Abstract Multi-camera Multi-Object Tracking has drawn significant attention in recent years
due to its critical role in surveillance analytics and related fields. Various challenges …

Multi-camera tracking of vehicles on a city-wide level is a core component of modern traffic
monitoring systems. For this task, single-camera tracking failures are the most common …

Identifying unusual driving behaviors exhibited by drivers during driving is essential for
understanding driver behavior and the underlying causes of crashes. Previous studies have …

Ensuring traffic safety and preventing accidents is a critical goal in daily driving, where the
advancement of computer vision technologies can be leveraged to achieve this goal. In this …

This paper introduces our solution for the Track2 in AI City Challenge 2021 (AICITY21). The
Track2 is a vehicle re-identification (ReID) task with both the real-world data and synthetic …

Natural Language (NL) descriptions can be one of the most convenient or the only way to
interact with systems built to understand and detect city scale traffic patterns and vehicle …

Deep learning has been widely utilized in intelligent vehicle systems, particularly in the field
of driver distraction detection. However, existing methods in this application tend to focus …

The human visual system can effortlessly recognize an object under different extrinsic
factors such as lighting, object poses, and background, yet current computer vision systems …

Traffic video analytics has become one of the core components in the evolution of
transportation systems. Artificially intelligent traffic management systems apply computer …

Motion Prediction (MP) of multiple surrounding agents in physical environments, and
accurate trajectory forecasting, is a crucial task for Autonomous Driving Stacks (ADS) and …