mlsanityData to 14 Oct 2026

AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition

arXiv 1907.11510 ↗First posted 10 Jul 2019cs.HC cs.CV cs.IRcited by 87

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Abstract (arXiv)

The Audio/Visual Emotion Challenge and Workshop (AVEC 2019) "State-of-Mind, Detecting Depression with AI, and Cross-cultural Affect Recognition" is the ninth competition event aimed at the comparison of multimedia processing and machine learning methods for automatic audiovisual health and emotion analysis, with all participants competing strictly under the same conditions. The goal of the Challenge is to provide a common benchmark test set for multimodal information processing and to bring together the health and emotion recognition communities, as well as the audiovisual processing communities, to compare the relative merits of various approaches to health and emotion recognition from real-life data. This paper presents the major novelties introduced this year, the challenge guidelines, the data used, and the performance of the baseline systems on the three proposed tasks: state-of-mind recognition, depression assessment with AI, and cross-cultural affect sensing, respectively.

Key facts. Cited by 87 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Jul 2019.

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Citing papers per year: 2021: 10; 2022: 15; 2023: 6; 2024: 22; 2025: 17; 2026: 17.

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  1. 2021Analysing Affective Behavior in the second ABAW2 Competitioncited by 163
  2. 2022CubeMLP: An MLP-based Model for Multimodal Sentiment Analysis and Depression Estimationcited by 40
  3. 2023MER 2023: Multi-label Learning, Modality Robustness, and Semi-Supervised Learningcited by 33
  4. 2022COLD Fusion: Calibrated and Ordinal Latent Distribution Fusion for Uncertainty-Aware Multimodal Emotion Recognitioncited by 22
  5. 2022Continuous Emotion Recognition using Visual-audio-linguistic information: A Technical Report for ABAW3cited by 20
  6. 2021Affective Processes: stochastic modelling of temporal context for emotion and facial expression recognitioncited by 16
  7. 2021Continuous Emotion Recognition with Audio-visual Leader-follower Attentive Fusioncited by 15
  8. 2021Graph-based Facial Affect Analysis: A Reviewcited by 14
  9. 2024DepMamba: Progressive Fusion Mamba for Multimodal Depression Detectioncited by 14
  10. 2022GRATIS: Deep Learning Graph Representation with Task-specific Topology and Multi-dimensional Edge Featurescited by 12
  11. 2024HiQuE: Hierarchical Question Embedding Network for Multimodal Depression Detectioncited by 12
  12. 2024Explainable Artificial Intelligence for Medical Applications: A Reviewcited by 12
38 more
  1. 2024Reading Between the Frames: Multi-Modal Depression Detection in Videos from Non-Verbal Cuescited by 11
  2. 2024Multi-scale Dynamic and Hierarchical Relationship Modeling for Facial Action Units Recognitioncited by 11
  3. 2021Two-stage Temporal Modelling Framework for Video-based Depression Recognition using Graph Representationcited by 10
  4. 2023MASA-TCN: Multi-anchor Space-aware Temporal Convolutional Neural Networks for Continuous and Discrete EEG Emotion Recognitioncited by 9
  5. 2022Artificial Intelligence for Suicide Assessment using Audiovisual Cues: A Reviewcited by 8
  6. 2023DEPAC: a Corpus for Depression and Anxiety Detection from Speechcited by 8
  7. 2025Enhancing Depression Detection with Chain-of-Thought Prompting: From Emotion to Reasoning Using Large Language Modelscited by 8
  8. 2022Continuous-Time Audiovisual Fusion with Recurrence vs. Attention for In-The-Wild Affect Recognitioncited by 7
  9. 2022Depression Diagnosis and Analysis via Multimodal Multi-order Factor Fusioncited by 7
  10. 2024Multimodal Machine Learning in Mental Health: A Survey of Data, Algorithms, and Challengescited by 7
  11. 2024Multimodal Gender Fairness in Depression Prediction: Insights on Data from the USA & Chinacited by 7
  12. 2024Underneath the Numbers: Quantitative and Qualitative Gender Fairness in LLMs for Depression Predictioncited by 6
  13. 2024DiagESC: Dialogue Synthesis for Integrating Depression Diagnosis into Emotional Support Conversationcited by 6
  14. 2024SynFER: Towards Boosting Facial Expression Recognition with Synthetic Datacited by 6
  15. 2025The First MPDD Challenge: Multimodal Personality-aware Depression Detectioncited by 6
  16. 2022Multi-Modal Learning for AU Detection Based on Multi-Head Fused Transformerscited by 5
  17. 2023Explainable Depression Detection via Head Motion Patternscited by 5
  18. 2024Depression Detection and Analysis using Large Language Models on Textual and Audio-Visual Modalitiescited by 5
  19. 2024Advancing Mental Health Pre-Screening: A New Custom GPT for Psychological Distress Assessmentcited by 5
  20. 2025OpenFace 3.0: A Lightweight Multitask System for Comprehensive Facial Behavior Analysiscited by 5
  21. 2022Are 3D Face Shapes Expressive Enough for Recognising Continuous Emotions and Action Unit Intensities?cited by 4
  22. 2024Computational Analysis of Stress, Depression and Engagement in Mental Health: A Surveycited by 4
  23. 2024Modeling Emotional Trajectories in Written Stories Utilizing Transformers and Weakly-Supervised Learningcited by 4
  24. 2024Leveraging Audio and Text Modalities in Mental Health: A Study of LLMs Performancecited by 4
  25. 2022Data Augmentation for Depression Detection Using Skeleton-Based Gait Informationcited by 3
  26. 2023Multitask learning for recognizing stress and depression in social mediacited by 3
  27. 2024Does the Definition of Difficulty Matter? Scoring Functions and their Role for Curriculum Learningcited by 3
  28. 2025Enhancing Depression Detection via Question-wise Modality Fusioncited by 3
  29. 2025Domain Adversarial Training for Mitigating Gender Bias in Speech-based Mental Health Detectioncited by 3
  30. 2025Large Language Models for Depression Recognition in Spoken Language Integrating Psychological Knowledgecited by 3
  31. 2025A Comprehensive Review of Datasets for Clinical Mental Health AI Systemscited by 3
  32. 2026Complementarity-Supervised Spectral-Band Routing for Multimodal Emotion Recognitioncited by 3
  33. 2021Predicting Mood Disorder Symptoms with Remotely Collected Videos Using an Interpretable Multimodal Dynamic Attention Fusion Networkcited by 2
  34. 2022Neural Architecture Searching for Facial Attributes-based Depression Recognitioncited by 2
  35. 2022Towards Intercultural Affect Recognition: Audio-Visual Affect Recognition in the Wild Across Six Culturescited by 2
  36. 2024Self-Supervised Embeddings for Detecting Individual Symptoms of Depressioncited by 2
  37. 2025Speech as a Multimodal Digital Phenotype for Multi-Task LLM-based Mental Health Predictioncited by 2
  38. 2025Automatic Depression Assessment using Machine Learning: A Comprehensive Surveycited by 2

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