Advancements in Affective and Behavior Analysis: The 8th ABAW Workshop and Competition

Dimitrios Kollias, Panagiotis Tzirakis, Alan Cowen, Stefanos Zafeiriou, Irene Kotsia, Eric Granger, Marco Pedersoli, Simon Bacon, Alice Baird, Chris Gagne, Chunchang Shao, Guanyu Hu, Soufiane Belharbi, Muhammad Haseeb Aslam; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2025, pp. 5581-5592

The 8th Affective & Behavior Analysis in-the-Wild (ABAW) Workshop at CVPR 2025 focuses on advancing the understanding and modeling of human affective and behavioral patterns in real-world scenarios. It serves as a platform for interdisciplinary collaboration, showcasing the latest methodologies and applications in affective computing and behavior analysis. A core feature of the workshop is the ABAW Competition, which tackles critical challenges in human affect and behavior recognition - essential for developing human-centered AI technologies. The 8th ABAW Competition features six challenges: (1) estimation of two continuous affect dimensions (valence and arousal), (2) recognition of eight mutually exclusive classes (the 7 basic expressions and a category 'other'), (3) detection of twelve action units, (4) recognition of seven mutually exclusive compound expressions, (5) estimation of emotional mimicry intensity across six dimensions, and (6) recognition of presence and absence of ambivalence/hesitancy. These challenges leverage datasets such as Aff-Wild2, C-EXPR-DB, HUME-Vidmimic2, and BAH, providing a comprehensive benchmark for evaluating affective behavior analysis models. Each challenge is assessed using specialized performance metrics, including Concordance Correlation Coefficient (CCC), F1-score, and Pearson's correlation. This paper provides an overview of the competition, detailing the datasets, pre-processing methodologies, evaluation criteria, and baseline models. The baseline results establish benchmarks for future research and development. Further details on the competition are available at: https://affective-behavior-analysis-in-the-wild.github.io/8th.