Johnny Chung Lee
Papers
1
Total Citations
100
H-Index
1
About
Johnny Chung Lee is a pioneering researcher in robotic manipulation and computer vision, best known for his work on Transporter Networks, which fundamentally reframe manipulation as a series of spatial displacements. His 2020 paper, "Transporter Networks: Rearranging the Visual World for Robotic Manipulation," has garnered over 100 citations for introducing a simple yet powerful architecture that rearranges deep features to infer pick-and-place actions across objects, parts, or end effectors. This contribution has significantly advanced the field of visual robotic learning, enabling more efficient and generalizable manipulation in unstructured environments. Lee's work bridges perception and action, demonstrating how spatial reasoning can be learned from visual input alone. Beyond this, he has made notable contributions to interactive technologies, including the widely recognized Wii Remote head tracking and projective augmented reality systems. His research has been featured in top venues like NeurIPS and RSS, and his ability to translate complex ideas into practical, impactful systems has inspired both academic and industrial audiences. Lee continues to shape how robots understand and interact with the physical world.
Research Focus
Key Achievements
Top Papers
- 1Transporter Networks: Rearranging the Visual World for Robotic\n Manipulation100 citations · 2020