To assure that an autonomous car is driving safely on public roads, its object detection
module should not only work correctly, but show its prediction confidence as well. Previous …

3D object detection based on LiDAR point clouds is a crucial module in autonomous driving
particularly for long range sensing. Most of the research is focused on achieving higher …

The past few years have witnessed an increasing interest in improving the perception
performance of LiDARs on autonomous vehicles. While most of the existing works focus on …

In this paper, we present LaserNet, a computationally efficient method for 3D object
detection from LiDAR data for autonomous driving. The efficiency results from processing …

For autonomous driving, vehicle detection is the prerequisite for many tasks like collision
avoidance and path planning. In this letter, we present a real-time three-dimensional (RT3D) …

3D object detection plays a fundamental role in enabling driving automation, which is
regarded as a significant leap forward for contemporary transportation systems from the …

3D object detection is a fundamental problem in the space of autonomous driving, and
pedestrians are some of the most important objects to detect. The recently introduced …

Autonomous vehicles may make wrong decisions due to inaccurate detection and
recognition. Therefore, an intelligent vehicle can combine its own data with that of other …

In the domain of autonomous driving, deep learning has substantially improved the 3D
object detection accuracy for LiDAR and stereo camera data alike. While deep networks are …

Understanding driving situations regardless the conditions of the traffic scene is a
cornerstone on the path towards autonomous vehicles; however, despite common sensor …