Anonymizing digital images utilizing a generative adversarial neural network
US12321495B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 2, 2022 |
| Grant date | Jun 3, 2025 |
| Priority date | — |
| Expiry date | Jul 31, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/0464
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems, methods, and non-transitory computer readable media for generating anonymized digital images utilizing a face anonymization neural network. In some embodiments, the disclosed systems utilize a face anonymization neural network to extract or encode a face anonymization guide that encodes face attribute features, such as gender, ethnicity, age, and expression. In some cases, the disclosed systems utilize the face anonymization guide to inform the face anonymization neural network in generating synthetic face pixels for anonymizing a digital image while retaining attributes, such as gender, ethnicity, age, and expression. The disclosed systems learn parameters for a face anonymization neural network for preserving face attributes, accounting for multiple faces in digital images, and generating synthetic face pixels for faces in profile poses.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.