FitDiT

FitDiT is a novel garment perception enhancement technology designed for high-fidelity virtual try-ons.

CommonProductImageVirtual Try-OnImage Processing

FitDiT aims to address issues of low fidelity and robustness in image-based virtual try-ons. By introducing a clothing texture extractor and employing frequency domain learning alongside an expanded relaxed mask strategy, it significantly enhances the fit and detail representation of virtual try-ons. Its main advantages include the ability to generate realistic and detail-rich clothing images, applicable in various scenarios with high practical value and competitiveness. Specific pricing and market positioning have not been clearly established yet.

Utilizes the Diffusion Transformers (DiT) architecture
allocating more parameters and attention to high-resolution features to improve image quality.
Introduces a clothing texture extractor that fine-tunes garment features by evolving clothing priors
allowing for better capture of rich details like stripes
patterns
and texts.
Customizes frequency distance loss for frequency domain learning to enhance high-frequency clothing details.
Employs an expanded relaxed mask strategy to ensure garments fit correctly in length
preventing the generation of clothes that fill the entire masked area during cross-category try-ons.
Surpasses all baseline models in both qualitative and quantitative evaluations

\The target audience primarily consists of fashion designers
e-commerce platforms
fashion bloggers
and consumers interested in virtual try-ons. FitDiT offers realistic fitting experiences that help users better visualize how clothing fits
enhancing both shopping experiences and design efficiency.\

Fashion designers utilize FitDiT for rapid previews of different designs on models
accelerating the design iteration process.
E-commerce platforms integrate FitDiT to allow consumers to virtually try on clothing before making purchases
reducing return rates.
Fashion bloggers use FitDiT to create virtual try-on videos

1. Visit the online demo site or use Huggingface Space.
2. Upload images of clothing and the target person.
3. Select appropriate settings
such as clothing type and fitting area.
4. Click to begin the try-on process and wait for the model to generate results.

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