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Kuangyi Chen

4 accepted papers

2026

LEAR: Learning Edge-Aware Representations for Event-To-LiDAR Localization

ICRA 2026poster

Event cameras offer high-temporal-resolution sensing that remains reliable under high-speed motion and challenging lighting, making them promising for localization from LiDAR point clouds in GPS-denied and visually degraded environments. However, aligning sparse, asynchronous events with dense LiDAR…

2025

EVLoc: Event-Based Visual Localization in LiDAR Maps via Event-Depth Registration

ICRA 2025

Event cameras are bio-inspired sensors with some notable features, including high dynamic range and low latency, which makes them exceptionally suitable for perception in challenging scenarios such as high-speed motion and extreme lighting conditions. In this paper, we explore their potential for lo

Cited by 3SourcecodeScholar
2024

FE-DeTr: Keypoint Detection and Tracking in Low-quality Image Frames with Events

ICRA 2024poster

Keypoint detection and tracking in traditional image frames are often compromised by image quality issues such as motion blur and extreme lighting conditions. Event cameras offer potential solutions to these challenges by virtue of their high temporal resolution and high dynamic range. However, they…

Cited by 4SourcecodeScholar
2024

I2D-Loc++: Camera Pose Tracking in LiDAR Maps With Multi-View Motion Flows

RA-L 2024

Camera localization in LiDAR maps has become increasingly popular due to its promising ability to handle complex scenarios, surpassing the limitations of visual-only localization methods. However, existing approaches mostly focus on addressing the cross-modal 2D–3D gaps while overlooking the relatio

Cited by 4SourceScholar