21.3.6.2 Emotion Recognition from Face Images

Chapter Contents (Back)
Application, Faces. Faces, Emotions. Emotion Recognition.
See also Emotion Recognition, Deep Learning.
See also Emotion Recognition, Survey, General, Review, Datasets, Database.
See also Multi-Modal Emotion, Multimodal Emotion Recognition.
See also Personality, Traits, Mood, Deception, Diagnosis Analysis.
See also Emotion Recognition, Body Gestures, Body Language.
See also Face Expression Recognition and Analysis, Facial Expression Analysis, Facial Expressions.
See also Audio-Visual Emotion, Audiovisual Emotion Recognition. Synthesis:
See also Emotions in Face Animation, Video Face Synthesis.

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IEEE DOI 1706
Convergence, Emotion recognition, Face recognition, Feature extraction, Genetic algorithms, Optimization, Search problems, Ensemble classifier, facial expression recognition, feature selection, particle swarm optimization, (PSO) BibRef

Wu, B., Jia, J., Yang, Y., Zhao, P., Tang, J., Tian, Q.,
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Videos, Feature extraction, Emotion recognition, Task analysis, Visualization, Psychology, Computer architecture, machine vision BibRef

Joseph, A.[Allen], Geetha, P.,
Facial emotion detection using modified eyemap-mouthmap algorithm on an enhanced image and classification with tensorflow,
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Continuous, Real-Time Emotion Annotation: A Novel Joystick-Based Analysis Framework,
AffCom(11), No. 1, January 2020, pp. 78-84.
IEEE DOI 2003
Videos, Usability, Tools, Standards, Real-time systems, Support vector machines, Affective computing, pattern recognition BibRef

Liu, T., Wan, J., Dai, X., Liu, F., You, Q., Luo, J.,
Sentiment Recognition for Short Annotated GIFs Using Visual-Textual Fusion,
MultMed(22), No. 4, April 2020, pp. 1098-1110.
IEEE DOI 2004
Sentiment analysis, Visualization, Feature extraction, Streaming media, Semantics, Twitter, GIFs Sentiment, 3-D Convolution, Grid Searching BibRef

Wang, X.S.[Xu-Sheng], Chen, X.[Xing], Cao, C.J.[Cong-Jun],
Human emotion recognition by optimally fusing facial expression and speech feature,
SP:IC(84), 2020, pp. 115831.
Elsevier DOI 2004
Facial expression recognition, Speech emotion recognition, Bimodal fusion, Feature fusion, RNN BibRef

Haber, N., Voss, C., Wall, D.,
Making emotions transparent: Google Glass helps autistic kids understand facial expressions through augmented-reaiity therapy,
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IEEE DOI 2004
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Multi-level context extraction and attention-based contextual inter-modal fusion for multimodal sentiment analysis and emotion classification,
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Springer DOI 2005
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Varni, G., Hupont, I., Clavel, C., Chetouani, M.,
Computational Study of Primitive Emotional Contagion in Dyadic Interactions,
AffCom(11), No. 2, April 2020, pp. 258-271.
IEEE DOI 2006
Computational modeling, Mathematical model, Atmospheric measurements, Particle measurements, Synchronization, cross-recurrence quantification analysis BibRef

Mumenthaler, C., Sander, D., Manstead, A.S.R.,
Emotion Recognition in Simulated Social Interactions,
AffCom(11), No. 2, April 2020, pp. 308-312.
IEEE DOI 2006
Avatars, Emotion recognition, Face recognition, Cognitive processes, Emotion recognition, cognitive appraisal, social interaction BibRef

Canales, L., Strapparava, C., Boldrini, E., Martínez-Barco, P.,
Intensional Learning to Efficiently Build Up Automatically Annotated Emotion Corpora,
AffCom(11), No. 2, April 2020, pp. 335-347.
IEEE DOI 2006
Semantics, Standards, Computational modeling, Emotion recognition, Proposals, Reliability, Affective computing, corpora annotation, textual emotion recognition BibRef

Savakar, D.G.[Dayanand G.], Hosur, R.[Ravi],
The 3D Emotion Recognition Using SVM and HoG Features,
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Yu, L., Wang, J., Lai, K.R., Zhang, X.,
Pipelined Neural Networks for Phrase-Level Sentiment Intensity Prediction,
AffCom(11), No. 3, July 2020, pp. 447-458.
IEEE DOI 2008
Artificial neural networks, Predictive models, Switches, Learning systems, Linear regression, Prediction algorithms, neural network BibRef

Yi, Y.[Yun], Wang, H.L.[Han-Li], Li, Q.Y.[Qin-Yu],
Affective Video Content Analysis With Adaptive Fusion Recurrent Network,
MultMed(22), No. 9, September 2020, pp. 2454-2466.
IEEE DOI 2008
Adaptive systems, Correlation, Computer science, Motion pictures, Hidden Markov models, Support vector machines, Task analysis, multiple modalities BibRef

Steephen, J.E., Obbineni, S.C., Kummetha, S., Bapi, R.S.,
HED-ID: An Affective Adaptation Model Explaining the Intensity-Duration Relationship of Emotion,
AffCom(11), No. 4, October 2020, pp. 736-750.
IEEE DOI 2011
Affective adaptation, intensity and duration, modeling human emotion, region-ß paradox BibRef

Yannakakis, G.N., Cowie, R., Busso, C.,
The Ordinal Nature of Emotions: An Emerging Approach,
AffCom(12), No. 1, January 2021, pp. 16-35.
IEEE DOI 2103
Affective computing, Psychology, Reliability theory, Computational modeling, Task analysis, Tools, Emotion annotation, preference learning BibRef

Muszynski, M., Tian, L., Lai, C., Moore, J.D., Kostoulas, T., Lombardo, P., Pun, T., Chanel, G.,
Recognizing Induced Emotions of Movie Audiences from Multimodal Information,
AffCom(12), No. 1, January 2021, pp. 36-52.
IEEE DOI 2103
Motion pictures, Emotion recognition, Feature extraction, Physiology, Databases, Brain modeling, Analytical models, crowdsourcing BibRef

Kulkarni, K.[Kaustubh], Corneanu, C.A.[Ciprian Adrian], Ofodile, I.[Ikechukwu], Escalera, S.[Sergio], Baró, X.[Xavier], Hyniewska, S.[Sylwia], Allik, J.[Jüri], Anbarjafari, G.[Gholamreza],
Automatic Recognition of Facial Displays of Unfelt Emotions,
AffCom(12), No. 2, April 2021, pp. 377-390.
IEEE DOI 2106
Emotion recognition, Face recognition, Feature extraction, Face, Psychology, Observers, Trajectory, Affective computing, human behaviour analysis BibRef

Aylett, R.[Ruth], Ritter, C.[Christopher], Lim, M.Y.[Mei Yii], Broz, F.[Frank], McKenna, P.E.[Peter E.], Keller, I.[Ingo], Rajendran, G.[Gnanathusharan],
An Architecture for Emotional Facial Expressions as Social Signals,
AffCom(12), No. 2, April 2021, pp. 293-305.
IEEE DOI 2106
Appraisal, Computer architecture, Robots, Face, Games, Computational modeling, Mirrors, Intelligent agents, cognitive informatics BibRef

Ren, M.J.[Min-Jie], Huang, X.D.[Xiang-Dong], Shi, X.Q.[Xiao-Qi], Nie, W.Z.[Wei-Zhi],
Interactive Multimodal Attention Network for Emotion Recognition in Conversation,
SPLetters(28), 2021, pp. 1046-1050.
IEEE DOI 2106
Visualization, Solid modeling, Acoustics, Task analysis, Emotion recognition, Convolution, Context modeling, recurrent neural network BibRef

Mittal, T.[Trisha], Bera, A.[Aniket], Manocha, D.[Dinesh],
Multimodal and Context-Aware Emotion Perception Model With Multiplicative Fusion,
MultMedMag(28), No. 2, April 2021, pp. 67-75.
IEEE DOI 2107
Emotion recognition, Context modeling, Computational modeling, Semantics, Feature extraction, Measurement, Additives, Perceived Emotion BibRef

Mittal, T., Guhan, P., Bhattacharya, U., Chandra, R., Bera, A.[Aniket], Manocha, D.[Dinesh],
EmotiCon: Context-Aware Multimodal Emotion Recognition Using Frege's Principle,
CVPR20(14222-14231)
IEEE DOI 2008
Emotion recognition, Videos, Psychology, TV, Semantics, Databases, Benchmark testing BibRef

Wang, X.Z.[Xin-Zhi], Chang, Y.D.[Yu-Dong], Sugumaran, V.[Vijayan], Luo, X.F.[Xiang-Feng], Wang, P.[Peng], Zhang, H.[Hui],
Implicit Emotion Relationship Mining Based on Optimal and Majority Synthesis From Multimodal Data Prediction,
MultMedMag(28), No. 2, April 2021, pp. 96-105.
IEEE DOI 2107
Emotion recognition, Predictive models, Data models, Computational modeling, Psychology, Feature extraction, Brain modeling BibRef

Yin, G.H.[Guang-Hao], Sun, S.Q.[Shou-Qian], Zhang, H.[Hui], Yu, D.[Dian], Li, C.[Chao], Zhang, K.J.[Ke-Jun], Zou, N.[Ning],
User Independent Emotion Recognition with Residual Signal-Image Network,
ICIP19(3277-3281)
IEEE DOI 1910
Emotion Recognition, Multi-feature Fusion, Residual Signal Image Network BibRef

Li, H.Y.[Hang-Yu], Wang, N.N.[Nan-Nan], Yang, X.[Xi], Gao, X.B.[Xin-Bo],
CRS-CONT: A Well-Trained General Encoder for Facial Expression Analysis,
IP(31), 2022, pp. 4637-4650.
IEEE DOI 2207
Face recognition, Task analysis, Feature extraction, Training data, Training, Representation learning, Data mining, coarse-contrastive learning BibRef

Du, Z.Y.[Zheng-Yin], Wu, S.[Suowei], Huang, D.[Di], Li, W.X.[Wei-Xin], Wang, Y.H.[Yun-Hong],
Spatio-Temporal Encoder-Decoder Fully Convolutional Network for Video-Based Dimensional Emotion Recognition,
AffCom(12), No. 3, July 2021, pp. 565-578.
IEEE DOI 2109
Emotion recognition, Convolution, Decoding, Feature extraction, Videos, Visualization, Task analysis, temporal intermediate supervision BibRef

Li, W.X.[Wei-Xin], Dong, X.[Xuan], Wang, Y.H.[Yun-Hong],
Human Emotion Recognition With Relational Region-Level Analysis,
AffCom(14), No. 1, January 2023, pp. 650-663.
IEEE DOI 2303
Emotion recognition, Faces, Feature extraction, Face recognition, Semantics, Geometry, Target recognition, Human emotion recognition, emotion label dependency modeling BibRef

Fujii, K.[Katsuya], Sugimura, D.[Daisuke], Hamamoto, T.[Takayuki],
Hierarchical Group-Level Emotion Recognition,
MultMed(23), 2021, pp. 3892-3906.
IEEE DOI 2110
Emotion recognition, Faces, Facial features, Visualization, Semantics, Face recognition, Feature extraction, scene features BibRef

Pei, E.[Ercheng], Oveneke, M.C.[Meshia Cédric], Zhao, Y.[Yong], Jiang, D.M.[Dong-Mei], Sahli, H.[Hichem],
Monocular 3D Facial Expression Features for Continuous Affect Recognition,
MultMed(23), 2021, pp. 3540-3550.
IEEE DOI 2110
Face recognition, Feature extraction, Solid modeling, Emotion recognition, Optical imaging, Strain, continuous affect recognition BibRef

Wang, S.F.[Shang-Fei], Peng, G.Z.[Guo-Zhu], Zheng, Z.Q.[Zhuang-Qiang], Xu, Z.W.[Zhi-Wei],
Capturing Emotion Distribution for Multimedia Emotion Tagging,
AffCom(12), No. 4, October 2021, pp. 821-831.
IEEE DOI 2112
Tagging, Streaming media, Multimedia databases, Media, Computational modeling, Adversarial machine learning, joint label distribution BibRef

Ghosh, S.[Surjya], Ganguly, N.[Niloy], Mitra, B.[Bivas], De, P.[Pradipta],
Designing an Experience Sampling Method for Smartphone Based Emotion Detection,
AffCom(12), No. 4, October 2021, pp. 913-927.
IEEE DOI 2112
Smart phones, Behavioral sciences, Sensors, Time-frequency analysis, Mobile handsets, Sampling methods, emotion detection BibRef

Shirian, A.[Amir], Tripathi, S.[Subarna], Guha, T.[Tanaya],
Dynamic Emotion Modeling With Learnable Graphs and Graph Inception Network,
MultMed(24), 2022, pp. 780-790.
IEEE DOI 2202
Emotion recognition, Videos, Dynamics, Convolution, Databases, Task analysis, Speech recognition, Emotion recognition, inception network BibRef

Zhang, J.[Jing], Liu, X.Y.[Xin-Yu], Wang, Z.[Zhe], Yang, H.[Hai],
Graph-Based Object Semantic Refinement for Visual Emotion Recognition,
CirSysVideo(32), No. 5, May 2022, pp. 3036-3049.
IEEE DOI 2205
Visualization, Semantics, Feature extraction, Emotion recognition, Analytical models, Predictive models, Neural networks, visual emotion recognition BibRef

Ayari, N., Abdelkawy, H., Chibani, A., Amirat, Y.,
Hybrid Model-Based Emotion Contextual Recognition for Cognitive Assistance Services,
Cyber(52), No. 5, May 2022, pp. 3567-3576.
IEEE DOI 2206
Emotion recognition, Robots, Ontologies, Hidden Markov models, Cognition, Face recognition, Context modeling, ubiquitous robotics BibRef

Yang, J.Y.[Jing-Yuan], Li, J.[Jie], Li, L.[Leida], Wang, X.M.[Xiu-Mei], Ding, Y.X.[Yu-Xuan], Gao, X.B.[Xin-Bo],
Seeking Subjectivity in Visual Emotion Distribution Learning,
IP(31), 2022, pp. 5189-5202.
IEEE DOI 2208
Visualization, Appraisal, Psychology, Feature extraction, Task analysis, Prediction algorithms, Annotations, memory network BibRef

Heimerl, A.[Alexander], Weitz, K.[Katharina], Baur, T.[Tobias], André, E.[Elisabeth],
Unraveling ML Models of Emotion With NOVA: Multi-Level Explainable AI for Non-Experts,
AffCom(13), No. 3, July 2022, pp. 1155-1167.
IEEE DOI 2209
Annotations, Machine learning, Computational modeling, Tools, Predictive models, Data models, Databases, annotation tools BibRef

Dindar, M.[Muhterem], Järvelä, S.[Sanna], Ahola, S.[Sara], Huang, X.H.[Xiao-Hua], Zhao, G.Y.[Guo-Ying],
Leaders and Followers Identified by Emotional Mimicry During Collaborative Learning: A Facial Expression Recognition Study on Emotional Valence,
AffCom(13), No. 3, July 2022, pp. 1390-1400.
IEEE DOI 2209
Collaboration, Collaborative work, Task analysis, Emotion recognition, Face recognition, Leadership, multimodality BibRef

Xing, S.[Songlong], Mai, S.[Sijie], Hu, H.F.[Hai-Feng],
Adapted Dynamic Memory Network for Emotion Recognition in Conversation,
AffCom(13), No. 3, July 2022, pp. 1426-1439.
IEEE DOI 2209
Emotion recognition, Adaptation models, Task analysis, Computational modeling, Psychology, Convolution, Memory modules, multimodal feature fusion BibRef

Fu, Y.H.[Ya-Hui], Okada, S.[Shogo], Wang, L.[Longbiao], Guo, L.[Lili], Song, Y.[Yaodong], Liu, J.X.[Jia-Xing], Dang, J.[Jianwu],
Context- and Knowledge-Aware Graph Convolutional Network for Multimodal Emotion Recognition,
MultMedMag(29), No. 3, July 2022, pp. 91-100.
IEEE DOI 2209
Emotion recognition, Context modeling, Semantics, Oral communication, Knowledge based systems, Task analysis, Social networking (online) BibRef

Lo, L.[Ling], Xie, H.X.[Hong-Xia], Shuai, H.H.[Hong-Han], Cheng, W.H.[Wen-Huang],
Facial Chirality: From Visual Self-Reflection to Robust Facial Feature Learning,
MultMed(24), 2022, pp. 4275-4284.
IEEE DOI 2210
Faces, Feature extraction, Transformers, Reflection, Robustness, Facial features, Face recognition, Facial expression, vision transformer BibRef

Lazarou, I.[Ilias], Kesidis, A.L.[Anastasios L.], Hloupis, G.[George], Tsatsaris, A.[Andreas],
Panic Detection Using Machine Learning and Real-Time Biometric and Spatiotemporal Data,
IJGI(11), No. 11, 2022, pp. xx-yy.
DOI Link 2212
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Smith, G.M.[Geneva M.], Carette, J.[Jacques],
What Lies Beneath: A Survey of Affective Theory Use in Computational Models of Emotion,
AffCom(13), No. 4, October 2022, pp. 1793-1812.
IEEE DOI 2212
Emotion recognition, Training, Task analysis, Protocols, Mood, Brain modeling, Software, Affective computing, psychology BibRef

Xu, Y.F.[Yi-Fan], Cui, Y.[Yuqi], Jiang, X.[Xue], Yin, Y.J.[Ying-Jie], Ding, J.T.[Jing-Ting], Li, L.[Liang], Wu, D.[Dongrui],
Inconsistency-Based Multi-Task Cooperative Learning for Emotion Recognition,
AffCom(13), No. 4, October 2022, pp. 2017-2027.
IEEE DOI 2212
Task analysis, Multitasking, Estimation, Emotion recognition, Computational modeling, Speech recognition, Labeling, emotion recognition BibRef

Wang, Z.L.[Zi-Li], Lao, L.J.[Ling-Jie], Zhang, X.Y.[Xiao-Ya], Li, Y.[Yong], Zhang, T.[Tong], Cui, Z.[Zhen],
Context-dependent emotion recognition,
JVCIR(89), 2022, pp. 103679.
Elsevier DOI 2212
Context-based Emotion Recognition, Tubal Transformer, Hierarchical Fusion, Affective Computing BibRef

Yan, W.J.[Wen-Jing], Ruan, Q.N.[Qian-Nan], Fu, X.L.[Xiao-Lan], Sun, Y.Q.[Yu-Qi],
Perceived emotions and AU combinations in ambiguous facial expressions,
PRL(164), 2022, pp. 74-80.
Elsevier DOI 2212
Ambiguous facial expressions, Perceived emotion, Action unit (AU), Network analysis BibRef

Tan, X.H.[Xiao-Hui], Fan, Y.[Yachun], Sun, M.[Mingrui], Zhuang, M.[Meiqi], Qu, F.[Fangbing],
An emotion index estimation based on facial action unit prediction,
PRL(164), 2022, pp. 183-190.
Elsevier DOI 2212
Affective computing, Emotion index estimation, Facial action units prediction, Convolutional neutral network BibRef

Deng, J.[Jiawen], Ren, F.[Fuji],
Multi-Label Emotion Detection via Emotion-Specified Feature Extraction and Emotion Correlation Learning,
AffCom(14), No. 1, January 2023, pp. 475-486.
IEEE DOI 2303
Correlation, Feature extraction, Task analysis, Sentiment analysis, Emotion recognition, Context modeling, Multi-label, multi-label focal loss BibRef

Xu, Z.W.[Zhi-Wei], Wang, S.F.[Shang-Fei],
Emotional Attention Detection and Correlation Exploration for Image Emotion Distribution Learning,
AffCom(14), No. 1, January 2023, pp. 357-369.
IEEE DOI 2303
Feature extraction, Visualization, Semantics, Mathematical model, Task analysis, Prediction algorithms, Correlation, graph convolutional network BibRef

Kollias, D.[Dimitrios],
ABAW: Learning from Synthetic Data & Multi-task Learning Challenges,
ABAWE22(157-172).
Springer DOI 2304
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Sun, H.Y.[Hai-Yang], Lian, Z.[Zheng], Liu, B.[Bin], Tao, J.H.[Jian-Hua], Sun, L.[Licai], Cai, C.[Cong], He, Y.[Yu],
Two-aspect Information Interaction Model for ABAW4 Multi-task Challenge,
ABAWE22(173-180).
Springer DOI 2304
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Li, Y.[Yifan], Sun, H.[Haomiao], Liu, Z.[Zhaori], Han, H.[Hu], Shan, S.G.[Shi-Guang],
Affective Behaviour Analysis Using Pretrained Model with Facial Prior,
ABAWE22(19-30).
Springer DOI 2304
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Zhang, T.G.[Teng-Gan], Liu, C.H.[Chuan-He], Liu, X.L.[Xiao-Long], Liu, Y.C.[Yu-Chen], Meng, L.[Liyu], Sun, L.[Lei], Jiang, W.Q.[Wen-Qiang], Zhang, F.Y.[Feng-Yuan], Zhao, J.M.[Jin-Ming], Jin, Q.[Qin],
Multi-task Learning Framework for Emotion Recognition In-the-wild,
ABAWE22(143-156).
Springer DOI 2304
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Mittel, A.[Akshita], Tripathi, S.[Shashank],
Peri: Part Aware Emotion Recognition in the Wild,
ABAWE22(76-92).
Springer DOI 2304
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Lee, H.[Hyungjun], Lim, H.[Hwangyu], Lim, S.[Sejoon],
Byel: Bootstrap Your Emotion Latent,
ABAWE22(121-131).
Springer DOI 2304
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Savchenko, A.V.[Andrey V.],
MT-emotieffnet for Multi-task Human Affective Behavior Analysis and Learning from Synthetic Data,
ABAWE22(45-59).
Springer DOI 2304
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Gera, D.[Darshan], Kumar, B.V.R.[Bobbili Veerendra Raj], Badveeti, N.S.K.[Naveen Siva Kumar], Balasubramanian, S.,
Facial Affect Recognition Using Semi-supervised Learning with Adaptive Threshold,
ABAWE22(31-44).
Springer DOI 2304
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Shahabinejad, M.[Mostafa], Wang, Y.[Yang], Yu, Y.H.[Yuan-Hao], Tang, J.[Jin], Li, J.[Jiani],
Toward Personalized Emotion Recognition: A Face Recognition Based Attention Method for Facial Emotion Recognition,
FG21(1-5)
IEEE DOI 2303
Emotion recognition, Face recognition, Gesture recognition, Convolutional neural networks, Task analysis BibRef

Pikoulis, I.[Ioannis], Filntisis, P.P.[Panagiotis P.], Maragos, P.[Petros],
Leveraging Semantic Scene Characteristics and Multi-Stream Convolutional Architectures in a Contextual Approach for Video-Based Visual Emotion Recognition in the Wild,
FG21(01-08)
IEEE DOI 2303
Emotion recognition, Visualization, Motion segmentation, Semantics, Lighting, Gesture recognition, Feature extraction BibRef

Madapana, N.[Naveen], Wachs, J.[Juan],
ZF-SSE: A Unified Sequential Semantic Encoder for Zero-Few-Shot Learning,
FG21(1-8)
IEEE DOI 2303
Learning systems, Emotion recognition, Face recognition, Semantics, Gesture recognition, Object recognition BibRef

Jegorova, M.[Marija], Petridis, S.[Stavros], Pantic, M.[Maja],
SS-VAERR: Self-Supervised Apparent Emotional Reaction Recognition from Video,
FG23(1-8)
IEEE DOI 2303
Emotion recognition, Annotations, Face recognition, Self-supervised learning, Gesture recognition, Task analysis BibRef

Jia, G.[Guoli], Yang, J.F.[Ju-Feng],
S2-VER: Semi-supervised Visual Emotion Recognition,
ECCV22(XXXVII:493-509).
Springer DOI 2211
BibRef

Yang, D.K.[Ding-Kang], Huang, S.[Shuai], Wang, S.L.[Shun-Li], Liu, Y.[Yang], Zhai, P.[Peng], Su, L.Z.[Liu-Zhen], Li, M.C.[Ming-Cheng], Zhang, L.H.[Li-Hua],
Emotion Recognition for Multiple Context Awareness,
ECCV22(XXXVII:144-162).
Springer DOI 2211
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Kim, D.[Daeha], Song, B.C.[Byung Cheol],
Emotion-aware Multi-view Contrastive Learning for Facial Emotion Recognition,
ECCV22(XIII:178-195).
Springer DOI 2211
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Bishay, M.[Mina], Turcot, J.[Jay], Page, G.[Graham], Mavadati, M.[Mohammad],
Automatic Detection of Sentimentality from Facial Expressions,
ICIP22(321-325)
IEEE DOI 2211
Training, Measurement, Gold, Emotion recognition, Multilayer perceptrons, Feature extraction, Sentimentality, Ad-level KPIs BibRef

Meng, L.[Liyu], Liu, Y.C.[Yu-Chen], Liu, X.L.[Xiao-Long], Huang, Z.P.[Zhao-Pei], Jiang, W.Q.[Wen-Qiang], Zhang, T.G.[Teng-Gan], Liu, C.[Chuanhe], Jin, Q.[Qin],
Valence and Arousal Estimation based on Multimodal Temporal-Aware Features for Videos in the Wild,
ABAW22(2344-2351)
IEEE DOI 2210
Correlation coefficient, Visualization, Smoothing methods, Fuses, Estimation, Predictive models, Transformers BibRef

Surabhi, S.[Saimourya], Shah, B.[Bhavik], Washington, P.[Peter], Mutlu, O.C.[Onur Cezmi], Leblanc, E.[Emilie], Mohite, P.[Prathamesh], Husic, A.[Arman], Kline, A.[Aaron], Dunlap, K.[Kaitlyn], McNealis, M.[Maya], Liu, B.[Bennett], Deveaux, N.[Nick], Sleiman, E.[Essam], Wall, D.P.[Dennis P.],
TikTok for good: Creating a diverse emotion expression database,
ABAW22(2495-2505)
IEEE DOI 2210
Bridges, Emotion recognition, Databases, Social networking (online), Face recognition BibRef

Deng, D.[Didan], Shi, B.E.[Bertram E.],
Estimating Multiple Emotion Descriptors by Separating Description and Inference,
ABAW22(2391-2399)
IEEE DOI 2210
Space vehicles, Representation learning, Visualization, Emotion recognition, Gold, Face recognition, Psychology BibRef

Stratton, D.[Derek], Hand, E.[Emily],
Bridging the Gap Between Automated and Human Facial Emotion Perception,
ABAW22(2400-2410)
IEEE DOI 2210
Emotion recognition, Uncertainty, Sociology, Psychology, Natural language processing BibRef

Ouzar, Y.[Yassine], Bousefsaf, F.[Frédéric], Djeldjli, D.[Djamaleddine], Maaoui, C.[Choubeila],
Video-based multimodal spontaneous emotion recognition using facial expressions and physiological signals,
ABAW22(2459-2468)
IEEE DOI 2210
Emotion recognition, Face recognition, Photoplethysmography, Feature extraction, Physiology, Spatiotemporal phenomena BibRef

Xu, L.W.[Li-Wen], Wang, Z.T.[Zheng-Tao], Wu, B.[Bin], Lui, S.[Simon],
MDAN: Multi-level Dependent Attention Network for Visual Emotion Analysis,
CVPR22(9469-9478)
IEEE DOI 2210
Bridges, Visualization, Correlation, Computational modeling, Semantics, Benchmark testing, Recognition: detection, retrieval BibRef

Pereira, L.[Lara], Brás, S.[Susana], Sebastião, R.[Raquel],
Characterization of Emotions Through Facial Electromyogram Signals,
IbPRIA22(230-241).
Springer DOI 2205
BibRef

Jia, M.L.[Meng-Lin], Wu, Z.[Zuxuan], Reiter, A.[Austin], Cardie, C.[Claire], Belongie, S.[Serge], Lim, S.N.[Ser-Nam],
Exploring Visual Engagement Signals for Representation Learning,
ICCV21(4186-4197)
IEEE DOI 2203
Representation learning, Visualization, Emotion recognition, Social networking (online), Computational modeling, Vision + language BibRef

Vonikakis, V.[Vassilios], Dexter, N.Y.R.[Neo Yuan Rong], Winkler, S.[Stefan],
Morphset: Augmenting Categorical Emotion Datasets With Dimensional Affect Labels Using Face Morphing,
ICIP21(2713-2717)
IEEE DOI 2201
Emotion recognition, Annotations, Face recognition, Image processing, Computational modeling, Supervised learning BibRef

Sanchez, E.[Enrique], Tellamekala, M.K.[Mani Kumar], Valstar, M.[Michel], Tzimiropoulos, G.[Georgios],
Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognition,
CVPR21(9070-9080)
IEEE DOI 2111
Emotion recognition, Uncertainty, Face recognition, Supervised learning, Stochastic processes, Estimation, Predictive models BibRef

Yang, J.Y.[Jing-Yuan], Li, J.[Jie], Li, L.[Leida], Wang, X.M.[Xiu-Mei], Gao, X.B.[Xin-Bo],
A Circular-Structured Representation for Visual Emotion Distribution Learning,
CVPR21(4235-4244)
IEEE DOI 2111
Visualization, Social networking (online), Psychology, Pattern recognition, Task analysis BibRef

d'Apolito, S.[Stefano], Paudel, D.P.[Danda Pani], Huang, Z.W.[Zhi-Wu], Romero, A.[Andrés], Van Gool, L.J.[Luc J.],
GANmut: Learning Interpretable Conditional Space for Gamut of Emotions,
CVPR21(568-577)
IEEE DOI 2111
Training, Image synthesis, Computational modeling, Aerospace electronics, Search problems, Pattern recognition BibRef

González-Meneses, Y.N.[Yesenia N.], Guerrero-García, J.[Josefina], Reyes-García, C.A.[Carlos Alberto], Zatarain-Cabada, R.[Ramón],
Automatic Recognition of Learning-Centered Emotions,
MCPR21(33-43).
Springer DOI 2108
BibRef

Zhang, S.W.[Si-Wei], Huang, Z.W.[Zhi-Wu], Paudel, D.P.[Danda Pani], Van Gool, L.J.[Luc J.],
Facial Emotion Recognition with Noisy Multi-task Annotations,
WACV21(21-31)
IEEE DOI 2106
Emotion recognition, Correlation, Annotations, Games, Encoding BibRef

Diamantini, C.[Claudia], Mircoli, A.[Alex], Potena, D.[Domenico], Storti, E.[Emanuele],
Automatic Annotation of Corpora For Emotion Recognition Through Facial Expressions Analysis,
ICPR21(5650-5657)
IEEE DOI 2105
Emotion recognition, Sentiment analysis, Gold, Machine learning algorithms, Annotations, dataset for sentiment analysis BibRef

Kolling, C.[Camila], Araujo, V.[Victor], Barros, R.C.[Rodrigo C.], Musse, S.R.[Soraia Raupp],
How Does Computer Animation Affect Our Perception of Emotions in Video Summarization?,
ISVC20(II:374-385).
Springer DOI 2103
BibRef

Shehu, H.A.[Harisu Abdullahi], Browne, W.[Will], Eisenbarth, H.[Hedwig],
Emotion Categorization from Video-frame Images Using a Novel Sequential Voting Technique,
ISVC20(II:618-632).
Springer DOI 2103
BibRef

Savchenko, A.V.[Andrey V.],
Video-based Frame-level Facial Analysis of Affective Behavior on Mobile Devices using EfficientNets,
ABAW22(2358-2365)
IEEE DOI 2210
Emotion recognition, Analytical models, Computational modeling, Multitasking, Feature extraction, Real-time systems, Mobile handsets BibRef

Demochkina, P.[Polina], Savchenko, A.V.[Andrey V.],
Mobileemotiface: Efficient Facial Image Representations in Video-based Emotion Recognition on Mobile Devices,
IMTA20(266-274).
Springer DOI 2103
BibRef

Haddad, J.[Jad], Lezoray, O.[Olivier], Hamel, P.[Philippe],
3D-CNN for Facial Emotion Recognition in Videos,
ISVC20(II:298-309).
Springer DOI 2103
BibRef

Kota, V., Gali, G.M., Nwogu, I.,
A Computational View of the Emotional Regulation of Disgust using Multimodal Sensors,
FG20(567-571)
IEEE DOI 2102
biomechanics, cognition, electrocardiography, electromyography, emotion recognition, face recognition, medical signal processing, disgust emotion BibRef

Happy, S., Dantcheva, A., Bremond, F.,
Semi-supervised Emotion Recognition using Inconsistently Annotated Data,
FG20(286-293)
IEEE DOI 2102
Data models, Adaptation models, Training, Predictive models, Noise measurement, Face recognition, Emotion recognition BibRef

Zhang, Z., Yi, M., Xu, J., Zhang, R., Shen, J.,
Two-stage Recognition and Beyond for Compound Facial Emotion Recognition,
FG20(900-904)
IEEE DOI 2102
Gesture recognition, Face recognition, emotion recognition BibRef

Luo, Z., Zhang, Z.,
Challenge report: Compound Emotion challenge,
FG20(905-907)
IEEE DOI 2102
Training, Gesture recognition, Face recognition BibRef

Wei, G., Jian, L., Mo, S.,
Multimodal(Audio, Facial and Gesture) based Emotion Recognition challenge,
FG20(908-911)
IEEE DOI 2102
Emotion recognition, Feature extraction, Face recognition, Data models, Hidden Markov models, Image recognition BibRef

Viegas, C.,
Two Stage Emotion Recognition using Frame-level and Video-level Features,
FG20(912-915)
IEEE DOI 2102
Support vector machines, Radio frequency, Feature extraction, Emotion recognition, Training, emotion recognition BibRef

Deng, D., Chen, Z., Shi, B.E.,
Multitask Emotion Recognition with Incomplete Labels,
FG20(592-599)
IEEE DOI 2102
Task analysis, Gold, Estimation, Training, Emotion recognition, Feature extraction, Correlation, Emotion Recognition, Incomplete Label BibRef

Happy, S.L., Dantcheva, A., Das, A., Bremond, F., Zeghari, R., Robert, P.,
Apathy Classification by Exploiting Task Relatedness,
FG20(489-494)
IEEE DOI 2102
Task analysis, Videos, Face recognition, Histograms, Feature extraction, Emotional responses, Visualization, task relatedness BibRef

Liu, J., Foged, I.W., Moeslund, T.B.,
Vision-based Individual Factors Acquisition for Thermal Comfort Assessment in a Built Environment,
FG20(662-666)
IEEE DOI 2102
Videos, Temperature measurement, Training, Optical imaging, Skin, HVAC, Thermometers BibRef

Kollias, D., Schulc, A., Hajiyev, E., Zafeiriou, S.,
Analysing Affective Behavior in the First ABAW 2020 Competition,
FG20(637-643)
IEEE DOI 2102
Videos, Annotations, Gold, Databases, Training, Task analysis, Face recognition, valence, arousal, basic expressions, action units, mobilenet BibRef

Kuhnke, F., Rumberg, L., Ostermann, J.[Jörn],
Two-Stream Aural-Visual Affect Analysis in the Wild,
FG20(600-605)
IEEE DOI 2102
Videos, Training, Task analysis, Visualization, Streaming media, Face recognition, expression recognition, action units, emotion recognition BibRef

Lei, S., Stefanov, K., Gratch, J.,
Emotion or expressivity? An automated analysis of nonverbal perception in a social dilemma,
FG20(544-551)
IEEE DOI 2102
Videos, Observers, Face recognition, Games, Tools, Standards, Protocols BibRef

Li, B.H.[Bing-Hua], Li, C.[Chao], Duan, F.[Feng], Zheng, N.[Ning], Zhao, Q.B.[Qi-Bin],
TPFN: Applying Outer Product Along Time to Multimodal Sentiment Analysis Fusion on Incomplete Data,
ECCV20(XXIV:431-447).
Springer DOI 2012
BibRef

Lim, L., Khor, H.Q., Chaemchoy, P., See, J., Wong, L.K.,
Where Is The Emotion? Dissecting A Multi-Gap Network For Image Emotion Classification,
ICIP20(1886-1890)
IEEE DOI 2011
Feature extraction, Visualization, Neural networks, Streaming media, Emotion recognition, Psychology, Robustness, class activation maps BibRef

Chouhayebi, H., Riffi, J., Mahraz, M.A., Yahyaouy, A., Tairi, H., Alioua, N.,
Facial expression recognition based on geometric features,
ISCV20(1-6)
IEEE DOI 2011
emotion recognition, face recognition, feature extraction, image classification, support vector machines, diverse emotions, SVM BibRef

He, G., Liu, X., Fan, F., You, J.,
Image2Audio: Facilitating Semi-supervised Audio Emotion Recognition with Facial Expression Image,
VL3W20(3978-3983)
IEEE DOI 2008
Spectrogram, Training, Emotion recognition, Reliability, Visualization, Face recognition BibRef

Kossaifi, J., Toisoul, A., Bulat, A., Panagakis, Y., Hospedales, T.M., Pantic, M.,
Factorized Higher-Order CNNs With an Application to Spatio-Temporal Emotion Estimation,
CVPR20(6059-6068)
IEEE DOI 2008
Tensile stress, Kernel, Estimation, Training, Videos, Neural networks BibRef

Wei, Z., Zhang, J., Lin, Z., Lee, J., Balasubramanian, N., Hoai, M., Samaras, D.,
Learning Visual Emotion Representations From Web Data,
CVPR20(13103-13112)
IEEE DOI 2008
Visualization, Feature extraction, Emotion recognition, Task analysis, Taxonomy, Training, Noise measurement BibRef

Zhan, C., She, D., Zhao, S., Cheng, M., Yang, J.,
Zero-Shot Emotion Recognition via Affective Structural Embedding,
ICCV19(1151-1160)
IEEE DOI 2004
emotion recognition, feature extraction, learning (artificial intelligence), psychology, BibRef

Zheng, R.L.[Ruo-Lin], Li, W.X.[Wei-Xin], Wang, Y.H.[Yun-Hong],
Visual Sentiment Analysis by Leveraging Local Regions and Human Faces,
MMMod20(I:303-314).
Springer DOI 2003
BibRef

Mo, S.[Siyi], Yang, W.M.[Wen-Ming], Wang, G.J.[Gui-Jin], Liao, Q.M.[Qing-Min],
Emotion Recognition with Facial Landmark Heatmaps,
MMMod20(I:278-289).
Springer DOI 2003
BibRef

Jia, X.[Xiuyi], Zheng, X.[Xiang], Li, W.W.[Wei-Wei], Zhang, C.Q.[Chang-Qing], Li, Z.C.[Ze-Chao],
Facial Emotion Distribution Learning by Exploiting Low-Rank Label Correlations Locally,
CVPR19(9833-9842).
IEEE DOI 2002
BibRef

Moroto, Y., Maeda, K., Ogawa, T., Haseyama, M.,
Estimation of Emotion Labels via Tensor-Based Spatiotemporal Visual Attention Analysis,
ICIP19(4105-4109)
IEEE DOI 1910
Emotion estimation, eye gaze, spatiotemporal visual attention analysis, tensor analysis BibRef

Li, Y.Y.[Yan-Ying], Cheng, H.J.[Hsin-Jung], Liu, Y.[Yen], Shen, C.T.[Chih-Tsung],
Edge-Computing Convolutional Neural Network with Homography-Augmented Data for Facial Emotion Recognition,
ICIP19(3287-3291)
IEEE DOI 1910
Face Recognition, Convolutional Neural Network, ASIC, VPU BibRef

Wang, C., Zeng, J., Shan, S., Chen, X.,
Multi-Task Learning of Emotion Recognition and Facial Action Unit Detection with Adaptively Weights Sharing Network,
ICIP19(56-60)
IEEE DOI 1910
facial expression recognition, emotion classification, facial action unit detection, multi-task learning BibRef

Pandey, R.K.[Ram Krishna], Karmakar, S.[Souvik], Ramakrishnan, A.G., Saha, N.,
Improving Facial Emotion Recognition Systems with Crucial Feature Extractors,
CIAP19(I:268-279).
Springer DOI 1909
BibRef

Aminbeidokhti, M.[Masih], Pedersoli, M.[Marco], Cardinal, P.[Patrick], Granger, E.[Eric],
Emotion Recognition with Spatial Attention and Temporal Softmax Pooling,
ICIAR19(I:323-331).
Springer DOI 1909
BibRef

Aly, S.F.[Sherin F.], Abbott, A.L.[A. Lynn],
Facial Emotion Recognition with Varying Poses and/or Partial Occlusion Using Multi-stage Progressive Transfer Learning,
SCIA19(101-112).
Springer DOI 1906
BibRef

Zhu, X.L.[Xue-Lin], Cao, B.W.[Bi-Wei], Xu, S.[Shuai], Liu, B.[Bo], Cao, J.X.[Jiu-Xin],
Joint Visual-Textual Sentiment Analysis Based on Cross-Modality Attention Mechanism,
MMMod19(I:264-276).
Springer DOI 1901
BibRef

Gonzalez-Diaz, R.[Rocio], Paluzo-Hidalgo, E.[Eduardo], Quesada, J.F.[José F.],
Towards Emotion Recognition: A Persistent Entropy Application,
CTIC19(96-109).
Springer DOI 1901
BibRef

Nguyen, D., Nguyen, K., Sridharan, S., Abbasnejad, I., Dean, D., Fookes, C.,
Meta Transfer Learning for Facial Emotion Recognition,
ICPR18(3543-3548)
IEEE DOI 1812
Task analysis, Emotion recognition, Face recognition, Feature extraction, Face, Computer architecture BibRef

Kumar, R.K., Garain, J., Kisku, D.R., Sanyal, G.,
Estimating Attention of Faces Due to its Growing Level of Emotions,
Cognitive18(2033-20338)
IEEE DOI 1812
Feature extraction, Training, Databases, Task analysis, Visualization, Convolution, Testing BibRef

Xu, J., Dong, Y., Ma, L., Bai, H.,
Video-based Emotion Recognition using Aggregated Features and Spatio-temporal Information,
ICPR18(2833-2838)
IEEE DOI 1812
Feature extraction, Videos, Emotion recognition, Task analysis, Face recognition, Face BibRef

Tautkute, I., Trzcinski, T., Bielski, A.,
I Know How You Feel: Emotion Recognition with Facial Landmarks,
WiCV18(1959-19592)
IEEE DOI 1812
Emotion recognition, Task analysis, Face, Face recognition, Convolutional neural networks, Databases BibRef

Yagis, E.[Ekin], Unel, M.[Mustafa],
Facial Expression Based Emotion Recognition Using Neural Networks,
ICIAR18(210-217).
Springer DOI 1807
BibRef

Abuhammad, H.[Huthaifa], Everson, R.[Richard],
Emotional Faces in the Wild: Feature Descriptors for Emotion Classification,
ICIAR18(164-174).
Springer DOI 1807
BibRef

Torres-Valencia, C., Alvarez-Meza, A., Orozco-Gutierrez, A.,
Emotion Assessment Using Adaptive Learning-Based Relevance Analysis,
ICIAR18(193-200).
Springer DOI 1807
BibRef

Gaus, Y.F.A., Meng, H.,
Linear and Non-Linear Multimodal Fusion for Continuous Affect Estimation In-the-Wild,
FG18(492-498)
IEEE DOI 1806
Correlation, Emotion recognition, Estimation, Feature extraction, Linear regression, Mathematical model, Predictive models, affect, non-linear BibRef

Sokolov, D., Patkin, M.,
Real-Time Emotion Recognition on Mobile Devices,
FG18(787-787)
IEEE DOI 1806
Emotion recognition, Face recognition, Feature extraction, Machine learning, Mobile handsets, Neural networks, mobile devices BibRef

Shamsi, S.N., Singh, B.P., Wadhwa, M.,
Group Affect Prediction Using Multimodal Distributions,
Assist18(77-83)
IEEE DOI 1806
convolution, emotion recognition, feature extraction, feedforward neural nets, object detection, CNN model, Training BibRef