In the near future, autonomous vehicles with full self-driving features will populate our public
roads. However, fully autonomous cars will require robust perception systems to safely …

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 …

Cooperative perception offers several benefits for enhancing the capabilities of autonomous
vehicles and improving road safety. Using roadside sensors in addition to onboard sensors …

Automated Driving Systems (ADS) rely on a variety of sensors and algorithms to perceive
their environment and make proper and timely driving decisions to ensure safety and …

Current multi-modal object detection approaches focus on the vehicle domain and are
limited in the perception range and the processing capabilities. Roadside sensor units …

The applications of Vision-Language Models (VLMs) in the field of Autonomous Driving (AD)
have attracted widespread attention due to their outstanding performance and the ability to …

The curation of large-scale datasets is still costly and requires much time and resources.
Data is often manually labeled, and the challenge of creating high-quality datasets remains …

This paper proposes an efficient and accurate process to find instances of a specific object
in a point cloud scene where the object is unique, a member of a trained class, and the …

Multi-modal 3D scene understanding has gained considerable attention due to its wide
applications in many areas, such as autonomous driving and human-computer interaction …

Ground segmentation is a crucial task in the field of 3D LiDAR perception for autonomous
driving. It is commonly used as a preprocessing step for tasks such as object detection and …