Technologies for AI-Driven Fashion Social Networking Service with E-Commerce

TL;DR

This paper presents AI technologies integrated into a fashion social networking service with e-commerce, enabling users to share outfits, receive style suggestions, and shop related products through deep learning models.

Contribution

It introduces a comprehensive AI-driven platform that combines visual search and recommendation systems for fashion social networking and e-commerce.

Findings

Successful deployment of the iTOO platform

Effective deep learning models for fashion analysis

Enhanced user engagement through AI features

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.