A semantic understanding of road traffic can help people understand road traffic flow
situations and emergencies more accurately and provide a more accurate basis for anomaly …

Visual change detection, aiming at segmentation of video frames into foreground and
background regions, is one of the elementary tasks in computer vision and video analytics …

The use of object detection algorithms has become extremely important in autonomous
vehicles. Object detection at high accuracy and a fast inference speed is essential for safe …

Simultaneous trajectory prediction for multiple heterogeneous traffic participants is essential
for safe and efficient operation of connected automated vehicles under complex driving …

Radar and camera information fusion sensing methods are used to solve the inherent
shortcomings of the single sensor in severe weather. Our fusion scheme uses radar as the …

Vehicle trajectory prediction is a keystone for the application of the internet of vehicles (IoV).
With the help of deep learning and big data, it is possible to understand the between-vehicle …

As a core function of autonomous driving (AD) and the Internet of Vehicles (IoV), accurately
predicting the trajectory of vehicles can significantly improve traffic safety and reduce crash …

Planning an autonomous vehicle's (AV) path in a space shared with pedestrians requires
reasoning about pedestrians' future trajectories. A practical pedestrian trajectory prediction …

With the rapid development of deep learning in recent years, the level of automatic driving
perception has also increased substantially. However, automatic driving perception under …

In recent years, deep learning technologies for object detection have made great progress
and have powered the emergence of state-of-the-art models to address object detection …