Accurately generating virtual try-on images utilizing a unified neural network framework
US11030782B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 9, 2019 |
| Grant date | Jun 8, 2021 |
| Priority date | — |
| Expiry date | Nov 9, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2210/44
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The present disclosure relates to systems, methods, and non-transitory computer readable media for generating a virtual try-on digital image utilizing a unified neural network framework. For example, the disclosed systems can utilize a coarse-to-fine warping process to generate a warped version of a product digital image to fit a model digital image. In addition, the disclosed systems can utilize a texture transfer process to generate a corrected segmentation mask indicating portions of a model digital image to replace with a warped product digital image. The disclosed systems can further generate a virtual try-on digital image based on a warped product digital image, a model digital image, and a corrected segmentation mask. In some embodiments, the disclosed systems can train one or more neural networks to generate accurate outputs for various stages of generating a virtual try-on digital image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.