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Local Deep Implicit Functions for 3D Shape
[article]
2020
arXiv
pre-print
The goal of this project is to learn a 3D shape representation that enables accurate surface reconstruction, compact storage, efficient computation, consistency for similar shapes, generalization across diverse shape categories, and inference from depth camera observations. Towards this end, we introduce Local Deep Implicit Functions (LDIF), a 3D shape representation that decomposes space into a structured set of learned implicit functions. We provide networks that infer the space decomposition
arXiv:1912.06126v2
fatcat:enbtwuhzkjbd7bfy2cdsywejwm