6 papers
Loss-Resilient Semantic Communication over Packet-Loss Networks at Extreme-Low Bandwidth
Shengshi Yao, Jincheng Dai, Sixian Wang +5
In extreme-low bandwidth network scenarios, generative semantic codecs have emerged as promising solutions to reduce bandwidth cost for visual communications. However, these learne…
DiT-JSCC: Rethinking Deep JSCC with Diffusion Transformers and Semantic Representations
Kailin Tan, Jincheng Dai, Sixian Wang +5
Generative joint source-channel coding (GJSCC) has emerged as a new Deep JSCC paradigm for achieving high-fidelity and robust image transmission under extreme wireless channel cond…
LGVSC: A Large-Model-Driven Generative Video Semantic Communication Framework
Yu Ma, Hang Yin, Li Qiao +4
Driven by the massive video transmission requirements in the Internet of Everything, semantic communication holds great promise for striking a balance between transmission efficien…
JSCGC: Joint Source-Channel-Generation Coding for Wireless Generative Communications
Tong Wu, Zhiyong Chen, Guo Lu +4
Conventional communication systems, including both separation-based coding and learning-based joint source-channel coding (JSCC), are typically designed under Shannon's rate-distor…
Generative AI Meets 6G and Beyond: Diffusion Models for Semantic Communications
Hai-Long Qin, Jincheng Dai, Guo Lu +6
Semantic communications mark a paradigm shift from bit-accurate transmission toward meaning-centric communication, essential as wireless systems approach theoretical capacity limit…
Structure-Guided Allocation of 2D Gaussians for Image Representation and Compression
Huanxiong Liang, Yunuo Chen, Yicheng Pan +4
Recent advances in 2D Gaussian Splatting (2DGS) have demonstrated its potential as a compact image representation with millisecond-level decoding. However, existing 2DGS-based pipe…