English(EN) Boosting Neural Video Codec via Scale-Driven Online Flow Refinement

新方法提升神经视频编解码器泛化能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-06-22 08:36

研究人员开发了一种新颖的无训练尺度驱动在线流细化（SOFR）方法，以增强神经视频编解码器（NVC）的泛化能力。该即插即用模块整合了多尺度的运动信息，并动态融合它们以最小的计算成本纠正运动估计误差。SOFR还包含一个感知比特率的策略和一个可靠性检查以提高鲁棒性，在USTC-TD数据集上，跨DCVC-SDD、DCVC-FM和EHVC等多种NVC框架均实现了显著的比特率节省。 AI

影响提高了神经视频编解码器的视频压缩效率和泛化能力。

排序理由该集群包含一篇详细介绍神经视频编解码器新方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CV TIER_1 English(EN) · Siwei Ma · 2026-06-22 08:36

通过尺度驱动的在线流细化提升神经视频编解码器

Although state-of-the-art neural video codecs (NVCs) have achieved remarkable performance, they suffer from limited generalization when encountering complex motion patterns unseen during training. To bridge this domain gap without the expensive cost of online fine-tuning, we prop…

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通过尺度驱动的在线流细化提升神经视频编解码器

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