Customers all over the world want to see how the clothes fit them or not
before purchasing. Therefore, customers by nature prefer brick-and-mortar
clothes shopping so they can try on products before purchasing them. But after
the Pandemic of COVID19 many sellers either shifted to online shopping or
closed their fitting rooms which made the shopping process hesitant and
doubtful. The fact that the clothes may not be suitable for their buyers after
purchase led us to think about using new AI technologies to create an online
platform or a virtual fitting room (VFR) in the form of a mobile application
and a deployed model using a webpage that can be embedded later to any online
store where they can try on any number of cloth items without physically trying
them. Besides, it will save much searching time for their needs. Furthermore,
it will reduce the crowding and headache in the physical shops by applying the
same technology using a special type of mirror that will enable customers to
try on faster. On the other hand, from business owners' perspective, this
project will highly increase their online sales, besides, it will save the
quality of the products by avoiding physical trials issues. The main approach
used in this work is applying Generative Adversarial Networks (GANs) combined
with image processing techniques to generate one output image from two input
images which are the person image and the cloth image. This work achieved
results that outperformed the state-of-the-art approaches found in literature.

在 COVID19 大流行病之后，由于许多卖家要么改为在线购物，要么关闭试衣间，顾客对购物过程感到犹豫和不确定，因此，使用新的 AI 技术创建一个在线平台或虚拟试衣间 (VFR) 可以满足顾客试穿产品的需求，从而提高销售量和产品质量。