A Coarse-to-fine Approach for Fast Super-Resolution with Flexible Magnification

Zhichao Fu, Tianlong Ma, Liang Xue, Yingbin Zheng, Hao Ye, Liang He

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We perform fast single image super-resolution with flexible magnification for natural images. A novel coarse-to-fine super-resolution framework is developed for the magnification that is factorized into a maximum integer component and the quotient. Specifically, our framework is embedded with a light-weight upscale network for super-resolution with the integer scale factor, followed by the fine-grained network to guide interpolation on feature maps as well as to generate the super-resolved image. Compared with the previous flexible magnification super-resolution approaches, the proposed framework achieves a tradeoff between computational complexity and performance. We conduct experiments using the coarse-to-fine framework on the standard benchmarks and demonstrate its superiority in terms of effectiveness and efficiency over previous approaches.

Original languageEnglish
Title of host publicationProceedings of the 3rd ACM International Conference on Multimedia in Asia, MMAsia 2021
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450386074
DOIs
StatePublished - 1 Dec 2021
Event3rd ACM International Conference on Multimedia in Asia, MMAsia 2021 - Virtual, Online, Australia
Duration: 1 Dec 20213 Dec 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference3rd ACM International Conference on Multimedia in Asia, MMAsia 2021
Country/TerritoryAustralia
CityVirtual, Online
Period1/12/213/12/21

Keywords

  • Super-resolution
  • coarse-to-fine
  • flexible magnification.

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