Get the latest tech news
NeuralSVG: An Implicit Representation for Text-to-Vector Generation
graphics are essential in design, providing artists with a versatile medium for creating resolution-independent and highly editable visual content. Recent advancements in vision-language and diffusion models have fueled interest in text-to-vector graphics generation.
We show results generated by our method when keeping a varying number of learned shapes in the final rendering. Even with a small number of shapes, our approach effectively captures the coarse structure of the scene. NeuralSVG generates sketches with varying numbers of strokes using a single network, without any modifications to the framework.
Or read this on Hacker News