暂无分享,去创建一个
Wei An | Yulan Guo | Longguang Wang | Zaiping Lin | Xinpu Deng | Yulan Guo | Longguang Wang | W. An | Zaiping Lin | Xinpu Deng
[1] Vincent Dumoulin,et al. Deconvolution and Checkerboard Artifacts , 2016 .
[2] Xianming Liu,et al. Learning Temporal Dynamics for Video Super-Resolution: A Deep Learning Approach , 2018, IEEE Transactions on Image Processing.
[3] Luc Van Gool,et al. A Probabilistic Approach to Optical Flow based Super-Resolution , 2004, 2004 Conference on Computer Vision and Pattern Recognition Workshop.
[4] Yunsong Li,et al. Robust Interpolation of Correspondences for Large Displacement Optical Flow , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Enhua Wu,et al. Handling motion blur in multi-frame super-resolution , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[6] Peyman Milanfar,et al. A computationally efficient superresolution image reconstruction algorithm , 2001, IEEE Trans. Image Process..
[7] Alan C. Bovik,et al. Motion Tuned Spatio-Temporal Quality Assessment of Natural Videos , 2010, IEEE Transactions on Image Processing.
[8] Yun Fu,et al. Residual Dense Network for Image Super-Resolution , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[9] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[10] J.-Y. Bouguet,et al. Pyramidal implementation of the lucas kanade feature tracker , 1999 .
[11] 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.
[12] 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).
[13] Michael Elad,et al. Super-Resolution Without Explicit Subpixel Motion Estimation , 2009, IEEE Transactions on Image Processing.
[14] Jian Yang,et al. Image Super-Resolution via Deep Recursive Residual Network , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[15] Deqing Sun,et al. Ieee Transactions on Pattern Analysis and Machine Intelligence 1 on Bayesian Adaptive Video Super Resolution , 2022 .
[16] Eirikur Agustsson,et al. NTIRE 2017 Challenge on Single Image Super-Resolution: Dataset and Study , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW).
[17] Renjie Liao,et al. Detail-Revealing Deep Video Super-Resolution , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[18] Luc Van Gool,et al. The 2017 DAVIS Challenge on Video Object Segmentation , 2017, ArXiv.
[19] Manuele Bicego,et al. Unsupervised scene analysis: a hidden Markov model approach , 2006 .
[20] Luc Van Gool,et al. Optical flow based super-resolution: A probabilistic approach , 2007, Comput. Vis. Image Underst..
[21] Kilian Q. Weinberger,et al. Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[22] Thomas Brox,et al. FlowNet: Learning Optical Flow with Convolutional Networks , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[23] Michael Elad,et al. Generalizing the Nonlocal-Means to Super-Resolution Reconstruction , 2009, IEEE Transactions on Image Processing.
[24] 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).
[25] Matthew A. Brown,et al. Frame-Recurrent Video Super-Resolution , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[26] Michael J. Black,et al. Optical Flow Estimation Using a Spatial Pyramid Network , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Raanan Fattal,et al. Image and video upscaling from local self-examples , 2011, TOGS.
[28] 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).
[29] Raanan Fattal,et al. Image upsampling via imposed edge statistics , 2007, ACM Trans. Graph..
[30] Stephen Wolf,et al. Video Quality Model for Variable Frame Delay (VQM_VFD) , 2011 .
[31] Xinbo Gao,et al. Fast and Accurate Single Image Super-Resolution via Information Distillation Network , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[32] Bernhard Schölkopf,et al. EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis , 2016, 2017 IEEE International Conference on Computer Vision (ICCV).
[33] 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.
[34] Renjie Liao,et al. Video Super-Resolution via Deep Draft-Ensemble Learning , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[35] Thomas Brox,et al. FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[36] 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.
[37] Aggelos K. Katsaggelos,et al. Video Super-Resolution With Convolutional Neural Networks , 2016, IEEE Transactions on Computational Imaging.
[38] Thomas Brox,et al. End-to-End Learning of Video Super-Resolution with Motion Compensation , 2017, GCPR.
[39] Xiaoou Tang,et al. Learning a Deep Convolutional Network for Image Super-Resolution , 2014, ECCV.
[40] 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).
[41] Xianming Liu,et al. Robust Video Super-Resolution with Learned Temporal Dynamics , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[42] 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).