JRDB-Social: A Multifaceted Robotic Dataset for Understanding of Context and Dynamics of Human Interactions Within Social Groups

• URL: http://arxiv.org/abs/2404.04458v1
• Date: Sat, 6 Apr 2024 00:33:39 GMT
• Title: JRDB-Social: A Multifaceted Robotic Dataset for Understanding of Context and Dynamics of Human Interactions Within Social Groups
• Authors: Simindokht Jahangard, Zhixi Cai, Shiki Wen, Hamid Rezatofighi,
• Abstract summary: JRDB-Social fills gaps in human understanding across diverse indoor and outdoor social contexts. This dataset aims to enhance our grasp of human social dynamics for robotic applications.
• Score: 8.415759777703125
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Understanding human social behaviour is crucial in computer vision and robotics. Micro-level observations like individual actions fall short, necessitating a comprehensive approach that considers individual behaviour, intra-group dynamics, and social group levels for a thorough understanding. To address dataset limitations, this paper introduces JRDB-Social, an extension of JRDB. Designed to fill gaps in human understanding across diverse indoor and outdoor social contexts, JRDB-Social provides annotations at three levels: individual attributes, intra-group interactions, and social group context. This dataset aims to enhance our grasp of human social dynamics for robotic applications. Utilizing the recent cutting-edge multi-modal large language models, we evaluated our benchmark to explore their capacity to decipher social human behaviour.

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