Super-resolution from internet-scale scene matching
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[1] Wojciech Matusik,et al. CG2Real: Improving the Realism of Computer Generated Images Using a Large Collection of Photographs , 2011, IEEE Transactions on Visualization and Computer Graphics.
[2] Wojciech Matusik,et al. Image restoration using online photo collections , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[3] William T. Freeman,et al. Learning Low-Level Vision , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.
[4] Takeo Kanade,et al. Limits on super-resolution and how to break them , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[5] Stephen Lin,et al. Super resolution using edge prior and single image detail synthesis , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[6] Michael J. Black,et al. Fields of Experts: a framework for learning image priors , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).
[7] Alexei A. Efros,et al. Recovering Surface Layout from an Image , 2007, International Journal of Computer Vision.
[8] Alexei A. Efros,et al. Segmenting Scenes by Matching Image Composites , 2009, NIPS.
[9] Michal Irani,et al. Internal statistics of a single natural image , 2011, CVPR 2011.
[10] Raanan Fattal,et al. Image upsampling via imposed edge statistics , 2007, ACM Trans. Graph..
[11] Raanan Fattal,et al. Image upsampling via texture hallucination , 2010, 2010 IEEE International Conference on Computational Photography (ICCP).
[12] Eero P. Simoncelli,et al. Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.
[13] Hans-Peter Seidel,et al. Photo zoom: high resolution from unordered image collections , 2010, SIGGRAPH '10.
[14] Yan Ke,et al. The Design of High-Level Features for Photo Quality Assessment , 2006, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06).
[15] Alexei A. Efros,et al. IM2GPS: estimating geographic information from a single image , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[16] Richard Szeliski,et al. Image deblurring and denoising using color priors , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[17] William T. Freeman,et al. What makes a good model of natural images? , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.
[18] Antonio Torralba,et al. Ieee Transactions on Pattern Analysis and Machine Intelligence 1 80 Million Tiny Images: a Large Dataset for Non-parametric Object and Scene Recognition , 2022 .
[19] Antonio Torralba,et al. Building the gist of a scene: the role of global image features in recognition. , 2006, Progress in brain research.
[20] Jason Lawrence,et al. Building and Using a Database of One Trillion Natural-Image Patches , 2011, IEEE Computer Graphics and Applications.
[21] Richard Szeliski,et al. Video and Image Bayesian Demosaicing with a Two Color Image Prior , 2006, ECCV.
[22] Alexei A. Efros,et al. Scene completion using millions of photographs , 2007, SIGGRAPH 2007.
[23] Richard Szeliski,et al. A content-aware image prior , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[24] Kwang In Kim,et al. Single-Image Super-Resolution Using Sparse Regression and Natural Image Prior , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[25] Harry Shum,et al. Face Hallucination: Theory and Practice , 2007, International Journal of Computer Vision.
[26] William T. Freeman,et al. Example-Based Super-Resolution , 2002, IEEE Computer Graphics and Applications.
[27] Michal Irani,et al. Super-resolution from a single image , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[28] Jitendra Malik,et al. A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics , 2001, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001.
[29] Charless C. Fowlkes,et al. Contour Detection and Hierarchical Image Segmentation , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[30] Michael J. Black,et al. Steerable Random Fields , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[31] Andrew Zisserman,et al. Video Google: a text retrieval approach to object matching in videos , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.
[32] Edward H. Adelson,et al. Exploring features in a Bayesian framework for material recognition , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[33] Krista A. Ehinger,et al. SUN database: Large-scale scene recognition from abbey to zoo , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[34] Yihong Gong,et al. Visual‐Quality Optimizing Super Resolution , 2009, Comput. Graph. Forum.
[35] Jiejie Zhu,et al. Context-constrained hallucination for image super-resolution , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[36] Song-Chun Zhu,et al. Filters, Random Fields and Maximum Entropy (FRAME): Towards a Unified Theory for Texture Modeling , 1998, International Journal of Computer Vision.
[37] Michael Isard,et al. Lost in quantization: Improving particular object retrieval in large scale image databases , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.