We present an approach for detecting human-object interactions (HOIs) in images, based on the idea that humans interact with functionally similar objects in a similar manner. The proposed model is simple and uses the visual features of the human, relative spatial orientation of the human and the object, and the knowledge that functionally similar objects take part in similar interactions with humans. We provide extensive experimental validation for our approach and demonstrate state-of-the-art results for HOI detection. On the HICO-Det dataset our method achieves a gain of over 7% absolute points in mean average precision (mAP) over published literature and even a gain of over 2.5% absolute mAP over contemporary work. We also show that our approach leads to significant performance gains for zero-shot HOI detection in the seen object setting. We further demonstrate that using a generic object detector, our model can generalize to interactions involving previously unseen objects.

本文提出了一种基于人与物体功能相似性的人类-物体交互检测方法，使用视觉特征、人类和物体之间的相对空间方向和功能相似物体参与相似交互的知识。在HOI数据集上，该方法在平均精度方面的绝对增益为2.5%，并且在已知物体情况下实现了零样本HOI检测和广义物体检测。

通过功能泛化检测人-物交互