Neural Style Transfer is an optimization technique which is used to take content and style image to create an image that looks like the content image but painted in the style of the style image. In this case, both the content and style loss function contribute to total cost function. Minimizing this total loss function using Adam optimization techniques and VGG-19 model from Pytorch gives an artistic style image that retains both content and style features.
