Hugging Face Trending Papers
Joint Semantic-Channel Coding and Modulation for Generative Image Transmission
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arXiv Computer Vision
4d ago
Joint Semantic-Channel Coding and Modulation for Generative Image Transmission
The paper introduces SemQAM, a joint semantic-channel coding and modulation framework for generative image transmission that converts source representations directly into modulated QAM symbols. By vector‑quantizing latent features and mapping each index to a QAM symbol, SemQAM allows channel impairments to influence codebook learning and employs conditional expectations of received codewords to mitigate error propagation in autoregressive decoding. Experiments demonstrate that SemQAM-C matches or surpasses conventional source coding methods while reducing channel uses by 18.57% compared to separated schemes, highlighting its efficiency and effectiveness in joint coding.
arXiv AI
Jun 12
JSCGC: Joint Source-Channel-Generation Coding for Wireless Generative Communications
arXiv:2606. 12858v1 Announce Type: cross Abstract: Conventional communication systems, including both separation-based coding and learning-based joint source-channel coding (JSCC), are typically designed under Shannon's rate-distortion theory.
arXiv Computer Vision
5d ago
PerQ: Inverse Generative Modeling for Neural Image Compression via Quantization Error Compensation
arXiv:2610.27374v1 Announce Type: new Abstract: Neural image codecs face a fundamental trade-off between pixel fidelity and perceptual quality. Distortion-optimized codecs preserve pixel-wise fidelit...
Hugging Face Trending Papers
Aug 11
Every Packet Counts: Dispersing Information for Loss-Resilient Learned Image Compression
Learned image compression (LIC) has achieved impressive rate-distortion performance. However, existing methods remain highly vulnerable to packet loss, a common challenge in satellite and emergency communications.
arXiv AI
Jun 6
Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission
arXiv:2606. 06273v1 Announce Type: cross Abstract: Lossless pixel-level image transmission is a fundamental regime beyond semantic communications, because exact recovery requires both accurate symbol probability modeling and reliable delivery over noisy channels.
arXiv Machine Learning
Aug 18
In-Context Source and Channel Coding
arXiv:2601. 10267v2 Announce Type: replace Abstract: Separate Source-Channel Coding (SSCC) remains attractive for text transmission due to its modularity and compatibility with mature entropy coders and powerful channel codes.