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.
Future Trends in Digital Face Manipulation and Detection / Tolosana, R.; Rathgeb, C.; Vera-Rodriguez, R.; Busch, C.; Verdoliva, L.; Lyu, S.; Nguyen, H. H.; Yamagishi, J.; Echizen, I.; Rot, P.; Grm, K.; Štruc, V.. - (2022), pp. 463-482. [10.1007/978-3-030-87664-7_21]
Future Trends in Digital Face Manipulation and Detection
L. Verdoliva;
2022
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
