Hands-On Image Generation with TensorFlow by Soon Yau Cheong
Author:Soon Yau Cheong
Language: eng
Format: epub
Publisher: Packt Publishing Pvt Ltd
Published: 2020-12-23T00:00:00+00:00
Figure 5.6 â Stylized images using neural style transfer
Feel free to change the weights and layers to create the styles that you want. I hope you now have a better understanding of content and style representation, which will come in handy when we explore advanced generative models. Next, we will look at ways to improve the neural style transfer.
Improving style transfer
The research community and industry were excited about neural style transfer and wasted no time in putting it to use. Some set up websites to allow users to upload photos to perform style transfer, while some used that to create merchandise to sell. Then people realized some of the shortcomings of the original neural style transfer and worked to improve it.
One of the biggest limitations is that style transfer takes all the style information, including the color and brush strokes of the entire style image, and transfers it to the whole of the content image. Using the examples that we just did in the previous section, the blueish color from the style image was transferred into both the building and background. Wouldn't it be nice if we had the choice to transfer only the brush stroke but not the color, and just to the preferred regions?
The lead author of neural style transfer and his team produced a new algorithm to address these issues. The following diagram shows the control the algorithm can give and an example of the results:
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