Fetching the paper…
Reading the bibliography…
Single image dehazing is a challenging ill-posed problem which estimates latent haze-free images from observed hazy images.
K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” 2009, pp. 1956–1963
1963
Earlier work this paper cites.
I. Sobel, G. Feldman et al. , “A 3x3 isotropic gradient operator for image processing,” a talk at the Stanford Artificial Project in , pp. 271–272, 1968
1968
Earlier work this paper cites.
J. M. Prewitt et al. , “Object enhancement and extraction,” Picture processing and Psychopictorics , vol. 10, no. 1, pp. 15–19, 1970
1970
Earlier work this paper cites.
H. Wu, J. Liu, Y. Xie, Y. Qu, and L. Ma, “Knowledge Transfer Dehazing Network for NonHomogeneous Dehazing,” in CVPR Workshop . IEEE, 2020, pp. 1975–1983
1983
Earlier work this paper cites.
H. Scharr, “Optimal operators in digital image processing,” Ph.D. dissertation, 2000
2000
Earlier work this paper cites.
T. Ojala, M. Pietikainen, and T. Maenpaa, “Multiresolution gray-scale and rotation invariant texture classification with local binary patterns,” IEEE Transactions on pattern analysis and machine intelligence , vol. 24, no. 7, pp. 971–987, 2002
2002
Earlier work this paper cites.
S. Narasimhan and S. Nayar, “Contrast restoration of weather degraded images,” IEEE Transactions on Pattern Analysis and Machine Intelligence , vol. 25, no. 6, pp. 713–724, 2003
2003
Earlier work this paper cites.
Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli, “Image quality assessment: from error visibility to structural similarity.” IEEE Transactions on Image Processing , vol. 13, pp. 600–612, 4 2004
2004
Earlier work this paper cites.
R. T. Tan, “Visibility in bad weather from a single image,” in CVPR . IEEE, 2008, pp. 1–8
2008
Earlier work this paper cites.
K. He, J. Sun, and X. Tang, “Single image haze removal using dark channel prior,” IEEE transactions on pattern analysis and machine intelligence , vol. 33, no. 12, pp. 2341–2353, 2010
2010
Earlier work this paper cites.
Q. Zhu, J. Mai, and L. Shao, “A fast single image haze removal algorithm using color attenuation prior,” IEEE transactions on image processing , vol. 24, no. 11, pp. 3522–3533, 2015
2015
Earlier work this paper cites.
D. P. Kingma and J. L. Ba, “Adam: A method for stochastic optimization,” in ICLR , 2015, pp. 1–15
2015
Earlier work this paper cites.
B. Cai, X. Xu, K. Jia, C. Qing, and D. Tao, “Dehazenet: An end-to-end system for single image haze removal,” IEEE Transactions on Image Processing , vol. 25, no. 11, pp. 5187–5198, 2016
2016
Earlier work this paper cites.
W. Ren, S. Liu, H. Zhang, J. Pan, X. Cao, and M.-H. Yang, “Single image dehazing via multi-scale convolutional neural networks,” in European conference on computer vision . Springer, 2016, pp. 154–169
2016
Earlier work this paper cites.
D. Berman, S. Avidan et al. , “Non-local image dehazing,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 1674–1682
2016
Earlier work this paper cites.
K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 770–778
2016
Cited alongside, same era.
B. Li, X. Peng, Z. Wang, J. Xu, and D. Feng, “Aod-net: All-in-one dehazing network,” in Proceedings of the IEEE international conference on computer vision , 2017, pp. 4770–4778
2017
Cited alongside, same era.
F. Juefei-Xu, V. Naresh Boddeti, and M. Savvides, “Local binary convolutional neural networks,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017, pp. 19–28
2017
Cited alongside, same era.
H. Zhang and V. M. Patel, “Densely connected pyramid dehazing network,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2018, pp. 3194–3203
2018
Cited alongside, same era.
Z. Yu, C. Zhao, Z. Wang, Y. Qin, Z. Su, X. Li, F. Zhou, and G. Zhao, “Searching central difference convolutional networks for face anti-spoofing,” in CVPR , 2020, pp. 5294–5304
2020
Later among the works it cites.
Z. Yu, C. Zhao, Z. Wang, Y. Qin, Z. Su, X. Li, F. Zhou, and G. Zhao, “Searching central difference convolutional networks for face anti-spoofing,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2020, pp. 5295–5305
2020
Later among the works it cites.
Z. Yu, J. Wan, Y. Qin, X. Li, S. Z. Li, and G. Zhao, “Nas-fas: Static-dynamic central difference network search for face anti-spoofing,” IEEE transactions on pattern analysis and machine intelligence , vol. 43, no. 9, pp. 3005–3023, 2020
2020
Later among the works it cites.
H. Wu, Y. Qu, S. Lin, J. Zhou, R. Qiao, Z. Zhang, Y. Xie, and L. Ma, “Contrastive learning for compact single image dehazing,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2021, pp. 10 551–10 560
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
S. Woo, J. Park, J.-Y. Lee, and I. S. Kweon, “Cbam: Convolutional block attention module,” in Proceedings of the European conference on computer vision (ECCV) , 2018, pp. 3–19
2018
Cited alongside, same era.
J. Hu, L. Shen, and G. Sun, “Squeeze-and-excitation networks,” in CVPR , 2018, pp. 7132–7141
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 Proceedings of the IEEE conference on computer vision and pattern recognition , 2018, pp. 3253–3261
2018
Cited alongside, same era.
X. Zhang, X. Zhou, M. Lin, and J. Sun, “Shufflenet: An extremely efficient convolutional neural network for mobile devices,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2018, pp. 6848–6856
2018
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, 2018
2018
Cited alongside, same era.
X. Liu, Y. Ma, Z. Shi, and J. Chen, “Griddehazenet: Attention-based multi-scale network for image dehazing,” in Proceedings of the IEEE/CVF international conference on computer vision , 2019, pp. 7314–7323
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.
P. Li, J. Tian, Y. Tang, G. Wang, and C. Wu, “Deep retinex network for single image dehazing,” IEEE Transactions on Image Processing , vol. 30, pp. 1100–1115, 2020
2020
Cited alongside, same era.
2021
Later among the works it cites.
2021
Later among the works it cites.
Z. Yu, Y. Qin, H. Zhao, X. Li, and G. Zhao, “Dual-cross central difference network for face anti-spoofing,” in Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 , Z.-H. Zhou, Ed. International Joint Conferences on Artificial Intelligence Organization, 8 2021, pp. 1281–1287, main Track. [Online]. Available: https://doi.org/10.24963/ijcai.2021/177
2021
Later among the works it cites.
Z. Su, W. Liu, Z. Yu, D. Hu, Q. Liao, Q. Tian, M. Pietikäinen, and L. Liu, “Pixel difference networks for efficient edge detection,” in Proceedings of the IEEE/CVF International Conference on Computer Vision , 2021, pp. 5117–5127
2021
Later among the works it cites.
C. Wang, H.-Z. Shen, F. Fan, M.-W. Shao, C.-S. Yang, J.-C. Luo, and L.-J. Deng, “Eaa-net: A novel edge assisted attention network for single image dehazing,” Knowledge-Based Systems , vol. 228, p. 107279, 2021
2021
Later among the works it cites.
Z. He, G. Fu, Y. Cao, Y. Cao, J. Yang, and X. Li, “Eskn: Enhanced selective kernel network for single image super-resolution,” Signal Processing , vol. 189, p. 108274, 2021
2021
Later among the works it cites.
Y. Liu, L. Zhu, S. Pei, H. Fu, J. Qin, Q. Zhang, L. Wan, and W. Feng, “From synthetic to real: Image dehazing collaborating with unlabeled real data,” in Proceedings of the 29th ACM International Conference on Multimedia , 2021, pp. 50–58
2021
Later among the works it cites.
C.-L. Guo, Q. Yan, S. Anwar, R. Cong, W. Ren, and C. Li, “Image dehazing transformer with transmission-aware 3d position embedding,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2022, pp. 5812–5820
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.
M. Hong, J. Liu, C. Li, and Y. Qu, “Uncertainty-driven dehazing network,” Proceedings of the AAAI Conference on Artificial Intelligence , vol. 36, no. 1, pp. 906–913, Jun. 2022. [Online]. Available: https://ojs.aaai.org/index.php/AAAI/article/view/19973
2022
Later among the works it cites.
Z. He, D. Chen, Y. Cao, J. Yang, Y. Cao, X. Li, S. Tang, Y. Zhuang, and Z. ming Lu, “Single image super‐resolution based on progressive fusion of orientation‐aware features,” Pattern Recognition , vol. 133, p. 109038, 1 2023
2023
Closest in time.