Skip navigation
Skip navigation

Super-Resolving Very Low-Resolution Face Images with Supplementary Attributes

Yu, Xin; Fernando, Basura; Hartley, Richard; Porikli, Fatih

Description

Given a tiny face image, existing face hallucination methods aim at super-resolving its high-resolution (HR) counterpart by learning a mapping from an exemplar dataset. Since a low-resolution (LR) input patch may correspond to many HR candidate patches, this ambiguity may lead to distorted HR facial details and wrong attributes such as gender reversal. An LR input contains low-frequency facial components of its HR version while its residual face image, defined as the difference between the HR...[Show more]

CollectionsANU Research Publications
Date published: 2018-06-18
Type: Journal article
URI: http://hdl.handle.net/1885/241635
Source: IEEE/CVF Conference on Computer Vision and Pattern Recognition
DOI: 10.1109/CVPR.2018.00101

Download

File Description SizeFormat Image
Super-Resolving_Very_Low-Resolution_Face_Images_with_Supplementary_Attributes.pdf1.51 MBAdobe PDF    Request a copy


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  19 May 2020/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator