A Switchable Deep Learning Approach for In-Loop Filtering in Video Coding

• Published in: IEEE transactions on circuits and systems for video technology Vol. 30; no. 7; pp. 1871 - 1887
• Main Authors: Ding, Dandan, Kong, Lingyi, Chen, Guangyao, Liu, Zoe, Fang, Yong
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.07.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adaptation models; Artificial neural networks; CNN; Codec; Coding; Correlation; Deep learning; Encoding; enhancement; Feature extraction; Filtration; Frames (data processing); in-loop filter; Machine learning; Structural hierarchy; Training; Video coding

Deep learning provides a great potential for in-loop filtering to improve both coding efficiency and subjective quality in video coding. State-of-the-art work focuses on network structure design and employs a single powerful network to solve all problems. In contrast, this paper proposes a deep lear...