imagen-pytorch VS CogVideo

If google doesnt, someone like lucidrains probably would implement it, just like he did for imagen and muse.

lucidrains/imagen-pytorch: Implementation of Imagen, Google's Text-to-Image Neural Network, in Pytorch (github.com)

Hi Can someone guide me a little, as to how i can use LAION dataset to train my imagen model? like how i can download the data, and in which format it should be fed to https://github.com/lucidrains/imagen-pytorch code?

If we were to put money into training something, I'd hope we use a better model, like Imagen.

I've been messing around with this open-source implementation. You can get a pretty good idea of the model size by just copying the parameters from the paper.

I'm waiting on this implementation/training of imagen: https://github.com/lucidrains/imagen-pytorch

I'm honestly surprised that they trained a StyleGAN. Recently, the Imagen architecture has been show to be both easier in structure, easier to train, and even faster to produce good results. Combined with the "Elucidating" paper by NVIDIA's Tero Karras you can train a 256px Imagen to tolerable quality within an hour on a RTX 3090.

Here's a PyTorch implementation by the LAION people:

https://github.com/lucidrains/imagen-pytorch

And here's 2 images I sampled after training it for some hours, like 2 hours base model + 4 hours upscaler:

https://imgur.com/a/46EZsJo

Additionally two open source demo models [CogVideo[(https://github.com/THUDM/CogVideo) by a groups of cs students a model by [Antonia Antonova](https://antonia.space/text-to-video-generation) and have presented their own innovative methods of generating video from text

The second thing that will happen is the appearance of AI video and audio. Google has shown two programs for video generation, one which is fairly high quality and the other which can make long videos with several scenes. Meta has also demonstrated their own. We've already seen other projects like CogVideo, as well as many others that are currently being worked on. It's likely that these techniques will become so refined that over the next year or two, they'll have a similar boom to image generation programs. And eventually, they'll have a similar application in video editing, once coherence is adequate enough. Select a person's shirt, and it stays that for the remainder of the scene. Change an actor's hairstyle in real time, or add characters that didn't exist into a scene and let the computer figure out the desired level of realism. This'll revolutionize VFX to a degree where making an effects heavy will be less about wrangling complex toolsets and more about making aesthetic choices of style and placement.

Check out https://github.com/THUDM/CogVideo - progress is being made on coherent video generation.

Characters and dialogue are effectively solved, just look at GPT-3.

The entity behind StableDiffusion is also supporting generative music art, so let's see what is coming out of that: https://www.harmonai.org/

We are currently far away from generating a production quality movie with AI, but I don't think it's going to be nearly as long as a lifetime. In my opinion, we'll have high quality AI shorts within the decade.

CogVideo and a CogView web app.

A better comparison to AI music generation would be video generation, which has not improved much since i saw first examples some years ago. The last iteration is stuff like CogVideo and this is only able to generate 4 second videos with mid-strong artifacts.

github: https://github.com/THUDM/CogVideo

GitHub repo.