Vision transformer attention with multi-reservoir echo state network for anomaly recognition
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ViT-ARN achieves 88.1% AUC on UCF-Crime.
“ViT-ARN [17] demonstrates strong performance on long-duration datasets such as UCF-Crime (88.1% AUC)”
From A Comprehensive Survey of Transformer-Based Models for Video Anomaly Detection in Surveillance Systems (2025) · cites this paper as [17]
Lightweight temporal reservoirs have an advantage over conventional LSTMs in supervised transformer settings.
“illustrating the advantage of lightweight temporal reservoirs over conventional LSTMs in supervised transformer settings.”
From A Comprehensive Survey of Transformer-Based Models for Video Anomaly Detection in Surveillance Systems (2025) · cites this paper as [17]
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References 62 · Cited by 47
- Authors
- Ullah, W., Hussain, T., & Baik, S. W.
- Affiliations
- Sejong University (KR)
- University of Leeds (GB)
- Corresponding author
- Baik, Sung Wook
- Venue
- Information Processing & Management
- Publisher
- Elsevier BV
- Published
- 2023-05
- Volume
- 60
- Issue
- 3
- Pages
- 103289
- ISSN
- 0020-0271 (ISSN-L)
- 0306-4573
- OpenAlex
- W4319301089
- Cited by
- 47
- References
- 62
- Citations by year
- 2026: 5 · 2025: 15 · 2024: 17 · 2023: 9 · 2022: 1
- FWCI
- 4.34
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Information Processing & Management (publishedVersion)
- Edge Hill University Research Information Repository (Edge Hill University) (submittedVersion)
- Funders
- National Research Foundation of Korea
- Ministry of Science, ICT and Future Planning (2019R1A2B5B01070067)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Anomaly Detection Techniques and Applications
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Human Pose and Action Recognition
- Keywords
- anomaly detection, video surveillance, vision transformer, online anomaly detection, filter pruning, geometric median, vandalism detection, traffic accident detection, smart city surveillance, anomaly classification, resource-constrained devices
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