StarVector

What if you could turn any image or text prompt into precise, editable vector graphics with a single AI model?

Automated product research from public website content. No hands-on app test is recorded for this profile. Pricing source and check date are shown below where available.

Research fitSource-based assessment: StarVector is a groundbreaking open-source AI model that redefines vectorization by generating precise SVG code from images and text, making it ideal for technical and iconic graphic conversion.

StarVector reframes vectorization as a code generation task, leveraging a vision-language architecture to understand images and text instructions. It generates complex SVG elements like circles, polygons, text, and paths, transcending limitations of traditional image processing.

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Key Features:

Advanced Multimodal Architecture: Processes both visual and textual information for precise SVG generation.
Unparalleled Complexity Handling: Generates intricate SVG elements including text, complex paths, and various primitives.
Robust Data Foundation: Trained on SVG-Stack, a dataset of over 2 million SVG samples.
Leading-Edge Performance: Significantly outperforms existing methods in text-to-SVG and image-to-SVG tasks.
Open-Source Resource: Fully accessible to the research community with models available on Hugging Face.

Pros

Designers needing to vectorize icons, logos, or technical diagrams from raster images.
Developers looking to integrate high-quality SVG generation into their applications.
Researchers in computer graphics and AI exploring advanced vectorization techniques.

Cons

Not suitable for natural images or illustrations, as explicitly stated.
Requires some coding knowledge to implement and use the models.
Performance metrics are based on DinoScore, which may not perfectly align with all subjective visual quality assessments.

Pricing

freeFree tier

Categories:

Image Generation & Editing Design & Creative Code & Development

Tags:

SVG Vector Graphics Image to Code AI Deep Learning Open Source CVPR 2025

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Quick Decision

Try if: You need a powerful, AI-driven solution for converting specific types of raster images (icons, diagrams, logos) into high-quality, editable SVG code, and you are comfortable with a programmatic approach.

Skip if: You primarily work with natural images or complex artistic illustrations, or you prefer a purely GUI-based vector editing experience without any coding.

Not for: Users needing to vectorize natural images or complex illustrations (not trained for these).; Individuals seeking a simple, drag-and-drop graphic design tool without code interaction.; Those who require real-time, interactive vector editing capabilities.

Trust Signals

Team Size
small

Tech Details

Platforms

api

Integrations

Hugging Face Transformers

AI Model
Vision-Language Model (VLM)

Open Source

Yes

Support

Channels

github_issues

Company

Name
ServiceNow Research, Mila - Quebec AI Institute, ETS, UBC, Apple
Location
Montreal, Vancouver, Cupertino

A collaborative research effort from multiple institutions and companies focused on advancing AI in vector graphics generation.

FAQ

What types of images can StarVector vectorize effectively?

StarVector excels at vectorizing icons, logotypes, technical diagrams, graphs, and charts. It is not designed for natural images or illustrations.

How does StarVector compare to traditional vectorization tools?

StarVector significantly outperforms traditional methods like AutoTrace, Potrace, and VTracer, as well as other AI models, in generating high-quality SVG code, especially for complex shapes and details, by treating vectorization as a code generation task.

Is StarVector open-source and how can I access it?

Yes, StarVector is an open-source resource. You can access its code repository on GitHub and its models (StarVector-8B and StarVector-1B) on Hugging Face.

Use Cases

Designers needing to vectorize icons, logos, or technical diagrams from raster images.
Developers looking to integrate high-quality SVG generation into their applications.
Researchers in computer graphics and AI exploring advanced vectorization techniques.