4 citations · 17 across the 27 of their papers we have counts for
17 papers · 1 filter
Is JPEG AI going to change image forensics?
Edoardo Daniele Cannas, Sara Mandelli, Nataša Popović +4
In this paper, we investigate the counter-forensic effects of the new JPEG AI standard based on neural image compression, focusing on two critical areas: deepfake image detection a…
Comparative Analysis of ASR Methods for Speech Deepfake Detection
Davide Salvi, Amit Kumar Singh Yadav, Kratika Bhagtani +3
Recent techniques for speech deepfake detection often rely on pre-trained self-supervised models. These systems, initially developed for Automatic Speech Recognition (ASR), have pr…
POLIPHONE: A Dataset for Smartphone Model Identification from Audio Recordings
Davide Salvi, Daniele Ugo Leonzio, Antonio Giganti +4
When dealing with multimedia data, source attribution is a key challenge from a forensic perspective. This task aims to determine how a given content was captured, providing valuab…
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…
DiffSSD: A Diffusion-Based Dataset For Speech Forensics
Kratika Bhagtani, Amit Kumar Singh Yadav, Paolo Bestagini +1
Diffusion-based speech generators are ubiquitous. These methods can generate very high quality synthetic speech and several recent incidents report their malicious use. To counter…
Freeze and Learn: Continual Learning with Selective Freezing for Speech Deepfake Detection
Davide Salvi, Viola Negroni, Luca Bondi +2
In speech deepfake detection, one of the critical aspects is developing detectors able to generalize on unseen data and distinguish fake signals across different datasets. Common a…
FakeMusicCaps: a Dataset for Detection and Attribution of Synthetic Music Generated via Text-to-Music Models
Luca Comanducci, Paolo Bestagini, Stefano Tubaro
Text-To-Music (TTM) models have recently revolutionized the automatic music generation research field. Specifically, by reaching superior performances to all previous state-of-the-…
Leveraging Mixture of Experts for Improved Speech Deepfake Detection
Viola Negroni, Davide Salvi, Alessandro Ilic Mezza +2
Speech deepfakes pose a significant threat to personal security and content authenticity. Several detectors have been proposed in the literature, and one of the primary challenges…
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…
Analyzing the Impact of Splicing Artifacts in Partially Fake Speech Signals
Viola Negroni, Davide Salvi, Paolo Bestagini +1
Speech deepfake detection has recently gained significant attention within the multimedia forensics community. Related issues have also been explored, such as the identification of…
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…
When Synthetic Traces Hide Real Content: Analysis of Stable Diffusion Image Laundering
Sara Mandelli, Paolo Bestagini, Stefano Tubaro
In recent years, methods for producing highly realistic synthetic images have significantly advanced, allowing the creation of high-quality images from text prompts that describe t…
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…
FairSSD: Understanding Bias in Synthetic Speech Detectors
Amit Kumar Singh Yadav, Kratika Bhagtani, Davide Salvi +2
Methods that can generate synthetic speech which is perceptually indistinguishable from speech recorded by a human speaker, are easily available. Several incidents report misuse of…
Spectrogram-Based Detection of Auto-Tuned Vocals in Music Recordings
Mahyar Gohari, Paolo Bestagini, Sergio Benini +1
In the domain of music production and audio processing, the implementation of automatic pitch correction of the singing voice, also known as Auto-Tune, has significantly transforme…
Compression Robust Synthetic Speech Detection Using Patched Spectrogram Transformer
Amit Kumar Singh Yadav, Ziyue Xiang, Kratika Bhagtani +3
Many deep learning synthetic speech generation tools are readily available. The use of synthetic speech has caused financial fraud, impersonation of people, and misinformation to s…
Listening Between the Lines: Synthetic Speech Detection Disregarding Verbal Content
Davide Salvi, Temesgen Semu Balcha, Paolo Bestagini +1
Recent advancements in synthetic speech generation have led to the creation of forged audio data that are almost indistinguishable from real speech. This phenomenon poses a new cha…