English

Mobile Fitting Room: On-device Virtual Try-on via Diffusion Models

Human-Computer Interaction 2024-02-06 v1 Artificial Intelligence Machine Learning

Abstract

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.

Keywords

Cite

@article{arxiv.2402.01877,
  title  = {Mobile Fitting Room: On-device Virtual Try-on via Diffusion Models},
  author = {Justin Blalock and David Munechika and Harsha Karanth and Alec Helbling and Pratham Mehta and Seongmin Lee and Duen Horng Chau},
  journal= {arXiv preprint arXiv:2402.01877},
  year   = {2024}
}

Comments

7 pages, 3 figures

R2 v1 2026-06-28T14:36:42.219Z