Summary of Instructir: High-quality Image Restoration Following Human Instructions, by Marcos V. Conde et al.
InstructIR: High-Quality Image Restoration Following Human Instructions
by Marcos V. Conde, Gregor Geigle, Radu Timofte
First submitted to arxiv on: 29 Jan 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG); Image and Video Processing (eess.IV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a novel approach to image restoration, InstructIR, which uses human-written instructions as prompts to guide the restoration model. Unlike traditional All-In-One models, InstructIR can recover high-quality images from their degraded counterparts considering multiple degradation types, including noise, rain, blur, haze, and low-light enhancement. The method achieves state-of-the-art results on several restoration tasks, outperforming previous all-in-one methods by +1dB. This work also introduces a novel benchmark dataset for text-guided image restoration and enhancement. The code, datasets, and models are available at the GitHub link provided. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about a new way to fix blurry or dirty pictures called InstructIR. It uses written instructions to help fix the picture. This method can take different kinds of messy pictures and make them look clean again. It’s better than other methods that try to do the same thing, by +1dB. The researchers also created a special set of pictures for others to test their own ideas on fixing blurry or dirty pictures. |
