IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing-Reference-Cited by-同舟云学术

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IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing

Published:2024-05 Issue:5 Volume:54 Page:2720-2733
ISSN:2168-2267
Container-title:IEEE Transactions on Cybernetics
language:
Short-container-title:IEEE Trans. Cybern.

Author:

Xie Guoyang¹^ORCID,Wang Jinbao²^ORCID,Liu Jiaqi²^ORCID,Lyu Jiayi³,Liu Yong⁴,Wang Chengjie⁴^ORCID,Zheng Feng²^ORCID,Jin Yaochu⁵^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

2. Department of Computer Science, University of Surrey, Guildford, U.K.

3. School of Engineering Science, University of Chinese Academy of Sciences, Beijing, China

4. Youtu Lab, Tencent, Shenzhen, China

5. School of Engineering, Westlake University, Hangzhou, China

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221036/10500879/10443076.pdf?arnumber=10443076

Reference102 articles.

1. The MVTec Anomaly Detection Dataset: A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection

2. Beyond Dents and Scratches: Logical Constraints in Unsupervised Anomaly Detection and Localization

3. MVTec AD — A Comprehensive Real-World Dataset for Unsupervised Anomaly Detection

4. Uninformed Students: Student-Teacher Anomaly Detection With Discriminative Latent Embeddings

5. The MVTec 3D-AD dataset for unsupervised 3D anomaly detection and localization;Bergmann;arXiv:2112.09045,2021

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