Lian Zou
Papers
2
Total Citations
36
H-Index
2
About
Lian Zou is a researcher specializing in 3D computer vision and deep learning, with a particular focus on point cloud analysis for autonomous driving and robotics. Their most influential work, "PSANet: Pyramid Splitting and Aggregation Network for 3D Object Detection in Point Cloud" (2020), has garnered 22 citations and addresses critical performance bottlenecks in one-stage 3D detectors by improving feature utilization in LiDAR data. This contribution enhances detection accuracy while maintaining real-time processing speeds essential for safety-critical applications. Zou also explored facial analysis with "Face age classification based on a deep hybrid model" (2018, 14 citations), demonstrating versatility in applying deep learning to both geometric and image-based tasks. Their research bridges the gap between efficient detection architectures and practical deployment in autonomous systems, making notable strides in overcoming the trade-off between speed and precision in 3D perception.
Research Focus
Key Achievements
Top Papers
- 1
- 2Face age classification based on a deep hybrid model14 citations · 2018