AI RESEARCH
GAViD: A Large-Scale Multimodal Dataset for Context-Aware Group Affect Recognition from Videos
arXiv CS.CV
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ArXi:2604.16214v1 Announce Type: new Understanding affective dynamics in real-world social systems is fundamental to modeling and analyzing human-human interactions in complex environments. Group affect emerges from intertwined human-human interactions, contextual influences, and behavioral cues, making its quantitative modeling a challenging computational social systems problem.