From Affect to Complex Behavior: Advancing Multimodal Human-Centered AI at the 10th ABAW Workshop & Competition
The 10th ABAW Workshop and Competition at CVPR 2026 advances multimodal human-centered AI by introducing new challenges including emotional mimicry intensity estimation, ambivalence/hesitancy recognition, and fine-grained violence detection, alongside traditional affect estimation and recognition tasks. The competition leverages large-scale in-the-wild datasets, and the paper track covers a broad range of topics from pose estimation to fairness and robustness.
Article intelligence
Key points
- ABAW 2026 introduces novel challenges: emotional mimicry intensity, ambivalence recognition, and violence detection.
- Workshop continues dual structure with competition and paper tracks.
- Focus on real-world, unconstrained environments using large-scale datasets.
Why it matters
This matters because ABAW 2026 introduces novel challenges: emotional mimicry intensity, ambivalence recognition, and violence detection.
Technical impact
May affect model selection, inference cost, product capability, and evaluation benchmarks.
[2605.27451] From Affect to Complex Behavior: Advancing Multimodal Human-Centered AI at the 10th ABAW Workshop & Competition
[Submitted on 24 May 2026]
Title:From Affect to Complex Behavior: Advancing Multimodal Human-Centered AI at the 10th ABAW Workshop & Competition
View a PDF of the paper titled From Affect to Complex Behavior: Advancing Multimodal Human-Centered AI at the 10th ABAW Workshop & Competition, by Dimitrios Kollias and Panagiotis Tzirakis and Alan Cowen and Stefanos Zafeiriou and Irene Kotsia and Eric Granger and Marco Pedersoli and Simon Bacon and Jens Madsen and Soufiane Belharbi and Muhammad Haseeb Aslam and Chunchang Shao and Guanyu Hu
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Abstract:The 10th Affective & Behavior Analysis in-the-Wild (ABAW) Workshop and Competition, held at CVPR 2026, continues to advance research on modelling, analysis, understanding of human affect and behavior in real-world, unconstrained environments. The workshop maintains its dual structure, comprising both a competition and a paper track. The ABAW Competition introduces a diverse set of challenges targeting key aspects of affective and behavioral understanding, including continuous affect (valence-arousal) estimation, discrete affect (expression and action unit) recognition, as well as more complex behavior analysis tasks, such as emotional mimicry intensity estimation, ambivalence/hesitancy recognition and fine-grained violence detection. These challenges are built upon large-scale in-the-wild datasets, providing comprehensive benchmarks for state-of-the-art approaches. In parallel, the paper track presents a wide range of contributions spanning pose, motion & behavior estimation, affect modelling & multimodal learning, benchmarks, datasets & evaluation protocols, fairness, robustness & deployment. Overall, the 10th ABAW Workshop and Competition continues to serve as a key platform for benchmarking, collaboration and innovation, shaping the development of next-generation multimodal, human-centered AI systems.
Comments: accepted at CVPR 2026
Subjects:
Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2605.27451 [cs.CV]
(or arXiv:2605.27451v1 [cs.CV] for this version)
https://doi.org/10.48550/arXiv.2605.27451
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Dimitrios Kollias [view email] [v1] Sun, 24 May 2026 17:44:37 UTC (3,041 KB)
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