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arXiv · 1909.12962

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

Yuezun Li·Xin Yang·Pu Sun·Honggang Qi·Siwei Lyu
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Abstract

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 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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Yuezun Li, Xin Yang, Pu Sun, Honggang Qi, Siwei Lyu. 2019-09-27. Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics. https://arxiv.org/abs/1909.12962

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