no code implementations • 30 Apr 2024 • Diangarti Tariang, Riccardo Corvi, Davide Cozzolino, Giovanni Poggi, Koki Nagano, Luisa Verdoliva
In this work we present an overview of approaches for the detection and attribution of synthetic images and highlight their strengths and weaknesses.
no code implementations • 30 Nov 2023 • Davide Cozzolino, Giovanni Poggi, Riccardo Corvi, Matthias Nießner, Luisa Verdoliva
The aim of this work is to explore the potential of pre-trained vision-language models (VLMs) for universal detection of AI-generated images.
1 code implementation • 14 Sep 2023 • Giada Zingarini, Davide Cozzolino, Riccardo Corvi, Giovanni Poggi, Luisa Verdoliva
Here, we investigate this issue and propose M3Dsynth, a large dataset of manipulated Computed Tomography (CT) lung images.
no code implementations • 13 Apr 2023 • Riccardo Corvi, Davide Cozzolino, Giovanni Poggi, Koki Nagano, Luisa Verdoliva
Detecting fake images is becoming a major goal of computer vision.
1 code implementation • 1 Nov 2022 • Riccardo Corvi, Davide Cozzolino, Giada Zingarini, Giovanni Poggi, Koki Nagano, Luisa Verdoliva
Over the past decade, there has been tremendous progress in creating synthetic media, mainly thanks to the development of powerful methods based on generative adversarial networks (GAN).