Pose-aware Multi-level Feature Network for Human Object Interaction Detection

ICCV 2019 Bo WanDesen ZhouYongfei LiuRongjie LiXuming He

Reasoning human object interactions is a core problem in human-centric scene understanding and detecting such relations poses a unique challenge to vision systems due to large variations in human-object configurations, multiple co-occurring relation instances and subtle visual difference between relation categories. To address those challenges, we propose a multi-level relation detection strategy that utilizes human pose cues to capture global spatial configurations of relations and as an attention mechanism to dynamically zoom into relevant regions at human part level... (read more)

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