Technologies for AI-Driven Fashion Social Networking Service with E-Commerce
This work addresses the need for innovative fashion services for online consumers, but it is incremental as it applies existing AI methods to a specific domain.
The paper tackled the problem of enhancing fashion social networking services with e-commerce by developing AI models for visual search and recommendation, resulting in the successful launch of the iTOO platform.
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.