Edify Image: High-Quality Image Generation with Pixel Space Laplacian
  Diffusion Models
Authors: name: NVIDIA; name: Yuval Atzmon; name: Maciej Bala; name: Yogesh Balaji; name: Tiffany Cai; name: Yin Cui; name: Jiaojiao Fan; name: Yunhao Ge; name: Siddharth Gururani; name: Jacob Huffman; name: Ronald Isaac; name: Pooya Jannaty; name: Tero Karras; name: Grace Lam; name: J. P. Lewis; name: Aaron Licata; name: Yen-Chen Lin; name: Ming-Yu Liu; name: Qianli Ma; name: Arun Mallya; name: Ashlee Martino-Tarr; name: Doug Mendez; name: Seungjun Nah; name: Chris Pruett; name: Fitsum Reda; name: Jiaming Song; name: Ting-Chun Wang; name: Fangyin Wei; name: Xiaohui Zeng; name: Yu Zeng; name: Qinsheng Zhang
Published: 2024-11-11 16:58:31

Abstract: We introduce Edify Image, a family of diffusion models capable of generating
photorealistic image content with pixel-perfect accuracy. Edify Image utilizes
cascaded pixel-space diffusion models trained using a novel Laplacian diffusion
process, in which image signals at different frequency bands are attenuated at
varying rates. Edify Image supports a wide range of applications, including
text-to-image synthesis, 4K upsampling, ControlNets, 360 HDR panorama
generation, and finetuning for image customization.