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arXiv · 2307.12706

Low-complexity Overfitted Neural Image Codec

Thomas Leguay·Théo Ladune·Pierrick Philippe·Gordon Clare·Félix Henry
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Abstract

We propose a neural image codec at reduced complexity which overfits the decoder parameters to each input image. While autoencoders perform up to a million multiplications per decoded pixel, the proposed approach only requires 2300 multiplications per pixel. Albeit low-complexity, the method rivals autoencoder performance and surpasses HEVC performance under various coding conditions. Additional lightweight modules and an improved training process provide a 14% rate reduction with respect to previous overfitted codecs, while offering a similar complexity. This work is made open-source at https://orange-opensource.github.io/Cool-Chic/

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Thomas Leguay, Théo Ladune, Pierrick Philippe, Gordon Clare, Félix Henry. 2023-07-24. Low-complexity Overfitted Neural Image Codec. https://arxiv.org/abs/2307.12706

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