-
1
-
-
79953048649
-
Contour detection and hierarchical image segmentation
-
May
-
P. Arbelaez, M. Maire, C. Fowlkes, and J. Malik. Contour detection and hierarchical image segmentation. IEEE TPAMI, 33(5):898-916, May 2011.
-
(2011)
IEEE TPAMI
, vol.33
, Issue.5
, pp. 898-916
-
-
Arbelaez, P.1
Maire, M.2
Fowlkes, C.3
Malik, J.4
-
2
-
-
77749243157
-
Fast motion deblurring
-
Dec.
-
S. Cho and S. Lee. Fast motion deblurring. ACM T. Graphics, 28(5), Dec. 2009.
-
(2009)
ACM T. Graphics
, vol.28
, Issue.5
-
-
Cho, S.1
Lee, S.2
-
4
-
-
77954018368
-
Removing camera shake from a single photograph
-
July
-
R. Fergus, B. Singh, A. Hertzmann, S. T. Roweis, and W. T. Freeman. Removing camera shake from a single photograph. ACM T. Graphics, 3(25):787-794, July 2006.
-
(2006)
ACM T. Graphics
, vol.3
, Issue.25
, pp. 787-794
-
-
Fergus, R.1
Singh, B.2
Hertzmann, A.3
Roweis, S.T.4
Freeman, W.T.5
-
5
-
-
52649143252
-
Practical Poissonian-Gaussian noise modeling and fitting for single-image raw-data
-
Oct.
-
A. Foi, M. Trimeche, V. Katkovnik, and K. Egiazarian. Practical Poissonian-Gaussian noise modeling and fitting for single-image raw-data. IEEE TIP, 17(10):1737-1754, Oct. 2008.
-
(2008)
IEEE TIP
, vol.17
, Issue.10
, pp. 1737-1754
-
-
Foi, A.1
Trimeche, M.2
Katkovnik, V.3
Egiazarian, K.4
-
6
-
-
84887323855
-
How well do filter-based MRFs model natural images?
-
Q. Gao and S. Roth. How well do filter-based MRFs model natural images? In Pattern Recognition (DAGM) 2012.
-
(2012)
Pattern Recognition (DAGM)
-
-
Gao, Q.1
Roth, S.2
-
8
-
-
84881043004
-
Loss-specific training of non-parametric image restoration models: A new state of the art
-
J. Jancsary, S. Nowozin, and C. Rother. Loss-specific training of non-parametric image restoration models: A new state of the art. In ECCV 2012.
-
(2012)
ECCV
-
-
Jancsary, J.1
Nowozin, S.2
Rother, C.3
-
9
-
-
84866674114
-
Regression tree fields - An efficient, non-parametric approach to image labeling problems
-
J. Jancsary, S. Nowozin, T. Sharp, and C. Rother. Regression tree fields - an efficient, non-parametric approach to image labeling problems. In CVPR 2012.
-
(2012)
CVPR
-
-
Jancsary, J.1
Nowozin, S.2
Sharp, T.3
Rother, C.4
-
10
-
-
77956384931
-
Image deblurring using inertial measurement sensors
-
July
-
N. Joshi, S. B. Kang, C. L. Zitnick, and R. Szeliski. Image deblurring using inertial measurement sensors. ACM T. Graphics, 29(4):30:1-30.9, July 2010.
-
(2010)
ACM T. Graphics
, vol.29
, Issue.4
, pp. 301-309
-
-
Joshi, N.1
Kang, S.B.2
Zitnick, C.L.3
Szeliski, R.4
-
12
-
-
84881081051
-
Recording and playback of camera shake: Benchmarking blind deconvolution with a real-world database
-
R. Köhler, M. Hirsch, B. Mohler, B. Schölkopf, and S. Harmeling. Recording and playback of camera shake: benchmarking blind deconvolution with a real-world database. In ECCV 2012.
-
(2012)
ECCV
-
-
Köhler, R.1
Hirsch, M.2
Mohler, B.3
Schölkopf, B.4
Harmeling, S.5
-
13
-
-
84858712496
-
Fast image deconvolution using hyper-Laplacian priors
-
D. Krishnan and R. Fergus. Fast image deconvolution using hyper-Laplacian priors. In NIPS, 2009.
-
(2009)
NIPS
-
-
Krishnan, D.1
Fergus, R.2
-
14
-
-
80052910212
-
Blind deconvolution using a normalized sparsity measure
-
D. Krishnan, T. Tay, and R. Fergus. Blind deconvolution using a normalized sparsity measure. In CVPR 2011.
-
(2011)
CVPR
-
-
Krishnan, D.1
Tay, T.2
Fergus, R.3
-
15
-
-
80052887928
-
Efficient marginal likelihood optimization in blind deconvolution
-
A. Levin, Y.Weiss, F. Durand, andW. T. Freeman. Efficient marginal likelihood optimization in blind deconvolution. In CVPR 2011.
-
(2011)
CVPR
-
-
Levin, A.1
Weiss, Y.2
Durand, F.3
Freeman, W.T.4
-
16
-
-
70450174344
-
Understanding and evaluating blind deconvolution algorithms
-
A. Levin, Y. Weiss, F. Durand, and W. T. Freeman. Understanding and evaluating blind deconvolution algorithms. In CVPR 2009.
-
(2009)
CVPR
-
-
Levin, A.1
Weiss, Y.2
Durand, F.3
Freeman, W.T.4
-
17
-
-
84925395305
-
Blind deblurring using internal patch recurrence
-
T. Michaeli and M. Irani. Blind deblurring using internal patch recurrence. In ECCV 2014.
-
(2014)
ECCV
-
-
Michaeli, T.1
Irani, M.2
-
18
-
-
84911440991
-
Total variation blind deconvolution: The devil is in the details
-
D. Perrone and P. Favaro. Total variation blind deconvolution: The devil is in the details. In CVPR 2014.
-
(2014)
CVPR
-
-
Perrone, D.1
Favaro, P.2
-
19
-
-
84911455347
-
-
arXiv:1404.2086
-
U. Schmidt, J. Jancsary, S. Nowozin, S. Roth, and C. Rother. Cascades of regression tree fields for image restoration. arXiv:1404.2086, 2014.
-
(2014)
Cascades of Regression Tree Fields for Image Restoration
-
-
Schmidt, U.1
Jancsary, J.2
Nowozin, S.3
Roth, S.4
Rother, C.5
-
20
-
-
84911451024
-
Shrinkage fields for effective image restoration
-
U. Schmidt and S. Roth. Shrinkage fields for effective image restoration. In CVPR 2014.
-
(2014)
CVPR
-
-
Schmidt, U.1
Roth, S.2
-
22
-
-
80052912678
-
Bayesian deblurring with integrated noise estimation
-
U. Schmidt, K. Schelten, and S. Roth. Bayesian deblurring with integrated noise estimation. In CVPR 2011.
-
(2011)
CVPR
-
-
Schmidt, U.1
Schelten, K.2
Roth, S.3
-
24
-
-
49249099286
-
High-quality motion deblurring from a single image
-
Aug.
-
Q. Shan, J. Jia, and A. Agarwala. High-quality motion deblurring from a single image. ACM T. Graphics, 27(3), Aug. 2008.
-
(2008)
ACM T. Graphics
, vol.27
, Issue.3
-
-
Shan, Q.1
Jia, J.2
Agarwala, A.3
-
25
-
-
84881080781
-
Edge-based blur kernel estimation using patch priors
-
L. Sun, S. Cho, J. Wang, and J. Hays. Edge-based blur kernel estimation using patch priors. In ICCP 2013.
-
(2013)
ICCP
-
-
Sun, L.1
Cho, S.2
Wang, J.3
Hays, J.4
-
26
-
-
84959244212
-
Good image priors for nonblind deconvolution: Generic vs specific
-
L. Sun, S. Cho, J. Wang, and J. Hays. Good image priors for nonblind deconvolution: Generic vs specific. In ECCV 2014.
-
(2014)
ECCV
-
-
Sun, L.1
Cho, S.2
Wang, J.3
Hays, J.4
-
27
-
-
34948821220
-
Learning Gaussian conditional random fields for low-level vision
-
M. F. Tappen, C. Liu, E. H. Adelson, and W. T. Freeman. Learning Gaussian conditional random fields for low-level vision. In CVPR 2007.
-
(2007)
CVPR
-
-
Tappen, M.F.1
Liu, C.2
Adelson, E.H.3
Freeman, W.T.4
-
31
-
-
84919907377
-
Analysis of Bayesian blind deconvolution
-
D. Wipf and H. Zhang. Analysis of Bayesian blind deconvolution. In EMMCVPR 2013.
-
(2013)
EMMCVPR
-
-
Wipf, D.1
Zhang, H.2
-
32
-
-
80052881205
-
Two-phase kernel estimation for robust motion deblurring
-
L. Xu and J. Jia. Two-phase kernel estimation for robust motion deblurring. In ECCV 2010.
-
(2010)
ECCV
-
-
Xu, L.1
Jia, J.2
-
33
-
-
84887395957
-
Unnatural L0 sparse representation for natural image deblurring
-
L. Xu, S. Zheng, and J. Jia. Unnatural L0 sparse representation for natural image deblurring. In CVPR 2013.
-
(2013)
CVPR
-
-
Xu, L.1
Zheng, S.2
Jia, J.3
-
34
-
-
84856650948
-
From learning models of natural image patches to whole image restoration
-
D. Zoran and Y. Weiss. From learning models of natural image patches to whole image restoration. In ICCV 2011.
-
(2011)
ICCV
-
-
Zoran, D.1
Weiss, Y.2
|