Training a generator for generating realistic images using a semantically segmenting discriminator
US12272123B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 20, 2021 |
| Grant date | Apr 8, 2025 |
| Priority date | — |
| Expiry date | Aug 3, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for training a generator for images from a semantic map that assigns to each pixel of the image a semantic meaning of an object to which this pixel belongs. The images generated by the generator and the at least one real training image that belong to the same semantic training map are supplied to a discriminator. The discriminator ascertains a semantic segmentation of the image assigned to it, the segmentation assigning a semantic meaning to each pixel of this image. From the semantic segmentation ascertained by the discriminator, it is evaluated whether the image supplied to the discriminator is a generated image or a real training image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.