Style Transfer - Styling Images with Convolutional Neural Networks
Creating Beautiful Image Effects
In today’s article, we are going to create remarkable style transfer effects. In order to do so, we will have to get a deeper understanding of how Convolutional Neural Networks and its layers work. By the end of this article, you will be able to create a style transfer application that is able to apply a new style to an image while still preserving its original content.
Style Transfer
Before we go to our Style Transfer application, let’s clarify what we are striving to achieve.
Let’s define a style transfer as a process of modifying the style of an image while still preserving its content.
Given an input image and a style image, we can compute an output image with the original content but a new style. It was outlined in Leon A. Gatys’ paper, A Neural Algorithm of Artistic Style, which is a great publication, and you should definitely check it out.
Input Image + Style Image -> Output Image (Styled Input)
