Generating image mattes without trimap segmentations via a multi-branch neural network
US12282987B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 8, 2022 |
| Grant date | Apr 22, 2025 |
| Priority date | — |
| Expiry date | Dec 15, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and non-transitory computer readable storage media are disclosed for generating image mattes for detected objects in digital images without trimap segmentation via a multi-branch neural network. The disclosed system utilizes a first neural network branch of a generative neural network to extract a coarse semantic mask from a digital image. The disclosed system utilizes a second neural network branch of the generative neural network to extract a detail mask based on the coarse semantic mask. Additionally, the disclosed system utilizes a third neural network branch of the generative neural network to fuse the coarse semantic mask and the detail mask to generate an image matte. In one or more embodiments, the disclosed system also utilizes a refinement neural network to generate a final image matte by refining selected portions of the image matte generated by the generative neural network.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.