ML-Based Retail Innovations: Virtual Fitting, Scanning and Recommendations

Abstract

This paper discusses the increasing use of machine learning (ML) models in the retail industry to improve the shopping experience of customers. The focus is on virtual trial rooms, self-checkout, and personalized recommendations. Virtual trial rooms allow customers to try on clothes virtually, while self-checkout provides a faster and more convenient checkout process. Personalized recommendations based on customers' purchase history and preferences can also improve the overall shopping experience. The paper reviews literature on the use of ML models and mentions advanced models that map clothes correctly to customers' pictures and use geolocation in barcode scanners to avoid long waiting queues.