Learning to Approximate Directional Fields Defined over 2D Planes

Maria Taktasheva; Albert Matveev; Alexey Artemov; Evgeny Burnaev

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arXiv · 1907.00559

Learning to Approximate Directional Fields Defined over 2D Planes

Maria Taktasheva·Albert Matveev·Alexey Artemov·Evgeny Burnaev

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Abstract

Reconstruction of directional fields is a need in many geometry processing tasks, such as image tracing, extraction of 3D geometric features, and finding principal surface directions. A common approach to the construction of directional fields from data relies on complex optimization procedures, which are usually poorly formalizable, require a considerable computational effort, and do not transfer across applications. In this work, we propose a deep learning-based approach and study the expressive power and generalization ability.

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Maria Taktasheva, Albert Matveev, Alexey Artemov, Evgeny Burnaev. 2019-07-01. Learning to Approximate Directional Fields Defined over 2D Planes. https://arxiv.org/abs/1907.00559

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