聚焦真实场景下人类情绪与行为分析，推动多模态人中心AI发展。
From Affect to Complex Behavior: Advancing Multimodal Human-Centered AI at the 10th ABAW Workshop & Competition
- 构建多任务挑战，覆盖情绪连续估计、表情识别与复杂行为分析。
- 基于大规模真实数据集，提供当前最优方法的综合评测基准。
- 适合关注多模态情感计算与可部署智能系统的研究者参考。
第10届《在野情感与行为分析》（ABAW）研讨会与竞赛于2026年CVPR期间举行，持续推动真实、非受限环境下人类情绪与行为建模与理解的研究。研讨会保持竞赛与论文双轨结构：竞赛涵盖连续情绪（愉悦-唤醒）估计、离散情绪（表情与动作单元）识别，以及更复杂的任务如情绪模仿强度评估、矛盾/犹豫识别与细粒度暴力检测。所有挑战均基于大规模在野数据集，为前沿方法提供全面基准。论文轨道则涵盖姿态、运动与行为估计，情感建模与多模态学习，基准、数据集与评估协议，公平性、鲁棒性与部署等广泛贡献。整体而言，第10届ABAW继续作为评测、协作与创新的关键平台，塑造下一代多模态人中心AI的发展方向。
原文摘要 · Abstract (English)
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.
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