COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection-Reference-Cited by-同舟云学术

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COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection

Published:2024 Issue: Volume:33 Page:2090-2103
ISSN:1057-7149
Container-title:IEEE Transactions on Image Processing
language:
Short-container-title:IEEE Trans. on Image Process.

Author:

Liao Jingyi¹^ORCID,Xu Xun¹^ORCID,Nguyen Manh Cuong¹^ORCID,Goodge Adam¹^ORCID,Foo Chuan Sheng²^ORCID

Affiliation:

1. Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR), Fusionopolis Way, Singapore

2. Institute for Infocomm Research (I2R) and the Centre for Frontier AI Research (CFAR), Agency for Science, Technology and Research (A*STAR), Fusionopolis Way, Singapore

Funder

Agency for Science, Technology and Research (A*STAR) through the Advanced Manufacturing and Engineering (AME) Programmatic Funds

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/83/10346232/10471293.pdf?arnumber=10471293

Reference54 articles.

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

2. Video Behavior Profiling for Anomaly Detection

3. Detecting the Unexpected via Image Resynthesis

4. A Hierarchical Transformation-Discriminating Generative Model for Few Shot Anomaly Detection

5. Registration Based Few-Shot Anomaly Detection

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