activity
20172022
most citedAligned and Non-Aligned Double JPEG Detection Using Convolutional Neural Networks

227 citations · 230 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV20222 cited

Detecting GAN-generated Images by Orthogonal Training of Multiple CNNs

Sara Mandelli, Nicolò Bonettini, Paolo Bestagini +1

In the last few years, we have witnessed the rise of a series of deep learning methods to generate synthetic images that look extremely realistic. These techniques prove useful in…

cs.CV20201 cited

Training CNNs in Presence of JPEG Compression: Multimedia Forensics vs Computer Vision

Sara Mandelli, Nicolò Bonettini, Paolo Bestagini +1

Convolutional Neural Networks (CNNs) have proved very accurate in multiple computer vision image classification tasks that required visual inspection in the past (e.g., object reco…

cs.CV2020

On the use of Benford's law to detect GAN-generated images

Nicolò Bonettini, Paolo Bestagini, Simone Milani +1

The advent of Generative Adversarial Network (GAN) architectures has given anyone the ability of generating incredibly realistic synthetic imagery. The malicious diffusion of GAN-g…

cs.CV2020

Video Face Manipulation Detection Through Ensemble of CNNs

Nicolò Bonettini, Edoardo Daniele Cannas, Sara Mandelli +3

In the last few years, several techniques for facial manipulation in videos have been successfully developed and made available to the masses (i.e., FaceSwap, deepfake, etc.). Thes…

cs.CR2017227 cited

Aligned and Non-Aligned Double JPEG Detection Using Convolutional Neural Networks

Mauro Barni, Luca Bondi, Nicolò Bonettini +5

Due to the wide diffusion of JPEG coding standard, the image forensic community has devoted significant attention to the development of double JPEG (DJPEG) compression detectors th…