Search Results for author: Theo Deprelle

Found 2 papers, 1 papers with code

Learning Joint Surface Atlases

no code implementations13 Jun 2022 Theo Deprelle, Thibault Groueix, Noam Aigerman, Vladimir G. Kim, Mathieu Aubry

We demonstrate that this improves the quality of the learned surface representation, as well as its consistency in a collection of related shapes.

Learning elementary structures for 3D shape generation and matching

3 code implementations NeurIPS 2019 Theo Deprelle, Thibault Groueix, Matthew Fisher, Vladimir G. Kim, Bryan C. Russell, Mathieu Aubry

We propose to represent shapes as the deformation and combination of learnable elementary 3D structures, which are primitives resulting from training over a collection of shape.

Ranked #8 on 3D Dense Shape Correspondence on SHREC'19 (using extra training data)

3D Dense Shape Correspondence 3D Shape Generation +1

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