中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Geometry Flow-Based Deep Riemannian Metric Learning

文献类型:期刊论文

作者Yangyang Li; Chaoqun Fei; Chuanqing Wang; Hongming Shan; Ruqian Lu
刊名IEEE/CAA Journal of Automatica Sinica
出版日期2023
卷号10期号:9页码:1882-1892
关键词Curvature regularization deep metric learning (DML) embedding learning geometry flow riemannian metric
ISSN号2329-9266
DOI10.1109/JAS.2023.123399
英文摘要Deep metric learning (DML) has achieved great results on visual understanding tasks by seamlessly integrating conventional metric learning with deep neural networks. Existing deep metric learning methods focus on designing pair-based distance loss to decrease intra-class distance while increasing inter-class distance. However, these methods fail to preserve the geometric structure of data in the embedding space, which leads to the spatial structure shift across mini-batches and may slow down the convergence of embedding learning. To alleviate these issues, by assuming that the input data is embedded in a lower-dimensional sub-manifold, we propose a novel deep Riemannian metric learning (DRML) framework that exploits the non-Euclidean geometric structural information. Considering that the curvature information of data measures how much the Riemannian (non-Euclidean) metric deviates from the Euclidean metric, we leverage geometry flow, which is called a geometric evolution equation, to characterize the relation between the Riemannian metric and its curvature. Our DRML not only regularizes the local neighborhoods connection of the embeddings at the hidden layer but also adapts the embeddings to preserve the geometric structure of the data. On several benchmark datasets, the proposed DRML outperforms all existing methods and these results demonstrate its effectiveness.
源URL[http://ir.ia.ac.cn/handle/173211/52376]  
专题自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica
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GB/T 7714
Yangyang Li,Chaoqun Fei,Chuanqing Wang,et al. Geometry Flow-Based Deep Riemannian Metric Learning[J]. IEEE/CAA Journal of Automatica Sinica,2023,10(9):1882-1892.
APA Yangyang Li,Chaoqun Fei,Chuanqing Wang,Hongming Shan,&Ruqian Lu.(2023).Geometry Flow-Based Deep Riemannian Metric Learning.IEEE/CAA Journal of Automatica Sinica,10(9),1882-1892.
MLA Yangyang Li,et al."Geometry Flow-Based Deep Riemannian Metric Learning".IEEE/CAA Journal of Automatica Sinica 10.9(2023):1882-1892.

入库方式: OAI收割

来源:自动化研究所

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