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AI-synthesized face-swapping videos, commonly known as DeepFakes, is an emerging problem threatening the trustworthiness of online information. The need to develop and evaluate DeepFake detection algorithms calls for datasets of DeepFake videos. However, current DeepFake datasets suffer from low visual quality and do not resemble DeepFake videos circulated on the Internet. We present a new large-scale challenging DeepFake video dataset, Celeb-DF, which contains 5,639 high-quality DeepFake videos of celebrities generated using improved synthesis process. We conduct a comprehensive evaluation of DeepFake detection methods and datasets to demonstrate the escalated level of challenges posed by Celeb-DF.
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Li et al. (Mon,) studied this question.
www.synapsesocial.com/papers/6942daf4ca2dd862627d75ce — DOI: https://doi.org/10.1109/cvpr42600.2020.00327
Yuezun Li
Xin Yang
Pu Sun
University of Chinese Academy of Sciences
University at Albany, State University of New York
Albany State University
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