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  1. To address the survey gap, the paper proposes a comprehensive review of deepfake generation and detection and the different ML/DL approaches to synthesize deepfake contents. We discuss a comparative analysis of deepfake models and public datasets present for deepfake detection purposes.

  2. 26 Mac 2024 · This survey comprehensively reviews the latest developments in deepfake generation and detection, summarizing and analyzing current state-of-the-arts in this rapidly evolving field. We first unify task definitions, comprehensively introduce datasets and metrics, and discuss developing technologies.

  3. 25 Feb 2021 · This paper provides a comprehensive review and detailed analysis of existing tools and machine learning (ML) based approaches for deepfake generation and the methodologies used to detect such manipulations for both audio and visual deepfakes.

  4. 8 Jan 2022 · In the paper, we make a survey on state-ofthe-art deepfake generation methods, detection methods, and existing datasets. Current deepfake generation methods can be classified into face swapping and facial reenactment. Deepfake detection methods are mainly based features and machine learning methods.

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  6. 4 Jun 2022 · Section 4 presents an overview of state-of-the-art audio and visual deepfake generation and detection techniques. Section 5 presents the details of available datasets used for both audio and video deepfakes detection. We have identified the open challenges for both audio-visual deepfake generation and detection in Section 6.

  7. Official repository for the next-generation deepfake detection dataset (called DF40 dataset), comprising 40 distinct deepfake techniques, even the just released SoTAs. Resources Readme