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Xiuzhuang Zhou
Researcher at Capital Normal University
Publications - 41
Citations - 2358
Xiuzhuang Zhou is an academic researcher from Capital Normal University. The author has contributed to research in topics: Facial recognition system & Discriminative model. The author has an hindex of 18, co-authored 37 publications receiving 1957 citations. Previous affiliations of Xiuzhuang Zhou include Beijing Institute of Technology & Beijing University of Posts and Telecommunications.
Papers
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Journal ArticleDOI
Neighborhood repulsed metric learning for kinship verification
TL;DR: This paper proposes a new neighborhood repulsed metric learning (NRML) method for kinship verification, and proposes a multiview NRM-L method to seek a common distance metric to make better use of multiple feature descriptors to further improve the verification performance.
Journal ArticleDOI
Learning Compact Binary Face Descriptor for Face Recognition
TL;DR: A compact binary face descriptor (CBFD) feature learning method for face representation and recognition that reduces the modality gap of heterogeneous faces at the feature level to make the method applicable to heterogeneous face recognition.
Journal ArticleDOI
Discriminative Multimetric Learning for Kinship Verification
TL;DR: Experimental results show the effectiveness of the proposed discriminative multimetric learning method for kinship verification via facial image analysis over the existing single-metric and multimetricLearning methods.
Journal ArticleDOI
Prototype-Based Discriminative Feature Learning for Kinship Verification
TL;DR: Experimental results on four publicly available kinship datasets show the superior performance of the proposed PDFL methods over both the state-of-the-art kinship verification methods and human ability in the kinships verification task.
Proceedings ArticleDOI
Kinship verification from facial images under uncontrolled conditions
TL;DR: This paper collects a kinship face database by searching 400+ pairs of public figures and celebrities from the internet, and automatically detect them with the Viola-Jones face detector and proposes a new spatial pyramid learning-based (SPLE) feature descriptor for face representation and applies support vector machine (SVM) for kinship verification.