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2. Efficient Context-Aware Lossy Image Compression

Author

Alexander Lytchier, Jan Xu, Dimitrios Kollias, Ciro Cursio, Arsalan Zafar, and Christian Besenbruch

Subjects
Context model, business.industry, Computer science, Computer vision, Context (language use), Data_CODINGANDINFORMATIONTHEORY, Artificial intelligence, Track (rail transport), business, Autoencoder, Pipeline (software), Lossy image compression, Image compression
Abstract

We present an efficient context-aware lossy image compression system to participate in the Low Rate track of the CLIC 2020 Image Compression challenge. Our method is based on an autoencoder pipeline augmented with a nested hyperprior model, a PixelCNN-based context model and an adversarial loss to remove artefacts.

Published
2020
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