Adaptive Loop Filter with a CNN-Based Classification | IEEE Conference Publication | IEEE Xplore

Adaptive Loop Filter with a CNN-Based Classification


Abstract:

In this paper, a data-driven generalization of the adaptive loop filter (ALF) of Versatile Video Coding (VVC) is presented. It is shown how the conventional ALF process o...Show More

Abstract:

In this paper, a data-driven generalization of the adaptive loop filter (ALF) of Versatile Video Coding (VVC) is presented. It is shown how the conventional ALF process of classification and FIR filtering can be generalized to define a natural model architecture for convolutional neural network (CNN) based in-loop filters. Experimental results show that over VVC, average bit-rate savings of 3.85%/4.75% and 4.39%/4.33% can be achieved for the all intra and random access configurations in the low- and high-QP settings.
Date of Conference: 16-19 October 2022
Date Added to IEEE Xplore: 18 October 2022
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Conference Location: Bordeaux, France

References

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