Detecting objects in 3D LiDAR data is a core technology for autonomous driving and other
robotics applications. Although LiDAR data is acquired over time, most of the 3D object …

Point clouds have garnered increasing research attention and found numerous practical
applications. However, many of these applications, such as autonomous driving and robotic …

The purpose of this work is to review the state-of-the-art LiDAR-based 3D object detection
methods, datasets, and challenges. We describe novel data augmentation methods …

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 …

In the autonomous driving domain, data collection and annotation from real vehicles are
expensive and sometimes unsafe. Simulators are often used for data augmentation, which …

Continuous frames of point-cloud-based object detection is a new research direction.
Currently, most research studies fuse multi-frame point clouds using concatenation-based …

The object detection and recognition algorithm based on the fusion of millimeter-wave radar
and high-definition video data can improve the safety of intelligent-driving vehicles …