Web: http://arxiv.org/abs/2209.06950

Sept. 16, 2022, 1:13 a.m. | Ruihan Yang, Stephan Mandt

stat.ML updates on arXiv.org arxiv.org

Diffusion models are a new class of generative models that mark a milestone
in high-quality image generation while relying on solid probabilistic
principles. This makes them promising candidate models for neural image
compression. This paper outlines an end-to-end optimized framework based on a
conditional diffusion model for image compression. Besides latent variables
inherent to the diffusion process, the model introduces an additional
per-instance "content" latent variable to condition the denoising process. Upon
decoding, the diffusion process conditionally generates/reconstructs an image …

arxiv compression diffusion diffusion models image

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