CartoonGAN in Web
Background
Generative adversarial network(GAN) has been widely used for tasks like image/audio generation, image to image translation, and 3D model reconstruction. GAN has become a commonly used tool for generating things. It is also a great help for doing style transfer for high-resolution images. Though, the trade-off is that such a model requires a large number of computational resources. Researchers have done a lot of jobs to mitigate the gap between cartoon and real image. And in this paper, we want to bring CartoonGAN[1] to the browser, optimize it, and make applications on top of it.
Motivation
TensorFlow.js makes performing deep learning projects within the browser possible. And the work of CartoonGAN[1] allows us to transfer any cartoon styles we want. Thus, it will be a great combination of web and CartoonGAN so that users can transfer the styles they want on the web.
