Semi-supervised learning for landmark localization
US10783393B2 · kind B2 · utility
2Cited by
17References
19Claims
0Family size
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Key dates
| Filing date | Jun 12, 2018 |
| Grant date | Sep 22, 2020 |
| Priority date | — |
| Expiry date | Feb 6, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30201
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method, computer readable medium, and system are disclosed for sequential multi-tasking to generate coordinates of landmarks within images. The landmark locations may be identified on an image of a human face and used for emotion recognition, face identity verification, eye gaze tracking, pose estimation, etc. A neural network model processes input image data to generate pixel-level likelihood estimates for landmarks in the input image data and a soft-argmax function computes predicted coordinates of each landmark based on the pixel-level likelihood estimates.
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