ArtGAN: Artwork synthesis with conditional categorical GANs

@article{Tan2017ArtGANAS,
  title={ArtGAN: Artwork synthesis with conditional categorical GANs},
  author={Wei Ren Tan and Chee Seng Chan and Hern{\'a}n E. Aguirre and Kiyoshi Tanaka},
  journal={2017 IEEE International Conference on Image Processing (ICIP)},
  year={2017},
  pages={3760-3764}
}
This paper proposes an extension to the Generative Adversarial Networks (GANs), namely as ArtGAN to synthetically generate more challenging and complex images such as artwork that have abstract characteristics. This is in contrast to most of the current solutions that focused on generating natural images such as room interiors, birds, flowers and faces. The key innovation of our work is to allow back-propagation of the loss function w.r.t. the labels (randomly assigned to each generated images… 

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