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Chroma Intra Prediction with attention-based CNN architectures
[article]
2020
arXiv
pre-print
Neural networks can be used in video coding to improve chroma intra-prediction. In particular, usage of fully-connected networks has enabled better cross-component prediction with respect to traditional linear models. Nonetheless, state-of-the-art architectures tend to disregard the location of individual reference samples in the prediction process. This paper proposes a new neural network architecture for cross-component intra-prediction. The network uses a novel attention module to model
arXiv:2006.15349v1
fatcat:m66ghbjewnbabof33l5swe4rwq