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

In this paper, we present a framework for the detection of anomalies in video scenes. Both
spatial and temporal features extract and learn through the framework. We employ inception …

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

Automated detection of abnormalities in data has been studied in research area in recent
years because of its diverse applications in practice including video surveillance, industrial …

Identifying suspicious activities or behaviors is essential in the domain of Anomaly Detection
(AD). In crowded scenes, the presence of inter-object occlusions often complicates the …

This paper introduces an innovative end-to-end trainable framework named Dense Attention-
aware Spatio-Temporal Network (DAST-Net) for video anomaly detection. The framework …

As an essential task in computer vision, video anomaly detection technology is used in video
surveillance, scene understanding, road traffic analysis and other fields. However, the …

Video anomaly detection is a challenging task because most anomalies are scarce and non-
deterministic. Many approaches investigate the reconstruction difference between normal …

Video Anomaly detection, aiming to detect the abnormal behaviors in surveillance videos, is
a challenging task since the anomalous events are diversified and complicated in different …

We propose a multi-task learning framework for video anomaly detection based on a novel
pipeline. Our model contains two crossing streams, one stream employs the backbone of …