Learning From Coding Features : High Efficiency Rate Control for AV1

Yi CHEN, Yunhao MAO, Shiqi WANG, Xianguo ZHANG, Sam KWONG

Research output: Journal PublicationsJournal Article (refereed)peer-review


Rate control, which typically includes bit allocation and quantization parameter (QP) determination, plays an important role in real-world video coding applications. In this paper, we propose a novel rate control scheme for AOMedia Video 1 (AV1) which enjoys adaptive bit allocation and effective QP determination. In particular, two supporting vector regression (SVR) models are learned for the hierarchical bit allocation and frame-level parameter estimation. To train the models, the multi-pass coding strategy is utilized for training data acquisition. Compared to the default scheme in AV1 and the state-of-the-art method, the proposed rate control scheme achieves superior performance in terms of bitrate accuracy and coding efficiency.

Original languageEnglish
Pages (from-to)1-7
Number of pages7
JournalIEEE Multimedia
Publication statusE-pub ahead of print - 10 Apr 2023
Externally publishedYes

Bibliographical note

Publisher Copyright:


  • Adaptation models
  • Bit rate
  • Encoding
  • Machine learning
  • Parameter estimation
  • Training
  • Video coding


Dive into the research topics of 'Learning From Coding Features : High Efficiency Rate Control for AV1'. Together they form a unique fingerprint.

Cite this