2 citations · 3 across the 3 of their papers we have counts for
4 papers
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…
Incremental learning for the detection and classification of GAN-generated images
Francesco Marra, Cristiano Saltori, Giulia Boato +1
Current developments in computer vision and deep learning allow to automatically generate hyper-realistic images, hardly distinguishable from real ones. In particular, human face g…
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…