deforum-stable-diffusion VS zero123

This looks a fine-tune of the classic zero123 (https://github.com/cvlab-columbia/zero123) I’m excited to check out the quality improvements.

Though 3d model synthesis is one use case, I found the less advertised base reprojection model to be more useful for gamedev at the moment. You can generate a multiview spritesheet from an image, and it’s fast enough for synthesis during a gameplay session. I couldn’t get a good quality/time balance to do the same with the 3d models, and the lack of mesh rigging or animation combined with imperfections in a fully 3d model tends to break the suspension of disbelief compared to what players are used to. I’m this will change as the tech develops and we layer more AI on top (automatic animation synthesis is an active research area).

If you’re interested in this you might also want to check out deforum (https://github.com/deforum-art/deforum-stable-diffusion) which provides even more powerful camera controls on top of stable diffusion designed for full scenes rather than single objects.

2/Deforum – Open source and good at developing trippy videos – I have not used this too much (https://github.com/deforum-art/deforum-stable-diffusion)

Why is StabilityAI releasing what seems to be a clone of Deforum ?

might be deforum (project) (webui extension) or img2img loopback wave (webui extension). it's definitely something with img2img though. that's clear from how it's warping.

Sorry, I missed it, thanks to Deforum: https://github.com/deforum-art/deforum-stable-diffusion

Have you seen Deforum? Kinda sounds like you're about to reinvent it. :)

I'm talking about it https://github.com/deforum-art/deforum-stable-diffusion It is not possible to put in a separate environment.

Someone with resources will have to train Zero123 [1] with this backbone.

[1] https://zero123.cs.columbia.edu/

This looks a fine-tune of the classic zero123 (https://github.com/cvlab-columbia/zero123) I’m excited to check out the quality improvements.

Though 3d model synthesis is one use case, I found the less advertised base reprojection model to be more useful for gamedev at the moment. You can generate a multiview spritesheet from an image, and it’s fast enough for synthesis during a gameplay session. I couldn’t get a good quality/time balance to do the same with the 3d models, and the lack of mesh rigging or animation combined with imperfections in a fully 3d model tends to break the suspension of disbelief compared to what players are used to. I’m this will change as the tech develops and we layer more AI on top (automatic animation synthesis is an active research area).

If you’re interested in this you might also want to check out deforum (https://github.com/deforum-art/deforum-stable-diffusion) which provides even more powerful camera controls on top of stable diffusion designed for full scenes rather than single objects.

As described in the stable-dreamfusion repo for the image to 3D using the zero123 model (you can read more about that in their repo here: https://github.com/cvlab-columbia/zero123) I used the 105000 checkpoint of zero123. It took about an hour to go through their initial NeRF generation and cleanup steps to get the model output.

Until then https://github.com/cvlab-columbia/zero123 was kinda okay, but practical results often left to be desired, from the imprecision of the view angles to the at times fanciful re-imaginations of the source object.

For anyone else who tried to download the weights and got Google Drive throwing a quota error at you, they're working on it: https://github.com/cvlab-columbia/zero123/issues/2