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Recent years have witnessed the remarkable performance of diffusion models in various vision tasks.
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S. Xie, Z. Zhang, Z. Lin, T. Hinz, and K. Zhang, “Smartbrush: Text and shape guided object inpainting with diffusion model,” in CVPR , 2023, pp. 22 428–22 437
2023
Closest in time.
A. Rahman, J. M. J. Valanarasu, I. Hacihaliloglu, and V. M. Patel, “Ambiguous medical image segmentation using diffusion models,” in CVPR , 2023, pp. 11 536–11 546
2023
Closest in time.
C. Saharia, J. Ho, W. Chan, T. Salimans, D. J. Fleet, and M. Norouzi, “Image super-resolution via iterative refinement,” IEEE TPAMI , vol. 45, no. 4, pp. 4713–4726, 2023
2023
Closest in time.
O. Özdenizci and R. Legenstein, “Restoring vision in adverse weather conditions with patch-based denoising diffusion models,” IEEE TPAMI , vol. 45, no. 8, pp. 10 346–10 357, 2023
2023
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Z. Luo, F. K. Gustafsson, Z. Zhao, J. Sjölund, and T. B. Schön, “Image restoration with mean-reverting stochastic differential equations,” in ICML , 2023
2023
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H. S. Lee and S. I. Cho, “Locally adaptive channel attention-based spatial–spectral neural network for image deblurring,” IEEE TCSVT , vol. 33, no. 10, pp. 5375–5390, 2023
2023
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X. Liu, G. Li, Z. Zhao, Q. Cao, Z. Zhang, S. Yan, J. Xie, and M. Tang, “Eaf-wgan: Enhanced alignment fusion-wasserstein generative adversarial network for turbulent image restoration,” IEEE TCSVT , vol. 33, no. 10, pp. 5605–5616, 2023
2023
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Y. Zhang, Q. Li, M. Qi, D. Liu, J. Kong, and J. Wang, “Multi-scale frequency separation network for image deblurring,” IEEE TCSVT , vol. 33, no. 10, pp. 5525–5537, 2023
2023
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