As technology advances, cities are getting smarter. Smart mobility is the key element in
smart cities and Autonomous Driving (AV) are an essential part of smart mobility. However …

Real-time 3D object detection is a fundamental technique in numerous applications, such as
autonomous driving, unmanned aerial vehicles (UAV) and robot vision. However, current …

Occlusion is a critical problem in the Autonomous Driving System. Solving this problem
requires robust collaboration among autonomous vehicles traveling on the same roads …

Data augmentation has been widely adopted for object detection in 3D point clouds.
However, all previous related efforts have focused on manually designing specific data …

We present an end-to-end method for object detection and trajectory prediction utilizing multi-
view representations of LiDAR returns. Our method builds on a state-of-the-art Bird's-Eye …

Multi-modal fusion overcomes the inherent limitations of single-sensor perception in 3D
object detection of autonomous driving. The fusion of 4D Radar and LiDAR can boost the …

Abstract Knowledge of the road network topology is crucial for autonomous planning and
navigation. Yet, recovering such topology from a single image has only been explored in …

Autonomous driving services depends on active sensing from modules such as camera,
LiDAR, radar, and communication units. Traditionally, these modules process the sensed …

Three-dimensional object detection is crucial for autonomous driving to understand the
driving environment. Since the pooling operation causes information loss in the standard …

On-board 3D object detection in autonomous vehicles often relies on geometry information
captured by LiDAR devices. Albeit image features are typically preferred for detection …