Please use this identifier to cite or link to this item:
PIRA download icon_1.1View/Download Full Text
Title: DeepSCC : deep learning-based fast prediction network for screen content coding
Authors: Kuang, W 
Chan, YL 
Tsang, SH 
Siu, WC 
Issue Date: Jul-2020
Source: IEEE transactions on circuits and systems for video technology, July 2020, v. 30, no. 7, 8764598, p. 1917-1932
Abstract: Screen content coding (SCC) is an extension of high efficiency video coding (HEVC), and it is developed to improve the coding efficiency of screen content videos by adopting two new coding modes: Intra Block Copy (IBC) and Palette (PLT). However, the flexible quadtree-based coding tree unit (CTU) partitioning structure and various mode candidates make the fast algorithms of the SCC extremely challenging. To efficiently reduce the computational complexity of SCC, we propose a deep learning-based fast prediction network DeepSCC that contains two parts: DeepSCC-I and DeepSCC-II. Before feeding to DeepSCC, incoming coding units (CUs) are divided into two categories: dynamic CTUs and stationary CTUs. For dynamic CTUs having different content as their collocated CTUs, DeepSCC-I takes raw sample values as the input to make fast predictions. For stationary CTUs having the same content as their collocated CTUs, DeepSCC-II additionally utilizes the optimal mode maps of the stationary CTU to further reduce the computational complexity. Compared with the HEVC-SCC reference software SCM-8.3, the proposed DeepSCC reduces the encoding time by 48.81% on average with a negligible Bjøntegaard delta bitrate increase of 1.18% under all-intra configuration
Keywords: Screen content coding (SCC)
High efficiency video coding (HEVC)
fast algorithm
Convolutional neural network (CNN)
Deep learning
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE transactions on circuits and systems for video technology 
ISSN: 1051-8215
EISSN: 1558-2205
DOI: 10.1109/TCSVT.2019.2929317
Rights: © 2019 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 W. Kuang, Y. Chan, S. Tsang and W. Siu, "DeepSCC: Deep Learning-Based Fast Prediction Network for Screen Content Coding," in IEEE Transactions on Circuits and Systems for Video Technology, vol. 30, no. 7, pp. 1917-1932, July 2020 is available at
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
2240_Keung_DeepSCC_Deep_Learning.pdfPre-Published version7.72 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Final Accepted Manuscript
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

Last Week
Last month
Citations as of Jun 4, 2023


Citations as of Jun 4, 2023


Citations as of Jun 2, 2023


Citations as of Jun 1, 2023

Google ScholarTM



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