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

Autonomous driving requires a comprehensive understanding of the surrounding
environment for reliable trajectory planning. Previous works rely on dense rasterized scene …

High-definition (HD) map provides abundant and precise static environmental information of
the driving scene, serving as a fundamental and indispensable component for planning in …

In recent years, vision-centric Bird's Eye View (BEV) perception has garnered significant
interest from both industry and academia due to its inherent advantages, such as providing …

High-definition (HD) map provides abundant and precise environmental information of the
driving scene, serving as a fundamental and indispensable component for planning in …

Abstract 3D Semantic Scene Completion (SSC) has emerged as a nascent and pivotal
undertaking in autonomous driving aiming to predict the voxel occupancy within volumetric …

Autonomous driving requires an accurate and fast 3D perception system that includes 3D
object detection, tracking, and segmentation. Although recent low-cost camera-based …

Early exiting has become a promising approach to im-proving the inference efficiency of
deep networks. By structuring models with multiple classifiers (exits), predictions for" easy" …

Online lane graph construction is a promising but challenging task in autonomous driving.
Previous methods usually model the lane graph at the pixel or piece level, and recover the …

In autonomous driving, the high-definition (HD) map plays a crucial role in localization and
planning. Recently, several methods have facilitated end-to-end online map construction in …