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SVG Differentiable Rendering: Generating vector graphics using neural networks.

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xingxmΒ 
updated a Space 10 months ago
xingxmΒ 
posted an update 10 months ago
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🌟 New Research Alert - CVPR 2024! 🌟
πŸ“„ Title: "SVGDreamer: Text-Guided SVG Generation with Diffusion Model"
πŸ“ TL;DR: Given a text prompt, SVGDreamer can generate editable and versatile high-fidelity vector graphics.
πŸ“ Description: In this work, the author has introduced SVGDreamer, an innovative model for text-guided vector graphics synthesis. SVGDreamer incorporates two crucial technical designs: semantic-driven image vectorization (SIVE) and vectorized particle-based score distillation (VPSD), which empower our model to generate vector graphics with high editability, superior visual quality, and notable diversity.
πŸ‘₯ Authors: [Ximing Xing](https://ximinng.github.io/), Haitao Zhou, Chuang Wang, [Jing zhang](https://hellojing89.github.io/), [Dong Xu](https://www.cs.hku.hk/index.php/people/academic-staff/dongxu), and [Qian Yu](https://yuqian1023.github.io/)
πŸ“… Conference: CVPR, Jun 17-21, 2024 | Seattle WA, USA πŸ‡ΊπŸ‡Έ
πŸ” Keywords: #SVGDreamer #Text-to-SVG #SVG #Diffusion #CVPR2024

Resources:
πŸ”— arXiv Paper: https://arxiv.org/abs/2312.16476
🌐 Github Page: https://ximinng.github.io/SVGDreamer-project/
πŸ“ Code Repository: https://github.com/ximinng/SVGDreamer
πŸ“œ Blog: https://huggingface.co/blog/xingxm/svgdreamer