公开(公告)号：US20220180650A1

公开(公告)日：2022-06-09

申请号：US17683514

申请日：2022-03-01

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Licheng TANG ,  Jiaming LIU

IPC: G06V30/244 ,  G06V10/774 ,  G06V10/82 ,  G06V10/74

Abstract: A method of generating a font database, and a method of training a neural network model are provided, which relate to a field of artificial intelligence, in particular to a computer vision and deep learning technology. The method of generating the font database includes: determining, by using a trained similarity comparison model, a basic font database most similar to handwriting font data of a target user in a plurality of basic font databases as a candidate font database; and adjusting, by using a trained basic font database model for generating the candidate font database, the handwriting font data of the target user, so as to obtain a target font database for the target user.

公开(公告)号：US20220148239A1

公开(公告)日：2022-05-12

申请号：US17583259

申请日：2022-01-25

Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

Inventor： Jiaming LIU ,  Licheng TANG

IPC: G06T11/20

Abstract: A method for training a font generation model is described below. A source domain sample character and a target domain association character are input into a font generation network to obtain a target domain generation character. The target domain generation character and at least one of a target domain sample character or the target domain association character are input into a loss analysis network to obtain a first loss, and a parameter of the font generation model is adjusted according to the first loss. The source domain sample character and a random vector are input into the font generation network to obtain a random domain generation character. The random domain generation character and a random domain sample character are input into the loss analysis network to obtain a second loss, and the parameter is readjusted according to the second loss.