3 citations · 5 across the 15 of their papers we have counts for
6 papers · 1 filter
SVGDreamer++: Advancing Editability and Diversity in Text-Guided SVG Generation
Ximing Xing, Qian Yu, Chuang Wang +3
Recently, text-guided scalable vector graphics (SVG) synthesis has demonstrated significant potential in domains such as iconography and sketching. However, SVGs generated from exi…
Empowering LLMs to Understand and Generate Complex Vector Graphics
Ximing Xing, Juncheng Hu, Guotao Liang +3
The unprecedented advancements in Large Language Models (LLMs) have profoundly impacted natural language processing but have yet to fully embrace the realm of scalable vector graph…
SVGFusion: A VAE-Diffusion Transformer for Vector Graphic Generation
Ximing Xing, Juncheng Hu, Ziteng Xue +5
Generating high-quality Scalable Vector Graphics (SVGs) from text remains a significant challenge. Existing LLM-based models that generate SVG code as a flat token sequence struggl…
TrackGo: A Flexible and Efficient Method for Controllable Video Generation
Haitao Zhou, Chuang Wang, Rui Nie +4
Recent years have seen substantial progress in diffusion-based controllable video generation. However, achieving precise control in complex scenarios, including fine-grained object…
VectorPainter: Advanced Stylized Vector Graphics Synthesis Using Stroke-Style Priors
Juncheng Hu, Ximing Xing, Jing Zhang +1
We introduce VectorPainter, a novel framework designed for reference-guided text-to-vector-graphics synthesis. Based on our observation that the style of strokes can be an importan…
Data-Free Generalized Zero-Shot Learning
Bowen Tang, Long Yan, Jing Zhang +3
Deep learning models have the ability to extract rich knowledge from large-scale datasets. However, the sharing of data has become increasingly challenging due to concerns regardin…