  Intra prediction is an essential component in the image coding. This paper
gives an intra prediction framework completely based on neural network modes
(NM). Each NM can be regarded as a regression from the neighboring reference
blocks to the current coding block. (1) For variable block size, we utilize
different network structures. For small blocks 4x4 and 8x8, fully connected
networks are used, while for large blocks 16x16 and 32x32, convolutional neural
networks are exploited. (2) For each prediction mode, we develop a specific
pre-trained network to boost the regression accuracy. When integrating into
HEVC test model, we can save 3.55%, 3.03% and 3.27% BD-rate for Y, U, V
components compared with the anchor. As far as we know, this is the first work
to explore a fully NM based framework for intra prediction, and we reach a
better coding gain with a lower complexity compared with the previous work.
