Han Geng

Papers

Total Citations

H-Index

About

Han Geng is a rising researcher in computer vision, with a primary focus on human-object interaction (HOI) detection—a field critical for advancing human-robot collaboration, intelligent surveillance, and automated sports analysis. His most-cited work, a comprehensive 2024 survey on deep learning-based HOI detection, synthesizes the state of the art in detecting humans, objects, and their interactions from images and video. This survey, already garnering 6 citations shortly after publication, serves as a key reference for newcomers and experts alike, mapping the landscape of architectures, datasets, and evaluation metrics. Geng’s contributions help bridge the gap between raw visual data and high-level semantic understanding, enabling machines to interpret complex social and physical scenes. His work is particularly notable for its practical implications—from safer human-robot workspaces to more nuanced security monitoring. As an early-career scholar, Geng’s ability to produce a timely, well-received survey signals a strong foundation for future breakthroughs. For students and researchers entering HOI detection, his paper is an essential starting point, reflecting both the field’s rapid evolution and Geng’s emerging role in shaping it.