Variational image compression with a scale hyperprior

ICLR, Volume abs/1802.01436, 2018.

Cited by: 188|Bibtex|Views88
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

We describe an end-to-end trainable model for image compression based on variational autoencoders. The model incorporates a hyperprior to effectively capture spatial dependencies in the latent representation. This hyperprior relates to side information, a concept universal to virtually all modern image codecs, but largely unexplored in im...More

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