论文标题
RB-pastanet：基于规则和部分状态的几次人类对象互动检测
Rb-PaStaNet: A Few-Shot Human-Object Interaction Detection Based on Rules and Part States
论文作者
论文摘要
现有的人类对象相互作用（HOI）检测方法在非种族类别上取得了巨大进展，而稀有的HOI类仍未得到充分检测。在本文中，我们打算将人类的先验知识应用于现有工作。因此，我们将人类标记的规则添加到浮渣中，并提出旨在改善稀有HOI类检测的RB-Pastanet。我们的结果表明，稀有类别有一定的改进，而非稀有类别和整体改进更为可观。
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.
