227 citations · 241 across the 6 of their papers we have counts for
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X-Edit: Detecting and Localizing Edits in Images Altered by Text-Guided Diffusion Models
Valentina Bazyleva, Nicolo Bonettini, Gaurav Bharaj
Text-guided diffusion models have significantly advanced image editing, enabling highly realistic and local modifications based on textual prompts. While these developments expand…
AVFF: Audio-Visual Feature Fusion for Video Deepfake Detection
Trevine Oorloff, Surya Koppisetti, Nicolò Bonettini +5
With the rapid growth in deepfake video content, we require improved and generalizable methods to detect them. Most existing detection methods either use uni-modal cues or rely on…
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…
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…
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…
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…