Abstract
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.
Abstract (translated)
基于人类与功能相似的物体以相似的方式相互作用的观点，我们提出了一种检测图像中人-物相互作用（HOI）的方法。该模型简单，利用了人的视觉特征、人和物体的相对空间方向以及功能相似的物体参与与人的相似交互的知识。我们为我们的方法提供了广泛的实验验证，并展示了最先进的检测结果。在HICO DET数据集上，我们的方法在平均平均精度（MAP）上比已发表的文献获得了超过7%的绝对值，甚至比当代作品获得了超过2.5%的绝对值。我们还表明，我们的方法导致在可见目标设置中零炮检测的性能显著提高。我们进一步证明，使用一个通用的对象检测器，我们的模型可以推广到涉及以前看不见的对象的交互。
URL
https://arxiv.org/abs/1904.03181
