Computer Graphics Forum最新文献_第2页

Shape Approximation by Surface Reuse 曲面重用的形状逼近

IF 2.9 4区计算机科学

Computer Graphics Forum Pub Date : 2025-08-28 DOI: 10.1111/cgf.70204

Berend Baas, David Bommes, Adrien Bousseau

引用次数: 0

Im2SurfTex: Surface Texture Generation via Neural Backprojection of Multi-View Images Im2SurfTex：通过多视图图像的神经反向投影生成表面纹理

IF 2.9 4区计算机科学

Computer Graphics Forum Pub Date : 2025-08-28 DOI: 10.1111/cgf.70191

Yiangos Georgiou, Marios Loizou, Melinos Averkiou, Evangelos Kalogerakis

引用次数: 0

Anisotropic Gauss Reconstruction and Global Orientation with Octree-based Acceleration 基于八叉树加速的各向异性高斯重建和全局定向

IF 2.9 4区计算机科学

Computer Graphics Forum Pub Date : 2025-08-28 DOI: 10.1111/cgf.70199

Yueji Ma, Jialu Shen, Yanzun Meng, Dong Xiao, Zuoqiang Shi, Bin Wang

{"title":"Anisotropic Gauss Reconstruction and Global Orientation with Octree-based Acceleration","authors":"Yueji Ma, Jialu Shen, Yanzun Meng, Dong Xiao, Zuoqiang Shi, Bin Wang","doi":"10.1111/cgf.70199","DOIUrl":"https://doi.org/10.1111/cgf.70199","url":null,"abstract":"Unoriented surface reconstruction is an important task in computer graphics. Recently, methods based on the Gauss formula or winding number have achieved state-of-the-art performance in both orientation and surface reconstruction. The Gauss formula or winding number, derived from the fundamental solution of the Laplace equation, initially found applications in calculating potentials in electromagnetism. Inspired by the practical necessity of calculating potentials in diverse electromagnetic media, we consider the anisotropic Laplace equation to derive the anisotropic Gauss formula and apply it to surface reconstruction, called “anisotropic Gauss reconstruction”. By leveraging the flexibility of anisotropic coefficients, additional constraints can be introduced to the indicator function. This results in a stable linear system, eliminating the need for any artificial regularization. In addition, the oriented normals can be refined by computing the gradient of the indicator function, ultimately producing high-quality normals and surfaces. Regarding the space/time complexity, we propose an octree-based acceleration algorithm to achieve a space complexity of O(N) and a time complexity of O(NlogN). Our method can reconstruct ultra-large-scale models (exceeding 5 million points) within 4 minutes on an NVIDIA RTX 4090 GPU. Extensive experiments demonstrate that our method achieves state-of-the-art performance in both orientation and reconstruction, particularly for models with thin structures, small holes, or high genus. Both CuPy-based and CUDA-accelerated implementations are made publicly available at https://github.com/mayueji/AGR.","PeriodicalId":10687,"journal":{"name":"Computer Graphics Forum","volume":"44 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144914969","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

Mint: Discretely Integrable Moments for Symmetric Frame Fields 对称框架场的离散可积矩

IF 2.9 4区计算机科学

Computer Graphics Forum Pub Date : 2025-08-28 DOI: 10.1111/cgf.70193

J. Vekhter, Z. Chen, E. Vouga

引用次数: 0

Beyond Complete Shapes: A Benchmark for Quantitative Evaluation of 3D Shape Surface Matching Algorithms 超越完整形状：三维形状表面匹配算法定量评估的基准

IF 2.9 4区计算机科学

Computer Graphics Forum Pub Date : 2025-08-28 DOI: 10.1111/cgf.70186

V. Ehm, N. El Amrani, Y. Xie, L. Bastian, M. Gao, W. Wang, L. Sang, D. Cao, T. Weißberg, Z. Lähner, D. Cremers, F. Bernard

{"title":"Beyond Complete Shapes: A Benchmark for Quantitative Evaluation of 3D Shape Surface Matching Algorithms","authors":"V. Ehm, N. El Amrani, Y. Xie, L. Bastian, M. Gao, W. Wang, L. Sang, D. Cao, T. Weißberg, Z. Lähner, D. Cremers, F. Bernard","doi":"10.1111/cgf.70186","DOIUrl":"https://doi.org/10.1111/cgf.70186","url":null,"abstract":"Finding correspondences between 3D deformable shapes is an important and long-standing problem in geometry processing, computer vision, graphics, and beyond. While various shape matching datasets exist, they are mostly static or limited in size, restricting their adaptation to different problem settings, including both full and partial shape matching. In particular the existing partial shape matching datasets are small (fewer than 100 shapes) and thus unsuitable for data-hungry machine learning approaches. Moreover, the type of partiality present in existing datasets is often artificial and far from realistic. To address these limitations, we introduce a generic and flexible framework for the procedural generation of challenging full and partial shape matching datasets. Our framework allows the propagation of custom annotations across shapes, making it useful for various applications. By utilising our framework and manually creating cross-dataset correspondences between seven existing (complete geometry) shape matching datasets, we propose a new large benchmark BeCoS with a total of 2543 shapes. Based on this, we offer several challenging benchmark settings, covering both full and partial matching, for which we evaluate respective state-of-the-art methods as baselines. Visualisations and code of our benchmark can be found at: https://nafieamrani.github.io/BeCoS/.","PeriodicalId":10687,"journal":{"name":"Computer Graphics Forum","volume":"44 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cgf.70186","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144914974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Affine Heat Method 仿射热法

IF 2.9 4区计算机科学

Computer Graphics Forum Pub Date : 2025-08-28 DOI: 10.1111/cgf.70205

Yousuf Soliman, Nicholas Sharp

引用次数: 0

Real-Time Secondary Animation with Spring Decomposed Skinning 实时二次动画与春季分解皮肤

IF 2.9 4区计算机科学

Computer Graphics Forum Pub Date : 2025-08-28 DOI: 10.1111/cgf.70209

B. Akyürek, Y. Sahillioğlu

{"title":"Real-Time Secondary Animation with Spring Decomposed Skinning","authors":"B. Akyürek, Y. Sahillioğlu","doi":"10.1111/cgf.70209","DOIUrl":"https://doi.org/10.1111/cgf.70209","url":null,"abstract":"We present a framework to integrate secondary motion into the existing animation pipelines. Skinning provides fast computation for real-time animation and intuitive control over the deformation. Despite the benefits, traditional skinning methods lack secondary dynamics such as the jiggling of fat tissues. We address the rigidity of skinning methods by physically simulating the deformation handles with spring forces. Most studies introduce secondary motion into skinning by employing FEM simulation on volumetric mesh vertices, coupling their computational complexity with mesh resolution. Unlike these approaches, we do not require any volumetric mesh input. Our method scales to higher mesh resolutions by directly simulating deformation handles. The simulated handles, namely the spring bones, enrich rigid skinning deformation with a diverse range of secondary animation for subjects including rigid bodies, elastic bodies, soft tissues, and cloth simulation. In essence, we leverage the benefits of physical simulations in the scope of deformation handles to achieve controllable real-time dynamics on a wide range of subjects while remaining compatible with existing skinning pipelines. Our method avoids tetrahedral remeshing and it is significantly faster compared to FEM-based volumetric mesh simulations.","PeriodicalId":10687,"journal":{"name":"Computer Graphics Forum","volume":"44 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144915178","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

Exact and Efficient Mesh-Kernel Generation 精确高效的网格核生成

IF 2.9 4区计算机科学

Computer Graphics Forum Pub Date : 2025-08-28 DOI: 10.1111/cgf.70187

J. Nehring-Wirxel, P. Kern, P. Trettner, L. Kobbelt

引用次数: 0

Volume Preserving Neural Shape Morphing 体积保持神经形状变形

IF 2.9 4区计算机科学

Computer Graphics Forum Pub Date : 2025-08-28 DOI: 10.1111/cgf.70196

Camille Buonomo, Julie Digne 1, Raphaëlle Chaine

{"title":"Volume Preserving Neural Shape Morphing","authors":"Camille Buonomo, Julie Digne 1, Raphaëlle Chaine","doi":"10.1111/cgf.70196","DOIUrl":"https://doi.org/10.1111/cgf.70196","url":null,"abstract":"Shape interpolation is a long standing challenge of geometry processing. As it is ill-posed, shape interpolation methods always work under some hypothesis such as semantic part matching or least displacement. Among such constraints, volume preservation is one of the traditional animation principles. In this paper we propose a method to interpolate between shapes in arbitrary poses favoring volume and topology preservation. To do so, we rely on a level set representation of the shape and its advection by a velocity field through the level set equation, both shape representation and velocity fields being parameterized as neural networks. While divergence free velocity fields ensure volume and topology preservation, they are incompatible with the Eikonal constraint of signed distance functions. This leads us to introduce the notion of adaptive divergence velocity field, a construction compatible with the Eikonal equation with theoretical guarantee on the shape volume preservation. In the non constant volume setting, our method is still helpful to provide a natural morphing, by combining it with a parameterization of the volume change over time. We show experimentally that our method exhibits better volume preservation than other recent approaches, limits topological changes and preserves the structures of shapes better without landmark correspondences.","PeriodicalId":10687,"journal":{"name":"Computer Graphics Forum","volume":"44 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144914965","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

MDNF: Multi-Diffusion-Nets for Neural Fields on Meshes 网格上神经场的多扩散网络

IF 2.9 4区计算机科学

Computer Graphics Forum Pub Date : 2025-08-28 DOI: 10.1111/cgf.70188

Avigail Cohen Rimon, Tal Shnitzer, Mirela Ben Chen

{"title":"MDNF: Multi-Diffusion-Nets for Neural Fields on Meshes","authors":"Avigail Cohen Rimon, Tal Shnitzer, Mirela Ben Chen","doi":"10.1111/cgf.70188","DOIUrl":"https://doi.org/10.1111/cgf.70188","url":null,"abstract":"We propose a novel framework for representing neural fields on triangle meshes that is multi-resolution across both spatial and frequency domains. Inspired by the Neural Fourier Filter Bank (NFFB), our architecture decomposes the spatial and frequency domains by associating finer spatial resolution levels with higher frequency bands, while coarser resolutions are mapped to lower frequencies. To achieve geometry-aware spatial decomposition we leverage multiple DiffusionNet components, each associated with a different spatial resolution level. Subsequently, we apply a Fourier feature mapping to encourage finer resolution levels to be associated with higher frequencies. The final signal is composed in a wavelet-inspired manner using a sine-activated MLP, aggregating higher-frequency signals on top of lower-frequency ones. Our architecture attains high accuracy in learning complex neural fields and is robust to discontinuities, exponential scale variations of the target field, and mesh modification. We demonstrate the effectiveness of our approach through its application to diverse neural fields, such as synthetic RGB functions, UV texture coordinates, and vertex normals, illustrating different challenges. To validate our method, we compare its performance against two alternatives, showcasing the advantages of our multi-resolution architecture.","PeriodicalId":10687,"journal":{"name":"Computer Graphics Forum","volume":"44 5","pages":""},"PeriodicalIF":2.9,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/cgf.70188","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144914967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0