2D Virtual Try-On
Our technology transforms flat images into personalized styling experiences—no 3D scans or special hardware required
A customized Stable Diffusion framework enables garment rendering by conditioning on the human body image, segmented clothing, and structural cues. The system uses a U-Net-based architecture to generate realistic try-on results, predicting how garments should appear based on body shape, pose, and garment texture.
Inputs include a person’s image (with parsed body parts and segmentation masks), a standalone garment image, and a noise map. These are concatenated and passed through a diffusion process that refines the output step-by-step into a photorealistic try-on result—accurate in fit, scale, and lighting.
The 2D approach allows for rapid processing, natural garment alignment, and high scalability without the complexity of 3D modeling or depth sensors.
How It Works
Upload or select clothes from your wardrobe
Our system renders garments onto your avatar in seconds
Mix, match, and preview complete outfits with realistic proportions
Plan and organize your style without physically trying anything on
