In this paper, we propose a novel virtual try-on from unconstrained designs
(ucVTON) task to enable photorealistic synthesis of personalized composite
clothing on input human images. Unlike prior arts constrained by specific input
types, our method allows flexible specification of style (text or image) and
texture (full garment, cropped sections, or texture patches) conditions. To
address the entanglement challenge when using full garment images as
conditions, we develop a two-stage pipeline with explicit disentanglement of
style and texture. In the first stage, we generate a human parsing map
reflecting the desired style conditioned on the input. In the second stage, we
composite textures onto the parsing map areas based on the texture input. To
represent complex and non-stationary textures that have never been achieved in
previous fashion editing works, we first propose extracting hierarchical and
balanced CLIP features and applying position encoding in VTON. Experiments
demonstrate superior synthesis quality and personalization enabled by our
method. The flexible control over style and texture mixing brings virtual
try-on to a new level of user experience for online shopping and fashion
design.

本研究提出了一种创新的虚拟试穿技术，能够在输入人体图像上实现个性化服装的逼真合成。我们的方法具有灵活的样式和纹理条件，并通过明确分离样式和纹理的双阶段流程来解决全服装图像作为条件时的交织挑战。通过提取层次化和平衡的 CLIP 特征以及在 VTON 中应用位置编码，我们首次实现了复杂的非平稳纹理，实验结果表明了我们方法在合成质量和个性化方面的卓越表现。样式和纹理的灵活控制为在线购物和时尚设计提供了新的用户体验水平。