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Creative Generation of 3D Objects with Deep Learning and Innovation Engines

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

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Creative Generation of 3D Objects with Deep Learning and Innovation Engines. / Lehman, Joel Anthony; Risi, Sebastian; Clune, Jeff.

Proceedings of the Seventh International Conference on Computational Creativity: ICCC 2016. Sony CSL Paris, 2016. p. 180-187.

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Harvard

Lehman, JA, Risi, S & Clune, J 2016, Creative Generation of 3D Objects with Deep Learning and Innovation Engines. in Proceedings of the Seventh International Conference on Computational Creativity: ICCC 2016. Sony CSL Paris, pp. 180-187, International Conference on Computational Creativity, Paris, France, 27/06/2016. <http://sebastianrisi.com/wp-content/uploads/lehman_iccc2016.pdf>

APA

Lehman, J. A., Risi, S., & Clune, J. (2016). Creative Generation of 3D Objects with Deep Learning and Innovation Engines. In Proceedings of the Seventh International Conference on Computational Creativity: ICCC 2016 (pp. 180-187). Sony CSL Paris. http://sebastianrisi.com/wp-content/uploads/lehman_iccc2016.pdf

Vancouver

Lehman JA, Risi S, Clune J. Creative Generation of 3D Objects with Deep Learning and Innovation Engines. In Proceedings of the Seventh International Conference on Computational Creativity: ICCC 2016. Sony CSL Paris. 2016. p. 180-187

Author

Lehman, Joel Anthony ; Risi, Sebastian ; Clune, Jeff. / Creative Generation of 3D Objects with Deep Learning and Innovation Engines. Proceedings of the Seventh International Conference on Computational Creativity: ICCC 2016. Sony CSL Paris, 2016. pp. 180-187

Bibtex

@inproceedings{d5ca2ebb25dc495ca167554c51a8b7ea,
title = "Creative Generation of 3D Objects with Deep Learning and Innovation Engines",
abstract = "Advances in supervised learning with deep neural networks have enabled robust classification in many real world domains. An interesting question is if such advances can also be leveraged effectively for computational creativity. One insight is that because evolutionary algorithms are free from strict requirements of mathematical smoothness, they can exploit powerful deep learning representations through arbitrary computational pipelines. In this way, deep networks trained on typical supervised tasks can be used as an ingredient in an evolutionary algorithm driven towards creativity. To highlight such potential, this paper creates novel 3D objects by leveraging feedback from a deep network trained only to recognize 2D images. This idea is testedby extending previous work with Innovation Engines, i.e. a principled combination of deep learning and evolutionary algorithms for computational creativity. The results of this automated process are interesting and recognizable 3D-printable objects, demonstrating the creative potential for combining evolutionary computation and deep learning in this way.",
author = "Lehman, {Joel Anthony} and Sebastian Risi and Jeff Clune",
year = "2016",
month = jun,
day = "30",
language = "English",
isbn = "9782746691551",
pages = "180--187",
booktitle = "Proceedings of the Seventh International Conference on Computational Creativity",
publisher = "Sony CSL Paris",
note = "International Conference on Computational Creativity, ICCC2016 ; Conference date: 27-06-2016 Through 01-07-2016",
url = "http://www.computationalcreativity.net/iccc2016/",

}

RIS

TY - GEN

T1 - Creative Generation of 3D Objects with Deep Learning and Innovation Engines

AU - Lehman, Joel Anthony

AU - Risi, Sebastian

AU - Clune, Jeff

N1 - Conference code: 7

PY - 2016/6/30

Y1 - 2016/6/30

N2 - Advances in supervised learning with deep neural networks have enabled robust classification in many real world domains. An interesting question is if such advances can also be leveraged effectively for computational creativity. One insight is that because evolutionary algorithms are free from strict requirements of mathematical smoothness, they can exploit powerful deep learning representations through arbitrary computational pipelines. In this way, deep networks trained on typical supervised tasks can be used as an ingredient in an evolutionary algorithm driven towards creativity. To highlight such potential, this paper creates novel 3D objects by leveraging feedback from a deep network trained only to recognize 2D images. This idea is testedby extending previous work with Innovation Engines, i.e. a principled combination of deep learning and evolutionary algorithms for computational creativity. The results of this automated process are interesting and recognizable 3D-printable objects, demonstrating the creative potential for combining evolutionary computation and deep learning in this way.

AB - Advances in supervised learning with deep neural networks have enabled robust classification in many real world domains. An interesting question is if such advances can also be leveraged effectively for computational creativity. One insight is that because evolutionary algorithms are free from strict requirements of mathematical smoothness, they can exploit powerful deep learning representations through arbitrary computational pipelines. In this way, deep networks trained on typical supervised tasks can be used as an ingredient in an evolutionary algorithm driven towards creativity. To highlight such potential, this paper creates novel 3D objects by leveraging feedback from a deep network trained only to recognize 2D images. This idea is testedby extending previous work with Innovation Engines, i.e. a principled combination of deep learning and evolutionary algorithms for computational creativity. The results of this automated process are interesting and recognizable 3D-printable objects, demonstrating the creative potential for combining evolutionary computation and deep learning in this way.

M3 - Article in proceedings

SN - 9782746691551

SP - 180

EP - 187

BT - Proceedings of the Seventh International Conference on Computational Creativity

PB - Sony CSL Paris

T2 - International Conference on Computational Creativity

Y2 - 27 June 2016 through 1 July 2016

ER -

ID: 81058618