The unabated mystique of large-scale neural networks, such as the CLIP dual image-and-text encoder, popularized automatically generated art. Increasingly more sophisticated generators enhanced the artworks' realism and visual appearance, and creative prompt engineering enabled stylistic expression. Guided by an artist-in-the-loop ideal, we design a gradient-based generator to produce collages. It requires the human artist to curate libraries of image patches and to describe (with prompts) the whole image composition, with the option to manually adjust the patches' positions during generation, thereby allowing humans to reclaim some control of the process and achieve greater creative freedom. We explore the aesthetic potentials of high-resolution collages, and provide an open-source Google Colab as an artistic tool.
翻译:大型神经网络,如CLIP的双层图像和文字编码器、普及的自动生成的艺术。 日益尖端的生成器加强了艺术作品的现实主义和视觉外观,以及创造性的迅速工程使得文体表达成为了一种文体。 我们以一流艺术家的理想为指导,设计了一个基于梯度的生成器来制作拼图。 它要求人类艺术家建立图像补丁图书馆,并(以快速的方式)描述整个图像构成,并允许在一代人中手动调整补丁的位置,从而使人类重新恢复对工艺的某些控制并实现更大的创作自由。 我们探索高分辨率拼图的审美潜力,并提供开放源的谷歌科拉布作为艺术工具。