Kanglei Zhou
MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality Assessment
Zhou, Kanglei; Wang, Liyuan; Zhang, Xingxing; Shum, Hubert P. H.; Li, Frederick W. B.; Li, Jianguo; Liang, Xiaohui
Authors
Liyuan Wang
Xingxing Zhang
Professor Hubert Shum hubert.shum@durham.ac.uk
Professor
Dr Frederick Li frederick.li@durham.ac.uk
Associate Professor
Jianguo Li
Xiaohui Liang
Citation
Zhou, K., Wang, L., Zhang, X., Shum, H. P. H., Li, F. W. B., Li, J., & Liang, X. (2024, September). MAGR: Manifold-Aligned Graph Regularization for Continual Action Quality Assessment. Presented at ECCV 2024: The 18th European Conference on Computer Vision, Milan, Italy
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | ECCV 2024: The 18th European Conference on Computer Vision |
Start Date | Sep 29, 2024 |
End Date | Oct 4, 2024 |
Acceptance Date | Jul 6, 2024 |
Deposit Date | Aug 5, 2024 |
Print ISSN | 0302-9743 |
Publisher | Springer |
Peer Reviewed | Peer Reviewed |
Series Title | Lecture Notes in Computer Science |
Series ISSN | 0302-9743 |
Public URL | https://durham-repository.worktribe.com/output/2740857 |
Publisher URL | https://link.springer.com/conference/eccv |
This file is under embargo due to copyright reasons.
You might also like
Advances in Web-Based Learning - ICWL 2015
(-0001)
Book
Tackling Data Bias in Painting Classification with Style Transfer
(2023)
Presentation / Conference Contribution
Aesthetic Enhancement via Color Area and Location Awareness
(2022)
Presentation / Conference Contribution
STIT: Spatio-Temporal Interaction Transformers for Human-Object Interaction Recognition in Videos
(2022)
Presentation / Conference Contribution
STGAE: Spatial-Temporal Graph Auto-Encoder for Hand Motion Denoising
(2021)
Presentation / Conference Contribution
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search