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20132026
most citedMedia Forensics and DeepFakes: an overview

952 citations · 2.4k across the 45 of their papers we have counts for

collaborators
Showing 2023Show all

6 papers · 1 filter

cs.CV2023★ 3 cited

Raising the Bar of AI-generated Image Detection with CLIP

Davide Cozzolino, Giovanni Poggi, Riccardo Corvi +2

The aim of this work is to explore the potential of pre-trained vision-language models (VLMs) for universal detection of AI-generated images. We develop a lightweight detection str…

cs.CV2023★ 1 cited

Synthetic Image Detection: Highlights from the IEEE Video and Image Processing Cup 2022 Student Competition

Davide Cozzolino, Koki Nagano, Lucas Thomaz +2

The Video and Image Processing (VIP) Cup is a student competition that takes place each year at the IEEE International Conference on Image Processing. The 2022 IEEE VIP Cup asked u…

cs.CR2023

Information Forensics and Security: A quarter-century-long journey

Mauro Barni, Patrizio Campisi, Edward J. Delp +7

Information Forensics and Security (IFS) is an active R&D area whose goal is to ensure that people use devices, data, and intellectual properties for authorized purposes and to fac…

eess.IV2023★ 1 cited

M3Dsynth: A dataset of medical 3D images with AI-generated local manipulations

Giada Zingarini, Davide Cozzolino, Riccardo Corvi +2

The ability to detect manipulated visual content is becoming increasingly important in many application fields, given the rapid advances in image synthesis methods. Of particular c…

cs.CV2023★ 3 cited

Intriguing properties of synthetic images: from generative adversarial networks to diffusion models

Riccardo Corvi, Davide Cozzolino, Giovanni Poggi +2

Detecting fake images is becoming a major goal of computer vision. This need is becoming more and more pressing with the continuous improvement of synthesis methods based on Genera…

cs.CV2023★ 2 cited

Learning Pairwise Interaction for Generalizable DeepFake Detection

Ying Xu, Kiran Raja, Luisa Verdoliva +1

A fast-paced development of DeepFake generation techniques challenge the detection schemes designed for known type DeepFakes. A reliable Deepfake detection approach must be agnosti…