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Multiscale Mesh Deformation Component Analysis With Attention-Based Autoencoders

文献类型：期刊论文

作者Yang, Jie3,4; Gao, Lin3,4; Tan, Qingyang2; Huang, Yi-Hua3,4; Xia, Shihong3,4; Lai, Yu-Kun1
刊名IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
出版日期2023-02-01
卷号29期号:2页码:1301-1317
关键词Multi-scale shape analysis attention mechanism sparse regularization stacked auto-encoder
ISSN号1077-2626
DOI10.1109/TVCG.2021.3112526
英文摘要Deformation component analysis is a fundamental problem in geometry processing and shape understanding. Existing approaches mainly extract deformation components in local regions at a similar scale while deformations of real-world objects are usually distributed in a multi-scale manner. In this article, we propose a novel method to exact multiscale deformation components automatically with a stacked attention-based autoencoder. The attention mechanism is designed to learn to softly weight multi-scale deformation components in active deformation regions, and the stacked attention-based autoencoder is learned to represent the deformation components at different scales. Quantitative and qualitative evaluations show that our method outperforms state-of-the-art methods. Furthermore, with the multiscale deformation components extracted by our method, the user can edit shapes in a coarse-to-fine fashion which facilitates effective modeling of new shapes.
资助项目National Natural Science Foundation of China[62061136007] ; National Natural Science Foundation of China[61872440] ; Beijing Municipal Natural Science Foundation[L182016] ; Science and Technology Service Network Initiative ; Chinese Academy of Sciences[KFJ-STS-QYZD-2021-11-001] ; Royal Society Newton Advanced Fellowship[NAF\R2\192151] ; Youth Innovation Promotion Association CAS ; Zhejiang Lab[2021KE0AB06]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000906475100002
出版者IEEE COMPUTER SOC
源URL[http://119.78.100.204/handle/2XEOYT63/20065]  
专题中国科学院计算技术研究所期刊论文
通讯作者Gao, Lin
作者单位1.Cardiff Univ, Sch Comp Sci & Informat, Cardiff CF10 3AT, Wales
2.Univ Maryland, College Pk, MD 20742 USA
3.Univ Chinese Acad Sci, Beijing 100864, Peoples R China
4.Chinese Acad Sci, Inst Comp Technol, Beijing Key Lab Mobile Comp & Pervas Device, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Yang, Jie,Gao, Lin,Tan, Qingyang,et al. Multiscale Mesh Deformation Component Analysis With Attention-Based Autoencoders[J]. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS,2023,29(2):1301-1317.
APA Yang, Jie,Gao, Lin,Tan, Qingyang,Huang, Yi-Hua,Xia, Shihong,&Lai, Yu-Kun.(2023).Multiscale Mesh Deformation Component Analysis With Attention-Based Autoencoders.IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS,29(2),1301-1317.
MLA Yang, Jie,et al."Multiscale Mesh Deformation Component Analysis With Attention-Based Autoencoders".IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 29.2(2023):1301-1317.

入库方式： OAI收割

来源：计算技术研究所

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