10 citations · 33 across the 10 of their papers we have counts for
9 papers · 1 filter
Towards Universal GAN Image Detection
Davide Cozzolino, Diego Gragnaniello, Giovanni Poggi +1
The ever higher quality and wide diffusion of fake images have spawn a quest for reliable forensic tools. Many GAN image detectors have been proposed, recently. In real world scena…
Are GAN generated images easy to detect? A critical analysis of the state-of-the-art
Diego Gragnaniello, Davide Cozzolino, Francesco Marra +2
The advent of deep learning has brought a significant improvement in the quality of generated media. However, with the increased level of photorealism, synthetic media are becoming…
Combining PRNU and noiseprint for robust and efficient device source identification
Davide Cozzolino, Francesco Marra, Diego Gragnaniello +2
PRNU-based image processing is a key asset in digital multimedia forensics. It allows for reliable device identification and effective detection and localization of image forgeries…
A Full-Image Full-Resolution End-to-End-Trainable CNN Framework for Image Forgery Detection
Francesco Marra, Diego Gragnaniello, Luisa Verdoliva +1
Due to limited computational and memory resources, current deep learning models accept only rather small images in input, calling for preliminary image resizing. This is not a prob…
Perceptual Quality-preserving Black-Box Attack against Deep Learning Image Classifiers
Diego Gragnaniello, Francesco Marra, Giovanni Poggi +1
Deep neural networks provide unprecedented performance in all image classification problems, taking advantage of huge amounts of data available for training. Recent studies, howeve…
Do GANs leave artificial fingerprints?
Francesco Marra, Diego Gragnaniello, Luisa Verdoliva +1
In the last few years, generative adversarial networks (GAN) have shown tremendous potential for a number of applications in computer vision and related fields. With the current pa…
Analysis of adversarial attacks against CNN-based image forgery detectors
Diego Gragnaniello, Francesco Marra, Giovanni Poggi +1
With the ubiquitous diffusion of social networks, images are becoming a dominant and powerful communication channel. Not surprisingly, they are also increasingly subject to manipul…
Image forgery detection based on the fusion of machine learning and block-matching methods
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. We develop a…
A novel framework for image forgery localization
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 an…