TY - GEN
T1 - Convolution Neural Network based Video Coding Technique using Reference Video Synthesis
AU - Lee, Jung Kyung
AU - Kim, Nayoung
AU - Cho, Seunghyun
AU - Kang, Je Won
N1 - Funding Information:
ACKNOWLEDGMENT This work was supported by Institute for Information and communications Technology Promotion(IITP) grant funded by the Korea government(MSIP) (2017-0-00072, Development of Audio/Video Coding and Light Field Media Fundamental Technologies for Ultra Realistic Tera-media )
Publisher Copyright:
© 2018 APSIPA organization.
PY - 2019/3/4
Y1 - 2019/3/4
N2 - In this paper, we propose a novel video coding technique that uses a virtual reference (VR) video frame, synthesized by a convolution neural network (CNN) for an inter-coding. Specifically, an encoder generates a VR frame from a video interpolation CNN (VI-CNN) using two reconstructed pictures, i.e., one from the forward reference frames and the other from the backward reference frames. The VR frame is included into the reference picture lists to exploit further temporal correlation in motion estimation and compensation. It is demonstrated by the experimental results that the proposed technique shows about 1.4% BD-rate reductions over the HEVC reference test model (HM 16.9) as an anchor in a Random Access (RA) coding scenario.
AB - In this paper, we propose a novel video coding technique that uses a virtual reference (VR) video frame, synthesized by a convolution neural network (CNN) for an inter-coding. Specifically, an encoder generates a VR frame from a video interpolation CNN (VI-CNN) using two reconstructed pictures, i.e., one from the forward reference frames and the other from the backward reference frames. The VR frame is included into the reference picture lists to exploit further temporal correlation in motion estimation and compensation. It is demonstrated by the experimental results that the proposed technique shows about 1.4% BD-rate reductions over the HEVC reference test model (HM 16.9) as an anchor in a Random Access (RA) coding scenario.
UR - http://www.scopus.com/inward/record.url?scp=85063507345&partnerID=8YFLogxK
U2 - 10.23919/APSIPA.2018.8659611
DO - 10.23919/APSIPA.2018.8659611
M3 - Conference contribution
AN - SCOPUS:85063507345
T3 - 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
SP - 505
EP - 508
BT - 2018 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2018 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 November 2018 through 15 November 2018
ER -