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 …

Vision-language navigation (VLN) requires an agent to navigate through an 3D environment
based on visual observations and natural language instructions. It is clear that the pivotal …

Abstract 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 …

In this paper we present a tensor decomposition and low-rank recovery approach
(LowRankOcc) for vision-based 3D semantic occupancy prediction. Conventional methods …

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 …

Occupancy prediction has increasingly garnered attention in recent years for its fine-grained
understanding of 3D scenes. Traditional approaches typically rely on dense, regular grid …

Given the capability of mitigating the long-tail deficiencies and intricate-shaped absence
prevalent in 3D object detection, occupancy prediction has become a pivotal component in …

Collaborative perception in automated vehicles leverages the exchange of information
between agents aiming to elevate perception results. Previous camera-based collaborative …

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

In autonomous driving, 3D occupancy prediction outputs voxel-wise status and semantic
labels for more comprehensive understandings of 3D scenes compared with traditional …