DiffBIR has three major differentiating advantages over traditional image restoration tools:
Technical Architecture Advantages
- Generating Diffusion Models: Exploit the incremental generation properties of diffusion models to generate more natural image details than GANs
- Blind repair capability: Adaptive handling of mixed degradation problems without the need to predefine the type of degradation (e.g., fuzzy kernel or noise distribution)
Advantages of Functional Features
- multitasking: A single model can accomplish tasks such as super-scoring/de-noising/face restoration without switching tools.
- Detail retention: Outstanding performance in texture recovery and edge sharpening to avoid over-smoothing problems
Application Ecology Advantage
- Open Source Customizable: Provide complete training code, support customized data fine-tuning
- Hardware friendly: Optimized reasoning process runs on consumer graphics cards (e.g. RTX3060)
According to the actual test, DiffBIR's PSNR index on CelebA-HQ dataset is 7% higher than Restormer, especially in the old photo restoration scenario can restore more than 80% of real details.
This answer comes from the articleDiffBIR: Intelligent Repair Tool to Improve Image QualityThe
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