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We present the Shape Part Slot Machine, a new method for assembling novel 3Dshapes from existing parts by performing contact-based reasoning. Our methodrepresents each shape as a graph of ``slots,'' where each slot is a region ofcontact between two shape parts. Based on this representation, we design agraph-neural-network-based model for generating new slot graphs and retrievingcompatible parts, as well as a gradient-descent-based optimization scheme forassembling the retrieved parts into a complete shape that respects thegenerated slot graph. This approach does not require any semantic part labels;interestingly, it also does not require complete part geometries -- reasoningabout the slots proves sufficient to generate novel, high-quality 3D shapes. Wedemonstrate that our method generates shapes that outperform existingmodeling-by-assembly approaches regarding quality, diversity, and structuralcomplexity.

The Shape Part Slot Machine: Contact-based Reasoning for Generating 3D Shapes from Parts