RealNet: A Feature Selection Network with Realistic Synthetic Anomaly for Anomaly Detection
Self-supervised feature reconstruction methods have shown promising advances in industrial image anomaly de-tection and localization. Despite this progress, these meth-ods still face challenges in synthesizing realistic and di-verse anomaly samples, as well as addressing the feature redundancy and p...
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| Published in: | Proceedings (IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Online) pp. 16699 - 16708 |
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| Main Authors: | , , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
IEEE
16.06.2024
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| Subjects: | |
| ISSN: | 1063-6919 |
| Online Access: | Get full text |
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