Deep Video Super-Resolution Using HR Optical Flow Estimation
暂无分享,去创建一个
Li Liu | Yulan Guo | Longguang Wang | Zaiping Lin | Wei An | Xinpu Deng | Yulan Guo | Longguang Wang | W. An | Zaiping Lin | Xinpu Deng | Li Liu
[1] Raanan Fattal,et al. Image upsampling via imposed edge statistics , 2007, ACM Trans. Graph..
[2] Luc Van Gool,et al. Is image super-resolution helpful for other vision tasks? , 2015, 2016 IEEE Winter Conference on Applications of Computer Vision (WACV).
[3] Peyman Milanfar,et al. A computationally efficient superresolution image reconstruction algorithm , 2001, IEEE Trans. Image Process..
[4] Alan C. Bovik,et al. Motion Tuned Spatio-Temporal Quality Assessment of Natural Videos , 2010, IEEE Transactions on Image Processing.
[5] Tal Hassner,et al. Face recognition in unconstrained videos with matched background similarity , 2011, CVPR 2011.
[6] Michael J. Black,et al. A Naturalistic Open Source Movie for Optical Flow Evaluation , 2012, ECCV.
[7] Michael Elad,et al. Super-Resolution Without Explicit Subpixel Motion Estimation , 2009, IEEE Transactions on Image Processing.
[8] Xiangyu Zhang,et al. ShuffleNet V2: Practical Guidelines for Efficient CNN Architecture Design , 2018, ECCV.
[9] Ken Turkowski,et al. Filters for common resampling tasks , 1990 .
[10] Renjie Liao,et al. Video Super-Resolution via Deep Draft-Ensemble Learning , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[11] Michael Elad,et al. Generalizing the Nonlocal-Means to Super-Resolution Reconstruction , 2009, IEEE Transactions on Image Processing.
[12] Yun Fu,et al. Residual Dense Network for Image Super-Resolution , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[13] Thomas Brox,et al. End-to-End Learning of Video Super-Resolution with Motion Compensation , 2017, GCPR.
[14] Xiaoou Tang,et al. Learning a Deep Convolutional Network for Image Super-Resolution , 2014, ECCV.
[15] Thomas S. Huang,et al. Coupled Dictionary Training for Image Super-Resolution , 2012, IEEE Transactions on Image Processing.
[16] 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).
[17] Kyung-Ah Sohn,et al. Fast, Accurate, and, Lightweight Super-Resolution with Cascading Residual Network , 2018, ECCV.
[18] Narendra Ahuja,et al. Deep Laplacian Pyramid Networks for Fast and Accurate Super-Resolution , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[19] Renjie Liao,et al. Detail-Revealing Deep Video Super-Resolution , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[20] Thomas Brox,et al. FlowNet: Learning Optical Flow with Convolutional Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[21] Russell C. Hardie,et al. Joint MAP registration and high-resolution image estimation using a sequence of undersampled images , 1997, IEEE Trans. Image Process..
[22] Matthew A. Brown,et al. Frame-Recurrent Video Super-Resolution , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[23] Michael J. Black,et al. Optical Flow Estimation Using a Spatial Pyramid Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[24] Gregory Shakhnarovich,et al. Deep Back-Projection Networks for Super-Resolution , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[25] Richard Szeliski,et al. A Database and Evaluation Methodology for Optical Flow , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[26] Deqing Sun,et al. Ieee Transactions on Pattern Analysis and Machine Intelligence 1 on Bayesian Adaptive Video Super Resolution , 2022 .
[27] Luc Van Gool,et al. The 2017 DAVIS Challenge on Video Object Segmentation , 2017, ArXiv.
[28] Roger Y. Tsai,et al. Multiframe image restoration and registration , 1984 .
[29] Chih-Yuan Yang,et al. Single-Image Super-Resolution: A Benchmark , 2014, ECCV.
[30] Wei Wang,et al. Video Super-Resolution via Bidirectional Recurrent Convolutional Networks , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[31] Yong-Sheng Chen,et al. Pyramid Stereo Matching Network , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[32] Andreas Geiger,et al. Object scene flow for autonomous vehicles , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Enhua Wu,et al. Handling motion blur in multi-frame super-resolution , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[34] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[35] Daniel Rueckert,et al. Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[36] Robert L. Stevenson,et al. Extraction of high-resolution frames from video sequences , 1996, IEEE Trans. Image Process..
[37] Luc Van Gool,et al. Anchored Neighborhood Regression for Fast Example-Based Super-Resolution , 2013, 2013 IEEE International Conference on Computer Vision.
[38] Wei An,et al. Learning for Video Super-Resolution through HR Optical Flow Estimation , 2018, ACCV.
[39] Kyoung Mu Lee,et al. Deeply-Recursive Convolutional Network for Image Super-Resolution , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Manuele Bicego,et al. Unsupervised scene analysis: a hidden Markov model approach , 2006 .
[41] Luc Van Gool,et al. Optical flow based super-resolution: A probabilistic approach , 2007, Comput. Vis. Image Underst..
[42] Alex Kendall,et al. End-to-End Learning of Geometry and Context for Deep Stereo Regression , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[43] Xianming Liu,et al. Robust Video Super-Resolution with Learned Temporal Dynamics , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[44] Jan Kautz,et al. PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[45] Yi Wang,et al. Scale-Recurrent Network for Deep Image Deblurring , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[46] Kyoung Mu Lee,et al. Simultaneous Super-Resolution of Depth and Images Using a Single Camera , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[47] Christian Ledig,et al. Real-Time Video Super-Resolution with Spatio-Temporal Networks and Motion Compensation , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[48] Xiaoou Tang,et al. LiteFlowNet: A Lightweight Convolutional Neural Network for Optical Flow Estimation , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[49] Aggelos K. Katsaggelos,et al. Video Super-Resolution With Convolutional Neural Networks , 2016, IEEE Transactions on Computational Imaging.
[50] Xianming Liu,et al. Learning Temporal Dynamics for Video Super-Resolution: A Deep Learning Approach , 2018, IEEE Transactions on Image Processing.
[51] Eric Dubois,et al. Image up-sampling using total-variation regularization with a new observation model , 2005, IEEE Transactions on Image Processing.
[52] Jian Yang,et al. Image Super-Resolution via Deep Recursive Residual Network , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[53] Moon Gi Kang,et al. Super-resolution image reconstruction: a technical overview , 2003, IEEE Signal Process. Mag..
[54] Seoung Wug Oh,et al. Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[55] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[56] Andreas Geiger,et al. Are we ready for autonomous driving? The KITTI vision benchmark suite , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[57] 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).
[58] Michal Irani,et al. Super-resolution from a single image , 2009, 2009 IEEE 12th International Conference on Computer Vision.