The demand for efficient multi-rate encoding techniques has surged with the increasing prevalence of ultra-high-definition (UHD) video content, particularly in adaptive streaming scenarios where a single video must be encoded at multiple bitrates to accommodate diverse network conditions. While Versatile Video Coding (VVC) significantly improves compression efficiency, it introduces considerable computational complexity, making multi-rate encoding a resource-intensive task. This paper examines coding unit (CU) partitioning strategies to minimize redundant computations in VVC while preserving high video quality. We propose single- and double-bound approaches, leveraging CU depth constraints from reference encodes to guide dependent encodes across multiple QPs. These methods are evaluated using VVenC with various presets, demonstrating consistent improvements in encoding efficiency. Our methods achieve up to 11.69 % reduction in encoding time with minimal bitrate overhead (<0.6 %). Comparative Pareto-front (PF) analysis highlights the superior performance of multi-rate approaches over existing configurations. These findings validate the potential of CU-guided strategies for scalable multi-rate encoding in adaptive streaming.
@article{arxiv.2510.14645,
title = {Block-Partitioning Strategies for Accelerated Multi-rate Encoding in Adaptive VVC Streaming},
author = {Vignesh V Menon and Adam Wieckowski and Yiquin Liu and Benjamin Bross and Detlev Marpe},
journal= {arXiv preprint arXiv:2510.14645},
year = {2025}
}