5 papers
Detecting Localized Deepfakes: How Well Do Synthetic Image Detectors Handle Inpainting?
Serafino Pandolfini, Lorenzo Pellegrini, Matteo Ferrara +1
The rapid progress of generative AI has enabled highly realistic image manipulations, including inpainting and region-level editing. These approaches preserve most of the original…
Generalized Design Choices for Deepfake Detectors
Lorenzo Pellegrini, Serafino Pandolfini, Davide Maltoni +3
The effectiveness of deepfake detection methods often depends less on their core design and more on implementation details such as data preprocessing, augmentation strategies, and…
AI-GenBench: A New Ongoing Benchmark for AI-Generated Image Detection
Lorenzo Pellegrini, Davide Cozzolino, Serafino Pandolfini +5
The rapid advancement of generative AI has revolutionized image creation, enabling high-quality synthesis from text prompts while raising critical challenges for media authenticity…
From Gaming to Research: GTA V for Synthetic Data Generation for Robotics and Navigations
Matteo Scucchia, Matteo Ferrara, Davide Maltoni
In computer vision, the development of robust algorithms capable of generalizing effectively in real-world scenarios more and more often requires large-scale datasets collected und…
Face morphing detection in the presence of printing/scanning and heterogeneous image sources
Matteo Ferrara, Annalisa Franco, Davide Maltoni
Face morphing represents nowadays a big security threat in the context of electronic identity documents as well as an interesting challenge for researchers in the field of face rec…