Driven by deep learning techniques, perception technology in autonomous driving has
developed rapidly in recent years, enabling vehicles to accurately detect and interpret …

Radar is a key component of the suite of perception sensors used for safe and reliable
navigation of autonomous vehicles. Its unique capabilities include high-resolution velocity …

As an emerging technology and a relatively affordable device, the 4D imaging radar has
already been confirmed effective in performing 3D object detection in autonomous driving …

Radar is ubiquitous in autonomous driving systems due to its low cost and good adaptability
to bad weather. Nevertheless, the radar detection performance is usually inferior because its …

The inherent noisy and sparse characteristics of radar data pose challenges in finding
effective representations for 3D object detection. In this paper we propose RadarDistill a …

Three-dimensional object detection is one of the key tasks in autonomous driving. To reduce
costs in practice low-cost multi-view cameras for 3D object detection are proposed to …

Low-cost, vision-centric 3D perception systems for autonomous driving have made
significant progress in recent years, narrowing the gap to expensive LiDAR-based methods …

In the context of autonomous driving environment perception, multi-modal fusion plays a
pivotal role in enhancing robustness, completeness, and accuracy, thereby extending the …

Accurate perception is essential for advancing autonomous driving and addressing safety
challenges in modern transportation systems. Despite significant advancements in computer …

In the field of 3D object detection for autonomous driving LiDAR-Camera (LC) fusion is the
top-performing sensor configuration. Still LiDAR is relatively high cost which hinders …