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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Veröffentlicht in:	IEEE International Workshop on Multimedia Signal Processing S. 1 - 6
1. Verfasser:	Sebai, Dorsaf
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 06.10.2021
Schlagworte:	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-Zugang:	Volltext
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