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Rain streaks can severely degrade the visibility, which causes many current computer vision algorithms fail to work.
Speaker verification using adapted gaussian mixture models
Reynolds, D.A., Quatieri, T.F., Dunn, R.B.: · 2000
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Recurrent neural networks for prediction: learning algorithms, architectures and stability
Mandic, D.P., Chambers, J.A., et al.: · 2001
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Detection and removal of rain from videos
Garg, K., Nayar, S.K.: · 2004
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Image quality assessment: from error visibility to structural similarity
Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: · 2004
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When does a camera see rain?
Garg, K., Nayar, S.K.: · 2005
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Rain removal in video by combining temporal and chromatic properties
Zhang, X., Li, H., Qi, Y., Leow, W.K., Ng, T.K.: · 2006
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Vision and rain
Garg, K., Nayar, S.K.: · 2007
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Scope of validity of psnr in image/video quality assessment
Huynh-Thu, Q., Ghanbari, M.: · 2008
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Online dictionary learning for sparse coding
Mairal, J., Bach, F., Ponce, J., Sapiro, G.: · 2009
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Analysis of rain and snow in frequency space
Barnum, P.C., Narasimhan, S., Kanade, T.: · 2010
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Rain or snow detection in image sequences through use of a histogram of orientation of streaks
Bossu, J., Hautière, N., Tarel, J.P.: · 2011
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Context-aware single image rain removal
Huang, D.A., Kang, L.W., Yang, M.C., Lin, C.W., Wang, Y.C.F.: · 2012
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Automatic single-image-based rain streaks removal via image decomposition
Kang, L.W., Lin, C.W., Fu, Y.H.: · 2012
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Robust recovery of subspace structures by low-rank representation
Liu, G., Lin, Z., Yan, S., Sun, J., Yu, Y., Ma, Y.: · 2013
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Rectifier nonlinearities improve neural network acoustic models
Maas, A.L., Hannun, A.Y., Ng, A.Y.: · 2013
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Removal of rain from videos: a review
Tripathi, A.K., Mukhopadhyay, S.: · 2014
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Cho, K., Van Merriënboer, B., Gulcehre, C., Bahdanau, D., Bougares, F., Schwenk, H., Bengio, Y.: · 2014
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Recurrent neural network regularization
Zaremba, W., Sutskever, I., Vinyals, O.: · 2014
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Transformed low-rank model for line pattern noise removal
Chang, Y., Yan, L., Zhong, S.: · 2017
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Removing rain from single images via a deep detail network
Fu, X., Huang, J., Zeng, D., Huang, Y., Ding, X., Paisley, J.: · 2017
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Deep joint rain detection and removal from a single image
Yang, W., Tan, R.T., Feng, J., Liu, J., Guo, Z., Yan, S.: · 2017
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Fast image processing with fully-convolutional networks
Chen, Q., Xu, J., Koltun, V.: · 2017
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Single image deraining using scale-aware multi-stage recurrent network
Li, R., Cheong, L.F., Tan, R.T.: · 2017
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A hierarchical approach for rain or snow removing in a single color image
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Kingma, D.P., Ba, J.: · 2014
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Utilizing local phase information to remove rain from video
Santhaseelan, V., Asari, V.K.: · 2015
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Removing rain from a single image via discriminative sparse coding
Luo, Y., Xu, Y., Ji, H.: · 2015
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Multi-scale context aggregation by dilated convolutions
Yu, F., Koltun, V.: · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Ioffe, S., Szegedy, C.: · 2015
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Rain streak removal using layer priors
Li, Y., Tan, R.T., Guo, X., Lu, J., Brown, M.S.: · 2016
Cited alongside, same era.
Joint rain detection and removal via iterative region dependent multi-task learning
Yang, W., Tan, R.T., Feng, J., Liu, J., Guo, Z., Yan, S.: · 2016
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Wang, Y., Liu, S., Chen, C., Zeng, B.: · 2017
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Joint convolutional analysis and synthesis sparse representation for single image layer separation
Gu, S., Meng, D., Zuo, W., Zhang, L.: · 2017
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Joint bi-layer optimization for single-image rain streak removal
Zhu, L., Fu, C.W., Lischinski, D., Heng, P.A.: · 2017
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Clearing the skies: A deep network architecture for single-image rain removal
Fu, X., Huang, J., Ding, X., Liao, Y., Paisley, J.: · 2017
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Image de-raining using a conditional generative adversarial network
Zhang, H., Sindagi, V., Patel, V.M.: · 2017
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Free-space optical channel models
Kaushal, H., Jain, V., Kar, S.: · 2017
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Squeeze-and-excitation networks
Hu, J., Shen, L., Sun, G.: · 2017
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