Jiani Tian, Hongtu Ye

(Hangzhou Normal University, School of Fine Arts)

Abstract：

Generative Adversarial Networks (GANs) are one of the iconic innovative products in the field of computer science. In recent years, generative adversarial networks have not only been widely applied in the field of technological production, but have also accelerated their integration into the diverse practices of contemporary art, presenting enormous potential in visual expression. Given the clear spectrum of applications of Generative Adversarial Network (GAN) technology in art, this article will provide a structural perspective to clarify the application of GAN technology in artistic creation, while also attempting to interpret the transformation of technological innovation into new forms of art. This article summarizes the expression of generative adversarial networks in art into three characteristics, analyzes the aesthetic value of related works and creative concepts in sequence, and provides ways to analyze and reflect on their possible problems.

Key Words：

generative adversarial network; visual uncertainty; machine perspective; generate art