GEM3D: GEnerative Medial Abstractions for 3D Shape Synthesis

We introduce GEM3D -- a new deep, topology-aware generative model of 3D shapes. The key ingredient of our method is a neural skeleton-based representation encoding information on both shape topology and geometry. Through a denoising diffusion probabilistic model, our method first generates skeleton-...

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Veröffentlicht in:	arXiv.org 2024-04
Hauptverfasser:	Petrov, Dmitry, Goyal, Pradyumn, Thamizharasan, Vikas, Kim, Vladimir G, Gadelha, Matheus, Averkiou, Melinos, Chaudhuri, Siddhartha, Kalogerakis, Evangelos
Format:	Artikel
Sprache:	eng
Schlagworte:	Image reconstruction Probabilistic models Representations Synthesis Three dimensional models Topology
Online-Zugang:	Volltext
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