TryOffDiff
High fidelity clothing reconstruction virtual try on technology based on diffusion model
0
- -High fidelity clothing image reconstruction: extracting standardized images of clothing from a single photo.
- -Detail preservation: Ensure that the shape, texture, and complex patterns of the clothing are accurately captured.
- -Based on diffusion model: using Stable Diffusion technology for clothing image generation.
- -SigLIP visual conditions: Improve the accuracy of clothing reconstruction through visual conditions.
- -Reducing preprocessing and post-processing steps: simplifies the conversion process from raw images to standardized clothing images.
- -Improving the image quality of e-commerce products: suitable for product display in online retail environments.
- -Advancing the evaluation of generative models: providing a new method for assessing the fidelity of reconstruction of generative models.
- -Stimulating high fidelity reconstruction research: providing new directions for future research in the field of clothing image reconstruction.
Product Details
TryOffDiff is a high fidelity clothing reconstruction technique based on diffusion models, used to generate standardized clothing images from a single photo of a wearing individual. This technology is different from traditional virtual try on, as it aims to extract standardized clothing images, which presents unique challenges in capturing clothing shapes, textures, and complex patterns. TryOffDiffusion ensures high fidelity and detail preservation by using Stable Diffusion and SigLIP based visual conditions. The experiment of this technology on the VITON-HD dataset shows that its method is superior to baseline methods based on pose transfer and virtual try on, and requires fewer preprocessing and post-processing steps. TryOffDiff can not only improve the quality of e-commerce product images, but also promote the evaluation of generative models and inspire future work in high fidelity reconstruction.
