Buildings account for a significant portion of the global energy consumption. Forecasting
personnel occupancy is critical for reducing energy consumption in buildings. This study …

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

Occupancy prediction, aiming at predicting the occupancy status within voxelized 3D
environment, is quickly gaining momentum within the autonomous driving community …

The task of vision-based 3D occupancy prediction aims to reconstruct 3D geometry and
estimate its semantic classes from 2D color images, where the 2D-to-3D view transformation …

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

3D occupancy prediction is important for autonomous driving due to its comprehensive
perception of the surroundings. To incorporate sequential inputs, most existing methods fuse …

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

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 attracted intensive attention and shown great superiority in the
development of autonomous driving systems. The fine-grained environmental …

Training deep learning models for semantic occupancy prediction is challenging due to
factors such as a large number of occupancy cells, severe occlusion, limited visual cues …