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cloud.google.com·8h ago
AI Research
arXiv CS.AI·Jul 24·5 min read
Deblurring in the Wild: A Real-World Image Deblurring Dataset from Smartphone High-Speed Videos
TL;DR
A new dataset for image deblurring has been created from smartphone slow-motion videos, featuring over 42,000 high-resolution blur-sharp image pairs. This dataset is significantly larger than existing ones and reveals the challenges faced by current deblurring models.
✦ Why It Matters
Consider integrating this dataset into your deblurring model training to improve real-world performance.
Key Takeaways
- Utilize the new dataset to benchmark your deblurring algorithms.
- Explore the impact of diverse scenes on model performance.
- Investigate the causes of performance degradation in existing models.
- Adapt your models to handle realistic long-exposure blur scenarios.
How It Works
The dataset simulates long-exposure blur by averaging frames from high-speed videos, creating realistic blurry images while retaining a sharp reference frame.