Enhanced style transfer with colorization and super-resolution

Style transfer is a novel and successful technology in the field of computer vision which allow people to create art pieces without training. This research has combined style transfer, colorization, and super-resolution algorithm to create a method to create art pieces from the black-white image as content and sketch art pieces as style with high resolution. This method could significantly lower the demand for art creation and allow people with little artistic skill to create desired artwork. Moreover, this research compares the impact of the different parameters in style transfer and the influence of the colorization in different processing stages resulting that colorizing the content image before style transfer would create a single style image that is more controllable but colorizing the generated image after style transfer would result in a more unpredictable multi-style image which depends on the training dataset of the image and the ratio of the weight in style transfer.