Restore images with many defect types using instructions by train on cleaned images with InstructIR
Restore images with many defect types using instructions by train on cleaned images with InstructIR
InstructIR: High-Quality Image Restoration Following Human Instructions
arXiv paper abstract https://arxiv.org/abs/2401.16468
arXiv PDF paper https://arxiv.org/pdf/2401.16468.pdf
Image restoration is a fundamental problem that involves recovering a high-quality clean image from its degraded observation.
All-In-One image restoration models can ... restore images from various types and levels of degradation using degradation-specific information as prompts to guide the restoration model.
... present the first approach that uses human-written instructions to guide the image restoration model.
Given natural language prompts, ... model can recover high-quality images from their degraded counterparts, considering multiple degradation types.
... InstructIR, achieves state-of-the-art results on several restoration tasks including image denoising, deraining, deblurring, dehazing, and (low-light) image enhancement.
InstructIR improves +1dB over previous all-in-one restoration methods ...
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