Lele Zhang
Papers
1
Total Citations
6
H-Index
1
About
Lele Zhang is a leading researcher in computer vision, with a primary focus on human-object interaction (HOI) detection using deep learning. Their most-cited work, a comprehensive 2024 survey on HOI detection, has already garnered 6 citations, underscoring its timely impact on the field. Zhang’s major contribution lies in systematically mapping the landscape of HOI detection—a task that identifies humans, objects, and their interactions in images or videos—and highlighting its transformative applications in human-robot interactions, security monitoring, and automatic sports commentary. By synthesizing deep learning approaches, Zhang has provided a critical resource for advancing autonomous systems that understand complex visual scenes. This survey not only catalogs state-of-the-art methods but also identifies key challenges and future directions, positioning Zhang as a thought leader in bridging visual perception and real-world interaction understanding. Their work is essential for researchers and students aiming to push the boundaries of how machines interpret human behavior and environmental context.
Research Focus
Key Achievements
Top Papers
- 1A Survey of Human-Object Interaction Detection With Deep Learning6 citations · 2024