Deep-learning-based automatic skin retouching
US10593023B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Feb 13, 2018 |
| Grant date | Mar 17, 2020 |
| Priority date | — |
| Expiry date | May 13, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30201
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments disclosed herein involve techniques for automatically retouching photos. A neural network is trained to generate a skin quality map from an input photo. The input photo is separated into high and low frequency layers which are separately processed. A high frequency path automatically retouches the high frequency layer using a neural network that accepts the skin quality map as an input. A low frequency path automatically retouches the low frequency layer using a color transformation generated by a second neural network and the skin quality map. The retouched high and low frequency layers are combined to generate the final output. In some embodiments, a training set for any or all of the networks is enhanced by applying a modification to an original image from a pair of retouched photos in the training set to improve the resulting performance of trained networks over different input conditions.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.