Discriminative deep metric learning for face verification in the wild

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...

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Bibliographic Details
Main Authors: Hu, Junlin, Lu, Jiwen, Tan, Yap Peng
Other Authors: School of Electrical and Electronic Engineering
Format: Conference Paper
Language:English
Published: 2015
Subjects:
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Pattern recognition
Online Access:https://hdl.handle.net/10356/100336
http://hdl.handle.net/10220/25706

Internet

https://hdl.handle.net/10356/100336
http://hdl.handle.net/10220/25706

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