Generalized Deepfake Detection Algorithm Based on Inconsistency Between Inner and Outer Faces

Jie Gao, Sara Concas, Giulia Orrù, Xiaoyi Feng, Gian Luca Marcialis, Fabio Roli

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Deepfake refers to using artificial intelligence (AI) and machine learning techniques to create compelling and realistic media content, such as videos, images, or recordings, that appear real but are fake. The most common form of deepfake involves using deep neural networks to replace or superimpose faces in existing videos or images on top of other people’s faces. While this technology can be used for various benign purposes, such as filmmaking or online education, it can also be used maliciously to spread misinformation by creating fake videos or images. Based on the classic deepfake generation process, this paper explores the Inconsistency between inner and outer faces in fake content to find synthetic defects and proposes a general deepfake detection algorithm. Experimental results show that our proposed method has certain advantages, especially regarding cross-method detection performance.

Original languageEnglish
Title of host publicationImage Analysis and Processing - ICIAP 2023 Workshops
EditorsGian Luca Foresti, Andrea Fusiello, Edwin Hancock
PublisherSpringer Science and Business Media Deutschland GmbH
Pages343-355
Number of pages13
ISBN (Print)9783031510229
DOIs
StatePublished - 2024
EventProceedings of the 22nd International Conference on Image Analysis and Processing, ICIAP 2023 - Udine, Italy
Duration: 11 Sep 202315 Sep 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14365 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceProceedings of the 22nd International Conference on Image Analysis and Processing, ICIAP 2023
Country/TerritoryItaly
CityUdine
Period11/09/2315/09/23

Keywords

  • deepfake detection
  • generalization
  • manipulations

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