Autonomous driving, in recent years, has been receiving increasing attention for its potential
to relieve drivers' burdens and improve the safety of driving. In modern autonomous driving …

Autonomous vehicles require constant environmental perception to obtain the distribution of
obstacles to achieve safe driving. Specifically, 3D object detection is a vital functional …

Recent advancements in perception for autonomous driving are driven by deep learning. In
order to achieve robust and accurate scene understanding, autonomous vehicles are …

Vehicle and pedestrian detection is one of the critical tasks in autonomous driving. Since
heterogeneous techniques have been proposed, the selection of a detection system with an …

Point clouds acquired through laser scanning and stereo vision techniques have been
applied in a wide range of applications, proving to be optimal sources for mapping 3D urban …

Accurate detection of obstacles in 3D is an essential task for autonomous driving and
intelligent transportation. In this work, we propose a general multimodal fusion framework …

How to ensure robust and accurate 3D object detection under various environment is
essential for autonomous driving (AD) environment perception. While, until now, most of the …

LiDAR and cameras are complementary sensors for 3D object detection in autonomous
driving. However, it is challenging to explore the unnatural interaction between point clouds …

In the era of sixth-generation (6G) wireless communications, integrated sensing and
communications (ISAC) is recognized as a promising solution to upgrade the physical …

Multi-modal fusion is a fundamental task for the perception of an autonomous driving
system, which has recently intrigued many researchers. However, achieving a rather good …