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[AAAI2024] FontDiffuser: One-Shot Font Generation via Denoising Diffusion with Multi-Scale Content Aggregation and Style Contrastive Learning

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您好,这个项目真的太牛了,我想要自己训练一下,但是不知道这个项目数据集的那424种字体的选取有什么特别的考虑吗。还是说从公开字库里随机下载的这些字体并没有什么考虑。如果是有特别进行挑选的话,是个什么挑选策略呢

您好,感谢您优秀的论文。文章中提到三个复杂程度的分类细节见附录,论文结尾并未找到附录,请问可以分享下附录的地址吗?非常感谢!

感谢你们的工作!我想用书法数据集来训练一下模型,所以问问模型在毛笔字上的效果如何呢?

I am very interested in your repository. The checkpoint file you have provided seems to be trained primarily on Chinese characters, as certain shapes such as the Korean character 'ㅇ'...

I found that it just generate one character

Hello, how was the SCR_210000 used during the second training process saved? How can I separate the corresponding SCR from the total_model. pth file generated during my training? Looking forward...

Hello, I am very interested in your research after reading your paper. But I have a confusion about the second stage of training. May I ask how to load the...

![image](https://github.com/yeungchenwa/FontDiffuser/assets/39057051/e6d6cf96-aee4-49e3-bcd5-77494badb634)