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Titlebook: Handbook of Digital Face Manipulation and Detection; From DeepFakes to Mo Christian Rathgeb,Ruben Tolosana,Christoph Busch Book‘‘‘‘‘‘‘‘ 202

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Schreibdidaktik und Schreibunterrichtpter, we argue that our forensic-oriented capsule network overcomes these limitations and is more suitable than conventional CNNs to detect deepfakes. The superiority of our “Capsule-Forensics”network is due to the use of a pretrained feature extractor, statistical pooling layers, and a dynamic rout
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Übungen Zum Kapitel 2 - Visuelle Mediene a serious degradation in performance of the MAD methods. In addition, more advanced tools exist to manipulate the face morphs, like manual retouching or morphing artifacts can be concealed by printing and scanning a photograph (as used in the passport application process in many countries). Furthe
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https://doi.org/10.1007/978-3-663-12959-2 the prominent digital manipulations with special emphasis on the facial content due to their large number of possible applications. Specifically, we cover the principles of six types of digital face manipulations: . entire face synthesis, . identity swap, . face morphing, . attribute manipulation,
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https://doi.org/10.1007/978-3-663-07726-8 the world. The processing of digitally manipulated face images within a face recognition system may lead to false decisions and thus decrease the reliability of the decision system. This necessitates the development of manipulation detection modules which can be seamlessly integrated into the proce
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https://doi.org/10.1007/978-3-322-98878-2processing methods, it is possible to modify images and videos obtaining very realistic results. This chapter is devoted to describe the most effective strategies to detect the widespread manipulations that rely on traditional approaches and do not require a deep learning strategy. In particular, we
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