MatFormer: A Generative Model for Procedural Materials

ACM Transactions on Graphics (Proc. SIGGRAPH 2022)

Published August 8, 2022

Paul Guerrero, Miloš Hašan, Kalyan Sunkavalli, Radomír Měch, Tamy Boubekeur, Niloy J. Mitra

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 accessible libraries contain only a few thousand such graphs. We present MatFormer, a generative model that can produce a diverse set of high-quality procedural materials with complex spatial patterns and appearance. While procedural materials can be modeled as directed (operation) graphs, they contain arbitrary numbers of heterogeneous nodes with unstructured, often long-range node connections, and functional constraints on node parameters and connections. MatFormer addresses these challenges with a multi-stage transformer-based model that sequentially generates nodes, node parameters, and edges, while ensuring the semantic validity of the graph. In addition to generation, MatFormer can be used for the auto-completion and exploration of partial material graphs.We qualitatively and quantitatively demonstrate that our method outperforms alternative approaches, in both generated graph and material quality.

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