TY - CHAP
T1 - Future Trends in Digital Face Manipulation and Detection
AU - Tolosana, Ruben
AU - Rathgeb, Christian
AU - Vera-Rodriguez, Ruben
AU - Busch, Christoph
AU - Verdoliva, Luisa
AU - Lyu, Siwei
AU - Nguyen, Huy H.
AU - Yamagishi, Junichi
AU - Echizen, Isao
AU - Rot, Peter
AU - Grm, Klemen
AU - Štruc, Vitomir
AU - Dantcheva, Antitza
AU - Akhtar, Zahid
AU - Romero-Tapiador, Sergio
AU - Fierrez, Julian
AU - Morales, Aythami
AU - Ortega-Garcia, Javier
AU - Kindt, Els
AU - Jasserand, Catherine
AU - Kalvet, Tarmo
AU - Tiits, Marek
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85124087816
U2 - 10.1007/978-3-030-87664-7_21
DO - 10.1007/978-3-030-87664-7_21
M3 - Chapter
AN - SCOPUS:85124087816
T3 - Advances in Computer Vision and Pattern Recognition
SP - 463
EP - 482
BT - Advances in Computer Vision and Pattern Recognition
PB - Springer Science and Business Media Deutschland GmbH
ER -