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

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.