服装
计算机科学
图像(数学)
任务(项目管理)
代表(政治)
人工智能
计算机视觉
生成模型
人机交互
生成语法
工程类
历史
考古
法学
系统工程
政治
政治学
作者
Xintong Han,Zuxuan Wu,Zhe Wu,Ruichi Yu,Larry S. Davis
标识
DOI:10.1109/cvpr.2018.00787
摘要
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.
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