Learning Domain-Invariant Discriminative Features for Heterogeneous Face Recognition

Learning Domain-Invariant Discriminative Features for Heterogeneous Face Recognition

Heterogeneous face recognition (HFR), referring to matching face images across different domains, is a challenging problem due to the vast cross-domain discrepancy and insufficient pairwise cross-domain training data. This article proposes a quadruplet framework for learning domain-invariant discrim...

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Bibliographic Details
Main Authors: Shanmin Yang, Keren Fu, Xiao Yang, Ye Lin, Jianwei Zhang, Cheng Peng
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Adversarial domain adaptation
domain-invariant feature
heterogeneous face recognition
quadruplet loss
Online Access:https://ieeexplore.ieee.org/document/9262951/

Internet

https://ieeexplore.ieee.org/document/9262951/

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