A Temporally Coherent Background Model For Dibr View Synthesis

This paper proposes a new downsampling-based light field video coding (D-LFVC) framework whose success relies on how to design an effective restoration method that can remove artifacts brought by both downsampling and compression. Since light field (LF) video is of high dimensionality data, the restoration methods designed for conventional 2D video are sub-optimal solutions for our D-LFVC. in this regard, we design a new restoration network, named ?LF-QEN,? for our D-LFVC framework. Specifically, the network contains three different feature extractor modules, allowing us to simultaneously exploit information from different kinds of 4D LF representation: spatial, angular, and epipolar image information. Our experimental results show that, compared to compression by HEVC-SCC standard, the proposed framework can obtain not only nearly 50% bitrate savings but also can significantly enhance the quality of decoded LF video.