Multi-rate deep semantic image compression with quantized modulated autoencoder

Recently, deep learning has demonstrated impressive performance in image compression. Methods, that achieve and even outperform conventional codecs performances, are continually emerging. However, most of them need to train and deploy separate networks for rate adaptation. This is impractical and ex...

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Bibliographic Details

Published in:	IEEE International Workshop on Multimedia Signal Processing pp. 1 - 6
Main Author:	Sebai, Dorsaf
Format:	Conference Proceeding
Language:	English
Published:	IEEE 06.10.2021
Subjects:	Computational modeling Conditional autoencoder Deep compression Image coding Memory management Quantization (signal) Quantized autoencoder Semantic analysis Semantics Training Variable-rate compression Visualization
ISSN:	2473-3628
Online Access:	Get full text
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