SEED is a new benchmark for sequential provenance tracing in diffusion-edited deepfake faces, with the FAITH baseline showing that wavelet-based high-frequency signals aid detection of accumulated editing artifacts.
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This position paper contends that the concept of 'real' images must be rethought because most modern photographs are computationally generated, undermining current deepfake detection methods.
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SEED: A Large-Scale Benchmark for Provenance Tracing in Sequential Deepfake Facial Edits
SEED is a new benchmark for sequential provenance tracing in diffusion-edited deepfake faces, with the FAITH baseline showing that wavelet-based high-frequency signals aid detection of accumulated editing artifacts.
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Deepfakes: we need to re-think the concept of "real" images
This position paper contends that the concept of 'real' images must be rethought because most modern photographs are computationally generated, undermining current deepfake detection methods.