Face super-resolution via bilayer contextual representation

[1]  S T Roweis,et al.  Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.

[2]  Takeo Kanade,et al.  Hallucinating faces , 2000, Proceedings Fourth IEEE International Conference on Automatic Face and Gesture Recognition (Cat. No. PR00580).

[3]  S. Saitoh.  Theory of Reproducing Kernels , 2003 .

[4]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[5]  Wen Gao,et al.  The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[6]  Yihong Gong,et al.  Nonlinear Learning using Local Coordinate Coding , 2009, NIPS.

[7]  C. Thomaz,et al.  A new ranking method for principal components analysis and its application to face image analysis , 2010, Image Vis. Comput..

[8]  Chun Qi,et al.  Hallucinating face by position-patch , 2010, Pattern Recognit..

[9]  Thomas S. Huang,et al.  Image Super-Resolution Via Sparse Representation , 2010, IEEE Transactions on Image Processing.

[10]  Ruimin Hu,et al.  Position-Patch Based Face Hallucination via Locality-Constrained Representation , 2012, 2012 IEEE International Conference on Multimedia and Expo.

[11]  Ruimin Hu,et al.  Locality-constraint iterative neighbor embedding for face hallucination , 2013, 2013 IEEE International Conference on Multimedia and Expo (ICME).

[12]  S. Yau,et al.  Variational Principles for Minkowski Type Problems, Discrete Optimal Transport, and Discrete Monge-Ampere Equations , 2013, 1302.5472.

[13]  Xuelong Li,et al.  A Comprehensive Survey to Face Hallucination , 2013, International Journal of Computer Vision.

[14]  Kin-Man Lam,et al.  Fast super-resolution based on weighted collaborative representation , 2014, 2014 19th International Conference on Digital Signal Processing.

[15]  Anil K. Jain,et al.  Nighttime face recognition at large standoff: Cross-distance and cross-spectral matching , 2014, Pattern Recognit..

[16]  Fei Zhou,et al.  Face hallucination via position-based dictionaries coding in kernel feature space , 2014, 2014 International Conference on Smart Computing.

[17]  Ruimin Hu,et al.  Face Hallucination Via Weighted Adaptive Sparse Regularization , 2014, IEEE Transactions on Circuits and Systems for Video Technology.

[18]  Thomas S. Huang,et al.  Deep Networks for Image Super-Resolution with Sparse Prior , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[19]  Wenhan Yang,et al.  Image super-resolution via nonlocal similarity and group structured sparse representation , 2015, 2015 Visual Communications and Image Processing (VCIP).

[20]  Xiaoou Tang,et al.  Image Super-Resolution Using Deep Convolutional Networks , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[21]  Dong Yue,et al.  Locality-Constrained Double Low-Rank Representation for Effective Face Hallucination , 2016, IEEE Access.

[22]  Xinbo Gao,et al.  Image super-resolution using non-local Gaussian process regression , 2016, Neurocomputing.

[23]  Xiaoou Tang,et al.  Deep Cascaded Bi-Network for Face Hallucination , 2016, ECCV.

[24]  Kyoung Mu Lee,et al.  Accurate Image Super-Resolution Using Very Deep Convolutional Networks , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[25]  Michael Elad,et al.  Con-Patch: When a Patch Meets Its Context , 2016, IEEE Transactions on Image Processing.

[26]  Zheng Wang,et al.  SRLSP: A Face Image Super-Resolution Algorithm Using Smooth Regression With Local Structure Prior , 2017, IEEE Transactions on Multimedia.

[27]  Zixiang Xiong,et al.  DLML: Deep linear mappings learning for face super-resolution with nonlocal-patch , 2017, 2017 IEEE International Conference on Multimedia and Expo (ICME).

[28]  Zixiang Xiong,et al.  AWCR: Adaptive and Weighted Collaborative Representations for Face Super-Resolution with Context Residual-Learning , 2017, PCM.

[29]  Bin Li,et al.  Face Hallucination and Recognition Using Kernel Canonical Correlation Analysis , 2017, ICONIP.

[30]  Tao Lu,et al.  Robust Face Super-Resolution via Locality-Constrained Low-Rank Representation , 2017, IEEE Access.

[31]  Mudar Sarem,et al.  A Mixed Non-local Prior Model for Image Super-resolution Reconstruction , 2017 .

[32]  Christian Ledig,et al.  Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[33]  Hao Wang,et al.  Face hallucination using region-based deep convolutional networks , 2017, 2017 IEEE International Conference on Image Processing (ICIP).

[34]  Guoying Zhao,et al.  Hallucinating Face Image by Regularization Models in High-Resolution Feature Space , 2018, IEEE Transactions on Image Processing.

[35]  Yi Yu,et al.  Deep CNN Denoiser and Multi-layer Neighbor Component Embedding for Face Hallucination , 2018, IJCAI.

[36]  Shing-Tung Yau,et al.  Geometric Understanding of Deep Learning , 2018, ArXiv.

[37]  Yi Yu,et al.  Graph-Regularized Locality-Constrained Joint Dictionary and Residual Learning for Face Sketch Synthesis , 2019, IEEE Transactions on Image Processing.

[38]  Shing-Tung Yau,et al.  A Geometric View of Optimal Transportation and Generative Model , 2017, Comput. Aided Geom. Des..