Conference Proceedings
WildDeepfake: A Challenging Real-World Dataset for Deepfake Detection
B Zi, M Chang, J Chen, X Ma, YG Jiang
Mm 2020 Proceedings of the 28th ACM International Conference on Multimedia | Published : 2020
Abstract
In recent years, the abuse of a face swap technique called deepfake has raised enormous public concerns. So far, a large number of deepfake videos (known as "deepfakes") have been crafted and uploaded to the internet, calling for effective countermeasures. One promising countermeasure against deepfakes is deepfake detection. Several deepfake datasets have been released to support the training and testing of deepfake detectors, such as DeepfakeDetection [1] and FaceForensics++ [23]. While this has greatly advanced deepfake detection, most of the real videos in these datasets are filmed with a few volunteer actors in limited scenes, and the fake videos are crafted by researchers using a few po..
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