Zheng-Chong/CatVTON

[ICLR 2025] CatVTON is a simple and efficient virtual try-on diffusion model with 1) Lightweight Network (899.06M parameters totally), 2) Parameter-Efficient Training (49.57M parameters trainable) and 3) Simplified Inference (< 8G VRAM for 1024X768 resolution).

53
/ 100
Established

This project helps online retailers and fashion brands create photorealistic images of clothing on models without physical photoshoots. You provide an image of a person and an image of a garment, and it generates a new image showing the person "wearing" that garment. This is ideal for e-commerce, virtual try-on experiences, or digital fashion design, allowing marketers and product managers to quickly visualize new collections.

1,615 stars.

Use this if you need to generate high-quality images of clothing on diverse models quickly and cost-effectively, reducing the need for traditional photography.

Not ideal if you require real-time, interactive video try-on experiences, though a future version may offer this capability.

e-commerce fashion-marketing product-visualization digital-garment-design virtual-try-on
No Package No Dependents
Maintenance 6 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 21 / 25

How are scores calculated?

Stars

1,615

Forks

207

Language

Python

License

Category

virtual-try-on

Last pushed

Dec 16, 2025

Commits (30d)

0

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