1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPEW34M/45E57FS |
Repository | sid.inpe.br/sibgrapi/2021/09.13.20.01 |
Last Update | 2021:09.13.20.01.21 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2021/09.13.20.01.21 |
Metadata Last Update | 2022:09.10.00.16.17 (UTC) administrator |
Citation Key | SchirmerVelhLope:2021:SeGrAt |
Title | Semantic graph attention networks and tensor decompositions for computer vision and computer graphics |
Format | On-line |
Year | 2021 |
Access Date | 2024, Oct. 15 |
Number of Files | 1 |
Size | 18647 KiB |
|
2. Context | |
Author | 1 Schirmer, Luiz 2 Velho, Luiz 3 Lopes, Hélio |
Affiliation | 1 PUC-Rio 2 IMPA 3 PUC-Rio |
Editor | Paiva, 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 Address | schirmer.luizj@gmail.com |
Conference Name | Conference on Graphics, Patterns and Images, 34 (SIBGRAPI) |
Conference Location | Gramado, RS, Brazil (virtual) |
Date | 18-22 Oct. 2021 |
Publisher | Sociedade Brasileira de Computação |
Publisher City | Porto Alegre |
Book Title | Proceedings |
Tertiary Type | Master's or Doctoral Work |
History (UTC) | 2021-09-13 20:01:21 :: schirmer.luizj@gmail.com -> administrator :: 2022-09-10 00:16:17 :: administrator -> :: 2021 |
|
3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Keywords | Neural Networks Gaph Neural Networks Human Pose Estimation |
Abstract | This thesis proposes new architectures for deep neural networks with attention enhancement and multilinear algebra methods to increase their performance. We also explore graph convolutions and their particularities. We focus here on the problems related to real-time human pose estimation. We explore different architectures to reduce computational complexity, and, as a result, we propose two novel neural network models for 2D and 3D pose estimation. We also introduce a new architecture for Graph attention networks called Semantic Graph Attention. |
Arrangement | urlib.net > SDLA > Fonds > SIBGRAPI 2021 > Semantic graph attention... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | |
|
4. Conditions of access and use | |
data URL | http://urlib.net/ibi/8JMKD3MGPEW34M/45E57FS |
zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/45E57FS |
Language | en |
Target File | WTD_Sibgrapi_2021 (4).pdf |
User Group | schirmer.luizj@gmail.com |
Visibility | shown |
|
5. Allied materials | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPEW34M/45PQ3RS |
Citing Item List | sid.inpe.br/sibgrapi/2021/11.12.11.46 86 sid.inpe.br/banon/2001/03.30.15.38.24 1 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
|
6. Notes | |
Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage doi 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 versiontype volume |
|