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In this paper, we propose a novel virtual try-on from unconstrained designs(ucVTON) task to enable photorealistic synthesis of personalized compositeclothing on input human images. Unlike prior arts constrained by specific inputtypes, our method allows flexible specification of style (text or image) andtexture (full garment, cropped sections, or texture patches) conditions. Toaddress the entanglement challenge when using full garment images asconditions, we develop a two-stage pipeline with explicit disentanglement ofstyle and texture. In the first stage, we generate a human parsing mapreflecting the desired style conditioned on the input. In the second stage, wecomposite textures onto the parsing map areas based on the texture input. Torepresent complex and non-stationary textures that have never been achieved inprevious fashion editing works, we first propose extracting hierarchical andbalanced CLIP features and applying position encoding in VTON. Experimentsdemonstrate superior synthesis quality and personalization enabled by ourmethod. The flexible control over style and texture mixing brings virtualtry-on to a new level of user experience for online shopping and fashiondesign.

PICTURE: PhotorealistIC virtual Try-on from UnconstRained dEsigns