While most recent autonomous driving system focuses on developing perception methods
on ego-vehicle sensors, people tend to overlook an alternative approach to leverage …

Transformer architectures have exhibited promising performance in various autonomous
driving applications in recent years. On the other hand, its dedicated hardware acceleration …

While most recent autonomous driving system focuses on developing perception methods
on ego-vehicle sensors, people tend to overlook an alternative approach to leverage …

We propose ImGeoNet, a multi-view image-based 3D object detection framework that
models a 3D space by an image-induced geometry-aware voxel representation. Unlike …

Roadside camera-driven 3D object detection is a crucial task in intelligent transportation
systems, which extends the perception range beyond the limitations of vision-centric …

Monocular 3D object detection has seen significant advancements with the incorporation of
depth information. However, there remains a considerable performance gap compared to …

Monocular online map segmentation is of great significance to mapless autonomous driving,
and the core step is the View Transformation Module (VTM), which is used to transfer feature …

This survey explores the adaptation of visual transformer models in Autonomous Driving, a
transition inspired by their success in Natural Language Processing. Surpassing traditional …

Notation conventions for rigid transformations are as diverse as they are fundamental to the
field of robotics. A well-defined convention that is practical, consistent and unambiguous is …

In this article, we explore the domain of 3D object detection, in particular its usage in
autonomous driving systems. To replace expensive LiDAR-based perception systems, the …