Image extension neural networks
US12236676B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 19, 2019 |
| Grant date | Feb 25, 2025 |
| Priority date | — |
| Expiry date | Jan 21, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20132
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating realistic extensions of images. In one aspect, a method comprises providing an input that comprises a provided image to a generative neural network having a plurality of generative neural network parameters. The generative neural network processes the input in accordance with trained values of the plurality of generative neural network parameters to generate an extended image. The extended image has (i) more rows, more columns, or both than the provided image, and (ii) is predicted to be a realistic extension of the provided image. The generative neural network is trained using an adversarial loss objective function.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.