Surveillance cameras have been increasingly used in many public and private spaces in
recent years to increase the security of those areas. Although many companies still recruit …

We present adversarial event prediction (AEP), a novel approach to detecting abnormal
events through an event prediction setting. Given normal event samples, AEP derives the …

In skeleton-based action recognition, graph convolutional networks (GCNs), which model
human body skeletons using graphical components such as nodes and connections, have …

Abnormal activity may indicate threats and risks to others. An anomaly can be defined as
something that deviates from what is expected, common, or normal. Because it is difficult to …

Given the scarcity of annotated datasets, learning the context-dependency of anomalous
events as well as mitigating false alarms represent challenges in the task of anomalous …

As the surveillance devices proliferate, various machine learning approaches for video
anomaly detection have been attempted. We propose a hybrid deep learning model …

In this paper, we propose adversarial predictive coding (APC), a novel method for detecting
abnormal events. Abnormal event detection (AED) is to identify unobserved events from a …

Ensuring traffic safety is crucial, which necessitates the detection and prevention of road
surface defects. As a result, there has been a growing interest in the literature on the subject …

In the past few years, the performance of road defect detection has been remarkably
improved thanks to advancements in various studies on computer vision and deep learning …

Video surveillance for real-world anomaly detection and prevention using deep learning is
an important and difficult research area. It is imperative to detect and prevent anomalies to …