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English(EN) Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission

新型神经视频编解码器增强了在不可靠信道上的传输性能

研究人员开发了一种新的语义感知神经视频编解码器,基于DCVC-RT框架,专为在不可靠信道上进行鲁棒的低延迟视频传输而设计。该方法将编码数据划分为具有不同语义重要性的数据包,并将它们分配到不同的优先级流中。还引入了一个容错熵模型,允许独立的数据包解码,增强了对数据包丢失的鲁棒性。实验表明,与基线DCVC-RT相比,鲁棒性有了显著提高,在不太关键的区域实现了平滑降级,同时保留了与任务相关的内容。 AI

影响 这项研究可以提高在具有挑战性网络条件下运行的AI系统的视频通信的可靠性。

排序理由 详细介绍新技术方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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新型神经视频编解码器增强了在不可靠信道上的传输性能

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详细介绍新技术方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Matin Mortaheb, Homa Esfahanizadeh, Jinfeng Du, Harish Viswanathan ·

    面向容错低延迟传输的语义感知神经视频编解码器

    arXiv:2609.16279v1 Announce Type: cross Abstract: Emerging physical AI systems require low-latency, task-oriented video communication over unreliable channels. We propose a semantic-aware multi-level neural video coding method for robust low-latency video transmission over unreli…