Computer-Aided Design最新文献_第10页

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 : 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

Fully discrete subdivision-based IGA scheme with decoupled structure and unconditional energy stability for the phase-field crystal model on surfaces 具有解耦结构和无条件能量稳定的基于完全离散细分的表面相场晶体模型IGA方案

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

Computer-Aided Design

Pub Date : 2025-09-29 DOI: 10.1016/j.cad.2025.103969

Qing Pan , Yunqing Huang , Chong Chen , Xiaofeng Yang , Yongjie Jessica Zhang

In this work, we aim to numerically solve the phase-field crystal (PFC) model to simulate atomic growth on manifolds. The geometric complexity, pronounced curvature variations, and nonlinearities inherent in the physical model pose significant challenges, necessitating the development of efficient and robust numerical schemes that can handle strong coupling and nonlinear terms while accurately accounting for curved geometries. To address these challenges, we first adopt a subdivision-based isogeometric analysis (IGA) for spatial discretization. This approach effectively resolves geometric complexities by offering hierarchical refinability, geometric exactness, and adaptability to arbitrary topologies, while eliminating geometric errors commonly encountered in traditional finite element methods. For temporal discretization, the highly nonlinear terms in the model are addressed using the Invariant Energy Quadratization (IEQ) method, which linearizes the nonlinear terms and guarantees strict unconditional energy stability. However, the introduction of auxiliary variables in the IEQ method results in a linearly coupled system. To overcome this limitation and further enhance computational efficiency, we incorporate the Zero-Energy-Coupling (ZEC) approach, ultimately constructing a scheme that achieves second-order accuracy, linearity, unconditional energy stability, and a fully decoupled structure. We rigorously prove the energy stability and solvability of the proposed scheme and validate its accuracy and robustness through extensive numerical experiments conducted on manifolds, demonstrating its capability to handle intricate geometric structures and nonlinear dynamics effectively.

在这项工作中，我们的目标是数值求解相场晶体（PFC）模型来模拟流形上的原子生长。几何复杂性、明显的曲率变化和物理模型固有的非线性构成了重大挑战，需要开发有效且稳健的数值方案，以处理强耦合和非线性项，同时准确地考虑弯曲几何。为了解决这些挑战，我们首先采用基于细分的等高分析（IGA）进行空间离散化。该方法通过提供层次精细化性、几何精确性和对任意拓扑的适应性，有效地解决了几何复杂性，同时消除了传统有限元方法中常见的几何误差。对于时间离散化，采用不变能量二次化（IEQ）方法处理模型中的高度非线性项，该方法将非线性项线性化并保证严格的无条件能量稳定性。然而，在IEQ方法中引入辅助变量会导致线性耦合系统。为了克服这一限制并进一步提高计算效率，我们引入了零能量耦合（ZEC）方法，最终构建了一个实现二阶精度、线性、无条件能量稳定性和完全解耦结构的方案。通过对流形进行的大量数值实验，我们严格地证明了该方案的能量稳定性和可解性，并验证了其准确性和鲁棒性，证明了该方案能够有效地处理复杂的几何结构和非线性动力学。

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引用次数: 0

A new measure of fairness for curves 曲线公平的新标准

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

Computer-Aided Design

Pub Date : 2025-09-26 DOI: 10.1016/j.cad.2025.103979

Shoichi Tsuchie

This paper proposes a novel measure based on curvature variation to evaluate the fairness of curves. It is demonstrated that, in the simplest case, controlling the curvature using the proposed measure results in the log-aesthetic curve (LAC). In other words, by utilizing the proposed measure as a novel shape parameter, a unified framework can be established for aesthetic curves that accommodates a broader range of curvature variations, encompassing the LAC as a special case. Several examples are presented to illustrate curve evaluation using the proposed measure, along with its application to the approximation of aesthetic curves. The findings of this study offer a new perspective for understanding and evaluating the geometric properties of curves, with potential applications in curve design, analysis, and fairing.

提出了一种基于曲率变化的曲线公平性评价方法。结果表明，在最简单的情况下，使用所提出的测量方法控制曲率可以得到对数美观曲线（LAC）。换句话说，通过利用所提出的测量作为一个新的形状参数，可以为美学曲线建立一个统一的框架，以适应更广泛的曲率变化，包括LAC作为一个特殊情况。给出了几个例子来说明使用所提出的测量曲线评估，以及它在美学曲线近似中的应用。本研究结果为理解和评价曲线的几何特性提供了一个新的视角，在曲线设计、分析和整流方面具有潜在的应用价值。

引用次数: 0

Prototype optimization and self-training for few-shot 3D point cloud semantic segmentation 少镜头三维点云语义分割的原型优化与自训练

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

Computer-Aided Design

Pub Date : 2025-09-26 DOI: 10.1016/j.cad.2025.103976

Jie Zhou , Yong Zhao , Fan Zhong

Few-shot point cloud segmentation aims to accurately decompose 3D point clouds into different semantic classes with few samples, and is crucial for subsequent tasks, such as analysis, modeling and editing. Despite the popularity of prototype-based approaches, prototypes often fail to adequately capture class-specific information. Therefore, for each class, a few points may exhibit significant differences from their prototype. And the lack of sufficient distinction between foreground and background prototypes presents a great challenge for precise segmentation. To address these issues, we propose a prototype optimization module to mitigate the interference among support prototypes, thereby generating prototypes of superior quality. These refined prototypes are capable of capturing the key characteristics of the data, which can prominently improve the generalization capability of our model. Then, we devise a self-training strategy that leverages pseudo query prototypes generated from high-confidence predicted labels. These prototypes are applied to query features to produce pseudo query labels and formulate a reconstruction constraint during training. By harnessing the contextual information embedded within query features, this approach significantly elevates segmentation performance. Extensive results on two popular benchmark datasets validate the superiority of our model, especially in the challenging 1-shot settings. Under the classic experimental setup, our method surpasses existing state-of-the-arts by 2.64% in 2-way 1-shot setting on the S3DIS dataset. On the ScanNet dataset, the improvements are 7.58% in 2-way 1-shot setting and 6.44% in 3-way 1-shot setting, respectively.

少镜头点云分割旨在用较少的样本将三维点云准确分解为不同的语义类，对后续的分析、建模和编辑等任务至关重要。尽管基于原型的方法很流行，但原型常常不能充分捕获特定于类的信息。因此，对于每个类，可能会有一些点与其原型有显著差异。前景和背景原型之间缺乏足够的区分，这给精确分割带来了很大的挑战。为了解决这些问题，我们提出了一个原型优化模块，以减轻支持原型之间的干扰，从而产生高质量的原型。这些精细化的原型能够捕获数据的关键特征，这可以显著提高我们模型的泛化能力。然后，我们设计了一种自我训练策略，利用高置信度预测标签生成的伪查询原型。将这些原型应用于查询特征，生成伪查询标签，并在训练过程中形成重构约束。通过利用嵌入在查询特征中的上下文信息，这种方法显著提高了分割性能。在两个流行的基准数据集上的广泛结果验证了我们模型的优越性，特别是在具有挑战性的1次射击设置中。在经典的实验设置下，我们的方法在S3DIS数据集上的2-way 1-shot设置比现有的最先进的方法高出2.64%。在ScanNet数据集上，2-way 1-shot设置的改进率为7.58%，3-way 1-shot设置的改进率为6.44%。

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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 : 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

CORNet: A Consistency-based Outlier Rejection Network for non-rigid registration CORNet：一种基于一致性的非刚性配准离群值拒绝网络

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

Computer-Aided Design

Pub Date : 2025-09-25 DOI: 10.1016/j.cad.2025.103980

Chang Yu, Sanguo Zhang, Li-Yong Shen

Non-rigid point cloud registration is an important problem in computer vision and graphics, aiming to find the warping function between deformed point clouds. In this paper, we propose CORNet, a consistency-based outlier rejection network for non-rigid registration. By leveraging the local geometric structure and probability distribution of point clouds, we obtain local spatial consistency and Gaussian probabilistic consistency. We then employ the Transformer mechanism, combined with consistency information, to classify inliers and outliers in correspondences, ultimately obtaining high-quality correspondences for non-rigid registration. Ablation studies validate the effectiveness of our method, and extensive experiments demonstrate that our method achieves state-of-the-art performance.

非刚性点云配准是计算机视觉和图形学中的一个重要问题，其目的是寻找变形点云之间的翘曲函数。本文提出了一种基于一致性的非刚性配准离群点拒绝网络CORNet。利用点云的局部几何结构和概率分布，获得局部空间一致性和高斯概率一致性。然后，我们使用Transformer机制，结合一致性信息，对对应中的内线和离群值进行分类，最终获得非刚性注册的高质量对应。烧蚀研究验证了我们方法的有效性，大量的实验表明我们的方法达到了最先进的性能。

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 : 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

MidSurfer: Efficient Mid-Surface Abstraction from Variable Thin-Walled Models 中冲浪者：从可变薄壁模型中高效提取中表面

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

Computer-Aided Design

Pub Date : 2025-09-22 DOI: 10.1016/j.cad.2025.103965

Li Ye , Xinhang Zhou , Peng Fan , Ruofeng Tong , Hailong Li , Peng Du , Min Tang

This paper addresses the challenge of efficiently abstracting mid-surfaces from complex variable thin-walled models, a critical task in computer-aided design (CAD) and finite element analysis (FEA) for simplifying thin-walled structures. Traditional methods often require manual specification of pairing faces, which can be time-consuming and error-prone. Alternatively, automatic face pairing methods fail to meet the actual needs of variable thin-walled models, resulting in the accumulation of topological errors. Additionally, existing algorithms struggle to extract mid-surfaces from models with varying wall thickness or produce mid-surfaces with poor accuracy, leading to geometric errors. Furthermore, the computational efficiency of these methods is often inadequate for large-scale models. To overcome these challenges, we propose an automated face-pairing mechanism that eliminates the need for manual intervention, enhancing the algorithm’s robustness and enabling it to handle cases that the commercial CAD modeling engine, Parasolid, cannot process. Our approach accurately processes variable thin-walled models, with results closely aligning with the ground truth, as demonstrated by the provided error distribution tables. Moreover, our algorithm achieves a

4 - 12

times improvement in efficiency than previous methods over the geometry extraction stage and supports multi-threaded acceleration, significantly reducing computation time. Experimental results demonstrate that our algorithm surpasses existing methods in both accuracy and efficiency, offering a promising solution for mid-surface extraction in complex, variable thin-walled models.

本文解决了从复杂的可变薄壁模型中有效地抽象中间曲面的挑战，这是简化薄壁结构的计算机辅助设计（CAD）和有限元分析（FEA）中的关键任务。传统方法通常需要手动指定配对面，这既耗时又容易出错。另一方面，自动人脸配对方法无法满足变薄壁模型的实际需要，导致拓扑误差的积累。此外，现有算法难以从不同壁厚的模型中提取中间面，或者产生精度较差的中间面，从而导致几何误差。此外，这些方法的计算效率往往不适合大规模模型。为了克服这些挑战，我们提出了一种自动人脸配对机制，消除了人工干预的需要，增强了算法的鲁棒性，并使其能够处理商业CAD建模引擎Parasolid无法处理的情况。我们的方法精确地处理可变薄壁模型，结果与地面事实紧密一致，如所提供的误差分布表所示。此外，我们的算法在几何提取阶段的效率比以前的方法提高了4 - 12倍，并支持多线程加速，显著减少了计算时间。实验结果表明，该算法在精度和效率上均优于现有方法，为复杂、可变薄壁模型的中表面提取提供了一种有希望的解决方案。

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引用次数: 0

Interactive design of developable surfaces by patch-based learning 基于补丁学习的可展开曲面交互设计

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

Computer-Aided Design

Pub Date : 2025-09-22 DOI: 10.1016/j.cad.2025.103970

Chaoyun Wang , Jianlei Wang , Chengcheng Tang , Nanning Zheng , Caigui Jiang

This paper introduces an interactive design method for developable surfaces, centered on a data-driven approach to optimize surface patches for developability. Surface patches are the fundamental components of an entire surface, typically represented by triangular meshes. We propose a novel learning-based method that effectively transforms patches with arbitrary boundaries into their closest developable surfaces. Based on this method, our tools enable real-time, drag-and-drop design of developable surfaces and support piecewise developable approximation through interactive inputs. Experimental results demonstrate that this method provides a fast computational foundation for the interactive design of developable surfaces, enhancing design flexibility while exhibiting excellent robustness and generalization. The piecewise developable approximation of the model, guided by human–computer collaborative segmentation, achieved higher overall approximation accuracy, fewer patches, and lifelike papercraft outcomes. This offers greater flexibility to meet the application requirements of complex real-world scenarios and provides a new paradigm for integrating deep learning with interactive geometry design.

本文介绍了一种可展表面的交互式设计方法，以数据驱动的方法为中心，优化表面斑块的可展性。表面斑块是整个表面的基本组成部分，通常由三角形网格表示。我们提出了一种新的基于学习的方法，有效地将具有任意边界的斑块转换为其最近的可展开曲面。基于这种方法，我们的工具可以实现可展开曲面的实时拖放设计，并通过交互式输入支持分段可展开近似。实验结果表明，该方法为可展开曲面的交互设计提供了快速的计算基础，提高了设计的灵活性，同时具有良好的鲁棒性和通用性。在人机协同分割的指导下，该模型的分段可开发近似实现了更高的整体近似精度，更少的补丁和逼真的纸工艺结果。这为满足复杂现实场景的应用需求提供了更大的灵活性，并为将深度学习与交互式几何设计集成提供了新的范例。

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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 : 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