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

sagipolaczek.github.io

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

#71

Post by cochlear »

vipshek wrote: post #26

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 use…

I couldn't agree more. I feel that the block-coding and rasterized approaches that are ubiquitous in audio codecs (even the modern "neural" ones) are a dead-end for the fine-grained control that musicians will want. They're just fine for text-to-music interfaces of course.

I'm working on a sparse audio codec that's mostly focused on "natural" sounds at the moment, and uses some (very roughly) physics-based assumptions to promote a sparse representation.

https://blog.cochlea.xyz/sparse-interpretable-audio-codec-pa...

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

#73

Post by airstrike »

lewisjoe wrote: post #64
airstrike wrote: post #12

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.

Curious how this can augment document authoring! Can you toss some ideas?

I just think about how often professionals need placeholder images or doodles in their documents, but cliparts are generally terrible and actually making a nice looking drawing for those purposes is out of scope for business users and immensely time consuming... so this fills a nice gap.

I'm obviously biased as a former "business user" writing a document authoring software!

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

#75

Post by brown_martin »

gwern wrote: post #56
esperent wrote: post #52

Earlier quoted context omitted.

Link to their vector page, since the main page makes them look like yet another AI image generator: https://www.recraft.ai/ai-image-vectorizer The quality does look quite amazing at first glance. How are the vectors to work with? Can you just open them in illustrator and start editing?

No, I actually was referring to their native vector AI image generator, not their vector izer - although the vectorizer was better than any other we found, and that's why we were using it to convert the Midjourney PNG dropcaps into SVGs (The editing quality of the vectorized ones were not great, but it is hard to see how they could be good given their raster-style appearance. I can't speak to the editing quality of t…

I was under the impression that their AI Vector generator generates a PNG and vectorizes under the hood.

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

#76

Post by astrodude »

scosman wrote: post #39

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...

oh, wow. this actually works. I didn't know :) thanks!

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

#77

Post by IanCal »

nojvek wrote: post #49
andy_ppp wrote: post #48

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 asked both Claude and ChatGPT o3 to "generate svg of mainland USA with black outline". Tried various models and they got it hopelessly wrong. Claude does an okay job at "Generate an SVG of a pelican riding a bicycle"

How's this? https://imgur.com/a/aWQ0J49

I might be missing something but at a first pass it looks good. Not from the US though so something may be more obviously wrong to you.

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

#78

Post by strangecasts »

CyberDildonics wrote: post #55

If you can generate an image you can flatten it and if you can flatten it you can cluster it, and if you can cluster the flat sections you can draw vectors around them.

This posterization-vectorization approach is what the Flash "Trace Bitmap" tool implemented (I'm not sure if Animate still has it?), but if your image isn't originally clipart/vector art, it gives the resulting vector art a very early 2000s look...

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

#79

Post by chaosprint »

cochlear wrote: post #71
vipshek wrote: post #26

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 use…

I couldn't agree more. I feel that the block-coding and rasterized approaches that are ubiquitous in audio codecs (even the modern "neural" ones) are a dead-end for the fine-grained control that musicians will want. They're just fine for text-to-music interfaces of course. I'm working on a sparse audio codec that's mostly focused on "natural" sounds at the moment, and uses some (very roughly) physics-based assumption…

itneresting. I'm approaching music generation from another perspective:

https://github.com/chaosprint/RaveForce

RaveForce - An OpenAI Gym style toolkit for music generation experiments.

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

#80

Post by chaosprint »

janalsncm wrote: post #20

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 generat…

good point.

few days ago I was thinking about restarting this project with Glicol

https://github.com/chaosprint/RaveForce

RaveForce - An OpenAI Gym style toolkit for music generation experiments.

Love suno but eventually I need midi or xml or some lossless samples to work with

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