Two distinct tasks - generating photorealistic pictures from given text
prompts and transferring the style of a painting to a real image to make it
appear as though it were done by an artist, have been addressed many times, and
several approaches have been proposed to accomplish them. However, the
intersection of these two, i.e., generating paintings from a given caption, is
a relatively unexplored area with little data available. In this paper, we have
explored two distinct strategies and have integrated them together. First
strategy is to generate photorealistic images and then apply style transfer and
the second strategy is to train an image generation model on real images with
captions and then fine-tune it on captioned paintings later. These two models
are evaluated using different metrics as well as a user study is conducted to
get human feedback on the produced results.

本文针对从文字获取真实风格的图片和使用图片风格实现真实画作两个任务，探索了两种策略，即生成真实图片并应用风格转移和训练图像生成模型，然后在后期精调含有标题的画作。最后评估了这两种模型，并进行了用户研究以获取反馈。