no code implementations • 30 Nov 2023 • Davide Cozzolino, Giovanni Poggi, Riccardo Corvi, Matthias Nießner, Luisa Verdoliva
Aim of this work is to explore the potential of pre-trained vision-language models (VLMs) for universal detection of AI-generated images.
no code implementations • 21 Sep 2023 • Davide Cozzolino, Koki Nagano, Lucas Thomaz, Angshul Majumdar, Luisa Verdoliva
The Video and Image Processing (VIP) Cup is a student competition that takes place each year at the IEEE International Conference on Image Processing.
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.
no code implementations • CVPR 2023 • Fabrizio Guillaro, Davide Cozzolino, Avneesh Sud, Nicholas Dufour, Luisa Verdoliva
In this paper we present TruFor, a forensic framework that can be applied to a large variety of image manipulation methods, from classic cheapfakes to more recent manipulations based on deep learning.
Ranked #1 on Image Manipulation Detection on Columbia
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).
1 code implementation • 5 Oct 2022 • Hannes Mareen, Dante Vanden Bussche, Fabrizio Guillaro, Davide Cozzolino, Glenn Van Wallendael, Peter Lambert, Luisa Verdoliva
In an attempt to fight fake news, forgery detection and localization methods were designed.
no code implementations • 28 Sep 2022 • Alessandro Pianese, Davide Cozzolino, Giovanni Poggi, Luisa Verdoliva
Thanks to recent advances in deep learning, sophisticated generation tools exist, nowadays, that produce extremely realistic synthetic speech.
1 code implementation • 6 Apr 2022 • Davide Cozzolino, Alessandro Pianese, Matthias Nießner, Luisa Verdoliva
The aim of this work is to propose a deepfake detector that can cope with the wide variety of manipulation methods and scenarios encountered in the real world.
no code implementations • 23 Dec 2021 • Davide Cozzolino, Diego Gragnaniello, Giovanni Poggi, Luisa Verdoliva
The ever higher quality and wide diffusion of fake images have spawn a quest for reliable forensic tools.
no code implementations • 16 Dec 2021 • Sara Mandelli, Davide Cozzolino, Edoardo D. Cannas, Joao P. Cardenuto, Daniel Moreira, Paolo Bestagini, Walter J. Scheirer, Anderson Rocha, Luisa Verdoliva, Stefano Tubaro, Edward J. Delp
As a matter of fact, the generation of synthetic content is not restricted to multimedia data like videos, photographs or audio sequences, but covers a significantly vast area that can include biological images as well, such as western blot and microscopic images.
1 code implementation • 6 Apr 2021 • Diego Gragnaniello, Davide Cozzolino, Francesco Marra, Giovanni Poggi, Luisa Verdoliva
The advent of deep learning has brought a significant improvement in the quality of generated media.
1 code implementation • ICCV 2021 • Davide Cozzolino, Andreas Rössler, Justus Thies, Matthias Nießner, Luisa Verdoliva
A major challenge in DeepFake forgery detection is that state-of-the-art algorithms are mostly trained to detect a specific fake method.
1 code implementation • 31 Jan 2020 • Sara Mandelli, Davide Cozzolino, Paolo Bestagini, Luisa Verdoliva, Stefano Tubaro
Source identification is an important topic in image forensics, since it allows to trace back the origin of an image.
no code implementations • 17 Jan 2020 • Davide Cozzolino, Francesco Marra, Diego Gragnaniello, Giovanni Poggi, Luisa Verdoliva
PRNU-based image processing is a key asset in digital multimedia forensics.
no code implementations • 27 Nov 2019 • Davide Cozzolino, Justus Thies, Andreas Rössler, Matthias Nießner, Luisa Verdoliva
Given a GAN-generated image, we insert the traces of a specific camera model into it and deceive state-of-the-art detectors into believing the image was acquired by that model.
14 code implementations • 25 Jan 2019 • Andreas Rössler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, Matthias Nießner
In particular, the benchmark is based on DeepFakes, Face2Face, FaceSwap and NeuralTextures as prominent representatives for facial manipulations at random compression level and size.
Ranked #1 on DeepFake Detection on FaceForensics
no code implementations • 6 Dec 2018 • Davide Cozzolino, Justus Thies, Andreas Rössler, Christian Riess, Matthias Nießner, Luisa Verdoliva
We devise a learning-based forensic detector which adapts well to new domains, i. e., novel manipulation methods and can handle scenarios where only a handful of fake examples are available during training.
1 code implementation • 28 Nov 2018 • Sergio Vitale, Davide Cozzolino, Giuseppe Scarpa, Luisa Verdoliva, Giovanni Poggi
We propose a new method for SAR image despeckling which leverages information drawn from co-registered optical imagery.
no code implementations • 29 Aug 2018 • Davide Cozzolino, Luisa Verdoliva
Camera fingerprints are precious tools for a number of image forensics tasks.
2 code implementations • 25 Aug 2018 • Davide Cozzolino, Luisa Verdoliva
Forensic analyses of digital images rely heavily on the traces of in-camera and out-camera processes left on the acquired images.
no code implementations • 24 Mar 2018 • Andreas Rössler, Davide Cozzolino, Luisa Verdoliva, Christian Riess, Justus Thies, Matthias Nießner
Research on the detection of face manipulations has been seriously hampered by the lack of adequate datasets.
no code implementations • 18 Sep 2017 • Giuseppe Scarpa, Sergio Vitale, Davide Cozzolino
We recently proposed a convolutional neural network (CNN) for remote sensing image pansharpening obtaining a significant performance gain over the state of the art.
no code implementations • 29 Aug 2017 • Dario D'Avino, Davide Cozzolino, Giovanni Poggi, Luisa Verdoliva
Video forgery detection is becoming an important issue in recent years, because modern editing software provide powerful and easy-to-use tools to manipulate videos.
no code implementations • 14 Mar 2017 • Luca D'Amiano, Davide Cozzolino, Giovanni Poggi, Luisa Verdoliva
We propose a new algorithm for the reliable detection and localization of video copy-move forgeries.
no code implementations • 14 Mar 2017 • Davide Cozzolino, Giovanni Poggi, Luisa Verdoliva
Local descriptors based on the image noise residual have proven extremely effective for a number of forensic applications, like forgery detection and localization.
no code implementations • 11 Sep 2015 • Luisa Verdoliva, Davide Cozzolino, Giovanni Poggi
We propose a new algorithm for fast approximate nearest neighbor search based on the properties of ordered vectors.
no code implementations • 27 Nov 2013 • Davide Cozzolino, Diego Gragnaniello, Luisa Verdoliva
Dense local descriptors and machine learning have been used with success in several applications, like classification of textures, steganalysis, and forgery detection.
no code implementations • 27 Nov 2013 • Davide Cozzolino, Diego Gragnaniello, Luisa Verdoliva
Image forgery localization is a very active and open research field for the difficulty to handle the large variety of manipulations a malicious user can perform by means of more and more sophisticated image editing tools.