Developing Creative AI to Generate Sculptural Objects

  • ©ISEA2019: 25th International Symposium on Electronic Art, Songwei Ge, Austin Dill, Eunsu Kang, Chun-Liang Li, Lingyao Zhang, and Barnabs Pczos, Developing Creative AI to Generate Sculptural Objects
  • ©ISEA2019: 25th International Symposium on Electronic Art, Songwei Ge, Austin Dill, Eunsu Kang, Chun-Liang Li, Lingyao Zhang, and Barnabs Pczos, Developing Creative AI to Generate Sculptural Objects
  • ©ISEA2019: 25th International Symposium on Electronic Art, Songwei Ge, Austin Dill, Eunsu Kang, Chun-Liang Li, Lingyao Zhang, and Barnabs Pczos, Developing Creative AI to Generate Sculptural Objects
  • ©ISEA2019: 25th International Symposium on Electronic Art, Songwei Ge, Austin Dill, Eunsu Kang, Chun-Liang Li, Lingyao Zhang, and Barnabs Pczos, Developing Creative AI to Generate Sculptural Objects
  • ©ISEA2019: 25th International Symposium on Electronic Art, Songwei Ge, Austin Dill, Eunsu Kang, Chun-Liang Li, Lingyao Zhang, and Barnabs Pczos, Developing Creative AI to Generate Sculptural Objects

Symposium:


Presentation Title:

  • Developing Creative AI to Generate Sculptural Objects

Presenter(s):



Abstract:

  • We explore the intersection of human and machine creativity by generating sculptural objects through machine learning. This research raises questions about both the technical details of automatic art generation and the interaction between AI and people, as both artists and the audience of art. We introduce two algorithms for generating 3D point clouds and then discuss their actualization as sculpture and incorporation into a holistic art installation. Specifically, the Amalgamated Deep Dream (ADD) algorithm solves the sparsity problem caused by the naive DeepDreaminspired approach and generates creative and printable point clouds. The Partitioned DeepDream (PDD) algorithm further allows us to explore more diverse 3D object creation by combining point cloud clustering algorithms and ADD.

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