Face Deepfakes -- A Comprehensive Review

Tharindu Fernando, Darshana Priyasad, Sridha Sridharan, Arun Ross, Clinton Fookes
2/13/2025
cs.CVcs.LG

No confident code implementation found for this paper. 1 possible match can be shown below.

Abstract

In recent years, remarkable advancements in deep-fake generation technology have led to unprecedented leaps in its realism and capabilities. Despite these advances, we observe a notable lack of structured and deep analysis deepfake technology. The principal aim of this survey is to contribute a thorough theoretical analysis of state-of-the-art face deepfake generation and detection methods. Furthermore, we provide a coherent and systematic evaluation of the implications of deepfakes on face biometric recognition approaches. In addition, we outline key applications of face deepfake technology, elucidating both positive and negative applications of the technology, provide a detailed discussion regarding the gaps in existing research, and propose key research directions for further investigation.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 1 weaker match is hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Cite this paper

@article{fernando2025face,
  title  = {Face Deepfakes -- A Comprehensive Review},
  author = {Tharindu Fernando and Darshana Priyasad and Sridha Sridharan and Arun Ross and Clinton Fookes},
  year   = {2025},
  eprint = {2502.09812},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2502.09812v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2502.09812.svg)](https://codeofpaper.com/paper/2502.09812)

Discussion