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Unsupervised Anomaly Detection with Specified Settings -- 0.1% anomaly 벤치마크

Unsupervised Anomaly Detection with Specified Settings -- 0.1% anomaly on Cats and Dogs

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AUC-ROC

0.545 0.6542 0.7635 0.8728 0.982 2008-12 2026-09 Isolation Forest — 0.777 (2008-12-15) DAGMM — 0.784 (2018-01-01) RSRAE — 0.982 (2019-03-30) Deep Unsup. — 0.545 (2021-01-05) Shell-Renormalized — 0.866 (2021-05-28) LVAD — 0.981 (2022-10-23) Isolation Forest — 0.777 (2008-12-15) DAGMM — 0.784 (2018-01-01) RSRAE — 0.982 (2019-03-30)
RankModel AUC-ROC Extra Training Data PaperCodeYear
1 RSRAE 0.982 Robust Subspace Recovery Layer for Unsupervised Anomaly Detection dmzou/RSRAE · marrrcin/rsrlayer-pytorch 2019
2 LVAD 0.981 Locally varying distance transform for unsupervised visual anomaly detection wen-yan-lin/LVAD-Locally-Varying-Anomaly-Detection 2022
3 Shell-Renormalized 0.866 Shell Theory: A Statistical Model of Reality wen-yan-lin/shell-theory 2021
4 DAGMM 0.784 Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection danieltan07/dagmm · RomainSabathe/dagmm 2018
5 Isolation Forest 0.777 Isolation forest 2008
6 Deep Unsup. 0.545 Deep unsupervised anomaly detection 2021
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