Locality-Constrained Double Low-Rank Representation for Effective Face Hallucination

Locality-Constrained Double Low-Rank Representation for Effective Face Hallucination

Recently, position-patch-based face hallucination methods have received much attention, and obtained promising progresses due to their effectiveness and efficiency. A locality-constrained double low-rank representation (LCDLRR) method is proposed for effective face hallucination in this paper. LCDLR...

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Bibliographic Details
Main Authors: Guangwei Gao, Xiao-Yuan Jing, Pu Huang, Quan Zhou, Songsong Wu, Dong Yue
Format: Article
Language:English
Published: IEEE 2016-01-01
Series:IEEE Access
Subjects:
Face hallucination
low-rank representation
position-patch
nuclear norm
Online Access:https://ieeexplore.ieee.org/document/7762113/

Internet

https://ieeexplore.ieee.org/document/7762113/

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