Dataset Generation and Study of Deepfake Techniques

Falcón-López, Sergio A., Robles-Gómez, Antonio, Tobarra, Llanos y Pastor-Vargas, Rafael(2023) .Dataset Generation and Study of Deepfake Techniques. 15th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAml 2023).En: . (2023)

Ficheros (Some files may be inaccessible until you login with your e-spacio credentials)
Nombre Descripción Tipo MIME Size
Robles_Gomez_Antonio_DatasetGeneration.pdf Robles Gomez_Antonio_DatasetGeneration.pdf application/pdf 1.78MB

Título de la Conferencia 15th International Conference on Ubiquitous Computing and Ambient Intelligence (UCAml 2023)
Fecha de inicio de la Conferencia 2023
Fecha fín de la Conferencia 2023
Numeros de las páginas 197-206
Titulo Dataset Generation and Study of Deepfake Techniques
Autor(es) Falcón-López, Sergio A.
Robles-Gómez, Antonio
Tobarra, Llanos
Pastor-Vargas, Rafael
Notas adicionales Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 842)
Materia(s) Ingeniería Informática
Resumen The consumption of multimedia content on the Internet has nowadays been expanded exponentially. These trends have contributed to fake news can become a very high influence in the current society. The latest techniques to influence the spread of digital false information are based on methods of generating images and videos, known as Deepfakes. This way, our research work analyzes the most widely used Deepfake content generation methods, as well as explore different conventional and advanced tools for Deepfake detection. A specific dataset has also been built that includes both fake and real multimedia contents. This dataset will allow us to verify whether the used image and video forgery detection techniques can detect manipulated multimedia content.
Palabra clave Deepfake
Dataset Generation
Detection Techniques
Multimedia Manipulation
Editor(es) Springer
Fecha 2023
Formato application/pdf
Identificador bibliuned:DptoSCC-ETSI-Ponencias-Arobles-001
http://e-spacio.uned.es/fez/view/bibliuned:DptoSCC-ETSI-Ponencias-Arobles-001
https://doi.org/10.1007/978-3-031-48642-5_19
ISBN: 978-3-031-48641-8.
Total de paginas 197-206
Idioma eng
Versión de la publicación publishedVersion
Nivel de acceso y licencia http://creativecommons.org/licenses/by-nc-nd/4.0
Tipo de recurso conferenceObject
Tipo de acceso Acceso restringido

 
Versiones
Versión Tipo de filtro
Contador de citas: Google Scholar Search Google Scholar
Estadísticas de acceso: 54 Visitas, 24 Descargas  -  Estadísticas en detalle
Creado: Fri, 09 Feb 2024, 04:51:07 CET