22.3.6.1.1 Face Expression Recognition Using Learning, Neural Nets

Chapter Contents (Back)
Faces, Expression. Facial Expressions. Expressions. Learning. Neural Nets.

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

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

Gupta, O.[Otkrist], Raviv, D.[Dan], Raskar, R.[Ramesh],
Illumination invariants in deep video expression recognition,
PR(76), No. 1, 2018, pp. 25-35.
Elsevier DOI 1801
Deep learning BibRef

Salmam, F.Z.[Fatima Zahra], Madani, A.[Abdellah], Kissi, M.[Mohamed],
Fusing multi-stream deep neural networks for facial expression recognition,
SIViP(13), No. 3, April 2019, pp. 609-616.
WWW Link. 1904
BibRef

Xie, S.Y.[Si-Yue], Hu, H.F.[Hai-Feng], Wu, Y.B.[Yong-Bo],
Deep multi-path convolutional neural network joint with salient region attention for facial expression recognition,
PR(92), 2019, pp. 177-191.
Elsevier DOI 1905
Attention, Convolutional neural network, Facial expression recognition, Salient expressional region descriptor BibRef

Xie, S.Y.[Si-Yue], Hu, H.F.[Hai-Feng], Chen, Y.Z.[Yi-Zhen],
Facial Expression Recognition With Two-Branch Disentangled Generative Adversarial Network,
CirSysVideo(31), No. 6, June 2021, pp. 2359-2371.
IEEE DOI 2106
Face recognition, Feature extraction, Generative adversarial networks, Task analysis, Generators, Two-branch Disentangled Generative Adversarial Network 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

Gupta, O.[Otkrist], Raviv, D.[Dan], Raskar, R.[Ramesh],
Multi-Velocity Neural Networks for Facial Expression Recognition in Videos,
AffCom(10), No. 2, April 2019, pp. 290-296.
IEEE DOI 1906
Videos, Training, Splines (mathematics), Face recognition, Convolutional codes, Biological neural networks, Deep learning, machine learning BibRef

Majumder, A.[Anima], Behera, L.[Laxmidhar], Subramanian, V.K.,
Automatic Facial Expression Recognition System Using Deep Network-Based Data Fusion,
Cyber(48), No. 1, January 2018, pp. 103-114.
IEEE DOI 1801
BibRef
Earlier: A1, A2, Only:
Facial Expression Recognition with Regional Features Using Local Binary Patterns,
CAIP13(556-563).
Springer DOI 1308
Active appearance model, Computer architecture, Data integration, Face, Face recognition, Feature extraction, support vector machine (SVM) BibRef

Zheng, W.M.[Wen-Ming], Zong, Y., Zhou, X.Y.[Xiao-Yan], Xin, M.,
Cross-Domain Color Facial Expression Recognition Using Transductive Transfer Subspace Learning,
AffCom(9), No. 1, January 2018, pp. 21-37.
IEEE DOI 1804
face recognition, feature extraction, image classification, image colour analysis, learning (artificial intelligence), transductive transfer learning BibRef

Zhang, W.J.[Wen-Jing], Song, P.[Peng], Zheng, W.M.[Wen-Ming],
A Novel Transferable Sparse Regression Method for Cross-Database Facial Expression Recognition,
IEICE(E105-D), No. 1, January 2022, pp. 184-188.
WWW Link. 2201
BibRef

Chen, D.L.[Dong-Liang], Song, P.[Peng], Zhang, W.J.[Wen-Jing], Zhang, W.J.[Wei-Jian], Xu, B.G.[Bin-Gui], Zhou, X.[Xuan],
Robust Transferable Subspace Learning for Cross-Corpus Facial Expression Recognition,
IEICE(E103-D), No. 10, October 2020, pp. 2241-2245.
WWW Link. 2010
BibRef

Chen, D.L.[Dong-Liang], Song, P.[Peng], Zheng, W.M.[Wen-Ming],
Learning Transferable Sparse Representations for Cross-Corpus Facial Expression Recognition,
AffCom(14), No. 2, April 2023, pp. 1322-1333.
IEEE DOI 2306
Face recognition, Dictionaries, Transfer learning, Training, Databases, Testing, Encoding, Sparse subspace clustering, facial expression recognition BibRef

Chen, D.L.[Dong-Liang], Wen, G.H.[Gui-Hua], Wen, P.C.[Peng-Cheng], Yang, P.[Pei], Chen, R.[Rui], Li, C.[Cheng],
Cross-Domain Sample Relationship Learning for Facial Expression Recognition,
MultMed(26), 2024, pp. 3788-3798.
IEEE DOI 2402
Databases, Transformers, Face recognition, Training, Task analysis, Target recognition, Knowledge transfer, Deep neural network, transformer BibRef

Zhang, W.J.[Wen-Jing], Song, P.[Peng], Zheng, W.M.[Wen-Ming],
Joint Local-Global Discriminative Subspace Transfer Learning for Facial Expression Recognition,
AffCom(14), No. 3, July 2023, pp. 2484-2495.
IEEE DOI 2310
BibRef

Zheng, W.M.[Wen-Ming], Zhou, X.Y.[Xiao-Yan],
Cross-pose color facial expression recognition using transductive transfer linear discriminat analysis,
ICIP15(1935-1939)
IEEE DOI 1512
Color facial expression recognition 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

Huang, Y.[Ying], Yan, Y.[Yan], Chen, S.[Si], Wang, H.Z.[Han-Zi],
Expression-targeted feature learning for effective facial expression recognition,
JVCIR(55), 2018, pp. 677-687.
Elsevier DOI 1809
Facial expression recognition, Multi-task learning, Feature learning, Convolutional neural network 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

Yan, Y.[Yan], Huang, Y.[Ying], Chen, S.[Si], Shen, C.H.[Chun-Hua], Wang, H.Z.[Han-Zi],
Joint Deep Learning of Facial Expression Synthesis and Recognition,
MultMed(22), No. 11, November 2020, pp. 2792-2807.
IEEE DOI 2010
Face recognition, Databases, Generative adversarial networks, Deep learning, Training data, generative adversarial net (GAN) BibRef

Ruan, D.[Delian], Mo, R.Y.[Rong-Yun], Yan, Y.[Yan], Chen, S.[Si], Xue, J.H.[Jing-Hao], Wang, H.Z.[Han-Zi],
Adaptive Deep Disturbance-Disentangled Learning for Facial Expression Recognition,
IJCV(130), No. 2, February 2022, pp. 455-477.
Springer DOI 2202
BibRef

Ruan, D.[Delian], Yan, Y.[Yan], Lai, S.Q.[Shen-Qi], Chai, Z.H.[Zhen-Hua], Shen, C.H.[Chun-Hua], Wang, H.Z.[Han-Zi],
Feature Decomposition and Reconstruction Learning for Effective Facial Expression Recognition,
CVPR21(7656-7665)
IEEE DOI 2111
Databases, Face recognition, Feature extraction BibRef

Zhang, Z.Z.[Zi-Zhao], Yan, Y.[Yan], Wang, H.Z.[Han-Zi],
Discriminative filter based regression learning for facial expression recognition,
ICIP13(1192-1196)
IEEE DOI 1402
Cost function BibRef

Li, S., Deng, W.,
Reliable Crowdsourcing and Deep Locality-Preserving Learning for Unconstrained Facial Expression Recognition,
IP(28), No. 1, January 2019, pp. 356-370.
IEEE DOI 1810
convolution, emotion recognition, expectation-maximisation algorithm, face recognition, deep learning BibRef

Li, S., Deng, W., Du, J.,
Reliable Crowdsourcing and Deep Locality-Preserving Learning for Expression Recognition in the Wild,
CVPR17(2584-2593)
IEEE DOI 1711
Compounds, Crowdsourcing, Databases, Face recognition, Gold, Machine learning, Reliability 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

Kuo, C., Lai, S., Sarkis, M.,
A Compact Deep Learning Model for Robust Facial Expression Recognition,
AMFG18(2202-22028)
IEEE DOI 1812
Databases, Training, Face recognition, Hidden Markov models, Face, Image recognition, Image sequences 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

Kim, D.H.[Dae Hoe], Baddar, W.J.[Wissam J.], Jang, J., Ro, Y.M.[Yong Man],
Multi-Objective Based Spatio-Temporal Feature Representation Learning Robust to Expression Intensity Variations for Facial Expression Recognition,
AffCom(10), No. 2, April 2019, pp. 223-236.
IEEE DOI 1906
BibRef
Earlier: A2, A1, A4, Only:
Learning Features Robust to Image Variations with Siamese Networks for Facial Expression Recognition,
MMMod17(I: 189-200).
Springer DOI 1701
Feature extraction, Face recognition, Robustness, Machine learning, Training, long short-term memory (LSTM) 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

Ye, Y.S.[Ying-Sheng], Zhang, X.M.[Xing-Ming], Lin, Y.B.[Yu-Bei], Wang, H.X.[Hao-Xiang],
Facial expression recognition via region-based convolutional fusion network,
JVCIR(62), 2019, pp. 1-11.
Elsevier DOI 1908
Facial expression recognition, Emotion recognition, Convolution neural network BibRef

Tang, Y.[Yan], Zhang, X.M.[Xing-Ming], Hu, X.P.[Xi-Ping], Wang, S.Q.[Si-Qi], Wang, H.X.[Hao-Xiang],
Facial Expression Recognition Using Frequency Neural Network,
IP(30), 2021, pp. 444-457.
IEEE DOI 2012
Frequency-domain analysis, Feature extraction, Discrete cosine transforms, Face recognition, Deep learning, deep learning BibRef

Huang, M.Y.[Meng-Yu], Zhang, X.M.[Xing-Ming], Lan, X.Y.[Xiang-Yuan], Wang, H.X.[Hao-Xiang], Tang, Y.[Yan],
Convolution by Multiplication: Accelerated Two- Stream Fourier Domain Convolutional Neural Network for Facial Expression Recognition,
CirSysVideo(32), No. 3, March 2022, pp. 1431-1442.
IEEE DOI 2203
Feature extraction, Face recognition, Frequency-domain analysis, Convolutional neural networks, Deep learning, Convolution, frequency domain BibRef

Zhou, J.Z.[Jin-Zhao], Zhang, X.M.[Xing-Ming], Lin, Y.B.[Yu-Bei], Liu, Y.[Yang],
Facial expression recognition using frequency multiplication network with uniform rectangular features,
JVCIR(75), 2021, pp. 103018.
Elsevier DOI 2103
Facial expression recognition, Uniform rectangular features, Frequency multiplication network BibRef

Zhou, J.Z.[Jin-Zhao], Zhang, X.M.[Xing-Ming], Liu, Y.[Yang], Lan, X.Y.[Xiang-Yuan],
Facial Expression Recognition Using Spatial-Temporal Semantic Graph Network,
ICIP20(1961-1965)
IEEE DOI 2011
Semantics, Face recognition, Feature extraction, Convolution, Heuristic algorithms, Geometry, Neural networks, Spatial Temporal Graph Convolutional Network 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

Fan, X.J.[Xi-Jian], Tjahjadi, T.[Tardi],
Fusing dynamic deep learned features and handcrafted features for facial expression recognition,
JVCIR(65), 2019, pp. 102659.
Elsevier DOI 1912
Convolutional neural network, Facial expression recognition, Feature extraction 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
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Liang, D.D.[Dan-Dan], Liang, H.G.[Hua-Gang], Yu, Z.B.[Zhen-Bo], Zhang, Y.P.[Yi-Pu],
Deep convolutional BiLSTM fusion network for facial expression recognition,
VC(36), No. 3, March 2020, pp. 499-508.
WWW Link. 2002
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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
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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
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Wang, K.[Kai], Peng, X.J.[Xiao-Jiang], Yang, J.F.[Jian-Fei], Meng, D.B.[De-Bin], Qiao, Y.[Yu],
Region Attention Networks for Pose and Occlusion Robust Facial Expression Recognition,
IP(29), 2020, pp. 4057-4069.
IEEE DOI 2002
Facial expression recognition, occlusion-robust and pose-invariant, region attention network, deep convolutional neural networks BibRef

Wang, K.[Kai], Peng, X.J.[Xiao-Jiang], Yang, J.F.[Jian-Fei], Lu, S.J.[Shi-Jian], Qiao, Y.[Yu],
Suppressing Uncertainties for Large-Scale Facial Expression Recognition,
CVPR20(6896-6905)
IEEE DOI 2008
Uncertainty, Face recognition, Feature extraction, Noise measurement, Training, Face 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

Zhang, H.P.[He-Peng], Huang, B.[Bin], Tian, G.H.[Guo-Hui],
Facial expression recognition based on deep convolution long short-term memory networks of double-channel weighted mixture,
PRL(131), 2020, pp. 128-134.
Elsevier DOI 2004
Facial expression recognition, Computer applications, CNN, LSTM BibRef

Sun, Z.[Zhe], Chiong, R.[Raymond], Hu, Z.P.[Zheng-Ping], Li, S.F.[Shu-Fang],
Deep subspace learning for expression recognition driven by a two-phase representation classifier,
SIViP(14), No. 3, April 2020, pp. 437-444.
WWW Link. 2004
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Rajan, S.[Saranya], Chenniappan, P.[Poongodi], Devaraj, S.[Somasundaram], Madian, N.[Nirmala],
Novel deep learning model for facial expression recognition based on maximum boosted CNN and LSTM,
IET-IPR(14), No. 7, 29 May 2020, pp. 1373-1381.
DOI Link 2005
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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

Lee, J.R.H.[J. R. Hou], Wong, A.,
TimeConvNets: A Deep Time Windowed Convolution Neural Network Design for Real-time Video Facial Expression Recognition,
CRV20(9-16)
IEEE DOI 2006
convolution, temporal, emotion, expression, dataset 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
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Mahmoudi, M.A.[M. Amine], Chetouani, A.[Aladine], Boufera, F.[Fatma], Tabia, H.[Hedi],
Learnable pooling weights for facial expression recognition,
PRL(138), 2020, pp. 644-650.
Elsevier DOI 1806
Facial expression recognition, Deep learning, Kernel methods BibRef

Mahmoudi, M.A.[M. Amine], Chetouani, A.[Aladine], Boufera, F.[Fatma], Tabia, H.[Hedi],
Kernel-based convolution expansion for facial expression recognition,
PRL(160), 2022, pp. 128-134.
Elsevier DOI 2208
Emotion recognition, Facial expression recognition, Deep learning, Kernel methods 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

Jain, D.K.[Deepak Kumar], Zhang, Z.[Zhang], Huang, K.Q.[Kai-Qi],
Multi angle optimal pattern-based deep learning for automatic facial expression recognition,
PRL(139), 2020, pp. 157-165.
Elsevier DOI 2011
STM, SURF, CNN, LSTM 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

Jiang, P., Wan, B., Wang, Q., Wu, J.,
Fast and Efficient Facial Expression Recognition Using a Gabor Convolutional Network,
SPLetters(27), 2020, pp. 1954-1958.
IEEE DOI 2011
Convolution, Feature extraction, Databases, Convolutional codes, Computational modeling, Training, Computer architecture, deep learning BibRef

Handa, A.[Anand], Agarwal, R.[Rashi], Kohli, N.[Narendra],
Incremental approach for multi-modal face expression recognition system using deep neural networks,
IJCVR(11), No. 1, 2021, pp. 1-20.
DOI Link 2012
BibRef

Nanda, A.[Abhilasha], Im, W.B.[Woo-Bin], Choi, K.S.[Key-Sun], Yang, H.S.[Hyun Seung],
Combined center dispersion loss function for deep facial expression recognition,
PRL(141), 2021, pp. 8-15.
Elsevier DOI 2101
Facial expression recognition, Deep learning, Combined center dispersion loss function, Ensemble model 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

Barros, P., Churamani, N., Sciutti, A.,
The FaceChannel: A Light-weight Deep Neural Network for Facial Expression Recognition.,
FG20(652-656)
IEEE DOI 2102
Face recognition, Adaptation models, Training, Computational modeling, Faces, Annotations, Data models, Deep Learning 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

Kondo, K.[Kazuaki], Nakamura, T.[Taichi], Nakamura, Y.[Yuichi], Satoh, S.[Shinichi],
Siamese-structure Deep Neural Network Recognizing Changes in Facial Expression According to the Degree of Smiling,
ICPR21(4605-4612)
IEEE DOI 2105
Measurement, Visualization, Image recognition, Face recognition, Perturbation methods, Neural networks, Mouth, Quality-of-life, Siamese network 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

Zhao, Z.Q.[Zeng-Qun], Liu, Q.S.[Qing-Shan], Wang, S.M.[Shan-Min],
Learning Deep Global Multi-Scale and Local Attention Features for Facial Expression Recognition in the Wild,
IP(30), 2021, pp. 6544-6556.
IEEE DOI 2108
Feature extraction, Face recognition, Image recognition, Faces, Convolution, Image reconstruction, Geometry, local attention 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

Qayyum, A.[Abdul], Razzak, I.[Imran], Moustafa, N.[Nour], Mazher, M.[Moona],
Progressive ShallowNet for large scale dynamic and spontaneous facial behaviour analysis in children,
IVC(119), 2022, pp. 104375.
Elsevier DOI 2202
Psychological health, Human computer interaction, Emotion care, Depressed, Facial behavior recognition, Patient monitoring 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

Tong, X.Y.[Xiao-Yun], Sun, S.L.[Song-Lin], Fu, M.X.[Mei-Xia],
Adaptive weight based on overlapping blocks network for facial expression recognition,
IVC(120), 2022, pp. 104399.
Elsevier DOI 2204
Facial expression recognition, Feature map block, Adaptive weight, Deep learning BibRef

Wang, C.[Cong], Xue, J.[Jian], Lu, K.[Ke], Yan, Y.F.[Yan-Fu],
Light Attention Embedding for Facial Expression Recognition,
CirSysVideo(32), No. 4, April 2022, pp. 1834-1847.
IEEE DOI 2204
Face recognition, Feature extraction, Task analysis, Training, Faces, Computer architecture, Videos, Facial expression recognition, deep neural network 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

Zhang, J.[Jing], Yu, H.M.[Hui-Min],
Improving the Facial Expression Recognition and Its Interpretability via Generating Expression Pattern-map,
PR(129), 2022, pp. 108737.
Elsevier DOI 2206
Facial expression recognition, Facial expression visualization, Deep neural networks 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.[Yuewei], 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

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

Mishra, R.K.[Ram Krishn], Urolagin, S.[Siddhaling], Arul-Jothi, J.A.[J. Angel], Gaur, P.[Pramod],
Deep hybrid learning for facial expression binary classifications and predictions,
IVC(128), 2022, pp. 104573.
Elsevier DOI 2212
Convolutional neural network, Deep neural network, Deep neural hybrid learning, Transfer learning BibRef

Albraikan, A.A.[Amani Abdulrahman], Alzahrani, J.S.[Jaber S.], Alshahrani, R.[Reem], Yafoz, A.[Ayman], Alsini, R.[Raed], Hilal, A.M.[Anwer Mustafa], Alkhayyat, A.[Ahmed], Gupta, D.[Deepak],
Intelligent facial expression recognition and classification using optimal deep transfer learning model,
IVC(128), 2022, pp. 104583.
Elsevier DOI 2212
Facial expression recognition, Deep learning, Mask RCNN, Face detection, Machine learning, Adam optimizer BibRef

Sun, Z.[Zhe], Zhang, H.[Hehao], Bai, J.[Jiatong], Liu, M.Y.[Ming-Yang], Hu, Z.P.[Zheng-Ping],
A discriminatively deep fusion approach with improved conditional GAN (im-cGAN) for facial expression recognition,
PR(135), 2023, pp. 109157.
Elsevier DOI 2212
Facial expression recognition, Discriminatively deep fusion approach, Discriminative loss function BibRef

Choi, J.Y.[Jae Young], Lee, B.[Bumshik],
Combining Deep Convolutional Neural Networks with Stochastic Ensemble Weight Optimization for Facial Expression Recognition in the Wild,
MultMed(25), 2023, pp. 100-111.
IEEE DOI 2301
Optimization, Face recognition, Deep learning, Faces, Convolutional neural networks, Bagging, Training, deep ensemble generalization error BibRef

Filntisis, P.P.[Panagiotis P.], Retsinas, G.[George], Paraperas-Papantoniou, F.[Foivos], Katsamanis, A.[Athanasios], Roussos, A.[Anastasios], Maragos, P.[Petros],
SPECTRE: Visual Speech-Informed Perceptual 3D Facial Expression Reconstruction from Videos,
ABAW23(5745-5755)
IEEE DOI 2309
BibRef

Antoniadis, P.[Panagiotis], Filntisis, P.P.[Panagiotis Paraskevas], Maragos, P.[Petros],
Exploiting Emotional Dependencies with Graph Convolutional Networks for Facial Expression Recognition,
FG21(1-8)
IEEE DOI 2303
Deep learning, Emotion recognition, Image recognition, Databases, Face recognition, Psychology 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

Li, Y.J.[Ying-Jian], Zhang, Z.[Zheng], Chen, B.Z.[Bing-Zhi], Lu, G.M.[Guang-Ming], Zhang, D.[David],
Deep Margin-Sensitive Representation Learning for Cross-Domain Facial Expression Recognition,
MultMed(25), 2023, pp. 1359-1373.
IEEE DOI 2305
Feature extraction, Databases, Face recognition, Semantics, Data mining, Representation learning, Measurement, semantic representations BibRef

Jabbooree, A.I.[Abbas Issa], Khanli, L.M.[Leyli Mohammad], Salehpour, P.[Pedram], Pourbahrami, S.[Shahin],
A novel facial expression recognition algorithm using geometry beta-Skeleton in fusion based on deep CNN,
IVC(134), 2023, pp. 104677.
Elsevier DOI 2305
Data fusion, ß-Skeleton, Geometry features, Deep learning, CNN 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

Banerjee, R.[Rudranath], De, S.[Sourav], Dey, S.[Shouvik],
A Survey on Various Deep Learning Algorithms for an Efficient Facial Expression Recognition System,
IJIG(23), No. 3 2023, pp. 2240005.
DOI Link 2306
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

Gavade, P.A.[Priyanka A.], Bhat, V.S.[Vandana S.], Pujari, J.[Jagadeesh],
Hybrid Features and Deep Learning Model for Facial Expression Recognition From Videos,
IJIG(23), No. 5 2023, pp. 2350045.
DOI Link 2310
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

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


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

Li, S.Y.[Si-Yang], Xu, Y.F.[Yi-Fan], Wu, H.Y.[Huan-Yu], Wu, D.R.[Dong-Rui], Yin, Y.J.[Ying-Jie], Cao, J.J.[Jia-Jiong], Ding, J.T.[Jing-Ting],
Facial Expression Recognition In-the-wild with Deep Pre-trained Models,
ABAWE22(181-190).
Springer DOI 2304
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

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

Le, N.[Nhat], Nguyen, K.[Khanh], Tran, Q.[Quang], Tjiputra, E.[Erman], Le, B.[Bac], Nguyen, A.[Anh],
Uncertainty-aware Label Distribution Learning for Facial Expression Recognition,
WACV23(6077-6086)
IEEE DOI 2302
Training, Learning systems, Deep learning, Adaptation models, Emotion recognition, Uncertainty, Face recognition, body pose 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

Bonnard, J.[Jules], Dapogny, A.[Arnaud], Dhombres, F.[Ferdinand], Bailly, K.[Kevin],
Privileged Attribution Constrained Deep Networks for Facial Expression Recognition,
ICPR22(1055-1061)
IEEE DOI 2212
Heating systems, Location awareness, Adaptation models, Ultrasonic imaging, Limiting, Face recognition, Computational modeling 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

Phan, K.N.[Kim Ngan], Nguyen, H.H.[Hong-Hai], Huynh, V.T.[Van-Thong], Kim, S.H.[Soo-Hyung],
Facial Expression Classification using Fusion of Deep Neural Network in Video,
ABAW22(2506-2510)
IEEE DOI 2210
Human computer interaction, Emotion recognition, Computational modeling, Neural networks, Transformers, Pattern recognition BibRef

Li, H.[Hangyu], Wang, N.N.[Nan-Nan], Yang, X.[Xi], Wang, X.Y.[Xiao-Yu], Gao, X.B.[Xin-Bo],
Towards Semi-Supervised Deep Facial Expression Recognition with An Adaptive Confidence Margin,
CVPR22(4156-4165)
IEEE DOI 2210
Training, Adaptation models, Codes, Face recognition, Semisupervised learning, Data models, Face and gestures, Self- semi- meta- unsupervised learning 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

Schoneveld, L.[Liam], Othmani, A.[Alice],
Towards a General Deep Feature Extractor for Facial Expression Recognition,
ICIP21(2339-2342)
IEEE DOI 2201
Training, Deep learning, Emotion recognition, Visualization, Image recognition, Face recognition, Knowledge distillation 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

Zheng, Z.Z.[Zhen-Zhu], Rasmussen, C.[Christopher], Peng, X.[Xi],
Student-Teacher Oneness: A Storage-efficient approach that improves facial expression recognition,
HTCV21(4060-4069)
IEEE DOI 2112
Training, Lead acid batteries, Deep learning, Face recognition, Memory management BibRef

Farzaneh, A.H.[Amir Hossein], Qi, X.J.[Xiao-Jun],
Facial Expression Recognition in the Wild via Deep Attentive Center Loss,
WACV21(2401-2410)
IEEE DOI 2106
Measurement, Learning systems, Face recognition, Neural networks, Linear programming 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

Méndez-Llanes, N.[Nelson], Castillo-Rosado, K.[Katy], Méndez-Vázquez, H.[Heydi], Tistarelli, M.[Massimo],
Quality-based Representation for Unconstrained Face Recognition,
ICPR21(6494-6500)
IEEE DOI 2105
Deep learning, Analytical models, Databases, Face recognition, Computational modeling, Feature extraction, Proposals 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

Valev, H.[Hristo], Gallucci, A.[Alessio], Leufkens, T.[Tim], Westerink, J.[Joyce], Sas, C.[Corina],
Applying Delaunay Triangulation Augmentation for Deep Learning Facial Expression Generation and Recognition,
FBE20(730-740).
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

Do, N.T., Nguyen-Quynh, T.T., Kim, S.H.,
Affective Expression Analysis in-the-wild using Multi-Task Temporal Statistical Deep Learning Model,
FG20(624-628)
IEEE DOI 2102
Face recognition, Emotion recognition, Training, Testing, Feature extraction, Faces, Annotations, ABAW Challenge 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

Rasipuram, S., Bhat, J.H., Maitra, A.,
Multi-modal Sequence-to-sequence Model for Continuous Affect Prediction in the Wild Using Deep 3D Features,
FG20(611-614)
IEEE DOI 2102
Feature extraction, Videos, Face recognition, Visualization, Databases, Emotion recognition, Training, affect recognition, multi modal anaysis 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

Bernheim, S., Arnaud, E., Dapogny, A.[Arnaud], Bailly, K.[Kevin],
MoDuL: Deep Modal and Dual Landmark-wise Gated Network for Facial Expression Recognition,
FG20(153-159)
IEEE DOI 2102
Logic gates, Feature extraction, Face recognition, Agriculture, Faces, Task analysis, Iron, Facial expression recognition, ensemble methods 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

Mavani, V., Raman, S., Miyapuram, K.P.,
Facial Expression Recognition Using Visual Saliency and Deep Learning,
CogCV17(2783-2788)
IEEE DOI 1802
Face recognition, Feature extraction, Machine learning, Testing, Training, Visualization 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

Liu, X.F.[Xiao-Feng], Kumar, B.V.K.V.[B.V.K. Vijaya], You, J.[Jane], Jia, P.[Ping],
Adaptive Deep Metric Learning for Identity-Aware Facial Expression Recognition,
Biometrics17(522-531)
IEEE DOI 1709
Face recognition, Feature extraction, Measurement, Optimization, Training 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

Ding, H., Zhou, S.K., Chellappa, R.,
FaceNet2ExpNet: Regularizing a Deep Face Recognition Net for Expression Recognition,
FG17(118-126)
IEEE DOI 1707
Convolution, Distribution functions, Face, Face recognition, Image recognition, Neurons, Training BibRef

Ghasemi, A., Baktashmotlagh, M., Denman, S., Sridharan, S., Tien, D.N., Fookes, C.,
Deep discovery of facial motions using a shallow embedding layer,
ICIP17(1567-1571)
IEEE DOI 1803
Feature extraction, Hidden Markov models, Kernel, Machine learning, Pain, Training BibRef

Ghasemi, A., Denman, S.[Simon], Sridharan, S.[Sridha], Fookes, C.[Clinton],
Discovery of facial motions using deep machine perception,
WACV16(1-7)
IEEE DOI 1606
Convolution 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

Karali, A.[Abubakrelsedik], Bassiouny, A.[Ahmad], El-Saban, M.[Motaz],
Facial expression recognition in the wild using rich deep features,
ICIP15(3442-3446)
IEEE DOI 1512
Facial expression recognition; deep neural networks features 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

Liu, P.[Ping], Han, S.Z.[Shi-Zhong], Meng, Z.[Zibo], Tong, Y.[Yan],
Facial Expression Recognition via a Boosted Deep Belief Network,
CVPR14(1805-1812)
IEEE DOI 1409
BibRef

Liu, P.[Ping], Zhou, J.T.Y.[Joey Tian-Yi], Tsang, I.W.H.[Ivor Wai-Hung], Meng, Z.[Zibo], Han, S.Z.[Shi-Zhong], Tong, Y.[Yan],
Feature Disentangling Machine: A Novel Approach of Feature Selection and Disentangling in Facial Expression Analysis,
ECCV14(IV: 151-166).
Springer DOI 1408
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

Li, W.[Wei], Li, M.[Min], Su, Z.[Zhong], Zhu, Z.G.[Zhi-Gang],
A Deep-Learning Approach to Facial Expression Recognition with Candid Images,
MVA15(279-282)
IEEE DOI 1507
Computational modeling BibRef

Jung, H.[Heechul], Lee, S.[Sihaeng], Yim, J., Park, S.[Sunjeong], Kim, J.[Junmo],
Joint Fine-Tuning in Deep Neural Networks for Facial Expression Recognition,
ICCV15(2983-2991)
IEEE DOI 1602
Databases BibRef

Jung, H.[Heechul], Lee, S.[Sihaeng], Park, S.[Sunjeong], Kim, B.J.[Byung-Ju], Kim, J.[Junmo], Lee, I.[Injae], Ahn, C.H.[Chung-Hyun],
Development of deep learning-based facial expression recognition system,
FCV15(1-4)
IEEE DOI 1506
Haar transforms 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

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
Sptatio-Temporal Analysis for Face Expression Recognition .


Last update:Mar 16, 2024 at 20:36:19