  Virtual try-on attracts increasing research attention as a promising way for
enhancing the user experience for online cloth shopping. Though existing
methods can generate impressive results, users need to provide a well-designed
reference image containing the target fashion clothes that often do not exist.
To support user-friendly fashion customization in full-body portraits, we
propose a multi-modal interactive setting by combining the advantages of both
text and texture for multi-level fashion manipulation. With the carefully
designed fashion editing module and loss functions, FashionTex framework can
semantically control cloth types and local texture patterns without annotated
pairwise training data. We further introduce an ID recovery module to maintain
the identity of input portrait. Extensive experiments have demonstrated the
effectiveness of our proposed pipeline.
