CalliffusionV2: Personalized Natural Calligraphy Generation with Flexible Multi-modal Control
October 03, 2024 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Qisheng Liao, Liang Li, Yulang Fei, Gus Xia
arXiv ID
2410.03787
Category
cs.CL: Computation & Language
Cross-listed
cs.AI,
cs.CV,
cs.MM
Citations
2
Venue
arXiv.org
Last Checked
5 months ago
Abstract
In this paper, we introduce CalliffusionV2, a novel system designed to produce natural Chinese calligraphy with flexible multi-modal control. Unlike previous approaches that 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.
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