Traffic safety is a major global concern. Helmet usage is a key factor in preventing head
injuries and fatalities caused by motorcycle accidents. However, helmet usage violations …

Abstract The AI City Challenge's seventh edition emphasizes two domains at the intersection
of computer vision and artificial intelligence-retail business and Intelligent Traffic Systems …

Abstract The task of Naturalistic Driving Action Recognition aims to detect and temporally
localize distracting driving behavior in untrimmed videos. Prior studies have demonstrated …

This study addresses the evolving challenges in urban traffic monitoring detection systems
based on fisheye lens cameras by proposing a framework that improves the efficacy and …

Temporal action localization (TAL) is a prevailing task due to its great application potential.
Existing works in this field mainly suffer from two weaknesses:(1) They often neglect the …

Laboratory safety is a critical area of broad societal concern, particularly in the detection of
abnormal actions. To enhance the efficiency and accuracy of detecting such actions, this …

In recent years, distracted driving has garnered considerable attention as it continues to
pose a significant threat to public safety on the roads. This has increased the need for …

Security and safety rely heavily on anomaly detection in surveillance footage. In this study,
we propose a modified YOLOv8 model for anomaly detection to pinpoint unusual …

When applied to autonomous vehicle (AV) settings, action recognition can enhance an
environment model's situational awareness. This is especially prevalent in scenarios where …