Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/90507
PIRA download icon_1.1View/Download Full Text
Title: FastSCCNet : fast mode decision in VVC screen content coding via fully convolutional network
Authors: Tsang, SH 
Kwong, NW 
Chan, YL 
Issue Date: 2020
Source: In 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP) : December 1-4, 2020, virtual conference, 2020, 9301885, p. 177-180
Abstract: Screen content coding have been supported recently in Versatile Video Coding (VVC) to improve the coding efficiency of screen content videos by adopting new coding modes which are dedicated to screen content video compression. Two new coding modes called Intra Block Copy (IBC) and Palette (PLT) are introduced. However, the flexible quad-tree plus multi-type tree (QTMT) coding structure for coding unit (CU) partitioning in VVC makes the fast algorithm of the SCC particularly challenging. To efficiently reduce the computational complexity of SCC in VVC, we propose a deep learning based fast prediction network, namely FastSCCNet, where a fully convolutional network (FCN) is designed. CUs are classified into natural content block (NCB) and screen content block (SCB). With the use of FCN, only one shot inference is needed to classify the block types of the current CU and all corresponding sub-CUs. After block classification, different subsets of coding modes are assigned according to the block type, to accelerate the encoding process. Compared with the conventional SCC in VVC, our proposed FastSCCNet reduced the encoding time by 29.88% on average, with negligible bitrate increase under all-intra configuration. To the best of our knowledge, it is the first approach to tackle the computational complexity reduction for SCC in VVC.
Keywords: Screen content coding (SCC)
Versatile video coding (VVC)
Convolutional neural network (CNN)
Fully convolutional network (FCN)
Deep learning
ISBN: 978-1-7281-8068-7 (Electronic)
978-1-7281-8067-0 (USB)
978-1-7281-8069-4 (Print on Demand)
DOI: 10.1109/VCIP49819.2020.9301885
Rights: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
The following publication S. -H. Tsang, N. -W. Kwong and Y. -L. Chan, "FastSCCNet: Fast Mode Decision in VVC Screen Content Coding via Fully Convolutional Network," 2020 IEEE International Conference on Visual Communications and Image Processing (VCIP), 2020, pp. 177-180 is available at https://dx.doi.org/10.1109/VCIP49819.2020.9301885
Appears in Collections:Conference Paper

Files in This Item:
File Description SizeFormat 
2237_FastSCCNet Fast Mode Decision in VVC Screen Content Coding via Fully Convolutional Network.pdfPre-Published version609.02 kBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

60
Last Week
0
Last month
Citations as of Mar 24, 2024

Downloads

75
Citations as of Mar 24, 2024

SCOPUSTM   
Citations

9
Citations as of Mar 28, 2024

WEB OF SCIENCETM
Citations

5
Citations as of Mar 28, 2024

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.