Neural style transfer
When convolutional neural networks (CNNs) outperformed all other algorithms in the ImageNet image classification competition, people started to realize the potential of it and began exploring it for other computer vision tasks. In the A Neural Algorithm of Artistic Style paper published in 2015 by Gatys et al., they demonstrated the use of CNNs to transfer the artistic style of one image to another, as shown in the following examples:
Figure 5.1 – (A) Content image. (B)-(D) Bottom image is the style image and the bigger pictures are stylized images (Source: Gatys et al., 2015, “A Neural Algorithm of Artistic Style” https://arxiv.org/abs/1508.06576)
Unlike most deep learning trainings that require tons of training data, neural style transfer requires only two images – content and style images. We can use pre-trained CNN such as VGG to transfer the style from the style image to the content image.
As shown...
