FIRST: A Million-Entry Dataset for Text-Driven Fashion Synthesis and
  Design
Zhen Huang Yihao Li Dong Pei Jiapeng Zhou Xuliang Ning Jianlin Han Xiaoguang Han Xuejun Chen
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.