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arXiv · 2504.02560

L-LBVC: Long-Term Motion Estimation and Prediction for Learned Bi-Directional Video Compression

Yongqi Zhai·Luyang Tang·Wei Jiang·Jiayu Yang·Ronggang Wang
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Abstract

Recently, learned video compression (LVC) has shown superior performance under low-delay configuration. However, the performance of learned bi-directional video compression (LBVC) still lags behind traditional bi-directional coding. The performance gap mainly arises from inaccurate long-term motion estimation and prediction of distant frames, especially in large motion scenes. To solve these two critical problems, this paper proposes a novel LBVC framework, namely L-LBVC. Firstly, we propose an adaptive motion estimation module that can handle both short-term and long-term motions. Specifically, we directly estimate the optical flows for adjacent frames and non-adjacent frames with small motions. For non-adjacent frames with large motions, we recursively accumulate local flows between adjacent frames to estimate long-term flows. Secondly, we propose an adaptive motion prediction module that can largely reduce the bit cost for motion coding. To improve the accuracy of long-term motion prediction, we adaptively downsample reference frames during testing to match the motion ranges observed during training. Experiments show that our L-LBVC significantly outperforms previous state-of-the-art LVC methods and even surpasses VVC (VTM) on some test datasets under random access configuration.

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Yongqi Zhai, Luyang Tang, Wei Jiang, Jiayu Yang, Ronggang Wang. 2025-04-03. L-LBVC: Long-Term Motion Estimation and Prediction for Learned Bi-Directional Video Compression. https://arxiv.org/abs/2504.02560

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