[CVPR 2025] SocialGesture: Delving into Multi-person Gesture Understanding

Dataset Description

We introduce SocialGesture, the first large-scale dataset specifically designed for multi-person gesture analysis. SocialGesture features a diverse range of natural scenarios and supports multiple gesture analysis tasks, including video-based recognition and temporal localization, providing a valuable resource for advancing the study of gesture during complex social interactions. Furthermore, we propose a novel visual question answering (VQA) task to benchmark vision language models' (VLMs) performance on social gesture understanding. Our findings highlight several limitations of current gesture recognition models, offering insights into future directions for improvement in this field.

Annotation Structure

----videos
    |----xxx.mp4
    |----xxx.mp4
----train_annotation.json
----test_annotation.json
----dataset_stat_link.xlsx

Reference

@inproceedings{cao2025socialgesture,
  title={SocialGesture: Delving into Multi-person Gesture Understanding},
  author={Cao, Xu and Virupaksha, Pranav and Jia, Wenqi and Lai, Bolin and Ryan, Fiona and Lee, Sangmin and Rehg, James M},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2025}
}