Papers
arxiv:2408.07009

Imagen 3

Published on Aug 13
· Submitted by akhaliq on Aug 14
#2 Paper of the day
Authors:
,
,
,
,
,
,
,
,
,
,
,
,
,

Abstract

We introduce Imagen 3, a latent diffusion model that generates high quality images from text prompts. We describe our quality and responsibility evaluations. Imagen 3 is preferred over other state-of-the-art (SOTA) models at the time of evaluation. In addition, we discuss issues around safety and representation, as well as methods we used to minimize the potential harm of our models.

Community

Paper submitter

Screen Shot 2024-08-13 at 9.55.34 PM.png

I cannot find any implementation details. I think Imagen 3 is harmful without control. However, I’m sad not to release the details as an engineer.

Google is as always lying and showing off

Unless they publish weights and we can try I say SOTA is FLUX

Here evidence

https://youtu.be/bupRePUOA18?si=abhlVZ-COMp_TMan

no one has seen imagen1 and imagen2. They are just pictures in pdf

·

so true. 0 reason to believe google at this point. hack i dont believe any of their AI claims. so far Gemini was only a joke for me

Total nothingburger of a paper. Bunch of unreplicatable user studies claiming everyone likes Imagen 3 better than other models, and a lot of waffling about safety and fairness. No implementation details, no info about the dataset or training, nothing. Basically just a PR stunt.

This is an automated message from the Librarian Bot. I found the following papers similar to this paper.

The following papers were recommended by the Semantic Scholar API

Please give a thumbs up to this comment if you found it helpful!

If you want recommendations for any Paper on Hugging Face checkout this Space

You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: @librarian-bot recommend

😍😍

Sign up or log in to comment

Models citing this paper 0

No model linking this paper

Cite arxiv.org/abs/2408.07009 in a model README.md to link it from this page.

Datasets citing this paper 1

Spaces citing this paper 0

No Space linking this paper

Cite arxiv.org/abs/2408.07009 in a Space README.md to link it from this page.

Collections including this paper 17