Hongchen Luo

University of Science and Technology of China

Papers

Total Citations

H-Index

About

Hongchen Luo is a leading researcher in computer vision and robotics, with a focused expertise in affordance detection—the ability to identify how objects can be used or interacted with. His work bridges the gap between visual perception and robotic manipulation, enabling machines to understand not just what an object is, but what can be done with it. Luo’s most impactful contribution is pioneering one-shot affordance detection, allowing robots to recognize interaction possibilities from a single example, as demonstrated in his 2021 paper (20 citations) and its expanded 2022 follow-up (37 citations). He further advanced the field by introducing visual affordance grounding from demonstration videos (2023, 24 citations), a method that segments all possible human-object interaction regions from images or videos. This work has direct applications in robot grasping and action recognition, moving beyond reliance on object appearance to learn from real-world demonstrations. With over 80 total citations and a rapidly growing influence, Luo’s research is shaping how autonomous systems perceive and interact with their environment, making him a key figure in the development of intelligent, adaptable robots.