Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission
📰 ArXiv cs.AI
Learn how to adapt diffusion language models for lossless pixel-level image transmission using a discrete-diffusion-model-based framework
Action Steps
- Apply discrete diffusion models to image transmission
- Configure separate source-channel coding frameworks
- Test lossless pixel-level image transmission using DDM-SSCC
- Compare performance with traditional raster-order autoregressive coding
- Implement reliable delivery over noisy channels
Who Needs to Know This
This research benefits computer vision engineers and researchers working on image transmission and compression, as it provides a new framework for lossless image transmission
Key Insight
💡 Diffusion language models can be adapted for lossless pixel-level image transmission using a separate source-channel coding framework
Share This
Lossless image transmission gets a boost with DDM-SSCC, a discrete-diffusion-model-based framework #computerVision #imageTransmission
Key Takeaways
Learn how to adapt diffusion language models for lossless pixel-level image transmission using a discrete-diffusion-model-based framework
Full Article
Title: Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission
Abstract:
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. This paper proposes DDM-SSCC, a discrete-diffusion-model-based separate source-channel coding framework for lossless image transmission. Different from raster-order autoregressive coding, the proposed source codec adapts a diffusion lang
Abstract:
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. This paper proposes DDM-SSCC, a discrete-diffusion-model-based separate source-channel coding framework for lossless image transmission. Different from raster-order autoregressive coding, the proposed source codec adapts a diffusion lang
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