Whilst there are perhaps only a few scientific methods, there seem to be almost as many artistic methods as there are artists. Artistic processes appear to inhabit the highest order of open-endedness. To begin to understand some of the processes of art making it is helpful to try to automate them even partially. In this paper, a novel algorithm for producing generative art is described which allows a user to input a text string, and which in a creative response to this string, outputs an image which interprets that string. It does so by evolving images using a hierarchical neural Lindenmeyer system, and evaluating these images along the way using an image text dual encoder trained on billions of images and their associated text from the internet. In doing so we have access to and control over an instance of an artistic process, allowing analysis of which aspects of the artistic process become the task of the algorithm, and which elements remain the responsibility of the artist.

中文翻译：

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使用神经视觉语法和双重编码器的生成艺术

虽然可能只有少数几种科学方法，但似乎几乎有多少种艺术家采用了艺术方法。艺术过程似乎占据了开放性的最高顺序。要开始理解某些艺术制作过程，尝试使其部分自动化会很有帮助。在本文中，描述了一种用于产生生成技术的新颖算法，该算法允许用户输入文本字符串，并且在对该字符串的创造性响应中，输出解释该字符串的图像。它通过使用分层神经Lindenmeyer系统演化图像，并使用在互联网上对数十亿图像及其相关文本进行训练的图像文本双重编码器，一路评估这些图像。这样，我们就可以访问和控制艺术过程的实例，