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Learning local shape descriptors for computing non-rigid dense correspondence | |
Jianwei Guo; Hanyu Wang; Zhanglin Cheng; Xiaopeng Zhang; Dong-Ming Yan | |
发表期刊 | computationalvisualmedia |
ISSN | 2096-0433 |
2020 | |
卷号 | 6期号:1页码:95-112 |
摘要 | A 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. |
DOI | 10.1007/s41095-020-0163-y |
语种 | 英语 |
七大方向——子方向分类 | 三维视觉 |
国重实验室规划方向分类 | 环境多维感知 |
是否有论文关联数据集需要存交 | 否 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/41487 |
专题 | 多模态人工智能系统全国重点实验室_三维可视计算 |
通讯作者 | Zhanglin Cheng; Dong-Ming Yan |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.University of Maryland-College Park 3.Chinese Academy of Sciences |
推荐引用方式 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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2020-CVMJ.pdf(4814KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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