S2RF: Semantically Stylized Radiance Fields

S2RF: Semantically Stylized Radiance Fields

We present our method for transferring style from any arbitrary image(s) to object(s) within a 3D scene. Our primary objective is to offer more control in 3D scene stylization, facilitating the creation of customizable and stylized scene images from arbitrary viewpoints. To achieve this, we propose...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:arXiv.org 2023-09
Hauptverfasser: Lahiri, Dishani, Panse, Neeraj, Kumar, Moneish
Format: Artikel
Sprache:eng
Schlagworte:
Image reconstruction
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title arXiv.org
container_volume
creator Lahiri, Dishani
Panse, Neeraj
Kumar, Moneish
description We present our method for transferring style from any arbitrary image(s) to object(s) within a 3D scene. Our primary objective is to offer more control in 3D scene stylization, facilitating the creation of customizable and stylized scene images from arbitrary viewpoints. To achieve this, we propose a novel approach that incorporates nearest neighborhood-based loss, allowing for flexible 3D scene reconstruction while effectively capturing intricate style details and ensuring multi-view consistency.
format Article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2861509982</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2861509982</sourcerecordid><originalsourceid>FETCH-proquest_journals_28615099823</originalsourceid><addsrcrecordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mTQDjYKcrNSCE7NTcwryUxOzMmpVAguqczJrEpNUQhKTMlMzEtOVXDLTM1JKeZhYE1LzClO5YXS3AzKbq4hzh66BUX5haWpxSXxWfmlRXlAqXgjCzNDUwNLSwsjY-JUAQD0dzCX</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2861509982</pqid></control><display><type>article</type><title>S2RF: Semantically Stylized Radiance Fields</title><source>Free E- Journals</source><creator>Lahiri, Dishani ; Panse, Neeraj ; Kumar, Moneish</creator><creatorcontrib>Lahiri, Dishani ; Panse, Neeraj ; Kumar, Moneish</creatorcontrib><description>We present our method for transferring style from any arbitrary image(s) to object(s) within a 3D scene. Our primary objective is to offer more control in 3D scene stylization, facilitating the creation of customizable and stylized scene images from arbitrary viewpoints. To achieve this, we propose a novel approach that incorporates nearest neighborhood-based loss, allowing for flexible 3D scene reconstruction while effectively capturing intricate style details and ensuring multi-view consistency.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Image reconstruction</subject><ispartof>arXiv.org, 2023-09</ispartof><rights>2023. This work is published under http://arxiv.org/licenses/nonexclusive-distrib/1.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>780,784</link.rule.ids></links><search><creatorcontrib>Lahiri, Dishani</creatorcontrib><creatorcontrib>Panse, Neeraj</creatorcontrib><creatorcontrib>Kumar, Moneish</creatorcontrib><title>S2RF: Semantically Stylized Radiance Fields</title><title>arXiv.org</title><description>We present our method for transferring style from any arbitrary image(s) to object(s) within a 3D scene. Our primary objective is to offer more control in 3D scene stylization, facilitating the creation of customizable and stylized scene images from arbitrary viewpoints. To achieve this, we propose a novel approach that incorporates nearest neighborhood-based loss, allowing for flexible 3D scene reconstruction while effectively capturing intricate style details and ensuring multi-view consistency.</description><subject>Image reconstruction</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNpjYuA0MjY21LUwMTLiYOAtLs4yMDAwMjM3MjU15mTQDjYKcrNSCE7NTcwryUxOzMmpVAguqczJrEpNUQhKTMlMzEtOVXDLTM1JKeZhYE1LzClO5YXS3AzKbq4hzh66BUX5haWpxSXxWfmlRXlAqXgjCzNDUwNLSwsjY-JUAQD0dzCX</recordid><startdate>20230903</startdate><enddate>20230903</enddate><creator>Lahiri, Dishani</creator><creator>Panse, Neeraj</creator><creator>Kumar, Moneish</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope></search><sort><creationdate>20230903</creationdate><title>S2RF: Semantically Stylized Radiance Fields</title><author>Lahiri, Dishani ; Panse, Neeraj ; Kumar, Moneish</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_28615099823</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Image reconstruction</topic><toplevel>online_resources</toplevel><creatorcontrib>Lahiri, Dishani</creatorcontrib><creatorcontrib>Panse, Neeraj</creatorcontrib><creatorcontrib>Kumar, Moneish</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lahiri, Dishani</au><au>Panse, Neeraj</au><au>Kumar, Moneish</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>S2RF: Semantically Stylized Radiance Fields</atitle><jtitle>arXiv.org</jtitle><date>2023-09-03</date><risdate>2023</risdate><eissn>2331-8422</eissn><abstract>We present our method for transferring style from any arbitrary image(s) to object(s) within a 3D scene. Our primary objective is to offer more control in 3D scene stylization, facilitating the creation of customizable and stylized scene images from arbitrary viewpoints. To achieve this, we propose a novel approach that incorporates nearest neighborhood-based loss, allowing for flexible 3D scene reconstruction while effectively capturing intricate style details and ensuring multi-view consistency.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier EISSN: 2331-8422
ispartof arXiv.org, 2023-09
issn 2331-8422
language eng
recordid cdi_proquest_journals_2861509982
source Free E- Journals
subjects Image reconstruction
title S2RF: Semantically Stylized Radiance Fields
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-11T10%3A19%3A32IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=S2RF:%20Semantically%20Stylized%20Radiance%20Fields&rft.jtitle=arXiv.org&rft.au=Lahiri,%20Dishani&rft.date=2023-09-03&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2861509982%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2861509982&rft_id=info:pmid/&rfr_iscdi=true