AI & ML
Token Importance-Aware Semantic Communication Enabled Robust Video Transmission
arXiv eess.IV0 views
arXiv:2611.12928v1 Announce Type: new Abstract: Video applications are increasingly prevalent, yet their high data volume and temporal dependency make robust wireless transmission challenging under limited communication resources. To address this issue, we propose a token importance-aware semantic communication (Ti-SemCom) framework for bandwidth-efficient video transmission. Specifically, object and motion information is jointly extracted to identify communication-relevant regions, which are hierarchically associated with semantic tokens according to their importance. The transmitted tokens are then dynamically selected based on both token importance and the available bandwidth, prioritizing more informative video content under resource constraints. At the receiver, untransmitted regions reuse recently reconstructed references to further reduce redundant transmission. Experiments on the CAVIAR dataset show that Ti-SemCom can achieve an 88.3\% reduction in communication cost while maintaining competitive reconstruction quality.
Source:https://arxiv.org/abs/2611.12928PreviousPygmalion Effect in Vision: Image-to-Clay Translation for Reflective Geometry ReconstructionNextIs a CNN-Transformer Ensemble Worth It When a Chest X-Ray Foundation Model Is Available?
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