CASIA OpenIR
Learning local shape descriptors for computing non-rigid dense correspondence
Jianwei Guo; Hanyu Wang; Zhanglin Cheng; Xiaopeng Zhang; Dong-Ming Yan
Source Publicationcomputationalvisualmedia
ISSN2096-0433
2020
Volume6Issue:1Pages:95-112
AbstractA discriminative local shape descriptor plays an important role in various applications. In this paper, we present a novel deep learning framework that derives discriminative local descriptors for deformable 3D shapes. We use local “geometry images” to encode the multi-scale local features of a point, via an intrinsic parameterization method based on geodesic polar coordinates. This new parameterization provides robust geometry images even for badly-shaped triangular meshes. Then a triplet network with shared architecture and parameters is used to perform deep metric learning; its aim is to distinguish between similar and dissimilar pairs of points. Additionally, a newly designed triplet loss function is minimized for improved, accurate training of the triplet network. To solve the dense correspondence problem, an efficient sampling approach is utilized to achieve a good compromise between training performance and descriptor quality. During testing, given a geometry image of a point of interest, our network outputs a discriminative local descriptor for it. Extensive testing of non-rigid dense shape matching on a variety of benchmarks demonstrates the superiority of the proposed descriptors over the state-of-the-art alternatives.
DOI10.1007/s41095-020-0163-y
Language英语
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/41487
Collection中国科学院自动化研究所
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.University of Maryland-College Park
3.Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Jianwei Guo,Hanyu Wang,Zhanglin Cheng,et al. Learning local shape descriptors for computing non-rigid dense correspondence[J]. computationalvisualmedia,2020,6(1):95-112.
APA Jianwei Guo,Hanyu Wang,Zhanglin Cheng,Xiaopeng Zhang,&Dong-Ming Yan.(2020).Learning local shape descriptors for computing non-rigid dense correspondence.computationalvisualmedia,6(1),95-112.
MLA Jianwei Guo,et al."Learning local shape descriptors for computing non-rigid dense correspondence".computationalvisualmedia 6.1(2020):95-112.
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