Invention Grant
- Patent Title: Deep generation of user-customized items
-
Application No.: US17192713Application Date: 2021-03-04
-
Publication No.: US11694248B2Publication Date: 2023-07-04
- Inventor: Chen Fang , Zhaowen Wang , Wangcheng Kang , Julian McAuley
- Applicant: Adobe Inc. , The Regents of the University of California
- Applicant Address: US CA San Jose
- Assignee: Adobe Inc.,The Regents of the University of California
- Current Assignee: Adobe Inc.,The Regents of the University of California
- Current Assignee Address: US CA San Jose; US CA Oakland
- Agency: Keller Preece PLLC
- The original application number of the division: US15897856 2018.02.15
- Main IPC: G06Q30/00
- IPC: G06Q30/00 ; G06Q30/0601 ; G06N3/08 ; G06F16/532 ; G06N3/088 ; G06N3/045

Abstract:
The present disclosure relates to a personalized fashion generation system that synthesizes user-customized images using deep learning techniques based on visually-aware user preferences. In particular, the personalized fashion generation system employs an image generative adversarial neural network and a personalized preference network to synthesize new fashion items that are individually customized for a user. Additionally, the personalized fashion generation system can modify existing fashion items to tailor the fashion items to a user's tastes and preferences.
Public/Granted literature
- US20210192594A1 DEEP GENERATION OF USER-CUSTOMIZED ITEMS Public/Granted day:2021-06-24
Information query