论文标题
时尚和服装的细分任务
Segmentation task for fashion and apparel
论文作者
论文摘要
时装业是全球经济中强大而重要的行业。全球化带来了快速的时尚，快速转移消费者购物偏好，更多的竞争以及在时尚商店和零售商中的丰富性，使时装行业的专业人士更难跟踪人们穿什么时尚物品以及如何结合它们。本文通过使用45,000张具有46种不同服装和服装类别的图像的图像来实施几个深度学习架构来解决此问题。
The Fashion Industry is a strong and important industry in the global economy. Globalization has brought fast fashion, quick shifting consumer shopping preferences, more competition, and abundance in fashion shops and retailers, making it more difficult for professionals in the fashion industry to keep track of what fashion items people wear and how they combine them. This paper solves this problem by implementing several Deep Learning Architectures using the iMaterialist dataset consisting of 45,000 images with 46 different clothing and apparel categories.
