Neural Network Based Inter Prediction for HEVC

HEVC is the latest video coding standard, in which inter prediction plays an important role to reduce the temporal redundancy. The accuracy of inter prediction is limited since only temporal information is used in conventional algorithms. In this paper, we propose a neural network based inter prediction algorithm for HEVC by using the spatial-temporal information. In the proposed algorithm, we first design a neural network architecture consisting of a fully connected network (FCN) and a convolutional neural network (CNN). Then the spatial neighboring pixels and the temporal neighboring pixels are inputted into FCN. The output of FCN and the prediction of current block are inputted into CNN, which will results the more accurate prediction of current block. Experimental results demonstrate that the proposed method can achieve average 1.7% (up to 8.6%) BD-rate reduction in low delay P test condition compared to HM 16.9.