Bi-Directional Deep Contextual Video Compression
<|reference_start|>Bi-Directional Deep Contextual Video Compression: Deep video compression has made remarkable process in recent years, with the majority of advancements concentrated on P-frame coding. Although efforts to enhance B-frame coding are ongoing, their compression performance is still far behind that of traditional bi-directional video codecs. In this paper, we introduce a bi-directional deep contextual video compression scheme tailored for B-frames, termed DCVC-B, to improve the compression performance of deep B-frame coding. Our scheme mainly has three key innovations. First, we develop a bi-directional motion difference context propagation method for effective motion difference coding, which significantly reduces the bit cost of bi-directional motions. Second, we propose a bi-directional contextual compression model and a corresponding bi-directional temporal entropy model, to make better use of the multi-scale temporal contexts. Third, we propose a hierarchical quality structure-based training strategy, leading to an effective bit allocation across large groups of pictures (GOP). Experimental results show that our DCVC-B achieves an average reduction of 26.6% in BD-Rate compared to the reference software for H.265/HEVC under random access conditions. Remarkably, it surpasses the performance of the H.266/VVC reference software on certain test datasets under the same configuration.<|reference_end|>
@article{sheng2024bi-directional,
    title={Bi-Directional Deep Contextual Video Compression},
    author={Xihua Sheng, Li Li, Dong Liu, Shiqi Wang},
    journal={arXiv preprint arXiv:2408.08604},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.08604},
    primaryClass={cs.CV}
}