Synthesis of High-Quality Visible Faces from Polarimetric Thermal Faces using Generative Adversarial Networks

The large domain discrepancy between faces captured in polarimetric (or conventional) thermal and visible domains makes cross-domain face verification a highly challenging problem for human examiners as well as computer vision algorithms. Previous approaches utilize either a two-step procedure (visi...

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Vydáno v:	International journal of computer vision Ročník 127; číslo 6-7; s. 845 - 862
Hlavní autoři:	Zhang, He, Riggan, Benjamin S., Hu, Shuowen, Short, Nathaniel J., Patel, Vishal M.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.06.2019 Springer Springer Nature B.V
Témata:	Algorithms Artificial Intelligence Computer Imaging Computer Science Computer vision Domains Face recognition Generative adversarial networks Image Processing and Computer Vision Image quality Image reconstruction Pattern Recognition Pattern Recognition and Graphics Polarimetry Program verification (computers) Protocol (computers) Signatures Synthesis Vision Deep learning Polarimetric data Generative adversarial networks Face synthesis Heterogeneous face recognition Thermal face recognition
ISSN:	0920-5691, 1573-1405
On-line přístup:	Získat plný text
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