It's funny that the authors are 'anonymous' but they have access to Imagen so obviously it's by Google.
The full author list is on the updated link at: https://dreamfusion3d.github.io/
DreamFusion: Text-to-3D using 2D Diffusion
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Re: DreamFusion: Text-to-3D using 2D Diffusion
#32Unclear to me what is going on, but there’s another URL that lists the authors names. Given it’s possible this change was done for reason, not linking to it, but strikes me as odd it’s still up. Anyone know what’s going on without causing problems for the authors?
Re: DreamFusion: Text-to-3D using 2D Diffusion
#33Did we hit some sort of technical inflection point in the last couple of weeks or is this just coincidence that all of these ML papers around high quality procedural generation are just dropping every other day?
They're AI generated, the singularity already happened but the machines are trying to ease us into it.
Re: DreamFusion: Text-to-3D using 2D Diffusion
#34Anonymously authored research is very ominous.
The full author list is on the updated link at: https://dreamfusion3d.github.io/
Re: DreamFusion: Text-to-3D using 2D Diffusion
#35Unclear to me what is going on, but there’s another URL that lists the authors names. Given it’s possible this change was done for reason, not linking to it, but strikes me as odd it’s still up. Anyone know what’s going on without causing problems for the authors?
This link was from OpenReview which must be anonymous (double blind). The full author list is on the updated link at: https://dreamfusion3d.github.io
Re: DreamFusion: Text-to-3D using 2D Diffusion
#36Earlier quoted context omitted.
From the abstract: “We introduce a loss based on probability density distillation that enables the use of a 2D diffusion model as a prior for optimization of a parametric image generator. Using this loss in a DeepDream-like procedure, we optimize a randomly-initialized 3D model (a Neural Radiance Field, or NeRF) via gradient descent such that its 2D renderings from random angles achieve a low loss.” This seems like b…
> This seems like basically plugging a couple of techniques together that already existed as with a majority of ML research
True (I made such a proposal myself a few hours ago, albeit in vaguer terms). The thing is deployment infrastructure is good enough now that we can just treat it as modular signal flows and experiment a lot without having to engineer a whole pile of custom infrastructure for each impulsive experiment.
Re: DreamFusion: Text-to-3D using 2D Diffusion
#37Did we hit some sort of technical inflection point in the last couple of weeks or is this just coincidence that all of these ML papers around high quality procedural generation are just dropping every other day?
[deleted]
Re: DreamFusion: Text-to-3D using 2D Diffusion
#38Huh, it's a pretty similar technique to what I outlined a couple days ago: https://news.ycombinator.com/item?id=32965139 Although they start with random initialization and a text prompt. It seems to work well. I now see no reason we can't start with image initialization!
"those who say it cannot be done should not interrupt the people doing it"
Re: DreamFusion: Text-to-3D using 2D Diffusion
#39Did we hit some sort of technical inflection point in the last couple of weeks or is this just coincidence that all of these ML papers around high quality procedural generation are just dropping every other day?
Maybe deadline for neurips which is coming up?
Re: DreamFusion: Text-to-3D using 2D Diffusion
#40Amazing! How long then until we get photorealistic AI generated 3D VR games and experiences in the metaverse?
Why the downvote? I wasn't being sarcastic, it was a honest question, I'm really impressed how far this technology has come since GPT-3 2 years ago to DALl-E and Stable Diffusion ro Meta's text to video to this...