Paper Info
Title
GPU Based Motion-Compensated Frame Interpolation Acceleration for Future Video Coding
Abstract
Being developed by Joint Video Exploration Team (JVET), Future Video Coding (FVC) aims at higher resolutions and higher compression performance than the state-of-the-art HEVC standard, undoubtedly at the cost of further computing increases. As an efficient computing platform, Graphics Processing Unit (GPU) is often used to accelerate encoding. But with the adoption of instruction set acceleration in the reference software of FVC, previous methods often become less efficient or even lead to a lower speed. In this paper, based on the comparative analysis of the time consumption between HEVC and FVC, we propose a GPU based acceleration method for the most computation-intensive step - frame interpolation of FVC, where frame caching strategy and a multi-stream mechanism is designed to make the best of GPU resources. Experimental results show that compared with the instruction set accelerated reference software of FVC, our method could achieve average 67.12% speed-up gains on the interpolation module and average 6.35% speed-up gains on overall encoding with exactly the same performance as before.
Year
DOI
Venue
2018
10.1109/ICIP.2018.8451246
2018 25th IEEE International Conference on Image Processing (ICIP)
Keywords
Field
DocType
FVC,Frame Interpolation,GPU
Computer vision,Instruction set,Computer science,Interpolation,Coding (social sciences),Acceleration,Motion interpolation,Artificial intelligence,Graphics processing unit,Reference software,Encoding (memory)
Conference
ISSN
ISBN
Citations 
1522-4880
978-1-4799-7062-9
0
PageRank 
References 
Authors
0.34
6
5
Name
Order
Citations
PageRank
Jianlun Tang100.34
Yan Huang233.03
Rong Xie35934.58
Zhengyi Luo4357.85
Li Song532365.87