TryOnDiffusion is a virtual try-on AI tool that generates photorealistic visualizations of garments on different people. It uses a novel diffusion-based architecture with two parallel UNets to preserve garment detail and accurately warp the clothing to match the body pose and shape of the target person. This approach outperforms previous methods in both qualitative and quantitative evaluations, even with challenging inputs like significant body pose and shape differences. While limitations exist such as garment leaking with inaccurate segmentation maps and the representation of identity through clothing-agnostic RGB, the tool demonstrates state-of-the-art performance in virtual try-on technology.
• image generation
• pose estimation
• virtual try-on
• state-of-the-art performance
• diffusion model
• clothing warping
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