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pro vyhledávání: '"Bonettini, Nicolò"'
Autor:
Oorloff, Trevine, Koppisetti, Surya, Bonettini, Nicolò, Solanki, Divyaraj, Colman, Ben, Yacoob, Yaser, Shahriyari, Ali, Bharaj, Gaurav
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 supervised training to capture the dissonance between the audio and vi
Externí odkaz:
http://arxiv.org/abs/2406.02951
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 the movie industry and for artistic purposes. However, they also prove
Externí odkaz:
http://arxiv.org/abs/2203.02246
Autor:
Cannas, Edoardo Daniele, Bonettini, Nicolò, Mandelli, Sara, Bestagini, Paolo, Tubaro, Stefano
Publikováno v:
in IEEE Access, vol. 10, pp. 33882-33899, 2022
Synthetic Aperture Radar (SAR) images are a valuable asset for a wide variety of tasks. In the last few years, many websites have been offering them for free in the form of easy to manage products, favoring their widespread diffusion and research wor
Externí odkaz:
http://arxiv.org/abs/2201.02409
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 recognition, face detection, etc.). Motivated by these astonishing results
Externí odkaz:
http://arxiv.org/abs/2009.12088
Autor:
Bonettini, Nicolò, Cannas, Edoardo Daniele, Mandelli, Sara, Bondi, Luca, Bestagini, Paolo, Tubaro, Stefano
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.). These methods enable anyone to easily edit faces in video sequences with i
Externí odkaz:
http://arxiv.org/abs/2004.07676
The advent of Generative Adversarial Network (GAN) architectures has given anyone the ability of generating incredibly realistic synthetic imagery. The malicious diffusion of GAN-generated images may lead to serious social and political consequences
Externí odkaz:
http://arxiv.org/abs/2004.07682
Autor:
Barni, Mauro, Bondi, Luca, Bonettini, Nicolò, Bestagini, Paolo, Costanzo, Andrea, Maggini, Marco, Tondi, Benedetta, Tubaro, Stefano
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 through the years. The ability of detecting whether an image has been co
Externí odkaz:
http://arxiv.org/abs/1708.00930
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