Wireless Video Semantic Communication with Decoupled Diffusion Multi-frame Compensation
- URL: http://arxiv.org/abs/2511.02478v1
- Date: Tue, 04 Nov 2025 11:05:41 GMT
- Title: Wireless Video Semantic Communication with Decoupled Diffusion Multi-frame Compensation
- Authors: Bingyan Xie, Yongpeng Wu, Yuxuan Shi, Biqian Feng, Wenjun Zhang, Jihong Park, Tony Quek,
- Abstract summary: We propose a wireless video semantic communication framework with decoupled diffusion multi-frame compensation.<n>WVSC-D first encodes original video frames as semantic frames and then conducts video coding based on such compact representations.<n>To further reduce the communication overhead, a reference semantic frame is introduced to substitute motion vectors of each frame in common video coding methods.
- Score: 21.650559510264312
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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 with decoupled diffusion multi-frame compensation (DDMFC), abbreviated as WVSC-D, which integrates the idea of semantic communication into wireless video transmission scenarios. WVSC-D 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, DDMFC is proposed to generate compensated current semantic frame by a two-stage conditional diffusion process. With both the reference frame transmission and DDMFC frame compensation, the bandwidth efficiency improves with satisfying video transmission performance. Experimental results verify the performance gain of WVSC-D over other DL-based methods e.g. DVSC about 1.8 dB in terms of PSNR.
Related papers
- Context Video Semantic Transmission with Variable Length and Rate Coding over MIMO Channels [49.624608869195065]
We propose the context video semantic transmission (CVST) framework for wireless video transmission.<n>We learn a context-channel correlation map to explicitly formulate the relationships between feature groups and multiple input multiple output (MIMO) subchannels.<n>We demonstrate substantial performance gains over various standardized separated coding methods and recent wireless video semantic communication approaches.
arXiv Detail & Related papers (2025-12-23T10:48:43Z) - VLF-MSC: Vision-Language Feature-Based Multimodal Semantic Communication System [0.9176056742068811]
Vision-Language Feature-based Multimodal Semantic Communication (VLF-MSC) is a unified system that transmits a single vision-language representation to support both image and text generation at the receiver.<n>By leveraging foundation models, the system achieves robustness to channel noise while preserving semantic fidelity.
arXiv Detail & Related papers (2025-11-13T08:29:32Z) - Motion-Aware Concept Alignment for Consistent Video Editing [57.08108545219043]
We introduce MoCA-Video (Motion-Aware Concept Alignment in Video), a training-free framework bridging the gap between image-domain semantic mixing and video.<n>Given a generated video and a user-provided reference image, MoCA-Video injects the semantic features of the reference image into a specific object within the video.<n>We evaluate MoCA's performance using the standard SSIM, image-level LPIPS, temporal LPIPS, and introduce a novel metric CASS (Conceptual Alignment Shift Score) to evaluate the consistency and effectiveness of the visual shifts between the source prompt and the modified video frames
arXiv Detail & Related papers (2025-06-01T13:28:04Z) - WVSC: Wireless Video Semantic Communication with Multi-frame Compensation [56.63352157833874]
Existing wireless video transmission schemes directly conduct video coding in pixel level.<n>We propose a wireless video semantic communication framework, abbreviated as WVSC, which integrates the idea of semantic communication into wireless video transmission scenarios.
arXiv Detail & Related papers (2025-03-27T06:27:15Z) - Generative Video Semantic Communication via Multimodal Semantic Fusion with Large Model [52.420489186647295]
We propose a scalable generative video semantic communication framework that extracts and transmits semantic information to achieve high-quality video reconstruction.<n>Specifically, at the transmitter, description and other condition signals are extracted from the source video, functioning as text and structural semantics, respectively.<n>At the receiver, the diffusion-based GenAI large models are utilized to fuse the semantics of the multiple modalities for reconstructing the video.
arXiv Detail & Related papers (2025-02-19T15:59:07Z) - Semantic-Aware Adaptive Video Streaming Using Latent Diffusion Models for Wireless Networks [12.180483357502293]
This paper proposes a novel framework for real-time adaptivebitrate video streaming by integrating Latent Diffusion Models (LDMs) within the FF techniques.<n>The proposed approach leverages LDMs to compress I-frames into a latent space, offering significant storage and semantic transmission savings.<n>This work opens new possibilities for scalable real-time video streaming in 5G and future post-5G networks.
arXiv Detail & Related papers (2025-02-08T21:14:28Z) - When Video Coding Meets Multimodal Large Language Models: A Unified Paradigm for Video Coding [118.72266141321647]
Cross-Modality Video Coding (CMVC) is a pioneering approach to explore multimodality representation and video generative models in video coding.<n>During decoding, previously encoded components and video generation models are leveraged to create multiple encoding-decoding modes.<n>Experiments indicate that TT2V achieves effective semantic reconstruction, while IT2V exhibits competitive perceptual consistency.
arXiv Detail & Related papers (2024-08-15T11:36:18Z) - Synchronous Multi-modal Semantic Communication System with Packet-level Coding [20.397350999784276]
We propose a Synchronous Multimodal Semantic Communication System (SyncSC) with Packet-Level Coding.
To achieve semantic and time synchronization, 3D Morphable Mode (3DMM) coefficients and text are transmitted as semantics.
To protect semantic packets under the erasure channel, we propose a packet-Level Forward Error Correction (FEC) method, called PacSC, that maintains a certain visual quality performance even at high packet loss rates.
arXiv Detail & Related papers (2024-08-08T15:42:00Z) - Neighbor Correspondence Matching for Flow-based Video Frame Synthesis [90.14161060260012]
We introduce a neighbor correspondence matching (NCM) algorithm for flow-based frame synthesis.
NCM is performed in a current-frame-agnostic fashion to establish multi-scale correspondences in the spatial-temporal neighborhoods of each pixel.
coarse-scale module is designed to leverage neighbor correspondences to capture large motion, while the fine-scale module is more efficient to speed up the estimation process.
arXiv Detail & Related papers (2022-07-14T09:17:00Z) - Wireless Deep Video Semantic Transmission [14.071114007641313]
We propose a new class of high-efficiency deep joint source-channel coding methods to achieve end-to-end video transmission over wireless channels.
Our framework is collected under the name deep video semantic transmission (DVST)
arXiv Detail & Related papers (2022-05-26T03:26:43Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.