Suzuki, K.[Kenji],
Yamada, H.[Hiroshi],
Hashimoto, S.[Shuji],
A similarity-based neural network for facial expression analysis,
PRL(28), No. 9, 1 July 2007, pp. 1104-1111.
Elsevier DOI
0704
Similarity-based neural network; Multidimensional perceptual scaling;
Facial expressions; Stable dynamic parameter adaptation; Nonlinear mapping
BibRef
Dornaika, F.,
Lazkano, E.,
Sierra, B.,
Improving dynamic facial expression recognition with feature subset
selection,
PRL(32), No. 5, 1 April 2011, pp. 740-748.
Elsevier DOI
1103
Dynamic facial expression recognition; Feature subset selection;
Estimation of Distribution Algorithms; Machine learning approaches;
Wrapper technique
BibRef
Li, Y.J.[Ying-Jian],
Lu, Y.[Yao],
Chen, B.Z.[Bing-Zhi],
Zhang, Z.[Zheng],
Li, J.X.[Jin-Xing],
Lu, G.M.[Guang-Ming],
Zhang, D.[David],
Learning Informative and Discriminative Features for Facial
Expression Recognition in the Wild,
CirSysVideo(32), No. 5, May 2022, pp. 3178-3189.
IEEE DOI
2205
Compounds, Face recognition, Feature extraction, Databases,
Computational modeling, Training, Neural networks, loss function
BibRef
Lopes, A.T.[André Teixeira],
de Aguiar, E.[Edilson],
de Souza, A.F.[Alberto F.],
Oliveira-Santos, T.[Thiago],
Facial expression recognition with Convolutional Neural Networks:
Coping with few data and the training sample order,
PR(61), No. 1, 2017, pp. 610-628.
Elsevier DOI
1609
Facial expression recognition
BibRef
Bougourzi, F.[Fares],
Mokrani, K.[Karim],
Ruichek, Y.[Yassine],
Dornaika, F.[Fadi],
Ouafi, A.[Abdelkrim],
Taleb-Ahmed, A.[Abdelmalik],
Fusion of transformed shallow features for facial expression
recognition,
IET-IPR(13), No. 9, 18 July 2019, pp. 1479-1489.
DOI Link
1907
BibRef
Yan, H.,
Ang, M.H.,
Poo, A.N.,
Adaptive discriminative metric learning for facial expression
recognition,
IET-Bio(1), No. 3, September 2012, pp. 160-167.
DOI Link
1305
BibRef
Liao, C.T.[Chia-Te],
Chuang, H.J.[Hui-Ju],
Duan, C.H.[Chih-Hsueh],
Lai, S.H.[Shang-Hong],
Learning spatial weighting for facial expression analysis via
constrained quadratic programming,
PR(46), No. 11, November 2013, pp. 3103-3116.
Elsevier DOI
1306
BibRef
Earlier:
Learning spatial weighting via quadratic programming for facial
expression analysis,
CVPR4HB10(86-93).
IEEE DOI
1006
Facial expression analysis; Quadratic programming; Expression
recognition; Expression intensity estimation
BibRef
Zhang, W.[Wei],
Zhang, Y.[Youmei],
Ma, L.[Lin],
Guan, J.W.[Jing-Wei],
Gong, S.J.[Shi-Jie],
Multimodal learning for facial expression recognition,
PR(48), No. 10, 2015, pp. 3191-3202.
Elsevier DOI
1507
Multimodal learning
BibRef
Wang, L.[Li],
Wang, K.[Ke],
Li, R.F.[Rui-Feng],
Unsupervised feature selection based on spectral regression from
manifold learning for facial expression recognition,
IET-CV(9), No. 5, 2015, pp. 655-662.
DOI Link
1511
emotion recognition
BibRef
Zen, G.,
Porzi, L.,
Sangineto, E.,
Ricci, E.,
Sebe, N.,
Learning Personalized Models for Facial Expression Analysis and
Gesture Recognition,
MultMed(18), No. 4, April 2016, pp. 775-788.
IEEE DOI
1604
Data models
BibRef
Ren, F.,
Huang, Z.,
Automatic Facial Expression Learning Method Based on Humanoid Robot
XIN-REN,
HMS(46), No. 6, December 2016, pp. 810-821.
IEEE DOI
1612
control engineering computing
BibRef
Sun, Z.[Zhe],
Hu, Z.P.[Zheng-Ping],
Wang, M.[Meng],
Zhao, S.H.[Shu-Huan],
Individual-free representation-based classification for facial
expression recognition,
SIViP(11), No. 4, May 2017, pp. 597-604.
WWW Link.
1704
BibRef
Sun, Z.[Zhe],
Hu, Z.P.[Zheng-Ping],
Wang, M.[Meng],
Zhao, S.H.[Shu-Huan],
Discriminative feature learning-based pixel difference representation
for facial expression recognition,
IET-CV(11), No. 8, December 2017, pp. 675-682.
DOI Link
1712
BibRef
Sun, Z.[Zhe],
Hu, Z.P.[Zheng-Ping],
Chiong, R.[Raymond],
Wang, M.[Meng],
Zhao, S.H.[Shu-Huan],
An adaptive weighted fusion model with two subspaces for facial
expression recognition,
SIViP(12), No. 5, July 2018, pp. 835-843.
Springer DOI
1806
BibRef
Liu, Y.Y.[Yuan-Yuan],
Yuan, X.H.[Xiao-Hui],
Gong, X.[Xi],
Xie, Z.[Zhong],
Fang, F.[Fang],
Luo, Z.W.[Zhong-Wen],
Conditional convolution neural network enhanced random forest for
facial expression recognition,
PR(84), 2018, pp. 251-261.
Elsevier DOI
1809
Classification, Feature extraction,
Facial expression recognition, Head pose alignment, Conditional CoNERF
BibRef
Li, T.H.[Tai-Hao],
Du, C.F.[Cui-Fen],
Naren, T.[Tuya],
Chen, Z.Q.[Zhi-Qiang],
Liu, S.P.[Shu-Peng],
Zhou, J.S.[Jian-She],
Xu, X.Y.[Xiao-Yin],
Using feature points and angles between them to recognise facial
expression by a neural network approach,
IET-IPR(12), No. 11, November 2018, pp. 1951-1955.
DOI Link
1810
BibRef
Yu, Z.B.[Zhen-Bo],
Liu, Q.S.[Qin-Shan],
Liu, G.C.[Guang-Can],
Deeper cascaded peak-piloted network for weak expression recognition,
VC(34), No. 12, December 2018, pp. 1691-1699.
WWW Link.
1811
BibRef
Yan, H.B.[Hai-Bin],
Collaborative discriminative multi-metric learning for facial
expression recognition in video,
PR(75), No. 1, 2018, pp. 33-40.
Elsevier DOI
1712
Facial expression recognition
BibRef
Gan, Y.L.[Yan-Ling],
Chen, J.Y.[Jing-Ying],
Xu, L.[Luhui],
Facial expression recognition boosted by soft label with a diverse
ensemble,
PRL(125), 2019, pp. 105-112.
Elsevier DOI
1909
Facial expression recognition, Convolutional neural network,
Soft label, Label-level perturbation strategy, Ensemble classifier
BibRef
Xie, S.Y.[Si-Yue],
Hu, H.F.[Hai-Feng],
Yin, Z.Y.[Zi-Yu],
Facial expression recognition using intra-class variation reduced
features and manifold regularisation dictionary pair learning,
IET-CV(12), No. 4, June 2018, pp. 458-465.
DOI Link
1805
BibRef
Du, L.S.[Ling-Shuang],
Hu, H.F.[Hai-Feng],
Weighted Patch-based Manifold Regularization Dictionary Pair Learning
model for facial expression recognition using Iterative Optimization
Classification Strategy,
CVIU(186), 2019, pp. 13-24.
Elsevier DOI
1908
Facial Expression Recognition, Weighted Patch-based LBP,
Manifold Regularization Dictionary Pair Learning model,
Iterative Optimization Classification Strategy
BibRef
Zou, X.[Xinyi],
Yan, Y.[Yan],
Xue, J.H.[Jing-Hao],
Chen, S.[Si],
Wang, H.Z.[Han-Zi],
Learn-to-Decompose: Cascaded Decomposition Network for Cross-Domain
Few-Shot Facial Expression Recognition,
ECCV22(XIX:683-700).
Springer DOI
2211
BibRef
Dai, S.,
Man, H.,
Mixture Statistic Metric Learning for Robust Human Action and
Expression Recognition,
CirSysVideo(28), No. 10, October 2018, pp. 2484-2499.
IEEE DOI
1811
BibRef
Earlier:
A statistic manifold kernel with graph embedding discriminant
analysis for action and expression recognition,
ICIP17(1792-1796)
IEEE DOI
1803
Measurement, Kernel, Manifolds, Face recognition, Visualization,
Indexes, Action recognition, facial expression recognition,
mixture statistical metric learning.
Task analysis,
Visualization, YouTube, Statistic manifold kernel
BibRef
Liu, X.F.[Xiao-Feng],
Vijaya Kumar, B.V.K.,
Jia, P.[Ping],
You, J.[Jane],
Hard negative generation for identity-disentangled facial expression
recognition,
PR(88), 2019, pp. 1-12.
Elsevier DOI
1901
Hard negative generation, Adaptive metric learning,
Face normalization, Facial expression recognition
BibRef
Li, Y.[Yong],
Zeng, J.B.[Jia-Bei],
Shan, S.G.[Shi-Guang],
Chen, X.L.[Xi-Lin],
Occlusion Aware Facial Expression Recognition Using CNN With
Attention Mechanism,
IP(28), No. 5, May 2019, pp. 2439-2450.
IEEE DOI
1903
BibRef
Earlier:
Patch-Gated CNN for Occlusion-aware Facial Expression Recognition,
ICPR18(2209-2214)
IEEE DOI
1812
convolutional neural nets, emotion recognition, face recognition,
learning (artificial intelligence), gate unit.
Task analysis, Feature extraction, Mouth, Computational modeling.
BibRef
Sadeghi, H.[Hamid],
Raie, A.A.[Abolghasem A.],
Histogram distance metric learning for facial expression recognition,
JVCIR(62), 2019, pp. 152-165.
Elsevier DOI
1908
Metric learning, Local metric learning, Chi-squared distance,
Histogram classification, Facial expression recognition in the wild
BibRef
Xie, L.,
Zhao, J.,
Wei, H.,
Zhang, K.,
Pang, G.,
Online Kernel-Based Structured Output SVM for Early Expression
Detection,
SPLetters(26), No. 9, September 2019, pp. 1305-1309.
IEEE DOI
1909
face recognition, feature extraction,
learning (artificial intelligence), support vector machines,
deep features
BibRef
Happy, S.L.,
Dantcheva, A.[Antitza],
Bremond, F.[Francois],
A Weakly Supervised learning technique for classifying facial
expressions,
PRL(128), 2019, pp. 162-168.
Elsevier DOI
1912
Weakly supervised learning, Facial expression recognition, Label smoothing
BibRef
Happy, S.L.,
Dantcheva, A.[Antitza],
Bremond, F.[François],
Expression recognition with deep features extracted from holistic and
part-based models,
IVC(105), 2021, pp. 104038.
Elsevier DOI
2101
Facial expression recognition, Convolutional neural networks,
Part-based face representation, Data augmentation
BibRef
Gogic, I.[Ivan],
Manhart, M.[Martina],
Pandžic, I.S.[Igor S.],
Ahlberg, J.[Jörgen],
Fast facial expression recognition using local binary features and
shallow neural networks,
VC(36), No. 1, January 2020, pp. 97-112.
WWW Link.
2001
BibRef
Mai, S.[Sijie],
Xing, S.L.[Song-Long],
Hu, H.F.[Hai-Feng],
Locally Confined Modality Fusion Network With a Global Perspective
for Multimodal Human Affective Computing,
MultMed(22), No. 1, January 2020, pp. 122-137.
IEEE DOI
2001
Multimodal human affective computing,
locally confined cross-modality interaction,
bidirectional multiconnected LSTM
BibRef
Mai, S.[Sijie],
Hu, H.F.[Hai-Feng],
Xu, J.[Jia],
Xing, S.L.[Song-Long],
Multi-Fusion Residual Memory Network for Multimodal Human Sentiment
Comprehension,
AffCom(13), No. 1, January 2022, pp. 320-334.
IEEE DOI
2203
Feature extraction, Acoustics, Hidden Markov models, Task analysis,
Fuses, Sentiment analysis, Visualization, Sentiment analysis,
residual memory network
BibRef
An, F.P.[Feng-Ping],
Liu, Z.W.[Zhi-Wen],
Facial expression recognition algorithm based on parameter adaptive
initialization of CNN and LSTM,
VC(36), No. 3, March 2020, pp. 483-498.
WWW Link.
2002
BibRef
Agrawal, A.[Abhinav],
Mittal, N.[Namita],
Using CNN for facial expression recognition: a study of the effects of
kernel size and number of filters on accuracy,
VC(36), No. 2, February 2020, pp. 405-412.
WWW Link.
2002
BibRef
Li, K.[Kuan],
Jin, Y.[Yi],
Akram, M.W.[Muhammad Waqar],
Han, R.Z.[Rui-Ze],
Chen, J.W.[Jiong-Wei],
Facial expression recognition with convolutional neural networks via a
new face cropping and rotation strategy,
VC(36), No. 2, February 2020, pp. 391-404.
WWW Link.
2002
BibRef
Du, L.S.[Ling-Shuang],
Wu, Y.B.[Yong-Bo],
Hu, H.F.[Hai-Feng],
Wang, W.X.[Wei-Xuan],
Self-adaptive weighted synthesised local directional pattern
integrating with sparse autoencoder for expression recognition based on
improved multiple kernel learning strategy,
IET-CV(14), No. 3, April 2020, pp. 73-83.
DOI Link
2003
BibRef
Bozorgtabar, B.[Behzad],
Mahapatra, D.[Dwarikanath],
Thiran, J.P.[Jean-Philippe],
ExprADA: Adversarial domain adaptation for facial expression analysis,
PR(100), 2020, pp. 107111.
Elsevier DOI
2005
Visual domain adaptation, Facial expression recognition, Adversarial learning
BibRef
Liu, X.Q.[Xiao-Qian],
Zhou, F.Y.[Feng-Yu],
Improved curriculum learning using SSM for facial expression
recognition,
VC(36), No. 8, August 2020, pp. 1635-1649.
WWW Link.
2007
BibRef
Wen, G.,
Chang, T.,
Li, H.,
Jiang, L.,
Dynamic Objectives Learning for Facial Expression Recognition,
MultMed(22), No. 11, November 2020, pp. 2914-2925.
IEEE DOI
2010
Face recognition, Covariance matrices, Feature extraction,
Residual neural networks, Convolution, Symmetric matrices, prior knowledge
BibRef
Tong, Y.[Ying],
Chen, R.[Rui],
Liang, R.Y.[Rui-Yu],
Unconstrained Facial Expression Recognition Based on Feature Enhanced
CNN and Cross-Layer LSTM,
IEICE(E103-D), No. 11, November 2020, pp. 2403-2406.
WWW Link.
2011
BibRef
Altameem, T.[Torki],
Altameem, A.[Ayman],
Facial expression recognition using human machine interaction and
multi-modal visualization analysis for healthcare applications,
IVC(103), 2020, pp. 104044.
Elsevier DOI
2011
CNN, Face visualization, Healthcare systems,
Human-machine interaction
BibRef
Li, H.,
Wang, N.,
Ding, X.,
Yang, X.,
Gao, X.,
Adaptively Learning Facial Expression Representation via C-F Labels
and Distillation,
IP(30), 2021, pp. 2016-2028.
IEEE DOI
2101
Face recognition, Feature extraction, Faces, Adaptation models,
Training, Mouth, Image coding, Facial expression recognition,
knowledge distillation
BibRef
Wu, M.,
Su, W.,
Chen, L.,
Liu, Z.,
Cao, W.,
Hirota, K.,
Weight-Adapted Convolution Neural Network for Facial Expression
Recognition in Human-Robot Interaction,
SMCS(51), No. 3, March 2021, pp. 1473-1484.
IEEE DOI
2102
Feature extraction, Genetic algorithms,
Principal component analysis, Face recognition, Optimization,
genetic algorithm (GA)
BibRef
Gera, D.[Darshan],
Balasubramanian, S.,
Landmark guidance independent spatio-channel attention and
complementary context information based facial expression recognition,
PRL(145), 2021, pp. 58-66.
Elsevier DOI
2104
Facial expression recognition, FER, Spatio-channel attention,
SCAN, CNN, Occlusion-robust, Pose-invariant
BibRef
Dharanya, V.,
Joseph Raj, A.N.[Alex Noel],
Gopi, V.P.[Varun P.],
Facial Expression Recognition through person-wise regeneration of
expressions using Auxiliary Classifier Generative Adversarial Network
(AC-GAN) based model,
JVCIR(77), 2021, pp. 103110.
Elsevier DOI
2106
Facial Expression Recognition (FER), Subject dependence,
Conditional GAN(CGAN), Auxiliary Classifier GAN(ACGAN), U-Net,
Capsule Network(capsuleNet)
BibRef
Li, M.[Ming],
Xu, H.[Hao],
Huang, X.C.[Xing-Chang],
Song, Z.M.[Zhan-Mei],
Liu, X.L.[Xiao-Lin],
Li, X.[Xin],
Facial Expression Recognition with Identity and Emotion Joint
Learning,
AffCom(12), No. 2, April 2021, pp. 544-550.
IEEE DOI
2106
Face recognition, Face, Task analysis, Feature extraction,
Convolution, Emotion recognition, Training data,
transfer learning
BibRef
Rao, T.R.[Tian-Rong],
Li, J.[Jie],
Wang, X.Y.[Xiao-Yu],
Sun, Y.[Yibo],
Chen, H.[Hong],
Facial Expression Recognition With Multiscale Graph Convolutional
Networks,
MultMedMag(28), No. 2, April 2021, pp. 11-19.
IEEE DOI
2107
Face recognition, Feature extraction, Emotion recognition,
Image recognition, Solid modeling, Data mining, Convolutional neural networks
BibRef
Xia, H.Y.[Hai-Ying],
Li, C.Y.[Chang-Yuan],
Tan, Y.[Yumei],
Li, L.Y.[Ling-Yun],
Song, S.X.[Shu-Xiang],
Destruction and Reconstruction Learning for Facial Expression
Recognition,
MultMedMag(28), No. 2, April 2021, pp. 20-28.
IEEE DOI
2107
Feature extraction, Face recognition, Image reconstruction,
Image recognition, Emotion recognition, Training data,
Destruction and Reconstruction
BibRef
Xia, H.Y.[Hai-Ying],
Su, C.H.[Chun-Hai],
Song, S.X.[Shu-Xiang],
Tan, Y.[Yumei],
Dual-consistency constraints network for noisy facial expression
recognition,
IVC(148), 2024, pp. 105141.
Elsevier DOI
2407
Facial expression recognition, Noisy label learning, Consistency constraints
BibRef
Jin, X.[Xing],
Lai, Z.H.[Zhi-Hui],
Jin, Z.[Zhong],
Learning Dynamic Relationships for Facial Expression Recognition
Based on Graph Convolutional Network,
IP(30), 2021, pp. 7143-7155.
IEEE DOI
2108
Convolution, Face recognition, Task analysis, Feature extraction,
Convolutional codes, Mouth, Gold, Facial expression recognition,
light-weight network
BibRef
Sun, W.[Wenyun],
Zhao, H.T.[Hai-Tao],
Jin, Z.[Zhong],
3D Convolutional Neural Networks for Facial Expression Classification,
SFBA16(I: 528-543).
Springer DOI
1704
BibRef
Yu, W.M.[Wen-Meng],
Xu, H.[Hua],
Co-attentive multi-task convolutional neural network for facial
expression recognition,
PR(123), 2022, pp. 108401.
Elsevier DOI
2112
Facial expression recognition, Facial landmarks detection, Multi-task learning
BibRef
Gan, C.Q.[Chen-Quan],
Xiao, J.H.[Jun-Hao],
Wang, Z.Y.[Zhang-Yi],
Zhang, Z.F.[Zu-Fan],
Zhu, Q.Y.[Qing-Yi],
Facial expression recognition using densely connected convolutional
neural network and hierarchical spatial attention,
IVC(117), 2022, pp. 104342.
Elsevier DOI
2112
Facial image, Facial expression recognition,
Densely connected convolutional neural network, Spatial attention
BibRef
Nguyen, H.D.[Hai-Duong],
Kim, S.H.[Sun-Hee],
Lee, G.S.[Guee-Sang],
Yang, H.J.[Hyung-Jeong],
Na, I.S.[In-Seop],
Kim, S.H.[Soo-Hyung],
Facial Expression Recognition Using a Temporal Ensemble of
Multi-Level Convolutional Neural Networks,
AffCom(13), No. 1, January 2022, pp. 226-237.
IEEE DOI
2203
Face recognition, Image recognition, Computer architecture,
Feature extraction, Emotion recognition,
multi-level convolutional neural networks
BibRef
Gera, D.[Darshan],
Balasubramanian, S.,
Jami, A.[Anwesh],
CERN: Compact facial expression recognition net,
PRL(155), 2022, pp. 9-18.
Elsevier DOI
2203
Light-weight, Transfer learning, Facial expression recognition,
Attention, Local-global context, CNN
BibRef
Kong, Y.H.[Ying-Hui],
Zhang, S.[Shuaitong],
Zhang, K.[Ke],
Ni, Q.[Qiang],
Han, J.G.[Jun-Gong],
Real-time facial expression recognition based on iterative transfer
learning and efficient attention network,
IET-IPR(16), No. 6, 2022, pp. 1694-1708.
DOI Link
2204
BibRef
Zhang, F.F.[Fei-Fei],
Xu, M.L.[Ming-Liang],
Xu, C.S.[Chang-Sheng],
Weakly-Supervised Facial Expression Recognition in the Wild With
Noisy Data,
MultMed(24), No. 2022, pp. 1800-1814.
IEEE DOI
2204
Noise measurement, Face recognition, Data models, Task analysis,
Training data, Training, Annotations,
noise modeling
BibRef
Zhang, X.[Xi],
Zhang, F.F.[Fei-Fei],
Xu, C.S.[Chang-Sheng],
Joint Expression Synthesis and Representation Learning for Facial
Expression Recognition,
CirSysVideo(32), No. 3, March 2022, pp. 1681-1695.
IEEE DOI
2203
Face recognition, Task analysis, Generative adversarial networks,
Image synthesis, Image recognition, Faces, Training,
representation learning
BibRef
Li, Y.J.[Ying-Jian],
Gao, Y.N.[Ying-Nan],
Chen, B.Z.[Bing-Zhi],
Zhang, Z.[Zheng],
Lu, G.M.[Guang-Ming],
Zhang, D.[David],
Self-Supervised Exclusive-Inclusive Interactive Learning for
Multi-Label Facial Expression Recognition in the Wild,
CirSysVideo(32), No. 5, May 2022, pp. 3190-3202.
IEEE DOI
2205
Task analysis, Databases, Training, Face recognition, Training data,
Data models, Uncertainty,
conditional adversarial learning
BibRef
Sun, Z.[Zhe],
Chiong, R.[Raymond],
Hu, Z.P.[Zheng-Ping],
Dhakal, S.[Sandeep],
A dynamic constraint representation approach based on cross-domain
dictionary learning for expression recognition,
JVCIR(85), 2022, pp. 103458.
Elsevier DOI
2205
Facial expression recognition,
Cross-domain dictionary learning, Dynamic constraint representation
BibRef
Chen, J.Y.[Jing-Ying],
Yang, L.[Lei],
Tan, L.[Lei],
Xu, R.[Ruyi],
Orthogonal channel attention-based multi-task learning for multi-view
facial expression recognition,
PR(129), 2022, pp. 108753.
Elsevier DOI
2206
Multi-view facial expression recognition,
Orthogonal channel attention, Multi-task learning,
Separated channel attention module
BibRef
Chen, J.Y.[Jing-Ying],
Shi, J.X.[Jin-Xin],
Xu, R.[Ruyi],
Dual subspace manifold learning based on GCN for intensity-invariant
facial expression recognition,
PR(148), 2024, pp. 110157.
Elsevier DOI
2402
Graph convolutional network, Semi-supervised learning,
Intensity-invariant representation, Manifold learning,
Facial expression recognition
BibRef
Fan, Y.R.[Ying-Ruo],
Li, V.O.K.[Victor O.K.],
Lam, J.C.K.[Jacqueline C.K.],
Facial Expression Recognition With Deeply-Supervised Attention
Network,
AffCom(13), No. 2, April 2022, pp. 1057-1071.
IEEE DOI
2206
Training, Face, Face recognition, Task analysis, Visualization,
Feature extraction, Facial expression recognition, visual explanation
BibRef
Kar, N.B.[Nikunja Bihari],
Babu, K.S.[Korra Sathya],
Bakshi, S.[Sambit],
Facial expression recognition system based on variational mode
decomposition and whale optimized KELM,
IVC(123), 2022, pp. 104445.
Elsevier DOI
2206
Facial expression recognition, Kernel extreme learning machine,
Whale optimization
BibRef
Liu, H.W.[Han-Wei],
Cai, H.L.[Hui-Ling],
Lin, Q.C.[Qing-Cheng],
Li, X.F.[Xue-Feng],
Xiao, H.[Hui],
Adaptive Multilayer Perceptual Attention Network for Facial
Expression Recognition,
CirSysVideo(32), No. 9, September 2022, pp. 6253-6266.
IEEE DOI
2209
Face recognition, Feature extraction, Mouth, Robustness,
Facial features, Data mining, Visualization,
variant pose
BibRef
Karnati, M.[Mohan],
Seal, A.[Ayan],
Yazidi, A.[Anis],
Krejcar, O.[Ondrej],
FLEPNet: Feature Level Ensemble Parallel Network for Facial
Expression Recognition,
AffCom(13), No. 4, October 2022, pp. 2058-2070.
IEEE DOI
2212
Face recognition, Feature extraction, Lighting, Databases,
Training data, Discrete Fourier transforms, Data mining,
facial expression classification
BibRef
Lang, J.J.[Jun-Jie],
Sun, X.[Xiao],
Li, J.[Jia],
Wang, M.[Meng],
Multi-stage and multi-branch network with similar expressions label
distribution learning for facial expression recognition,
PRL(163), 2022, pp. 17-24.
Elsevier DOI
2212
Similar expressions,
Multi-stage multi-branch classification network, Label distribution learning
BibRef
Liu, P.[Ping],
Lin, Y.W.[Yue-Wei],
Meng, Z.[Zibo],
Lu, L.[Lu],
Deng, W.H.[Wei-Hong],
Zhou, J.T.Y.[Joey Tian-Yi],
Yang, Y.[Yi],
Point Adversarial Self-Mining: A Simple Method for Facial Expression
Recognition,
Cyber(52), No. 12, December 2022, pp. 12649-12660.
IEEE DOI
2212
Face recognition, Training, Feature extraction, Faces,
Facial expression recognition (FER), in-the-wild data, point adversarial attack
BibRef
Chen, T.S.[Tian-Shui],
Pu, T.[Tao],
Wu, H.F.[He-Feng],
Xie, Y.[Yuan],
Liu, L.B.[Ling-Bo],
Lin, L.[Liang],
Cross-Domain Facial Expression Recognition:
A Unified Evaluation Benchmark and Adversarial Graph Learning,
PAMI(44), No. 12, December 2022, pp. 9887-9903.
IEEE DOI
2212
Feature extraction, Benchmark testing,
Adversarial machine learning, Face recognition, Task analysis,
fair evaluation
BibRef
Gao, Y.F.[Yue-Fang],
Xie, Y.H.[Yu-Hao],
Hu, Z.Z.X.[Zeke Ze-Xi],
Chen, T.S.[Tian-Shui],
Lin, L.[Liang],
Adaptive Global-Local Representation Learning and Selection for
Cross-Domain Facial Expression Recognition,
MultMed(26), 2024, pp. 6676-6688.
IEEE DOI
2404
Feature extraction, Adaptation models,
Adversarial machine learning, Face recognition, Semantics,
Facial expression recognition
BibRef
Xie, Y.H.[Yu-Hao],
Gao, Y.F.[Yue-Fang],
Lin, J.T.[Jian-Tao],
Chen, T.S.[Tian-Shui],
Learning Consistent Global-Local Representation for Cross-Domain
Facial Expression Recognition,
ICPR22(2489-2495)
IEEE DOI
2212
Representation learning, Analytical models, Face recognition,
Semantics, Reliability
BibRef
Jiang, M.[Man],
Yin, S.[Shoulin],
Facial expression recognition based on convolutional block attention
module and multi-feature fusion,
IJCVR(13), No. 1, 2023, pp. 21-37.
DOI Link
2212
BibRef
Zhang, Z.Y.[Zi-Yang],
Sun, X.[Xiao],
Li, J.[Jia],
Wang, M.[Meng],
MAN: Mining Ambiguity and Noise for Facial Expression Recognition in
the Wild,
PRL(164), 2022, pp. 23-29.
Elsevier DOI
2212
Facial Expression Recognition, Annotation ambiguity,
Mutual Learning, Unsupervised Learning
BibRef
Wan, F.[Fei],
Zhi, R.C.[Rui-Cong],
Gaussian distribution-based facial expression feature extraction
network,
PRL(164), 2022, pp. 104-111.
Elsevier DOI
2212
Facial expression recognition, Gaussian distribution model,
Feature disentanglement
BibRef
Badea, M.[Mihai],
Florea, C.[Corneliu],
Racoviteanu, A.[Andrei],
Florea, L.[Laura],
Vertan, C.[Constantin],
Timid semi-supervised learning for face expression analysis,
PR(138), 2023, pp. 109417.
Elsevier DOI
2303
BibRef
Earlier: A2, A1, A5, A3, A5:
Margin-mix: Semi-supervised Learning for Face Expression Recognition,
ECCV20(XXIII:1-17).
Springer DOI
2011
Face expression, Action units, Semi-supervised learning, Diversity
BibRef
Zhang, W.G.[Wei-Guang],
Zhang, X.G.[Xu-Guang],
Tang, Y.G.[Ying-Gan],
Facial expression recognition based on improved residual network,
IET-IPR(17), No. 7, 2023, pp. 2005-2014.
DOI Link
2305
convolutional neural nets, face recognition
BibRef
Hao, M.[Meng],
Yuan, F.[Fei],
Li, J.[Jing],
Sun, Y.T.[Yu-Ting],
Facial expression recognition based on regional adaptive correlation,
IET-CV(17), No. 4, 2023, pp. 445-460.
DOI Link
2306
convolutional neural nets, correlation methods,
emotion recognition, feature extraction, image classification
BibRef
Liang, X.R.[Xun-Ru],
Liang, J.F.[Jian-Feng],
Yin, T.[Tao],
Tang, X.Y.[Xiao-Yu],
A lightweight method for face expression recognition based on
improved MobileNetV3,
IET-IPR(17), No. 8, 2023, pp. 2375-2384.
DOI Link
2306
emotion recognition, image classification, image recognition
BibRef
Zhao, R.[Rui],
Liu, T.S.[Tian-Shan],
Huang, Z.X.[Zi-Xun],
Lun, D.P.K.[Daniel P.K.],
Lam, K.M.[Kin-Man],
Geometry-Aware Facial Expression Recognition via Attentive Graph
Convolutional Networks,
AffCom(14), No. 2, April 2023, pp. 1159-1174.
IEEE DOI
2306
Face recognition, Emotion recognition, Convolution, Semantics,
Cognition, Streaming media, Feature extraction,
multi-level attentive learning
BibRef
Shabbir, N.[Nazir],
Rout, R.K.[Ranjeet Kumar],
FgbCNN: A unified bilinear architecture for learning a fine-grained
feature representation in facial expression recognition,
IVC(137), 2023, pp. 104770.
Elsevier DOI
2309
Fine-grained, Facial expression, Convolutional neural networks,
Bi-linear pooling, Fine tuning, Matrix normalization
BibRef
Cai, J.[Jie],
Meng, Z.[Zibo],
Khan, A.S.[Ahmed Shehab],
Li, Z.Y.[Zhi-Yuan],
O'Reilly, J.[James],
Tong, Y.[Yan],
Probabilistic Attribute Tree Structured Convolutional Neural Networks
for Facial Expression Recognition in the Wild,
AffCom(14), No. 3, July 2023, pp. 1927-1941.
IEEE DOI
2310
BibRef
Earlier:
Island Loss for Learning Discriminative Features in Facial Expression
Recognition,
FG18(302-309)
IEEE DOI
1806
Backpropagation, Databases, Face recognition, Head, Lighting,
Propagation losses, Training, Convolutional Neural Network,
Island Loss
BibRef
Li, Y.J.[Ying-Jian],
Huang, J.X.[Jia-Xing],
Lu, S.J.[Shi-Jian],
Zhang, Z.[Zheng],
Lu, G.M.[Guang-Ming],
Cross-Domain Facial Expression Recognition via Contrastive Warm up
and Complexity-Aware Self-Training,
IP(32), 2023, pp. 5438-5450.
IEEE DOI
2310
BibRef
Wang, S.M.[Shan-Min],
Shuai, H.[Hui],
Liu, C.G.[Cheng-Guang],
Liu, Q.S.[Qing-Shan],
Bias-Based Soft Label Learning for Facial Expression Recognition,
AffCom(14), No. 4, October 2023, pp. 3257-3268.
IEEE DOI
2312
BibRef
Dong, Q.[Qian],
Ren, W.H.[Wei-Hong],
Gao, Y.[Yu],
Jiang, W.[Weibo],
Liu, H.H.[Hong-Hai],
Multi-Scale Attention Learning Network for Facial Expression
Recognition,
SPLetters(30), 2023, pp. 1732-1736.
IEEE DOI
2312
BibRef
Chen, D.L.[Dong-Liang],
Wen, G.H.[Gui-Hua],
Li, H.H.[Hui-Hui],
Chen, R.[Rui],
Li, C.[Cheng],
Multi-Relations Aware Network for In-the-Wild Facial Expression
Recognition,
CirSysVideo(33), No. 8, August 2023, pp. 3848-3859.
IEEE DOI
2308
Face recognition, Feature extraction, Transformers,
Representation learning, Training, Task analysis, transformer
BibRef
Chen, X.B.[Xiao-Bo],
Du, J.[Jian],
Deng, F.[Fuwen],
Zhao, F.[Feng],
Transferable driver facial expression recognition based on joint
discriminative correlation alignment network with enhanced feature
attention,
IET-ITS(17), No. 12, 2023, pp. 2444-2457.
DOI Link
2312
correlation alignment, driver expression recognition,
spatial-channel attention, transfer learning
BibRef
Tan, Y.[Yumei],
Xia, H.Y.[Hai-Ying],
Song, S.[Shuxiang],
Learning informative and discriminative semantic features for robust
facial expression recognition,
JVCIR(98), 2024, pp. 104062.
Elsevier DOI
2402
Facial expression recognition, Attention, Informative features, Robust learning
BibRef
Liu, Y.[Yang],
Zhang, X.M.[Xing-Ming],
Kauttonen, J.[Janne],
Zhao, G.Y.[Guo-Ying],
Uncertain Facial Expression Recognition via Multi-Task Assisted
Correction,
MultMed(26), 2024, pp. 2531-2543.
IEEE DOI
2402
Task analysis, Uncertainty, Annotations, Training, Semantics,
Multitasking, Estimation, Facial expression recognition,
multi-task learning
BibRef
Behzad, M.[Muzammil],
Zhao, G.Y.[Guo-Ying],
Self-Supervised Learning via Multi-view Facial Rendezvous for 3D/4D
Affect Recognition,
FG21(1-5)
IEEE DOI
2303
Training, Correlation, Computational modeling, Face recognition,
Gesture recognition, Computer architecture
BibRef
Behzad, M.[Muzammil],
Vo, N.,
Li, X.,
Zhao, G.Y.[Guo-Ying],
Landmarks-assisted Collaborative Deep Framework for Automatic 4D
Facial Expression Recognition,
FG20(1-5)
IEEE DOI
2102
Feature extraction, Collaboration,
Face recognition, Strain, Training
BibRef
Li, H.Y.[Hang-Yu],
Wang, N.N.[Nan-Nan],
Yang, X.[Xi],
Wang, X.Y.[Xiao-Yu],
Gao, X.B.[Xin-Bo],
Unconstrained Facial Expression Recognition With No-Reference
De-Elements Learning,
AffCom(15), No. 1, January 2024, pp. 173-185.
IEEE DOI
2403
Faces, Visualization, Feature extraction, Face recognition,
Task analysis, Representation learning, Pipelines, De-elements,
no-reference learning
BibRef
Shin, H.[Hyunuk],
Lee, B.[Bokyeung],
Ku, B.[Bonhwa],
Ko, H.S.[Han-Seok],
Noisy label facial expression recognition via face-specific label
distribution learning,
IVC(143), 2024, pp. 104901.
Elsevier DOI
2403
Facial expression recognition (FER), Emotion recognition,
Noisy label, Label distribution learning (LDL), Uncertainty, Ambiguity
BibRef
Liu, S.S.[Shuai-Shi],
Zhao, D.X.[Dong-Xu],
Sun, Z.B.[Zhong-Bo],
Chen, Y.K.[Yue-Kun],
BPMB: BayesCNNs with perturbed multi-branch structure for robust
facial expression recognition,
IVC(143), 2024, pp. 104960.
Elsevier DOI
2403
Facial expression recognition, Uncertainty,
Perturbed multi-branch structure, Bayesian convolutional neural network
BibRef
Wang, S.F.[Shang-Fei],
Chang, Y.[Yanan],
Li, Q.[Qiong],
Wang, C.[Can],
Li, G.M.[Guo-Ming],
Mao, M.[Meng],
Pose-robust personalized facial expression recognition through
unsupervised multi-source domain adaptation,
PR(150), 2024, pp. 110311.
Elsevier DOI
2403
Facial expression recognition, Pose-robust, Personalized,
Multi-source domain adaptation
BibRef
Xie, W.C.[Wei-Cheng],
Peng, Z.B.[Zhi-Bin],
Shen, L.L.[Lin-Lin],
Lu, W.[Wenya],
Zhang, Y.[Yang],
Song, S.Y.[Si-Yang],
Cross-Layer Contrastive Learning of Latent Semantics for Facial
Expression Recognition,
IP(33), 2024, pp. 2514-2529.
IEEE DOI
2404
Semantics, Cross layer design, Face recognition,
Self-supervised learning, Representation learning, Faces,
multi-layer attention
BibRef
Li, M.[Ming],
Fu, H.Z.[Hua-Zhu],
He, S.F.[Sheng-Feng],
Fan, H.[Hehe],
Liu, J.[Jun],
Keppo, J.[Jussi],
Shou, M.Z.[Mike Zheng],
DR-FER: Discriminative and Robust Representation Learning for Facial
Expression Recognition,
MultMed(26), 2024, pp. 6297-6309.
IEEE DOI
2404
Annotations, Task analysis, Training, Representation learning,
Schedules, Artificial neural networks, self-paced learning
BibRef
Zhang, J.Y.[Jian-Yang],
Wang, W.[Wei],
Li, X.Y.[Xiang-Yu],
Han, Y.J.[Yag-Jiang],
Recognizing facial expressions based on pyramid multi-head grid and
spatial attention network,
CVIU(244), 2024, pp. 104010.
Elsevier DOI
2405
Facial expression recognition, Convolutional neural network,
Attention mechanism, Fine-Grained Image Classification, Deep learning
BibRef
Yang, Z.F.[Zhi-Fang],
Chiu, D.Y.[Dai-Yi],
Early event detection for facial expression based on infinite mixture
prototypes,
PR(153), 2024, pp. 110527.
Elsevier DOI
2405
Early event detection, Few-shot learning, Infinite mixture prototypes
BibRef
Wang, F.P.[Feng-Ping],
Li, J.[Jie],
Qi, C.[Chun],
Wang, L.[Lin],
Wang, P.[Pan],
JGULF: Joint Global and Unilateral Local Feature Network for
Micro-Expression Recognition,
IVC(147), 2024, pp. 105091.
Elsevier DOI
2406
micro-expression recognition, Unilateral local feature,
Global feature, Feature selection
BibRef
Jiang, S.P.[Shao-Ping],
Xu, X.M.[Xiang-Min],
Xing, X.F.[Xiao-Fen],
Wang, L.[Lin],
Liu, F.[Fang],
Two-Stream Gabor-AGraph Convolutional Networks for Facial Expression
Recognition,
FG21(1-8)
IEEE DOI
2303
Visualization, Correlation, Face recognition,
Gesture recognition, Faces
BibRef
Wen, Y.[Yaoli],
Xu, X.M.[Xiang-Min],
Liu, F.[Fang],
Xing, X.F.[Xiao-Fen],
Wang, L.[Lin],
Two-Stream Global-Guided Attention Network for Facial Expression
Recognition,
FG21(1-8)
IEEE DOI
2303
Correlation, Face recognition, Lighting,
Gesture recognition, Feature extraction, Transformers
BibRef
Zhang, Z.Y.[Zi-Yang],
Tian, X.[Xiang],
Zhang, Y.[Yuan],
Guo, K.L.[Kai-Ling],
Xu, X.M.[Xiang-Min],
Label-Guided Dynamic Spatial-Temporal Fusion for Video-Based Facial
Expression Recognition,
MultMed(26), 2024, pp. 10503-10513.
IEEE DOI
2411
Feature extraction, Transformers, Convolutional neural networks,
Face recognition, Data mining, Entropy, frame label
BibRef
Zhang, Y.[Yuan],
Tian, X.[Xiang],
Zhang, Z.Y.[Zi-Yang],
Xu, X.M.[Xiang-Min],
Lightweight Multi-level Information Fusion Network for Facial
Expression Recognition,
MMMod23(II: 151-163).
Springer DOI
2304
BibRef
Chen, P.[Puhua],
Wang, Z.[Zhe],
Mao, S.[Shasha],
Hui, X.Y.[Xin-Yue],
Huyan, N.[Ning],
Dual-Branch Residual Disentangled Adversarial Learning Network for
Facial Expression Recognition,
SPLetters(31), 2024, pp. 1840-1844.
IEEE DOI
2408
Feature extraction, Face recognition, Training, Facial features,
Adversarial machine learning, Loss measurement, Testing, adversarial training
BibRef
Yang, Y.J.[Yu-Jie],
Hu, L.[Lin],
Zu, C.[Chen],
Zhang, J.J.[Jian-Jia],
Hou, Y.[Yun],
Chen, Y.[Ying],
Zhou, J.[Jiliu],
Zhou, L.P.[Lu-Ping],
Wang, Y.[Yan],
CL-TransFER: Collaborative learning based transformer for facial
expression recognition with masked reconstruction,
PR(156), 2024, pp. 110741.
Elsevier DOI
2408
Facial expression recognition, Representation learning,
Collaborative learning, Noisy annotations
BibRef
Yang, W.W.[Wen-Wu],
Yu, J.Y.[Jin-Yi],
Chen, T.[Tuo],
Liu, Z.G.[Zhen-Guang],
Wang, X.[Xun],
Shen, J.B.[Jian-Bing],
Multi-threshold deep metric learning for facial expression
recognition,
PR(156), 2024, pp. 110711.
Elsevier DOI
2408
Facial expression recognition, Triplet loss learning, Multiple thresholds
BibRef
Witherow, M.A.[Megan A.],
Samad, M.D.[Manar D.],
Diawara, N.[Norou],
Bar, H.Y.[Haim Y.],
Iftekharuddin, K.M.[Khan M.],
Deep Adaptation of Adult-Child Facial Expressions by Fusing Landmark
Features,
AffCom(15), No. 3, July 2024, pp. 847-858.
IEEE DOI
2409
Pediatrics, Feature extraction, Benchmark testing, Data models,
Face recognition, Estimation, Transfer learning,
child expressions
BibRef
Huang, P.J.[Pin-Jui],
Xie, H.X.[Hong-Xia],
Huang, H.C.[Hung-Cheng],
Shuai, H.H.[Hong-Han],
Cheng, W.H.[Wen-Huang],
CA-FER: Mitigating Spurious Correlation With Counterfactual Attention
in Facial Expression Recognition,
AffCom(15), No. 3, July 2024, pp. 977-989.
IEEE DOI
2409
Feature extraction, Correlation, Face recognition, Training,
Computational modeling, Image color analysis, Deep learning,
spurious correlation
BibRef
Halawa, M.[Marah],
Blume, F.[Florian],
Bideau, P.[Pia],
Maier, M.[Martin],
Rahman, R.A.[Rasha Abdel],
Hellwich, O.[Olaf],
Multi-Task Multi-Modal Self-Supervised Learning for Facial Expression
Recognition,
ABAW24(4604-4614)
IEEE DOI
2410
Visualization, Annotations, Face recognition, Source coding,
Semantics, Self-supervised learning, Manuals,
representation learning
BibRef
Hong, S.[SangHwa],
Purposeful Regularization with Reinforcement Learning for Facial
Expression Recognition In-the-Wild,
ABAW24(4615-4624)
IEEE DOI
2410
Training, Emotion recognition, Numerical analysis,
Face recognition, Noise, FER, Overfitting, Reinforcement Learning
BibRef
Foteinopoulou, N.M.[Niki Maria],
Patras, I.[Ioannis],
EmoCLIP: A Vision-Language Method for Zero-Shot Video Facial
Expression Recognition,
FG24(1-10)
IEEE DOI Code:
WWW Link.
2408
Training, Emotion recognition, Face recognition, Mental disorders,
Natural languages, Estimation, Prototypes
BibRef
Nourivandi, T.[Tara],
Hinduja, S.[Saurabh],
Srivastava, S.[Shivam],
Cohn, J.F.[Jeffrey F.],
Canavan, S.[Shaun],
Mitigating Class Imbalance for Facial Expression Recognition Using
SMOTE on Deep Features,
FG24(1-5)
IEEE DOI
2408
Training, Pain, Face recognition, Neural networks, Decision making,
Entertainment industry, Gesture recognition
BibRef
Li, H.[Hebeizi],
Yang, H.Y.[Hong-Yu],
Huang, D.[Di],
DrFER: Learning Disentangled Representations for 3D Facial Expression
Recognition,
FG24(1-8)
IEEE DOI
2408
Point cloud compression, Face recognition,
Disentangled representation learning, Gesture recognition, Robustness
BibRef
Cho, Y.[Yunseong],
Kim, C.[Chanwoo],
Cho, H.[Hoseong],
Ku, Y.[Yunhoe],
Kim, E.[Eunseo],
Boboev, M.[Muhammadjon],
Lee, J.[Joonseok],
Baek, S.[Seungryul],
RMFER: Semi-supervised Contrastive Learning for Facial Expression
Recognition with Reaction Mashup Video,
WACV24(5901-5910)
IEEE DOI Code:
WWW Link.
2404
Training, Representation learning, Mashups, Face recognition,
Supervised learning, Self-supervised learning, Benchmark testing,
Datasets and evaluations
BibRef
Zhang, X.[Xiang],
Wang, T.[Taoyue],
Li, X.T.[Xiao-Tian],
Yang, H.Y.[Hui-Yuan],
Yin, L.J.[Li-Jun],
Weakly-Supervised Text-driven Contrastive Learning for Facial
Behavior Understanding,
ICCV23(20694-20705)
IEEE DOI
2401
BibRef
Wu, Z.Y.[Zhi-Yu],
Cui, J.S.[Jin-Shi],
LA-Net: Landmark-Aware Learning for Reliable Facial Expression
Recognition under Label Noise,
ICCV23(20641-20650)
IEEE DOI
2401
BibRef
Gu, Y.J.[Ya-Jie],
Pears, N.[Nick],
Sun, H.[Hao],
Adversarial 3D Face Disentanglement of Identity and Expression,
FG23(1-7)
IEEE DOI
2303
Codes, Shape, Face recognition,
Design methodology, Gesture recognition, Adversarial machine learning
BibRef
Lei, J.[Jie],
Liu, Z.[Zhao],
Li, T.[Tong],
Zou, Z.[Zeyu],
Feng, Z.L.[Zun-Lei],
Xu, J.[Juan],
Li, X.[Xuan],
Liang, R.H.[Rong-Hua],
Enhanced Dual-Level Representations for Facial Expression Recognition,
ICIP22(2241-2245)
IEEE DOI
2211
Representation learning, Gold, Image recognition, Image coding,
Databases, Face recognition, Task analysis,
high-level representation enhancement
BibRef
Zhang, Y.H.[Yu-Hang],
Wang, C.[Chengrui],
Ling, X.[Xu],
Deng, W.H.[Wei-Hong],
Learn from All: Erasing Attention Consistency for Noisy Label Facial
Expression Recognition,
ECCV22(XXVI:418-434).
Springer DOI
2211
BibRef
Wang, C.[Chao],
Ding, J.[Jundi],
Yan, H.[Hui],
Shen, S.[Si],
A Prototype-oriented Contrastive Adaption Network for Cross-domain
Facial Expression Recognition,
ACCV22(II:324-340).
Springer DOI
2307
BibRef
Ming, H.P.[Hai-Peng],
Lu, W.H.[Wen-Huan],
Zhang, W.[Wei],
Soft Label Mining and Average Expression Anchoring for Facial
Expression Recognition,
ACCV22(IV:728-744).
Springer DOI
2307
BibRef
Jeong, J.Y.[Jae-Yeop],
Hong, Y.G.[Yeong-Gi],
Hong, S.[Sumin],
Oh, J.[JiYeon],
Jung, Y.C.[Yu-Chul],
Kim, S.H.[Sang-Ho],
Jeong, J.W.[Jin-Woo],
Ensemble of Multi-task Learning Networks for Facial Expression
Recognition In-the-wild with Learning from Synthetic Data,
ABAWE22(60-75).
Springer DOI
2304
BibRef
Stoychev, S.[Samuil],
Churamani, N.[Nikhil],
Gunes, H.[Hatice],
Latent Generative Replay for Resource-Efficient Continual Learning of
Facial Expressions,
FG23(1-8)
IEEE DOI
2303
Performance evaluation, Adaptation models, Face recognition,
Computational modeling, Memory management, Machine learning, Gesture recognition
BibRef
Cheong, J.[Jiaee],
Kalkan, S.[Sinan],
Gunes, H.[Hatice],
Counterfactual Fairness for Facial Expression Recognition,
PeopleAn22(245-261).
Springer DOI
2304
BibRef
Han, J.Y.[Jia-Yi],
Li, A.[Ang],
Han, D.H.[Dong-Hong],
Feng, J.F.[Jian-Feng],
Learning Effective Global Receptive Field for Facial Expression
Recognition,
FG23(1-7)
IEEE DOI
2303
Measurement, Upper bound, Convolution, Fuses, Face recognition,
Gesture recognition, Feature extraction
BibRef
Zhang, W.[Wei],
Ji, X.P.[Xian-Peng],
Chen, K.Y.[Ke-Yu],
Ding, Y.[Yu],
Fan, C.J.[Chang-Jie],
Learning a Facial Expression Embedding Disentangled from Identity,
CVPR21(6755-6764)
IEEE DOI
2111
Manifolds, Image recognition, Head, Annotations,
Face recognition, Image retrieval
BibRef
Yu, B.C.[Bao-Cheng],
Zhang, G.Y.[Guan-Yu],
Xu, W.X.[Wen-Xia],
Wei, M.[Ming],
Face Expression Recognition Based on Lightweight Fused Attention
Mechanism,
ICRVC22(85-89)
IEEE DOI
2301
Target recognition, Convolution, Face recognition,
Computational modeling, Feature extraction, depthwise seperable convolution
BibRef
Liu, X.W.[Xue-Wen],
Guo, Z.[Zhe],
Yuan, B.[Boya],
Guo, H.J.[Hao-Jie],
Robust Facial Expression Recognition Based on Dual Branch
Multi-feature Learning,
ICIVC22(1-6)
IEEE DOI
2301
Training, Adaptation models, Sensitivity, Image recognition, Face recognition,
Mouth, Feature extraction, Densely connected dynamic selection
BibRef
Li, X.[Xiao],
Li, C.L.[Chun-Lei],
Tian, B.[Bo],
Liu, Z.F.[Zhou-Feng],
Yang, R.M.[Rui-Min],
Learning Discriminative Features with Region Attention and Refinement
Network for Facial Expression Recognition in the Wild,
ICPR22(1113-1119)
IEEE DOI
2212
Face recognition, Source coding, Feature extraction,
Facial Expression Recognition, discriminative features,
latent feature mining
BibRef
Miyoshi, R.[Ryo],
Akizuki, S.[Shuichi],
Tobitani, K.[Kensuke],
Nagata, N.[Noriko],
Hashimoto, M.[Manabu],
Convolutional Neural Tree for Video-Based Facial Expression
Recognition Embedding Emotion Wheel as Inductive Bias,
ICIP22(3261-3265)
IEEE DOI
2211
Performance evaluation, Emotion recognition, Image recognition,
Face recognition, Psychology, Wheels, Videos, Emotion model
BibRef
Jin, R.[Rijin],
Zhao, S.[Sirui],
Hao, Z.K.[Zhong-Kai],
Xu, Y.F.[Yi-Fan],
Xu, T.[Tong],
Chen, E.[Enhong],
AVT: Au-Assisted Visual Transformer for Facial Expression Recognition,
ICIP22(2661-2665)
IEEE DOI
2211
Gold, Visualization, Image recognition, Fuses, Face recognition,
Lighting, Transformers, Facial Expression Recognition, Transformer, AU
BibRef
Pan, X.S.[Xiang-Shuai],
Liu, W.F.[Wei-Feng],
Wang, Y.J.[Yan-Jiang],
Lu, X.P.[Xiao-Ping],
Liu, B.[Baodi],
MSL-FER: Mirrored Self-Supervised Learning for Facial Expression
Recognition,
ICIP22(1601-1605)
IEEE DOI
2211
Representation learning, Uncertainty, Image recognition, Costs,
Face recognition, Self-supervised learning, Feature extraction,
Attention
BibRef
Xue, F.L.[Fang-Lei],
Wang, Q.C.[Qiang-Chang],
Guo, G.D.[Guo-Dong],
TransFER: Learning Relation-aware Facial Expression Representations
with Transformers,
ICCV21(3581-3590)
IEEE DOI
2203
Adaptation models, Face recognition, Computational modeling,
Transfer learning, Computer architecture, Benchmark testing, Faces,
Recognition and classification
BibRef
Verma, M.[Manisha],
Nakashima, Y.[Yuta],
Kobori, H.[Hirokazu],
Takaoka, R.[Ryota],
Takemura, N.[Noriko],
Kimura, T.[Tsukasa],
Nagahara, H.[Hajime],
Numao, M.[Masayuki],
Shinohara, K.[Kazumitsu],
Learners' Efficiency Prediction Using Facial Behavior Analysis,
ICIP21(1084-1088)
IEEE DOI
2201
Measurement, Analytical models, Portable computers,
Electronic learning, Webcams, Image processing, Sociology,
facial behavior analysis
BibRef
Du, Y.T.[Yang-Tao],
Yang, D.K.[Ding-Kang],
Zhai, P.[Peng],
Li, M.C.[Ming-Chen],
Zhang, L.H.[Li-Hua],
Learning Associative Representation for Facial Expression Recognition,
ICIP21(889-893)
IEEE DOI
2201
Image recognition, Face recognition, Lighting, Benchmark testing,
Generative adversarial networks, Generators, Facial expression,
robust representation
BibRef
Shome, D.[Debaditya],
Kar, T.,
FedAffect: Few-shot federated learning for facial expression
recognition,
HTCV21(4151-4158)
IEEE DOI
2112
Training, Data privacy, Face recognition,
Supervised learning, Collaborative work
BibRef
Aslam, M.H.[Muhammad Haseeb],
Zeeshan, M.O.[Muhammad Osama],
Belharbi, S.[Soufiane],
Pedersoli, M.[Marco],
Koerich, A.L.[Alessandro Lameiras],
Bacon, S.[Simon],
Granger, E.[Eric],
Distilling Privileged Multimodal Information for Expression
Recognition using Optimal Transport,
FG24(1-10)
IEEE DOI
2408
Training, Deep learning, Pain, Face recognition, Semantics,
Laboratories, Estimation
BibRef
Zeeshan, M.O.[Muhammad Osama],
Aslam, M.H.[Muhammad Haseeb],
Belharbi, S.[Soufiane],
Koerich, A.L.[Alessandro Lameiras],
Pedersoli, M.[Marco],
Bacon, S.[Simon],
Granger, E.[Eric],
Subject-Based Domain Adaptation for Facial Expression Recognition,
FG24(1-10)
IEEE DOI
2408
Training, Adaptation models, Pain, Target recognition,
Image color analysis, Face recognition, Robustness
BibRef
Ayral, T.[Théo],
Pedersoli, M.[Marco],
Bacon, S.[Simon],
Granger, E.[Eric],
Temporal Stochastic Softmax for 3D CNNs:
An Application in Facial Expression Recognition,
WACV21(3028-3037)
IEEE DOI
2106
Training, Visualization, Annotations,
Face recognition, Computational modeling, Stochastic processes
BibRef
Liu, D.Z.[Dai-Zong],
Zhang, H.T.[Hong-Ting],
Zhou, P.[Pan],
Video-based Facial Expression Recognition using Graph Convolutional
Networks,
ICPR21(607-614)
IEEE DOI
2105
Image recognition, Face recognition,
Video sequences, Streaming media, Feature extraction, Data mining
BibRef
Georgescu, M.I.[Mariana-Iuliana],
Ionescu, R.T.[Radu Tudor],
Teacher-Student Training and Triplet Loss for Facial Expression
Recognition under Occlusion,
ICPR21(2288-2295)
IEEE DOI
2105
Training, Headphones, Knowledge engineering, Solid modeling,
Face recognition, Neural networks, Virtual reality
BibRef
Zhu, Y.P.[Yong-Pei],
Fan, H.W.[Hong-Wei],
Yuan, K.[Kehong],
Classification Mechanism of Convolutional Neural Network for Facial
Expression Recognition,
FBE20(717-729).
Springer DOI
2103
BibRef
Zhou, J.,
Zhang, X.,
Liu, Y.,
Learning the Connectivity: Situational Graph Convolution Network for
Facial Expression Recognition,
VCIP20(230-234)
IEEE DOI
2102
Face recognition, Convolution, Feature extraction, Training,
Robustness, Geometry, Topology, facial expression recognition,
occluded facial expression recognition
BibRef
Chen, S.K.[Shi-Kai],
Wang, J.F.[Jian-Feng],
Chen, Y.D.[Yue-Dong],
Shi, Z.C.[Zhong-Chao],
Geng, X.[Xin],
Rui, Y.[Yong],
Label Distribution Learning on Auxiliary Label Space Graphs for
Facial Expression Recognition,
CVPR20(13981-13990)
IEEE DOI
2008
Face recognition, Task analysis, Training, Face, Data models, Image recognition
BibRef
Aspandi, D.,
Mallol-Ragolta, A.,
Schuller, B.,
Binefa, X.,
Latent-Based Adversarial Neural Networks for Facial Affect
Estimations,
FG20(606-610)
IEEE DOI
2102
Feature extraction, Computational modeling, Training, Generators,
Estimation, Biological system modeling,
Latent Representation
BibRef
Rasipuram, S.,
Bhat, J.H.,
Maitra, A.,
Multi-modal Expression Recognition in the Wild Using Sequence
Modeling,
FG20(629-631)
IEEE DOI
2102
Face recognition, Feature extraction, Videos, Databases,
Mel frequency cepstral coefficient, Emotion recognition,
multi modal analysis
BibRef
Churamani, N.,
Gunes, H.,
CLIFER: Continual Learning with Imagination for Facial Expression
Recognition,
FG20(322-328)
IEEE DOI
2102
Adaptation models, Data models, Semantics, Face recognition,
Image recognition, Convolution, Brain modeling,
Affective Computing
BibRef
Mahmoudi, M.A.,
Chetouani, A.,
Boufera, F.,
Tabia, H.,
Kernelized Dense Layers For Facial Expression Recognition,
ICIP20(2226-2230)
IEEE DOI
2011
Kernel, Convolution, Neurons, Standards, Task analysis,
Computational modeling, Training, facial expression recognition,
fully connected layers
BibRef
Jin, L.,
Zhou, Y.,
Liu, H.,
Song, E.,
Deformable Quaternion Gabor Convolutional Neural Network For Color
Facial Expression Recognition,
ICIP20(1696-1700)
IEEE DOI
2011
Quaternions, Gabor filters, Training, Convolution,
Image color analysis, Feature extraction, color image processing
BibRef
Zhu, K.,
Wang, Y.,
Yang, H.,
Huang, D.,
Chen, L.,
Intensity Enhancement Via GAN for Multimodal Facial Expression
Recognition,
ICIP20(1346-1350)
IEEE DOI
2011
Face Expression Recognition, Generative Adversarial Network,
Intensity Enhancement
BibRef
Fan, X.,
Deng, Z.,
Wang, K.,
Peng, X.,
Qiao, Y.,
Learning Discriminative Representation For Facial Expression
Recognition From Uncertainties,
ICIP20(903-907)
IEEE DOI
2011
Facial expression, Rayleigh loss, weighted Softmax, robust representation.
BibRef
Xu, X.,
Ruan, Z.,
Yang, L.,
Facial Expression Recognition Based on Graph Neural Network,
ICIVC20(211-214)
IEEE DOI
2009
Face recognition, Face, Feature extraction,
Convolutional neural networks, Image recognition, Databases,
graph convolutional neural network
BibRef
Verma, M.,
Kobori, H.,
Nakashima, Y.,
Takemura, N.,
Nagahara, H.,
Facial Expression Recognition with Skip-Connection to Leverage
Low-Level Features,
ICIP19(51-55)
IEEE DOI
1910
Facial expression recognition, facial landmarks,
convolutional neural network, low level features.
BibRef
Bai, M.,
Xie, W.,
Shen, L.,
Disentangled Feature Based Adversarial Learning for Facial Expression
Recognition,
ICIP19(31-35)
IEEE DOI
1910
Disentangled feature, adversarial learning,
expression disentangling, residual expression
BibRef
Chen, J.,
Konrad, J.,
Ishwar, P.,
VGAN-Based Image Representation Learning for Privacy-Preserving
Facial Expression Recognition,
PRIV18(1651-165109)
IEEE DOI
1812
Face, Face recognition, Privacy, Visualization,
Image recognition, Generative adversarial networks
BibRef
Yang, H.,
Ciftci, U.,
Yin, L.,
Facial Expression Recognition by De-expression Residue Learning,
CVPR18(2168-2177)
IEEE DOI
1812
Face, Generators, Face recognition, Databases,
Training data, Training
BibRef
Lin, F.,
Hong, R.,
Zhou, W.,
Li, H.,
Facial Expression Recognition with Data Augmentation and Compact
Feature Learning,
ICIP18(1957-1961)
IEEE DOI
1809
Face, Training, Databases, Face recognition, Shape, Solid modeling,
cluster loss
BibRef
Shen, F.,
Liu, J.,
Wu, P.,
Double Complete D-LBP with Extreme Learning Machine Auto-Encoder and
Cascade Forest for Facial Expression Analysis,
ICIP18(1947-1951)
IEEE DOI
1809
Databases, Forestry, Feature extraction, Histograms,
Face recognition, Principal component analysis, Training,
cascade forest
BibRef
Aneja, D.[Deepali],
Chaudhuri, B.,
Colburn, A.[Alex],
Faigin, G.[Gary],
Shapiro, L.G.[Linda G.],
Mones, B.[Barbara],
Learning to Generate 3D Stylized Character Expressions from Humans,
WACV18(160-169)
IEEE DOI
1806
computer animation, face recognition, feedforward neural nets,
learning (artificial intelligence), 3D animated character rig,
BibRef
Aneja, D.[Deepali],
Colburn, A.[Alex],
Faigin, G.[Gary],
Shapiro, L.G.[Linda G.],
Mones, B.[Barbara],
Modeling Stylized Character Expressions via Deep Learning,
ACCV16(II: 136-153).
Springer DOI
1704
BibRef
Mikheeva, O.,
Ek, C.H.,
Kjellstroem, H.,
Perceptual Facial Expression Representation,
FG18(179-186)
IEEE DOI
1806
Computational modeling, Data models, Encoding, Face, Neural networks,
Semantics, Standards, facial expressions, representation learning,
variational auto encoder
BibRef
Li, Z.,
Wu, S.,
Xiao, G.,
Facial Expression Recognition by Multi-Scale CNN with Regularized
Center Loss,
ICPR18(3384-3389)
IEEE DOI
1812
convolution, face recognition, feature extraction,
feedforward neural nets, image classification,
regularized center loss
BibRef
Dong, J.Y.[Jia-Yu],
Zheng, H.C.[Hui-Cheng],
Lian, L.[Lina],
Dynamic Facial Expression Recognition Based on Convolutional Neural
Networks with Dense Connections,
ICPR18(3433-3438)
IEEE DOI
1812
Databases, Image sequences, Face, Training, Face recognition,
Training data, Convolutional neural networks
BibRef
Tran, E.,
Mayhew, M.B.,
Kim, H.,
Karande, P.,
Kaplan, A.D.,
Facial Expression Recognition Using a Large Out-of-Context Dataset,
Assist18(52-59)
IEEE DOI
1806
emotion recognition, face recognition, neural nets, FER+ dataset,
MS-Celeb-1M dataset, emotion labels, emotion recognition model,
Training
BibRef
Gu, J.,
Hu, H.,
Xie, S.,
Enhanced dictionary pair learning sparse representation model for
facial expression classification,
ICIP17(4467-4471)
IEEE DOI
1803
Dictionaries, Face, Feature extraction, Indexes, Training,
dictionary pair learning, facial expression recognition,
sparse representation
BibRef
Liu, X.,
Guo, Z.,
Li, S.,
Jia, P.,
Kong, L.,
You, J.,
Kumar, B.V.K.V.,
Permutation-Invariant Feature Restructuring for Correlation-Aware
Image Set-Based Recognition,
ICCV19(4985-4995)
IEEE DOI
2004
face recognition, feature extraction, image sequences,
learning (artificial intelligence), optimisation,
Image reconstruction
BibRef
Gui, L.,
Baltrušaitis, T.,
Morency, L.P.[Louis-Philippe],
Curriculum Learning for Facial Expression Recognition,
FG17(505-511)
IEEE DOI
1707
Complexity theory, Emotion recognition, Face, Face recognition,
Machine learning, Neural networks, Training
BibRef
Huang, Y.,
Lu, H.Q.[Han-Qing],
Hybrid hypergraph construction for facial expression recognition,
ICPR16(4142-4147)
IEEE DOI
1705
Face, Face recognition, Image recognition, Mathematical model,
Neural networks, Training
BibRef
Arbabzadah, F.[Farhad],
Montavon, G.[Grégoire],
Müller, K.R.[Klaus-Robert],
Samek, W.[Wojciech],
Identifying Individual Facial Expressions by Deconstructing a Neural
Network,
GCPR16(344-354).
Springer DOI
1611
BibRef
Cai, J.[Jie],
Meng, Z.[Zibo],
Khan, A.S.[Ahmed Shehab],
O'Reilly, J.[James],
Li, Z.Y.[Zhi-Yuan],
Han, S.Z.[Shi-Zhong],
Tong, Y.[Yan],
Identity-Free Facial Expression Recognition Using Conditional
Generative Adversarial Network,
ICIP21(1344-1348)
IEEE DOI
2201
Image recognition, Face recognition, Neural networks, Lighting,
Transforms, Generative adversarial networks,
Generative Adversarial Network
BibRef
Meng, Z.[Zibo],
Liu, P.[Ping],
Cai, J.,
Han, S.Z.[Shi-Zhong],
Tong, Y.[Yan],
Identity-Aware Convolutional Neural Network for Facial Expression
Recognition,
FG17(558-565)
IEEE DOI
1707
Databases, Face recognition, Feature extraction, Image recognition,
Measurement, Spatiotemporal phenomena, Training
BibRef
de Vries, G.J.[Gert-Jan],
Pauws, S.[Steffen],
Biehl, M.[Michael],
Facial Expression Recognition Using Learning Vector Quantization,
CAIP15(II:760-771).
Springer DOI
1511
BibRef
Fang, Y.C.[Yu-Chun],
Chang, L.[Lu],
Multi-instance Feature Learning Based on Sparse Representation for
Facial Expression Recognition,
MMMod15(I: 224-233).
Springer DOI
1501
BibRef
Liu, W.F.[Wei-Feng],
Song, C.F.[Cai-Feng],
Wang, Y.J.[Yan-Jiang],
Facial expression recognition based on discriminative dictionary
learning,
ICPR12(1839-1842).
WWW Link.
1302
BibRef
Ptucha, R.[Raymond],
Tsagkatakis, G.[Grigorios],
Savakis, A.E.[Andreas E.],
Manifold based Sparse Representation for robust expression recognition
without neutral subtraction,
BenchFace11(2136-2143).
IEEE DOI
1201
BibRef
And:
Manifold learning for simultaneous pose and facial expression
recognition,
ICIP11(3021-3024).
IEEE DOI
1201
BibRef
Earlier: A1, A3, Only
Facial Expression Recognition Using Facial Features and Manifold
Learning,
ISVC10(III: 301-309).
Springer DOI
1011
BibRef
And: A1, A3, Only
Pose estimation using facial feature points and manifold learning,
ICIP10(3261-3264).
IEEE DOI
1009
BibRef
Tax, D.M.J.,
Hendriks, E.,
Valstar, M.F.[Michel F.],
Pantic, M.[Maja],
The Detection of Concept Frames Using Clustering Multi-instance
Learning,
ICPR10(2917-2920).
IEEE DOI
1008
For facial expressions. Not model sequence, just concept (key) frames.
BibRef
Isukapalli, R.,
Elgammal, A.M.,
Greiner, R.,
Learning to Identify Facial Expression During Detection Using Markov
Decision Process,
FGR06(305-310).
IEEE DOI
0604
BibRef
Kumar, R.[Ranjeeth],
Manikandan, S.,
Jawahar, C.V.,
Task Specific Factors for Video Characterization,
ICCVGIP06(376-387).
Springer DOI
0612
Learn factorization for facial expression recognition and synthesis.
BibRef
Chen, X.[Xilen],
Kwong, S.[Sam],
Lu, Y.[Yan],
Human facial expression recognition based on learning subspace method,
ICME00(MP7).
0007
BibRef
Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Deep Learning Facial Expression Recognition .