Human-object interaction detection via recycling of ground-truth annotations

Xue Lin, Qi Zou, Xixia Xu

Abstract: Highlights•Recycling the ground-truth annotations can obtain valuable information.•A closeness labeling auxiliary task is designed to capture the contextual information.•The direct supervision on the learning of graph structure is first introduced.•The proposed approach achieves competitive performance even without any extra data.