Light Field Super-Resolution: A Benchmark
暂无分享,去创建一个
Dong Liu | Zhiwei Xiong | Zhen Cheng | Chang Chen | Dong Liu | Zhiwei Xiong | C. Chen | Zhen Cheng
[1] Alexei A. Efros,et al. Occlusion-Aware Depth Estimation Using Light-Field Cameras , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[2] Andrew Lumsdaine,et al. Superresolution with the focused plenoptic camera , 2011, Electronic Imaging.
[3] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[4] In-So Kweon,et al. Learning a Deep Convolutional Network for Light-Field Image Super-Resolution , 2015, 2015 IEEE International Conference on Computer Vision Workshop (ICCVW).
[5] Eero P. Simoncelli,et al. Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.
[6] Ravi Ramamoorthi,et al. A Light Transport Framework for Lenslet Light Field Cameras , 2015, TOGS.
[7] Tieniu Tan,et al. LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution , 2018, IEEE Transactions on Image Processing.
[8] E. Adelson,et al. The Plenoptic Function and the Elements of Early Vision , 1991 .
[9] Lennart Wietzke,et al. Single lens 3D-camera with extended depth-of-field , 2012, Electronic Imaging.
[10] Ting-Chun Wang,et al. Learning-based view synthesis for light field cameras , 2016, ACM Trans. Graph..
[11] Pascal Frossard,et al. Graph-based light field super-resolution , 2017, 2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP).
[12] Dong Liu,et al. LF-fusion: Dense and accurate 3D reconstruction from light field images , 2017, 2017 IEEE Visual Communications and Image Processing (VCIP).
[13] P. Hanrahan,et al. Light Field Photography with a Hand-held Plenoptic Camera , 2005 .
[14] Yochai Blau,et al. The Perception-Distortion Tradeoff , 2017, CVPR.
[15] Ashok Veeraraghavan,et al. Light field denoising, light field superresolution and stereo camera based refocussing using a GMM light field patch prior , 2012, 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.
[16] Xiaoou Tang,et al. Learning a Deep Convolutional Network for Image Super-Resolution , 2014, ECCV.
[17] Yan Yuan,et al. Light-Field Image Superresolution Using a Combined Deep CNN Based on EPI , 2018, IEEE Signal Processing Letters.
[18] Qionghai Dai,et al. Light Field Reconstruction Using Deep Convolutional Network on EPI , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Ashok Veeraraghavan,et al. Improving resolution and depth-of-field of light field cameras using a hybrid imaging system , 2014, 2014 IEEE International Conference on Computational Photography (ICCP).
[20] Dong Liu,et al. Light field super-resolution using internal and external similarities , 2017, 2017 IEEE International Conference on Image Processing (ICIP).
[21] Kyoung Mu Lee,et al. Enhanced Deep Residual Networks for Single Image Super-Resolution , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[22] Tieniu Tan,et al. End-to-End View Synthesis for Light Field Imaging with Pseudo 4DCNN , 2018, ECCV.
[23] Chih-Yuan Yang,et al. Learning a No-Reference Quality Metric for Single-Image Super-Resolution , 2016, Comput. Vis. Image Underst..
[24] W. Freeman,et al. Understanding Camera Trade-Offs through a Bayesian Analysis of Light Field Projections , 2008, ECCV.
[25] In-So Kweon,et al. Accurate depth map estimation from a lenslet light field camera , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[26] Luc Van Gool,et al. NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[27] Sven Wanner,et al. Datasets and Benchmarks for Densely Sampled 4D Light Fields , 2013, VMV.
[28] Stefan B. Williams,et al. Decoding, Calibration and Rectification for Lenselet-Based Plenoptic Cameras , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[29] Michal Irani,et al. Super-resolution from a single image , 2009, 2009 IEEE 12th International Conference on Computer Vision.
[30] Pascal Frossard,et al. A Nonsmooth Graph-Based Approach to Light Field Super-Resolution , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).
[31] Lei Zhang,et al. An edge-guided image interpolation algorithm via directional filtering and data fusion , 2006, IEEE Transactions on Image Processing.
[32] Alexei A. Efros,et al. The Unreasonable Effectiveness of Deep Features as a Perceptual Metric , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[33] Touradj Ebrahimi,et al. New Light Field Image Dataset , 2016, QoMEX 2016.
[34] Bahadir K. Gunturk,et al. Spatial and Angular Resolution Enhancement of Light Fields Using Convolutional Neural Networks , 2017, IEEE Transactions on Image Processing.
[35] J. P. Luke,et al. Simultaneous estimation of super-resolved depth and all-in-focus images from a plenoptic camera , 2009, 2009 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video.
[36] Aljoscha Smolic,et al. Light field denoising by sparse 5D transform domain collaborative filtering , 2017, 2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP).
[37] Xiaoming Chen,et al. Fast Light Field Reconstruction with Deep Coarse-to-Fine Modeling of Spatial-Angular Clues , 2018, ECCV.
[38] Tom E. Bishop,et al. The Light Field Camera: Extended Depth of Field, Aliasing, and Superresolution , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[39] Sven Wanner,et al. Variational Light Field Analysis for Disparity Estimation and Super-Resolution , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[40] Yoshua Bengio,et al. Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach , 2011, ICML.
[41] Touradj Ebrahimi,et al. JPEG Pleno: Toward an Efficient Representation of Visual Reality , 2016, IEEE MultiMedia.
[42] Saber Farag,et al. A NOVEL DISPARITY-ASSISTED BLOCK MATCHING-BASED APPROACH FOR SUPER-RESOLUTION OF LIGHT FIELD IMAGES , 2018, 2018 - 3DTV-Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON).
[43] Reuben A. Farrugia,et al. Super Resolution of Light Field Images Using Linear Subspace Projection of Patch-Volumes , 2017, IEEE Journal of Selected Topics in Signal Processing.
[44] Lu Fang,et al. Combining Exemplar-Based Approach and learning-Based Approach for Light Field Super-Resolution Using a Hybrid Imaging System , 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).
[45] Ming Yang,et al. 3D Convolutional Neural Networks for Human Action Recognition , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[46] Seong-Deok Lee,et al. Improving the spatail resolution based on 4D light field data , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).
[47] Alexei A. Efros,et al. A 4D Light-Field Dataset and CNN Architectures for Material Recognition , 2016, ECCV.
[48] Aljoscha Smolic,et al. Light Field Super-Resolution via LFBM5D Sparse Coding , 2018, 2018 25th IEEE International Conference on Image Processing (ICIP).
[49] Dong Liu,et al. Two-stage convolutional neural network for light field super-resolution , 2017, 2017 IEEE International Conference on Image Processing (ICIP).
[50] Rama Chellappa,et al. Domain adaptation for object recognition: An unsupervised approach , 2011, 2011 International Conference on Computer Vision.
[51] Dong Liu,et al. Unsupervised Depth Estimation from Light Field Using a Convolutional Neural Network , 2018, 2018 International Conference on 3D Vision (3DV).
[52] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[53] Edmond Boyer,et al. FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[54] Lu Fang,et al. Cross-Scale Reference-Based Light Field Super-Resolution , 2018, IEEE Transactions on Computational Imaging.