Understanding and Creating Art with AI: Review and Outlook

@article{Cetinic2021UnderstandingAC,
  title={Understanding and Creating Art with AI: Review and Outlook},
  author={Eva Cetinic and James She},
  journal={ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)},
  year={2021},
  volume={18},
  pages={1 - 22}
}
  • E. CetinicJames She
  • Published 18 February 2021
  • Art
  • ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)
Technologies related to artificial intelligence (AI) have a strong impact on the changes of research and creative practices in visual arts. The growing number of research initiatives and creative applications that emerge in the intersection of AI and art motivates us to examine and discuss the creative and explorative potentials of AI technologies in the context of art. This article provides an integrated review of two facets of AI and art: (1) AI is used for art analysis and employed on… 
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141 References

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DeepArt: Learning Joint Representations of Visual Arts

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Biases in Generative Art: A Causal Look from the Lens of Art History

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