Litcius/Paper detail

Future Trends in Digital Face Manipulation and Detection

Rubén Tolosana, Christian Rathgeb, Rubén Vera-Rodríguez, Christoph Busch, Luisa Verdoliva, Siwei Lyu, Huy H. Nguyen, Junichi Yamagishi, Isao Echizen, Peter Rot, Klemen Grm, Vitomir Štruc, Antitza Dantcheva, Zahid Akhtar, Sergio Romero-Tapiador, Julián Fiérrez, Aythami Morales, Javier Ortega-García, Els Kindt, Catherine Jasserand, Tarmo Kalvet, Marek Tiits

2022Advances in computer vision and pattern recognition17 citationsDOIOpen Access PDF

Abstract

Abstract Recently, digital face manipulation and its detection have sparked large interest in industry and academia around the world. Numerous approaches have been proposed in the literature to create realistic face manipulations, such as DeepFakes and face morphs. To the human eye manipulated images and videos can be almost indistinguishable from real content. Although impressive progress has been reported in the automatic detection of such face manipulations, this research field is often considered to be a cat and mouse game . This chapter briefly discusses the state of the art of digital face manipulation and detection. Issues and challenges that need to be tackled by the research community are summarized, along with future trends in the field.

Topics & Concepts

Face (sociological concept)Field (mathematics)Computer scienceFace detectionArtificial intelligenceHuman–computer interactionComputer visionData scienceFacial recognition systemPattern recognition (psychology)SociologySocial scienceMathematicsPure mathematicsFace recognition and analysisFace and Expression RecognitionBiometric Identification and Security