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Stable Video Diffusion

stability.ai

211–220 of 316 posts

Re: Stable Video Diffusion

#211

I'm still puzzled as to how these "non-commercial" model licenses are supposed to be enforceable. Software licenses govern the redistribution of the software , not products produced with it. An image isn't GPL'd because it was produced with GIMP.

A software licence can definitely govern who can use it and what they can do with it.

> An image isn't GPL'd because it was produced with GIMP.

That's because of how the GPL is written, not because of some limitation of software licences.

Re: Stable Video Diffusion

#213

A seemingly off topic question, but with enough compute and optimization, could you eventually simulate “reality”? Like, at this point, what are the technical counters to the assertion that our world is a simulation?

That theory was never meant to be so airtight such that it 'needs' to be refuted.

Re: Stable Video Diffusion

#214

I understand the magnitude of innovation that's going on here. But still feel like we are generating these videos with both hands tied behind our backs. In other words, it's nearly impossible to edit the videos in this constraints. (Imagine trying to edit the blue Jays to get the perfect view). Since videos are rarely consumed raw, what if this becomes a pipeline in Blender instead? (Blender the 3d software). Now the…

What would solve all these issues is full generation of 3D models that we hopefully get a chance to see over the next decade. I’ve been advocating for a solid LiDAR camera on the iPhone so there is a lot of training data for these LLMs.

Re: Stable Video Diffusion

#215

Earlier quoted context omitted.

> sportsball This is not the flex you think it is. You don't have to like sports, but snarking on people who do doesn't make you intellectual, it just makes you come across as a douchebag, no different than a sports fan making fun of "D&D nerds" or something.

This has become a colloquial term for describing all sports, not the insult you're perceiving it to be. Rather than projecting your own hangups and calling people names, try instead assuming that they're not trying to offend you personally and are just using common vernacular.

If only there was an existing way to refer to sports generally! And OP was referring to a specific sport (baseball), not sports generally.

Re: Stable Video Diffusion

#216

In the video towards the bottom of the page, there are two birds (blue jays), but in the background there are two identical buildings (which look a lot like the CN Tower). CN Tower is the main landmark of Toronto, whose baseball team happens to be the Blue Jays. It's located near the main sportsball stadium downtown. I vaguely understand how text-to-image works, and so it makes sense that the vector space for "blue j…

> Has anyone come across a solution where model can iterate (eg, with prompts like "move the bicycle to the left side of the photo")? It feels like we're close.

Nearly all of the available models have this, even the highly commercialized ones like in Adobe Firefly and Canva, it’s called inpainting in most tools.

Re: Stable Video Diffusion

#217
post #142
post #113

Earlier quoted context omitted.

>3D scene file format is no different Not in theory, but the level of complexity is way higher and the amount of data available is much smaller. Compare bitmaps to this: https://fossies.org/linux/blender/doc/blender_file_format/my...

Also the level of fault tolerance... if your pixels are a bit blurry, chances are no one notices at a high enough resolution. If your json is a bit blurry you have problems.

You can do "constrained decoding" on a code model which keeps it grammatically correct.

But we haven't gotten diffusion working well for text/code, so generating long files is a problem.

Re: Stable Video Diffusion

#218

I'm still puzzled as to how these "non-commercial" model licenses are supposed to be enforceable. Software licenses govern the redistribution of the software , not products produced with it. An image isn't GPL'd because it was produced with GIMP.

So, there's a few different things interacting here that are a little confusing. First off, you have copyright law, which grants monopolies on the act of copying to the creators of the original. In order to legally make use of that work you need to either have permission to do so (a license), or you need to own a copy of the work that was made by someone with permission to make and sell copies (a sale). For the purpo…

If a company train the model from scratch, on its own dataset, could the resulting model be used commercially?

Re: Stable Video Diffusion

#219

Earlier quoted context omitted.

As I stated and you selectively omitted, 3D scenes are collections of many arbitrary data structures. Not at all the same as fixed sized arrays representing images.

Text gen, one of the things you contrast 3d to, similarly isn't fixed size (capped in most models, but not fixed .) In fact, the data structures of a 3D scene can be serialized as text, and a properly trained text gen system could generate such a representation directly, though that's probably not the best route to decent text-to-3d.

Text is a standard sized embedding vector that gets passed one at a time to an LLM. All tokens have the same shape. Each token is processed one at a time. All tokens also have a pre defined order. It is very different and vastly simpler.

Serializing 3D models as text is not going to work for negligibly non trivial circumstances.

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