4 papers
Multi-Modality Co-Learning for Efficient Skeleton-based Action Recognition
Jinfu Liu, Chen Chen, Mengyuan Liu
Skeleton-based action recognition has garnered significant attention due to the utilization of concise and resilient skeletons. Nevertheless, the absence of detailed body informati…
HDBN: A Novel Hybrid Dual-branch Network for Robust Skeleton-based Action Recognition
Jinfu Liu, Baiqiao Yin, Jiaying Lin +3
Skeleton-based action recognition has gained considerable traction thanks to its utilization of succinct and robust skeletal representations. Nonetheless, current methodologies oft…
Explore Human Parsing Modality for Action Recognition
Jinfu Liu, Runwei Ding, Yuhang Wen +4
Multimodal-based action recognition methods have achieved high success using pose and RGB modality. However, skeletons sequences lack appearance depiction and RGB images suffer irr…
Integrating Human Parsing and Pose Network for Human Action Recognition
Runwei Ding, Yuhang Wen, Jinfu Liu +3
Human skeletons and RGB sequences are both widely-adopted input modalities for human action recognition. However, skeletons lack appearance features and color data suffer large amo…