Technologies for AI-Driven Fashion Social Networking Service with E-Commerce
March 11, 2022 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Jinseok Seol, Seongjae Kim, Sungchan Park, Holim Lim, Hyunsoo Na, Eunyoung Park, Dohee Jung, Soyoung Park, Kangwoo Lee, Sang-goo Lee
arXiv ID
2203.10996
Category
cs.IR: Information Retrieval
Cross-listed
cs.AI,
cs.MM
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
The rapid growth of the online fashion market brought demands for innovative fashion services and commerce platforms. With the recent success of deep learning, many applications employ AI technologies such as visual search and recommender systems to provide novel and beneficial services. In this paper, we describe applied technologies for AI-driven fashion social networking service that incorporate fashion e-commerce. In the application, people can share and browse their outfit-of-the-day (OOTD) photos, while AI analyzes them and suggests similar style OOTDs and related products. To this end, we trained deep learning based AI models for fashion and integrated them to build a fashion visual search system and a recommender system for OOTD. With aforementioned technologies, the AI-driven fashion SNS platform, iTOO, has been successfully launched.
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