PRODUCT IMAGE GENERATION BASED ON DIFFUSION MODEL

Organization Name

Inventor(s)

PRODUCT IMAGE GENERATION BASED ON DIFFUSION MODEL - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240355019 titled 'PRODUCT IMAGE GENERATION BASED ON DIFFUSION MODEL

The abstract describes a method and system for creating an extended reality try-on experience using a diffusion model to generate artificial images of fashion items on real-world objects.

The system receives an image of a real-world object and a textual description of a fashion item.
It uses a generative machine learning model to create an artificial image of an object wearing the fashion item described.
The system then matches the visual attributes of the artificial fashion item with a real-world product image to replace it in the artificial image.

Potential Applications: - Virtual try-on experiences for online shopping - Augmented reality fashion apps - Virtual fitting rooms in retail stores

Problems Solved: - Enhancing the online shopping experience by allowing customers to virtually try on items before purchasing - Providing a more interactive and engaging way to shop for clothing and accessories

Benefits: - Increased customer engagement and satisfaction - Reduced return rates for online purchases - Improved visualization of how items will look in real life

Commercial Applications: Virtual try-on technology can be used by e-commerce platforms, fashion retailers, and AR/VR developers to enhance the shopping experience and drive sales.

Questions about the technology: 1. How does the system ensure that the artificial fashion item matches the real-world object accurately? 2. What are the potential limitations of using a diffusion model for generating artificial images in extended reality applications?

Original Abstract Submitted

methods and systems are disclosed for generating an extended reality (xr) try-on experience based on an image produced by a diffusion model. the system receives an image depicting a real-world object and generates a prompt comprising a textual description of a fashion item. the system analyzes the image and the textual description of the fashion item using a generative machine learning model to generate an artificial image that depicts an artificial object that resembles the real-world object wearing an artificial fashion item matching the textual description of the fashion item. the system identifies an object comprising a real-world product image that matches visual attributes of the artificial fashion item and replaces the artificial fashion item in the artificial image with the object to generate an output image.