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Single image rain streaks removal is extremely important since rainy images adversely affect many computer vision systems.
Boosting and Other Ensemble Methods
Harris Drucker, Corinna Cortes, L. D. Jackel, and Yann Lecun. 1989 · 1989
Earlier work this paper cites.
Stacked regressions
Leo Breiman. 1996 · 1996
Earlier work this paper cites.
Detection and Removal of Rain from Videos. In Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on
Kshitiz Garg and Shree K. Nayar. 2004 · 2004
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli. 2004 · 2004
Earlier work this paper cites.
Analysis of Rain and Snow in Frequency Space
Peter C Barnum, Srinivasa Narasimhan, and Takeo Kanade. 2010 · 2010
Earlier work this paper cites.
Rain or snow detection in image sequences through use of a histogram of orientation of streaks
Jérémie Bossu, Nicolas Hautière, and Jean-Philippe Tarel. 2011 · 2011
Earlier work this paper cites.
Automatic single-image-based rain streaks removal via image decomposition
L. W. Kang, C. W. Lin, and Y. H. Fu. 2012 · 2012
Earlier work this paper cites.
Convolutional-recursive deep learning for 3d object classification. In Advances in Neural Information Processing Systems . 656–664
Richard Socher, Brody Huval, Bharath Bath, Christopher D Manning, and Andrew Y Ng. 2012 · 2012
Earlier work this paper cites.
Understanding deep architectures using a recursive convolutional network
David Eigen, Jason Rolfe, Rob Fergus, and Yann LeCun. 2013 · 2013
Cited alongside, same era.
Video Deraining and Desnowing Using Temporal Correlation and Low-Rank Matrix Completion
J. H. Kim, J. Y. Sim, and C. S. Kim. 2015 · 2015
Cited alongside, same era.
Recurrent convolutional neural network for object recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 3367–3375
Ming Liang and Xiaolin Hu. 2015 · 2015
Cited alongside, same era.
Removing Rain from a Single Image via Discriminative Sparse Coding. In IEEE International Conference on Computer Vision . 3397–3405
Yu Luo, Yong Xu, and Hui Ji. 2015 · 2015
Cited alongside, same era.
Utilizing Local Phase Information to Remove Rain from Video
Varun Santhaseelan and Vijayan K. Asari. 2015 · 2015
Cited alongside, same era.
Rain Streak Removal Using Layer Priors. In CVPR . 2736–2744
Yu Li, Robby T Tan, Xiaojie Guo, Jiangbo Lu, and Michael S. Brown. 2016 · 2016
Later among the works it cites.
Single image dehazing via multi-scale convolutional neural networks. In European conference on computer vision . Springer, 154–169
Wenqi Ren, Si Liu, Hua Zhang, Jinshan Pan, Xiaochun Cao, and Ming-Hsuan Yang. 2016 · 2016
Later among the works it cites.
Clearing the skies: A deep network architecture for single-image rain removal
Xueyang Fu, Jiabin Huang, Xinghao Ding, Yinghao Liao, and John Paisley. 2017a · 2017
Later among the works it cites.
Multi-scale dense convolutional networks for efficient prediction
Gao Huang, Danlu Chen, Tianhong Li, Felix Wu, Laurens van der Maaten, and Kilian Q Weinberger. 2017a · 2017
Later among the works it cites.
An All-in-One Network for Dehazing and Beyond
Boyi Li, Xiulian Peng, Zhangyang Wang, Jizheng Xu, and Dan Feng. 2017 · 2017
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Dehazenet: An end-to-end system for single image haze removal
Bolun Cai, Xiangmin Xu, Kui Jia, Chunmei Qing, and Dacheng Tao. 2016 · 2016
Cited alongside, same era.
Perceptual losses for real-time style transfer and super-resolution. In European Conference on Computer Vision . Springer, 694–711
Justin Johnson, Alexandre Alahi, and Li Fei-Fei. 2016 · 2016
Cited alongside, same era.
Deeply-recursive convolutional network for image super-resolution. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 1637–1645
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee. 2016 · 2016
Cited alongside, same era.
Removing Rain from Single Images via a Deep Detail Network. In CVPR
Xueyang Fu, Jiabin Huang, Delu Zeng, Yue Huang, Xinghao Ding, and John Paisley. 2017b
Cited in the paper.
Deep residual learning for image recognition. In Proceedings of the IEEE conference on computer vision and pattern recognition . 770–778
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016a
Cited in the paper.
Identity mappings in deep residual networks. In European Conference on Computer Vision . Springer, 630–645
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016b
Cited in the paper.
Densely connected convolutional networks. In Proceedings of the IEEE conference on computer vision and pattern recognition , Vol. 1. 3
Gao Huang, Zhuang Liu, Kilian Q Weinberger, and Laurens van der Maaten. 2017b
Cited in the paper.
Later among the works it cites.
Deep joint rain detection and removal from a single image. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition . 1357–1366
Wenhan Yang, Robby T Tan, Jiashi Feng, Jiaying Liu, Zongming Guo, and Shuicheng Yan. 2017 · 2017
Later among the works it cites.
Image de-raining using a conditional generative adversarial network
He Zhang, Vishwanath Sindagi, and Vishal M Patel. 2017 · 2017
Later among the works it cites.