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CVPR2020顶会

Celeb-DF: A Large-Scale Challenging Dataset for DeepFake Forensics

Yuezun Li, Xin Yang, Pu Sun, Honggang Qi, Siwei Lyu

2020年份
140顶会引用

摘要

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 large-scale datasets. However, current DeepFake datasets suffer from low visual quality and do not resemble Deep-Fake 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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