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 …

Understanding how the 3D scene evolves is vital for making decisions in autonomous
driving. Most existing methods achieve this by predicting the movements of object boxes …

In contrast to extensive studies on general vision pre-training for scalable visual
autonomous driving remains seldom explored. Visual autonomous driving applications …

The aspiration of the next generation's autonomous driving (AD) technology relies on the
dedicated integration and interaction among intelligent perception, prediction, planning, and …

Understanding how the surrounding environment changes is crucial for performing
downstream tasks safely and reliably in autonomous driving applications. Recent occupancy …

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

Scene completion and forecasting are two popular perception problems in research for
mobile agents like autonomous vehicles. Existing approaches treat the two problems in …

Occupancy prediction plays a pivotal role in autonomous driving. Previous methods typically
construct dense 3D volumes, neglecting the inherent sparsity of the scene and suffering high …

We study a new problem of semantic complete scene forecasting (SCSF) in this work. Given
a 4D dynamic point cloud sequence, our goal is to forecast the complete scene …

World models are receiving increasing attention in autonomous driving for their ability to
predict potential future scenarios. In this paper, we present BEVWorld, a novel approach that …