(CA) Event-guided Neural Video Compression

新型视频编解码器利用事件流提高RGB压缩效率

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-05 04:00

研究人员开发了一种事件引导的神经视频编解码器（ENVC），它利用事件流（捕捉帧间亮度变化）来提高RGB视频压缩的效率。ENVC模型将这些事件流整合到运动编码和帧编码过程中。对于运动编码，它形成一个事件引导的运动先验并编码残差；对于帧编码，一个事件条件预测器改进了时间上下文。在六个基准上的评估显示，BD率显著节省，ENVC使用PSNR-RGB比DCMVC基线高39.13%，使用LPIPS比DCMVC基线高67.63%，证明了事件作为互补数据源在降低RGB编码率方面的效用。 AI

影响通过整合事件数据等互补数据流，这项研究可能带来更高效的视频压缩技术。

排序理由这是一篇描述新颖视频压缩方法的论文。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv cs.CV TIER_1 (CA) · Jiyun Kong, Jungwoo Kim, Enes Eray Demirtas, Touradj Ebrahimi, Jong-Seok Lee · 2026-10-05 04:00

事件引导的神经视频压缩

arXiv:2610.02265v1 Announce Type: cross Abstract: Neural video codecs derive motion and temporal contexts mainly from RGB frames, leaving room for cross-modal guidance from complementary temporal observations. Event streams can provide such observations by recording brightness ch…

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事件引导的神经视频压缩

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