SVGFusion: Scalable Text-to-SVG Generation via Vector Space Diffusion

Ximing Xing, Juncheng Hu, Jing Zhang, Dong Xu, Qian Yu

TL;DR: SVGFusion is a novel Text-to-SVG model that generates high-quality vector graphics by learning continuous latent space representations.

Project | Code

SVGDreamer++: Advancing Editability and Diversity in Text-Guided SVG Generation

Ximing Xing, Qian Yu, Chuang Wang, Haitao Zhou, Jing Zhang, Dong Xu

TL;DR: Upgrade version of SVGDreamer: A new optimization-based Text-to-SVG method

Project | Code

Empowering LLMs to Understand and Generate Complex Vector Graphics

Ximing Xing, Juncheng Hu, Guotao Liang, Jing Zhang, Dong Xu, Qian Yu

TL;DR: LLM4SVG enables LLMs to understand and generate vector graphics using SVG Semantic Tokens.

Project | Code

VectorPainter: Advanced Stylized Vector Graphics Synthesis Using Stroke-Style Priors

Juncheng Hu, Ximing Xing, Jing Zhang, Qian Yu

TL;DR: VectorPainter synthesizes text-guided vector graphics by imitating strokes.

SVGDreamer: Text Guided SVG Generation with Diffusion Model

Ximing Xing, Chuang Wang, Haitao Zhou, Jing Zhang, Dong Xu, Qian Yu

TL;DR: SVGDreamer introduces semantic-driven vectorization (SIVE) and particle-based distillation (VPSD) to generate editable, high-quality SVGs with better shape control and diversity.

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024

Project | Code | Blog

DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models

Ximing Xing, Chuang Wang, Haitao Zhou, Jing Zhang, Qian Yu, Dong Xu

TL;DR: DiffSketcher pioneered the use of diffusion models for text-to-vector sketch generation.

Advances in Neural Information Processing Systems (NeurIPS), 2023

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Inversion-by-Inversion: Exemplar-based Sketch-to-Photo Synthesis via Stochastic Differential Equations without Training

Ximing Xing, Chuang Wang, Haitao Zhou, Zhihao Hu, Chongxuan Li, Dong Xu, Qian Yu

TL;DR: Free training for sketch control image synthesis via Stochastic Differential Equations (SDEs).

Project | Code

A Graph-Based Method for Reasoning About Label Noise

HaiYang Zhang, Ximing Xing, Liang Liu

TL;DR: DualGraph, the first method for label noise processing based on graph neural networks.

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021

Pytorch-SVGRender: A Differentiable Rendering Library for SVG Creation

👥 Main Contributors: Ximing Xing, Juncheng Hu

TL;DR: SVG Differentiable Rendering: Generating vector graphics using neural networks. Support: text-to-SVG, Image-to-SVG, SVG Editing.

🌐 Project | 📁Code | 🤗HuggingFace | 📄Docs