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20202025
most citedMatFormer: A Generative Model for Procedural Materials

44 citations · 141 across the 13 of their papers we have counts for

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9 papers · 1 filter

cs.GR2025

RealMat: Realistic Materials with Diffusion and Reinforcement Learning

Xilong Zhou, Pedro Figueiredo, Miloš Hašan +4

Generative models for high-quality materials are particularly desirable to make 3D content authoring more accessible. However, the majority of material generation methods are train…

cs.GR2023★ 26 cited

Generating Procedural Materials from Text or Image Prompts

Yiwei Hu, Paul Guerrero, Miloš Hašan +2

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…

cs.GR2022★ 44 cited

MatFormer: A Generative Model for Procedural Materials

Paul Guerrero, Miloš Hašan, Kalyan Sunkavalli +3

Procedural material graphs are a compact, parameteric, and resolution-independent representation that are a popular choice for material authoring. However, designing procedural mat…

cs.GR2022★ 21 cited

Node Graph Optimization Using Differentiable Proxies

Yiwei Hu, Paul Guerrero, Miloš Hašan +2

Graph-based procedural materials are ubiquitous in content production industries. Procedural models allow the creation of photorealistic materials with parametric control for flexi…

cs.GR2022

Controlling Material Appearance by Examples

Yiwei Hu, Miloš Hašan, Paul Guerrero +2

Despite the ubiquitousness of materials maps in modern rendering pipelines, their editing and control remains a challenge. In this paper, we present an example-based material contr…

cs.GR2022★ 2 cited

TileGen: Tileable, Controllable Material Generation and Capture

Xilong Zhou, Miloš Hašan, Valentin Deschaintre +3

Recent methods (e.g. MaterialGAN) have used unconditional GANs to generate per-pixel material maps, or as a prior to reconstruct materials from input photographs. These models can…

cs.GR2022

Differentiable Rendering of Neural SDFs through Reparameterization

Sai Praveen Bangaru, Michaël Gharbi, Tzu-Mao Li +7

We present a method to automatically compute correct gradients with respect to geometric scene parameters in neural SDF renderers. Recent physically-based differentiable rendering…

cs.GR2021

Neural BRDFs: Representation and Operations

Jiahui Fan, Beibei Wang, Miloš Hašan +2

Bidirectional reflectance distribution functions (BRDFs) are pervasively used in computer graphics to produce realistic physically-based appearance. In recent years, several works…

cs.GR2021

SpongeCake: A Layered Microflake Surface Appearance Model

Beibei Wang, Wenhua Jin, Miloš Hašan +1

In this paper, we propose SpongeCake: a layered BSDF model where each layer is a volumetric scattering medium, defined using microflake or other phase functions. We omit any reflec…