Deep Learning for Video Anomaly Detection: A Review

Northwestern Polytechnical University · Singapore Management University

PubMed
Indexed incrossrefpubmed

Abstract

Video anomaly detection (VAD) aims to discover behaviors or events deviating from the normality in videos. As a long-standing task in the field of computer vision, VAD has witnessed much good progress. In the era of deep learning, with the explosion of architectures of continuously growing capability and capacity, a great variety of deep learning-based methods are constantly emerging for the VAD task, greatly improving the generalization ability of detection algorithms and broadening the application scenarios. Therefore, such a multitude of methods and a large body of literature make a comprehensive survey a pressing necessity. In this article, we present an extensive and comprehensive research review,…

Citation impact

12
total citations
FWCI
136.66
Percentile
100%
References
0
Citations per year

Authors

7

Topics & keywords

Keywords
  • Deep learning
  • Task (project management)
  • Construct (python library)
  • Generalization
  • Anomaly detection
  • Field (mathematics)
No related works found for this paper.

Funding