Image Restoration Models
Confidence Intervals for Diffusion Models
Introduced by Horwitz et al. in Conffusion: Confidence Intervals for Diffusion ModelsGiven a corrupted input image, Con\textit{ffusion}, repurposes a pretrained diffusion model to generate lower and upper bounds around each reconstructed pixel. The true pixel value is guaranteed to fall within these bounds with probability $p$.
Source: Conffusion: Confidence Intervals for Diffusion ModelsPapers
| Paper | Code | Results | Date | Stars |
|---|
Tasks
| Task | Papers | Share |
|---|---|---|
| Conformal Prediction | 1 | 16.67% |
| Facial Inpainting | 1 | 16.67% |
| Image Generation | 1 | 16.67% |
| Image Inpainting | 1 | 16.67% |
| Prediction Intervals | 1 | 16.67% |
| Super-Resolution | 1 | 16.67% |
Usage Over Time
Components
| Component | Type |
|
|---|---|---|
| 🤖 No Components Found | You can add them if they exist; e.g. Mask R-CNN uses RoIAlign |
