The robustness of 3D perception systems under natural corruptions from environments and
sensors is pivotal for safety-critical applications. Existing large-scale 3D perception datasets …

Abstract 3D object detection is an important task in autonomous driving to perceive the
surroundings. Despite the excellent performance, the existing 3D detectors lack the …

Recent years have witnessed significant advancements in deep learning-based 3D object
detection, leading to its widespread adoption in numerous applications. As 3D object …

Autonomous driving has received enormous attention from the academic and industrial
communities. However, achieving full driving autonomy is not a trivial task, because of the …

In the context of autonomous driving, sensing systems play a crucial role, and their accuracy
and reliability can significantly impact the overall safety of autonomous vehicles. Despite …

Three-dimensional object detection is a pivotal research topic in computer vision, aiming to
identify and locate objects in three-dimensional space. It has wide applications in various …

The robustness of the 3D perception system under common corruptions and sensor failure is
pivotal for safety-critical applications. Existing large-scale 3D perception datasets often …

The annotation process for 3D point cloud data is more complex than for image data, and
training with a small amount of annotated data significantly reduces the performance of deep …

With the increase of assisted and automated functions provided on new vehicles and some
automotive manufacturers starting to equip high end vehicles with LiDARs, there is a need to …

This paper proposes a new method of blooming artifacts estimation, which is inherent in
flash light detection and ranging (LiDAR) based on single-photon avalanche diode (SPAD) …