MFRNet: A New CNN Architecture for Post-Processing and In-loop Filtering

Understand

In this paper, we propose a novel convolutional neural network (CNN) architecture, MFRNet, for post-processing (PP) and in-loop filtering (ILF) in the context of video compression.

• This network consists of four Multi-level Feature review Residual dense Blocks (MFRBs), which are connected using a cascading structure.
• Each MFRB extracts features from multiple convolutional layers using dense connections and a multi-level residual learning structure.
• In order to further improve information flow between these blocks, each of them also reuses high dimensional features from the previous MFRB.