Cool-chic video: Learned video coding with 800 parameters
CoRR(2024)
摘要
We propose a lightweight learned video codec with 900 multiplications per
decoded pixel and 800 parameters overall. To the best of our knowledge, this is
one of the neural video codecs with the lowest decoding complexity. It is built
upon the overfitted image codec Cool-chic and supplements it with an inter
coding module to leverage the video's temporal redundancies. The proposed model
is able to compress videos using both low-delay and random access
configurations and achieves rate-distortion close to AVC while out-performing
other overfitted codecs such as FFNeRV. The system is made open-source:
orange-opensource.github.io/Cool-Chic.
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