Luyang Zhu

University of Washington

Papers

2

Total Citations

89

H-Index

2

About

Luyang Zhu is a leading researcher at the intersection of computer vision and robotics, with a primary focus on 3D perception, depth estimation, and the challenging domain of transparent object reconstruction. Their most significant contribution is the pioneering work on "RGB-D Local Implicit Function for Depth Completion of Transparent Objects" (2021), which has garnered 85 citations. This research directly tackles a critical failure point in standard RGB-D sensors: their inability to capture depth for transparent objects due to light refraction and absorption. By introducing a novel local implicit function that leverages both RGB and depth cues, Zhu’s method enables robots to perceive and interact with transparent surfaces—a long-standing bottleneck in manipulation tasks. This work is foundational for advancing robotic grasping and scene understanding in real-world environments. Zhu’s research has been instrumental in pushing the boundaries of what robots can see and handle, making a lasting impact on the field of robotic perception and 3D computer vision.

Research Focus

Key Achievements

2
H-Index
2
Papers
89
Total Citations
45
Avg Citations/Paper
🏆 Most Cited Paper
RGB-D Local Implicit Function for Depth Completion of Transparent Objects
85 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of Washington

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago