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Geometry and learning in 3D correspondence problems

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VMVW03 - Flows, mappings and shapes

The need to compute correspondence between three-dimensional objects is a fundamental ingredient in numerous computer vision and graphics tasks. In this talk, I will show how several geometric notions related to the Laplacian spectrum provide a set of tools for efficiently calculating correspondence between deformable shapes. I will also show how this framework combined with recent ideas in deep learning promises to bring correspondence problems to new levels of accuracy.

This talk is part of the Isaac Newton Institute Seminar Series series.

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