Celeb-DF: A Large-scale Challenging Dataset for DeepFake Forensics
Yuezun Li, Xin Yang, Pu Sun, Honggang Qi, Siwei Lyu
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ReproduceCode
- github.com/danmohaha/celeb-deepfakeforensicsOfficialnone★ 0
- github.com/Recognito-Vision/Linux-FaceRecognition-FaceLivenessDetectionnone★ 363
- github.com/polimi-ispl/icpr2020dfdcpytorch★ 278
- github.com/beibuwandeluori/DFGC_Detectionpytorch★ 33
- github.com/SuyashSonawane/fakedetectorpytorch★ 13
- github.com/seongilp/DFE604-2020F-FinalProjectnone★ 1
- github.com/jhchang/DFDCpytorch★ 0
- github.com/CatoGit/Comparing-the-Performance-of-Deepfake-Detection-Methods-on-Benchmark-Datasetspytorch★ 0
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.