In Autonomous Driving (AD), detection and tracking of obstacles on the roads is a critical
task. Deep-learning based methods using annotated LiDAR data have been the most widely …

We tackle the problem of producing realistic simulations of LiDAR point clouds, the sensor of
preference for most self-driving vehicles. We argue that, by leveraging real data, we can …

LiDAR is an indispensable sensor for autonomous driving that can provide precise 3D
information about the environment. Among various types of LiDARs, mechanical LiDARs are …

3D LiDAR scanners are playing an increasingly important role in autonomous driving as
they can generate depth information of the environment. However, creating large 3D LiDAR …

We introduce the Precise Synthetic Image and LiDAR (PreSIL) dataset for autonomous
vehicle perception. Grand Theft Auto V (GTA V), a commercial video game, has a large …

Recently, the advancement of deep learning (DL) in discriminative feature learning from 3-D
LiDAR data has led to rapid development in the field of autonomous driving. However …

LiDAR (Light Detection And Ranging) is an important and widely adopted sensor for
autonomous vehicles, particularly for those vehicles operating at higher levels (L4-L5) of …

We present a review of 3D point cloud processing and learning for autonomous driving. As
one of the most important sensors in autonomous vehicles, light detection and ranging …

We present a review of 3D point cloud processing and learning for autonomous driving. As
one of the most important sensors in autonomous vehicles (AVs), lidar sensors collect 3D …

Autonomous vehicles rely on their perception systems to acquire information about their
immediate surroundings. It is necessary to detect the presence of other vehicles …