Graphical Models最新文献_第9页

A deep architecture for log-Euclidean Fisher vector end-to-end learning with application to 3D point cloud classification 一个深度架构的对数欧氏费雪向量端到端学习与应用于三维点云分类

IF 1.7 4区计算机科学

Graphical Models Pub Date : 2022-09-01 DOI: 10.1016/j.gmod.2022.101164

Amira Chekir

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引用次数: 2

Construction of quasi-Bézier surfaces from boundary conditions 从边界条件构造拟bsamzier曲面

IF 1.7 4区计算机科学

Graphical Models Pub Date : 2022-09-01 DOI: 10.1016/j.gmod.2022.101159

Yong-Xia Hao, Ting Li

引用次数: 0

Deep functional maps for simultaneously computing direct and symmetric correspondences of 3D shapes 用于同时计算三维形状的直接和对称对应的深度功能映射

IF 1.7 4区计算机科学

Graphical Models Pub Date : 2022-09-01 DOI: 10.1016/j.gmod.2022.101163

Hui Wang , Bitao Ma , Junjie Cao , Xiuping Liu , Hui Huang

{"title":"Deep functional maps for simultaneously computing direct and symmetric correspondences of 3D shapes","authors":"Hui Wang , Bitao Ma , Junjie Cao , Xiuping Liu , Hui Huang","doi":"10.1016/j.gmod.2022.101163","DOIUrl":"https://doi.org/10.1016/j.gmod.2022.101163","url":null,"abstract":"<div><p><span>We introduce a novel method of isometric correspondences for 3D shapes, designed to address the problem of multiple solutions associated with deep functional maps when matching shapes with left-to-right reflectional intrinsic symmetries. Unlike the existing methods that only find the direct correspondences using single </span>Siamese network, our proposed method is able to detect both the direct and symmetric correspondences among shapes simultaneously. Furthermore, our method detects the reflectional intrinsic symmetry of each shape. Key to our method is the using of two Siamese networks that learn consistent direct descriptors and their symmetric ones, combined with carefully designed regularized functional maps and supervised loss. This leads to the first deep functional map capable of both producing two high-quality correspondences of shapes and detecting the left-to-right reflectional intrinsic symmetry of each shape. Extensive experiments demonstrate that the proposed method obtains more accurate results than state-of-the-art methods for shape correspondences and reflectional intrinsic symmetries detection.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"123 ","pages":"Article 101163"},"PeriodicalIF":1.7,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91718990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Patch-based mesh inpainting via low rank recovery 基于补丁的网格绘制通过低等级恢复

IF 1.7 4区计算机科学

Graphical Models Pub Date : 2022-07-01 DOI: 10.1016/j.gmod.2022.101139

Xiaoqun Wu, Xiaoyun Lin, Nan Li, Haisheng Li

引用次数: 2

Out-of-core outlier removal for large-scale indoor point clouds 大规模室内点云的核外离群值去除

IF 1.7 4区计算机科学

Graphical Models Pub Date : 2022-07-01 DOI: 10.1016/j.gmod.2022.101142

Linlin Ge, Jieqing Feng

引用次数: 0

Untangling all-hex meshes via adaptive boundary optimization 通过自适应边界优化解开所有六边形网格

IF 1.7 4区计算机科学

Graphical Models Pub Date : 2022-05-01 DOI: 10.1016/j.gmod.2022.101136

Qing Huang, Wen-Xiang Zhang, Qi Wang, Ligang Liu, Xiao-Ming Fu

{"title":"Untangling all-hex meshes via adaptive boundary optimization","authors":"Qing Huang, Wen-Xiang Zhang, Qi Wang, Ligang Liu, Xiao-Ming Fu","doi":"10.1016/j.gmod.2022.101136","DOIUrl":"https://doi.org/10.1016/j.gmod.2022.101136","url":null,"abstract":"<div><p>We propose a novel method to untangle and optimize all-hex meshes. Central to this algorithm is an adaptive boundary optimization process that significantly improves practical robustness. Given an all-hex mesh with many inverted hexahedral elements, we first optimize a high-quality quad boundary mesh with a small approximation<span> error to the input boundary. Since the boundary constraints limit the optimization space to search for the inversion-free meshes, we then relax the boundary constraints to generate an inversion-free all-hex mesh. We develop an adaptive boundary relaxation algorithm to implicitly restrict the shape difference between the relaxed and input boundaries, thereby facilitating the next step. Finally, an adaptive boundary difference minimization is developed to effectively and efficiently force the distance difference between the relaxed boundary and the optimized boundary of the first step to approach zero while avoiding inverted elements. We demonstrate the efficacy of our algorithm on a data set containing 1004 all-hex meshes. Compared to previous methods, our method achieves higher practical robustness.</span></p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"121 ","pages":"Article 101136"},"PeriodicalIF":1.7,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72219342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

TAD-Net: tooth axis detection network based on rotation transformation encoding TAD-Net:基于旋转变换编码的齿轴检测网络

IF 1.7 4区计算机科学

Graphical Models Pub Date : 2022-05-01 DOI: 10.1016/j.gmod.2022.101138

Yeying Fan , Qian Ma , Guangshun Wei , Zhiming Cui , Yuanfeng Zhou , Wenping Wang

引用次数: 0

3D Printed hair modeling from strand-level hairstyles 3D打印头发造型，从发丝级别发型

IF 1.7 4区计算机科学

Graphical Models Pub Date : 2022-05-01 DOI: 10.1016/j.gmod.2022.101135

Han Chen, Minghai Chen, Lin Lu

{"title":"3D Printed hair modeling from strand-level hairstyles","authors":"Han Chen, Minghai Chen, Lin Lu","doi":"10.1016/j.gmod.2022.101135","DOIUrl":"https://doi.org/10.1016/j.gmod.2022.101135","url":null,"abstract":"<div><p><span><span>Recent advances in the design and fabrication of personalized figurines have made the creation of high-quality figurines possible for ordinary users with the facilities of 3D printing<span> techniques. The hair plays an important role in gaining the realism of the figurines. Existing hair reconstruction methods suffer from the high demand for acquisition equipment, or the result is approximated very coarsely. Instead of creating hairs for figurines by scanning devices, we present a novel surface reconstruction method to generate a 3D printable hair model with geometric features from a strand-level hairstyle, thus converting the exiting digital hair database to a 3D printable database. Given a strand-level hair model, we filter the strands via bundle clustering, retain the main features, and reconstruct hair strands in two stages. First, our algorithm is the key to extracting the hair contour surface according to the structure of strands and calculating the normal for each vertex. Next, a close, manifold triangle mesh with </span></span>geometric details and an embedded </span>direction field is achieved with the Poisson surface reconstruction. We obtain closed-manifold hairstyles without user interactions, benefiting personalized figurine fabrication. We verify the feasibility of our method by exhibiting a wide range of examples.</p></div>","PeriodicalId":55083,"journal":{"name":"Graphical Models","volume":"121 ","pages":"Article 101135"},"PeriodicalIF":1.7,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72219324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Point cloud denoising review: from classical to deep learning-based approaches 点云去噪综述：从经典到基于深度学习的方法

IF 1.7 4区计算机科学

Graphical Models Pub Date : 2022-05-01 DOI: 10.1016/j.gmod.2022.101140

Lang Zhou , Guoxing Sun , Yong Li , Weiqing Li , Zhiyong Su

引用次数: 0

Jacobi–PIA algorithm for bi-cubic B-spline interpolation surfaces 双三次b样条插值曲面的Jacobi-PIA算法

IF 1.7 4区计算机科学

Graphical Models Pub Date : 2022-03-01 DOI: 10.1016/j.gmod.2022.101134

Chengzhi Liu, Juncheng Li, Lijuan Hu

引用次数: 3