3D occupancy prediction holds significant promise in the fields of robot perception and
autonomous driving, which quantifies 3D scenes into grid cells with semantic labels. Recent …

Since real-world machine systems are running in non-stationary environments, Continual
Test-Time Adaptation (CTTA) task is proposed to adapt the pre-trained model to continually …

Currently, existing state-of-the-art 3D object detectors are in two-stage paradigm. These
methods typically comprise two steps: 1) Utilize a region proposal network to propose a …

Multi-modal fusion is a promising approach to boost the autonomous driving performance
and has already received a large amount of attention. Meanwhile, to increase driving …

In the near future, autonomous vehicles with full self-driving features will populate our public
roads. However, fully autonomous cars will require robust perception systems to safely …

Robots navigating autonomously need to perceive and track the motion of objects and other
agents in its surroundings. This information enables planning and executing robust and safe …

Multi-modal fusion overcomes the inherent limitations of single-sensor perception in 3D
object detection of autonomous driving. The fusion of 4D Radar and LiDAR can boost the …

Autonomous Vehicles (AVs) have the potential to solve many traffic problems, such as
accidents, congestion and pollution. However, there are still challenges to overcome, for …

Monocular 3D object detection has the merit of low cost and can be served as an auxiliary
module for autonomous driving system, becoming a growing concern in recent years. In this …

Abstract Machine learning is driving development across many fields in science and
engineering. A simple and efficient programming language could accelerate applications of …