Computer-Aided Design最新文献_第4页

High-connectivity polycube-maps: Solvable space expansion through validity-augmented topological conditions 高连通性多立方映射：通过有效性增强拓扑条件的可解空间扩展

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Computer-Aided Design

Pub Date : 2026-02-01 Epub Date: 2025-10-16 DOI: 10.1016/j.cad.2025.103972

Lu He, Na Lei, Ziliang Wang, Chen Wang, Xiaopeng Zheng, Zhongxuan Luo

Polycube-maps play a critical role in computer graphics, especially for generating high-quality hexahedral meshes. Existing polycube validity conditions, primarily based on Steinitz and Eppstein’s approach, are limited to 3-connected graphs. Extending polycube-maps to handle higher connectivity graphs is crucial for practical applications. In this work, we introduce Validity-Augmented Topological Conditions (VAT conditions) based on the Gauss–Bonnet theorem. These conditions offer both global and local topological criteria, enabling the solvability of k-connected graphs, non-manifold structures, and meshes with voids. Our VAT conditions allow models that do not meet traditional polycube validity criteria but are still valid polycube polyhedra in practice. Additionally, we propose an Immune Genetic Algorithm (ImGA) tailored to our VAT conditions to enhance the robustness of polycube-map generation. We evaluate our method using the Thingi10k and ABC datasets. Results demonstrate that our VAT conditions expands the solvable space of polycubes and achieves higher quality all-hexahedral meshing for higher-connectivity or more complex models. Furthermore, we discuss the limitations associated with our proposed method.

多立方体映射在计算机图形学中起着至关重要的作用，特别是在生成高质量的六面体网格方面。现有的聚立方有效性条件，主要基于Steinitz和Eppstein的方法，局限于3连通图。扩展多立方体映射以处理更高的连通性图对于实际应用程序至关重要。在这项工作中，我们引入了基于高斯-博内定理的有效性增强拓扑条件（VAT条件）。这些条件提供了全局和局部拓扑标准，使k连通图、非流形结构和带空洞的网格具有可解性。我们的增值条件允许模型不符合传统的多面体有效性标准，但在实践中仍然是有效的多面体。此外，我们提出了一种适合我们VAT条件的免疫遗传算法（ImGA），以增强多立方体地图生成的鲁棒性。我们使用Thingi10k和ABC数据集来评估我们的方法。结果表明，我们的增值条件扩展了聚立方体的可解空间，并对更高连通性或更复杂的模型实现了更高质量的全六面体网格划分。此外，我们讨论了与我们提出的方法相关的局限性。

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引用次数: 0

LoGAvatar: Local Gaussian Splatting for human avatar modeling from monocular video LoGAvatar：局部高斯喷溅，用于单目视频的人类头像建模

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Computer-Aided Design

Pub Date : 2026-01-01 Epub Date: 2025-09-29 DOI: 10.1016/j.cad.2025.103973

Jinsong Zhang , Xiongzheng Li , Hailong Jia , Jin Li , Zhuo Su , Guidong Wang , Kun Li

Avatar reconstruction from monocular videos plays a pivotal role in various virtual and augmented reality applications. Recent methods have utilized 3D Gaussian Splatting (GS) to model human avatars, achieving fast rendering speeds with high visual quality. However, due to the independent nature of GS primitives, existing approaches often struggle to capture high-fidelity details and lack the ability to edit the reconstructed avatars effectively. To address these limitations, we propose Local Gaussian Splatting Avatar (LoGAvatar), a novel framework designed to enhance both geometry and texture modeling of human avatars. Specifically, we introduce a hierarchical Gaussian splatting framework, where local GS primitives are predicted based on sampled points from a human template model, such as SMPL. For texture modeling, we design a convolution-based texture atlas that preserves spatial continuity and enriches fine details. By aggregating local information for both geometry and texture, our approach reconstructs high-fidelity avatars while maintaining real-time rendering efficiency. Experimental results on two public datasets demonstrate the superior performance of our method in terms of avatar fidelity and rendering quality. Moreover, based on our LoGAvatar, we can edit the shape and texture of the reconstructed avatar, which inspires more customized avatar applications. The code is available at http://cic.tju.edu.cn/faculty/likun/projects/LoGAvatar.

单目视频的虚拟化身重建在各种虚拟现实和增强现实应用中起着至关重要的作用。最近的方法利用三维高斯飞溅（GS）来建模人类化身，实现快速渲染速度和高视觉质量。然而，由于GS原语的独立性，现有的方法往往难以捕获高保真的细节，并且缺乏有效编辑重建头像的能力。为了解决这些限制，我们提出了局部高斯飞溅头像（LoGAvatar），这是一个新的框架，旨在增强人类头像的几何和纹理建模。具体来说，我们引入了一个分层高斯飞溅框架，其中局部GS原语是基于人类模板模型（如SMPL）的采样点来预测的。在纹理建模方面，我们设计了一个基于卷积的纹理图谱，既保留了空间连续性，又丰富了精细细节。通过聚合几何和纹理的局部信息，我们的方法在保持实时渲染效率的同时重建了高保真的化身。在两个公开数据集上的实验结果表明，我们的方法在头像保真度和渲染质量方面表现优异。此外，基于我们的LoGAvatar，我们可以编辑重构头像的形状和纹理，从而激发更多的定制头像应用。代码可在http://cic.tju.edu.cn/faculty/likun/projects/LoGAvatar上获得。

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引用次数: 0

Mechanics simulation with Implicit Neural Representations of complex geometries 复杂几何的隐式神经表征力学模拟

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Computer-Aided Design

Pub Date : 2026-01-01 Epub Date: 2025-10-06 DOI: 10.1016/j.cad.2025.103978

Samundra Karki, Ming-Chen Hsu, Adarsh Krishnamurthy, Baskar Ganapathysubramanian

Implicit Neural Representations (INRs), characterized by neural network-encoded signed distance fields, provide a powerful means to represent complex geometries continuously and efficiently. While successful in computer vision and generative modeling, integrating INRs into computational analysis workflows, such as finite element simulations, remains underdeveloped, primarily due to the necessity of explicit geometry representations (meshes). Conventional mesh-based finite element methods (FEM) introduce computational overhead, discretization errors, and manual effort, particularly for intricate or dynamically evolving geometries. Although immersed boundary methods partially address these issues, they are susceptible to numerical artifacts from explicit boundary treatments. In this work, we propose an innovative computational framework that seamlessly combines INRs with the Shifted Boundary Method (SBM) for performing high-fidelity linear elasticity simulations without explicit geometry transformations. By directly querying the neural implicit geometry, we obtain the surrogate boundaries and distance vectors essential for SBM, effectively eliminating the intermediate meshing step. We demonstrate the efficacy and robustness of our approach through elasticity simulations on complex geometries sourced from diverse representations, including triangle soup and point cloud reconstructions (Stanford Bunny, Eiffel Tower, gyroids). Our method showcases significant computational advantages and accuracy, underscoring its potential in biomedical, geophysical, and advanced manufacturing applications, thus offering a versatile tool for geometric and physical modeling aligned with contemporary design and analysis workflows.

隐式神经表示（INRs）以神经网络编码的符号距离域为特征，为复杂几何图形的连续高效表示提供了强有力的手段。虽然在计算机视觉和生成建模方面取得了成功，但将inr集成到计算分析工作流程（如有限元模拟）中仍然不发达，主要是由于需要显式几何表示（网格）。传统的基于网格的有限元方法（FEM）引入了计算开销、离散误差和人工工作量，特别是对于复杂或动态发展的几何形状。虽然浸入式边界方法部分解决了这些问题，但它们容易受到显式边界处理的数值伪影的影响。在这项工作中，我们提出了一种创新的计算框架，将INRs与移位边界法（SBM）无缝结合，在没有显式几何变换的情况下执行高保真线性弹性模拟。通过直接查询神经隐式几何，我们获得了SBM所需的代理边界和距离向量，有效地消除了中间网格划分步骤。我们通过对来自不同表示的复杂几何图形进行弹性模拟，包括三角汤和点云重建（斯坦福兔、埃菲尔铁塔、陀螺仪），证明了我们方法的有效性和鲁棒性。我们的方法展示了显著的计算优势和准确性，强调了其在生物医学，地球物理和先进制造应用中的潜力，从而提供了与当代设计和分析工作流程相一致的几何和物理建模的多功能工具。

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引用次数: 0

Adaptive gap closing for complex triangular mesh repair using geometric and topological characteristics 基于几何和拓扑特征的复杂三角形网格自适应闭合修复

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Computer-Aided Design

Pub Date : 2026-01-01 Epub Date: 2025-09-25 DOI: 10.1016/j.cad.2025.103981

Shuwei Shen , Shuai Zhou , Zhoufang Xiao , Jingchen Gao , Chenhao Xu

Gaps are prevalent defects in triangular meshes, often arising from various sources such as surface scanning and CAD model generation. Despite their significance, the automatic repair of complex gaps has received limited attention compared to other mesh imperfections. This study presents a novel surface-based gap-closing method for triangular mesh repair, leveraging both local geometric and topological characteristics to robustly match and merge gap boundaries. The proposed approach first employs a global–local vertex merging procedure with adaptive tolerances to eliminate duplicate vertices and simplify complex gaps. Subsequently, gaps are identified and classified into connected and disconnected types based on their topological and geometric features. For each detected gap, a non-iterative closing procedure is applied, simultaneously matching and merging all boundary vertices. An adaptive scheme is introduced to determine the geometric tolerance for vertex matching, ensuring the effective preservation of the original geometric shape. Extensive numerical experiments on a large dataset of discrete models demonstrate the effectiveness and robustness of the proposed method in closing both connected and disconnected gaps.

在三角形网格中，由于曲面扫描和CAD模型生成等原因，产生了许多缺陷。尽管具有重要意义，但与其他网格缺陷相比，复杂间隙的自动修复受到的关注有限。本文提出了一种新的基于表面的三角形网格修补方法，利用局部几何和拓扑特征对缝隙边界进行鲁棒匹配和合并。该方法首先采用具有自适应容差的全局-局部顶点合并过程，消除重复顶点，简化复杂间隙。然后，根据其拓扑和几何特征对间隙进行识别，并将其分为连通型和非连通型。对于每个检测到的间隙，应用非迭代闭合过程，同时匹配和合并所有边界顶点。引入了一种自适应方案来确定顶点匹配的几何公差，保证了原始几何形状的有效保留。在大量离散模型数据集上进行的大量数值实验证明了该方法在关闭连接和不连接间隙方面的有效性和鲁棒性。

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引用次数: 0

Text-driven 3D human motion generation for pose estimation using dual-transformer architecture 文本驱动的三维人体运动生成的姿态估计使用双变压器架构

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Computer-Aided Design

Pub Date : 2026-01-01 Epub Date: 2025-10-03 DOI: 10.1016/j.cad.2025.103991

Rizwan Abbas , Hua Gao , Xi Li

Text-to-motion generation has made significant progress in recent years. However, existing approaches struggle to generate high-quality 3D human motions that effectively capture pose estimation. These limitations are due to weak pose estimation and limited skeletal modeling. To address these limitations, we propose DT3DPE (Dual-Transformer for 3D Pose Estimation), a framework that integrates pose estimation to generate text-aligned, realistic 3D human motions. The proposed approach introduces residual vector quantization with additional layers for encoding pose tokens, enabling the capture of fine-grained details in body dynamics. Furthermore, DT3DPE employs a dual-transformer architecture, consisting of a masked transformer for motion token prediction and a residual transformer for refining motion details. This dual-transformer architecture allows the model to generate high-fidelity 3D human poses with precise body joint positioning and smooth temporal transitions. The experimental results on HumanML3D and KIT-ML datasets demonstrate that DT3DPE outperforms existing state-of-the-art methods in text-driven 3D human motion generation. Our code is available at https://github.com/swerizwan/DT3DPE.

近年来，文本到动作生成技术取得了重大进展。然而，现有的方法很难产生高质量的3D人体运动，有效地捕捉姿势估计。这些限制是由于弱姿态估计和有限的骨骼建模。为了解决这些限制，我们提出了DT3DPE（用于3D姿态估计的双变压器），这是一个集成姿态估计以生成文本对齐的逼真的3D人体运动的框架。该方法引入残差矢量量化和附加层来编码姿态标记，从而能够捕获身体动力学中的细粒度细节。此外，DT3DPE采用双变压器架构，包括用于运动令牌预测的屏蔽变压器和用于细化运动细节的残余变压器。这种双变压器结构使模型能够生成高保真的3D人体姿势，具有精确的身体关节定位和平滑的时间过渡。在HumanML3D和KIT-ML数据集上的实验结果表明，DT3DPE在文本驱动的3D人体运动生成方面优于现有的最先进方法。我们的代码可在https://github.com/swerizwan/DT3DPE上获得。

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引用次数: 0

On design, analysis, and hybrid manufacturing of microstructured blade-like geometries 微结构叶片状几何形状的设计、分析和混合制造

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Computer-Aided Design

Pub Date : 2026-01-01 Epub Date: 2025-09-20 DOI: 10.1016/j.cad.2025.103967

Pablo Antolin , Michael Bartoň , Georges-Pierre Bonneau , Annalisa Buffa , Amaia Calleja-Ochoa , Gershon Elber , Stefanie Elgeti , Gaizka Gómez Escudero , Alicia Gonzalez , Haizea González Barrio , Stefanie Hahmann , Thibaut Hirschler , Q Youn Hong , Konstantin Key , Myung-Soo Kim , Michael Kofler , Norberto Lopez de Lacalle , Silvia de la Maza , Kanika Rajain , Jacques Zwar

With the evolution of new manufacturing technologies such as multi-material 3D printing, one can think of new type of objects that consist of considerably less, yet heterogeneous, material, consequently being porous, lighter and cheaper, while having the very same functionality as the original object when manufactured from one single solid material. We aim at questioning five decades of traditional paradigms in geometric CAD and focus at new generation of CAD objects that are not solid, but contain heterogeneous free-form internal microstructures. We propose a unified manufacturing pipeline that involves all stages, namely design, optimization, manufacturing, and inspection of microstructured free-form geometries. We demonstrate our pipeline on an industrial test case of a blisk blade that sustains the desired pressure limits, yet requires significantly less material when compared to the solid counterpart.

随着新制造技术的发展，如多材料3D打印，人们可以想到由更少，但异质的材料组成的新型物体，因此多孔，更轻，更便宜，同时具有与原始物体完全相同的功能，当由单一固体材料制造时。我们的目标是质疑五十年来几何CAD的传统范式，并专注于新一代的CAD对象，这些对象不是固体的，而是包含异质自由形式的内部微观结构。我们提出了一个统一的制造管道，涉及所有阶段，即设计，优化，制造和检查微结构的自由形状几何。我们在一个工业测试案例中展示了我们的管道，该管道可以维持所需的压力限制，但与固体叶片相比，所需的材料要少得多。

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引用次数: 0

Research on dynamic simulation and optimization of garment wrinkles combining computer vision and image processing 结合计算机视觉与图像处理的服装褶皱动态仿真与优化研究

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Computer-Aided Design

Pub Date : 2026-01-01 Epub Date: 2025-09-22 DOI: 10.1016/j.cad.2025.103982

Zhong Tian, Xu Xubing

This study presents a novel framework for real-time cloth wrinkle detection and optimisation, combining physics-based modelling with LSTM-Reinforcement Learning (LSTM-RL) and advanced computer vision techniques. A curated dataset of 45,876 annotated static garment images was used, featuring wrinkle attributes such as location, depth, width, and geometry. CNNs were employed for feature extraction, enhanced by Mask R-CNN to handle occlusions and RGBD data for depth-aware wrinkle modelling. A mass-spring system simulated fabric dynamics under environmental forces, while LSTM networks predicted the temporal evolution of wrinkles. Reinforcement learning dynamically adjusted fabric parameters, improving adaptability. The proposed RGBD model achieved a wrinkle detection accuracy of 96.4 %, outperforming the 2D model by over 9 %. Key metrics include an MSE of 0.0246, drift of 0.0187, and a reward value of -0.13543, with low policy and value loss confirming the RL agent’s learning stability. These results demonstrate high accuracy, real-time performance, and robustness, with strong implications for virtual fashion, robotics, and AR/VR applications.

本研究提出了一种新的实时布料皱纹检测和优化框架，将基于物理的建模与lstm -强化学习（LSTM-RL）和先进的计算机视觉技术相结合。使用了一个由45876张带注释的静态服装图像组成的精心策划的数据集，该数据集具有褶皱属性，如位置、深度、宽度和几何形状。采用cnn进行特征提取，通过Mask R-CNN进行增强处理遮挡，并使用RGBD数据进行深度感知皱纹建模。质量-弹簧系统模拟了环境力作用下的织物动力学，而LSTM网络预测了皱褶的时间演变。强化学习动态调整织物参数，提高适应性。所提出的RGBD模型的皱纹检测准确率达到96.4%，比2D模型高出9%以上。关键指标包括MSE为0.0246，漂移为0.0187，奖励值为-0.13543，低策略和价值损失证实了RL代理的学习稳定性。这些结果显示出高精度、实时性和鲁棒性，对虚拟时尚、机器人和AR/VR应用具有重要意义。

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引用次数: 0

A computational framework for simulating accurate deployment motion paths of rigid foldable origami tessellations 一种模拟刚性可折叠折纸镶嵌精确展开运动路径的计算框架

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Computer-Aided Design

Pub Date : 2026-01-01 Epub Date: 2025-09-15 DOI: 10.1016/j.cad.2025.103975

Marco Meloni, Qian Zhang, Jianguo Cai

Origami tessellations have found widespread applications in fields such as robotics, space structures, and mechanical metamaterials. Among these, rigid foldable origami has garnered significant attention due to its desirable characteristics, including controlled motion, scalability, and the ability to fold without deforming panels. However, assessing folding motions and folded shapes with generalized approaches remains a critical yet challenging step in their design. To address this, we present a computational framework that leverages the Kangaroo solver to achieve accurate motion paths and folded configurations of rigid foldable origami tessellations. This framework extends beyond the capabilities of the Kangaroo plug-in alone, enabling the accurate motion path simulation of developable and non-developable patterns, bound and joined models, and sequential folding motions. It also supports a wide range of geometries, from origami and kirigami to composites and metamaterials. By providing advanced tools for simulating complex folding behaviours, the proposed method could foster the development of innovative origami-based designs across diverse applications.

折纸镶嵌在机器人、空间结构和机械超材料等领域得到了广泛的应用。其中，刚性可折叠折纸由于其理想的特性，包括控制运动，可扩展性和在不变形面板的情况下折叠的能力，已经引起了极大的关注。然而，用广义方法评估折叠运动和折叠形状仍然是其设计中关键但具有挑战性的一步。为了解决这个问题，我们提出了一个计算框架，利用袋鼠求解器来实现精确的运动路径和刚性可折叠折纸镶嵌的折叠构型。该框架扩展了Kangaroo插件的功能，支持可展开和不可展开模式、绑定和连接模型以及顺序折叠运动的精确运动路径模拟。它还支持广泛的几何形状，从折纸和kirigami复合材料和超材料。通过提供先进的工具来模拟复杂的折叠行为，提出的方法可以促进创新的折纸设计的发展，跨越各种应用。

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引用次数: 0

Evolution-based tool path and motion planning optimization for 5-axis CNC machining of free-form surfaces 基于进化的五轴自由曲面数控加工刀具轨迹与运动规划优化

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Computer-Aided Design

Pub Date : 2026-01-01 Epub Date: 2025-09-10 DOI: 10.1016/j.cad.2025.103951

Juan Zaragoza Chichell , Michal Bizzarri , Judith Echevarrieta Ibarra , Aritz Pérez , Michael Bartoň

Manufacturing of free-form geometries using 5-axis Computer Numerically Controlled (CNC) machining brings challenges in path- and motion-planning as one typically wants to minimize the manufacturing time of the object under consideration, while keeping the machining error within fine machining tolerances that ranges in tens of microns. We propose an optimization-based pipeline that, for a given toroidal and/or cylindrical flat-end cutter, simultaneously optimizes its milling paths together with its local positioning represented by the rotation and tilt functions.

The proposed strategy is validated on a variety of benchmark surfaces, with different hyperparameters for the objective function and initial conditions, showing that our results provide high-quality approximations of free-form geometries using by-construction non-colliding motions of the given tool.

使用五轴计算机数控（CNC）加工制造自由几何形状带来了路径和运动规划方面的挑战，因为人们通常希望最大限度地减少所考虑对象的制造时间，同时将加工误差控制在几十微米的精细加工公差范围内。我们提出了一个基于优化的管道，对于给定的环面和/或圆柱形平端铣刀，同时优化其铣削路径及其由旋转和倾斜函数表示的局部定位。该策略在各种基准曲面上进行了验证，目标函数和初始条件具有不同的超参数，表明我们的结果使用给定工具的构造非碰撞运动提供了高质量的自由几何形状近似值。

引用次数: 0

Robust and fast local repair for intersecting triangle meshes 鲁棒和快速局部修复相交三角形网格

IF 3.1 3区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Computer-Aided Design

Pub Date : 2026-01-01 Epub Date: 2025-09-18 DOI: 10.1016/j.cad.2025.103963

Taoran Liu , Hongfei Ye , Xiangqiao Meng , Zhiwei Liu , Jianjun Chen

Triangle meshes frequently exhibit defects such as self-intersections and low-quality elements. Existing intersection resolution methods either lack robustness due to floating-point inaccuracies or incur high computational costs by processing meshes globally. We propose a robust and efficient method for repairing meshes with intersecting triangles that combines localized processing with rational number computations. The core challenge we address is converting exact intersection repair results to stable floating-point representation without reintroducing intersections. Our solution embeds intersecting regions into tetrahedral meshes for constrained optimization, naturally preventing surface intersections during the conversion process. Our approach begins with a preprocessing step that refines the mesh and localizes intersection issues by separating intersecting and intersection-free regions. For each intersecting region, we ensure the robustness of intersection calculations by using rational numbers. Subsequently, the intersection repair results are stably converted from rational to floating-point representation using a constrained boundary tetrahedral mesh optimization method. The repaired local meshes are then stitched back into the intersection-free mesh, followed by a remeshing step to enhance overall mesh quality. Experimental results on complex models demonstrate that our method significantly reduces computational overhead while producing high-quality, intersection-free meshes suitable for downstream applications.

三角形网格经常出现自交和低质量元素等缺陷。现有的交点解析方法要么由于浮点精度不高而缺乏鲁棒性，要么由于对网格进行全局处理而导致计算成本高。我们提出了一种结合局部处理和有理数计算的鲁棒高效的三角形网格修复方法。我们解决的核心挑战是在不重新引入交叉点的情况下将精确的交叉点修复结果转换为稳定的浮点表示。我们的解决方案将相交区域嵌入到四面体网格中进行约束优化，在转换过程中自然地防止表面相交。我们的方法从预处理步骤开始，该步骤通过分离相交和无相交区域来细化网格并定位相交问题。对于每个相交区域，我们使用有理数来保证相交计算的鲁棒性。随后，采用约束边界四面体网格优化方法，将相交修复结果稳定地从有理表示转换为浮点表示。然后将修复的局部网格缝合回无相交网格，然后进行重划分步骤以提高整体网格质量。在复杂模型上的实验结果表明，我们的方法显著降低了计算开销，同时产生适合下游应用的高质量、无交集的网格。

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引用次数: 0