An Inverse Procedural Modeling Pipeline for SVBRDF Maps

TL;DR

This paper introduces a semi-automatic pipeline that decomposes SVBRDF maps into hierarchical procedural models using novel spectrum-aware matting, instance-based decomposition, and differentiable rendering optimization, enabling scalable and editable material representations.

Contribution

The work presents a new hierarchical proceduralization pipeline for SVBRDF maps, combining spectrum-aware matting, instance-based decomposition, and differentiable rendering, advancing material modeling techniques.

Findings

Successfully decomposes diverse real and synthetic materials.

Produces fully procedural, scalable, and editable material models.

Eliminates the need for artist-designed material graphs.

Abstract

Procedural modeling is now the de facto standard of material modeling in industry. Procedural models can be edited and are easily extended, unlike pixel-based representations of captured materials. In this paper, we present a semi-automatic pipeline for general material proceduralization. Given Spatially-Varying Bidirectional Reflectance Distribution Functions (SVBRDFs) represented as sets of pixel maps, our pipeline decomposes them into a tree of sub-materials whose spatial distributions are encoded by their associated mask maps. This semi-automatic decomposition of material maps progresses hierarchically, driven by our new spectrum-aware material matting and instance-based decomposition methods. Each decomposed sub-material is proceduralized by a novel multi-layer noise model to capture local variations at different scales. Spatial distributions of these sub-materials are modeled either by a by-example inverse synthesis method recovering Point Process Texture Basis Functions (PPTBF) or via random sampling. To reconstruct procedural material maps, we propose a differentiable rendering-based optimization that recomposes all generated procedures together to maximize the similarity between our procedural models and the input material pixel maps. We evaluate our pipeline on a variety of synthetic and real materials. We demonstrate our method's capacity to process a wide range of material types, eliminating the need for artist designed material graphs required in previous work. As fully procedural models, our results expand to arbitrary resolution and enable high level user control of appearance.