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Procedural materials, represented as functional node graphs, are ubiquitous in computer graphics for photorealistic material appearance design. They allow users to perform intuitive and precise editing to achieve desired visual appearances.…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Beichen Li , Rundi Wu , Armando Solar-Lezama , Changxi Zheng , Liang Shi , Bernd Bickel , Wojciech Matusik

Node graph systems are used ubiquitously for material design in computer graphics. They allow the use of visual programming to achieve desired effects without writing code. As high-level design tools they provide convenience and…

Graphics · Computer Science 2023-04-27 Yiwei Hu , Paul Guerrero , Miloš Hašan , Holly Rushmeier , Valentin Deschaintre

Procedural material graphs are a compact, parameteric, and resolution-independent representation that are a popular choice for material authoring. However, designing procedural materials requires significant expertise and publicly…

Graphics · Computer Science 2022-08-16 Paul Guerrero , Miloš Hašan , Kalyan Sunkavalli , Radomír Měch , Tamy Boubekeur , Niloy J. Mitra

Multimodal program synthesis, which leverages different types of user input to synthesize a desired program, is an attractive way to scale program synthesis to challenging settings; however, it requires integrating noisy signals from the…

Computation and Language · Computer Science 2021-09-16 Xi Ye , Qiaochu Chen , Isil Dillig , Greg Durrett

Methods that use neural networks for synthesizing 3D shapes in the form of a part-based representation have been introduced over the last few years. These methods represent shapes as a graph or hierarchy of parts and enable a variety of…

Graphics · Computer Science 2024-09-20 Yanran Guan , Oliver van Kaick

Artificial intelligence is transforming computational materials science, improving the prediction of material properties, and accelerating the discovery of novel materials. Recently, publicly available material data repositories have grown…

Artificial intelligence for graphs has achieved remarkable success in modeling complex systems, ranging from dynamic networks in biology to interacting particle systems in physics. However, the increasingly heterogeneous graph datasets call…

Machine Learning · Computer Science 2023-01-25 Yasha Ektefaie , George Dasoulas , Ayush Noori , Maha Farhat , Marinka Zitnik

Multimodal recommender systems improve the performance of canonical recommender systems with no item features by utilizing diverse content types such as text, images, and videos, while alleviating inherent sparsity of user-item interactions…

Information Retrieval · Computer Science 2026-03-25 Yu-Seung Roh , Joo-Young Kim , Jin-Duk Park , Won-Yong Shin

Material responses to static and dynamic stimuli, represented as nonlinear curves, are design targets for engineering functionalities like structural support, impact protection, and acoustic and photonic bandgaps. Three-dimensional…

Graph-based procedural materials are ubiquitous in content production industries. Procedural models allow the creation of photorealistic materials with parametric control for flexible editing of appearance. However, designing a specific…

Graphics · Computer Science 2022-07-19 Yiwei Hu , Paul Guerrero , Miloš Hašan , Holly Rushmeier , Valentin Deschaintre

The development of synthesis procedures remains a fundamental challenge in materials discovery, with procedural knowledge scattered across decades of scientific literature in unstructured formats that are challenging for systematic…

Graph embeddings are low dimensional representations of nodes, edges or whole graphs. Such representations allow for data in a network format to be used along with machine learning models for a variety of tasks (e.g., node classification),…

Social and Information Networks · Computer Science 2021-02-24 Kaléu Delphino

Graph-structured combinatorial challenges are inherently difficult due to their nonlinear and intricate nature, often rendering traditional computational methods ineffective or expensive. However, these challenges can be more naturally…

Artificial Intelligence · Computer Science 2025-01-22 Jie Zhao , Kang Hao Cheong , Witold Pedrycz

Given the growing importance of large-scale graph analytics, there is a need to improve the performance of graph analysis frameworks without compromising on productivity. GraphMat is our solution to bridge this gap between a user-friendly…

Although most current large multimodal models (LMMs) can already understand photos of natural scenes and portraits, their understanding of abstract images, e.g., charts, maps, or layouts, and visual reasoning capabilities remains quite…

Computer Vision and Pattern Recognition · Computer Science 2024-10-04 Wenqi Zhang , Zhenglin Cheng , Yuanyu He , Mengna Wang , Yongliang Shen , Zeqi Tan , Guiyang Hou , Mingqian He , Yanna Ma , Weiming Lu , Yueting Zhuang

This paper aims to generate materials for 3D meshes from text descriptions. Unlike existing methods that synthesize texture maps, we propose to generate segment-wise procedural material graphs as the appearance representation, which…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Shangzan Zhang , Sida Peng , Tao Xu , Yuanbo Yang , Tianrun Chen , Nan Xue , Yujun Shen , Hujun Bao , Ruizhen Hu , Xiaowei Zhou

Machine Learning models have emerged as a powerful tool for fast and accurate prediction of different crystalline properties. Exiting state-of-the-art models rely on a single modality of crystal data i.e. crystal graph structure, where they…

Materials Science · Physics 2023-07-12 Kishalay Das , Pawan Goyal , Seung-Cheol Lee , Satadeep Bhattacharjee , Niloy Ganguly

Procedural models (i.e. symbolic programs that output visual data) are a historically-popular method for representing graphics content: vegetation, buildings, textures, etc. They offer many advantages: interpretable design parameters,…

Multi-robot systems of increasing size and complexity are used to solve large-scale problems, such as area exploration and search and rescue. A key decision in human-robot teaming is dividing a multi-robot system into teams to address…

Robotics · Computer Science 2020-04-09 Brian Reily , Christopher Reardon , Hao Zhang

We introduce ProcGen3D, a new approach for 3D content creation by generating procedural graph abstractions of 3D objects, which can then be decoded into rich, complex 3D assets. Inspired by the prevalent use of procedural generators in…

Computer Vision and Pattern Recognition · Computer Science 2025-11-11 Xinyi Zhang , Daoyi Gao , Naiqi Li , Angela Dai
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