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Shengnan Hu

2 accepted papers

2026

Learning Topology-Aware Dynamic Associations for Robust Multi-Person Pose Estimation

AAAI 2026technical

Multi-person pose estimation in real-world scenarios remains a challenging task due to frequent occlusions, scale variations, and complex human interactions. Existing methods often rely on fixed keypoint association patterns that fail to capture the dynamic and context-dependent nature of human body

Cited by 0SourcePDFScholar
2023

LAMP: Leveraging Language Prompts for Multi-Person Pose Estimation

IROS 2023poster

Human-centric visual understanding is an important desideratum for effective human-robot interaction. In order to navigate crowded public places, social robots must be able to interpret the activity of the surrounding humans. This paper addresses one key aspect of human-centric visual understanding,…

Cited by 6SourcecodeScholar