扩散
计算机科学
移动设备
人机交互
万维网
物理
热力学
作者
Justin Blalock,David Munechika,Harsha Karanth,Alec Helbling,Prateek Mehta,Seongmin Lee,Duen Horng Chau
出处
期刊:Cornell University - arXiv
日期:2024-02-02
标识
DOI:10.48550/arxiv.2402.01877
摘要
The growing digital landscape of fashion e-commerce calls for interactive and user-friendly interfaces for virtually trying on clothes. Traditional try-on methods grapple with challenges in adapting to diverse backgrounds, poses, and subjects. While newer methods, utilizing the recent advances of diffusion models, have achieved higher-quality image generation, the human-centered dimensions of mobile interface delivery and privacy concerns remain largely unexplored. We present Mobile Fitting Room, the first on-device diffusion-based virtual try-on system. To address multiple inter-related technical challenges such as high-quality garment placement and model compression for mobile devices, we present a novel technical pipeline and an interface design that enables privacy preservation and user customization. A usage scenario highlights how our tool can provide a seamless, interactive virtual try-on experience for customers and provide a valuable service for fashion e-commerce businesses.
科研通智能强力驱动
Strongly Powered by AbleSci AI