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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPEW34M/47MDRPP
Repositorysid.inpe.br/sibgrapi/2022/09.26.00.26
Last Update2022:09.26.00.26.31 (UTC) menottid@gmail.com
Metadata Repositorysid.inpe.br/sibgrapi/2022/09.26.00.26.31
Metadata Last Update2023:05.23.04.20.43 (UTC) administrator
DOI10.1109/SIBGRAPI55357.2022.9991799
Citation KeySantosLaRiNePrMe:2022:FaSuUs
TitleFace Super-Resolution Using Stochastic Differential Equations
FormatOn-line
Year2022
Access Date2024, Apr. 28
Number of Files1
Size3230 KiB
2. Context
Author1 Santos, Marcelo dos
2 Laroca, Rayson
3 Ribeiro, Rafael O.
4 Neves, João
5 Proença, Hugo
6 Menotti, David
Affiliation1 Department of Informatics, Federal University of Paraná, Curitiba, Brazil
2 Department of Informatics, Federal University of Paraná, Curitiba, Brazil
3 † National Institute of Criminalistics, Brazilian Federal Police, Brasília, Brazil
4 Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal
5 Instituto de Telecomunicações, University of Beira Interior, Covilhã, Portugal
6 Department of Informatics, Federal University of Paraná, Curitiba, Brazil
e-Mail Addressmenotti@inf.ufpr.br
Conference NameConference on Graphics, Patterns and Images, 35 (SIBGRAPI)
Conference LocationNatal, RN
Date24-27 Oct. 2022
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2022-09-26 00:26:31 :: menottid@gmail.com -> administrator ::
2023-05-23 04:20:43 :: administrator -> :: 2022
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
KeywordsSuper-Resolution
Stochastic Differencial Equaitons
Face Recognition
AbstractDiffusion models have proven effective for various applications such as images, audio and graph generation. Other important applications are image super-resolution and the solution of inverse problems. More recently, some works have used stochastic differential equations (SDEs) to generalize diffusion models to continuous time. In this work, we introduce SDEs to generate super-resolution face images. To the best of our knowledge, this is the first time SDEs have been used for such an application. The proposed method provides an improved peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and consistency than the existing super-resolution methods based on diffusion models. In particular, we also assess the potential application of this method for the face recognition task. A generic facial feature extractor is used to compare the super-resolution images with the ground truth, and superior results were obtained compared with other methods. Our code is publicly available at https://github.com/marcelowds/sr-sde.
Arrangementurlib.net > SDLA > Fonds > SIBGRAPI 2022 > Face Super-Resolution Using...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/47MDRPP
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/47MDRPP
Languageen
Target File2022_SIBGRAPI_SDE_INPE.pdf
User Groupmenottid@gmail.com
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/495MHJ8
Citing Item Listsid.inpe.br/sibgrapi/2023/05.19.12.10 8
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition editor electronicmailaddress group holdercode isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project publisher publisheraddress readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url versiontype volume


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