No Shifted Augmentations (NSA): compact distributions for robust self-supervised Anomaly Detection

no code implementations • 19 Mar 2022 • Mohamed Yousef, Marcel Ackermann, Unmesh Kurup, Tom Bishop

We propose novel architectural modifications to the self-supervised feature learning step, that enable such compact distributions for ID data to be learned.

Out of Distribution (OOD) Detection Self-Supervised Anomaly Detection +2

No Shifted Augmentations (NSA): strong baselines for self-supervised Anomaly Detection

no code implementations • 29 Sep 2021 • Mohamed Yousef, Tom Bishop, Unmesh Kurup

We propose novel architectural modifications to the self-supervised feature learning step, that enable such compact ID distributions to be learned.

Out of Distribution (OOD) Detection Self-Supervised Anomaly Detection +3