发表机构
United Arab Emirates University; Hefei University of Technology; University College London; Zhejiang University; University of Oulu; CMVS, University of Oulu（阿联酋大学; 合肥工业大学; 伦敦大学学院; 浙江大学; 奥卢大学; 奥卢大学计算机视觉与媒体研究中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文介绍第三届MAC 2026，以从识别到细粒度微动作理解为主题，扩大挑战范围，引入新任务并借助多模态大语言模型评估，总结了相关数据集、设置、结果等，还探讨了微动作分析未来方向及在视频理解中的作用。
AI 中文摘要
微动作是人类微妙且自发的行为，在社交互动和情感交流中提供重要的非语言线索。然而，其持续时间短、运动模式弱以及细粒度语义差异，使得难以对其进行标准化的标注、建模和评估。为推动微动作分析的学术研究，我们提出并每年组织微动作分析大挑战（MAC）作为该新兴领域的公共基准平台。前两版MAC为微动作识别和检测建立了标准化评估设置，并提供了可公开访问的数据集和协议。在此基础上，本文介绍了与ACM多媒体2026联合举办的第三届MAC。该版本以从识别到细粒度微动作理解为主题，进一步扩大了挑战范围。特别引入了细粒度微动作理解新任务，借助多模态大语言模型进行评估，旨在评估模型捕捉细粒度语义线索和深入解释人类微动作的能力。我们总结了数据集、任务设置、评估协议、竞赛结果以及顶尖团队的代表性解决方案。最后，我们讨论了微动作分析的未来方向及其在以人类为中心的视频理解中的更广泛作用。
英文摘要
Micro-Actions (MAs) are subtle and spontaneous human behaviors that provide important non-verbal cues in social interaction and affective communication. However, their short duration, weak motion patterns, and fine-grained semantic differences make them difficult to annotate, model, and evaluate in a standardized manner. To promote academic research on micro-action analysis, we proposed and have annually organized the Micro-Action Analysis Grand Challenge (MAC) as a public benchmark platform for this emerging field. The first two editions of MAC established standardized evaluation settings for micro-action recognition and detection, providing publicly accessible datasets and protocols. Building upon these editions, this paper presents the 3rd MAC, held in conjunction with ACM Multimedia 2026. Under the theme of moving from recognition to fine-grained micro-action understanding, this edition further expands the scope of the challenge beyond conventional recognition and detection. In particular, we introduce a new task named fine-grained micro-action understanding, evaluated with the assistance of multimodal large language models, aiming to assess models' ability to capture fine-grained semantic cues and interpret subtle human micro-actions at a deeper level. We summarize the datasets, task settings, evaluation protocols, competition results, and representative solutions from top-performing teams. Finally, we discuss future directions for micro-action analysis and its broader role in human-centric video understanding.
CommentsChallenge Summary Paper of the 3rd Micro-Action Analysis Grand Challenge (MAC 2026) at ACM Multimedia 2026
