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Recently, deep learning-based methods have dominated image dehazing domain.
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D. Liu, B. Wen, Y. Fan, C. C. Loy, and T. S. Huang, “Non-local recurrent network for image restoration,” in NIPS , 2018, pp. 1673–1682
2018
Cited alongside, same era.
W. Ren, L. Ma, J. Zhang, J. Pan, X. Cao, W. Liu, and M.-H. Yang, “Gated Fusion Network for Single Image Dehazing,” in CVPR , 2018, pp. 3253–3261
2018
Cited alongside, same era.
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2019
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2019
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2019
M. Hong, J. Liu, C. Li, and Y. Qu, “Uncertainty-Driven Dehazing Network,” in AAAI , vol. 36, no. 1, 2022, pp. 906–913
2022
Later among the works it cites.
T. Ye, M. Jiang, Y. Zhang, L. Chen, E. Chen, P. Chen, and Z. Lu, “Perceiving and Modeling Density is All You Need for Image Dehazing,” in ECCV , 2022, pp. 130–145
2022
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J. Zhang, W. Ren, S. Zhang, H. Zhang, Y. Nie, Z. Xue, and X. Cao, “Hierarchical Density-Aware Dehazing Network,” IEEE Transactions on Cybernetics , vol. 52, no. 10, pp. 11 187–11 199, oct 2022
2022
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C. Guo, Q. Yan, S. Anwar, R. Cong, W. Ren, and C. Li, “Image Dehazing Transformer with Transmission-Aware 3D Position Embedding,” in CVPR , 2022, pp. 5812–5820
2022
Later among the works it cites.
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Cited alongside, same era.
X. Liu, Y. Ma, Z. Shi, and J. Chen, “GridDehazeNet: Attention-based multi-scale network for image dehazing,” in ICCV , 2019, pp. 7313–7322
2019
Cited alongside, same era.
Z. Zhu, M. Xu, S. Bai, T. Huang, and X. Bai, “Asymmetric non-local neural networks for semantic segmentation,” in ICCV , 2019, pp. 593–602
2019
Cited alongside, same era.
B. Li, W. Ren, D. Fu, D. Tao, D. Feng, W. Zeng, and Z. Wang, “Benchmarking single-image dehazing and beyond,” IEEE Transactions on Image Processing , vol. 28, no. 1, pp. 492–505, 2019
2019
Cited alongside, same era.
T. He, Z. Zhang, H. Zhang, Z. Zhang, J. Xie, and M. Li, “Bag of tricks for image classification with convolutional neural networks,” in CVPR . IEEE, 6 2019, pp. 558–567
2019
Cited alongside, same era.
X. Qin, Z. Wang, Y. Bai, X. Xie, and H. Jia, “FFA-Net: Feature Fusion Attention Network for Single Image Dehazing,” in AAAI , vol. 34, no. 07, 2020, pp. 11 908–11 915
2020
Cited alongside, same era.
H. Dong, J. Pan, L. Xiang, Z. Hu, X. Zhang, F. Wang, and M. H. Yang, “Multi-scale boosted dehazing network with dense feature fusion,” in CVPR , 2020, pp. 2154–2164
2020
Cited alongside, same era.
S. Zhang, F. He, and W. Ren, “Nldn: Non-local dehazing network for dense haze removal,” Neurocomputing , vol. 410, pp. 363–373, 10 2020
2020
Cited alongside, same era.
2022
Later among the works it cites.
H. Bai, J. Pan, X. Xiang, and J. Tang, “Self-guided image dehazing using progressive feature fusion,” IEEE Transactions on Image Processing , vol. 31, pp. 1217–1229, 2022
2022
Later among the works it cites.
Z. Tu, H. Talebi, H. Zhang, F. Yang, P. Milanfar, A. Bovik, and Y. Li, “Maxim: Multi-axis mlp for image processing,” in CVPR , 2022, pp. 5769–5780
2022
Later among the works it cites.
C. Lin, X. Rong, and X. Yu, “MSAFF-Net: Multiscale Attention Feature Fusion Networks for Single Image Dehazing and beyond,” IEEE Transactions on Multimedia , vol. 25, pp. 3089–3100, 2023
2023
Closest in time.
Y. Wang, J. Xiong, X. Yan, and M. Wei, “USCFormer: Unified Transformer With Semantically Contrastive Learning for Image Dehazing,” IEEE Transactions on Intelligent Transportation Systems , vol. 24, no. 10, pp. 11 321–11 333, 2023
2023
Closest in time.
Y. Song, Z. He, H. Qian, and X. Du, “Vision Transformers for Single Image Dehazing,” IEEE Transactions on Image Processing , vol. 32, pp. 1927–1941, apr 2023
2023
Closest in time.
H. Sun, B. Li, Z. Dan, W. Hu, B. Du, W. Yang, and J. Wan, “Multi-level feature interaction and efficient non-local information enhanced channel attention for image dehazing,” Neural Networks , vol. 163, pp. 10–27, 6 2023
2023
Closest in time.
Y. Zheng, J. Zhan, S. He, J. Dong, and Y. Du, “Curricular Contrastive Regularization for Physics-aware Single Image Dehazing,” in CVPR , 2023, pp. 5785–5794
2023
Closest in time.
Z. Wang, H. Zhao, L. Yao, J. Peng, and K. Zhao, “DFR-Net: Density Feature Refinement Network for Image Dehazing Utilizing Haze Density Difference,” IEEE Transactions on Multimedia , vol. 26, pp. 7673–7686, 2024
2024
Closest in time.
D. Cheng, Y. Li, D. Zhang, N. Wang, J. Sun, and X. Gao, “Progressive Negative Enhancing Contrastive Learning for Image Dehazing and Beyond,” IEEE Transactions on Multimedia , vol. 26, pp. 8783–8798, 2024
2024
Closest in time.
Z. Chen, Z. He, and Z.-M. Lu, “DEA-Net: Single Image Dehazing Based on Detail-Enhanced Convolution and Content-Guided Attention,” IEEE Transactions on Image Processing , vol. 33, pp. 1002–1015, 2024
2024
Closest in time.
Y. Su, N. Wang, Z. Cui, Y. Cai, C. He, and A. Li, “Real Scene Single Image Dehazing Network with Multi-Prior Guidance and Domain Transfer,” IEEE Transactions on Multimedia , vol. PP, pp. 1–16, 2025
2025
Closest in time.
Y. Cui, J. Zhu, and A. Knoll, “Enhancing Perception for Autonomous Vehicles: A Multi-Scale Feature Modulation Network for Image Restoration,” IEEE Transactions on Intelligent Transportation Systems , vol. 26, no. 4, pp. 4621–4632, 2025
2025
Closest in time.