Junze Wen
Papers
2
Total Citations
27
H-Index
2
About
Junze Wen is an emerging researcher specializing in autonomous driving perception and mobile robotics, with a particular focus on grid-centric approaches to traffic scenario understanding. His most notable contribution is a comprehensive review of grid-centric traffic scenario perception for autonomous driving, which has garnered significant attention in the research community, accumulating 27 citations across its iterations published in 2023 and 2024. Wen's work addresses a critical gap in autonomous driving research: while object-centric perception has dominated the field, grid-centric methods offer unique advantages for representing complex, dynamic traffic environments at scale. His comprehensive review synthesizes the challenges and computational complexities inherent in grid-based representations, providing researchers and engineers with a structured understanding of this underexplored paradigm. By advocating for grid-centric perception frameworks, Wen contributes to advancing how autonomous vehicles interpret their surroundings in highly dynamic, large-scale scenarios — a fundamental challenge for achieving reliable self-driving systems. His work serves as a valuable reference for researchers navigating the intersection of mobile robotics, sensor fusion, and scene understanding, helping bridge the gap between theoretical perception models and real-world autonomous driving applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2