Obfuscation Based Privacy Preserving Representations are Recoverable Using Neighborhood Information

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F25%3A00388451" target="_blank" >RIV/68407700:21230/25:00388451 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21730/25:00388451
Result on the web
<a href="https://doi.org/10.1109/3DV66043.2025.00023" target="_blank" >https://doi.org/10.1109/3DV66043.2025.00023</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/3DV66043.2025.00023" target="_blank" >10.1109/3DV66043.2025.00023</a>

Result language
angličtina
Original language name
Obfuscation Based Privacy Preserving Representations are Recoverable Using Neighborhood Information
Original language description
The rapid growth of AR/VR/MR applications and cloudbased visual localization has heightened concerns over user privacy. This privacy concern has been further escalated by the ability of deep neural networks to recover detailed images of a scene from a sparse set of 3D or 2D points and their descriptors - the so-called inversion attacks. Research on privacy-preserving localization has therefore focused on preventing such attacks through geometry obfuscation techniques like lifting points to higher dimensions or swapping coordinates. In this paper, we reveal a common vulnerability in these methods that allows approximate point recovery using known neighborhoods. We further show that these neighborhoods can be computed by learning to identify descriptors that co-occur in neighborhoods. Extensive experiments demonstrate that all existing geometric obfuscation schemes remain susceptible to such recovery, challenging their claims of being privacy-preserving. Code will be available at https://github.com/kunalchelani/RecoverPointsNeighborhood.
Czech name
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Czech description
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Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project
<a href="/en/project/GM22-23183M" target="_blank" >GM22-23183M: New generation of camera geometry solvers</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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