# WVSC: Wireless Video Semantic Communication with Multi-frame Compensation

arXiv: https://arxiv.org/abs/2503.21197 · HTML: https://mlsanity.com/paper/2503.21197/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 15 references that are in the map.
- First posted on arXiv 27 Mar 2025.

## Builds on (most cited first, 8 of 8)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [FVC: A New Framework towards Deep Video Compression in Feature Space](https://mlsanity.com/paper/2105.09600/) (2021)
- [Sionna: An Open-Source Library for Next-Generation Physical Layer Research](https://mlsanity.com/paper/2203.11854/) (2022)
- [Wireless Semantic Communications for Video Conferencing](https://mlsanity.com/paper/2204.07790/) (2022)
- [Learning to Fuse Monocular and Multi-view Cues for Multi-frame Depth Estimation in Dynamic Scenes](https://mlsanity.com/paper/2304.08993/) (2023)
- [Robust Image Semantic Coding with Learnable CSI Fusion Masking over MIMO Fading Channels](https://mlsanity.com/paper/2406.07389/) (2024)

## Built on by (most cited first, 2 of 2)

- [Wireless Video Semantic Communication with Decoupled Diffusion Multi-frame Compensation](https://mlsanity.com/paper/2511.02478/) (2025)
- [Context Video Semantic Transmission with Variable Length and Rate Coding over MIMO Channels](https://mlsanity.com/paper/2601.06059/) (2025)

## Abstract (arXiv)

Existing wireless video transmission schemes directly conduct video coding in pixel level, while neglecting the inner semantics contained in videos. In this paper, we propose a wireless video semantic communication framework, abbreviated as WVSC, which integrates the idea of semantic communication into wireless video transmission scenarios. WVSC first encodes original video frames as semantic frames and then conducts video coding based on such compact representations, enabling the video coding in semantic level rather than pixel level. Moreover, to further reduce the communication overhead, a reference semantic frame is introduced to substitute motion vectors of each frame in common video coding methods. At the receiver, multi-frame compensation (MFC) is proposed to produce compensated current semantic frame with a multi-frame fusion attention module. With both the reference frame transmission and MFC, the bandwidth efficiency improves with satisfying video transmission performance. Experimental results verify the performance gain of WVSC over other DL-based methods e.g. DVSC about 1 dB and traditional schemes about 2 dB in terms of PSNR.