22.3.6.1.2 Deep Learning Facial Expression Recognition

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

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

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

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

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

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], 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

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

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

Lv, Y.L.[Yuan-Ling], Yan, Y.[Yan], Xue, J.H.[Jing-Hao], Chen, S.[Si], Wang, H.Z.[Han-Zi],
Relationship-Guided Knowledge Transfer for Class-Incremental Facial Expression Recognition,
IP(33), 2024, pp. 2293-2304.
IEEE DOI 2404
Compounds, Task analysis, Knowledge transfer, Representation learning, Feature extraction, Training, knowledge transfer 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

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

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

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
BibRef

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

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
BibRef

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
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

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

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

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

Jiang, P.[Ping], Liu, G.[Gang], Wang, Q.[Quan], Wu, J.[Jiang],
Accurate and Reliable Facial Expression Recognition Using Advanced Softmax Loss With Fixed Weights,
SPLetters(27), 2020, pp. 725-729.
IEEE DOI 2005
Deep learning, convolutional neural networks, softmax loss, multiclass imbalance, facial expression recognition BibRef

Xie, W.C.[Wei-Cheng], Shen, L.L.[Lin-Lin], Duan, J.M.[Jin-Ming],
Adaptive Weighting of Handcrafted Feature Losses for Facial Expression Recognition,
Cyber(51), No. 5, May 2021, pp. 2787-2800.
IEEE DOI 2104
Training, Databases, Face, Feature extraction, Loss measurement, Adaptive systems, Deep feature loss, expression recognition, loss adaptive weighting BibRef

Zeng, G., Zhou, J., Jia, X.[Xi], Xie, W.C.[Wei-Cheng], Shen, L.L.[Lin-Lin],
Hand-Crafted Feature Guided Deep Learning for Facial Expression Recognition,
FG18(423-430)
IEEE DOI 1806
Convolution, Face, Feature extraction, Loss measurement, Optimization, Training, deep metric learning, hand crafted feature BibRef

Xie, W.C.[Wei-Cheng], Wu, H.Q.[Hao-Qian], Tian, Y.[Yi], Bai, M.C.[Meng-Chao], Shen, L.L.[Lin-Lin],
Triplet Loss With Multistage Outlier Suppression and Class-Pair Margins for Facial Expression Recognition,
CirSysVideo(32), No. 2, February 2022, pp. 690-703.
IEEE DOI 2202
Training, Measurement, Faces, Loss measurement, Task analysis, Face recognition, Databases, Facial expression recognition, adaptive class-pair margin BibRef

Tian, Y.[Yi], Wen, Z.W.[Zhi-Wei], Xie, W.C.[Wei-Cheng], Zhang, X.[Xi], Shen, L.L.[Lin-Lin], Duan, J.M.[Jin-Ming],
Outlier-Suppressed Triplet Loss with Adaptive Class-Aware Margins for Facial Expression Recognition,
ICIP19(46-50)
IEEE DOI 1910
triplet loss, class-aware margin, outlier suppression, facial expression recognition BibRef

Xie, W.C.[Wei-Cheng], Chen, W.T.[Wen-Ting], Shen, L.L.[Lin-Lin], Duan, J.M.[Jin-Ming], Yang, M.[Meng],
Surrogate network-based sparseness hyper-parameter optimization for deep expression recognition,
PR(111), 2021, pp. 107701.
Elsevier DOI 2012
Expression recognition, Deep sparseness strategies, Hyper-parameter optimization, Surrogate network, Heuristic optimizer BibRef

Xie, W.C.[Wei-Cheng], Jia, X.[Xi], Shen, L.L.[Lin-Lin], Yang, M.[Meng],
Sparse deep feature learning for facial expression recognition,
PR(96), 2019, pp. 106966.
Elsevier DOI 1909
Expression recognition, Feature sparseness, Deep metric learning, Fine tuning, Generalization capability 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

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

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

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

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

Huang, W.[Wei], Zhang, S.Y.[Si-Yuan], Zhang, P.[Peng], Zha, Y.F.[Yu-Fei], Fang, Y.M.[Yu-Ming], Zhang, Y.N.[Yan-Ning],
Identity-Aware Facial Expression Recognition Via Deep Metric Learning Based on Synthesized Images,
MultMed(24), 2022, pp. 3327-3339.
IEEE DOI 2207
Task analysis, Measurement, Generative adversarial networks, Face recognition, Feature extraction, Image synthesis, metric learning 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

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

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

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

Liu, T.[Tong], Li, J.[Jing], Wu, J.[Jia], Du, B.[Bo], Chang, J.[Jun], Liu, Y.[Yi],
Facial Expression Recognition on the High Aggregation Subgraphs,
IP(32), 2023, pp. 3732-3745.
IEEE DOI 2307
Feature extraction, Convolutional neural networks, Face recognition, Task analysis, Deep learning, Visualization, relationship between expressions BibRef


Chang, D.[Di], Yin, Y.F.[Yu-Feng], Li, Z.[Zongjian], Tran, M.[Minh], Soleymani, M.[Mohammad],
LibreFace: An Open-Source Toolkit for Deep Facial Expression Analysis,
WACV24(8190-8200)
IEEE DOI Code:
WWW Link. 2404
Knowledge engineering, Human computer interaction, Deep learning, Gold, Analytical models, Visualization, Face recognition, Psychology and cognitive science BibRef

Oucherif, S.D.[Sabrine Djedjiga], Nawaf, M.M.[Mohamad Motasem], Boď, J.M.[Jean-Marc], Nicod, L.[Lionel], Merad, D.[Djamal], Dubuisson, S.[Séverine],
Facial Expression Recognition Using Light Field Cameras: A Comparative Study of Deep Learning Architectures,
ICIP23(3324-3328)
IEEE DOI 2312
BibRef

Liang, G.[Guang], Wang, S.F.[Shang-Fei], Wang, C.[Can],
Pose-Invariant Facial Expression Recognition,
FG21(01-08)
IEEE DOI 2303
Learning systems, Deep learning, Training, Databases, Face recognition, Pose estimation, Neural networks BibRef

Mathur, L.[Leena], Mataric, M.J.[Maja J],
Affect-Aware Deep Belief Network Representations for Multimodal Unsupervised Deception Detection,
FG21(1-8)
IEEE DOI 2303
Training, Visualization, Law, Psychology, Machine learning, Gesture recognition, Feature extraction BibRef

Huang, X.H.[Xiao-Hua],
Anchor-free face detection in the wild with an application to facial expression recognition,
ICIVC22(256-262)
IEEE DOI 2301
Location awareness, Emotion recognition, Image recognition, Databases, Face recognition, Semantics, Object detection, Deep Learning BibRef

Psaroudakis, A.[Andreas], Kollias, D.[Dimitrios],
MixAugment & Mixup: Augmentation Methods for Facial Expression Recognition,
ABAW22(2366-2374)
IEEE DOI 2210
Deep learning, Databases, Face recognition, Neural networks, Training data 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

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

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

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

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

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

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

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

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

Ekundayo, O.[Olufisayo], Viriri, S.[Serestina],
Facial Expression Recognition and Ordinal Intensity Estimation: A Multilabel Learning Approach,
ISVC20(II:581-592).
Springer DOI 2103
BibRef
Earlier:
Deep Forest Approach for Facial Expression Recognition,
PSIVT19(149-161).
Springer DOI 2003
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

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

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

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

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.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

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

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

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

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

Chapter on Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Sptatio-Temporal Analysis for Face Expression Recognition .


Last update:May 6, 2024 at 15:50:14