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cs.CV2025
Correcting Deviations from Normality: A Reformulated Diffusion Model for Multi-Class Unsupervised Anomaly Detection
Farzad Beizaee, Gregory A. Lodygensky, Christian Desrosiers +1
Recent advances in diffusion models have spurred research into their application for Reconstruction-based unsupervised anomaly detection. However, these methods may struggle with m…
cs.CV2025
MAD-AD: Masked Diffusion for Unsupervised Brain Anomaly Detection
Farzad Beizaee, Gregory Lodygensky, Christian Desrosiers +1
Unsupervised anomaly detection in brain images is crucial for identifying injuries and pathologies without access to labels. However, the accurate localization of anomalies in medi…