Variable Rate Deep Image Compression With a Conditional Autoencoder

ICCV 2019 Yoojin ChoiMostafa El-KhamyJungwon Lee

In this paper, we propose a novel variable-rate learned image compression framework with a conditional autoencoder. Previous learning-based image compression methods mostly require training separate networks for different compression rates so they can yield compressed images of varying quality... (read more)

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