公开(公告)号：US20220058865A1

公开(公告)日：2022-02-24

申请号：US17408258

申请日：2021-08-20

Applicant: DASSAULT SYSTEMES

Inventor： NICOLAS BELTRAND

IPC: G06T17/10 ,  G06F30/12 ,  G06N3/04

Abstract: A computer-implemented method of machine-learning. The method includes obtaining a Variational Auto-encoder architecture for a neural network which is configured to take as an input a 2D sketch and a random variable, and to output a 3D model represented by the 2D sketch. The method of machine-learning also includes teaching the neural network.

公开(公告)号：US20220058866A1

公开(公告)日：2022-02-24

申请号：US17408319

申请日：2021-08-20

Applicant: DASSAULT SYSTEMES

Inventor： NICOLAS BELTRAND

IPC: G06T17/10 ,  G06N3/04

Abstract: A computer-implemented method of machine-learning including obtaining an architecture for a neural network which is configured to take as an input a 2D sketch, and to output a 3D model represented by the 2D sketch. The 3D model is a parameterized 3D model defined by a set of parameters consisting of a first subset of one or more parameters and a second subset of one or more parameters. The neural network is configured to selectively output a value for the set and take as input a value for the first subset from a user and output a value for the second subset. The method of machine-learning also includes teaching the neural network.