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MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning
16 references·0 citing·36 second hop
MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learning (2023)MER 2023: Multi-label Learning, Modality …CTNet: Conversational Transformer Network for Emotion Recognition (2021)CTNet: Conversational Transfo…MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations (2019)MELD: A Multimodal Multi-Part…AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition (2019)AVEC 2019 Workshop and Challe…AVEC 2018 Workshop and Challenge (2018)AVEC 2018 Workshop and Challe…From individual to group-level emotion recognition: EmotiW 5.0 (2017)From individual to group-leve…AVEC 2017 (2017)AVEC 2017AVEC 2016 (2016)AVEC 2016Video and Image based Emotion Recognition Challenges in the Wild (2015)Video and Image based Emotion…Recurrent Neural Networks for Emotion Recognition in Video (2015)Recurrent Neural Networks for…EmoNets: Multimodal deep learning approaches for emotion recognition in video (2015)EmoNets: Multimodal deep lear…Emotion Recognition In The Wild Challenge 2014 (2014)Emotion Recognition In The Wi…AVEC 2014 (2014)AVEC 2014Emotion recognition in the wild challenge 2013 (2013)Emotion recognition in the wi…AVEC 2013 (2013)AVEC 2013AVEC 2011–The First International Audio/Visual Emotion Challenge (2011)AVEC 2011–The First Internati…IEMOCAP: interactive emotional dyadic motion capture database (2008)IEMOCAP: interactive emotiona…Collecting Large, Richly Annotated Facial-Expression Databases from Movies (2012)Automatic Analysis of Facial Actions: A Survey (2017)Extended deep neural network for facial emotion recognition (2019)Development of a Rating Scale for Primary Depressive Illness (1967)Comparison of Beck Depression Inventories-IA and-II in Psychiatric Outpatients (1996)Affective Computing (1997)EEG Based Emotion Recognition: A Tutorial and Review (2022)Coefficient Alpha and the Internal Structure of Tests (1951)The Hidden Dimension (1973)Speech emotion recognition using deep 1D & 2D CNN LSTM networks (2018)OpenEAR — Introducing the munich open-source emotion and affect recognition toolkit (2009)Combining modality specific deep neural networks for emotion recognition in video (2013)Hierarchical committee of deep convolutional neural networks for robust facial expression recognition (2016)Deep Learning for Human Affect Recognition: Insights and New Developments (2019)Intraclass correlations: Uses in assessing rater reliability. (1979)A Concordance Correlation Coefficient to Evaluate Reproducibility (1989)The PHQ-8 as a measure of current depression in the general population (2008)The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing (2015)Automated depression analysis using convolutional neural networks from speech (2018)Deep learning for depression recognition with audiovisual cues: A review (2021)MFCC-based Recurrent Neural Network for automatic clinical depression recognition and assessment from speech (2021)Measuring emotion: The self-assessment manikin and the semantic differential (1994)A review of affective computing: From unimodal analysis to multimodal fusion (2017)DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation (2019)COSMIC: COmmonSense knowledge for eMotion Identification in Conversations (2020)A systematic review on affective computing: emotion models, databases, and recent advances (2022)Mood, misattribution, and judgments of well-being: Informative and directive functions of affective states. (1983)Core affect and the psychological construction of emotion. (2003)Analysing Affective Behavior in the First ABAW 2020 Competition (2020)A multimodal fusion model with multi-level attention mechanism for depression detection (2022)CubeMLP: An MLP-based Model for Multimodal Sentiment Analysis and Depression Estimation (2022)Aff-Wild: Valence and Arousal ‘In-the-Wild’ Challenge (2017)Deep Affect Prediction in-the-Wild: Aff-Wild Database and Challenge, Deep Architectures, and Beyond (2019)Natural language processing applied to mental illness detection: a narrative review (2022)Multi-Objective Based Spatio-Temporal Feature Representation Learning Robust to Expression Intensity Variations for Facial Expression Recognition (2017)Emotion Recognition for Human-Robot Interaction: Recent Advances and Future Perspectives (2020)
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References

  • 2008IEMOCAP: interactive emotional dyadic motion capture database3,864 cited
  • 2019MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations1,413 cited
  • 2013AVEC 2013584 cited
  • 2016AVEC 2016505 cited
  • 2014AVEC 2014475 cited
  • 2015EmoNets: Multimodal deep learning approaches for emotion recognition in video413 cited
  • 2019AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition407 cited
  • 2015Recurrent Neural Networks for Emotion Recognition in Video386 cited
  • 2017AVEC 2017332 cited
  • 2015Video and Image based Emotion Recognition Challenges in the Wild305 cited
  • 2021CTNet: Conversational Transformer Network for Emotion Recognition299 cited
  • 2011AVEC 2011–The First International Audio/Visual Emotion Challenge271 cited
  • 2017From individual to group-level emotion recognition: EmotiW 5.0218 cited
  • 2014Emotion Recognition In The Wild Challenge 2014216 cited
  • 2013Emotion recognition in the wild challenge 2013179 cited
  • 2018AVEC 2018 Workshop and Challenge

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