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cs.CV2026
APEX: Assumption-free Projection-based Embedding eXamination Metric for Generative Distribution Evaluation
Caterina Gallegati, Monica Bianchini, Franco Scarselli +2
As generative models achieve unprecedented visual quality, the gold standard for image evaluation remains traditional feature-distribution metrics. However, these metrics are prova…
cs.CV2025
Who Made This? Fake Detection and Source Attribution with Diffusion Features
Simone Bonechi, Paolo Andreini, Barbara Toniella Corradini
The rapid rise of generative models has yielded synthetic images of striking realism, blurring the line between real and fake content. As novel models proliferate, detectors must g…
cs.CV2024
FreeSeg-Diff: Training-Free Open-Vocabulary Segmentation with Diffusion Models
Barbara Toniella Corradini, Mustafa Shukor, Paul Couairon +3
Foundation models have exhibited unprecedented capabilities in tackling many domains and tasks. Models such as CLIP are currently widely used to bridge cross-modal representations,…