Invention Application
- Patent Title: DOMAIN GENERALIZED MARGIN VIA META-LEARNING FOR DEEP FACE RECOGNITION
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Application No.: US17521252Application Date: 2021-11-08
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Publication No.: US20220147767A1Publication Date: 2022-05-12
- Inventor: Xiang Yu , Yi-Hsuan Tsai , Masoud Faraki , Ramin Moslemi , Manmohan Chandraker , Chang Liu
- Applicant: NEC Laboratories America, Inc.
- Applicant Address: US NJ Princeton
- Assignee: NEC Laboratories America, Inc.
- Current Assignee: NEC Laboratories America, Inc.
- Current Assignee Address: US NJ Princeton
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06N20/00 ; G06K9/00

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.
Public/Granted literature
- US11977602B2 Domain generalized margin via meta-learning for deep face recognition Public/Granted day:2024-05-07
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