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JBE, vol. 27, no. 4, pp.477-486, July, 2022
Accurate Prediction of VVC Intra-coded Block using Convolutional Neural Network
Hye-Sun Jeong and Je-Won Kang
C.A E-mail: email@example.com
In this paper, we propose a novel intra-prediction method using convolutional neural network (CNN) to improve a quality of a predicted block in VVC. The proposed algorithm goes through a two-step procedure. First, an input prediction block is generated using one of the VVC intra-prediction modes. Second, the prediction block is further refined through a CNN model, by inputting the prediction block itself and reconstructed reference samples in the boundary. The proposed algorithm outputs a refined block to reduce residual signals and enhance coding efficiency, which is enabled by a CU-level flag. Experimental results demonstrate that the proposed method achieves improved rate-distortion performance as compared a VVC reference software, I.e., VTM version 10.0.
Keyword: Intra Prediction, Convolutional Neural Network, Versatile Video Coding
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