The human-object interaction (HOI) detection task refers to localizing humans, localizing objects, and predicting the interactions between each human-object pair. HOI is considered one of the fundamental steps in truly understanding complex visual scenes. For detecting HOI, it is important to utilize relative spatial configurations and object semantics to find salient spatial regions of images that highlight the interactions between human object pairs. This issue is addressed by the novel self-attention based guided transformer network, GTNet. GTNet encodes this spatial contextual information in human and object visual features via self-attention while achieving state of the art results on both the V-COCO and HICO-DET datasets. Code will be made available online.

翻译：人体物体相互作用(HOI)检测任务是指将人类定位、物体定位和预测每个人体物体对应方之间的相互作用。 HOI被视为真正理解复杂视觉场景的基本步骤之一。为了探测HOI,必须利用相对的空间配置和物体语义来找到突出显示人类物体对子之间相互作用的图像的显著空间区域。这个问题由基于自我注意的新颖的自知式制导变压器网络GTNet来解决。 GTNet通过自我注意将人类空间背景信息和物体视觉特征编码,同时取得V-CO和HiCO-DET数据集的艺术成果。代码将在线公布。