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Human–object interaction (HOI) detection is crucial for human-centric image understanding which aims to infer ⟨human, action, object⟩ triplets within an image. Recent studies often exploit visual features and the spatial configuration of a human–object pair in order to learn the action linking the human and object in the pair. We argue that such a paradigm of pairwise feature extraction and action inference can be applied not only at the whole human and object instance level, but also at thedoi:10.1007/s41095-020-0188-2 fatcat:f6hp2htx25caripys3bpvwd4si