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cs.CV2026

CUPID: Reconstructing UV Texture Maps for Interpretable Person-of-Interest Deepfake Detection

Giovanni Affatato, Sara Mandelli, Edoardo Daniele Cannas +2

Deepfakes targeting a high-profile individual, known as Person-of-Interest (POI), are a threat to modern democracies and societies. Current POI deepfake detection methods still str…

cs.CV2025

Beyond Spectral Peaks: Interpreting the Cues Behind Synthetic Image Detection

Sara Mandelli, Diego Vila-Portela, David Vázquez-Padín +2

Over the years, the forensics community has proposed several deep learning-based detectors to mitigate the risks of generative AI. Recently, frequency-domain artifacts (particularl…

cs.CV2025

Leveraging Land Cover Priors for Isoprene Emission Super-Resolution

Christopher Ummerle, Antonio Giganti, Sara Mandelli +2

Remote sensing plays a crucial role in monitoring Earth's ecosystems, yet satellite-derived data often suffer from limited spatial resolution, restricting their applicability in at…

cs.CV2025

Hiding Local Manipulations on SAR Images: a Counter-Forensic Attack

Sara Mandelli, Edoardo Daniele Cannas, Paolo Bestagini +2

The vast accessibility of Synthetic Aperture Radar (SAR) images through online portals has propelled the research across various fields. This widespread use and easy availability h…

cs.CV2024

Explainable Artifacts for Synthetic Western Blot Source Attribution

João Phillipe Cardenuto, Sara Mandelli, Daniel Moreira +3

Recent advancements in artificial intelligence have enabled generative models to produce synthetic scientific images that are indistinguishable from pristine ones, posing a challen…

cs.CV2024

Localization of Synthetic Manipulations in Western Blot Images

Anmol Manjunath, Viola Negroni, Sara Mandelli +2

Recent breakthroughs in deep learning and generative systems have significantly fostered the creation of synthetic media, as well as the local alteration of real content via the in…