Zobrazeno 1 - 10
of 2 183
pro vyhledávání: '"Tubaro, P."'
Autor:
Cannas, Edoardo Daniele, Mandelli, Sara, Popovic, Natasa, Alkhateeb, Ayman, Gnutti, Alessandro, Bestagini, Paolo, Tubaro, Stefano
In this paper, we investigate the counter-forensic effects of the forthcoming JPEG AI standard based on neural image compression, focusing on two critical areas: deepfake image detection and image splicing localization. Neural image compression lever
Externí odkaz:
http://arxiv.org/abs/2412.03261
Autor:
Casilli, Antonio A., Tubaro, Paola, Cornet, Maxime, Ludec, Clément Le, Torres-Cierpe, Juana, Braz, Matheus Viana
Labor plays a major, albeit largely unrecognized role in the development of artificial intelligence. Machine learning algorithms are predicated on data-intensive processes that rely on humans to execute repetitive and difficult-to-automate, but no le
Externí odkaz:
http://arxiv.org/abs/2410.14230
Autor:
Salvi, Davide, Leonzio, Daniele Ugo, Giganti, Antonio, Eutizi, Claudio, Mandelli, Sara, Bestagini, Paolo, Tubaro, Stefano
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 valuable insights for various applications, including legal proceedings and
Externí odkaz:
http://arxiv.org/abs/2410.06221
While much has been written about the problem of information overload in news and social media, little attention has been paid to its consequence in science. Scientific literature, however, has witnessed decades of exponential growth, to the point th
Externí odkaz:
http://arxiv.org/abs/2410.00788
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 approaches to this challenge involve incorporating diverse data into th
Externí odkaz:
http://arxiv.org/abs/2409.17598
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 these systems have to face is the generalization over unseen data to i
Externí odkaz:
http://arxiv.org/abs/2409.16077
Publikováno v:
Ricardo Festi; J{\"o}rg Nowak. As novas infraestruturas produtivas: digitaliza{\c c}{\~a}o do trabalho, e-log{\'i}stica e ind{\'u}stria 4.0, Boitempo, pp.105-120, 2024, 6557173871
AI generates both enthusiasm and disillusionment, with promises that often go unfulfilled. It is therefore not surprising that human labor, which is its fundamental component, is also subject to these same deceptions. The development of "smart techno
Externí odkaz:
http://arxiv.org/abs/2410.03694
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-art models and by lowering the technical proficiency needed to use the
Externí odkaz:
http://arxiv.org/abs/2409.10684
Speech deepfake detection has recently gained significant attention within the multimedia forensics community. Related issues have also been explored, such as the identification of partially fake signals, i.e., tracks that include both real and fake
Externí odkaz:
http://arxiv.org/abs/2408.13784
Autor:
Amerini, Irene, Barni, Mauro, Battiato, Sebastiano, Bestagini, Paolo, Boato, Giulia, Bonaventura, Tania Sari, Bruni, Vittoria, Caldelli, Roberto, De Natale, Francesco, De Nicola, Rocco, Guarnera, Luca, Mandelli, Sara, Marcialis, Gian Luca, Micheletto, Marco, Montibeller, Andrea, Orru', Giulia, Ortis, Alessandro, Perazzo, Pericle, Puglisi, Giovanni, Salvi, Davide, Tubaro, Stefano, Tonti, Claudia Melis, Villari, Massimo, Vitulano, Domenico
AI-generated synthetic media, also called Deepfakes, have significantly influenced so many domains, from entertainment to cybersecurity. Generative Adversarial Networks (GANs) and Diffusion Models (DMs) are the main frameworks used to create Deepfake
Externí odkaz:
http://arxiv.org/abs/2408.00388