Discriminative deep metric learning for face verification in the wild
This paper presents a new discriminative deep metric learning (DDML) method for face verification in the wild. Different from existing metric learning-based face verification methods which aim to learn a Mahalanobis distance metric to maximize the inter-class variations and minimize the intra-c...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2015
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/100336 http://hdl.handle.net/10220/25706 |