GPU Based Motion-Compensated Frame Interpolation Acceleration for Future Video Coding


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.

2018 25th IEEE International Conference on Image Processing (ICIP)
Li Song
Li Song
Professor, IEEE Senior Member

Professor, Doctoral Supervisor, the Deputy Director of the Institute of Image Communication and Network Engineering of Shanghai Jiao Tong University, the Double-Appointed Professor of the Institute of Artificial Intelligence and the Collaborative Innovation Center of Future Media Network, the Deputy Secretary-General of the China Video User Experience Alliance and head of the standards group.