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Multi-Kernel Appearance Model,
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1306
Facial feature localization; Multiple-kernel learning;
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BibRef
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Facial Feature Tracking for Emotional Dynamic Analysis,
ACIVS11(495-506).
Springer DOI
1108
See also Combining AAM coefficients with LGBP histograms in the multi-kernel SVM framework to detect facial action units.
BibRef
Senechal, T.[Thibaud],
Bailly, K.[Kevin],
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Automatic Facial Action Detection Using Histogram Variation Between
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ICPR10(3752-3755).
IEEE DOI
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BibRef
Kim, D.H.[Dae Hoe],
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Multi-Objective Based Spatio-Temporal Feature Representation Learning
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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
Kim, H.I.[Hyung-Il],
Lee, S.H.[Seung Ho],
Ro, Y.M.[Yong Man],
Face image assessment learned with objective and relative face image
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ICIP15(4027-4031)
IEEE DOI
1512
BibRef
Earlier:
Adaptive feature extraction for blurred face images in facial
expression recognition,
ICIP14(5971-5975)
IEEE DOI
1502
Face recognition.
BibRef
Sariyanidi, E.[Evangelos],
Gunes, H.[Hatice],
Cavallaro, A.[Andrea],
Learning Bases of Activity for Facial Expression Recognition,
IP(26), No. 4, April 2017, pp. 1965-1978.
IEEE DOI
1704
Computational modeling
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Zhao, S.,
Yao, H.,
Gao, Y.,
Ji, R.,
Ding, G.,
Continuous Probability Distribution Prediction of Image Emotions via
Multitask Shared Sparse Regression,
MultMed(19), No. 3, March 2017, pp. 632-645.
IEEE DOI
1702
Distance measurement
BibRef
Zhao, S.,
Ding, G.,
Gao, Y.,
Zhao, X.,
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Yao, H.,
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Discrete Probability Distribution Prediction of Image Emotions with
Shared Sparse Learning,
AffCom(11), No. 4, October 2020, pp. 574-587.
IEEE DOI
2011
Visualization, Feature extraction, Probability distribution,
Training, Task analysis, Dictionaries, Learning systems,
multi-feature fusion
BibRef
Zhao, S.,
Yao, H.,
Gao, Y.,
Ding, G.,
Chua, T.,
Predicting Personalized Image Emotion Perceptions in Social Networks,
AffCom(9), No. 4, October 2018, pp. 526-540.
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1812
Feature extraction, Social network services, Visualization,
Bridges, Context, Meteorology, Clouds, Personalized image emotion,
heypergraph learning
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Xia, R.,
Liu, Y.,
A Multi-Task Learning Framework for Emotion Recognition Using 2D
Continuous Space,
AffCom(8), No. 1, January 2017, pp. 3-14.
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1703
Acoustics
BibRef
Wu, B.,
Jia, J.,
Yang, Y.,
Zhao, P.,
Tang, J.,
Tian, Q.,
Inferring Emotional Tags From Social Images With User Demographics,
MultMed(19), No. 7, July 2017, pp. 1670-1684.
IEEE DOI
1706
Computer science, Correlation, Feature extraction,
Learning systems, Social network services,
Support vector machines, Visualization, Emotion, image, user, demographics
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Ferrari, C.,
Lisanti, G.,
Berretti, S.[Stefano],
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A Dictionary Learning-Based 3D Morphable Shape Model,
MultMed(19), No. 12, December 2017, pp. 2666-2679.
IEEE DOI
1712
Face, Face recognition, Shape, Solid modeling,
Training. emotion recognition
BibRef
Li, X.,
Rao, Y.,
Xie, H.,
Lau, R.Y.K.,
Yin, J.,
Wang, F.L.,
Bootstrapping Social Emotion Classification with Semantically Rich
Hybrid Neural Networks,
AffCom(8), No. 4, October 2017, pp. 428-442.
IEEE DOI
1712
Computational modeling, Education, Encoding, Feature extraction,
Neural networks, Semantics, Unsupervised learning, transfer learning
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Liu, W.F.[Wei-Feng],
Zhang, L.[Lianbo],
Tao, D.P.[Da-Peng],
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Reinforcement online learning for emotion prediction by using
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PRL(107), 2018, pp. 123-130.
Elsevier DOI
1805
Emotion prediction, Reinforcement learning, Online learning,
Biometric surveillance
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Xu, B.,
Fu, Y.,
Jiang, Y.G.,
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Heterogeneous Knowledge Transfer in Video Emotion Recognition,
Attribution and Summarization,
AffCom(9), No. 2, April 2018, pp. 255-270.
IEEE DOI
1806
Emotion recognition, Feature extraction, Image recognition,
Knowledge transfer, Semantics, Training, Visualization, zero-shot learning
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Schuller, D.,
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The Age of Artificial Emotional Intelligence,
Computer(51), No. 9, September 2018, pp. 38-46.
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1810
Artificial intelligence, Emotion recognition, Machine learning,
Learning systems, Artificial Emotional Intelligence,
future of AI
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Recognition of Emotions in User-Generated Videos through Frame-Level
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MultMed(25), 2023, pp. 881-891.
IEEE DOI
2303
BibRef
Earlier:
Recognition of Emotions in User-Generated Videos With Kernelized
Features,
MultMed(20), No. 10, October 2018, pp. 2824-2835.
IEEE DOI
1810
Videos, Feature extraction, Emotion recognition, Task analysis,
Semantics, Adaptation models, Adversarial domain adaptation,
video emotion recognition.
discrete Fourier transforms,
feature extraction, image classification, image representation,
kernel method
BibRef
Zhang, Y.,
Qian, Y.,
Wu, D.,
Hossain, M.S.,
Ghoneim, A.,
Chen, M.,
Emotion-Aware Multimedia Systems Security,
MultMed(21), No. 3, March 2019, pp. 617-624.
IEEE DOI
1903
authorisation, cloud computing, data privacy, emotion recognition,
learning (artificial intelligence), multimedia systems,
social robot
BibRef
Wang, X.H.[Xiao-Hua],
Peng, M.[Muzi],
Pan, L.J.[Li-Juan],
Hu, M.[Min],
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Ren, F.[Fuji],
Two-level attention with two-stage multi-task learning for facial
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JVCIR(62), 2019, pp. 217-225.
Elsevier DOI
1908
BibRef
Earlier:
Two-Level Attention with Multi-task Learning for Facial Emotion
Estimation,
MMMod19(I:227-238).
Springer DOI
1901
Facial emotion recognition, Attention mechanism,
Multi-task learning, Valence-arousal dimension
BibRef
Yan, Y.X.[Yi-Xin],
Li, C.Y.[Chen-Yang],
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Canales, L.,
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Martínez-Barco, P.,
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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
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
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
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
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
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
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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
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
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
Karumbaiah, S.[Shamya],
Baker, R.S.[Ryan S.],
Ocumpaugh, J.[Jaclyn],
Andres, J.M.A.L.[Juliana Ma. Alexandra L.],
A Re-Analysis and Synthesis of Data on Affect Dynamics in Learning,
AffCom(14), No. 2, April 2023, pp. 1696-1710.
IEEE DOI
2306
Context modeling, Predictive models, Urban areas,
Analytical models, Statistics, Sociology, Affective computing,
modeling human emotion
BibRef
Bisogni, C.[Carmen],
Cimmino, L.[Lucia],
de Marsico, M.[Maria],
Hao, F.[Fei],
Narducci, F.[Fabio],
Emotion recognition at a distance: The robustness of machine learning
based on hand-crafted facial features vs deep learning models,
IVC(136), 2023, pp. 104724.
Elsevier DOI
2308
Emotion recognition, Facial expression,
Expression recognition at a distance, Deep learning, Mediapipe
BibRef
Zhang, T.Y.[Tian-Yi],
El Ali, A.[Abdallah],
Wang, C.[Chen],
Hanjalic, A.[Alan],
Cesar, P.[Pablo],
Weakly-Supervised Learning for Fine-Grained Emotion Recognition Using
Physiological Signals,
AffCom(14), No. 3, July 2023, pp. 2304-2322.
IEEE DOI
2310
BibRef
Bota, P.[Patrícia],
Zhang, T.Y.[Tian-Yi],
El Ali, A.[Abdallah],
Fred, A.[Ana],
da Silva, H.P.[Hugo Plácido],
Cesar, P.[Pablo],
Group Synchrony for Emotion Recognition Using Physiological Signals,
AffCom(14), No. 4, October 2023, pp. 2614-2625.
IEEE DOI
2312
BibRef
Zhang, T.Y.[Tian-Yi],
El Ali, A.[Abdallah],
Hanjalic, A.[Alan],
Cesar, P.[Pablo],
Few-Shot Learning for Fine-Grained Emotion Recognition Using
Physiological Signals,
MultMed(25), 2023, pp. 3773-3787.
IEEE DOI
2310
BibRef
Yang, K.[Kailai],
Zhang, T.[Tianlin],
Alhuzali, H.[Hassan],
Ananiadou, S.[Sophia],
Cluster-Level Contrastive Learning for Emotion Recognition in
Conversations,
AffCom(14), No. 4, October 2023, pp. 3269-3280.
IEEE DOI Code:
WWW Link.
2312
BibRef
Zhang, X.Q.[Xiao-Qin],
Li, M.[Min],
Lin, S.[Sheng],
Xu, H.[Hang],
Xiao, G.[Guobao],
Transformer-Based Multimodal Emotional Perception for Dynamic Facial
Expression Recognition in the Wild,
CirSysVideo(34), No. 5, May 2024, pp. 3192-3203.
IEEE DOI
2405
Feature extraction, Transformers, Face recognition,
Emotion recognition, Visualization, Data mining, deep learning
BibRef
Shi, G.[Ge],
Deng, S.[Sinuo],
Wang, B.[Bo],
Feng, C.[Chong],
Zhuang, Y.[Yan],
Wang, X.M.[Xiao-Mei],
One for All: A Unified Generative Framework for Image Emotion
Classification,
CirSysVideo(34), No. 8, August 2024, pp. 7057-7068.
IEEE DOI
2408
Task analysis, IEC, Emotion recognition, Semantics, Data models,
Adaptation models, Psychology, Pre-training model, multi-modal learning
BibRef
Tang, X.Y.[Xiao-Yu],
Feng, J.[Jiewen],
Huang, J.[Jinbo],
Xiang, Q.C.[Qiu-Chi],
Xue, B.H.[Bo-Huan],
A lightweight and continuous dimensional emotion analysis system of
facial expression recognition under complex background,
JVCIR(103), 2024, pp. 104260.
Elsevier DOI Code:
WWW Link.
2409
Artificial intelligence, Deep learning, Embedding system,
Facial expression recognition, Intelligent control
BibRef
Hosseini, I.[Iman],
Hossain, M.Z.[Md Zakir],
Zhang, Y.H.[Yu-Hao],
Rahman, S.[Shafin],
Deep learning model for simultaneous recognition of quantitative and
qualitative emotion using visual and bio-sensing data,
CVIU(248), 2024, pp. 104121.
Elsevier DOI Code:
WWW Link.
2409
Emotion recognition, Deep learning, Physiological signals,
End-to-end learning, Human facial expressions
BibRef
Su, X.X.[Xin-Xin],
Huang, Z.[Zhen],
Su, Y.X.[Yi-Xin],
Trisedya, B.D.[Bayu Distiawan],
Dou, Y.[Yong],
Zhao, Y.X.[Yun-Xiang],
Hierarchical Shared Encoder With Task-Specific Transformer Layer
Selection for Emotion-Cause Pair Extraction,
AffCom(15), No. 4, October 2024, pp. 1934-1948.
IEEE DOI
2412
Task analysis, Feature extraction, Emotion recognition, Benchmark testing,
Affective computing, Transformers, Tagging, BERT, joint learning
BibRef
Singh, G.[Gargi],
Brahma, D.[Dhanajit],
Rai, P.[Piyush],
Modi, A.[Ashutosh],
Text-Based Fine-Grained Emotion Prediction,
AffCom(15), No. 2, April 2024, pp. 405-416.
IEEE DOI
2406
Task analysis, Predictive models, Transformers,
Emotion recognition, Bit error rate, Transfer learning, transformers
BibRef
Ryumina, E.[Elena],
Ryumin, D.[Dmitry],
Axyonov, A.[Alexandr],
Ivanko, D.[Denis],
Karpov, A.[Alexey],
Multi-corpus emotion recognition method based on cross-modal gated
attention fusion,
PRL(190), 2025, pp. 192-200.
Elsevier DOI
2503
Multimodal emotion recognition, Encoders-decoder,
Context-independent features, Gated feature fusion, Affective computing
BibRef
Dresvyanskiy, D.[Denis],
Markitantov, M.[Maxim],
Yu, J.W.[Jia-Wei],
Kaya, H.[Heysem],
Karpov, A.[Alexey],
Multi-modal Arousal and Valence Estimation under Noisy Conditions,
ABAW24(4773-4783)
IEEE DOI
2410
Deep learning, Emotion recognition, Protocols, Estimation,
Transformers, Valence-Arousal Estimation,
BibRef
Chen, C.[Chuang],
Sun, X.[Xiao],
Liu, Z.[Zhi],
UniEmoX: Cross-Modal Semantic-Guided Large-Scale Pretraining for
Universal Scene Emotion Perception,
IP(34), 2025, pp. 4691-4705.
IEEE DOI Code:
WWW Link.
2508
Visualization, Training, Psychology, Feature extraction, Semantics,
Optimization, Data mining, Contrastive learning, Sun,
vision transformer
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Achlioptas, P.[Panos],
Ovsjanikov, M.[Maks],
Guibas, L.J.[Leonidas J.],
Tulyakov, S.[Sergey],
Affection: Learning Affective Explanations for Real-World Visual Data,
CVPR23(6641-6651)
IEEE DOI
2309
BibRef
Xue, F.L.[Fang-Lei],
Sun, Y.F.[Yi-Fan],
Yang, Y.[Yi],
Exploring Expression-related Self-supervised Learning and Spatial
Reserve Pooling for Affective Behaviour Analysis,
ABAW23(5701-5708)
IEEE DOI
2309
BibRef
Kollias, D.[Dimitrios],
ABAW: Learning from Synthetic Data & Multi-task Learning Challenges,
ABAWE22(157-172).
Springer DOI
2304
BibRef
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
BibRef
Min, S.[Seongjae],
Yang, J.[Junseok],
Lim, S.[Sejoon],
Emotion Recognition Using Transformers with Random Masking,
ABAW24(4860-4865)
IEEE DOI
2410
Deep learning, Emotion recognition, Gold, Computational modeling,
Estimation, Transformer cores
BibRef
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
BibRef
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
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
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
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
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, 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
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
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
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
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
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
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
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
Torres-Valencia, C.,
Alvarez-Meza, A.,
Orozco-Gutierrez, A.,
Emotion Assessment Using Adaptive Learning-Based Relevance Analysis,
ICIAR18(193-200).
Springer DOI
1807
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
Lai, Y.H.,
Lai, S.H.,
Emotion-Preserving Representation Learning via Generative Adversarial
Network for Multi-View Facial Expression Recognition,
FG18(263-270)
IEEE DOI
1806
Emotion recognition, Face, Face recognition, Feature extraction,
Generators, face frontalization,
pose variation
BibRef
Saxen, F.,
Werner, P.,
Al-Hamadi, A.,
Real vs. Fake Emotion Challenge: Learning to Rank Authenticity from
Facial Activity Descriptors,
EmotionComp17(3073-3078)
IEEE DOI
1802
Computational modeling, Estimation, Gold,
Support vector machines, Training, Videos
BibRef
Zhao, S.C.[Si-Cheng],
Yao, H.X.[Hong-Xun],
Jiang, X.L.[Xiao-Lei],
Sun, X.S.[Xiao-Shuai],
Predicting discrete probability distribution of image emotions,
ICIP15(2459-2463)
IEEE DOI
1512
Emotion Distribution Prediction; Image Emotion; Sparse Learning
BibRef
Acar, E.[Esra],
Hopfgartner, F.[Frank],
Albayrak, S.[Sahin],
Understanding Affective Content of Music Videos through Learned
Representations,
MMMod14(I: 303-314).
Springer DOI
1405
BibRef
Rojas Quiñones, M.[Mario],
Masip, D.[David],
Vitrià, J.[Jordi],
Predicting dominance judgements automatically:
A machine learning approach,
FG11(939-944).
IEEE DOI
1103
Facial features for social dominance estimation.
BibRef
Chang, K.Y.[Kai-Yueh],
Liu, T.L.[Tyng-Luh],
Lai, S.H.[Shang-Hong],
Learning partially-observed hidden conditional random fields for facial
expression recognition,
CVPR09(533-540).
IEEE DOI
0906
BibRef
Chapter on Face Recognition, Human Pose, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Emotion Recognition, Deep Learning .