VideoQA-SC: Adaptive Semantic Communication for Video Question Answering

TL;DR

This paper introduces VideoQA-SC, an innovative semantic communication system for video question answering that transmits task-relevant video semantics directly over noisy channels, bypassing video reconstruction to improve efficiency and robustness.

Contribution

It proposes an end-to-end adaptive semantic communication framework with a spatiotemporal encoder and a deep joint source-channel coding scheme tailored for VideoQA tasks, enhancing performance over noisy channels.

Findings

Outperforms traditional SC systems in accuracy and bandwidth efficiency.

Achieves 5.17% higher answer accuracy at low SNR.

Saves 99.5% bandwidth compared to existing systems.

Abstract

Although semantic communication (SC) has shown its potential in efficiently transmitting multimodal data such as texts, speeches and images, SC for videos has focused primarily on pixel-level reconstruction. However, these SC systems may be suboptimal for downstream intelligent tasks. Moreover, SC systems without pixel-level video reconstruction present advantages by achieving higher bandwidth efficiency and real-time performance of various intelligent tasks. The difficulty in such system design lies in the extraction of task-related compact semantic representations and their accurate delivery over noisy channels. In this paper, we propose an end-to-end SC system, named VideoQA-SC for video question answering (VideoQA) tasks. Our goal is to accomplish VideoQA tasks directly based on video semantics over noisy or fading wireless channels, bypassing the need for video reconstruction at the receiver. To this end, we develop a spatiotemporal semantic encoder for effective video semantic extraction, and a learning-based bandwidth-adaptive deep joint source-channel coding (DJSCC) scheme for efficient and robust video semantic transmission. Experiments demonstrate that VideoQA-SC outperforms traditional and advanced DJSCC-based SC systems that rely on video reconstruction at the receiver under a wide range of channel conditions and bandwidth constraints. In particular, when the signal-to-noise ratio is low, VideoQA-SC can improve the answer accuracy by 5.17% while saving almost 99.5\% of the bandwidth at the same time, compared with the advanced DJSCC-based SC system. Our results show the great potential of SC system design for video applications.