VVC Encoding Speed Survey: Best QTMTT Acceleration Methods Revealed
Five years of VTM evolution benchmarked to find the fastest partitioning heuristics...
The Versatile Video Coding (VVC) standard, released in 2020, delivers 40-50% bitrate savings over HEVC at equivalent visual quality. However, this efficiency comes at a steep cost: encoding complexity increased dramatically due to the new Quad Tree Multi Type Tree (QTMTT) partitioning structure. The QTMTT allows more flexible block splits, but the search space grows combinatorially, making real-time encoding challenging. In a new arXiv survey and evaluation, researchers M.E.A. Kherchouche and colleagues systematically analyze acceleration techniques designed to reduce this partitioning complexity.
The study tracks how these techniques have evolved alongside successive versions of the VVC Test Model (VTM), the reference software. It examines adaptations to internal changes such as updated heuristics and fast decision algorithms. The authors highlight the difficulty of improving the speed-versus-compression trade-off when testing across diverse VTM configurations and multiple software versions. This comprehensive evaluation provides a roadmap for developers looking to deploy VVC encoders in latency-sensitive applications, such as live streaming or cloud transcoding, without degrading video quality.
- VVC achieves 40-50% bitrate savings over HEVC but at the cost of significantly higher encoding complexity due to QTMTT partitioning.
- The survey evaluates acceleration techniques across multiple VTM versions, tracking how heuristics evolved from VTM 1.0 to VTM 10.0.
- Findings help engineers balance encoding speed and compression efficiency, critical for real-time VVC deployment.
Why It Matters
Guidance for video engineers to accelerate VVC encoding without sacrificing compression, enabling faster live transcoding and streaming.