Papers
2
Total Citations
5
H-Index
2
About
Jinwei Ye is a leading researcher in autonomous systems and multi-modal perception, with a focus on enhancing safety and reliability in challenging environments. His work centers on integrating diverse sensor modalities—such as RGB cameras, LiDAR, and passive imaging—to enable robust object detection and navigation, particularly under adverse conditions. A key contribution is his development of hybrid frameworks for real-time moving-target detection, which fuse RGB images with LiDAR point clouds to identify dynamic obstacles like pedestrians and vehicles. This work, published in 2020, addresses critical safety risks in autonomous driving, laying groundwork for future intelligent transportation systems. More recently, Ye introduced M2P2, a multi-modal passive perception dataset designed for off-road mobility in extreme low-light conditions. This 2025 study tackles the limitations of active sensors (e.g., LiDAR) by leveraging passive imaging, enabling long-duration autonomous missions without reliance on power-hungry active systems. While his citation counts are currently modest (3 and 2 citations respectively), these pioneering efforts are gaining traction as foundational advances in autonomous navigation, particularly for applications in defense, search-and-rescue, and space exploration. Ye’s work exemplifies a shift toward energy-efficient, all-weather perception systems.
Research Focus
Key Achievements
Top Papers
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