Generative Adversarial Network Algorithms in Art: Machine Vision in Generation of Collage Art

TIN, Lai Man. Generative Adversarial Network Algorithms in Art: Machine Vision in Generation of Collage Art. Online. In Tin, L. (2022). Generative Adversarial Network Algorithms in Art: Machine Vision in Generation of Collage Art. In: Tareq Ahram and Redha Taiar (eds) Human Interaction & Emerging Technologies (IHIET 2022): Artificial Intelligence & Future Applications. AHFE (2022) International Conference. AHFE Open Access, vol 68. AHFE International, USA. http://doi.org/10.54941/ahfe1002778. 2022. Available from: https://dx.doi.org/10.54941/ahfe1002778.

Basic information

Original name

Generative Adversarial Network Algorithms in Art: Machine Vision in Generation of Collage Art

Authors

TIN, Lai Man

Edition

Tin, L. (2022). Generative Adversarial Network Algorithms in Art: Machine Vision in Generation of Collage Art. In: Tareq Ahram and Redha Taiar (eds) Human Interaction & Emerging Technologies (IHIET 2022): Artificial Intelligence & Future Applications. AHFE (2022) International Conference. AHFE Open Access, vol 68. AHFE International, USA. http://doi.org/10.54941/ahfe1002778, 2022

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Other information

Type of outcome

Stať ve sborníku

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

electronic version available online

References:

AHFE Open Access

DOI

http://dx.doi.org/10.54941/ahfe1002778

Keywords in English

Artificial Intelligence, Machine Learning, Generative Adversarial Network, GAN, Art Creation, Collage

Tags

International impact, Reviewed

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Abstract

V originále

The paper proposes artistic and computational approaches to investigate the ability of matching learning to synthesise and manipulate the image dataset into artwork creation. By using the Generative Adversarial Network (GAN), it is observed how the machine algorithms are able to learn artistic styles and manipulate relevant pictures to generate digital artifacts, in particular, the images generated through latent space interpolation. Referring to an artwork of Pablo Picasso, the paper also aims at observing the collages being generated by GAN in order to understand and compare the machine vision with human vision in collage and artwork creation. And finally, to explore the process of seeing through the phenomenology of embodiment, trying to understand how the objects could be visible to us through the machine and artificial intelligence without being "bodily involvement in the world".