<?xml version="1.0" encoding="ISO-8859-1"?>
<metadatalist>
	<metadata ReferenceType="Conference Proceedings">
		<site>sibgrapi.sid.inpe.br 802</site>
		<holdercode>{ibi 8JMKD3MGPEW34M/46T9EHH}</holdercode>
		<identifier>8JMKD3MGPEW34M/4389E48</identifier>
		<repository>sid.inpe.br/sibgrapi/2020/09.10.17.52</repository>
		<lastupdate>2020:09.10.17.52.55 sid.inpe.br/banon/2001/03.30.15.38 administrator</lastupdate>
		<metadatarepository>sid.inpe.br/sibgrapi/2020/09.10.17.52.55</metadatarepository>
		<metadatalastupdate>2022:06.14.00.00.01 sid.inpe.br/banon/2001/03.30.15.38 administrator {D 2020}</metadatalastupdate>
		<doi>10.1109/SIBGRAPI51738.2020.00011</doi>
		<citationkey>AlegreOliv:2020:InMuTr</citationkey>
		<title>SelfieArt: Interactive Multi-Style Transfer for Selfies and Videos with Soft Transitions</title>
		<format>On-line</format>
		<year>2020</year>
		<numberoffiles>1</numberoffiles>
		<size>9734 KiB</size>
		<author>Alegre, Lucas N.,</author>
		<author>Oliveira, Manuel M.,</author>
		<affiliation>Universidade Federal do Rio Grande do Sul (UFRGS)</affiliation>
		<affiliation>Universidade Federal do Rio Grande do Sul (UFRGS)</affiliation>
		<editor>Musse, Soraia Raupp,</editor>
		<editor>Cesar Junior, Roberto Marcondes,</editor>
		<editor>Pelechano, Nuria,</editor>
		<editor>Wang, Zhangyang (Atlas),</editor>
		<e-mailaddress>lnalegre@inf.ufrgrs.br</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 33 (SIBGRAPI)</conferencename>
		<conferencelocation>Porto de Galinhas (virtual)</conferencelocation>
		<date>7-10 Nov. 2020</date>
		<publisher>IEEE Computer Society</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>multi-style transfer,semantic segmentation,selfie.</keywords>
		<abstract>We introduce SelfieArt, an interactive technique for performing multi-style transfer for portraits and videos. Our method provides a simple and intuitive way of producing exquisite artistic results that combine multiple styles in a harmonious fashion. It uses face parsing and a multi-style transfer model to apply different styles to the various semantic segments. This is achieved using parameterized soft masks, allowing users to adjust the smoothness of the transitions between stylized regions in real-time. We demonstrate the effectiveness of our solution on a large set of images and videos. Given its flexibility, speed, and quality of results, our solution can be a valuable tool for creative exploration, allowing anyone to transform photographs and drawings in world-class artistic results.</abstract>
		<language>en</language>
		<targetfile>Paper ID 99.pdf</targetfile>
		<usergroup>lnalegre@inf.ufrgrs.br</usergroup>
		<visibility>shown</visibility>
		<documentstage>not transferred</documentstage>
		<mirrorrepository>sid.inpe.br/banon/2001/03.30.15.38.24</mirrorrepository>
		<nexthigherunit>8JMKD3MGPEW34M/43G4L9S</nexthigherunit>
		<nexthigherunit>8JMKD3MGPEW34M/4742MCS</nexthigherunit>
		<citingitemlist>sid.inpe.br/sibgrapi/2020/10.28.20.46 4</citingitemlist>
		<hostcollection>sid.inpe.br/banon/2001/03.30.15.38</hostcollection>
		<username>lnalegre@inf.ufrgrs.br</username>
		<agreement>agreement.html .htaccess .htaccess2</agreement>
		<lasthostcollection>sid.inpe.br/banon/2001/03.30.15.38</lasthostcollection>
		<url>http://sibgrapi.sid.inpe.br/rep-/sid.inpe.br/sibgrapi/2020/09.10.17.52</url>
	</metadata>
</metadatalist>