Artistic style transfer using deep learning
P. Mounica, A. Nagaratnam, Mohammad Farzana, Kundeti Muralidhar · International journal of advance research, ideas and innovations in technology · 2019
In this paper, we are implementing the style transfer using convolutional neural networks. The style transfer means to extract the style and texture of a style image and applying it to the extracted content of another image. Our work is based on the work proposed by LA Gatys. We use a pre-trained model, VGG 16 for our work. This work includes the content reconstruction and style reconstruction from the content image and style image respectively. Now the style and content are merged in a manner that the features of content and style are retained.