Conventional versus learning-based video coding benchmarking: Where are we?

Helena Oliveira; João Ascenso; Fernando Pereira

doi:10.1117/12.2626001

30 April 2022 Conventional versus learning-based video coding benchmarking: Where are we?

Helena Oliveira, João Ascenso, Fernando Pereira

Proceedings Volume 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022; 121770T (2022) https://doi.org/10.1117/12.2626001
Event: International Workshop on Advanced Imaging Technology 2022 (IWAIT 2022), 2022, Hong Kong, China

Abstract

Video coding technology and standards have largely shaped the current world in many domains, notably personal communications and entertainment, as demonstrated during recent COVID-19 times. AI-based multimedia tools already have a major impact in many computer vision tasks, even reaching above human performance, and are now arriving to multimedia coding. In this context, this paper offers one of the first extensive benchmarking of deep learning-based video coding solutions regarding the most powerful and optimized conventional video coding standard, the Versatile Video Coding standard, under the solid, meaningful, and extensive JVET common test conditions. This study will allow the video coding research community to know the current status quo in this emerging ‘battle’ between learning-based and conventional video coding solutions and better design future developments.

Citation Download Citation

Helena Oliveira, João Ascenso, and Fernando Pereira "Conventional versus learning-based video coding benchmarking: Where are we?", Proc. SPIE 12177, International Workshop on Advanced Imaging Technology (IWAIT) 2022, 121770T (30 April 2022); https://doi.org/10.1117/12.2626001

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