JRDB-Social: A Multifaceted Robotic Dataset for Understanding of Context and Dynamics of Human Interactions Within Social Groups
<|reference_start|>JRDB-Social: A Multifaceted Robotic Dataset for Understanding of Context and Dynamics of Human Interactions Within Social Groups: 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.<|reference_end|>
@article{jahangard2024jrdb-social:,
    title={JRDB-Social: A Multifaceted Robotic Dataset for Understanding of Context
  and Dynamics of Human Interactions Within Social Groups},
    author={Simindokht Jahangard, Zhixi Cai, Shiki Wen, Hamid Rezatofighi},
    journal={arXiv preprint arXiv:2404.04458},
    year={2024},
    archivePrefix={arXiv},
    eprint={2404.04458},
    primaryClass={cs.CV}
}