Cool-Chic: Perceptually Tuned Low Complexity Overfitted Image Coder

Théo Ladune, Pierrick Philippe,Gordon Clare, Félix Henry, Thomas Leguay

2024 Data Compression Conference (DCC)(2024)

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摘要
This paper summarises the design of the Cool-Chic candidate for the Challenge on Learned Image Compression. This candidate attempts to demonstrate that neural coding methods can lead to low complexity and lightweight image decoders while still offering competitive performance. The approach is based on the already published overfitted lightweight neural networks Cool-Chic, further adapted to the human subjective viewing targeted in this challenge.
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关键词
Image Compression,Decoding,Multilayer Perceptron,Latent Representation
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