Imagen 3
Published on Aug 14
·
Submitted by
akhaliq
on Aug 14
#2 Paper of the day
Authors:
Imagen-Team-Google
,
Jason Baldridge
,
Jakob Bauer
,
Mukul Bhutani
,
Nicole Brichtova
,
Andrew Bunner
,
Kelvin Chan
,
Yichang Chen
,
Sander Dieleman
,
Yuqing Du
,
Zach Eaton-Rosen
,
Hongliang Fei
,
Nando de Freitas
,
Yilin Gao
,
Evgeny Gladchenko
,
Sergio Gómez Colmenarejo
,
Mandy Guo
,
Alex Haig
,
Will Hawkins
,
Hexiang Hu
,
Huilian Huang
,
Tobenna Peter Igwe
+229 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.
Published on Aug 14
·
Submitted by
akhaliq
on Aug 14
#2 Paper of the day
Authors:
Imagen-Team-Google
,
Jason Baldridge
,
Jakob Bauer
,
Mukul Bhutani
,
Nicole Brichtova
,
Andrew Bunner
,
Kelvin Chan
,
Yichang Chen
,
Sander Dieleman
,
Yuqing Du
,
Zach Eaton-Rosen
,
Hongliang Fei
,
Nando de Freitas
,
Yilin Gao
,
Evgeny Gladchenko
,
Sergio Gómez Colmenarejo
,
Mandy Guo
,
Alex Haig
,
Will Hawkins
,
Hexiang Hu
,
Huilian Huang
,
Tobenna Peter Igwe
+229 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.