HOI-R1: Exploring the Potential of Multimodal Large Language Models for Human-Object Interaction Detection

HOI-R1 is inspired by recent advances in reinforcement learning for large language models and investigates how vision-language models can reason about and detect human-object interactions more effectively.

🔍 Overview

Task: Human-Object Interaction Detection (HOID)
Our Motivation:
Leverage the reasoning capability of Multimodal LLMs and reinforcement learning–style optimization to explore HOI detection performance.

📌 Citation

If you find this work useful, please consider citing:

@article{chen2025hoi,
  title={HOI-R1: Exploring the Potential of Multimodal Large Language Models for Human-Object Interaction Detection},
  author={Chen, Junwen and Xiong, Peilin and Yanai, Keiji},
  journal={arXiv preprint arXiv:2510.05609},
  year={2025}
}