Neural Painting (Creating art using machine learning)

Zahra Khosravi

I train models on Persian patterns, paintings, motives, texts using machine learning style transfer. I used the models to transfer Persian Art style to world modern artworks.

https://elliekh.wixsite.com/zahra-thesis

Description

I train models on Persian patterns, paintings, motives, texts using machine learning style transfer technique. I used the models to transfer Persian Art style to world modern artworks. I started by training models on my style, then on motives form Persian art and Culture.

Classes

Autonomous Artificial Artists, Thesis

Cats

Yuguang Zhang

“Cats” is a generative arts piece that explores the relationship between AI synthesized digital contents and human beings.

https://www.ygzhang.com/cats.html

Description

This piece is inspired by R. Luke Dubois's Pop Icon: Bowie piece, and the recent advancement in high-resolution AI image synthesis. While AI is now capable of producing images that look exactly like photos taken using a camera, it does not rely on any physicality of the subject of those imageries. In this case, what's the point of doing so? And what does it imply? In search of answers to this question, I found that it could be used as a platform to explore our “hive mind” perception of concepts, ideas, and bias, and to present them in realistically convincing or utterly surreal ways.

In this piece, I chose the combination of human portrait arts and real-life cat photos – two categories that wouldn't normally come across each other – as my subject of synthesis. 5000+ images of human portraits were trained on StyleGAN, with an additional layer of 1000+ cat faces. The results were then used to synthesize semi-human, semi-cat portraits and generate a piece of “cat” music modeled after Beethoven's Sonata No. 8.

This piece was performed at the Cycling '74 Expo on April, 2019, and its part of the my Hivemind series.

Classes

Autonomous Artificial Artists, Machine Learning for the Web