Gluing Reference Patches Together for Face Super-Resolution
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Ji-Soo | - |
dc.contributor.author | Ko, Keunsoo | - |
dc.contributor.author | Kim, Chang-Su | - |
dc.date.accessioned | 2022-03-10T16:40:20Z | - |
dc.date.available | 2022-03-10T16:40:20Z | - |
dc.date.created | 2022-02-09 | - |
dc.date.issued | 2021 | - |
dc.identifier.issn | 2169-3536 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/138485 | - |
dc.description.abstract | Face super-resolution is a domain-specific super-resolution task to generate a high-resolution facial image from a low-resolution one. In this paper, we propose a novel face super-resolution network, called CollageNet, to super-resolve an input image by exploiting a reference image of an identical person at the patch level. First, we extract feature pyramids from input and reference images to exploit multi-scale information hierarchically. Next, we compute the patch-wise similarities between input and reference feature pyramids and select the K most similar reference patches to each input patch. Then, we compose a collaged feature pyramid by gluing those selected patches together. Finally, we obtain a super-resolved image by blending the collaged feature pyramid and the input feature. Experimental results demonstrate that the proposed CollageNet yields state-of-the-art performances. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Gluing Reference Patches Together for Face Super-Resolution | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Chang-Su | - |
dc.identifier.doi | 10.1109/ACCESS.2021.3138442 | - |
dc.identifier.scopusid | 2-s2.0-85122090204 | - |
dc.identifier.wosid | 000736730500001 | - |
dc.identifier.bibliographicCitation | IEEE ACCESS, v.9, pp.169321 - 169334 | - |
dc.relation.isPartOf | IEEE ACCESS | - |
dc.citation.title | IEEE ACCESS | - |
dc.citation.volume | 9 | - |
dc.citation.startPage | 169321 | - |
dc.citation.endPage | 169334 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordAuthor | Face super-resolution | - |
dc.subject.keywordAuthor | convolutional neural network | - |
dc.subject.keywordAuthor | patch matching | - |
dc.subject.keywordAuthor | reference-based super-resolution | - |
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