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 …

Multi-object tracking (MOT) aims to associate target objects across video frames in order to
obtain entire moving trajectories. With the advancement of deep neural networks and the …

Multi-object tracking (MOT) is an important topic and critical task related to both static and
moving camera applications, such as traffic flow analysis, autonomous driving and robotic …

Multi-object tracking in unmanned aerial vehicle (UAV) videos is an important vision task
and can be applied in a wide range of applications. However, conventional multi-object …

Any intelligent traffic monitoring system must be able to detect anomalies such as traffic
accidents in real-time. In this paper, we propose a Decision-Tree enabled approach …

Vehicle tracking is an essential task in the multi-object tracking (MOT) field. A distinct
characteristic in vehicle tracking is that the trajectories of vehicles are fairly smooth in both …

We tackle the complex problem of detecting and recognising anomalies in surveillance
videos at the frame level, utilising only video-level supervision. We introduce the novel …

Abstract The AI City Challenge has been created to accelerate intelligent video analysis that
helps make cities smarter and safer. With millions of traffic video cameras acting as sensors …

Multi-object tracking (MOT) is an essential task in the computer vision field. With the fast
development of deep learning technology in recent years, MOT has achieved great …

Automatic detection, localization and interpretation of an unusual event in a sequence of
video is a challenging task due to its equivocal and complex nature. The development of …