44-Issue 5

Permanent URI for this collection

Geometry Processing 2025 - Symposium Proceedings
Bilbao, Spain | June 30 - July 4, 2025

Fields on Meshes
GreenCloud: Volumetric Gradient Filtering via Regularized Green's Functions
Kenji Tojo and Nobuyuki Umetani
Mint: Discretely Integrable Moments for Symmetric Frame Fields
Josh Vekhter, Zhen Chen, and Etienne Vouga
The Affine Heat Method
Yousuf Soliman and Nicholas Sharp
MDNF: Multi-Diffusion-Nets for Neural Fields on Meshes
Avigail Cohen Rimon, Tal Shnitzer, and Mirela Ben-Chen
Reconstruction
Anisotropic Gauss Reconstruction and Global Orientation with Octree-based Acceleration
Yueji Ma, Jialu Shen, Yanzun Meng, Dong Xiao, Zuoqiang Shi, and Bin Wang
Bayesian 3D Shape Reconstruction from Noisy Points and Normals
Eduard Pujol and Antonio Chica
Symmetrized Poisson Reconstruction
Maximilian Kohlbrenner, Hongyi Liu, Marc Alexa, and Misha Kazhdan
Implicit Representations
Uniform Sampling of Surfaces by Casting Rays
Selena Ling, Abhishek Madan, Nicholas Sharp, and Alec Jacobson
Arrange and Traverse Algorithm for Computation of Reeb Spaces of Piecewise Linear Maps
Petar Hristov, Daiske Sakurai, Hamish Carr, Ingrid Hotz, and Talha Bin Masood
One-Shot Method for Computing Generalized Winding Numbers
Cedric Martens and Mikhail Bessmeltsev
Shape Analysis
Beyond Complete Shapes: A Benchmark for Quantitative Evaluation of 3D Shape Matching Algorithms
Viktoria Ehm, Nafie El Amrani, Yizheng Xie, Lennart Bastian, Maolin Gao, Weikang Wang, Lu Sang, Dongliang Cao, Tobias Weißberg, Zorah Lähner, Daniel Cremers, and Florian Bernard
High-Resolution 3D Shape Matching with Global Optimality and Geometric Consistency
Nafie El Amrani, Paul Roetzer, and Florian Bernard
An Efficient Global-to-Local Rotation Optimization Approach via Spherical Harmonics
Zihang He, Yuezhi Yang, Congyue Deng, Jiaxin Lu, Leonidas Guibas, and Qixing Huang
FRIDU: Functional Map Refinement with Guided Image Diffusion
Avigail Cohen Rimon, Mirela Ben-Chen, and Or Litany
Mesh Processing
Exact and Efficient Mesh-Kernel Generation
Julius Nehring-Wirxel, Paul Kern, Philip Trettner, and Leif Kobbelt
Controlling Quadric Error Simplification with Line Quadrics
Hsueh-Ti Derek Liu, Mehdi Rahimzadeh, and Victor Zordan
Resolving Self-intersections in 3D Meshes while Preserving Floating-point Coordinates
Léo Valque and Sylvain Lazard
Fabrication
MatAIRials: Isotropic Inflatable Metamaterials for Freeform Surface Design
Siyuan He, Meng-Jan Wu, Arthur Lebée, and Mélina Skouras
Atomizer: Beyond Non-Planar Slicing for Fused Filament Fabrication
Xavier Chermain, Giovanni Cocco, Cédric Zanni, Eric Garner, Pierre-Alexandre Hugron, and Sylvain Lefebvre
Shape Approximation by Surface Reuse
Berend Baas, David Bommes, and Adrien Bousseau
Shape Segmentation and Texturing
OctFusion: Octree-based Diffusion Models for 3D Shape Generation
Bojun Xiong, Si-Tong Wei, Xin-Yang Zheng, Yan-Pei Cao, Zhouhui Lian, and Peng-Shuai Wang
Robust Construction of Polycube Segmentations via Dual Loops
Maxim Snoep, Bettina Speckmann, and Kevin Verbeek
Im2SurfTex: Surface Texture Generation via Neural Backprojection of Multi-View Images
Yiangos Georgiou, Marios Loizou, Melinos Averkiou, and Evangelos Kalogerakis
Animation and Morphing
Volume Preserving Neural Shape Morphing
Camille Buonomo, Julie Digne, and Raphaelle Chaine
Real-Time Secondary Animation with Spring Decomposed Skinning
Bartu Akyürek and Yusuf Sahillioglu
Representing Animatable Avatar via Factorized Neural Fields
Chunjin Song, Zhijie Wu, Bastian Wandt, Leonid Sigal, and Helge Rhodin

BibTeX (44-Issue 5)
                
@article{
10.1111:cgf.70200,
journal = {Computer Graphics Forum}, title = {{
SGP 2025 CGF 44-5: Frontmatter}},
author = {
Attene, Marco
and
Sellán, Silvia
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70200}
}
                
@article{
10.1111:cgf.70184,
journal = {Computer Graphics Forum}, title = {{
Controlling Quadric Error Simplification with Line Quadrics}},
author = {
Liu, Hsueh-Ti Derek
and
Rahimzadeh, Mehdi
and
Zordan, Victor
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70184}
}
                
@article{
10.1111:cgf.70185,
journal = {Computer Graphics Forum}, title = {{
An Efficient Global-to-Local Rotation Optimization Approach via Spherical Harmonics}},
author = {
He, Zihang
and
Yang, Yuezhi
and
Deng, Congyue
and
Lu, Jiaxin
and
Guibas, Leonidas
and
Huang, Qixing
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70185}
}
                
@article{
10.1111:cgf.70186,
journal = {Computer Graphics Forum}, title = {{
Beyond Complete Shapes: A Benchmark for Quantitative Evaluation of 3D Shape Matching Algorithms}},
author = {
Ehm, Viktoria
and
Amrani, Nafie El
and
Cremers, Daniel
and
Bernard, Florian
and
Xie, Yizheng
and
Bastian, Lennart
and
Gao, Maolin
and
Wang, Weikang
and
Sang, Lu
and
Cao, Dongliang
and
Weißberg, Tobias
and
Lähner, Zorah
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70186}
}
                
@article{
10.1111:cgf.70187,
journal = {Computer Graphics Forum}, title = {{
Exact and Efficient Mesh-Kernel Generation}},
author = {
Nehring-Wirxel, Julius
and
Kern, Paul
and
Trettner, Philip
and
Kobbelt, Leif
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70187}
}
                
@article{
10.1111:cgf.70188,
journal = {Computer Graphics Forum}, title = {{
MDNF: Multi-Diffusion-Nets for Neural Fields on Meshes}},
author = {
Rimon, Avigail Cohen
and
Shnitzer, Tal
and
Ben-Chen, Mirela
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70188}
}
                
@article{
10.1111:cgf.70189,
journal = {Computer Graphics Forum}, title = {{
Atomizer: Beyond Non-Planar Slicing for Fused Filament Fabrication}},
author = {
Chermain, Xavier
and
Cocco, Giovanni
and
Zanni, Cédric
and
Garner, Eric
and
Hugron, Pierre-Alexandre
and
Lefebvre, Sylvain
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70189}
}
                
@article{
10.1111:cgf.70190,
journal = {Computer Graphics Forum}, title = {{
MatAIRials: Isotropic Inflatable Metamaterials for Freeform Surface Design}},
author = {
He, Siyuan
and
Wu, Meng-Jan
and
Lebée, Arthur
and
Skouras, Mélina
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70190}
}
                
@article{
10.1111:cgf.70191,
journal = {Computer Graphics Forum}, title = {{
Im2SurfTex: Surface Texture Generation via Neural Backprojection of Multi-View Images}},
author = {
Georgiou, Yiangos
and
Loizou, Marios
and
Averkiou, Melinos
and
Kalogerakis, Evangelos
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70191}
}
                
@article{
10.1111:cgf.70197,
journal = {Computer Graphics Forum}, title = {{
Resolving Self-intersections in 3D Meshes while Preserving Floating-point Coordinates}},
author = {
Valque, Léo
and
Lazard, Sylvain
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70197}
}
                
@article{
10.1111:cgf.70193,
journal = {Computer Graphics Forum}, title = {{
Mint: Discretely Integrable Moments for Symmetric Frame Fields}},
author = {
Vekhter, Josh
and
Chen, Zhen
and
Vouga, Etienne
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70193}
}
                
@article{
10.1111:cgf.70194,
journal = {Computer Graphics Forum}, title = {{
One-Shot Method for Computing Generalized Winding Numbers}},
author = {
Martens, Cedric
and
Bessmeltsev, Mikhail
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70194}
}
                
@article{
10.1111:cgf.70195,
journal = {Computer Graphics Forum}, title = {{
Robust Construction of Polycube Segmentations via Dual Loops}},
author = {
Snoep, Maxim
and
Speckmann, Bettina
and
Verbeek, Kevin
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70195}
}
                
@article{
10.1111:cgf.70196,
journal = {Computer Graphics Forum}, title = {{
Volume Preserving Neural Shape Morphing}},
author = {
Buonomo, Camille
and
Digne, Julie
and
Chaine, Raphaelle
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70196}
}
                
@article{
10.1111:cgf.70192,
journal = {Computer Graphics Forum}, title = {{
Representing Animatable Avatar via Factorized Neural Fields}},
author = {
Song, Chunjin
and
Wu, Zhijie
and
Wandt, Bastian
and
Sigal, Leonid
and
Rhodin, Helge
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70192}
}
                
@article{
10.1111:cgf.70198,
journal = {Computer Graphics Forum}, title = {{
OctFusion: Octree-based Diffusion Models for 3D Shape Generation}},
author = {
Xiong, Bojun
and
Wei, Si-Tong
and
Zheng, Xin-Yang
and
Cao, Yan-Pei
and
Lian, Zhouhui
and
Wang, Peng-Shuai
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70198}
}
                
@article{
10.1111:cgf.70199,
journal = {Computer Graphics Forum}, title = {{
Anisotropic Gauss Reconstruction and Global Orientation with Octree-based Acceleration}},
author = {
Ma, Yueji
and
Shen, Jialu
and
Meng, Yanzun
and
Xiao, Dong
and
Shi, Zuoqiang
and
Wang, Bin
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70199}
}
                
@article{
10.1111:cgf.70201,
journal = {Computer Graphics Forum}, title = {{
Bayesian 3D Shape Reconstruction from Noisy Points and Normals}},
author = {
Pujol, Eduard
and
Chica, Antonio
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70201}
}
                
@article{
10.1111:cgf.70202,
journal = {Computer Graphics Forum}, title = {{
Uniform Sampling of Surfaces by Casting Rays}},
author = {
Ling, Selena
and
Madan, Abhishek
and
Sharp, Nicholas
and
Jacobson, Alec
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70202}
}
                
@article{
10.1111:cgf.70203,
journal = {Computer Graphics Forum}, title = {{
FRIDU: Functional Map Refinement with Guided Image Diffusion}},
author = {
Rimon, Avigail Cohen
and
Ben-Chen, Mirela
and
Litany, Or
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70203}
}
                
@article{
10.1111:cgf.70204,
journal = {Computer Graphics Forum}, title = {{
Shape Approximation by Surface Reuse}},
author = {
Baas, Berend
and
Bommes, David
and
Bousseau, Adrien
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70204}
}
                
@article{
10.1111:cgf.70205,
journal = {Computer Graphics Forum}, title = {{
The Affine Heat Method}},
author = {
Soliman, Yousuf
and
Sharp, Nicholas
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70205}
}
                
@article{
10.1111:cgf.70206,
journal = {Computer Graphics Forum}, title = {{
Arrange and Traverse Algorithm for Computation of Reeb Spaces of Piecewise Linear Maps}},
author = {
Hristov, Petar
and
Sakurai, Daisuke
and
Carr, Hamish
and
Hotz, Ingrid
and
Masood, Talha Bin
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70206}
}
                
@article{
10.1111:cgf.70207,
journal = {Computer Graphics Forum}, title = {{
GreenCloud: Volumetric Gradient Filtering via Regularized Green's Functions}},
author = {
Tojo, Kenji
and
Umetani, Nobuyuki
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70207}
}
                
@article{
10.1111:cgf.70208,
journal = {Computer Graphics Forum}, title = {{
High-Resolution 3D Shape Matching with Global Optimality and Geometric Consistency}},
author = {
Amrani, Nafie El
and
Roetzer, Paul
and
Bernard, Florian
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70208}
}
                
@article{
10.1111:cgf.70209,
journal = {Computer Graphics Forum}, title = {{
Real-Time Secondary Animation with Spring Decomposed Skinning}},
author = {
Akyürek, Bartu
and
Sahillioglu, Yusuf
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70209}
}
                
@article{
10.1111:cgf.70210,
journal = {Computer Graphics Forum}, title = {{
Symmetrized Poisson Reconstruction}},
author = {
Kohlbrenner, Maximilian
and
Liu, Hongyi
and
Alexa, Marc
and
Kazhdan, Misha
}, year = {
2025},
publisher = {
The Eurographics Association and John Wiley & Sons Ltd.},
ISSN = {1467-8659},
DOI = {
10.1111/cgf.70210}
}

Browse

Recent Submissions

Now showing 1 - 27 of 27
  • Item
    SGP 2025 CGF 44-5: Frontmatter
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Attene, Marco; Sellán, Silvia; Attene, Marco; Sellán, Silvia
  • Item
    Controlling Quadric Error Simplification with Line Quadrics
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Liu, Hsueh-Ti Derek; Rahimzadeh, Mehdi; Zordan, Victor; Attene, Marco; Sellán, Silvia
    This work presents a method to control the output of mesh simplification algorithms based on iterative edge collapses. Traditional mesh simplification focuses on preserving the visual appearance. Despite still being an important criterion, other geometric properties also play critical roles in different applications, such as triangle quality for computations. This motivates our work to stay under the umbrella of the popular quadric error mesh simplification, while proposing different ways to control the simplified mesh to possess other geometric properties. The key ingredient of our work is another quadric error, called line quadrics, which can be seamlessly added to the vanilla quadric error metric. We show that, theoretically and empirically, adding our line quadrics can improve the numerics and encourage the simplified mesh to have uniformly distributed vertices. If we spread the line quadric adaptively to different regions, it can easily lead to soft preservation of feature vertices and edges. Our method is simple to implement, requiring only a few lines of code change on top of the original quadric error simplification, and can lead to a variety of user controls.
  • Item
    An Efficient Global-to-Local Rotation Optimization Approach via Spherical Harmonics
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) He, Zihang; Yang, Yuezhi; Deng, Congyue; Lu, Jiaxin; Guibas, Leonidas; Huang, Qixing; Attene, Marco; Sellán, Silvia
    This paper studies the classical problem of 3D shape alignment, namely computing the relative rotation between two shapes (centered at the origin and normalized by scale) by aligning spherical harmonic coefficients of their spherical function representations. Unlike most prior work, which focuses on the regime in which the inputs have approximately the same shape, we focus on the more general and challenging setting in which the shapes may differ. Central to our approach is a stability analysis of spherical harmonic coefficients, which sheds light on how to align them for robust rotation estimation. We observe that due to symmetries, certain spherical harmonic coefficients may vanish. As a result, using a robust norm for alignment that automatically discards such coefficients offers more accurate rotation estimates than the widely used L2 norm. To enable efficient continuous optimization, we show how to analytically compute the Jacobian of spherical harmonic coefficients with respect to rotations. We also introduce an efficient approach for rotation initialization that requires only a sparse set of rotation samples. Experimental results show that our approach achieves better accuracy and efficiency compared to baseline approaches.
  • Item
    Beyond Complete Shapes: A Benchmark for Quantitative Evaluation of 3D Shape Matching Algorithms
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Ehm, Viktoria; Amrani, Nafie El; Xie, Yizheng; Bastian, Lennart; Gao, Maolin; Wang, Weikang; Sang, Lu; Cao, Dongliang; Weißberg, Tobias; Lähner, Zorah; Cremers, Daniel; Bernard, Florian; Attene, Marco; Sellán, Silvia
    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/.
  • Item
    Exact and Efficient Mesh-Kernel Generation
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Nehring-Wirxel, Julius; Kern, Paul; Trettner, Philip; Kobbelt, Leif; Attene, Marco; Sellán, Silvia
    The mesh kernel for a star-shaped mesh is a convex polyhedron given by the intersection of all half-spaces defined by the faces of the input mesh. For all non-star-shaped meshes, the kernel is empty. We present a method to robustly and efficiently compute the kernel of an input triangle mesh by using exact plane-based integer arithmetic to compute the mesh kernel. We make use of several ways to accelerate the computation time. Since many applications just require information if a non-empty mesh kernel exists, we also propose a method to efficiently determine whether a kernel exists by developing an exact plane-based linear program solver. We evaluate our method on a large dataset of triangle meshes and show that in contrast to previous methods, our approach is exact and robust while maintaining a high performance. It is on average two orders of magnitude faster than other exact state-of-the-art methods and often about one order of magnitude faster than non-exact methods.
  • Item
    MDNF: Multi-Diffusion-Nets for Neural Fields on Meshes
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Rimon, Avigail Cohen; Shnitzer, Tal; Ben-Chen, Mirela; Attene, Marco; Sellán, Silvia
    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.
  • Item
    Atomizer: Beyond Non-Planar Slicing for Fused Filament Fabrication
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Chermain, Xavier; Cocco, Giovanni; Zanni, Cédric; Garner, Eric; Hugron, Pierre-Alexandre; Lefebvre, Sylvain; Attene, Marco; Sellán, Silvia
    Fused filament fabrication (FFF) enables users to quickly design and fabricate parts with unprecedented geometric complexity, fine-tuning both the structural and aesthetic properties of each object. Nevertheless, the full potential of this technology has yet to be realized, as current slicing methods fail to fully exploit the deposition freedom offered by modern 3D printers. In this work, we introduce a novel approach to toolpath generation that moves beyond the traditional layer-based concept. We use frames, referred to as atoms, as solid elements instead of slices. We optimize the distribution of atoms within the part volume to ensure even spacing and smooth orientation while accurately capturing the part's geometry. Although these atoms collectively represent the complete object, they do not inherently define a fabrication plan. To address this, we compute an extrusion toolpath as an ordered sequence of atoms that, when followed, provides a collision-free fabrication strategy. This general approach is robust, requires minimal user intervention compared to existing techniques, and integrates many of the best features into a unified framework: precise deposition conforming to non-planar surfaces, effective filling of narrow features - down to a single path - and the capability to locally print vertical structures before transitioning elsewhere. Additionally, it enables entirely new capabilities, such as anisotropic appearance fabrication on curved surfaces.
  • Item
    MatAIRials: Isotropic Inflatable Metamaterials for Freeform Surface Design
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) He, Siyuan; Wu, Meng-Jan; Lebée, Arthur; Skouras, Mélina; Attene, Marco; Sellán, Silvia
    Inflatable pads, such as those used as mattresses or protective equipment, are structures made of two planar membranes sealed according to periodic patterns, typically parallel lines or dots. In this work, we propose to treat these inflatables as metamaterials. By considering novel sealing patterns with 6-fold symmetry, we are able to generate a family of inflatable materials whose macroscale contraction is isotropic and can be modulated by controlling the parameters of the seals. We leverage this property of our inflatable materials family to propose a simple and effective algorithm based on conformal mapping that allows us to design the layout of inflatable structures that can be fabricated flat and whose inflated shapes approximate those of given target freeform surfaces.
  • Item
    Im2SurfTex: Surface Texture Generation via Neural Backprojection of Multi-View Images
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Georgiou, Yiangos; Loizou, Marios; Averkiou, Melinos; Kalogerakis, Evangelos; Attene, Marco; Sellán, Silvia
    We present Im2SurfTex, a method that generates textures for input 3D shapes by learning to aggregate multi-view image outputs produced by 2D image diffusion models onto the shapes' texture space. Unlike existing texture generation techniques that use ad hoc backprojection and averaging schemes to blend multiview images into textures, often resulting in texture seams and artifacts, our approach employs a trained neural module to boost texture coherency. The key ingredient of our module is to leverage neural attention and appropriate positional encodings of image pixels based on their corresponding 3D point positions, normals, and surface-aware coordinates as encoded in geodesic distances within surface patches. These encodings capture texture correlations between neighboring surface points, ensuring better texture continuity. Experimental results show that our module improves texture quality, achieving superior performance in high-resolution texture generation.
  • Item
    Resolving Self-intersections in 3D Meshes while Preserving Floating-point Coordinates
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Valque, Léo; Lazard, Sylvain; Attene, Marco; Sellán, Silvia
    We present a straightforward and robust method for resolving the mesh intersection problem. We focus specifically on the challenge caused by the intersections resulting from the conversion of the vertices coordinates from their exact mathematical values to a fixed-precision floating-point format. Our method takes as input a soup of triangles and outputs intersection-free models whose vertices coordinates are all represented with double-precision floating-point format. We evaluated our approach thoroughly, considering a large collection of meshes. In particular, we can process all the 4 524 models in Thingi10K [ZJ16] that contain self-intersections. This outperforms previous state-of-the-art approaches: On the 527 models of Thingi10K for which naive rounding fails, Zhou et al.'s approach [ZGZJ16] is capable of handling 91% of them, and Valque's 94% [Val24]. In terms of time efficiency, our approach handles about 50k vertices per second on average, which is faster to that of Zhou et al. by a factor 1.4 on these non-trivial models and is faster than that of Valque by several order of magnitude.
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    Mint: Discretely Integrable Moments for Symmetric Frame Fields
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Vekhter, Josh; Chen, Zhen; Vouga, Etienne; Attene, Marco; Sellán, Silvia
    This paper studies the problem of unconstrained (e.g. not orthogonal or unit) symmetric frame field design in volumes. Our principal contribution is a novel (and theoretically well-founded) local integrability condition for frame fields represented as a triplet of symmetric tensors of second, fourth, and sixth order. We also formulate a novel smoothness energy for this representation. To validate our discritization, we study the problem of seamless parameterization of volumetric objects. We compare against baseline approaches by formulating a smooth, integrable, and approximately octahedral frame objective in our discritization. Our method is the first to solve these problems with automatic placement of singularities while also enforcing a symmetric proxy for local integrability as a hard constraint, achieving significantly higher quality parameterizations, in expectation, relative to other frame field design based approaches.
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    One-Shot Method for Computing Generalized Winding Numbers
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Martens, Cedric; Bessmeltsev, Mikhail; Attene, Marco; Sellán, Silvia
    The generalized winding number is an essential part of the geometry processing toolkit, allowing to quantify how much a given point is inside a surface, even when the surface has boundaries and noise. We propose a new universal method to compute a generalized winding number, based only on the surface boundary and the intersections of a single ray with the surface, supporting any oriented surface representations that support a ray intersection query. Due to the focus on the boundary, our algorithm has a unique set of properties. For 2D parametric curves, on a regular grid of query points, our method is up to 4× faster than the current state of the art, maintaining the same precision. In 3D, our method can compute a winding number of a surface without discretizing it, including parametric surfaces. For some meshes with many triangles and a simple boundary, our method is faster than the hierarchical evaluation of the generalized winding number while still being precise. Similarly, on some parametric surfaces with a simple boundary, our method can be faster than adaptive quadrature. We validate our algorithms theoretically, numerically, and by demonstrating a gallery of results on a variety of parametric surfaces and meshes, as well uses in a variety of applications, including voxelizations and boolean operations.
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    Robust Construction of Polycube Segmentations via Dual Loops
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Snoep, Maxim; Speckmann, Bettina; Verbeek, Kevin; Attene, Marco; Sellán, Silvia
    Polycube segmentations for 3D models effectively support a wide variety of applications such as seamless texture mapping, spline fitting, structured multi-block grid generation, and hexahedral mesh construction. However, the automated construction of valid polycube segmentations suffers from robustness issues: state-of-the-art methods are not guaranteed to find a valid solution. In this paper we present DualCube: an iterative algorithm which is guaranteed to return a valid polycube segmentation for 3D models of any genus. Our algorithm is based on a dual representation of polycubes. Starting from an initial simple polycube of the correct genus, together with the corresponding dual loop structure and polycube segmentation, we iteratively refine the polycube, loop structure, and segmentation, while maintaining the correctness of the solution. DualCube is robust by construction: at any point during the iterative process the current segmentation is valid. Its iterative nature furthermore facilitates a seamless trade-off between quality and complexity of the solution. DualCube can be implemented using comparatively simple algorithmic building blocks; our experimental evaluation establishes that the quality of our polycube segmentations is on par with, or exceeding, the state-of-the-art.
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    Volume Preserving Neural Shape Morphing
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Buonomo, Camille; Digne, Julie; Chaine, Raphaelle; Attene, Marco; Sellán, Silvia
    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.
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    Representing Animatable Avatar via Factorized Neural Fields
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Song, Chunjin; Wu, Zhijie; Wandt, Bastian; Sigal, Leonid; Rhodin, Helge; Attene, Marco; Sellán, Silvia
    For reconstructing high-fidelity human 3D models from monocular videos, it is crucial to maintain consistent large-scale body shapes along with finely matched subtle wrinkles. This paper explores how per-frame rendering results can be factorized into a pose-independent component and a corresponding pose-dependent counterpart to facilitate frame consistency at multiple scales. Pose adaptive texture features are further improved by restricting the frequency bands of these two components. Pose-independent outputs are expected to be low-frequency, while high-frequency information is linked to pose-dependent factors. We implement this with a dual-branch network. The first branch takes coordinates in the canonical space as input, while the second one additionally considers features outputted by the first branch and pose information of each frame. A final network integrates the information predicted by both branches and utilizes volume rendering to generate photo-realistic 3D human images. Through experiments, we demonstrate that our method consistently surpasses all state-of-the-art methods in preserving high-frequency details and ensuring consistent body contours. Our code is accessible at https://github.com/ChunjinSong/facavatar.
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    OctFusion: Octree-based Diffusion Models for 3D Shape Generation
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Xiong, Bojun; Wei, Si-Tong; Zheng, Xin-Yang; Cao, Yan-Pei; Lian, Zhouhui; Wang, Peng-Shuai; Attene, Marco; Sellán, Silvia
    Diffusion models have emerged as a popular method for 3D generation. However, it is still challenging for diffusion models to efficiently generate diverse and high-quality 3D shapes. In this paper, we introduce OctFusion, which can generate 3D shapes with arbitrary resolutions in 2.5 seconds on a single Nvidia 4090 GPU, and the extracted meshes are guaranteed to be continuous and manifold. The key components of OctFusion are the octree-based latent representation and the accompanying diffusion models. The representation combines the benefits of both implicit neural representations and explicit spatial octrees and is learned with an octree-based variational autoencoder. The proposed diffusion model is a unified multi-scale U-Net that enables weights and computation sharing across different octree levels and avoids the complexity of widely used cascaded diffusion schemes. We verify the effectiveness of OctFusion on the ShapeNet and Objaverse datasets and achieve state-of-the-art performances on shape generation tasks. We demonstrate that OctFusion is extendable and flexible by generating high-quality color fields for textured mesh generation and high-quality 3D shapes conditioned on text prompts, sketches, or category labels. Our code and pre-trained models are available at https://github.com/octree-nn/octfusion.
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    Anisotropic Gauss Reconstruction and Global Orientation with Octree-based Acceleration
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Ma, Yueji; Shen, Jialu; Meng, Yanzun; Xiao, Dong; Shi, Zuoqiang; Wang, Bin; Attene, Marco; Sellán, Silvia
    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.
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    Bayesian 3D Shape Reconstruction from Noisy Points and Normals
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Pujol, Eduard; Chica, Antonio; Attene, Marco; Sellán, Silvia
    Reconstructing three-dimensional shapes from point clouds remains a central challenge in geometry processing, particularly due to the inherent uncertainties in real-world data acquisition. In this work, we introduce a novel Bayesian framework that explicitly models and propagates uncertainty from both input points and their estimated normals. Our method incorporates the uncertainty of normals derived via Principal Component Analysis (PCA) from noisy input points. Building upon the Smooth Signed Distance (SSD) reconstruction algorithm, we integrate a smoothness prior based on the curvatures of the resulting implicit function following Gaussian behavior. Our method reconstructs a shape represented as a distribution, from which sampling and statistical queries regarding the shape's properties are possible. Additionally, because of the high cost of computing the variance of the resulting distribution, we develop efficient techniques for variance computation. Our approach thus combines two common steps of the geometry processing pipeline, normal estimation and surface reconstruction, while computing the uncertainty of the output of each of these steps.
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    Uniform Sampling of Surfaces by Casting Rays
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Ling, Selena; Madan, Abhishek; Sharp, Nicholas; Jacobson, Alec; Attene, Marco; Sellán, Silvia
    Randomly sampling points on surfaces is an essential operation in geometry processing. This sampling is computationally straightforward on explicit meshes, but it is much more difficult on other shape representations, such as widely-used implicit surfaces. This work studies a simple and general scheme for sampling points on a surface, which is derived from a connection to the intersections of random rays with the surface. Concretely, given a subroutine to cast a ray against a surface and find all intersections, we can use that subroutine to uniformly sample white noise points on the surface. This approach is particularly effective in the context of implicit signed distance functions, where sphere marching allows us to efficiently cast rays and sample points, without needing to extract an intermediate mesh. We analyze the basic method to show that it guarantees uniformity, and find experimentally that it is significantly more efficient than alternative strategies on a variety of representations. Furthermore, we show extensions to blue noise sampling and stratified sampling, and applications to deform neural implicit surfaces as well as moment estimation.
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    FRIDU: Functional Map Refinement with Guided Image Diffusion
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Rimon, Avigail Cohen; Ben-Chen, Mirela; Litany, Or; Attene, Marco; Sellán, Silvia
    We propose a novel approach for refining a given correspondence map between two shapes. A correspondence map represented as a functional map, namely a change of basis matrix, can be additionally treated as a 2D image. With this perspective, we train an image diffusion model directly in the space of functional maps, enabling it to generate accurate maps conditioned on an inaccurate initial map. The training is done purely in the functional space, and thus is highly efficient. At inference time, we use the pointwise map corresponding to the current functional map as guidance during the diffusion process. The guidance can additionally encourage different functional map objectives, such as orthogonality and commutativity with the Laplace-Beltrami operator. We show that our approach is competitive with state-of-the-art methods of map refinement and that guided diffusion models provide a promising pathway to functional map processing.
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    Shape Approximation by Surface Reuse
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Baas, Berend; Bommes, David; Bousseau, Adrien; Attene, Marco; Sellán, Silvia
    The manufacturing industry faces an urgent need to transition from the linear ''make-take-use-dispose'' production model towards more sustainable circular models that retain resources in the production chain. Motivated by this need, we introduce the new problem of approximating 3D surfaces by reusing panels from other surfaces. We present an algorithm that takes as input one or several existing shapes and relies on partial shape registration to identify a small set of simple panels that, once cut from the existing shapes and transformed rigidly, approximate a target shape within a user-defined distance threshold. As a proof of concept, we demonstrate our algorithm in the context of rapid prototyping, where we harvest curved panels from plastic bottles and assemble them with custom connectors to fabricate medium-size freeform structures.
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    The Affine Heat Method
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Soliman, Yousuf; Sharp, Nicholas; Attene, Marco; Sellán, Silvia
    This work presents the Affine Heat Method for computing logarithmic maps. These maps are local surface parameterizations defined by the direction and distance along shortest geodesic paths from a given source point, and arise in many geometric tasks from local texture mapping to geodesic distance-based optimization. Our main insight is to define a connection Laplacian with a homogeneous coordinate accounting for the translation between tangent coordinate frames; the action of short-time heat flow under this Laplacian gives both the direction and distance from the source, along shortest geodesics. The resulting numerical method is straightforward to implement, fast, and improves accuracy compared to past approaches. We present two variants of the method, one of which enables pre-computation for fast repeated solves, while the other resolves the map even near the cut locus in high detail. As with prior heat methods, our approach can be applied in any dimension and to any spatial discretization, including polygonal meshes and point clouds, which we demonstrate along with applications of the method.
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    Arrange and Traverse Algorithm for Computation of Reeb Spaces of Piecewise Linear Maps
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Hristov, Petar; Sakurai, Daisuke; Carr, Hamish; Hotz, Ingrid; Masood, Talha Bin; Attene, Marco; Sellán, Silvia
    We present the first combinatorial algorithm for efficiently computing the Reeb space in all dimensions. The Reeb space is a higher-dimensional generalization of the Reeb graph, which is standard practice in the analysis of scalar fields, along with other computational topology tools such as persistent homology and the Morse-Smale complex. One significant limitation of topological tools for scalar fields is that data often involves multiple variables, where joint analysis is more insightful. Generalizing topological data structures to multivariate data has proven challenging and the Reeb space is one of the few available options. However, none of the existing algorithms can efficiently compute the Reeb space in arbitrary dimensions and there are no available implementations which are robust with respect to numerical errors. We propose a new algorithm for computing the Reeb space of a generic piecewise linear map over a simplicial mesh of any dimension called arrange and traverse. We implement a robust specialization of our algorithm for tetrahedral meshes and evaluate it on real-life data.
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    GreenCloud: Volumetric Gradient Filtering via Regularized Green's Functions
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Tojo, Kenji; Umetani, Nobuyuki; Attene, Marco; Sellán, Silvia
    Gradient-based optimization is a fundamental tool in geometry processing, but it is often hampered by geometric distortion arising from noisy or sparse gradients. Existing methods mitigate these issues by filtering (i.e., diffusing) gradients over a surface mesh, but they require explicit mesh connectivity and solving large linear systems, making them unsuitable for point-based representation. In this work, we introduce a gradient filtering method tailored for point-based geometry. Our method bypasses explicit connectivity by leveraging regularized Green's functions to directly compute the filtered gradient field from discrete spatial points. Additionally, our approach incorporates elastic deformation based on Green's function of linear elasticity (known as Kelvinlets), reproducing various elastic behaviors such as smoothness and volume preservation while improving robustness in affine transformations. We further accelerate computation using a hierarchical Barnes-Hut style approximation, enabling scalable optimization of one million points. Our method significantly improves convergence across a wide range of applications, including reconstruction, editing, stylization, and simplified optimization experiments with Gaussian splatting.
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    High-Resolution 3D Shape Matching with Global Optimality and Geometric Consistency
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Amrani, Nafie El; Roetzer, Paul; Bernard, Florian; Attene, Marco; Sellán, Silvia
    3D shape matching plays a fundamental role in applications such as texture transfer and 3D animation. A key requirement for many scenarios is that matchings exhibit geometric consistency, which ensures that matchings preserve neighbourhood relations across shapes. Despite the importance of geometric consistency, few existing methods explicitly address it, and those that do are either local optimisation methods requiring accurate initialisation, or are severely limited in terms of shape resolution, handling shapes with only up to 3,000 triangles. In this work, we present a scalable approach for geometrically consistent 3D shape matching that, for the first time, scales to high-resolution meshes with up to 10,000 triangles. Our method follows a two-stage procedure: (i) we compute a globally optimal and geometrically consistent mapping of surface patches on the source shape to the target shape via a novel integer linear programming formulation. (ii) we find geometrically consistent matchings of corresponding surface patches which respect correspondences of boundaries of patches obtained from stage (i). With this, we obtain dense, smooth, and guaranteed geometrically consistent correspondences between high-resolution shapes. Empirical evaluations demonstrate that our method is scalable and produces highquality, geometrically consistent correspondences across a wide range of challenging shapes. Our code is publicly available: https://github.com/NafieAmrani/SuPa-Match.
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    Real-Time Secondary Animation with Spring Decomposed Skinning
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Akyürek, Bartu; Sahillioglu, Yusuf; Attene, Marco; Sellán, Silvia
    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.
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    Symmetrized Poisson Reconstruction
    (The Eurographics Association and John Wiley & Sons Ltd., 2025) Kohlbrenner, Maximilian; Liu, Hongyi; Alexa, Marc; Kazhdan, Misha; Attene, Marco; Sellán, Silvia
    Many common approaches for reconstructing surfaces from point clouds leverage normal information to fit an implicit function to the points. Normals typically play two roles: the direction provides a planar approximation to the surface and the sign distinguishes inside from outside. When the sign is missing, reconstructing a surface with globally consistent sidedness is challenging. In this work, we investigate the idea of squaring the Poisson Surface Reconstruction, replacing the normals with their outer products, making the approach agnostic to the signs of the input/estimated normals. Squaring results in a quartic optimization problem, for which we develop an iterative and hierarchical solver, based on setting the cubic partial derivatives to zero. We show that this technique significantly outperforms standard L-BFGS solver and demonstrate reconstruction of surfaces from unoriented noisy input in linear time.