activity
20222024
most citedMatFormer: A Generative Model for Procedural Materials

44 citations · 124 across the 9 of their papers we have counts for

collaborators

9 papers

cs.CV2024

PBIR-NIE: Glossy Object Capture under Non-Distant Lighting

Guangyan Cai, Fujun Luan, Miloš Hašan +5

Glossy objects present a significant challenge for 3D reconstruction from multi-view input images under natural lighting. In this paper, we introduce PBIR-NIE, an inverse rendering…

cs.CV2024

Woven Fabric Capture with a Reflection-Transmission Photo Pair

Yingjie Tang, Zixuan Li, Miloš Hašan +2

Digitizing woven fabrics would be valuable for many applications, from digital humans to interior design. Previous work introduces a lightweight woven fabric acquisition approach b…

cs.GR2024

Rendering Participating Media Using Path Graphs

Becky Hu, Xi Deng, Fujun Luan +2

Rendering volumetric scattering media, including clouds, fog, smoke, and other complex materials, is crucial for realism in computer graphics. Traditional path tracing, while unbia…

cs.CV202332 cited

PhotoMat: A Material Generator Learned from Single Flash Photos

Xilong Zhou, Miloš Hašan, Valentin Deschaintre +4

Authoring high-quality digital materials is key to realism in 3D rendering. Previous generative models for materials have been trained exclusively on synthetic data; such data is l…

cs.GR202326 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.GR202244 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…