Shuwei Zhang
Papers
1
Total Citations
17
H-Index
1
About
Shuwei Zhang is a leading researcher in autonomous driving perception, specializing in 3D object detection from LiDAR point cloud data. His work focuses on advancing real-time, single-shot neural network architectures that enable autonomous vehicles to perceive their environment with greater speed and accuracy. Zhang’s most cited paper, “Realtime Single-Shot Refinement Neural Network With Adaptive Receptive Field for 3D Object Detection From LiDAR Point Cloud” (2021, 17 citations), introduces a novel refinement network that adapts its receptive field to capture both fine-grained details and broader spatial context. This contribution addresses a critical bottleneck in autonomous driving: balancing detection precision with computational efficiency for real-time operation. By integrating adaptive mechanisms into single-shot frameworks, Zhang’s research pushes the boundaries of how LiDAR sensors interpret complex driving scenes, directly impacting the reliability of perception systems in self-driving cars and robotics. His work exemplifies the intersection of deep learning innovation and practical engineering, offering scalable solutions for safer autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1