Domain generalized margin via meta-learning for deep face recognition
US11977602B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 8, 2021 |
| Grant date | May 7, 2024 |
| Priority date | — |
| Expiry date | Nov 18, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/172
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for training a model for face recognition is provided. The method forward trains a training batch of samples to form a face recognition model w(t), and calculates sample weights for the batch. The method obtains a training batch gradient with respect to model weights thereof and updates, using the gradient, the model w(t) to a face recognition model what(t). The method forwards a validation batch of samples to the face recognition model what(t). The method obtains a validation batch gradient, and updates, using the validation batch gradient and what(t), a sample-level importance weight of samples in the training batch to obtain an updated sample-level importance weight. The method obtains a training batch upgraded gradient based on the updated sample-level importance weight of the training batch samples, and updates, using the upgraded gradient, the model w(t) to a trained model w(t+1) corresponding to a next iteration.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.