IDM-VTONis a novel diffusion model for image-based virtual try-on tasks, which generates virtual try-on images with a high degree of realism and detail by combining high-level semantics of visual coders and UNet networks as well as low-level features. The technique enhances the realism of the generated images by providing detailed textual cues and further improves the fidelity and realism in real world scenarios through customization methods.
IDM-VTON is a state-of-the-art virtual fitting technology that generates high-quality virtual fitting images by combining a visual coder and a UNet model, and can be customized to further improve image consistency and realism.
IDM-VTON Function
Virtual Try-On Image Generation: Generates a virtual image of a user wearing a specific garment based on images of the user and the garment.
Garment detail preservation: Low-level features of the garment are extracted by GarmentNet to ensure that the details of the garment, such as patterns and textures, are accurately reflected in the generated image.
Supports textual cue comprehension: utilizes visual coders and textual cues to enable the model to understand high-level semantic information about garments, such as style, type, etc.
Personalization: Allows users to customize and generate a fitting that better matches their personal characteristics by providing their own images and images of the garment.
Realistic fitting effect: IDM-VTON generates visually realistic fitting images that are not only visually consistent with the garment image, but also naturally adapt to the posture and body shape of the person.
Official website address:https://idm-vton.github.io/