12 citations · 14 across the 8 of their papers we have counts for
8 papers
Backbone is All You Need: Assessing Vulnerabilities of Frozen Foundation Models in Synthetic Image Forensics
Chiara Musso, Joy Battocchio, Andrea Montibeller +1
As AI-generated synthetic images become increasingly realistic, Vision Transformers (ViTs) have emerged as a cornerstone of modern deepfake detection. However, the prevailing relia…
Don't Guess, Escalate: Towards Explainable Uncertainty-Calibrated AI Forensic Agents
Giulia Boato, Andrea Montibeller, Edward Delp +2
AI is reshaping the landscape of multimedia forensics. We propose AI forensic agents: reliable orchestrators that select and combine forensic detectors, identify provenance and con…
Advance Fake Video Detection via Vision Transformers
Joy Battocchio, Stefano Dell'Anna, Andrea Montibeller +1
Recent advancements in AI-based multimedia generation have enabled the creation of hyper-realistic images and videos, raising concerns about their potential use in spreading misinf…
TrueFake: A Real World Case Dataset of Last Generation Fake Images also Shared on Social Networks
Stefano Dell'Anna, Andrea Montibeller, Giulia Boato
AI-generated synthetic media are increasingly used in real-world scenarios, often with the purpose of spreading misinformation and propaganda through social media platforms, where…
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…
Deepfake Media Forensics: State of the Art and Challenges Ahead
Irene Amerini, Mauro Barni, Sebastiano Battiato +21
AI-generated synthetic media, also called Deepfakes, have significantly influenced so many domains, from entertainment to cybersecurity. Generative Adversarial Networks (GANs) and…
An Adaptive Method for Camera Attribution under Complex Radial Distortion Corrections
Andrea Montibeller, Fernando Pérez-González
Radial correction distortion, applied by in-camera or out-camera software/firmware alters the supporting grid of the image so as to hamper PRNU-based camera attribution. Existing s…
GPU-accelerated SIFT-aided source identification of stabilized videos
Andrea Montibeller, Cecilia Pasquini, Giulia Boato +2
Video stabilization is an in-camera processing commonly applied by modern acquisition devices. While significantly improving the visual quality of the resulting videos, it has been…