a510f05a574d4203ef3952973672fe2f-Paper-Conference.pdf

Neural Information Processing Systems 

Scalable Vector Graphics (SVG) have become a cornerstone of modern digital design because of their resolution independence, compact file size, and inherent editability. Widely adopted in professional workflows from UI/UX design to industrial CAD systems, SVG enables precise manipulation of geometric primitives (e.g., Bézier curves, polygons) while maintaining high precision and consistent visual quality across varying resolutions. However, creating high-quality SVG content remains challenging for non-experts, requiring mastery of specialized tools or intricate XML syntax. Existing methods adopt either optimization-based methods or auto-regressive approaches to generate SVG contents. The optimization-based methods [34, 12, 29] iteratively refine the SVG parameters by minimizing the differences between the input image and the raster image created by differentiable vector graphics rasterizers.

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