1 citations · 1 across the 2 of their papers we have counts for
6 papers
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…
A Modified Fourier-Mellin Approach for Source Device Identification on Stabilized Videos
Sara Mandelli, Fabrizio Argenti, Paolo Bestagini +3
To decide whether a digital video has been captured by a given device, multimedia forensic tools usually exploit characteristic noise traces left by the camera sensor on the acquir…
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…
CNN-based fast source device identification
Sara Mandelli, Davide Cozzolino, Paolo Bestagini +2
Source identification is an important topic in image forensics, since it allows to trace back the origin of an image. This represents a precious information to claim intellectual p…
Interpolation and Denoising of Seismic Data using Convolutional Neural Networks
Sara Mandelli, Vincenzo Lipari, Paolo Bestagini +1
Seismic data processing algorithms greatly benefit from regularly sampled and reliable data. Therefore, interpolation and denoising play a fundamental role as one of the starting s…
Facing Device Attribution Problem for Stabilized Video Sequences
Sara Mandelli, Paolo Bestagini, Luisa Verdoliva +1
A problem deeply investigated by multimedia forensics researchers is the one of detecting which device has been used to capture a video. This enables to trace down the owner of a v…