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Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models

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arxiv 2411.07126 v1 pith:OTR3LDGX submitted 2024-11-11 cs.CV cs.LG

Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models

NVIDIA: Yuval Atzmon , Maciej Bala , Yogesh Balaji , Tiffany Cai , Yin Cui , Jiaojiao Fan , Yunhao Ge , Siddharth Gururani
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Jacob Huffman Ronald Isaac Pooya Jannaty Tero Karras Grace Lam J. P. Lewis Aaron Licata Yen-Chen Lin Ming-Yu Liu Qianli Ma Arun Mallya Ashlee Martino-Tarr Doug Mendez Seungjun Nah Chris Pruett Fitsum Reda Jiaming Song Ting-Chun Wang Fangyin Wei Xiaohui Zeng Yu Zeng Qinsheng Zhang
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classification cs.CV cs.LG
keywords imagediffusionedifymodelsgenerationlaplacianaccuracyapplications
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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Cited by 7 Pith papers

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