A learning-based low complexity in-loop filter for video coding

Chao Liu, Heming Sun, Jiro Katto, Xiaoyang Zeng, Yibo Fan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the continuous development of mobile devices, it becomes possible for people to demand higher definition videos. To alleviate the pressure of deploying the video codec in mobile multimedia, a learning-based low complexity in-loop filter is proposed in this paper. Depthwise separable convolution is combined with batch normalization to construct this model. To enhance its performance, the knowledge from a pre-trained teacher model is transferred to it. However, the over-smoothing problem in the inter frames caused by double enhancing effect remains. To solve this, a Wiener-based filtering algorithm that tries to restore the distortion from the learned residuals is designed and introduces an adequate filtering effect. The experimental results show that our proposed methods achieve considerable BD-rate reduction than HEVC anchor. Compared with the previous state-of-the-art work VR-CNN, our model achieves 1.65% extra BD-rate reduction, 79.1% decrease in FLOPs, 25% decrease in encoding complexity, and 70% decoding complexity decrease.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728114859
DOIs
Publication statusPublished - 2020 Jul
Event2020 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2020 - London, United Kingdom
Duration: 2020 Jul 62020 Jul 10

Publication series

Name2020 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2020

Conference

Conference2020 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2020
CountryUnited Kingdom
CityLondon
Period20/7/620/7/10

Keywords

  • CNN
  • HEVC
  • In-loop filter
  • Inter
  • Knowledge transfer

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Media Technology

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