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A review of deep learning-based approaches for deepfake content detection

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Author(s):
Passos, Leandro A. ; Jodas, Danilo ; Costa, Kelton A. P. ; Souza, Luis A. ; Rodrigues, Douglas ; Del Ser, Javier ; Camacho, David ; Papa, Joao Paulo
Total Authors: 8
Document type: Journal article
Source: EXPERT SYSTEMS; v. 41, n. 8, p. 34-pg., 2024-02-22.
Abstract

Recent advancements in deep learning generative models have raised concerns as they can create highly convincing counterfeit images and videos. This poses a threat to people's integrity and can lead to social instability. To address this issue, there is a pressing need to develop new computational models that can efficiently detect forged content and alert users to potential image and video manipulations. This paper presents a comprehensive review of recent studies for deepfake content detection using deep learning-based approaches. We aim to broaden the state-of-the-art research by systematically reviewing the different categories of fake content detection. Furthermore, we report the advantages and drawbacks of the examined works, and prescribe several future directions towards the issues and shortcomings still unsolved on deepfake detection. (AU)

FAPESP's process: 21/05516-1 - On the application of Explainable Artificial Intelligence (XAI) techniques for generating images from data packages to detect anomalies in computer networks
Grantee:Kelton Augusto Pontara da Costa
Support Opportunities: Regular Research Grants
FAPESP's process: 23/10823-6 - On the Study and Development of Biological Plausible Computational Intelligent Models
Grantee:Leandro Aparecido Passos Junior
Support Opportunities: Scholarships in Brazil - Support Program for Fixating Young Doctors
FAPESP's process: 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?
Grantee:Alexandre Xavier Falcão
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 19/07665-4 - Center for Artificial Intelligence
Grantee:Fabio Gagliardi Cozman
Support Opportunities: Research Grants - Research Program in eScience and Data Science - Research Centers in Engineering Program
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC