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

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arxiv 1909.12962 v4 pith:BTUUGT5H submitted 2019-09-27 cs.CR cs.CVeess.IV

Yuezun Li , Xin Yang , Pu Sun , Honggang Qi , Siwei Lyu This is my paper · ORCID
classification cs.CRcs.CVeess.IV
keywords deepfakeceleb-dfdatasetslarge-scalevideoschallengingdatasetdetection
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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 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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Cited by 6 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 104 citations worldwide. Full citation record

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  4. Nearly Solved? Robust Deepfake Detection Requires More than Visual Forensics

    cs.CV 2024-12 reject novelty 5.0 of 10

    Black-box genetic attacks flip 70% of correct fake detections in a retrained patch-based detector, GPT-4o reaches 73% AUC zero-shot on a Celeb-DF subset, and a 6.64% typographic attack degrades it.

  5. Visual Language Models as Zero-Shot Deepfake Detectors

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    Zero-shot VLMs scored by normalized yes/no token probabilities beat most trained deepfake detectors on a new SimSwap dataset, and a lightly fine-tuned InstructBLIP is near-perfect on DFDC-P.

  6. AWARE-NET: Adaptive Weighted Averaging for Robust Ensemble Network in Deepfake Detection

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    A two-tier ensemble that averages three instances of Xception, Res2Net101, and EfficientNet-B7 and learns a softmax-weighted fusion reports near-perfect intra-dataset scores, but its headline cross-dataset AUC of 88.2...

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