SOURCE-LINKED INTELLIGENCE
Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission
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 unreliable channels that are abstracted as multi-level packet erasure channels. Built upon the real-time DCVC-RT neural video codec, the proposed framework introduces a semantic- and feature-aware coding strategy that partitions encoded representations into packets carrying different levels of semantic and latent-feature importance and assigns these packets to different str
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-14T19:37:33.000Z
First collected: 2026-09-20T09:41:04.278Z. This is not the publication date.