Gaussian material synthesis

Károly Zsolnai-Fehér, Peter Wonka, Michael Wimmer

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

We present a learning-based system for rapid mass-scale material synthesis that is useful for novice and expert users alike. The user preferences are learned via Gaussian Process Regression and can be easily sampled for new recommendations. Typically, each recommendation takes 40-60 seconds to render with global illumination, which makes this process impracticable for real-world workflows. Our neural network eliminates this bottleneck by providing high-quality image predictions in real time, after which it is possible to pick the desired materials from a gallery and assign them to a scene in an intuitive manner.Workflow timings against Disney's
Original languageEnglish (US)
Pages (from-to)1-14
Number of pages14
JournalACM Transactions on Graphics
Volume37
Issue number4
DOIs
StatePublished - Jul 31 2018

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