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MADPOT: Medical Anomaly Detection with CLIP Adaptation and Partial Optimal Transport
Mahshid Shiri, Cigdem Beyan, Vittorio Murino
Medical anomaly detection (AD) is challenging due to diverse imaging modalities, anatomical variations, and limited labeled data. We propose a novel approach combining visual adapt…
MadCLIP: Few-shot Medical Anomaly Detection with CLIP
Mahshid Shiri, Cigdem Beyan, Vittorio Murino
An innovative few-shot anomaly detection approach is presented, leveraging the pre-trained CLIP model for medical data, and adapting it for both image-level anomaly classification…
A Mutual Information Perspective on Multiple Latent Variable Generative Models for Positive View Generation
Dario Serez, Marco Cristani, Alessio Del Bue +2
In image generation, Multiple Latent Variable Generative Models (MLVGMs) employ multiple latent variables to gradually shape the final images, from global characteristics to finer…