Shape Controllable Virtual Try-on for Underwear Models

28 Jul 2021  ·  Xin Gao, Zhenjiang Liu, Zunlei Feng, Chengji Shen, Kairi Ou, Haihong Tang, Mingli Song ·

Image virtual try-on task has abundant applications and has become a hot research topic recently. Existing 2D image-based virtual try-on methods aim to transfer a target clothing image onto a reference person, which has two main disadvantages: cannot control the size and length precisely; unable to accurately estimate the user's figure in the case of users wearing thick clothes, resulting in inaccurate dressing effect. In this paper, we put forward an akin task that aims to dress clothing for underwear models. %, which is also an urgent need in e-commerce scenarios. To solve the above drawbacks, we propose a Shape Controllable Virtual Try-On Network (SC-VTON), where a graph attention network integrates the information of model and clothing to generate the warped clothing image. In addition, the control points are incorporated into SC-VTON for the desired clothing shape. Furthermore, by adding a Splitting Network and a Synthesis Network, we can use clothing/model pair data to help optimize the deformation module and generalize the task to the typical virtual try-on task. Extensive experiments show that the proposed method can achieve accurate shape control. Meanwhile, compared with other methods, our method can generate high-resolution results with detailed textures.

PDF Abstract


Results from the Paper

  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.


No methods listed for this paper. Add relevant methods here