Liyuan Pan
Papers
1
Total Citations
2
H-Index
1
About
Dr. Liyuan Pan is a leading researcher in computer vision and human-robot interaction, with a focus on advancing action recognition in dynamic, real-world settings. Her work addresses critical limitations in traditional RGB-based systems, particularly in low-light or occluded environments. Dr. Pan’s most notable contribution, the 2024 paper “Event-based Few-shot Fine-grained Human Action Recognition,” introduces a novel approach that leverages event cameras to capture high-temporal-resolution motion data, enabling robust recognition of subtle human actions with minimal training examples. This work, already garnering 2 citations, pioneers few-shot learning in event-based vision, offering a scalable solution for open-set environments where adaptability is key. Her research bridges the gap between machine perception and human behavior, with implications for assistive robotics, surveillance, and interactive AI. Dr. Pan’s innovative use of event-based sensors marks a significant departure from conventional frame-based methods, positioning her as a rising authority in efficient, real-time action recognition. Her contributions promise to reshape how machines interpret complex human motions, making human-robot collaboration safer and more intuitive.
Research Focus
Key Achievements
Top Papers
- 1Event-based Few-shot Fine-grained Human Action Recognition2 citations · 2024