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Image deblurring aims to restore a high-quality image from its corresponding blurred.
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V. Singh, K. Ramnath, and A. Mittal, “Refining high-frequencies for sharper super-resolution and deblurring,” Computer Vision and Image Understanding , vol. 199, no. C, p. 103034, 2020
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L. Chen, X. Lu, J. Zhang, X. Chu, and C. Chen, “Hinet: Half instance normalization network for image restoration,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops , June 2021, pp. 182–192
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2021
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J. Dong, J. Pan, Z. Yang, and J. Tang, “Multi-scale residual low-pass filter network for image deblurring,” in 2023 IEEE/CVF International Conference on Computer Vision (ICCV) , 2023, pp. 12 311–12 320
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A. Gu, I. Johnson, K. Goel, K. Saab, T. Dao, A. Rudra, and C. Ré, “Combining recurrent, convolutional, and continuous-time models with linear state space layers,” Advances in neural information processing systems , vol. 34, pp. 572–585, 2021
2021
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H. Son, J. Lee, S. Cho, and S. Lee, “Single image defocus deblurring using kernel-sharing parallel atrous convolutions,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2021, pp. 2642–2650
2021
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2022
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2022
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2022
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F.-J. Tsai, Y.-T. Peng, Y.-Y. Lin, C.-C. Tsai, and C.-W. Lin, “Stripformer: Strip transformer for fast image deblurring,” in ECCV , 2022
2022
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Z. Wang, X. Cun, J. Bao, W. Zhou, J. Liu, and H. Li, “Uformer: A general u-shaped transformer for image restoration,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , June 2022, pp. 17 683–17 693
2022
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2022
Cited alongside, same era.
J. T. Smith, A. Warrington, and S. W. Linderman, “Simplified state space layers for sequence modeling,” ICLR , 2023
2023
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2023
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2023
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2023
Later among the works it cites.
2024
Closest in time.
Y. Cui, W. Ren, X. Cao, and A. Knoll, “Image restoration via frequency selection,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 46, no. 2, pp. 1093–1108, 2024
2024
Closest in time.
X. Zhou, H. Huang, Z. Wang, and R. He, “Ristra: Recursive image super-resolution transformer with relativistic assessment,” IEEE Transactions on Multimedia , pp. 1–12, 2024
2024
Closest in time.
L. Zhu, B. Liao, Q. Zhang, X. Wang, W. Liu, and X. Wang, “Vision mamba: Efficient visual representation learning with bidirectional state space model,” 2024
2024
Closest in time.
2024
Closest in time.
2024
Closest in time.
H. Liu, B. Li, C. Liu, and M. Lu, “Deblurdinat: A lightweight and effective transformer for image deblurring,” 2024
2024
Closest in time.
J. Lee, H. Son, J. Rim, S. Cho, and S. Lee, “Iterative filter adaptive network for single image defocus deblurring,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2021, pp. 2034–2042
2042
Closest in time.