Motion transfer using machine-learning models
US11373352B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 4, 2021 |
| Grant date | Jun 28, 2022 |
| Priority date | — |
| Expiry date | Mar 4, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, a method includes generating a keypoint pose and a dense pose for a first person in a first pose based on a first image comprising the first person in the first pose, generating an input semantic segmentation map corresponding to a second person in a second pose based on a second image comprising the second person in the second pose, generating a target semantic segmentation map corresponding to the second person in the first pose by processing the keypoint pose, the dense pose, and the input segmentation map using a first machine-learning model, generating an encoding vector representing the second person based on the second image, and generating a target image of the second person in the first pose by processing the encoding vector and the target segmentation map using a second machine-learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.