StarVector is a foundation model for generating scalable vector graphics (SVG) from images and text instructions. It uses a Vision-Language Modeling architecture to vectorize a range of visual inputs, including icons, logotypes, and technical diagrams, by integrating visual and textual information.
Features
Advanced Multimodal Architecture
Processes both visual and textual information with precision, enabling sophisticated image vectorization and text-guided SVG creation that captures fine details and structural relationships.
Unparalleled Complexity Handling
Recognizes and generates intricate SVG elements, including complex paths and various primitives, directly from images, maintaining professional quality.
Robust Data Foundation
Built on SVG-Stack, a meticulously curated dataset of over 2 million SVG samples, ensuring consistent performance across various graphic styles.
Leading-Edge Performance
Significantly outperforms existing methods in text-to-SVG and image-to-SVG generation tasks, providing high-quality vectorization while being open source.