In the realm of modern autonomous driving, the perception system is indispensable for
accurately assessing the state of the surrounding environment, thereby enabling informed …

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 …

Abstract View Transformation Module (VTM), where transformations happen between multi-
view image features and Bird-Eye-View (BEV) representation, is a crucial step in camera …

Long-term temporal fusion is a crucial but often overlooked technique in camera-based
Bird's-Eye-View (BEV) 3D perception. Existing methods are mostly in a parallel manner …

Recently, perception task based on Bird's-Eye View (BEV) representation has drawn more
and more attention, and BEV representation is promising as the foundation for next …

In this paper, we draw inspiration from Alberto Elfes' pioneering work in 1989, where he
introduced the concept of the occupancy grid as World Models for robots. We imbue the …

Multi-vehicle cooperative perception has recently emerged for facilitating long-range and
large-scale perception ability of connected automated vehicles (CAVs). Nonetheless …

Abstract Bird's-eye View (BeV) representations have emerged as the de-facto shared space
in driving applications offering a unified space for sensor data fusion and supporting various …

This paper introduces InverseMatrixVT3D, an efficient method for transforming multi-view
image features into 3D feature volumes for 3D semantic occupancy prediction. Existing …

The recent advances in query-based multi-camera 3D object detection are featured by
initializing object queries in the 3D space, and then sampling features from perspective-view …