Rb-PaStaNet: A Few-Shot Human-Object Interaction Detection Based on Rules and Part States

Shenyu Zhang, Zichen Zhu, Qingquan Bao

Abstract: Existing Human-Object Interaction (HOI) Detection approaches have achieved great progress on nonrare classes while rare HOI classes are still not well-detected. In this paper, we intend to apply human prior knowledge into the existing work. So we add human-labeled rules to PaStaNet and propose Rb-PaStaNet aimed at improving rare HOI classes detection. Our results show a certain improvement of the rare classes, while the non-rare classes and the overall improvement is more considerable.