9 papers
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…
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…
Neural Hamiltonian Deformation Fields for Dynamic Scene Rendering
Hai-Long Qin, Sixian Wang, Guo Lu +1
Representing and rendering dynamic scenes with complex motions remains challenging in computer vision and graphics. Recent dynamic view synthesis methods achieve high-quality rende…
Neural Coding Is Not Always Semantic: Toward the Standardized Coding Workflow in Semantic Communications
Hai-Long Qin, Jincheng Dai, Sixian Wang +5
Semantic communication, leveraging advanced deep learning techniques, emerges as a new paradigm that meets the requirements of next-generation wireless networks. However, current s…
ResiComp: Loss-Resilient Image Compression via Dual-Functional Masked Visual Token Modeling
Sixian Wang, Jincheng Dai, Xiaoqi Qin +3
Recent advancements in neural image codecs (NICs) are of significant compression performance, but limited attention has been paid to their error resilience. These resulting NICs te…