Automatically generating a trimap segmentation for a digital image by utilizing a trimap generation neural network
US11393100B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 7, 2020 |
| Grant date | Jul 19, 2022 |
| Priority date | — |
| Expiry date | Dec 3, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20221
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and non-transitory computer readable storage media are disclosed for utilizing a plurality of neural networks in a multi-branch pipeline to generate image masks for digital images. Specifically, the disclosed system can classify a digital image as a portrait or a non-portrait image. Based on classifying a portrait image, the disclosed system can utilize separate neural networks to generate a first mask portion for a portion of the digital image including a defined boundary region and a second mask portion for a portion of the digital image including a blended boundary region. The disclosed system can generate the mask portion for the blended boundary region by utilizing a trimap generation neural network to automatically generate a trimap segmentation including the blended boundary region. The disclosed system can then merge the first mask portion and the second mask portion to generate an image mask for the digital image.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.