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Shape Inference and Grammar Induction for Example-based Procedural Generation

arXiv 2109.10217 ↗First posted 21 Sep 2021cs.AI cs.LGcited by 0

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Abstract (arXiv)

Designers increasingly rely on procedural generation for automatic generation of content in various industries. These techniques require extensive knowledge of the desired content, and about how to actually implement such procedural methods. Algorithms for learning interpretable generative models from example content could alleviate both difficulties. We propose SIGI, a novel method for inferring shapes and inducing a shape grammar from grid-based 3D building examples. This interpretable grammar is well-suited for co-creative design. Applied to Minecraft buildings, we show how the shape grammar can be used to automatically generate new buildings in a similar style.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 1 of its 25 references that are in the map. First posted on arXiv 21 Sep 2021.

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References · 1

  1. 2017Procedural Content Generation via Machine Learning (PCGML)cited by 137

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