  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.

Computer Vision and Pattern Recognition;Artificial Intelligence