論文速讀:Attribute Restoration Framework for Anomaly Detection
這一篇是近期reconstruction-based 在anomaly detection上有較大突破的一篇，想法很有意思，將傳統reconstruction task 變成 restoration task：在喂入encoder 之前除去input x的某些屬性變成 (比如去除顏色，像素等)，再喂入encoder，如下圖, 而非重瞳的input直接喂入encoder 進行reconstruct
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相關文章
- 1. 【論文速讀】DEEP SEMI-SUPERVISED ANOMALY DETECTION
- 2. [論文閱讀筆記]Learning Memory-guided Normality for Anomaly Detection
- 3. 論文速讀:Deep Anomaly Detection Using Geometric Transformations [2018 NPIS]
- 4. 論文速讀:Adversarially Learned One-Class Classifier for Novelty Detection [CVPR 2018]
- 5. 【PaperReading】System Log Analysis for Anomaly Detection
- 6. 論文譯文《ANOMALY DETECTION WITH GENERATIVE ADVERSARIAL NETWORKS》
- 7. Anomaly Detection for Business Metrics with R
- 8. Deep Anomaly Detection with Deviation Networks 論文筆記
- 9. Anomaly Detection with partially Observed Anomalies論文筆記
- 10. Label Decoupling Framework for Salient Object Detection 論文閱讀記錄