Papers
3
Total Citations
6
H-Index
2
About
Li Fang’s research bridges the worlds of competitive robotics and cutting-edge computer vision, with a focus on autonomous systems, underwater perception, and 3D reconstruction. As a key member of the ZJUNlict team, Fang contributed to the RoboCup 2013 Small Size League championship, a milestone in multi-agent coordination and real-time strategy. More recently, Fang has advanced underwater object detection with VVNet, a novel architecture combining Vision Transformers and Vision RetNet to overcome challenges like turbidity and variable lighting—work that directly supports underwater robot picking tasks. Fang also introduced ART-InvRec, an adversarial framework for rotation-invariant 3D object reconstruction, addressing a fundamental challenge in shape recovery from partial views. Though still early in their career, Fang’s work has already garnered citations from the robotics and vision communities, and their contributions to both competition-winning systems and practical deep learning solutions highlight a versatile and impactful trajectory.
Research Focus
Key Achievements
Top Papers
- 1ZJUNlict: RoboCup 2013 Small Size League Champion3 citations · 2014
- 2
- 3