Empowering LLMs to Understand and Generate Complex Vector Graphics

Official implementation for "Empowering LLMs to Understand and Generate Complex Vector Graphics"

🚀 Stay Tuned: Code Release Coming Soon

Our LLM4SVG can understand and generate vector graphics from textual description. Our LLM4SVG is designed to: (a) Understand the semantics of SVG (Scalable Vector Graphics) source code and directly extract the meanings conveyed by vector images; (b) Generate corresponding structured SVG representations from textual prompts and decode them into SVG source code that accurately reflects the described content. (c) illustrates some SVG examples generated by our method.

📎 Citation

If you use this code for your research, please cite the following work:

@article{xing2024llm4svg,
  title={Empowering LLMs to Understand and Generate Complex Vector Graphics},
  author={Xing, Ximing and Hu, juncheng and Zhang, Liang and Guotao, Jing and Xu, Dong and Yu, Qian},
  journal={arXiv preprint},
  year={2024}
}

©️ Licence

This work is licensed under a MIT License.