Fetching the paper…
Reading the bibliography…
Image motion blur results from a combination of object motions and camera shakes, and such blurring effect is generally directional and non-uniform.
R. Fergus, B. Singh, A. Hertzmann, S. T. Roweis, and W. T. Freeman, “Removing camera shake from a single photograph,”
2006
Earlier work this paper cites.
Q. Shan, J. Jia, and A. Agarwala, “High-quality motion deblurring from a single image,”
2008
Earlier work this paper cites.
S. Cho and S. Lee, “Fast motion deblurring,”
2009
Earlier work this paper cites.
N. Joshi, C. L. Zitnick, R. Szeliski, and D. J. Kriegman, “Image deblurring and denoising using color priors,” in
2009
Earlier work this paper cites.
L. Xu and J. Jia, “Two-phase kernel estimation for robust motion deblurring,” in
2010
Earlier work this paper cites.
A. Gupta, N. Joshi, L. Zitnick, M. Cohen, and B. Curless, “Single image deblurring using motion density functions,” in
2010
Earlier work this paper cites.
S. Harmeling, H. Michael, and B. Schölkopf, “Space-variant single-image blind deconvolution for removing camera shake,” in
2010
Earlier work this paper cites.
O. Whyte, J. Sivic, A. Zisserman, and J. Ponce, “Non-uniform deblurring for shaken images,” in
2010
Earlier work this paper cites.
M. Hirsch, C. J. Schuler, S. Harmeling, and B. Schölkopf, “Fast removal of non-uniform camera shake,” in
2011
Earlier work this paper cites.
T. H. Kim and K. M. Lee, “Segmentation-free dynamic scene deblurring,” in
2014
Earlier work this paper cites.
J. Pan, Z. Hu, Z. Su, and M. Yang, “Deblurring text images via l0-regularized intensity and gradient prior,” in
2014
Earlier work this paper cites.
D. Tian and D. Tao, “Coupled learning for facial deblur,”
2016
Earlier work this paper cites.
S. Nah, T. H. Kim, and K. M. Lee, “Deep multi-scale convolutional neural network for dynamic scene deblurring,” in
2017
Earlier work this paper cites.
Y. Yan, W. Ren, Y. Guo, R. Wang, and X. Cao, “Image deblurring via extreme channels prior,” in
2017
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin, “Attention is all you need,” in
2017
Earlier work this paper cites.
2017
Cited alongside, same era.
W.-S. Lai, J.-B. Huang, N. Ahuja, and M.-H. Yang, “Deep laplacian pyramid networks for fast and accurate super-resolution,” in
2017
Cited alongside, same era.
X. Xu, J. Pan, Y.-J. Zhang, and M.-H. Yang, “Motion blur kernel estimation via deep learning,”
2018
Cited alongside, same era.
X. Tao, H. Gao, X. Shen, J. Wang, and J. Jia, “Scale-recurrent network for deep image deblurring,” in
2018
Cited alongside, same era.
J. Pan, D. Sun, H. Pfister, and M.-H. Yang, “Deblurring images via dark channel prior,” in
2018
Cited alongside, same era.
L. Chen, F. Fang, T. Wang, and G. Zhang, “Blind image deblurring with local maximum gradient prior,” in
2019
Later among the works it cites.
O. Kupyn, T. Martyniuk, J. Wu, and Z. Wang, “Deblurgan-v2: Deblurring (orders-of-magnitude) faster and better,” in
2019
Later among the works it cites.
Z. Shen, W. Wang, J. Shen, H. Ling, T. Xu, and L. Shao, “Human-aware motion deblurring,” in
2019
Later among the works it cites.
R. Yasarla, F. Perazzi, and V. M. Patel, “Deblurring face images using uncertainty guided multi-stream semantic networks,”
2020
Later among the works it cites.
D. Park, D. U. Kang, J. Kim, and S. Y. Chun, “Multi-temporal recurrent neural networks for progressive non-uniform single image deblurring with incremental temporal training,” in
2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
O. Kupyn, V. Budzan, M. Mykhailych, D. Mishkin, and J. Matas, “Deblurgan: Blind motion deblurring using conditional adversarial networks,” in
2018
Cited alongside, same era.
N. Parmar, A. Vaswani, J. Uszkoreit, Ł. Kaiser, N. Shazeer, A. Ku, and D. Tran, “Image transformer,”
2018
Cited alongside, same era.
J. Hu, L. Shen, and G. Sun, “Squeeze-and-excitation networks,” in
2018
Cited alongside, same era.
X. Wang, R. Girshick, A. Gupta, and K. He, “Non-local neural networks,” in
2018
Cited alongside, same era.
S. Liu, D. Huang, and a. Wang, “Receptive field block net for accurate and fast object detection,” in
2018
Cited alongside, same era.
H. Lee, C. Jung, and C. Kim, “Blind deblurring of text images using a text-specific hybrid dictionary,”
2019
Cited alongside, same era.
L. Pan, Y. Dai, M. Liu, F. Porikli, and Q. Pan, “Joint stereo video deblurring, scene flow estimation and moving object segmentation,”
2019
Cited alongside, same era.
J. Cai, W. Zuo, and L. Zhang, “Dark and bright channel prior embedded network for dynamic scene deblurring,”
2020
Later among the works it cites.
M. Suin, K. Purohit, and A. N. Rajagopalan, “Spatially-attentive patch-hierarchical network for adaptive motion deblurring,” in
2020
Later among the works it cites.
K. Purohit and A. N. Rajagopalan, “Region-adaptive dense network for efficient motion deblurring,” in
2020
Later among the works it cites.
Y. Yuan, W. Su, and D. Ma, “Efficient dynamic scene deblurring using spatially variant deconvolution network with optical flow guided training,” in
2020
Later among the works it cites.
L. Li, J. Pan, W.-S. Lai, C. Gao, N. Sang, and M.-H. Yang, “Dynamic scene deblurring by depth guided model,”
2020
Later among the works it cites.
Q. Hou, L. Zhang, M.-M. Cheng, and J. Feng, “Strip Pooling: Rethinking spatial pooling for scene parsing,” in
2020
Later among the works it cites.
2020
Later among the works it cites.
S. W. Zamir, A. Arora, S. Khan, M. Hayat, F. S. Khan, M.-H. Yang, and L. Shao, “Multi-stage progressive image restoration,” in
2021
Closest in time.
S.-J. Cho, S.-W. Ji, J.-P. Hong, S.-W. Jung, and S.-J. Ko, “Rethinking coarse-to-fine approach in single image deblurring,” in
2021
Closest in time.