Autonomous cars have achieved exceptional growth in the automotive industry in the last
century in terms of reliability, safety and affordability. Due to significant advancements in …

Autonomous driving is a promising way to future safe, efficient, and low-carbon
transportation. Real-time accurate target detection is an essential precondition for the …

Autonomous vehicles require accurate, and fast decision-making perception systems to
know the driving environment. The 2D object detection is critical in allowing the perception …

This paper presents a novel method for pedestrian detection and tracking by fusing camera
and LiDAR sensor data. To deal with the challenges associated with the autonomous driving …

Network fusion has been recently explored as an approach for improving pedestrian
detection performance. However, most existing fusion methods suffer from runtime …

Pedestrian detection has a wide range of application prospects in many fields such as
unmanned driving, intelligent monitoring, robot, etc., and has always been a hot issue in the …

The research in pedestrian detection has made remarkable progress in recent years.
However, robust pedestrian detection in crowded scenes remains a considerable challenge …

Connected autonomous vehicles (CAVs) have the potential to deal with the steady increase
in road traffic while solving transportation related issues such as traffic congestion, pollution …

Despite ongoing beta tests and research, significant challenges still need to be addressed
before fully autonomous driving can be commercialized. At levels 3 or higher, the …

Pedestrian detection and tracking are critical functions in the application of computer vision
for autonomous driving in terms of accident avoidance and safety. Extending the application …