Apr 29, 2021 · View a PDF of the paper titled NURBS-Diff: A Differentiable Programming Module for NURBS, by Anjana Deva Prasad and 5 other authors. View PDF.
We propose a differentiable NURBS module to integrate NURBS representations of CAD models with deep learning methods. We mathematically define the derivatives ...
Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer · Computer Science. Neural Information Processing Systems · 2019.
We propose a differentiable NURBS module to integrate NURBS representations of CAD models with deep learning methods. We mathematically define the derivatives ...
Missing: pdf | Show results with:pdf
NURBS-Diff: A Differentiable Programming Module for NURBS
nyuscholars.nyu.edu › publications › nur...
We propose a differentiable NURBS module to integrate NURBS representations of CAD models with deep learning methods. We mathematically define the derivatives ...
Missing: pdf | Show results with:pdf
Apr 29, 2021 · PreprintPDF Available. NURBS-Diff: A Differentiable NURBS Layer for Machine Learning CAD Applications. April 2021. April 2021. License; CC BY-NC ...
NURBS-Diff: A Differentiable Programming Module for NURBS
www.sciencedirect.com › article › abs › pii
A gradient descent-based optimization framework using NURBS-Diff for performing CAD operations such as curve or surface fitting and surface offsetting. 4. The ...
Calculus, finite differences. Interpolation, Splines, NURBS. CMSC 828 D. Least Squares, SVD, Pseudoinverse. • Ax=b A is m×n, x is n×1 and b is m×1. • A=USVt ...
A differentiable NURBS layer is proposed for evaluating the curve or surface given a set of NURBS parameters and its utility in deep learning applications ...
Comparing NURBS and Bezier representations, optimized direct evaluation with approximated normal vectors computation is more efficient than all. Bezier ...