Changcai Li
Papers
2
Total Citations
17
H-Index
2
About
Changcai Li is a researcher at the forefront of 3D computer vision, with a focused expertise in efficient object detection for autonomous driving and robotics. His work directly tackles the critical challenge of balancing high accuracy with real-time performance and cost-effectiveness. Li’s major contributions center on developing practical, deployable solutions for 3D perception. Notably, his work on "Efficient 3D Object Detection Based on Pseudo-LiDAR Representation" (15 citations) addresses the high cost of traditional LiDAR sensors by leveraging more affordable alternatives without sacrificing detection quality. Complementing this, his "ER3D: An Efficient Real-time 3D Object Detection Framework" (2 citations) explicitly targets the need for lightweight systems that can operate in real-time, moving beyond complex, bulky models that are impractical for real-world deployment. By prioritizing both efficiency and accuracy, Li is helping to bridge the gap between cutting-edge research and the tangible requirements of mobile robotics and autonomous vehicles, making self-driving technology more accessible and robust.
Research Focus
Key Achievements
Top Papers
- 1Efficient 3D Object Detection Based on Pseudo-LiDAR Representation15 citations · 2023
- 2