Video anomaly detection in surveillance systems with only video-level labels (ie weakly
supervised) is challenging. This is due to (i) the complex integration of a large variety of …

Surveillance cameras are installed across various sectors of a smart city in order to capture
ongoing events for monitoring purposes. The analysis of these surveillance videos is an …

Video anomaly detection aims to develop automated models capable of identifying
abnormal events in surveillance videos. The benchmark setup for this task is extremely …

Video anomaly detection under weak supervision is complicated due to the difficulties in
identifying the anomaly and normal instances during training, hence, resulting in non …

Weakly supervised video anomaly detection aims to identify abnormal events in videos
using only video-level labels. Recently, two-stage self-training methods have achieved …

Weakly supervised detection of anomalies in surveillance videos is a challenging task.
Going beyond existing works that have deficient capabilities to localize anomalies in long …

Anomaly detection with weakly supervised video-level labels is typically formulated as a
multiple instance learning (MIL) problem, in which we aim to identify snippets containing …

Anomaly detection with weakly supervised video-level labels is typically formulated as a
multiple instance learning (MIL) problem, in which we aim to identify snippets containing …

Video anomaly detection under weak supervision presents significant challenges,
particularly due to the lack of frame-level annotations during training. While prior research …

Anomaly detection in surveillance videos is a challenging task due to the diversity of
anomalous video content and duration. In this paper, we consider video anomaly detection …