2023
Conference article  Open Access

AIMH Lab approaches for deepfake detection

Coccomini D. A., Caldelli R., Esuli A., Falchi F., Gennaro C., Messina N., Amato G.

Deepfake detection  Computer vision  Syntehthic content detection  Deep Learning 

The creation of highly realistic media known as deepfakes has been facilitated by the rapid development of artificial intelligence technologies, including deep learning algorithms, in recent years. Concerns about the increasing ease of creation and credibility of deepfakes have then been growing more and more, prompting researchers around the world to concentrate their efforts on the field of deepfake detection. In this same context, researchers at ISTI-CNR's AIMH Lab have conducted numerous researches, investigations and proposals to make their own contribution to combating this worrying phenomenon. In this paper, we present the main work carried out in the field of deepfake detection and synthetic content detection, conducted by our researchers and in collaboration with external organizations.

Source: Ital-IA 2023, pp. 432–436, Pisa, Italy, 29-31/05/2023



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BibTeX entry
@inproceedings{oai:it.cnr:prodotti:489897,
	title = {AIMH Lab approaches for deepfake detection},
	author = {Coccomini D. A. and Caldelli R. and Esuli A. and Falchi F. and Gennaro C. and Messina N. and Amato G.},
	booktitle = {Ital-IA 2023, pp. 432–436, Pisa, Italy, 29-31/05/2023},
	year = {2023}
}
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