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SDM-NET: Deep Generative Network for Structured Deformable Mesh
[article]
2019
arXiv
pre-print
We introduce SDM-NET, a deep generative neural network which produces structured deformable meshes. Specifically, the network is trained to generate a spatial arrangement of closed, deformable mesh parts, which respect the global part structure of a shape collection, e.g., chairs, airplanes, etc. Our key observation is that while the overall structure of a 3D shape can be complex, the shape can usually be decomposed into a set of parts, each homeomorphic to a box, and the finer-scale geometry
arXiv:1908.04520v2
fatcat:3dmtrxswqrdkngles35y434jdu