Please use this identifier to cite or link to this item:
Title: HMANet: Hyperbolic Manifold Aware Network for Skeleton-Based Action Recognition
Authors: Chen, J
Zhao, C
Wang, Q
Meng, H
Keywords: action recognition;hyperbolic manifold;Poincaré model;Riemannian geometry;spatio-temporal features
Issue Date: 2-May-2022
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: Chen, J., Zhao, C., Wang, Q. and Meng, H. (2022) 'HMANet: Hyperbolic Manifold Aware Network for Skeleton-Based Action Recognition', IEEE Transactions on Cognitive and Developmental Systems, 0 (in press), pp. 1 - 13. doi: 10.1109/tcds.2022.3171550.
ISSN: 2379-8920
Appears in Collections:Dept of Electronic and Computer Engineering Research Papers

Files in This Item:
File Description SizeFormat 
FullText.pdfCopyright © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.19.19 MBAdobe PDFView/Open

Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.