Chinese Journal of Liquid Crystals and Displays, Volume. 36, Issue 12, 1693(2021)
Motion image deblurring based on depth residual generative adversarial network
[2] [2] PAN J S, SUN D Q, PFISTER H, et al. Blind image deblurring using dark channel prior [C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, NV, USA: IEEE, 2016: 1628-1636.
[3] [3] LEVIN A, WEISS Y, DURAND F, et al. Understanding and evaluating blind deconvolution algorithms [C]//Proceedings of 2009 IEEE Conference on Computer Vision and Pattern Recognition. Miami, FL, USA: IEEE, 2009: 1964-1971.
[4] [4] XU L, REN J S J, LIU C, et al. Deep convolutional neural network for image deconvolution [J]. Advances in Neural Information Processing Systems, 2014, 2: 1790-1798.
[5] [5] SU S C, DELBRACIO M, WANG J, et al. Deep video deblurring for hand-held cameras [C]//Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition. Honolulu, HI, USA: IEEE, 2017: 237-246.
[6] [6] XU L, JIA J Y. Two-phase kernel estimation for robust motion deblurring [C]//Proceedings of the 11th European Conference on Computer Vision. Berlin, Heidelberg: Springer, 2010: 157-170.
[7] [7] YAN Y Y, REN W Q, GUO Y F, et al. Image deblurring via extreme channels prior [C]//Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition. Honolulu, HI, USA: IEEE, 2017: 4003-4011.
[8] [8] NAH S, KIM T H, LEE K M. Deep multi-scale convolutional neural network for dynamic scene deblurring [C]//Proceedings of2017 IEEE Conference on Computer Vision and Pattern Recognition. Honolulu, HI, USA: IEEE, 2017: 3883-3891.
[9] [9] TAO X, GAO H Y, SHEN X Y, et al. Scale-recurrent network for deep image deblurring [C]//Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City, USA: IEEE, 2018: 8174-8182.
[10] [10] GOODFELLOW I, POUGET-ABADIE J, MIRZA M, et al. Generative adversarial networks [J]. Advances in Neural Information Processing Systems, 2014, 27: 2672-2680.
[11] [11] MAO X D, LI Q, XIE H R, et al. Least squares generative adversarial networks [C]//Proceedings of 2017 IEEE International Conference on Computer Vision. Venice, Italy: IEEE, 2017: 2794-2802.
[12] [12] JOHNSON J, ALAHI A, LI F F. Perceptual losses for real-time style transfer and super-resolution [C]//Proceedings of the 14th European Conference on Computer Vision. Amsterdam, The Netherlands: Springer, 2016: 694-711.
[13] [13] KUPYN O, BUDZAN V, MYKHAILYCH M, et al. DeblurGAN: blind motion deblurring using conditional adversarial networks [C]//Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City, USA: IEEE, 2018: 8183-8192.
[14] [14] ZHANG K H, LUO W H, ZHONG Y R, et al. Deblurring by realistic blurring [C]//Proceedings of 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Seattle, WA, USA: IEEE, 2020: 2734-2743.
[15] [15] TAI Y W, CHEN X G, KIM S, et al. Nonlinear camera response functions and image deblurring: theoretical analysis and practice [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, 35(10): 2498-2512.
[16] [16] HIRSCH M, SCHULER C J, HARMELING S, et al. Fast removal of non-uniform camera shake [C]//Proceedings of 2011 International Conference on Computer Vision. Barcelona, Spain: IEEE, 2011: 463-470.
[19] [19] GULRAJANI I, AHMED F, ARJOVSKY M, et al. Improved training of wasserstein GANs [C]//Proceedings of the 31st International Conference on Neural Information Processing Systems. Red Hook, NY, USA: ACM, 2017: 5769-5779.
[20] [20] HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition [C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition. Las Vegas, USA: IEEE, 2016: 770-778.
[21] [21] ISOLA P, ZHU J Y, ZHOU T H, et al. Image-to-image translation with conditional adversarial networks [C]//Proceedings of 2017 IEEE Conference on Computer Vision and Pattern Recognition. Honolulu, HI, USA: IEEE, 2017: 5967-5976.
[22] [22] KIM T H, AHN B, LEE K M. Dynamic scene deblurring [C]//Proceedings of 2013 IEEE International Conference on Computer Vision. Sydney, NSW, Australia: IEEE, 2013: 3160-3167.
[23] [23] WIESCHOLLEK P, HIRSCH M, SCHLKOPF B, et al. Learning blind motion deblurring [C]//Proceedings of 2017 IEEE International Conference on Computer Vision. Venice, Italy: IEEE, 2017: 231-240.
[24] [24] LAI W S, HUANG J B, HU Z, et al. A comparative study for single image blind deblurring [C]//Proceedings of 2016 IEEE Conference on Computer Vision and Pattern Recognition. LAS Vegas, USA: IEEE, 2016: 1701-1709.
[25] [25] KIM T H, LEE K M, SCHLKOPF B, et al. Online video deblurring via dynamic temporal blending network [C]//Proceedings of 2017 IEEE International Conference on Computer Vision. Venice, Italy: IEEE, 2017: 4058-4067.
[26] [26] SUN J, CAO W F, XU Z B, et al. Learning a convolutional neural network for non-uniform motion blur removal [C]//Proceedings of 2015 IEEE Conference on Computer Vision and Pattern Recognition. Boston, MA, USA: IEEE, 2015: 769-777.
[27] [27] KRISHNAN D, TAY T, FERGUS R. Blind deconvolution using a normalized sparsity measure [C]//Proceedings of the CVPR 2011. Colorado Springs, USA: IEEE, 2011: 233-240.
[28] [28] WHYTE O, SIVIC J, ZISSERMAN A, et al. Non-uniform deblurring for shaken images [C]//Proceedings of 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Francisco, California, USA: IEEE, 2010: 491-498.
[29] [29] XU L, ZHENG S C, JIA J Y. Unnatural L0 sparse representation for natural image deblurring [C]//Proceedings of 2013 IEEE Conference on Computer Vision and Pattern Recognition. Portland, Oregon, USA: IEEE, 2013: 1107-1114.
Get Citation
Copy Citation Text
WEI Bing-cai, ZHANG Li-ye, MENG Xiao-liang, WANG Kang-tao. Motion image deblurring based on depth residual generative adversarial network[J]. Chinese Journal of Liquid Crystals and Displays, 2021, 36(12): 1693
Category:
Received: Apr. 8, 2021
Accepted: --
Published Online: Jan. 1, 2022
The Author Email: WEI Bing-cai (1394594109@qq.com)