第一:文本驱动时装合成与设计的百万条目数据集

Huang, Zhen, Li, Yihao, Pei, Dong, Zhou, Jiapeng, Ning, Xuliang, Han, Jianlin, Han, Xiaoguang, Chen, Xuejun
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引用次数: 1

摘要

文本驱动的时尚合成和设计是人工智能生成内容(AIGC)的一个非常有价值的部分,它有可能推动传统时尚产业的巨大革命。为了推进文本驱动的时尚合成和设计研究,我们引入了一个新的数据集,该数据集由一百万张高分辨率时尚图像组成,具有丰富的结构化文本(FIRST)描述。在FIRST中,有广泛的服装类别,每个图像配对的文本描述都是在多个层次上组织的。在常用的生成模型上进行的实验表明了FIRST的必要性。我们邀请社区进一步开发更智能的时装合成和设计系统,使时装设计基于我们的数据集更具创造性和想象力。数据集将于近期发布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
FIRST: A Million-Entry Dataset for Text-Driven Fashion Synthesis and Design
Text-driven fashion synthesis and design is an extremely valuable part of artificial intelligence generative content(AIGC), which has the potential to propel a tremendous revolution in the traditional fashion industry. To advance the research on text-driven fashion synthesis and design, we introduce a new dataset comprising a million high-resolution fashion images with rich structured textual(FIRST) descriptions. In the FIRST, there is a wide range of attire categories and each image-paired textual description is organized at multiple hierarchical levels. Experiments on prevalent generative models trained over FISRT show the necessity of FIRST. We invite the community to further develop more intelligent fashion synthesis and design systems that make fashion design more creative and imaginative based on our dataset. The dataset will be released soon.
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