论文标题
夹子：夹子引导的拼贴画和摄影
CLIP-CLOP: CLIP-Guided Collage and Photomontage
论文作者
论文摘要
大规模神经网络的毫无疑问的神秘感，例如剪辑双图像和文本编码器，普遍会自动生成艺术。越来越复杂的发电机增强了艺术品的现实主义和视觉外观，并促进了工程的创造性促进文体表达。在艺术家理想的指导下，我们设计了一个基于梯度的发电机来生产拼贴。它要求人类艺术家策划图像贴片的库，并描述（提示）整个图像组成，并可以选择在世代期间手动调整贴片的位置，从而使人类能够重新获得对过程的控制并获得更大的创作自由。我们探索高分辨率拼贴的美学潜力，并提供开源的Google Colab作为艺术工具。
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.
