参考文献/References:
[1] LEI Sen,SHI Zhenwei,ZOU Zhengxia.Coupled adversarial training for remote sensing image super-resolution[J].IEEE Transactions on Geoscience and Remote Sensing,2020,58(5):3633-3643.DOI:10.1109/TGRS.2019.29590 20.
[2] LYU Qing,SHAN Hongming,WANG Ge.MRI super-resolution with ensemble learning and complementary priors[J].IEEE Transactions on Computational Imaging,2020,6:615-624.DOI:10.1109/TCI.2020.2964201.
[3] ZHU Jianqing,ZENG Huanqiang,HUANG Jingchang,et al.Vehicle re-identification using quadruple directional deep learning features[J].IEEE Transactions on Intelligent Transportation Systems,2020,21(1):410-420.DOI:10.1109/TITS.2019.2901312.
[4] CHEN Jin,CHEN Jun,WANG Zheng,et al.Identity-aware face super-resolution for low-resolution face recognition[J].IEEE Signal Processing Letters,2020,27:645-649.DOI:10.1109/LSP.2020.2986942.
[5] KEYS R.Cubic convolution interpolation for digital image processing[J].IEEE Transactions on Acoustics, Speech, and Signal Processing,1981,29(6):1153-1160.DOI:10.1109/TASSP.1981.1163711.
[6] FATTAL R.Image upsampling via imposed edge statistics[J].ACM Transactions on Graphics,2007,26(3):95.DOI:10.1145/1276377.1276496.
[7] AKHTAR N,SHAFAIT F,MIAN A.Bayesian sparse representation for hyperspectral image super resolution[C]//IEEE Conference on Computer Vision and Pattern Recognition.Boston:IEEE Press,2015:3631-3640.DOI:10.1109/CVPR.2015.7298986.
[8] ZHANG Kaibing,GAO Xinbo,TAO Dacheng,et al.Image super-resolution via non-local steering kernel regression regularization[C]//IEEE International Conference on Image Processing.Melbourne:IEEE Press,2013:943-946.DOI:10.1109/ICIP.2013.6738195.
[9] WANG Lingfeng,XIANG Shiming MENG Gaofeng,et al.Edge-directed single-image super-resolution via adaptive gradient magnitude self-interpolation[J].IEEE Transactions on Circuits and Systems for Video Technology,2013,23(8):1289-1299.DOI:10.1109/TCSVT.2013.2240915.
[10] TIMOFTE R,DESMET V,VANGOOL L.A+: Adjusted anchored neighborhood regression for fast super-resolution[C]//Asian Conference on Computer Vision.Singapore:Springer,2014:111-126.DOI:10.1007/978-3-319-16817-3_8.
[11] YANG Jianchao,WRIGHT J,HUANG T S,et al.Image super-resolution via sparse representation[J].IEEE Transactions on Image Processing,2010,19(11):2861-2873.DOI:10.1109/TIP.2010.2050625.
[12] DONG Chao,LOY C C,HE Kaiming,et al.Image super-resolution using deep convolutional networks[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2016,38(2):295-307.DOI:10.1109/TPAMI.2015.2439281.
[13] KIM J,LEE J K,LEE K M.Accurate image super-resolution using very deep convolutional networks[C]//IEEE Conference on Computer Vision and Pattern Recognition.Las Vegas:IEEE Press,2016:1646-1654.DOI:10.1109/CVPR.2016.182.
[14] DONG Chao,LOY C C,TANG Xiaoou.Accelerating the super-resolution convolutional neural network[C]//European Conference on Computer Vision.Amsterdam:Springer,2016:391-407.DOI:10.1007/978-3-319-46475-6_25.
[15] WAI Weisheng,HUANG Jiabin,AHUJA N,et al.Deep laplacian pyramid networks for fast and accurate super-resolution[C]//IEEE Conference on Computer Vision and Pattern Recognition.Honolulu:IEEE Press,2017:5835-5843.DOI:10.1109/CVPR.2017.618.
[16] LIM B,SON S,KIM H,et al.Enhanced deep residual networks for single image super-resolution[C]//IEEE Conference on Computer Vision and Pattern Recognition Workshops.Honolulu:IEEE Press,2017:1132-1140.DOI:10.1109/CVPRW.2017.151.
[17] LEDIG C,THEIS L,HUSZáR F,et al.Photo-realistic single image super-resolution using a generative adversarial network[C]//IEEE Conference on Computer Vision and Pattern Recognition.Honolulu:IEEE Press,2017:105-114.DOI:10.1109/CVPR.2017.19.
[18] HARIS M,SHAKHNAROVICH G,UKITA N.Deep back-projection networks for super-resolution[C]//IEEE/CVF Conference on Computer Vision and Pattern Recognition.Salt Lake City:IEEE Press,2018:1664-1673.DOI:10.1109/CVPR.2018.00179.
[19] ZHANG Yulun,LI Kunpeng,LI Kai,et al.Image super-resolution using very deep residual channel attention networks[C]//Proceedings of the European Conference on Computer Vision.Munich:Springer,2018:294-310.DOI:10.1007/978-3-030-01234-2_18.
[20] ZHANG Yulun,LI Kunpeng,LI Kai,et al.Residual non-local attention networks for image restoration[C]//International Conference on Learning Representations.New Orleans:[s.n.],2019:1-18.
[21] HE Xiangyu,MO Zitao, WANG Peisong, et al. ODE-inspired network design for single image super-resolution[C]//IEEE/CVF Conference on Computer Vision and Pattern Recognition.Long Beach:IEEE Press,2019:1732-1741.DOI:10.1109/CVPR.2019.00183.
[22] YE Xinchen,SUN Baoli,WANG Zhihui,et al.PMBANet: Progressive multi-branch aggregation network for scene depth super-resolution[J].IEEE Transactions on Image Processing,2020,29:7427-7442.DOI:10.1109/TIP.2020.3002664.
[23] YE Xinchen,SUN Baoli,WANG Zhihui,et al.Depth super-resolution via deep controllable slicing network[C]//Proceedings of the 28th ACM International Conference on Multimedia.Seattle:ACM,2020:1809-1818.DOI:10.1145/3394171.3413874.
[24] SALIMANS T,KINGMA D P.Weight normalization: A simple reparameterization to accelerate training of deep neural networks[C]//Advances in Neural Information Processing Systems.Barcelona:Curran Associates Inc,2016:901-909.
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