Invention Grant
- Patent Title: Techniques for generating UV-net representations of 3D CAD objects for machine learning models
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Application No.: US17348295Application Date: 2021-06-15
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Publication No.: US12288013B2Publication Date: 2025-04-29
- Inventor: Pradeep Kumar Jayaraman , Thomas Ryan Davies , Joseph George Lambourne , Nigel Jed Wesley Morris , Aditya Sanghi , Hooman Shayani
- Applicant: AUTODESK, INC.
- Applicant Address: US CA San Francisco
- Assignee: AUTODESK, INC.
- Current Assignee: AUTODESK, INC.
- Current Assignee Address: US CA San Francisco
- Agency: Artegis Law Group, LLP
- Main IPC: G06F30/27
- IPC: G06F30/27 ; G06F30/23 ; G06N20/00 ; G06T17/10
Abstract:
In various embodiments, a parameter domain graph application generates UV-net representations of 3D CAD objects for machine learning models. In operation, the parameter domain graph application generates a graph based on a B-rep of a 3D CAD object. The parameter domain graph application discretizes a parameter domain of a parametric surface associated with the B-rep into a 2D grid. The parameter domain graph application computes at least one feature at a grid point included in the 2D grid based on the parametric surface to generate a 2D UV-grid. Based on the graph and the 2D UV-grid, the parameter domain graph application generates a UV-net representation of the 3D CAD object. Advantageously, generating UV-net representations of 3D CAD objects that are represented using B-reps enables the 3D CAD objects to be processed efficiently using neural networks.
Public/Granted literature
- US20220318466A1 TECHNIQUES FOR GENERATING UV-NET REPRESENTATIONS OF 3D CAD OBJECTS FOR MACHINE LEARNING MODELS Public/Granted day:2022-10-06
Information query
