DreamFusion: Text-to-3D using 2D Diffusion
51–60 of 208 posts
Re: DreamFusion: Text-to-3D using 2D Diffusion
#52Did 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?
Re: DreamFusion: Text-to-3D using 2D Diffusion
#53It's funny that the authors are 'anonymous' but they have access to Imagen so obviously it's by Google.
Re: DreamFusion: Text-to-3D using 2D Diffusion
#54https://dreamfusion-cdn.ajayj.com/gallery_sept28/crf20/a_DSL...
But if you look closely, the pin looks like it's actually rolling across the dough as the camera orbits.
Re: DreamFusion: Text-to-3D using 2D Diffusion
#55The thing that frightens me is that we are rapidly reaching broad humanity disrupting ML technologies without any of the social or societal frameworks to cope with it.
Re: DreamFusion: Text-to-3D using 2D Diffusion
#56The thing that frightens me is that we are rapidly reaching broad humanity disrupting ML technologies without any of the social or societal frameworks to cope with it.
Stable diffusion has been made available to the public for quite a while now and if anything has disproved a lot of the ungrounded nonsense that made companies like OpenAI censor their generative models.
Re: DreamFusion: Text-to-3D using 2D Diffusion
#57Did 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?
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…
In his Lex Fridman interview, John Carmack makes similar assertions about this prospect for AGI: That it will likely be the clever combination of existing primitives (plus maybe a couple novel new ones) that make the first AGI feasible in just a couple thousand lines of code.
Re: DreamFusion: Text-to-3D using 2D Diffusion
#58Did 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?
It’s called the technological singularity. Pretty fun so far!
Re: DreamFusion: Text-to-3D using 2D Diffusion
#59Earlier 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
Re: DreamFusion: Text-to-3D using 2D Diffusion
#60Did 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?