Combining Progressive Rethinking and Collaborative Learning: A Deep Framework for In-Loop Filtering

16 Jan 2020Dezhao WangSifeng XiaWenhan YangJiaying Liu

In this paper, we aim to address two critical issues in deep-learning based in-loop filter of modern codecs: 1) how to model spatial and temporal redundancies more effectively in the coding scenario; 2) what kinds of side information (side-info) can be inferred from the codecs to benefit in-loop filter models and how this side-info is injected. For the first issue, we design a deep network with both progressive rethinking and collaborative learning mechanisms to improve quality of the reconstructed intra-frames and inter-frames, respectively... (read more)

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