VITON: An Image-Based Virtual Try-On Network

Xintong Han, Zuxuan Wu, Zhe Wu, Ruichi Yu, Larry S. Davis; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018, pp. 7543-7552

Abstract


We present an image-based VIirtual Try-On Network (VITON) without using 3D information in any form, which seamlessly transfers a desired clothing item onto the corresponding region of a person using a coarse-to-fine strategy. Conditioned upon a new clothing-agnostic yet descriptive person representation, our framework first generates a coarse synthesized image with the target clothing item overlaid on that same person in the same pose. We further enhance the initial blurry clothing area with a refinement network. The network is trained to learn how much detail to utilize from the target clothing item, and where to apply to the person in order to synthesize a photo-realistic image in which the target item deforms naturally with clear visual patterns. Experiments on our newly collected Zalando dataset demonstrate its promise in the image-based virtual try-on task over state-of-the-art generative models.

Related Material


[pdf] [Supp] [arXiv]
[bibtex]
@InProceedings{Han_2018_CVPR,
author = {Han, Xintong and Wu, Zuxuan and Wu, Zhe and Yu, Ruichi and Davis, Larry S.},
title = {VITON: An Image-Based Virtual Try-On Network},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2018}
}