Phd in COMPUTER SCIENCE

Thesis title: Editing Methods for Procedural Materials

Procedural modeling has long offered resolution-independent, editable representations for computer graphics, yet the inverse estimation of procedural parameters, interactive editing, and collaborative version control remain challenging. In this work, we present a suite of complementary techniques that tackle these issues. First, we introduce a method for recovering the parameters of procedural vector patterns, defined as collections of standard graphics primitives arranged by arbitrary programs, by differentiating their Signed Distance Fields rather than relying solely on raster-based losses. This approach yields reliable parameter estimation even when target images are hand-drawn or comprise sparse overlapping elements. Second, we propose an interactive system to sketch procedural patterns, where complex designs are decomposed into a hierarchy of coarse-to-fine levels, namely scaffolds. Users can iteratively refine their sketches while a gradient-free, GPU-accelerated optimizer updates only the additional parameters introduced at each scaffold level. Finally, we develop a version control system for procedural node graphs. By directly comparing typed node structures using a greedy matching algorithm, which approximates the Graph Edit Distance under type constraints, our method reliably diffs and merges concurrent edits in collaborative settings. Extensive experiments and comparisons with state-of-the-art approaches prove that our work enhances both the quality and efficiency of procedural content creation workflows.