Fantomas: Understanding Face Anonymization Reversibility
Not on the map. Why?
Abstract (arXiv)
Face images are a rich source of information that can be used to identify individuals and infer private information about them. To mitigate this privacy risk, anonymizations employ transformations on clear images to obfuscate sensitive information, all while retaining some utility. Albeit published with impressive claims, they sometimes are not evaluated with convincing methodology. Reversing anonymized images to resemble their real input -- and even be identified by face recognition approaches -- represents the strongest indicator for flawed anonymization. Some recent results indeed indicate that this is possible for some approaches. It is, however, not well understood, which approaches are reversible, and why. In this paper, we provide an exhaustive investigation in the phenomenon of face anonymization reversibility. Among other things, we find that 11 out of 15 tested face anonymizations are at least partially reversible and highlight how both reconstruction and inversion are the underlying processes that make reversal possible.
Key facts. Cited by 4 papers in the map (data through 13 Oct 2026). Builds on 24 of its 83 references that are in the map. First posted on arXiv 19 Oct 2022.
Builds on
24 of 83 references.
References · 24
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12 more
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Built on by
Citing papers per year: 2024: 1; 2025: 2; 2026: 1.
4 papers.
- 2026Face anonymization preserving facial expressions and photometric realism18 Mar 2026
- 2025Controllable Localized Face Anonymization Via Diffusion Inpainting18 Sep 2025
- 2025Restoring Gaussian Blurred Face Images for Deanonymization Attacks14 Jun 2025
- 2024Face Anonymization Made Simple1 Nov 2024