ChronoSC: Task-Oriented Semantic Communication via Temporal-to-Color Encoding

• URL: http://arxiv.org/abs/2605.16388v1
• Date: Mon, 11 May 2026 17:29:05 GMT
• Title: ChronoSC: Task-Oriented Semantic Communication via Temporal-to-Color Encoding
• Abstract summary: We propose a task-oriented semantic communication framework for Video Questioning (VideoQA)<n> Chrono-SC Stacking encodes temporal video dynamics into a single static image, enabling extreme temporal compression before transmission.<n> Experiments on the CLEVR dataset show that Chrono-SC achieves up to 192 times bandwidth reduction compared to raw video transmission.
• Score: 6.67386396580815
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Semantic communication (SC) aims to reduce transmission overhead by conveying task-relevant information rather than raw data. However, existing SC approaches for video largely focus on pixel-level reconstruction or rely on complex spatiotemporal pipelines, leading to excessive bandwidth usage and latency that are unsuitable for low-resource deployments. In this paper, we propose ChronoSC, a task-oriented semantic communication framework for Video Question Answering (VideoQA). ChronoSC introduces Chrono-Color Stacking, a lightweight and lossless projection scheme that encodes temporal video dynamics into a single static image, enabling extreme temporal compression before transmission. This compact semantic representation is transmitted using a lightweight Deep Joint Source-Channel Coding (DeepJSCC) transceiver and explicitly reconstructed at the receiver. Unlike latent-space methods, explicit visual reconstruction enables the direct reuse of pre-trained vision-language models; specifically, a pre-trained BLIP model is employed to infer answers from noisy, reconstructed chrono-images. Experiments on the CLEVRER dataset show that ChronoSC achieves up to 192 times bandwidth reduction compared to raw video transmission while maintaining high VideoQA accuracy.

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