Corpus ID: 218763191

VideoForensicsHQ: Detecting High-quality Manipulated Face Videos

@article{Fox2020VideoForensicsHQDH,
  title={VideoForensicsHQ: Detecting High-quality Manipulated Face Videos},
  author={Gereon Fox and Wentao Liu and Hyeongwoo Kim and Hans-Peter Seidel and Mohamed A. Elgharib and Christian Theobalt},
  journal={ArXiv},
  year={2020},
  volume={abs/2005.10360}
}
  • Gereon Fox, Wentao Liu, +3 authors Christian Theobalt
  • Published 2020
  • Computer Science
  • ArXiv
  • New approaches to synthesize and manipulate face videos at very high quality have paved the way for new applications in computer animation, virtual and augmented reality, or face video analysis. However, there are concerns that they may be used in a malicious way, e.g. to manipulate videos of public figures, politicians or reporters, to spread false information. The research community therefore developed techniques for automated detection of modified imagery, and assembled benchmark datasets… CONTINUE READING

    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 50 REFERENCES

    Deepfake Video Detection through Optical Flow Based CNN

    VIEW 1 EXCERPT

    Recurrent Convolutional Strategies for Face Manipulation Detection in Videos

    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    FaceForensics++: Learning to Detect Manipulated Facial Images

    VIEW 10 EXCERPTS
    HIGHLY INFLUENTIAL

    Unmasking DeepFakes with simple Features

    VIEW 6 EXCERPTS
    HIGHLY INFLUENTIAL

    Deep video portraits

    VIEW 10 EXCERPTS

    MesoNet: a Compact Facial Video Forgery Detection Network

    VIEW 20 EXCERPTS
    HIGHLY INFLUENTIAL

    Media Forensics and DeepFakes: an overview

    VIEW 1 EXCERPT