[Paper] VFIG: Vectorizing Complex Figures in SVG with Vision-Language Models

Summary

The VFIG paper introduces a method using Vision-Language Models to convert complex raster images (like PNGs or JPEGs) back into Scalable Vector Graphics (SVG) format. This addresses the common problem where original vector source files are lost, leaving only difficult-to-modify raster versions. By automating the reconstruction of these figures, VFIG offers a significant improvement over the current labor-intensive manual process, enhancing editability and scalability for technical illustrations and digital designs.

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