General world models represent a crucial pathway toward achieving Artificial General
Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual …

This paper explores the emerging knowledge-driven autonomous driving technologies. Our
investigation highlights the limitations of current autonomous driving systems, in particular …

The rise of large foundation models, trained on extensive datasets, is revolutionizing the
field of AI. Models such as SAM, DALL-E2, and GPT-4 showcase their adaptability by …

In the rapidly evolving landscape of autonomous driving, the capability to accurately predict
future events and assess their implications is paramount for both safety and efficiency …

Foundation models have indeed made a profound impact on various fields, emerging as
pivotal components that significantly shape the capabilities of intelligent systems. In the …

World models can foresee the outcomes of different actions, which is of paramount
importance for autonomous driving. Nevertheless, existing driving world models still have …

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

World models simulate future states of the world in response to different actions. They
facilitate interactive content creation and provides a foundation for grounded, long-horizon …

Understanding the evolution of 3D scenes is important for effective autonomous driving.
While conventional methods mode scene development with the motion of individual …

3D semantic occupancy prediction aims to obtain 3D fine-grained geometry and semantics
of the surrounding scene and is an important task for the robustness of vision-centric …