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Rain removal is important for improving the robustness of outdoor vision based systems.
MLESAC: a new robust estimator with application to estimating image geometry
P. H. Torr and A. Zisserman · 2000
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S. G. Narasimhan and S. K. Nayar · 2002
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Detection and removal of rain from videos
K. Garg and S. K. Nayar · 2004
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When does a camera see rain?
K. Garg and S. K. Nayar · 2005
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Rain removal in video by combining temporal and chromatic properties
X. Zhang, H. Li, Y. Qi, W. K. Leow, and T. K. Ng · 2006
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Vision and rain
K. Garg and S. K. Nayar · 2007
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Speeded-Up Robust Features (SURF)
H. Bay, A. Ess, T. Tuytelaars, and L. V. Gool · 2008
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Analysis of rain and snow in frequency space
P. C. Barnum, S. Narasimhan, and T. Kanade · 2009
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Tensor decompositions and applications
T. G. Kolda and B. W. Bader · 2009
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Understanding the difficulty of training deep feedforward neural networks
X. Glorot and Y. Bengio · 2010
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Rain or snow detection in image sequences through use of a histogram of orientation of streaks
J. Bossu, N. Hautière, and J.-P. Tarel · 2011
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SLIC superpixels compared to state-of-the-art superpixel methods
R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Susstrunk · 2012
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Automatic single-image-based rain streaks removal via image decomposition
L.-W. Kang, C.-W. Lin, and Y.-H. Fu · 2012
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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A phase space approach for detection and removal of rain in video
V. Santhaseelan and V. K. Asari · 2012
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Video post processing: low-latency spatiotemporal approach for detection and removal of rain
A. Tripathi and S. Mukhopadhyay · 2012
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SEEDS: Superpixels Extracted via Energy-Driven Sampling
M. Van den Bergh, X. Boix, G. Roig, B. de Capitani, and L. Van Gool · 2012
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Single-image deraining using an adaptive nonlocal means filter
J.-H. Kim, C. Lee, J.-Y. Sim, and C.-S. Kim · 2013
Superpixel segmentation using linear spectral clustering
Z. Li and J. Chen · 2015
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Removing rain from a single image via discriminative sparse coding
Y. Luo, Y. Xu, and H. Ji · 2015
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Utilizing local phase information to remove rain from video
V. Santhaseelan and V. K. Asari · 2015
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Matconvnet: Convolutional neural networks for matlab
A. Vedaldi and K. Lenc · 2015
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Accurate image super-resolution using very deep convolutional networks
J. Kim, J. K. Lee, and K. M. Lee · 2016
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Rain streak removal using layer priors
Y. Li, R. T. Tan, X. Guo, J. Lu, and M. S. Brown · 2016
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Cited alongside, same era.
Single-image-based rain and snow removal using multi-guided filter
X. Zheng, Y. Liao, W. Guo, X. Fu, and X. Ding · 2013
Cited alongside, same era.
Visual depth guided color image rain streaks removal using sparse coding
D.-Y. Chen, C.-C. Chen, and L.-W. Kang · 2014
Cited alongside, same era.
A rain pixel recovery algorithm for videos with highly dynamic scenes
J. Chen and L.-P. Chau · 2014
Cited alongside, same era.
Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
Cited alongside, same era.
Dynamic scene rain removal for moving cameras
C.-H. Tan, J. Chen, and L.-P. Chau · 2014
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
Cited alongside, same era.
Adherent raindrop modeling, detectionand removal in video
S. You, R. T. Tan, R. Kawakami, Y. Mukaigawa, and K. Ikeuchi · 2016
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Removing rain from single images via a deep detail network
X. Fu, J. Huang, D. Z. Y. Huang, X. Ding, and J. Paisley · 2017
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Video desnowing and deraining based on matrix decomposition
W. Ren, J. Tian, Z. Han, A. Chan, and Y. Tang · 2017
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Deep joint rain detection and removal from a single image
W. Yang, R. T. Tan, J. Feng, J. Liu, Z. Guo, and S. Yan · 2017
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Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
K. Zhang, W. Zuo, Y. Chen, D. Meng, and L. Zhang · 2017
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