Zibu Wei
Papers
2
Total Citations
65
H-Index
2
About
Zibu Wei is a researcher advancing the field of 3D object detection, with a primary focus on bridging domain gaps in LiDAR-based perception systems. His most significant contribution is the introduction of **LiDAR Distillation**, a novel technique that addresses the critical challenge of beam-induced domain gaps between different LiDAR sensors. This work, which has accumulated 63 citations, proposes a knowledge distillation framework that enables models trained on high-beam LiDAR data (common in public datasets) to effectively transfer their capabilities to lower-beam sensors used in mass-produced robots and vehicles. This is particularly impactful for real-world deployment, where cost constraints often necessitate fewer LiDAR beams. By tackling this practical limitation, Wei’s research directly improves the robustness and transferability of 3D object detectors, making autonomous systems more reliable across diverse hardware configurations. His work represents a key step toward democratizing high-performance perception for production-grade autonomous vehicles and robotics, bridging the gap between academic datasets and industrial applications.
Research Focus
Key Achievements
Top Papers
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