High resolution conditional face generation
US11887216B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 19, 2021 |
| Grant date | Jan 30, 2024 |
| Priority date | — |
| Expiry date | Jun 25, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/172
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure describes systems and methods for image processing. Embodiments of the present disclosure include an image processing apparatus configured to generate modified images (e.g., synthetic faces) by conditionally changing attributes or landmarks of an input image. A machine learning model of the image processing apparatus encodes the input image to obtain a joint conditional vector that represents attributes and landmarks of the input image in a vector space. The joint conditional vector is then modified, according to the techniques described herein, to form a latent vector used to generate a modified image. In some cases, the machine learning model is trained using a generative adversarial network (GAN) with a normalization technique, followed by joint training of a landmark embedding and attribute embedding (e.g., to reduce inference time).
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.