Methods › Computer Vision › Image Restoration Models › MPRNet

MPRNet

3 papers tagged archive 2025-07-28

Introduced by Syed Waqas Zamir et al. in Multi-Stage Progressive Image Restoration

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

MPRNet is a multi-stage progressive image restoration architecture that progressively learns restoration functions for the degraded inputs, thereby breaking down the overall recovery process into more manageable steps. Specifically, the model first learns the contextualized features using encoder-decoder architectures and later combines them with a high-resolution branch that retains local information. At each stage, a per-pixel adaptive design is introduced that leverages in-situ supervised attention to reweight the local features.

PaperSource

Papers archive 2025-07-28

3 shown of 3, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

11 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Deblurring1
Decoder1
Denoising1
Flare Removal1
Image Deblurring1
Image Denoising1
Image Restoration1
Rain Removal1
SSIM1
Single Image Deraining1
Spectral Reconstruction1

Usage over time archive 2025-07-28

Papers per year tagged with MPRNet: 2021 to 2024, peak 1 1 0 2021: 1 paper 2021 2022: 1 paper 2022 2023: 0 papers 2023 2024: 1 paper 2024
Papers per year the archive tags with this method, by the paper's archive date (3 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Image Restoration Models

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