REVOLUTIONIZING FASHION: A GENERATIVE AI APPROACH TO PERSONALIZED APPAREL DESIGN AND CUSTOM FITTING
Keywords:
Generative AI, Personalized Fashion, 3D Body Modeling, Virtual Try-on, Sustainable Apparel Design, Computer Vision, GANAbstract
This article presents an innovative approach to personalized apparel design using generative artificial intelligence (AI), addressing the longstanding challenges of fit, style, and accessibility in the fashion industry. The proposed mobile application leverages advanced computer vision, machine learning algorithms, and 3D modeling techniques to offer a fully customizable design experience. The solution bridges the gap between mass-produced and custom-tailored clothing by capturing precise body measurements, simulating fabric textures, and enabling real-time design customization. The core technologies, including 3D body modeling, style and pattern generation through Generative Adversarial Networks (GANs), and real-time rendering, work synergistically to create accurate digital avatars and photorealistic garment visualizations. This AI-driven approach promises enhanced personalization, cost-effective customization, improved sustainability, and increased accessibility in fashion, potentially transforming the industry's design and manufacturing processes.
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