StarVector is a pioneering Foundation Model for Scalable Vector Graphics (SVG) generation that integrates both visual and textual inputs. Designed to address the limitations of traditional image processing algorithms, StarVector excels in complex tasks such as image vectorization and text-conditional SVG generation.

2023年12月17日 · To train StarVector, we create SVG-Stack, a diverse dataset of 2M samples that enables generalization across vectorization tasks and precise use of primitives like ellipses, polygons, and text. We address challenges in SVG evaluation, showing that pixel-based metrics like MSE fail to capture the unique qualities of vector graphics.

2023年12月17日 · Scalable Vector Graphics (SVGs) have become integral in modern image rendering applications due to their infinite scalability in resolution, versatile usability, and editing capabilities. SVGs are particularly popular in the fields of web development and graphic design.

Check out the paper here. Rest of the code is coming soon. title={StarVector: Generating Scalable Vector Graphics Code from Images}, author={Rodriguez, Juan A and Agarwal, Shubham and Laradji, Issam H and Rodriguez, Pau and Vazquez, David and Pal, Christopher and Pedersoli, Marco}, journal={arXiv preprint arXiv:2312.11556}, year={2023}

StarVector represents a significant advance in automatic vector graphics generation. The ability to produce editable SVG code from raster images has broad applications in design, web development, and digital art. The technology shows promise for automating graphic design workflows and improving scalable graphics on the web.

本文介绍了StarVector，这是一个多模态SVG生成模型，有效地集成了代码生成大型语言模型（CodeLLMs）和视觉模型。 我们的方法利用CLIP图像编码器从基于像素的图像中提取视觉表示，然后通过适配器模块将其转换为视觉令牌。 这些视觉令牌被预先添加到SVG令牌嵌入中，StarCoder模型使用下一个令牌预测对序列进行建模，从而有效地学习对齐视觉和代码令牌。 这使得StarVector能够生成准确表示像素图像的不受限制的SVG。 为了评估StarVector的性能， …

We present StarVector, a Multimodal Foundation Model for SVG generation that effectively integrates Code Generation Large Language Models (CodeLLMs) and Vision Models. StarVector can perform image vectorization and text-conditional SVG generation by learning to predict SVG codes from a sequence of visual (CLIP) or textual (LLM) representations.

This dataset contains SVG code examples for training and evaluating SVG models for image vectorization. The dataset contains the following fields: To evaluate your model on this …

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A feature-oriented vector image pyramid that offers multiple levels of abstraction simultaneously is designed, which can be rasterized efficiently using GPU-accelerated subdivision and achieves high visual quality and better supports editing operations than existing representations.