The grid-centric perception is a crucial field for mobile robot perception and navigation.
Nonetheless, the grid-centric perception is less prevalent than object-centric perception as …

In recent years, autonomous driving has garnered escalating attention for its potential to
relieve drivers' burdens and improve driving safety. Vision-based 3D occupancy prediction …

Abstract 3D occupancy perception technology aims to observe and understand dense 3D
environments for autonomous vehicles. Owing to its comprehensive perception capability …

Abstract 3D occupancy-based perception pipeline has significantly advanced autonomous
driving by capturing detailed scene descriptions and demonstrating strong generalizability …

Vision-based occupancy prediction, also known as 3D Semantic Scene Completion (SSC),
presents a significant challenge in computer vision. Previous methods, confined to onboard …

3D Semantic Occupancy Prediction is fundamental for spatial understanding as it provides a
comprehensive semantic cognition of surrounding environments. However, prevalent …

In recent years, 3D object perception has become a crucial component in the development
of autonomous driving systems, providing essential environmental awareness. However, as …

Vision-centric semantic occupancy prediction plays a crucial role in autonomous driving,
which requires accurate and reliable predictions from low-cost sensors. Although having …

The end-to-end autonomous driving paradigm has recently attracted lots of attention due to
its scalability. However, existing methods are constrained by the limited scale of real-world …

Driving World Models (DWMs) have become essential for autonomous driving by enabling
future scene prediction. However, existing DWMs are limited to scene generation and fail to …