Abstract
In today's fast-moving world, many people struggle with selecting outfits that reflect their personal style and current trends. Existing fashion recommendation apps typically offer
generic suggestions that don't fully account for individual tastes or real-life contexts. This project addresses these challenges by providing an interactive, AI-driven mobile application that transforms outfit selection into an engaging, conversational experience.
By integrating multi-modal inputs—including text queries, image uploads, and location data—“ChicMate” leverages state-of-the-art deep learning techniques for visual feature
extraction and natural language processing. This integration allows the app to generate personalized outfit recommendations that are both context-aware and visually supported,
displaying not only descriptive feedback but also images of the suggested items.
Overall, ChicMate offers a practical solution to everyday styling dilemmas, making wardrobe management more personal and enjoyable.