CLIP-CLOP: CLIP-Guided Collage and Photomontage

Intech Pub Date : 2022-05-06 DOI:10.48550/arXiv.2205.03146
Piotr Wojciech Mirowski, D. Banarse, Mateusz Malinowski, Simon Osindero, Chrisantha Fernando
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引用次数: 7

Abstract

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.
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CLIP-CLOP:剪辑引导拼贴和蒙太奇
大规模神经网络(如CLIP双图像和文本编码器)的神秘感有增无减,普及了自动生成的艺术。越来越复杂的生成器增强了艺术品的现实性和视觉外观,创造性的提示工程使风格表达成为可能。在环路艺术家理想的指导下,我们设计了一个基于梯度的生成器来制作拼贴画。它要求人类艺术家管理图像补丁库,并描述(用提示)整个图像组成,并选择在生成过程中手动调整补丁的位置,从而允许人类收回对过程的一些控制,并实现更大的创作自由。我们探索高分辨率拼贴画的美学潜力,并提供一个开源的谷歌Colab作为艺术工具。
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