In this paper, we propose a weakly supervised deep temporal encoding–decoding solution
for anomaly detection in surveillance videos using multiple instance learning. The proposed …

As video surveillance exponentially increases, a method that automatically detects abnormal
events in video surveillance is essential. Several anomaly detection methods have been …

Video anomaly detection and localization is still a challenging task in the computer vision
field. Previous methods took this task as an outlier detection problem, which computed the …

A key challenge in video anomaly detection is the identification of rare abnormal patterns in
the positive instances as they exhibit only a small variation compared to normal patterns …

Over the past decade, video anomaly detection has been explored with remarkable results.
However, research on methodologies suitable for online performance is still very limited. In …

Video anomaly detection aims to detect the segments containing abnormal events from
video sequence, which is a current research hotspot due to the importance in maintaining …

Anomaly detection is critically important for intelligent surveillance systems to detect in a
timely manner any malicious activities. Many video anomaly detection approaches using …

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

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

Anomaly detection in video surveillance is challenging due to the variety of anomaly types
and definitions, which limit the use of supervised techniques. As such, auto-encoder …