22.3.6.1.1 Face Expression Recognition Using Learning, Neural Nets

Chapter Contents (Back)
Faces, Expression. Facial Expressions. Expressions. Learning. Neural Nets. A subset:
See also Deep Learning Facial Expression Recognition.

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.[Ziyu],
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

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.[Hanwei], 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
computer vision, 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


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.[Zhiyu], 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

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, Computer vision, Correlation, Face recognition, Gesture recognition, Faces 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

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

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.[Ruimin],
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

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 .


Last update:Jun 17, 2024 at 21:38:11