Benchmarking Conventional and Learned Video Codecs with a Low-Delay Configuration
<|reference_start|>Benchmarking Conventional and Learned Video Codecs with a Low-Delay Configuration: Recent advances in video compression have seen significant coding performance improvements with the development of new standards and learning-based video codecs. However, most of these works focus on application scenarios that allow a certain amount of system delay (e.g., Random Access mode in MPEG codecs), which is not always acceptable for live delivery. This paper conducts a comparative study of state-of-the-art conventional and learned video coding methods based on a low delay configuration. Specifically, this study includes two MPEG standard codecs (H.266/VVC VTM and JVET ECM), two AOM codecs (AV1 libaom and AVM), and two recent neural video coding models (DCVC-DC and DCVC-FM). To allow a fair and meaningful comparison, the evaluation was performed on test sequences defined in the AOM and MPEG common test conditions in the YCbCr 4:2:0 color space. The evaluation results show that the JVET ECM codecs offer the best overall coding performance among all codecs tested, with a 16.1% (based on PSNR) average BD-rate saving over AOM AVM, and 11.0% over DCVC-FM. We also observed inconsistent performance with the learned video codecs, DCVC-DC and DCVC-FM, for test content with large background motions.<|reference_end|>
@article{teng2024benchmarking,
    title={Benchmarking Conventional and Learned Video Codecs with a Low-Delay
  Configuration},
    author={Siyue Teng (1), Yuxuan Jiang (1), Ge Gao (1), Fan Zhang (1), Thomas
  Davis (2), Zoe Liu (2), David Bull (1) ((1) University of Bristol, (2)
  Visionular Inc.)},
    journal={arXiv preprint arXiv:2408.05042},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.05042},
    primaryClass={cs.MM cs.CV eess.IV}
}