1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPEW34M/45CPHC5 |
Repository | sid.inpe.br/sibgrapi/2021/09.05.17.11 |
Last Update | 2021:09.05.17.11.38 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2021/09.05.17.11.38 |
Metadata Last Update | 2022:06.14.00.00.26 (UTC) administrator |
DOI | 10.1109/SIBGRAPI54419.2021.00016 |
Citation Key | VieiraOliv:2021:GaEsVi |
Title | Gaze estimation via self-attention augmented convolutions |
Format | On-line |
Year | 2021 |
Access Date | 2024, Sep. 20 |
Number of Files | 1 |
Size | 1497 KiB |
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2. Context | |
Author | 1 Vieira, Gabriel Lefundes 2 Oliveira, Luciano |
Affiliation | 1 Federal University of Bahia 2 Federal University of Bahia |
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 | lefundes.gabriel@gmail.com |
Conference Name | Conference on Graphics, Patterns and Images, 34 (SIBGRAPI) |
Conference Location | Gramado, RS, Brazil (virtual) |
Date | 18-22 Oct. 2021 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full Paper |
History (UTC) | 2021-09-05 17:11:38 :: lefundes.gabriel@gmail.com -> administrator :: 2022-03-02 00:54:15 :: administrator -> menottid@gmail.com :: 2021 2022-03-02 13:39:55 :: menottid@gmail.com -> administrator :: 2021 2022-06-14 00:00:26 :: administrator -> :: 2021 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Version Type | finaldraft |
Keywords | deep learning gaze estimation attention-augmented convolutions |
Abstract | Although recently deep learning methods have boosted the accuracy of appearance-based gaze estimation, there is still room for improvement in the network architectures for this particular task. Hence we propose here a novel network architecture grounded on self-attention augmented convolutions to improve the quality of the learned features during the training of a shallower residual network. The rationale is that self-attention mechanism can help outperform deeper architectures by learning dependencies between distant regions in full-face images. This mechanism can also create better and more spatially-aware feature representations derived from the face and eye images before gaze regression. We dubbed our framework ARes-gaze, which explores our Attention-augmented ResNet (ARes-14) as twin convolutional backbones. In our experiments, results showed a decrease of the average angular error by 2.38% when compared to state-of-the-art methods on the MPIIFaceGaze data set, while achieving a second-place on the EyeDiap data set. It is noteworthy that our proposed framework was the only one to reach high accuracy simultaneously on both data sets. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2021 > Gaze estimation via... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > Gaze estimation via... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/8JMKD3MGPEW34M/45CPHC5 |
zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/45CPHC5 |
Language | en |
Target File | gaze_attention_sibgrapi_2021_CAMERA_READY(1).pdf |
User Group | lefundes.gabriel@gmail.com |
Visibility | shown |
Update Permission | not transferred |
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5. Allied materials | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPEW34M/45PQ3RS 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2021/11.12.11.46 75 sid.inpe.br/sibgrapi/2022/06.10.21.49 1 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Empty Fields | archivingpolicy 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 |
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