BeautifAI -- A Personalised Occasion-oriented Makeup Recommendation System
This addresses the need for more context-aware and interactive makeup recommendation systems for users in the beauty industry, though it appears incremental by building on existing personalized methods.
The authors tackled the problem of personalized makeup recommendation by incorporating occasion context and user feedback, resulting in a system that provides real-time previews and region-wise recommendations, with efficacy demonstrated through a user study.
With the global metamorphosis of the beauty industry and the rising demand for beauty products worldwide, the need for an efficacious makeup recommendation system has never been more. Despite the significant advancements made towards personalised makeup recommendation, the current research still falls short of incorporating the context of occasion in makeup recommendation and integrating feedback for users. In this work, we propose BeautifAI, a novel makeup recommendation system, delivering personalised occasion-oriented makeup recommendations to users while providing real-time previews and continuous feedback. The proposed work's novel contributions, including the incorporation of occasion context, region-wise makeup recommendation, real-time makeup previews and continuous makeup feedback, set our system apart from the current work in makeup recommendation. We also demonstrate our proposed system's efficacy in providing personalised makeup recommendation by conducting a user study.