Comprehensive image quality assessment via predicting the distribution of opinion score

[1]  Ke Lu,et al.  Transfer Independently Together: A Generalized Framework for Domain Adaptation , 2019, IEEE Transactions on Cybernetics.

[2]  Meng Wang,et al.  A Framework of Joint Low-Rank and Sparse Regression for Image Memorability Prediction , 2019, IEEE Transactions on Circuits and Systems for Video Technology.

[3]  Stephen J. Wright,et al.  Numerical Optimization , 2018, Fundamental Statistical Inference.

[4]  Bin Wang,et al.  Off-the-shelf CNN features for 3D object retrieval , 2018, Multimedia tools and applications.

[5]  Tat-Seng Chua,et al.  Quality Matters: Assessing cQA Pair Quality via Transductive Multi-View Learning , 2018, IJCAI.

[6]  Yu Liu,et al.  CNN-RNN: a large-scale hierarchical image classification framework , 2018, Multimedia Tools and Applications.

[7]  Heng Tao Shen,et al.  Exploring Auxiliary Context: Discrete Semantic Transfer Hashing for Scalable Image Retrieval , 2018, IEEE Transactions on Neural Networks and Learning Systems.

[8]  Zi Huang,et al.  Exploring Consistent Preferences: Discrete Hashing with Pair-Exemplar for Scalable Landmark Search , 2017, ACM Multimedia.

[9]  Ling Shao,et al.  Dynamic Multi-View Hashing for Online Image Retrieval , 2017, IJCAI.

[10]  Alan C. Bovik,et al.  No-Reference Quality Assessment of Tone-Mapped HDR Pictures , 2017, IEEE Transactions on Image Processing.

[11]  Lei Zhu,et al.  Unsupervised Visual Hashing with Semantic Assistant for Content-Based Image Retrieval , 2017, IEEE Transactions on Knowledge and Data Engineering.

[12]  Xuan Wang,et al.  Quality biased multimedia data retrieval in microblogs , 2016, J. Vis. Commun. Image Represent..

[13]  Leon A. Gatys,et al.  Image Style Transfer Using Convolutional Neural Networks , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[14]  Li Fei-Fei,et al.  Perceptual Losses for Real-Time Style Transfer and Super-Resolution , 2016, ECCV.

[15]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[16]  Leon A. Gatys,et al.  A Neural Algorithm of Artistic Style , 2015, ArXiv.

[17]  Xin Geng,et al.  Pre-release Prediction of Crowd Opinion on Movies by Label Distribution Learning , 2015, IJCAI.

[18]  Leon A. Gatys,et al.  Texture Synthesis Using Convolutional Neural Networks , 2015, NIPS.

[19]  Andrea Vedaldi,et al.  MatConvNet: Convolutional Neural Networks for MATLAB , 2014, ACM Multimedia.

[20]  F. Gasparini,et al.  How to assess image quality within a workflow chain: an overview , 2014, International Journal on Digital Libraries.

[21]  Dumitru Erhan,et al.  Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[22]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[23]  Stefan Carlsson,et al.  CNN Features Off-the-Shelf: An Astounding Baseline for Recognition , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops.

[24]  Xin Geng,et al.  Label Distribution Learning , 2013, 2013 IEEE 13th International Conference on Data Mining Workshops.

[25]  Trevor Darrell,et al.  DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition , 2013, ICML.

[26]  C.-C. Jay Kuo,et al.  Color image database TID2013: Peculiarities and preliminary results , 2013, European Workshop on Visual Information Processing (EUVIP).

[27]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[28]  Alan C. Bovik,et al.  No-Reference Image Quality Assessment in the Spatial Domain , 2012, IEEE Transactions on Image Processing.

[29]  Christophe Charrier,et al.  Blind Image Quality Assessment: A Natural Scene Statistics Approach in the DCT Domain , 2012, IEEE Transactions on Image Processing.

[30]  Meng Wang,et al.  Oracle in Image Search: A Content-Based Approach to Performance Prediction , 2012, TOIS.

[31]  Alexandre Bernardino,et al.  Matrix Completion for Multi-label Image Classification , 2011, NIPS.

[32]  Alan C. Bovik,et al.  Blind Image Quality Assessment: From Natural Scene Statistics to Perceptual Quality , 2011, IEEE Transactions on Image Processing.

[33]  Xian-Sheng Hua,et al.  A transductive multi-label learning approach for video concept detection , 2011, Pattern Recognit..

[34]  Timothy N. Rubin,et al.  Statistical topic models for multi-label document classification , 2011, Machine Learning.

[35]  Jan Kautz,et al.  Bitmap Movement Detection: HDR for Dynamic Scenes , 2010, 2010 Conference on Visual Media Production.

[36]  Zhi-Hua Zhou,et al.  Facial Age Estimation by Learning from Label Distributions , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[37]  Gustavo de Veciana,et al.  An information fidelity criterion for image quality assessment using natural scene statistics , 2005, IEEE Transactions on Image Processing.

[38]  Fernando Pérez-Cruz,et al.  SVM multiregression for nonlinear channel estimation in multiple-input multiple-output systems , 2004, IEEE Transactions on Signal Processing.

[39]  M. Werman,et al.  Gradient domain high dynamic range compression , 2002, SIGGRAPH.

[40]  Christine D. Piatko,et al.  A visibility matching tone reproduction operator for high dynamic range scenes , 1997, SIGGRAPH '97.

[41]  Alexander J. Smola,et al.  Support Vector Regression Machines , 1996, NIPS.

[42]  John D. Lafferty,et al.  Inducing Features of Random Fields , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[43]  Haitao Huang,et al.  Abstractive text summarization using LSTM-CNN based deep learning , 2018, Multimedia Tools and Applications.

[44]  Jian Yang,et al.  Coupled-learning convolutional neural networks for object recognition , 2017, Multimedia Tools and Applications.

[45]  Subhasis Chaudhuri,et al.  Bilateral Filter Based Compositing for Variable Exposure Photography , 2009, Eurographics.

[46]  Alex Smola,et al.  Learning with Kernels: support vector machines, regularization, optimization, and beyond , 2001, Adaptive computation and machine learning series.

[47]  Fernando Pérez-Cruz,et al.  Fast Training of Support Vector Classifiers , 2000, NIPS.