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Point-StyleGAN: Multi-scale point cloud synthesis with style modulation 点-风格-广域网:带风格调制的多尺度点云合成
IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-04-24 DOI: 10.1016/j.cagd.2024.102309
Yang Zhou , Cheng Xu , Zhiqiang Lin , Xinwei He , Hui Huang

A point cloud is a set of discrete surface samples. As the simplest 3D representation, it is widely used in 3D reconstruction and perception. Yet developing a generative model for point clouds remains challenging due to the sparsity and irregularity of points. Drawn by StyleGAN, the forefront image generation model, this paper presents Point-StyleGAN, a generator adapted from StyleGAN2 architecture for point cloud synthesis. Specifically, we replace all the 2D convolutions with 1D ones and introduce a series of multi-resolution discriminators to overcome the under-constrained issue caused by the sparsity of points. We further add a metric learning-based loss to improve generation diversity. Besides the generation task, we show several applications based on GAN inversion, among which an inversion encoder Point-pSp is designed and applied to point cloud reconstruction, completion, and interpolation. To our best knowledge, Point-pSp is the first inversion encoder for point cloud embedding in the latent space of GANs. The comparisons to prior work and the applications of GAN inversion demonstrate the advantages of our method. We believe the potential brought by the Point-StyleGAN architecture would further inspire massive follow-up works.

点云是一组离散的表面样本。作为最简单的三维表示,它被广泛应用于三维重建和感知。然而,由于点的稀疏性和不规则性,为点云开发生成模型仍然具有挑战性。本文借鉴最前沿的图像生成模型 StyleGAN,提出了点云生成模型 Point-StyleGAN,这是一种从 StyleGAN2 架构改编而来的点云合成生成器。具体来说,我们用一维卷积替换了所有二维卷积,并引入了一系列多分辨率判别器,以克服由点稀疏性导致的约束不足问题。我们还进一步添加了基于度量学习的损失,以提高生成多样性。除了生成任务,我们还展示了基于 GAN 反演的几种应用,其中设计了一种反演编码器 Point-pSp,并将其应用于点云重建、补全和插值。据我们所知,Point-pSp 是第一个用于在 GAN 潜在空间中嵌入点云的反转编码器。与之前工作的比较以及 GAN 反演的应用证明了我们方法的优势。我们相信,Point-StyleGAN 架构所带来的潜力将进一步激发大量后续工作。
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引用次数: 0
Automated placement of dental attachments based on orthodontic pathways 根据正畸路径自动安置牙科附件
IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-04-24 DOI: 10.1016/j.cagd.2024.102320
Yiheng Lv , Guangshun Wei , Yeying Fan , Long Ma , Dongxu Liu , Yuanfeng Zhou

The aesthetic appeal and removability of clear aligners have led to their widespread popularity in orthodontic treatments. Dental attachments significantly contribute to shortening treatment duration and enhancing orthodontic outcomes. The automation of tailor-made dental attachments for individual teeth plays a crucial role in the field of orthodontics. This is because they enable more precise control over the forces applied, thereby effectively facilitating tooth movement. This study introduces an automated algorithm that generates dental attachments based on the orthodontic path. The algorithm automatically selects and places the appropriate type of attachment according to the magnitude of rotation and translation of teeth during orthodontic procedures. It adjusts the position and posture of the attachments to fit the teeth accurately. To validate the effectiveness of automatically placed attachments in guiding teeth along the predetermined path, this study employs finite element analysis to simulate the impact of attachments on teeth. Comparative analyses between the automated method and traditional manual techniques show that the proposed algorithm significantly enhances the precision and efficiency of attachment placement. Additionally, finite element simulations confirm the feasibility and effectiveness of this approach in clinical orthodontic applications, providing a novel technical pathway for automating attachment placement in orthodontic treatments and offering significant practical value for personalized and efficient orthodontic care.

透明矫治器的美观性和可拆卸性使其在正畸治疗中广受欢迎。牙齿附着器在缩短治疗时间和提高正畸效果方面做出了巨大贡献。为每颗牙齿量身定制的牙科附件的自动化在正畸领域发挥着至关重要的作用。这是因为它们能够更精确地控制施加的力量,从而有效地促进牙齿移动。本研究介绍了一种根据正畸路径生成牙齿附着体的自动算法。该算法可根据正畸过程中牙齿旋转和平移的幅度,自动选择和放置适当类型的附着体。它还能调整附着体的位置和姿势,使其与牙齿准确贴合。为了验证自动放置的附着体在引导牙齿沿着预定路径移动方面的有效性,本研究采用了有限元分析来模拟附着体对牙齿的影响。自动方法与传统人工技术的对比分析表明,所提出的算法大大提高了附着体安置的精确度和效率。此外,有限元模拟证实了这种方法在临床正畸应用中的可行性和有效性,为在正畸治疗中自动安置附着体提供了一条新的技术途径,为个性化和高效的正畸护理提供了重要的实用价值。
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引用次数: 0
An attention enhanced dual graph neural network for mesh denoising 用于网格去噪的注意力增强型双图神经网络
IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-04-24 DOI: 10.1016/j.cagd.2024.102307
Mengxing Wang , Yi-Fei Feng , Bowen Lyu , Li-Yong Shen , Chun-Ming Yuan

Mesh denoising is a crucial research topic in geometric processing, as it is widely used in reverse engineering and 3D modeling. The main objective of denoising is to eliminate noise while preserving sharp features. In this paper, we propose a novel denoising method called Attention Enhanced Dual Mesh Denoise (ADMD), which is based on a graph neural network and attention mechanism. ADMD simulates the two-stage denoising method by using a new training strategy and total variation (TV) regular term to enhance feature retention. Our experiments have demonstrated that ADMD can achieve competitive or superior results to state-of-the-art methods for noise CAD models, non-CAD models, and real-scanned data. Moreover, our method can effectively handle large mesh models with different-scale noisy situations and prevent model shrinking after mesh denoising.

网格去噪是几何处理领域的一个重要研究课题,因为它被广泛应用于逆向工程和三维建模。去噪的主要目的是消除噪声,同时保留清晰的特征。本文提出了一种名为 "注意力增强双网格去噪"(Attention Enhanced Dual Mesh Denoise,ADMD)的新型去噪方法,该方法基于图神经网络和注意力机制。ADMD 通过使用新的训练策略和总变异(TV)正则项来增强特征保留,从而模拟两阶段去噪方法。我们的实验证明,ADMD 在噪声 CAD 模型、非 CAD 模型和真实扫描数据上都能取得与最先进方法相当或更优的结果。此外,我们的方法还能有效处理不同尺度噪声情况下的大型网格模型,并防止网格去噪后模型缩小。
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引用次数: 0
A task-driven network for mesh classification and semantic part segmentation 用于网格分类和语义部分分割的任务驱动网络
IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-04-24 DOI: 10.1016/j.cagd.2024.102304
Qiujie Dong , Xiaoran Gong , Rui Xu , Zixiong Wang , Junjie Gao , Shuangmin Chen , Shiqing Xin , Changhe Tu , Wenping Wang

Given the rapid advancements in geometric deep-learning techniques, there has been a dedicated effort to create mesh-based convolutional operators that act as a link between irregular mesh structures and widely adopted backbone networks. Despite the numerous advantages of Convolutional Neural Networks (CNNs) over Multi-Layer Perceptrons (MLPs), mesh-oriented CNNs often require intricate network architectures to tackle irregularities of a triangular mesh. These architectures not only demand that the mesh be manifold and watertight but also impose constraints on the abundance of training samples. In this paper, we note that for specific tasks such as mesh classification and semantic part segmentation, large-scale shape features play a pivotal role. This is in contrast to the realm of shape correspondence, where a comprehensive understanding of 3D shapes necessitates considering both local and global characteristics. Inspired by this key observation, we introduce a task-driven neural network architecture that seamlessly operates in an end-to-end fashion. Our method takes as input mesh vertices equipped with the heat kernel signature (HKS) and dihedral angles between adjacent faces. Notably, we replace the conventional convolutional module, commonly found in ResNet architectures, with MLPs and incorporate Layer Normalization (LN) to facilitate layer-wise normalization. Our approach, with a seemingly straightforward network architecture, demonstrates an accuracy advantage. It exhibits a marginal 0.1% improvement in the mesh classification task and a substantial 1.8% enhancement in the mesh part segmentation task compared to state-of-the-art methodologies. Moreover, as the number of training samples decreases to 1/50 or even 1/100, the accuracy advantage of our approach becomes more pronounced. In summary, our convolution-free network is tailored for specific tasks relying on large-scale shape features and excels in the situation with a limited number of training samples, setting itself apart from state-of-the-art methodologies.

鉴于几何深度学习技术的快速发展,人们一直致力于创建基于网格的卷积算子,作为不规则网格结构与广泛采用的骨干网络之间的纽带。尽管与多层感知器(MLP)相比,卷积神经网络(CNN)具有诸多优势,但面向网格的 CNN 通常需要复杂的网络架构来处理三角形网格的不规则性。这些架构不仅要求网格具有多面性和无懈可击性,还对训练样本的丰富程度施加了限制。在本文中,我们注意到在网格分类和语义部分分割等特定任务中,大规模形状特征起着举足轻重的作用。这与形状对应领域形成了鲜明对比,在形状对应领域,要全面了解三维形状,必须同时考虑局部和全局特征。受这一重要观点的启发,我们引入了一种任务驱动型神经网络架构,该架构以端到端的方式无缝运行。我们的方法将配备热核特征(HKS)的网格顶点和相邻面之间的二面角作为输入。值得注意的是,我们用 MLP 取代了 ResNet 架构中常见的传统卷积模块,并加入了层归一化(LN)以促进层归一化。我们的方法采用看似简单的网络架构,但在准确性方面却具有优势。与最先进的方法相比,它在网格分类任务中提高了 0.1%,在网格部分分割任务中提高了 1.8%。此外,当训练样本数减少到 1/50 甚至 1/100 时,我们的方法在准确性上的优势会更加明显。总之,我们的无卷积网络专为依赖大规模形状特征的特定任务定制,并在训练样本数量有限的情况下表现出色,从而在最先进的方法中脱颖而出。
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引用次数: 0
Computing nodes for plane data points by constructing cubic polynomial with constraints 通过构建带约束条件的三次多项式计算平面数据点的节点
IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-04-24 DOI: 10.1016/j.cagd.2024.102308
Hua Wang , Fan Zhang

To construct a parametric polynomial curve for interpolating a set of data points, the interpolation accuracy and shape of the constructed curve are influenced by two principal factors: parameterization of the data points (computing a node for each data point) and interpolation method. A new method of computing nodes for a set of data points was proposed. In this paper, the functional relationship between data points and corresponding nodes in cubic polynomials was established. Using this functional relationship, a functional cubic polynomial with one degree of freedom can pass through four adjacent data points. The degree of the freedom can be represented by two adjacent node intervals can be obtained by minimizing the cubic terms of the cubic polynomial. Since each node is computed in different node spaces, a method for constructing a quadratic curve is presented, which transforms all the quadratic curves into a unified form to compute nodes. Nodes computed using the new method exhibit quadratic polynomial precision, i.e., if the set of data point is taken from a quadratic polynomial F(t), the nodes by the new method are used to construct a interpolation curve, an interpolation method reproducing quadratic polynomial gives quadratic polynomial F(t). The primary advantage of the proposed method is that the constructed curve has a shape described by data points. Another advantage of the new method is that the nodes computed by it have affine invariance. The experimental results indicate that the curve constructed by the nodes using the new method has a better interpolation accuracy and shape compared to that constructed using other methods.

要构建用于对一组数据点进行插值的参数多项式曲线,插值精度和所构建曲线的形状受两个主要因素的影响:数据点的参数化(为每个数据点计算一个节点)和插值方法。本文提出了一种为一组数据点计算节点的新方法。本文建立了数据点与三次多项式中相应节点之间的函数关系。利用这种函数关系,一个具有一个自由度的函数立方多项式可以通过四个相邻的数据点。通过最小化三次多项式的三次项,可以用两个相邻节点区间来表示自由度。由于每个节点都是在不同的节点空间中计算的,因此提出了一种构建二次曲线的方法,它将所有二次曲线转化为统一的形式来计算节点。使用新方法计算的节点具有二次多项式精度,也就是说,如果数据点集合取自二次多项式 F(t),则新方法计算的节点用于构建插值曲线,插值方法再现二次多项式,得到二次多项式 F(t)。拟议方法的主要优点是所构建的曲线具有数据点描述的形状。新方法的另一个优点是计算出的节点具有仿射不变性。实验结果表明,与其他方法相比,使用新方法通过节点构建的曲线具有更好的插值精度和形状。
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引用次数: 0
Two novel iterative approaches for improved LSPIA convergence 改进 LSPIA 收敛性的两种新型迭代方法
IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-04-24 DOI: 10.1016/j.cagd.2024.102312
Chengzhi Liu , Nian-Ci Wu , Juncheng Li , Lijuan Hu

This paper introduces two improved variants of the least squares progressive-iterative approximation (LSPIA) by leveraging momentum techniques. Specifically, based on the Polyak's and Nesterov's momentum techniques, the proposed methods utilize the previous iteration information to update the control points. We name these two methods PmLSPIA and NmLSPIA, respectively. The introduction of momentum enhances the determination of the search directions, leading to a significant improvement in convergence rate. The geometric interpretations of PmLSPIA and NmLSPIA are elucidated, providing insights into the underlying principles of these accelerated algorithms. Rigorous convergence analyses are conducted, revealing that both PmLSPIA and NmLSPIA exhibit faster convergence than LSPIA. Numerical results further validate the efficacy of the proposed algorithms.

本文通过利用动量技术,介绍了最小二乘渐进迭代逼近法(LSPIA)的两种改进变体。具体来说,基于 Polyak 和 Nesterov 的动量技术,所提出的方法利用前一次迭代信息来更新控制点。我们将这两种方法分别命名为 PmLSPIA 和 NmLSPIA。动量的引入增强了搜索方向的确定,从而显著提高了收敛速度。我们阐明了 PmLSPIA 和 NmLSPIA 的几何解释,从而深入了解了这些加速算法的基本原理。严谨的收敛分析表明,PmLSPIA 和 NmLSPIA 都比 LSPIA 表现出更快的收敛速度。数值结果进一步验证了所提算法的有效性。
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引用次数: 0
An adaptive collocation method on implicit domains using weighted extended THB-splines 使用加权扩展 THB-样条线的隐式域自适应配准法
IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-04-23 DOI: 10.1016/j.cagd.2024.102297
Jingjing Yang , Chun-Gang Zhu

Implicit representations possess many merits when dealing with geometries with certain properties, such as small holes, reentrant corners and other complex details. Truncated hierarchical B-splines (THB-splines) has recently emerged as a novel tool in many fields including design and analysis due to its local refinement ability. In this paper, we propose an adaptive collocation method with weighted extended THB-splines (WETHB-splines) on implicit domains. We modify the classification strategy for the WETHB-basis, and the centers of the supports of inner THB-splines on each level are chosen to be collocation points. We also use weighted collocation in the transition regions, in order to enrich information concerning the hierarchical basis. In contrast to the traditional WEB-collocation method, the proposed approach possesses much higher convergence rate. To show the efficiency and superiority of the proposed method, numerical examples in two and three dimensions are performed to solve Poisson's equations.

在处理具有某些特性的几何图形(如小孔、重入角和其他复杂细节)时,隐式表示法具有许多优点。截断分层 B 样条曲线(THB 样条曲线)因其局部细化能力,最近已成为设计和分析等许多领域的新工具。在本文中,我们提出了一种在隐式域上使用加权扩展 THB 样条线(WETHB 样条线)的自适应配准方法。我们修改了 WETHB 基准的分类策略,并选择每一级内 THB 样条曲线的支撑中心作为配准点。我们还在过渡区域使用加权配准,以丰富分层基础的相关信息。与传统的 WEB 拼合方法相比,所提出的方法具有更高的收敛率。为了证明所提方法的效率和优越性,我们用二维和三维数值实例求解了泊松方程。
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引用次数: 0
High-precision teeth reconstruction based on automatic multimodal fusion with CBCT and IOS 基于 CBCT 和 IOS 自动多模态融合的高精度牙齿重建技术
IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-04-23 DOI: 10.1016/j.cagd.2024.102299
Zhiyuan Ren , Long Ma , Minfeng Xu , Guangshun Wei , Shaojie Zhuang , Yuanfeng Zhou

In digital orthodontic treatment, the high-precision reconstruction of complete teeth, encompassing both the crown and the actual root, plays a pivotal role. Current mainstream techniques, prioritizing the high resolution of intraoral scanned models (IOS), are confined to using IOS data for orthodontic treatments. However, the lack of root information in the IOS data may lead to complications such as dehiscence. In contrast, Cone Beam Computed Tomography (CBCT) data encompasses comprehensive dental information with roots. Nonetheless, the radiative character of CBCT scans renders patients unsuitable for repeated examinations in a short time. In addition, lower scanning precision of CBCT leads to suboptimal teeth segmentation outcomes, hindering the accurate representation of dental occlusal relationships. Therefore, in order to fully utilize the complementarity between dental multimodal data, we propose a method for high-precision 3D teeth model reconstruction based on IOS and CBCT, which mainly consists of global rigid registration and local nonrigid registration. Specifically, we extract the priori information of dental arch curves for coarse alignment to provide a good initial position for the Iterative Closest Point (ICP) algorithm, and design a conformal parameterization method for a single tooth to effectively obtain the point correspondence between IOS and CBCT crowns. The rough crown of the CBCT will gradually fit towards the IOS through iterative optimization of nonrigid registration. The experimental results show that our method robustly fuses the advantageous features of IOS and CBCT. The 3D teeth model reconstructed by our method contains the high-precision crown of IOS and the real root of CBCT, which can be effectively used in clinical orthodontic treatment.

在数字化正畸治疗中,包括牙冠和实际牙根在内的整颗牙齿的高精度重建起着至关重要的作用。目前的主流技术优先考虑口内扫描模型(IOS)的高分辨率,因此仅限于将 IOS 数据用于正畸治疗。然而,IOS 数据中缺乏牙根信息可能会导致开裂等并发症。相比之下,锥形束计算机断层扫描(CBCT)数据包含了全面的牙根信息。然而,CBCT 扫描的辐射特性使患者不适合在短时间内重复检查。此外,CBCT 扫描精度较低,导致牙齿分割效果不理想,阻碍了牙齿咬合关系的准确呈现。因此,为了充分利用牙科多模态数据之间的互补性,我们提出了一种基于 IOS 和 CBCT 的高精度三维牙齿模型重建方法,主要包括全局刚性配准和局部非刚性配准。具体来说,我们提取牙弓曲线的先验信息进行粗配准,为迭代最邻近点(ICP)算法提供良好的初始位置,并设计单颗牙齿的保形参数化方法,以有效获得 IOS 和 CBCT 牙冠之间的点对应关系。通过非刚性配准的迭代优化,CBCT 的粗糙牙冠将逐渐向 IOS 靠拢。实验结果表明,我们的方法稳健地融合了 IOS 和 CBCT 的优势特征。用我们的方法重建的三维牙齿模型包含了 IOS 的高精度牙冠和 CBCT 的真实牙根,可有效用于临床正畸治疗。
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引用次数: 0
High-order shape interpolation 高阶形状插值
IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-04-23 DOI: 10.1016/j.cagd.2024.102301
Zhaobin Huang, Shibo Liu, Xiao-Ming Fu

We propose a simple yet effective method to interpolate high-order meshes. Given two manifold high-order triangular (or tetrahedral) meshes with identical connectivity, our goal is to generate a continuum of curved shapes with as little distortion as possible in the mapping from the source mesh to the interpolated mesh. Our algorithm contains two steps: (1) linearly blend the pullback metric of the identity mapping and the input mapping between two Bézier elements on a set of sampling points; (2) project the interpolated metric into the metric space between Bézier elements using the Newton method for nonlinear optimization. We demonstrate the feasibility and practicability of the method for high-order meshes through extensive experiments in both 2D and 3D.

我们提出了一种简单而有效的高阶网格插值方法。给定两个具有相同连通性的流形高阶三角形(或四面体)网格,我们的目标是生成一个连续的曲线图形,在从源网格到插值网格的映射中尽可能减少变形。我们的算法包含两个步骤:(1) 在一组采样点上线性混合两个贝塞尔元素之间的标识映射和输入映射的回拉度量;(2) 使用牛顿非线性优化方法将插值度量投影到贝塞尔元素之间的度量空间。我们通过大量二维和三维实验证明了该方法在高阶网格上的可行性和实用性。
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引用次数: 0
3D auxetic linkage based on Kirigami 基于桐纸的 3D 辅助连接装置
IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Pub Date : 2024-04-23 DOI: 10.1016/j.cagd.2024.102296
Xiaopeng Sun , Shihan Liu , Zhiqiang Luo , Zhongtai Yang

The structural design of 3D auxetic linkages is a burgeoning field in digital manufacturing. This article presents a novel algorithm for designing 3D auxetic linkage structures based on Kirigami principles to address existing limitations. The 3D input model is initially mapped to a 2D space using conformal mapping based on the BFF method. This is followed by 2D re-meshing using an equilateral triangle mesh. Subsequently, a 3D topological mesh of the auxetic linkage is calculated through inverse mapping based on directed area. We then introduce new basic rotating and non-rotating units, employing them as the initial structure of the 3D auxetic linkage in accordance with Kirigami techniques. Lastly, a deformation energy function is defined to optimize the shape of the rotating units. The vertex coordinates of the non-rotating units are updated according to the optimized positions of the rotating units, thereby generating an optimal 3D auxetic linkage structure. Experimental results validate the effectiveness and accuracy of our algorithm. Quantitative analyses of structural porosity and optimization accuracy, as well as comparisons with related works, indicate that our algorithm yields structures with smaller shape errors.

三维辅助连杆结构设计是数字制造领域的一个新兴领域。本文介绍了一种基于桐神原理的三维辅助连杆结构设计新算法,以解决现有的局限性。三维输入模型首先通过基于 BFF 方法的保角映射被映射到二维空间。然后使用等边三角形网格进行二维再映射。随后,通过基于有向面积的反映射,计算出辅助连接的三维拓扑网格。然后,我们引入了新的基本旋转和非旋转单元,并根据桐神技术将其用作三维辅助连杆的初始结构。最后,我们定义了变形能量函数,以优化旋转单元的形状。根据旋转单元的优化位置更新非旋转单元的顶点坐标,从而生成最佳的三维辅助连杆结构。实验结果验证了我们算法的有效性和准确性。对结构孔隙率和优化精度的定量分析,以及与相关工作的比较表明,我们的算法产生的结构形状误差较小。
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引用次数: 0
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Computer Aided Geometric Design
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