Unified Anomaly Detection via Multi-Scale Contrasted Memory
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Deep anomaly detection aims to provide robust and efficient classifiers for zero-shot (unsupervised, UNS) and few-shot (imbalanced supervised, IMS) settings. However, current models still struggle on edge-case normal samples and are often unable to keep high p... ...
