Semantic face hallucination: Super-resolving very low-resolution face images with supplementary attributes
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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 exemplary 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 and rejuvenation. An LR input contains low-frequency facial components of its HR version while its residual face image, defined as the...[Show more]
Collections | ANU Research Publications |
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Date published: | 2020 |
Type: | Journal article |
URI: | http://hdl.handle.net/1885/293991 |
Source: | IEEE Transactions on Pattern Analysis and Machine Intelligence |
DOI: | 10.1109/TPAMI.2019.2916881 |
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Semantic Face Hallucination.pdf | 10.56 MB | Adobe PDF | Request a copy |
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