SAQENet: A Quality Enhancement Network for Compressed Video with Self-attention
Xuan Sun, Pengyu Liu, Kebin Jia, Shanji Chen · 2022
Existing block-based encoding frameworks often use inaccurate quantification and motion compensation techniques, which result in many compression artifacts due to the loss of high-frequency information. In particular, the blurring of content edges and significant compression distortion can negatively impact the subjective video quality given limited coding resources. Hence, there is an urgent need to build a quality enhancement method for improving the quality of the compressed video at the receiving end given the same coding resources.