In the realm of modern autonomous driving, the perception system is indispensable for
accurately assessing the state of the surrounding environment, thereby enabling informed …

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 …

LiDAR and camera are two critical sensors that can provide complementary information for
accurate 3D object detection. Most works are devoted to improving the detection …

This survey reviews advances in 3D object detection approaches for autonomous driving. A
brief introduction to 2D object detection is first discussed and drawbacks of the existing …

The reliability of driving perception systems under unprecedented conditions is crucial for
practical usage. Latest advancements have prompted increasing interest in multi-LiDAR …

The recent advances in camera-based bird's eye view (BEV) representation exhibit great
potential for in-vehicle 3D perception. Despite the substantial progress achieved on …

Safety-critical 3D scene understanding tasks necessitate not only accurate but also
confident predictions from 3D perception models. This study introduces Calib3D, a …

Recent advancements in bird's eye view (BEV) representations have shown remarkable
promise for in-vehicle 3D perception. However, while these methods have achieved …

At present the perception system of autonomous vehicles is grounded on 3D vision
technologies along with deep learning to process depth information. Although deep learning …

Deep learning networks have demonstrated outstanding performance in 2D and 3D vision
tasks. However, recent research demonstrated that these networks result in failures when …