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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/3U3K5TH
Repositorysid.inpe.br/sibgrapi/2019/09.16.01.10
Last Update2019:09.16.01.10.43 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2019/09.16.01.10.43
Metadata Last Update2022:06.14.00.09.43 (UTC) administrator
DOI10.1109/SIBGRAPI.2019.00025
Citation KeyCáceresCondCháv:2019:ExDoCr
TitleExploring Double Cross Cyclic Interpolation in Unpaired Image-to-Image Translation
FormatOn-line
Year2019
Access Date2024, Apr. 28
Number of Files1
Size2736 KiB
2. Context
Author1 Cáceres, Jorge Roberto López
2 Condori, Manasses Antoni Mauricio
3 Chávez, Guillermo Cámara
Affiliation1 Universidad Católica San Pablo
2 Universidad Católica San Pablo
3 Federal University of Ouro Preto
EditorOliveira, Luciano Rebouças de
Sarder, Pinaki
Lage, Marcos
Sadlo, Filip
e-Mail Addressmanasses.mauricio@ucsp.edu.pe
Conference NameConference on Graphics, Patterns and Images, 32 (SIBGRAPI)
Conference LocationRio de Janeiro, RJ, Brazil
Date28-31 Oct. 2019
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2019-09-16 01:10:43 :: manasses.mauricio@ucsp.edu.pe -> administrator ::
2022-06-14 00:09:43 :: administrator -> manasses.mauricio@ucsp.edu.pe :: 2019
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsUnpaired Image-to-Image Translation
Latent Space Interpolation
Cross-domain Model
AbstractThe unpaired image-to-image translation consists of transferring a sample $a$ in the domain $A$ to an analog sample $b$ in the domain $B$ without intensive pixel-to-pixel supervision. The current vision focuses on learning a generative function that maps both domains but ignoring the latent information, although its exploration is not explicit supervision. This paper proposes a cross-domain GAN-based model to achieve a bi-directional translation guided by latent space supervision. The proposed architecture provides a double-loop cyclic reconstruction loss in an exchangeable training adopted to reduce mode collapse and enhance local details. Our proposal has outstanding results in visual quality, stability, and pixel-level segmentation metrics over different public datasets.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2019 > Exploring Double Cross...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Exploring Double Cross...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
agreement.html 15/09/2019 22:10 1.2 KiB 
4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/3U3K5TH
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/3U3K5TH
Languageen
Target FileSibgrapi19_CycleGAN.pdf
User Groupmanasses.mauricio@ucsp.edu.pe
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/3UA4FNL
8JMKD3MGPEW34M/3UA4FPS
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2019/10.25.18.30.33 3
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume
7. Description control
e-Mail (login)manasses.mauricio@ucsp.edu.pe
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