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eess.IV2025
Bridging the Gap between Gaussian Diffusion Models and Universal Quantization for Image Compression
Lucas Relic, Roberto Azevedo, Yang Zhang +2
Generative neural image compression supports data representation at extremely low bitrate, synthesizing details at the client and consistently producing highly realistic images. By…
eess.IV2024
Lossy Image Compression with Foundation Diffusion Models
Lucas Relic, Roberto Azevedo, Markus Gross +1
Incorporating diffusion models in the image compression domain has the potential to produce realistic and detailed reconstructions, especially at extremely low bitrates. Previous m…