π New Research Alert - CVPR 2024! π π Title: "SVGDreamer: Text-Guided SVG Generation with Diffusion Model" π TL;DR: Given a text prompt, SVGDreamer can generate editable and versatile high-fidelity vector graphics. π 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. π₯ 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/) π Conference: CVPR, Jun 17-21, 2024 | Seattle WA, USA πΊπΈ π Keywords: #SVGDreamer #Text-to-SVG #SVG #Diffusion #CVPR2024