Unilaterally Aggregated Contrastive Learning with Hierarchical Augmentation for Anomaly Detection-Reference-Cited by-同舟云学术

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Unilaterally Aggregated Contrastive Learning with Hierarchical Augmentation for Anomaly Detection

Published:2023-10-01 Issue: Volume:6 Page:6865-6874
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
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Author:

Wang Guodong¹,Wang Yunhong²,Qin Jie³,Zhang Dongming⁴,Bao Xiuguo⁴,Huang Di¹

Affiliation:

1. Beihang University,State Key Laboratory of Software Development Environment,Beijing,China

2. Beihang University,School of Computer Science and Engineering,Beijing,China

3. NUAA,College of Computer Science and Technology,Nanjing,China

4. Natl. Comp. Net. Emer. Resp. Tech. Team/Coord. Ctr. of China,Beijing,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377073.pdf?arnumber=10377073

Reference68 articles.

1. Directional Self-supervised Learning for Heavy Image Augmentations

2. Curriculum learning

3. Classification-based anomaly detection for general data;Bergman;ICLR,2020

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

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

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