Reliable Facial Forgery Detection

  • Unique Paper ID: 150064
  • Volume: 7
  • Issue: 2
  • PageNo: 279-283
  • Abstract:
  • The free access to large-scale public databases, alongside the fast progress of deep learning techniques, especially Generative Adversarial Networks, have led to the generation of very realistic fake contents which can be threatening and have various implications in today's world where enforcing fake news is pretty simple. This survey provides a radical review of techniques for manipulating face images including DeepFake methods, and methods to detect such manipulations. These techniques are, face synthesis, face identity swap, facial attributes manipulation, and countenance manipulation. For each manipulation type, we offer details regarding manipulation techniques, existing public databases, and key benchmarks for technology evaluation of faux detection methods, including a summary of results from those evaluations.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{150064,
        author = {Dr Simmi Dutta and Aditya Sharma and Ruban Nazir Shah and Harsharan Singh Raina},
        title = {Reliable Facial Forgery Detection},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {7},
        number = {2},
        pages = {279-283},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=150064},
        abstract = {The free access to large-scale public databases, alongside the fast progress of deep learning techniques, especially Generative Adversarial Networks, have led to the generation of very realistic fake contents which can be threatening and have various implications in today's world where enforcing fake news is pretty simple. This survey provides a radical review of techniques for manipulating face images including DeepFake methods, and methods to detect such manipulations. These techniques are, face synthesis, face identity swap, facial attributes manipulation, and countenance manipulation. For each manipulation type, we offer details regarding manipulation techniques, existing public databases, and key benchmarks for technology evaluation of faux detection methods, including a summary of results from those evaluations.},
        keywords = {Deepfakes, FaceForensics, Resnet, XceptionNet},
        month = {},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 7
  • Issue: 2
  • PageNo: 279-283

Reliable Facial Forgery Detection

Related Articles