Deep video prediction network-ased inter-frame coding in HEVC

Jung Kyung Lee, Nayoung Kim, Seunghyun Cho, Je Won Kang

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

In this paper, we propose a novel Convolutional Neural Network (CNN) based video coding technique using a video prediction network (VPN) to support enhanced motion prediction in High Efficiency Video Coding (HEVC). Specifically, we design a CNN VPN to generate a virtual reference frame (VRF), which is synthesized using previously coded frames, to improve coding efficiency. The proposed VPN uses two sub-VPN architectures in cascade to predict the current frame in the same time instance. The VRF is expected to have higher temporal correlation than a conventional reference frame, and, thus it is substituted for a conventional reference frame. The proposed technique is incorporated into the HEVC inter-coding framework. Particularly, the VRF is managed in a HEVC reference picture list, so that each prediction unit (PU) can choose a better prediction signal through Rate-Distortion optimization without any additional side information. Furthermore, we modify the HEVC inter-prediction mechanisms of Advanced Motion Vector Prediction and Merge modes adaptively when the current PU uses the VRF as a reference frame. In this manner, the proposed technique can exploit the PU-wise multi-hypothesis prediction techniques in HEVC. Since the proposed VPN can perform both the video interpolation and extrapolation, it can be used for Random Access (RA) and Low Delay B (LD) coding configurations. It is shown in experimental results that the proposed technique provides -2.9% and -5.7% coding gains, respectively, in RA and LD coding configurations as compared to the HEVC reference software, HM 16.6 version.

Original languageEnglish
Article number9090881
Pages (from-to)95906-95917
Number of pages12
JournalIEEE Access
Volume8
DOIs
StatePublished - 2020

Keywords

  • HEVC
  • VVC
  • Video coding
  • convolutional neural network
  • deep learning
  • inter-prediction
  • video prediction network
  • virtual reference frame

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