Towards Detailed Characteristic-Preserving Virtual Try-on

Abstract

While virtual try-on has rapidly progressed recently, existing virtual try-on methods still struggle to faithfully represent various details of the clothes when worn. In this paper, we propose a simple yet effective method to better preserve details of the clothing and person by introducing an additional fitting step after geometric warping. This minimal modification enables disentangling representations of the clothing from the wearer, hence we are able to preserve the wearer-agnostic structure and details of the clothing, to fit a garment naturally to a variety of poses and body shapes. Moreover, we propose a novel evaluation framework applicable to any metric, to better reflect the semantics of clothes fitting. From extensive experiments, we empirically verify that the proposed method not only learns to disentangle clothing from the wearer, but also preserves details of the clothing on the try-on results.

Cite

Text

Lee et al. "Towards Detailed Characteristic-Preserving Virtual Try-on." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022. doi:10.1109/CVPRW56347.2022.00244

Markdown

[Lee et al. "Towards Detailed Characteristic-Preserving Virtual Try-on." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022.](https://mlanthology.org/cvprw/2022/lee2022cvprw-detailed/) doi:10.1109/CVPRW56347.2022.00244

BibTeX

@inproceedings{lee2022cvprw-detailed,
  title     = {{Towards Detailed Characteristic-Preserving Virtual Try-on}},
  author    = {Lee, Sangho and Lee, Seoyoung and Lee, Joonseok},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2022},
  pages     = {2235-2239},
  doi       = {10.1109/CVPRW56347.2022.00244},
  url       = {https://mlanthology.org/cvprw/2022/lee2022cvprw-detailed/}
}