Skip to main navigation Skip to search Skip to main content

Exposing Lip-syncing Deepfakes from Mouth Inconsistencies

  • SUNY Buffalo

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

9 Scopus citations

Abstract

A lip-syncing deepfake is a digitally manipulated video in which a person's lip movements are created convincingly using AI models to match altered or entirely new audio. Lipsyncing deepfakes are a dangerous type of deepfakes as the artifacts are limited to the lip region and more difficult to discern. In this paper, we describe a novel approach, LIP-syncing detection based on mouth INConsistency (LIPINC), for lip-syncing deepfake detection by identifying temporal inconsistencies in the mouth region. These inconsistencies are seen in the adjacent frames and throughout the video. Our model can successfully capture these irregularities and outperforms the state-of-the-art methods on several benchmark deepfake datasets. Code is available at https://github.com/skrantidatta/LIPINC.

Original languageEnglish
Title of host publication2024 IEEE International Conference on Multimedia and Expo, ICME 2024
PublisherIEEE Computer Society
ISBN (Electronic)9798350390155
DOIs
StatePublished - 2024
Event2024 IEEE International Conference on Multimedia and Expo, ICME 2024 - Niagra Falls, Canada
Duration: Jul 15 2024Jul 19 2024

Publication series

NameProceedings - IEEE International Conference on Multimedia and Expo
ISSN (Print)1945-7871
ISSN (Electronic)1945-788X

Conference

Conference2024 IEEE International Conference on Multimedia and Expo, ICME 2024
Country/TerritoryCanada
CityNiagra Falls
Period07/15/2407/19/24

Keywords

  • DeepFake detection
  • Lip-syncing deepfakes
  • Spatial-temporal inconsistency

Fingerprint

Dive into the research topics of 'Exposing Lip-syncing Deepfakes from Mouth Inconsistencies'. Together they form a unique fingerprint.

Cite this