Autonomous driving is a promising way to future safe, efficient, and low-carbon
transportation. Real-time accurate target detection is an essential precondition for the …

Accurately detecting multi-class objects in a single pass is critical but challenging for real-
world autonomous driving scenarios. Several single-class anchor-based methods have …

The 3D object detection is becoming indispensable for environmental perception in
autonomous driving. Light detection and ranging (LiDAR) point clouds often fail to …

3D multi-object detection and tracking is an essential constituent for many applications in
today's world. Object detection is a technology related to computer vision and image …

Situation Awareness (SA) is a process of sensing, understanding and predicting the
environment and is an important component in complex systems. The reception of …

Enhancing original LiDAR point cloud features with virtual points has gained widespread
attention in multimodal information fusion. However, existing methods struggle to leverage …

Fueled by substantial advancements in deep learning, the domain of autonomous driving is
swiftly advancing towards more robust and effective intelligent systems. One of the critical …

In the autonomous driving industry, there is a growing trend to employ long-wave infrared
(LWIR)-based uncooled thermal-imaging cameras, capable of robustly collecting data even …

Currently, there are many kinds of voxel‐based multisensor 3D object detectors, while point‐
based multisensor 3D object detectors have not been fully studied. In this paper, we propose …

Many computer vision applications require multi-object detection, such as robotics,
surveillance, and autonomous vehicles. Hough Transform (HT) is a popular method for …