Roadside perception is a fundamental task for vehicle-to-road cooperative perception and
traffic scheduling. However, most existing roadside perception strategies prefer to deploy …

In autonomous driving, Vehicle-Infrastructure Cooperative 3D Object Detection (VIC3D)
makes use of multi-view cameras from both vehicles and traffic infrastructure, providing a …

Accurate detection of objects in 3D point clouds is a key problem in autonomous driving
systems. Collaborative perception can incorporate information from spatially diverse sensors …

Vehicle–infrastructure cooperative perception is becoming increasingly crucial for
autonomous driving systems and involves leveraging infrastructure's broader spatial …

Abstract 3D object detection plays a crucial role in the perception system of autonomous
vehicles, however, the vehicle's field of view is restricted due to obstructions from nearby …

3D-LiDAR-based cooperative perception has been generating significant interest for its
ability to tackle challenges such as occlusion, sparse point clouds, and out-of-range issues …

Autonomous vehicles rely extensively on onboard sensors to perceive their surrounding
environments for motion planning and vehicle control. Despite recent advancements …

3D object detection is a significant aspect of the perception module in autonomous driving;
however, with current technology, data sharing between vehicles and cloud servers for …

Object detection is the central issue of intelligent traffic systems, and recent advancements in
single-vehicle lidar-based 3D detection indicate that it can provide accurate position …

Autonomous driving technology faces significant safety challenges due to the lack of a
global perspective and the limitations of long-range perception capabilities. It is widely …