Image Anomaly Detection
Image Anomaly Detection is a computational framework within the field of computer vision that identifies deviations from normal patterns in visual data by leveraging models trained predominantly on normal instances to detect rare or unseen anomalies.
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2017–2026
804
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MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection
Paul Bergmann, Michael Fauser, David Sattlegger et al. · 2019 · 1.8K citations
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization
Chunliang Li, Kihyuk Sohn, Jinsung Yoon et al. · 2021 · 902 citations
A Unifying Review of Deep and Shallow Anomaly Detection
Proceedings of the IEEE · 2021 · 812 citations · Full text
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Xidian University
Xi'an, China
31 h-index
204 publications
10.6K citations

Chinese Academy of Sciences
Beijing, China
30 h-index
125 publications
11.7K citations
University of Chinese Academy of Sciences
Beijing, China
25 h-index
69 publications
6.4K citations

Universidad de Extremadura
Badajoz, Spain
21 h-index
40 publications
3.9K citations
Mississippi State University
Starkville, United States
21 h-index
33 publications
3.3K citations
Wuhan University
Wuhan, China
19 h-index
61 publications
5.5K citations

Beijing Institute of Technology
Beijing, China
18 h-index
43 publications
3K citations

Northwestern Polytechnical University
Xi'an, China
15 h-index
41 publications
3.1K citations
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90 publications · 10K citations
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Repository · 83 publications · 4.8K citations
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GRSL · 38 publications · 1.8K citations
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26 publications · 836 citations
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