  Convolutional Neural Networks have been highly successful in performing a
host of computer vision tasks such as object recognition, object detection,
image segmentation and texture synthesis. In 2015, Gatys et. al [7] show how
the style of a painter can be extracted from an image of the painting and
applied to another normal photograph, thus recreating the photo in the style of
the painter. The method has been successfully applied to a wide range of images
and has since spawned multiple applications and mobile apps. In this paper, the
neural style transfer algorithm is applied to fashion so as to synthesize new
custom clothes. We construct an approach to personalize and generate new custom
clothes based on a users preference and by learning the users fashion choices
from a limited set of clothes from their closet. The approach is evaluated by
analyzing the generated images of clothes and how well they align with the
users fashion style.
