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This paper proposes an image dehazing model built with a convolutional neural network (CNN), called All-in-One Dehazing Network (AOD-Net).
Optics of the atmosphere: scattering by molecules and particles
E. J. McCartney · 1976
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Chromatic framework for vision in bad weather
S. G. Narasimhan and S. K. Nayar · 2000
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Instant dehazing of images using polarization
Y. Y. Schechner, S. G. Narasimhan, and S. K. Nayar · 2001
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Vision and the atmosphere
S. G. Narasimhan and S. K. Nayar · 2002
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Contrast restoration of weather degraded images
S. G. Narasimhan and S. K. Nayar · 2003
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High-accuracy stereo depth maps using structured light
D. Scharstein and R. Szeliski · 2003
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Image quality assessment: from error visibility to structural similarity
Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli · 2004
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The PASCAL Visual Object Classes Challenge 2007 (VOC2007) Results
M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman · 2007
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Evaluation of cost functions for stereo matching
H. Hirschmuller and D. Scharstein · 2007
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Learning conditional random fields for stereo
D. Scharstein and C. Pal · 2007
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Single image dehazing
R. Fattal · 2008
Earlier work this paper cites.
Deep photo: Model-based photograph enhancement and viewing
J. Kopf, B. Neubert, B. Chen, M. Cohen, D. Cohen-Or, O. Deussen, M. Uyttendaele, and D. Lischinski · 2008
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Multi-frame image denoising and stabilization
M. Tico · 2008
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Factorizing scene albedo and depth from a single foggy image
L. Kratz and K. Nishino · 2009
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Fast visibility restoration from a single color or gray level image
J.-P. Tarel and N. Hautiere · 2009
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Polarization: Beneficial for visibility enhancement?
T. Treibitz and Y. Y. Schechner · 2009
Cited alongside, same era.
A multi-frame image super-resolution method
X. Li, Y. Hu, X. Gao, D. Tao, and B. Ning · 2010
Cited alongside, same era.
Single image haze removal using dark channel prior
K. He, J. Sun, and X. Tang · 2011
Cited alongside, same era.
Close the loop: Joint blind image restoration and recognition with sparse representation prior
H. Zhang, J. Yang, Y. Zhang, N. M. Nasrabadi, and T. S. Huang · 2011
Cited alongside, same era.
Bayesian defogging
K. Nishino, L. Kratz, and S. Lombardi · 2012
Cited alongside, same era.
Indoor segmentation and support inference from rgbd images
N. Silberman, D. Hoiem, P. Kohli, and R. Fergus · 2012
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Faster r-cnn: Towards real-time object detection with region proposal networks
S. Ren, K. He, R. Girshick, and J. Sun · 2015
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Self-tuned deep super resolution
Z. Wang, Y. Yang, Z. Wang, S. Chang, W. Han, J. Yang, and T. Huang · 2015
Later among the works it cites.
A fast single image haze removal algorithm using color attenuation prior
Q. Zhu, J. Mai, and L. Shao · 2015
Later among the works it cites.
Non-local image dehazing
D. Berman, S. Avidan, et al · 2016
Later among the works it cites.
Dehazenet: An end-to-end system for single image haze removal
B. Cai, X. Xu, K. Jia, C. Qing, and D. Tao · 2016
Later among the works it cites.
Learning depth from single monocular images using deep convolutional neural fields
F. Liu, C. Shen, G. Lin, and I. Reid · 2016
Later among the works it cites.
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Vision enhancement in homogeneous and heterogeneous fog
J.-P. Tarel, N. Hautiere, L. Caraffa, A. Cord, H. Halmaoui, and D. Gruyer · 2012
Cited alongside, same era.
Image denoising and inpainting with deep neural networks
J. Xie, L. Xu, and E. Chen · 2012
Cited alongside, same era.
Efficient image dehazing with boundary constraint and contextual regularization
G. Meng, Y. Wang, J. Duan, S. Xiang, and C. Pan · 2013
Cited alongside, same era.
On the difficulty of training recurrent neural networks
R. Pascanu, T. Mikolov, and Y. Bengio · 2013
Cited alongside, same era.
Dehazing using color-lines
R. Fattal · 2014
Cited alongside, same era.
Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
Cited alongside, same era.
Single image dehazing via multi-scale convolutional neural networks
W. Ren, S. Liu, H. Zhang, J. Pan, X. Cao, and M.-H. Yang · 2016
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Learning to deblur
C. J. Schuler, M. Hirsch, S. Harmeling, and B. Schölkopf · 2016
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Studying very low resolution recognition using deep networks
Z. Wang, S. Chang, Y. Yang, D. Liu, and T. S. Huang · 2016
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Unitbox: An advanced object detection network
J. Yu, Y. Jiang, Z. Wang, Z. Cao, and T. Huang · 2016
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Air-light estimation using haze-lines
D. Berman, T. Treibitz, and S. Avidan · 2017
Closest in time.
Robust emotion recognition from low quality and low bit rate video: A deep learning approach
B. Cheng, Z. Wang, Z. Zhang, Z. Li, J. Yang, and T. S. Huang · 2017
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Dirty pixels: Optimizing image classification architectures for raw sensor data
S. Diamond, V. Sitzmann, S. Boyd, G. Wetzstein, and F. Heide · 2017
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Aod-net: All-in-one dehazing network
B. Li, X. Peng, Z. Wang, J. Xu, and D. Feng · 2017
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When image denoising meets high-level vision tasks: A deep learning approach
D. Liu, B. Wen, X. Liu, and T. S. Huang · 2017
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