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Virtual Try-On Using Machine Learning in Clothing Sector

 

 

Champa M S1 , Anusha Shetti2 , Nischitha S H3, Priya G4, Vijayakumari H L5

1Assistant Professor, Information Science Engineering, AMC Engineering College, Karnataka, India

 2Student, Dept. of Information Science Engineering, AMC Engineering College, Karnataka, India

 3Student, Dept. of Information Science Engineering, AMC Engineering College, Karnataka, India

 4Student, Dept. of Information Science Engineering, AMC Engineering College, Karnataka, India

5Student, Dept. of Information Science Engineering, AMC Engineering College, Karnataka, India

 

 

Abstract - This paper, AI-powered web portal designed to transform the traditional fashion retail experience by integrating virtual try-on technology and personalized product recommendations. The system allows users to authenticate, specify preferences such as gender and occasion, and receive intelligently created clothing suhhestions. Through VIRTUAL TRY ON, an advanced AI module, users can visualize garments on their own body shape and size, reducing the need for physical try-ons and improving decision-making accuracy. Machine learning algorithms analyze user behavior and continuously refine recommendations, creating a highly personalized shopping experience. Beyond enhancing convenience, the system addresses common industry challenges such as inaccurate size selection, high return rates, and limited personalization. The platform also supports real-time garment rendering, scalable product catalog integration, and improved user engagement through adaptive learning models. By promoting sustainable Virtual Try-On practices, optimizing retail efficiency, and increasing customer confidence, the project offers a forward thinking solution that bridges technology and fashion. Overall, this innovative portal positions itself as a comprehensive, environmentally conscious, and future-ready approach to modern fashion retail.

Key Words: AI-powered fashion portal, Virtual Try-On, Personalized recommendations, User preferences, Body measurement visualization, Machine Learning, Recommendation system.

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