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Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Identifier8JMKD3MGPEW34M/45DPE5L
Repositorysid.inpe.br/sibgrapi/2021/09.11.20.09
Last Update2021:09.11.20.09.14 (UTC) schirmer.luizj@gmail.com
Metadatasid.inpe.br/sibgrapi/2021/09.11.20.09.14
Metadata Last Update2021:11.12.11.47.14 (UTC) administrator
Citation KeySchirmerSSNYMPVL:2021:NeNeIm
TitleNeural Networks for Implicit Representations of 3D Scenes
FormatOn-line
Year2021
Access Date2022, Jan. 22
Number of Files1
Size5299 KiB
Context area
Author1 Schirmer, Luiz
2 Schardong, Guilherme
3 Silva, Vinícius da
4 Novello, Tiago
5 Yukimura, Daniel
6 Magalhães, Thales
7 Paz, Hallison
8 Velho, Luiz
9 Lopes, Hélio
Affiliation1 PUC-Rio
2 PUC-Rio
3 PUC-Rio
4 IMPA
5 IMPA
6 IMPA
7 IMPA
8 IMPA
9 PUC-Rio
EditorPaiva, Afonso
Menotti, David
Baranoski, Gladimir V. G.
Proença, Hugo Pedro
Junior, Antonio Lopes Apolinario
Papa, João Paulo
Pagliosa, Paulo
dos Santos, Thiago Oliveira
e Sá, Asla Medeiros
da Silveira, Thiago Lopes Trugillo
Brazil, Emilio Vital
Ponti, Moacir A.
Fernandes, Leandro A. F.
Avila, Sandra
e-Mail Addressschirmer.luizj@gmail.com
Conference NameConference on Graphics, Patterns and Images, 34 (SIBGRAPI)
Conference LocationGramado (Virtual), Brazil
DateOctober 18th to October 22nd, 2021
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeTutorial
History (UTC)2021-10-05 00:47:12 :: schirmer.luizj@gmail.com -> administrator :: 2021
2021-11-12 11:47:14 :: administrator -> schirmer.luizj@gmail.com :: 2021
Content and structure area
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Content TypeExternal Contribution
KeywordsNeural Networks
Implicit Functions
Signal Distance Functions
AbstractThis survey presents methods that use neural networks for implicit representations of 3D geometry --- neural implicit functions. We explore the different aspects of neural implicit functions for shape modeling and synthesis. We aim to provide a theoretical analysis of 3D shape reconstruction using deep neural networks and introduce a discussion between researchers interested in this research field.
Arrangementurlib.net > SDLA > SIBGRAPI 2021 > Neural Networks for...
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data URLhttp://sibgrapi.sid.inpe.br/ibi/8JMKD3MGPEW34M/45DPE5L
zipped data URLhttp://sibgrapi.sid.inpe.br/zip/8JMKD3MGPEW34M/45DPE5L
Languageen
Target FileTutorial_Sibgrapi_2021 (2).pdf
User Groupschirmer.luizj@gmail.com
Visibilityshown
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Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/45PQ3RS
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
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e-Mail (login)schirmer.luizj@gmail.com
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