Web: http://arxiv.org/abs/2104.14547

Jan. 14, 2022, 2:11 a.m. | Anjana Deva Prasad, Aditya Balu, Harshil Shah, Soumik Sarkar, Chinmay Hegde, Adarsh Krishnamurthy

cs.LG updates on arXiv.org arxiv.org

Boundary representations (B-reps) using Non-Uniform Rational B-splines
(NURBS) are the de facto standard used in CAD, but their utility in deep
learning-based approaches is not well researched. We propose a differentiable
NURBS module to integrate NURBS representations of CAD models with deep
learning methods. We mathematically define the derivatives of the NURBS curves
or surfaces with respect to the input parameters (control points, weights, and
the knot vector). These derivatives are used to define an approximate Jacobian
used for performing the "backward" evaluation to train the deep learning
models. We …

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