lixinustc/Awesome-diffusion-model-for-image-processing
A compiled survey of research papers on diffusion model-based methods for image restoration, enhancement, compression, and quality assessment.
Not currently ranked — collecting fresh signals.
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This repository provides a structured summary of diffusion model research applied to image processing. It catalogs papers covering tasks such as image restoration, enhancement, coding, and perceptual quality assessment. The collection is maintained by academic researchers and includes periodic updates tracking new publications in the field. An associated arXiv paper documents the survey findings.
Frequently asked
- What is lixinustc/Awesome-diffusion-model-for-image-processing?
- A compiled survey of research papers on diffusion model-based methods for image restoration, enhancement, compression, and quality assessment.
- Is Awesome-diffusion-model-for-image-processing open source?
- Yes — lixinustc/Awesome-diffusion-model-for-image-processing is open source, released under the Apache-2.0 license.
- How popular is Awesome-diffusion-model-for-image-processing?
- lixinustc/Awesome-diffusion-model-for-image-processing has 954 stars on GitHub.
- Where can I find Awesome-diffusion-model-for-image-processing?
- lixinustc/Awesome-diffusion-model-for-image-processing is on GitHub at https://github.com/lixinustc/Awesome-diffusion-model-for-image-processing.