activity
20242026
collaborators

10 papers

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.SD2025

Phoneme-Level Analysis for Person-of-Interest Speech Deepfake Detection

Davide Salvi, Viola Negroni, Sara Mandelli +2

Recent advances in generative AI have made the creation of speech deepfakes widely accessible, posing serious challenges to digital trust. To counter this, various speech deepfake…

eess.AS2025

Adaptive Mixture of Low-Rank Experts for Robust Audio Spoofing Detection

Qixian Chen, Yuxiong Xu, Sara Mandelli +2

In audio spoofing detection, most studies rely on clean datasets, making models susceptible to real-world post-processing attacks, such as channel compression and noise. To overcom…

cs.MM2025

WILD: a new in-the-Wild Image Linkage Dataset for synthetic image attribution

Pietro Bongini, Sara Mandelli, Andrea Montibeller +14

Synthetic image source attribution is an open challenge, with an increasing number of image generators being released yearly. The complexity and the sheer number of available gener…

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…