March 1, 2024, 5:47 a.m. | Christos Koutlis, Symeon Papadopoulos

cs.CV updates on arXiv.org arxiv.org

arXiv:2402.19091v1 Announce Type: new
Abstract: The recently developed and publicly available synthetic image generation methods and services make it possible to create extremely realistic imagery on demand, raising great risks for the integrity and safety of online information. State-of-the-art Synthetic Image Detection (SID) research has led to strong evidence on the advantages of feature extraction from foundation models. However, such extracted features mostly encapsulate high-level visual semantics instead of fine-grained details, which are more important for the SID task. On …

arxiv cs.cv detection encoder image image detection intermediate synthetic type

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