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Low-complexity Overfitted Neural Image Codec

2023-07-24 · Thomas Leguay, Théo Ladune, Pierrick Philippe, Gordon Clare, Félix Henry

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/

📄 PDF Abstract BibTeX arXiv:2307.12706

Code (1)

orange-opensource/cool-chic 공식 구현 pytorch

Tasks

Decoder

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