# Helsinki Deblur Challenge 2021: description of photographic data

arXiv: https://arxiv.org/abs/2105.10233 · HTML: https://mlsanity.com/paper/2105.10233/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 12 references that are in the map.
- First posted on arXiv 21 May 2021.

## Builds on (most cited first, 1 of 1)

- [RENOIR - A Dataset for Real Low-Light Image Noise Reduction](https://mlsanity.com/paper/1409.8230/) (2014)

## Built on by (most cited first, 1 of 1)

- [Deblurring Photographs of Characters Using Deep Neural Networks](https://mlsanity.com/paper/2205.15053/) (2022)

## Abstract (arXiv)

The photographic dataset collected for the Helsinki Deblur Challenge 2021 (HDC2021) contains pairs of images taken by two identical cameras of the same target but with different conditions. One camera is always in focus and produces sharp and low-noise images the other camera produces blurred and noisy images as it is gradually more and more out of focus and has a higher ISO setting. Even though the dataset was designed and captured with the HDC2021 in mind it can be used for any testing and benchmarking of image deblurring algorithms. The data is available here: https://doi.org/10.5281/zenodo.477228