.com/LetheSec/Fer2013-Recognition-Pytorch/blob/main/README.md
|
Accuracy
|
73.70
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
VGGNet
|
https://arxiv.org/abs/2105.03588v1
|
Accuracy
|
73.28
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
CNN Hyperparameter Optimisation
|
https://www.semanticscholar.org/paper/Convolutional-Neural-Network-Hyperparameters-for-Vulpe-Grigora%C5%9Fi-Grigore/fe344427eafecc60a1ba29beb87a46e91b7c1420#related-papers
|
Accuracy
|
72.16
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
Ad-Corre
|
https://ieeexplore.ieee.org/document/9727163
|
Accuracy
|
72.03
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
Mini-ResEmoteNet (B)
|
https://arxiv.org/abs/2501.18538v1
|
Accuracy
|
70.20
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
DeepEmotion
|
http://arxiv.org/abs/1902.01019v1
|
Accuracy
|
70.02
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
FER2013
|
Local Learning BOW
|
http://arxiv.org/abs/1307.0414v1
|
Accuracy
|
67.48
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
ResEmoteNet
|
https://arxiv.org/abs/2409.10545v2
|
Overall Accuracy
|
94.76
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
FMAE
|
https://arxiv.org/abs/2407.11243v2
|
Overall Accuracy
|
93.45
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
QCS
|
https://arxiv.org/abs/2411.01988v5
|
Overall Accuracy
|
93.02
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
Norface
|
https://arxiv.org/abs/2407.15617v1
|
Overall Accuracy
|
92.97
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
S2D
|
https://arxiv.org/abs/2312.05447v2
|
Overall Accuracy
|
92.57
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
BTN
|
https://arxiv.org/abs/2407.04218v1
|
Overall Accuracy
|
92.54
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
BTN
|
https://arxiv.org/abs/2407.04218v1
|
Avg. Accuracy
|
87.3
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
GReFEL
|
https://arxiv.org/abs/2410.15927v1
|
Overall Accuracy
|
92.47
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
DDAMFN++
|
https://scholar.google.com/citations?view_op=view_citation&hl=zh-CN&user=P4efBMcAAAAJ&citation_for_view=P4efBMcAAAAJ:d1gkVwhDpl0C
|
Overall Accuracy
|
92.34
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
DCJT
|
https://ieeexplore.ieee.org/document/10483295
|
Overall Accuracy
|
92.24
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
POSTER++
|
https://arxiv.org/abs/2301.12149v2
|
Overall Accuracy
|
92.21
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
APViT
|
https://arxiv.org/abs/2212.05463v1
|
Overall Accuracy
|
91.98
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
DDAMFN
|
https://scholar.google.com/citations?view_op=view_citation&hl=zh-CN&user=P4efBMcAAAAJ&citation_for_view=P4efBMcAAAAJ:d1gkVwhDpl0C
|
Overall Accuracy
|
91.35
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
ViT-base + MAE
|
https://arxiv.org/abs/2207.11081v4
|
Overall Accuracy
|
91.07
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
LFNSB
|
https://www.preprints.org/manuscript/202408.1304/v1
|
Overall Accuracy
|
91.07
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
ExpLLM
|
https://arxiv.org/abs/2409.02828v1
|
Overall Accuracy
|
91.03
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
EAC(ResNet-50)
|
https://arxiv.org/abs/2207.10299v2
|
Overall Accuracy
|
90.35
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
Ada-DF
|
https://ieeexplore.ieee.org/document/10097033
|
Overall Accuracy
|
90.04
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
DAN
|
https://arxiv.org/abs/2109.07270v6
|
Overall Accuracy
|
89.70
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
RUL (ResNet-18)
|
http://proceedings.neurips.cc/paper/2021/hash/9332c513ef44b682e9347822c2e457ac-Abstract.html
|
Overall Accuracy
|
88.98
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
PSR
|
https://doi.org/10.1109/ACCESS.2020.3010018
|
Overall Accuracy
|
88.98
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
FerNeXt
|
https://ieeexplore.ieee.org/document/10278345
|
Overall Accuracy
|
88.56
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
EfficientFace
|
https://ojs.aaai.org/index.php/AAAI/article/view/16465
|
Overall Accuracy
|
88.36
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
MA-Net
|
https://ieeexplore.ieee.org/document/9474949
|
Overall Accuracy
|
88.36
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
DACL (ResNet-18)
|
https://openaccess.thecvf.com/content/WACV2021/html/Farzaneh_Facial_Expression_Recognition_in_the_Wild_via_Deep_Attentive_Center_WACV_2021_paper.html
|
Overall Accuracy
|
87.78
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
DACL (ResNet-18)
|
https://openaccess.thecvf.com/content/WACV2021/html/Farzaneh_Facial_Expression_Recognition_in_the_Wild_via_Deep_Attentive_Center_WACV_2021_paper.html
|
Avg. Accuracy
|
80.44
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
MixAugment
|
https://arxiv.org/abs/2205.04442v1
|
Overall Accuracy
|
87.54
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
MixAugment
|
https://arxiv.org/abs/2205.04442v1
|
Avg. Accuracy
|
77.30
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
ViT-base
|
https://arxiv.org/abs/2207.11081v4
|
Overall Accuracy
|
87.22
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
ViT-tiny
|
https://arxiv.org/abs/2207.11081v4
|
Overall Accuracy
|
87.03
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
Ad-Corre
|
https://ieeexplore.ieee.org/document/9727163
|
Overall Accuracy
|
86.96
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
RAN (ResNet-18)
|
https://arxiv.org/abs/1905.04075v2
|
Overall Accuracy
|
86.9
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
C-EXPR-NET
|
http://openaccess.thecvf.com//content/CVPR2023/html/Kollias_Multi-Label_Compound_Expression_Recognition_C-EXPR_Database__Network_CVPR_2023_paper.html
|
Avg. Accuracy
|
87.5
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
C MT PSR
|
https://arxiv.org/abs/2401.01219v2
|
Avg. Accuracy
|
84.8
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
C MT VGGFACE
|
https://arxiv.org/abs/2401.01219v2
|
Avg. Accuracy
|
81.4
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
FaceBehaviorNet
|
https://arxiv.org/abs/2105.03790v1
|
Avg. Accuracy
|
78
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
VGG-FACE
|
https://arxiv.org/abs/1811.05027v2
|
Avg. Accuracy
|
77.5
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
RAF-DB
|
MT-ArcVGG
|
https://arxiv.org/abs/1910.04855v1
|
Avg. Accuracy
|
76
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
DISFA
|
Norface
|
https://arxiv.org/abs/2407.15617v1
|
ICC
|
0.67
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
DISFA
|
Ours (VGG-F)
|
https://arxiv.org/abs/2103.16554v2
|
ICC
|
0.598
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
SFEW
|
Ada-DF
|
https://ieeexplore.ieee.org/document/10097033
|
Accuracy
|
60.46
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
SFEW
|
RAN (VGG16+ResNet18)
|
https://arxiv.org/abs/1905.04075v2
|
Accuracy
|
56.4
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
SFEW
|
ViT + SE
|
https://arxiv.org/abs/2107.03107v4
|
Accuracy
|
54.29
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
SFEW
|
Island Loss
|
http://arxiv.org/abs/1710.03144v3
|
Accuracy
|
52.52
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
Norface
|
https://arxiv.org/abs/2407.15617v1
|
Accuracy (8 emotion)
|
68.69
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
DDAMFN++
|
https://scholar.google.com/citations?view_op=view_citation&hl=zh-CN&user=P4efBMcAAAAJ&citation_for_view=P4efBMcAAAAJ:d1gkVwhDpl0C
|
Accuracy (7 emotion)
|
67.36
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
DDAMFN++
|
https://scholar.google.com/citations?view_op=view_citation&hl=zh-CN&user=P4efBMcAAAAJ&citation_for_view=P4efBMcAAAAJ:d1gkVwhDpl0C
|
Accuracy (8 emotion)
|
65.04
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
FMAE
|
https://arxiv.org/abs/2407.11243v2
|
Accuracy (8 emotion)
|
64.79
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
QCS
|
https://arxiv.org/abs/2411.01988v5
|
Accuracy (7 emotion)
|
67.94
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
QCS
|
https://arxiv.org/abs/2411.01988v5
|
Accuracy (8 emotion)
|
64.4
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
BTN
|
https://arxiv.org/abs/2407.04218v1
|
Accuracy (7 emotion)
|
67.60
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
BTN
|
https://arxiv.org/abs/2407.04218v1
|
Accuracy (8 emotion)
|
64.29
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
DDAMFN
|
https://scholar.google.com/citations?view_op=view_citation&hl=zh-CN&user=P4efBMcAAAAJ&citation_for_view=P4efBMcAAAAJ:d1gkVwhDpl0C
|
Accuracy (7 emotion)
|
67.03
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
DDAMFN
|
https://scholar.google.com/citations?view_op=view_citation&hl=zh-CN&user=P4efBMcAAAAJ&citation_for_view=P4efBMcAAAAJ:d1gkVwhDpl0C
|
Accuracy (8 emotion)
|
64.25
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
EmoNeXt
|
https://link.springer.com/article/10.1007/s00521-024-10938-0
|
Accuracy (7 emotion)
|
67.46
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
EmoNeXt
|
https://link.springer.com/article/10.1007/s00521-024-10938-0
|
Accuracy (8 emotion)
|
64.13
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
POSTER++
|
https://arxiv.org/abs/2301.12149v2
|
Accuracy (7 emotion)
|
67.49
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
POSTER++
|
https://arxiv.org/abs/2301.12149v2
|
Accuracy (8 emotion)
|
63.77
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
LFNSB
|
https://www.preprints.org/manuscript/202408.1304/v1
|
Accuracy (7 emotion)
|
66.57
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
LFNSB
|
https://www.preprints.org/manuscript/202408.1304/v1
|
Accuracy (8 emotion)
|
63.12
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
S2D
|
https://arxiv.org/abs/2312.05447v2
|
Accuracy (7 emotion)
|
67.62
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
S2D
|
https://arxiv.org/abs/2312.05447v2
|
Accuracy (8 emotion)
|
63.06
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
Multi-task EfficientNet-B2
|
https://ieeexplore.ieee.org/document/9815154
|
Accuracy (7 emotion)
|
66.29
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
Multi-task EfficientNet-B2
|
https://ieeexplore.ieee.org/document/9815154
|
Accuracy (8 emotion)
|
63.03
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
MT-ArcRes
|
https://arxiv.org/abs/1910.04855v1
|
Accuracy (8 emotion)
|
63
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
ExpLLM
|
https://arxiv.org/abs/2409.02828v1
|
Accuracy (7 emotion)
|
65.93
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
ExpLLM
|
https://arxiv.org/abs/2409.02828v1
|
Accuracy (8 emotion)
|
62.86
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
Vit-base + MAE
|
https://arxiv.org/abs/2207.11081v4
|
Accuracy (8 emotion)
|
62.42
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
CAGE
|
https://arxiv.org/abs/2404.14975v1
|
Accuracy (7 emotion)
|
66.6
|
Facial Recognition and Modelling > Facial Expression Recognition (FER)
|
AffectNet
|
CAGE
|
https://arxiv.org/abs/2404.14975v1
|
Accuracy (8 emotion)
|
62.2
|
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