Weakly-supervised Video Anomaly Detection (W-VAD) aims to detect abnormal events in
videos given only video-level labels for training. Recent methods relying on multiple …

Reconstruction-based and prediction-based approaches are widely used for video anomaly
detection (VAD) in smart city surveillance applications. However, neither of these …

Detecting suspicious activities in surveillance videos is a longstanding problem in real-time
surveillance that leads to difficulties in detecting crimes. Hence, we propose a novel …

Video anomaly detection and localization is one of the key components of the intelligent
video surveillance system. Video anomaly detection refers to the process of spatiotemporal …

The aim of surveillance services is to detect anomalous events that occur in given
surveillance videos. Most existing video anomaly detection methods rely on minimizing …

Outdoor fall detection, in the context of accidents, such as falling from heights or in water, is
a research area that has not received as much attention as other automated surveillance …

Semi-supervised learning suffers from the imbalance of labeled and unlabeled training data
in the video surveillance scenario. In this paper, we propose a new semi-supervised …

Autonomous vehicles (AVs) have the potential to revolutionize transportation. However,
ensuring passenger safety within these vehicles in the absence of a dedicated onboard …

Industrial image anomaly detection (AD) is a critical issue that has been investigated in
different research areas. Many works have attempted to detect anomalies by simulating …

Human society significantly relies on CCTV cameras to maintain a high standard of security.
CCTV footage is usually only utilized a few hours or days following an incident. Although it …