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We propose a variational technique to optimize for generalized barycentric coordinates that offers additional control compared to existing models. Prior work represents barycentric coordinates using meshes or closed-form formulae, limiting the choice of objective function. In contrast, we directly parameterize the continuous function mapping any coordinate in a polytope’s interior to its barycentric coordinates using a neural field. Enabled by our theoretical characterization of barycentric coordinates, we construct neural fields parameterizing valid coordinates. We demonstrate flexibility using various objective functions, validate our algorithm, and present several applications.more » « less
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Dodik, Ana; Stein, Oded; Sitzmann, Vincent; Solomon, Justin (, ACM Transactions on Graphics)We propose a variational technique to optimize for generalized barycentric coordinates that offers additional control compared to existing models. Prior work represents barycentric coordinates using meshes or closed-form formulae, limiting the choice of objective function. In contrast, we directly parameterize the continuous function mapping any coordinate in a polytope’s interior to its barycentric coordinates using a neural field. Enabled by our theoretical characterization of barycentric coordinates, we construct neural fields parameterizing valid coordinates. We demonstrate flexibility using various objective functions, validate our algorithm, and present several applications.more » « less
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