![]() Particularly, various convolutional neural network (CNN) based in-loop filters have been proposed to further alleviate coding artifacts and improve coding efficiency on top of the traditional in-loop filters. Motivated by the promising advances of deep-learning based image/video processing, such as super resolution and image denoising, learning based techniques have also been investigated in the video coding domain. deblocking filter (DBF), sample adaptive offset (SAO) and adaptive loop filter (ALF), etc. To mitigate visual artifacts and improve coding efficiency, some in-loops filters are included and sequentially applied in VVC, e.g. The state-of-the-art video coding standard VVC/H.266, similar to its predecessor HEVC/H.265, still uses a block-based hybrid coding architecture. In recent years, the new emerging video requirements, such as 4k, 8k, virtual reality and immersive 360° videos, keep driving the evolution of video compression standards with better coding efficiency.
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