Summary of Calliffusionv2: Personalized Natural Calligraphy Generation with Flexible Multi-modal Control, by Qisheng Liao et al.
CalliffusionV2: Personalized Natural Calligraphy Generation with Flexible Multi-modal Control
by Qisheng Liao, Liang Li, Yulang Fei, Gus Xia
First submitted to arxiv on: 3 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Multimedia (cs.MM)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces CalliffusionV2, a novel system for producing natural Chinese calligraphy with flexible multi-modal control. Unlike previous approaches, which rely solely on image or text inputs and lack fine-grained control, our system leverages both images to guide generations at fine-grained levels and natural language texts to describe the features of generations. CalliffusionV2 excels at creating a broad range of characters and can quickly learn new styles through a few-shot learning approach. It is also capable of generating non-Chinese characters without prior training. Comprehensive tests confirm that our system produces calligraphy that is both stylistically accurate and recognizable by neural network classifiers and human evaluators. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Our paper introduces CalliffusionV2, a system that makes beautiful Chinese writing with the help of pictures and words. It’s different from other systems because it uses both images and text to control what it writes, giving it fine-tuned control. This new system can write many different characters quickly and even learn new styles after seeing just a few examples. It’s so good that it can also write characters from languages other than Chinese without any training beforehand. Overall, our tests show that the calligraphy produced by CalliffusionV2 is both very accurate and easy for computers and people to understand. |
Keywords
» Artificial intelligence » Few shot » Multi modal » Neural network
