Diffuse to Choose
Virtual try-on product image restoration model
Product Details
Diffuse to Choose is a diffusion-based image repair model mainly used in virtual try-on scenarios. It is able to preserve the details of reference items when repairing images and is capable of accurate semantic operations. By directly incorporating the detailed features of the reference image into the latent feature map of the main diffusion model, and combining perceptual losses to further preserve the details of the reference items, this model achieves a good balance between fast inference and high-fidelity details.
Main Features
Target Users
Diffuse to Choose is suitable for image restoration tasks in virtual try-on scenarios such as online shopping.
Examples
Fix images in virtual try-on app
Add missing details to product images
Perform semantic operations on images
Quick Access
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