In this paper, we propose a scene-aware context reasoning method that exploits context
information from visual features for unsupervised abnormal event detection in videos, which …

Abnormal event detection in the surveillance video is an essential but challenging task, and
many methods have been proposed to deal with this problem. The previous methods either …

Video anomaly detection is to automatically identify predefined anomalous contents (eg
abnormal objects, behaviors and scenes) in videos. The performance of video anomaly …

Unsupervised approaches for video anomaly detection may not perform as good as
supervised approaches. However, learning unknown types of anomalies using an …

Most video anomaly detection approaches are based on data-intensive end-to-end trained
neural networks, which extract spatiotemporal features from videos. The extracted feature …

Video anomaly detection is an essential yet challenging task in the multimedia community,
with promising applications in smart cities and secure communities. Existing methods …

Video anomaly detection aims to detect abnormal segments in a video sequence, which is a
key problem in video surveillance. Based on deep prediction methods, we propose a …

Abnormal event detection in video is a challenging vision problem. Most existing
approaches formulate abnormal event detection as an outlier detection task, due to the …

Recent progress in video anomaly detection (VAD) has shown that feature discrimination is
the key to effectively distinguishing anomalies from normal events. We observe that many …

Video surveillance systems are used to enhance the public safety and private assets.
Automatic anomaly detection is vital in such surveillance systems to reduce the human labor …