mlsanityData to 7 Oct 2026

Assessing the Use of Face Swapping Methods as Face Anonymizers in Videos

arXiv 2505.20985 ↗First posted 27 May 2025cs.CVcited by 0

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Abstract (arXiv)

The increasing demand for large-scale visual data, coupled with strict privacy regulations, has driven research into anonymization methods that hide personal identities without seriously degrading data quality. In this paper, we explore the potential of face swapping methods to preserve privacy in video data. Through extensive evaluations focusing on temporal consistency, anonymity strength, and visual fidelity, we find that face swapping techniques can produce consistent facial transitions and effectively hide identities. These results underscore the suitability of face swapping for privacy-preserving video applications and lay the groundwork for future advancements in anonymization focused face-swapping models.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 26 of its 34 references that are in the map. First posted on arXiv 27 May 2025.

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26 of 34 references.

References · 26

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2020Denoising Diffusion Implicit Modelscited by 9,655
  5. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  6. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  7. 2018Towards Accurate Generative Models of Video: A New Metric & Challengescited by 1,204
  8. 2019FaceForensics++: Learning to Detect Manipulated Facial Imagescited by 1,095
  9. 2021SimSwap: An Efficient Framework For High Fidelity Face Swappingcited by 243
  10. 2024BrushNet: A Plug-and-Play Image Inpainting Model with Decomposed Dual-Branch Diffusioncited by 200
  11. 2019DeepPrivacy: A Generative Adversarial Network for Face Anonymizationcited by 108
  12. 2020CIAGAN: Conditional Identity Anonymization Generative Adversarial Networkscited by 88
14 more
  1. 2021Sample and Computation Redistribution for Efficient Face Detectioncited by 86
  2. 2022DeepPrivacy2: Towards Realistic Full-Body Anonymizationcited by 51
  3. 2019AnonymousNet: Natural Face De-Identification with Measurable Privacycited by 50
  4. 2022FaceDancer: Pose- and Occlusion-Aware High Fidelity Face Swappingcited by 44
  5. 2024Realistic and Efficient Face Swapping: A Unified Approach with Diffusion Modelscited by 35
  6. 2022Shape Preserving Facial Landmarks with Graph Attention Networkscited by 23
  7. 2023LDFA: Latent Diffusion Face Anonymization for Self-driving Applicationscited by 21
  8. 2024G2Face: High-Fidelity Reversible Face Anonymization via Generative and Geometric Priorscited by 20
  9. 2024Face Anonymization Made Simplecited by 18
  10. 2021CFA-Net: Controllable Face Anonymization Network with Identity Representation Manipulationcited by 12
  11. 2023GANonymization: A GAN-based Face Anonymization Framework for Preserving Emotional Expressionscited by 9
  12. 2017Face Deidentification with Generative Deep Neural Networkscited by 8
  13. 2023E4S: Fine-grained Face Swapping via Editing With Regional GAN Inversioncited by 8
  14. 2024Latent Diffusion Models for Attribute-Preserving Image Anonymizationcited by 7

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