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Face Hallucination via Deep Neural Networks.

Yu, Xin

Description

We firstly address aligned low-resolution (LR) face images (i.e. 16X16 pixels) by designing a discriminative generative network, named URDGN. URDGN is composed of two networks: a generative model and a discriminative model. We introduce a pixel-wise L2 regularization term to the generative model and exploit the feedback of the discriminative network to make the upsampled face images more similar to real ones. We present an end-to-end transformative discriminative neural network (TDN)...[Show more]

CollectionsOpen Access Theses
Date published: 2019
Type: Thesis (PhD)
URI: http://hdl.handle.net/1885/154708
DOI: 10.25911/5d51433625f11

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