Deep Learning in Motion Deblurring: Current Status, Benchmarks and Future Prospects

:fire::fire: In this review, we have systematically examined over 150 papers :page_with_curl::page_with_curl::page_with_curl:, summarizing and analyzing :star2:more than 30 blind motion deblurring methods.

:fire::fire::fire: Extensive qualitative and quantitative comparisons have been conducted against the current SOTA methods on four datasets, highlighting their limitations and pointing out future research directions.

:fire::fire::fire::fire: The latest deblurring papers of CVPR 2024 have been included~

Fig 1. Overview of deep learning methods for blind motion deblurring.

Content:

1. Related Reviews and Surveys to Deblurring
2. CNN-based Blind Motion Deblurring Models
3. RNN-based Blind Motion Deblurring Models
4. GAN-based Blind Motion Deblurring Models
5. Transformer-based Blind Motion Deblurring Models
6. Diffusion-based Blind Motion Deblurring Models
7. Motion Deblurring Datasets
8. Evaluation
9. Citation

0. Related Reviews and Surveys to Deblurring:

:rocket::rocket::rocket:Update (in 2023-12-28) :balloon:

1. CNN-based Blind Motion Deblurring Models:

:rocket::rocket::rocket:Update (in 2024-01-08) :balloon:

2. RNN-based Blind Motion Deblurring Models:

:rocket::rocket::rocket:Update (in 2024-01-06) :balloon:

3. GAN-based Blind Motion Deblurring Models:

:rocket::rocket::rocket:Update (in 2024-01-07) :balloon:

4. Transformer-based Blind Motion Deblurring Models:

:rocket::rocket::rocket:Update (in 2024-03-08) :balloon:

5. Diffusion-based Blind Motion Deblurring Models:

:rocket::rocket::rocket:Update (in 2024-03-08) :balloon:

6. Motion Deblurring Datasets:

:rocket::rocket::rocket:Update (in 2024-01-08) :balloon:

7. Evaluation:

• For evaluation on GoPro results in MATLAB, modify './out/...' to the corresponding path

evaluation_GoPro.m

• For evaluation on HIDE results in MATLAB, modify './out/...' to the corresponding path

evaluation_HIDE.m

• For evaluation on RealBlur_J results, modify './out/...' to the corresponding path

python evaluate_RealBlur_J.py

• For evaluation on RealBlur_R results, modify './out/...' to the corresponding path

python evaluate_RealBlur_R.py

Citation:

If you find our survey paper and evaluation code are useful, please cite the following paper:

@article{xiang2024application,
      title={Application of Deep Learning in Blind Motion Deblurring: Current Status and Future Prospects}, 
      author={Yawen Xiang and Heng Zhou and Chengyang Li and Fangwei Sun and Zhongbo Li and Yongqiang Xie},
      year={2024},
      journal={arXiv preprint arXiv:2401.05055},
}

:clap::clap::clap: Thanks to the above authors for their excellent work！