NeuralSVG: An Implicit Representation for Text-to-Vector Generation

I am really impressed with how it generates rough sketches because everything in the design world begins that way.

This is excellent!

I think the utility of generating vectors is far, far greater than all the raster generation that's been a big focus thus far (DALL-E, Midjourney, etc). Those efforts have been incredibly impressive, of course, but raster outputs are so much more difficult to work with. You're forced to "upscale" or "inpaint" the rasters using subsequent generative AI calls to actually iterate towards something useful.

By contrast, generated vectors are inherently scalable and easy to edit. These outputs in particular seem to be low-complexity, with each shape composed of as few points as possible. This is a boon for "human-in-the-loop" editing experiences.

When it comes to generative visuals, creating simplified representations is much harder (and, IMO, more valuable) than creating highly intricate, messy representations.

I am a huge fan of this type of incremental generative approach. Language isn’t precise enough to describe a final product, so generating intermediate steps is very powerful.

I’d also like to see this in music generation. Tools like Suno are cool but I would much rather have something that generates MIDIs and instrument configurations instead.

Maybe this is a good lesson for generative tools. It’s possible to generate something that’s a good starting point. But what people actually want is long tail, so including the capability of precision modification is the difference between a canned demo and a powerful tool.

> Code coming soon

The examples are quite nice but I have no idea how reproducible they are.

I’ve been impressed with even applying sonnet to SVGs for animations. This looks like it could be a lot more powerful.

Fun example: https://gist.github.com/scosman/701275e737331aaab6a2acf74a52...

I’ve always thought that generation of intermediate representations was the way to go. Instead of generating concrete syntax, generate AST. Instead of generating PNG, generate SVG. Instead of generating a succession of images for animation, generate wire frame or rigging plus script.

Once you have your IR, modify and render. Once you have your render, apply a final coat of AI pixie dust.

Maybe generative models will get so powerful that fine-grained control can be achieved through natural language. But until then, this method would have the advantages of controllability, interoperability with existing tools (like Intellisense, image editors), and probably smaller, cheaper models that don’t have to accommodate high dimensional pixel space.

I’m looking forward to seeing what this makes of Simon Willison’s LLM SVG generation test prompt: “Generate an SVG of a pelican riding a bicycle”.

It’s quite amazing the progress we are seeing in AI and it will keep getting better which is somewhat terrifying.

I wonder if you can use an existing svg as a starting point. I would love to use the sketch approach and generate frame-by-frame animations to plot with my pen plotter.

This is very nice.

I has to convert a bitmask to svg and was wishing to skip the intermediatary step so looked around for papers about segmentation models outputting svg and found this one https://arxiv.org/abs/2311.05276

The sketch generation is wild… and apparently comes for free.

This is the kind of image generation I've been waiting for. No more messing around in Inkscape (or at least, less of it) when I need a specific icon.

This opens up lots of opportunities for document authoring tools. Really cool stuff, can't wait to try out the code once it's available.

Claude has been doing a good job generating SVGs compared to its rivals, happy to see new models bringing image generation even further