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In materials science, microstructures and their associated extrinsic properties are critical for engineering advanced structural and functional materials, yet their robust reconstruction and generation remain significant challenges. In this…

Materials Science · Physics 2024-10-01 Yixuan Zhang , Teng Long , Hongbin Zhang

As 3D point clouds become a cornerstone of modern technology, the need for sophisticated generative models and reliable evaluation metrics has grown exponentially. In this work, we first expose that some commonly used metrics for evaluating…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Matteo Bastico , David Ryckelynck , Laurent Corté , Yannick Tillier , Etienne Decencière

While the community of 3D point cloud generation has witnessed a big growth in recent years, there still lacks an effective way to enable intuitive user control in the generation process, hence limiting the general utility of such methods.…

Computer Vision and Pattern Recognition · Computer Science 2023-08-22 Kiyohiro Nakayama , Mikaela Angelina Uy , Jiahui Huang , Shi-Min Hu , Ke Li , Leonidas J Guibas

Crystalline materials are a fundamental component in next-generation technologies, yet modeling their distribution presents unique computational challenges. Of the plausible arrangements of atoms in a periodic lattice only a vanishingly…

Machine Learning · Computer Science 2024-06-10 Benjamin Kurt Miller , Ricky T. Q. Chen , Anuroop Sriram , Brandon M Wood

We present a generative modeling framework for atomistic systems that combines score-based diffusion for atomic positions with a novel continuous-time discrete diffusion process for atomic types. This approach enables flexible and…

Computational Physics · Physics 2025-09-17 Nikolaj Rønne , Bjørk Hammer

Diffusion-based deep generative models have emerged as powerful tools for inverse materials design. Yet, many existing approaches overlook essential chemical constraints such as oxidation state balance, which can lead to chemically invalid…

Materials Science · Physics 2025-07-29 Mouyang Cheng , Weiliang Luo , Hao Tang , Bowen Yu , Yongqiang Cheng , Weiwei Xie , Ju Li , Heather J. Kulik , Mingda Li

We propose a method to generate 3D shapes using point clouds. Given a point-cloud representation of a 3D shape, our method builds a kd-tree to spatially partition the points. This orders them consistently across all shapes, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2017-07-21 Matheus Gadelha , Subhransu Maji , Rui Wang

Equivariant diffusion models have emerged as the prevailing approach for generating novel crystal materials due to their ability to leverage the physical symmetries of periodic material structures. However, current models do not effectively…

Machine Learning · Computer Science 2025-03-04 Kishalay Das , Subhojyoti Khastagir , Pawan Goyal , Seung-Cheol Lee , Satadeep Bhattacharjee , Niloy Ganguly

Discovering materials with new structural chemistry is key to achieving transformative functionality. Generative artificial intelligence offers a scalable route to propose candidate crystal structures. We introduce a reliable low-cost proxy…

In this paper we propose a novel point cloud generator that is able to reconstruct and generate 3D point clouds composed of semantic parts. Given a latent representation of the target 3D model, the generation starts from a single point and…

Computer Vision and Pattern Recognition · Computer Science 2021-06-01 Wei-Jan Ko , Hui-Yu Huang , Yu-Liang Kuo , Chen-Yi Chiu , Li-Heng Wang , Wei-Chen Chiu

Diffusion generative models transform noise into data by inverting a process that progressively adds noise to data samples. Inspired by concepts from the renormalization group in physics, which analyzes systems across different scales, we…

Machine Learning · Computer Science 2024-10-04 Mathis Gerdes , Max Welling , Miranda C. N. Cheng

This pictorial presents an ongoing research programme comprising three practice-based Design Research projects conducted through 2024, exploring the affordances of diffusion-based AI image generation systems, specifically Stable Diffusion.…

Human-Computer Interaction · Computer Science 2024-11-21 Joseph Lindley , Roger Whitham

Creating high-quality materials in computer graphics is a challenging and time-consuming task, which requires great expertise. To simplify this process, we introduce MatFuse, a unified approach that harnesses the generative power of…

Computer Vision and Pattern Recognition · Computer Science 2024-11-18 Giuseppe Vecchio , Renato Sortino , Simone Palazzo , Concetto Spampinato

In this paper, we present DesignDiffusion, a simple yet effective framework for the novel task of synthesizing design images from textual descriptions. A primary challenge lies in generating accurate and style-consistent textual and visual…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Zhendong Wang , Jianmin Bao , Shuyang Gu , Dong Chen , Wengang Zhou , Houqiang Li

Photonic crystals enable fine control over light propagation at the nanoscale, and thus play a central role in the development of photonic and quantum technologies. Photonic band diagrams (BDs) are a key tool to investigate light…

Crystal structures can be viewed as assemblies of space-filling polyhedra, which play a critical role in determining material properties such as ionic conductivity and dielectric constant. However, most conventional crystal structure…

Materials Science · Physics 2026-03-20 Tomoyasu Yokoyama , Kazuhide Ichikawa , Hisashi Naito

Discovering new solid-state materials requires rapidly exploring the vast space of crystal structures and locating stable regions. Generating stable materials with desired properties and compositions is extremely difficult as we search for…

Machine Learning · Computer Science 2024-11-08 Tri Minh Nguyen , Sherif Abdulkader Tawfik , Truyen Tran , Sunil Gupta , Santu Rana , Svetha Venkatesh

The discovery of novel solid-state materials, such as electrocatalysts, super-ionic conductors, or photovoltaic materials, plays a critical role in addressing various global challenges. It has, for instance, the potential to significantly…

As 3D point clouds become the representation of choice for multiple vision and graphics applications, the ability to synthesize or reconstruct high-resolution, high-fidelity point clouds becomes crucial. Despite the recent success of deep…

Computer Vision and Pattern Recognition · Computer Science 2019-09-04 Guandao Yang , Xun Huang , Zekun Hao , Ming-Yu Liu , Serge Belongie , Bharath Hariharan

Generative diffusion models have achieved remarkable success in producing high-quality images. However, these models typically operate in continuous intensity spaces, diffusing independently across pixels and color channels. As a result,…

Graphics · Computer Science 2025-05-20 Javier E. Santos , Agnese Marcato , Roman Colman , Nicholas Lubbers , Yen Ting Lin