Machine vision based vehicle counting and traffic flow estimation are challenging problems
especially for dense traffic scenarios. Previous line of interest (LOI) counting methods rarely …

A wide variety of vehicle detection approaches using the deep convolutional neural network
(CNN) have achieved great success in recent years. However, the existing CNN-based …

In the era of emotional consumption, it has become a hot topic that commodities meet
consumers' emotional needs. As a necessity of life, the car also needs to meet the needs of …

A vehicle detection algorithm is an indispensable component of intelligent traffic
management and control systems, influencing the efficiency and functionality of the system …

The next generation of intelligent traffic signal control systems needs multi-object tracking
(MOT) algorithms that can track vehicles hundreds of meters away from traffic intersections …

Night-time vehicle detection plays a vital role due to the high incidence of abnormal events
in our daily security field. However, existing studies mainly focus on vehicle detection in …

Recent works have shown that combining object detection and tracking tasks, in the case of
video data, results in higher performance for both tasks, but they require a high frame-rate as …

This paper proposes a method exploiting temporal context with an attention mechanism for
detecting objects in real-time in a live streaming video. Video object detection is challenging …

Tracking multiple athletes in sports videos is a very challenging Multi-Object Tracking (MOT)
task, as athletes generally share high similarity in appearance with large deformations. In …

Video object detection is a widely studied topic and has made significant progress in the
past decades. However, the feature extraction and calculations in existing video object …