Learning Deep Non-blind Image Deconvolution Without Ground Truths
暂无分享,去创建一个
[1] Hui Ji,et al. Supplementary Materials for “Self-supervised Deep Image Restoration via Adaptive Stochastic Gradient Langevin Dynamics” , 2022 .
[2] Hui Ji,et al. Nonblind Image Deconvolution via Leveraging Model Uncertainty in An Untrained Deep Neural Network , 2022, International Journal of Computer Vision.
[3] Yuhui Quan,et al. Recorrupted-to-Recorrupted: Unsupervised Deep Learning for Image Denoising , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[4] B. Schiele,et al. Learning Spatially-Variant MAP Models for Non-blind Image Deblurring , 2021, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[5] Mike E. Davies,et al. Equivariant Imaging: Learning Beyond the Range Space , 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV).
[6] Tom Tirer,et al. BP-DIP: A Backprojection based Deep Image Prior , 2020, 2020 28th European Signal Processing Conference (EUSIPCO).
[7] Stefan Roth,et al. Deep Wiener Deconvolution: Wiener Meets Deep Learning for Image Deblurring , 2021, NeurIPS.
[8] J. Ponce,et al. End-to-end Interpretable Learning of Non-blind Image Deblurring , 2020, ECCV.
[9] Hui Ji,et al. Deep Learning for Handling Kernel/model Uncertainty in Image Deconvolution , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[10] Yuhui Quan,et al. Variational-EM-Based Deep Learning for Noise-Blind Image Deblurring , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[11] K. Batenburg,et al. Noise2Inverse: Self-Supervised Deep Convolutional Denoising for Tomography , 2020, IEEE Transactions on Computational Imaging.
[12] Stamatios Lefkimmiatis,et al. Microscopy Image Restoration with Deep Wiener-Kolmogorov filters , 2019, ECCV.
[13] Jong Chul Ye,et al. CycleGAN With a Blur Kernel for Deconvolution Microscopy: Optimal Transport Geometry , 2019, IEEE Transactions on Computational Imaging.
[14] Yuhui Quan,et al. Self-supervised Bayesian Deep Learning for Image Recovery with Applications to Compressive Sensing , 2020, ECCV.
[15] Hakan Bilen,et al. Image Deconvolution with Deep Image and Kernel Priors , 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).
[16] Zhihao Xia,et al. Training Image Estimators without Image Ground-Truth , 2019, NeurIPS.
[17] Yide Zhang,et al. A Poisson-Gaussian Denoising Dataset With Real Fluorescence Microscopy Images , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[18] Guangming Shi,et al. Denoising Prior Driven Deep Neural Network for Image Restoration , 2018, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[19] Mirabela Rusu,et al. A deep learning-based algorithm for 2-D cell segmentation in microscopy images , 2018, BMC Bioinformatics.
[20] A. N. Rajagopalan,et al. Non-blind Deblurring: Handling Kernel Uncertainty with CNNs , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[21] Se Young Chun,et al. Training Deep Learning based Denoisers without Ground Truth Data , 2018, NeurIPS.
[22] Wei Liu,et al. Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation , 2018, NeurIPS.
[23] David Zhang,et al. Partial Deconvolution With Inaccurate Blur Kernel , 2018, IEEE Transactions on Image Processing.
[24] Carsten Rother,et al. Learning to Push the Limits of Efficient FFT-Based Image Deconvolution , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[25] Matthias Zwicker,et al. Deep Mean-Shift Priors for Image Restoration , 2017, NIPS.
[26] Stefan Roth,et al. Noise-Blind Image Deblurring , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[27] Wangmeng Zuo,et al. Learning Deep CNN Denoiser Prior for Image Restoration , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Michael Möller,et al. Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[29] Rynson W. H. Lau,et al. Learning Fully Convolutional Networks for Iterative Non-blind Deconvolution , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[30] Stephen Becker,et al. Efficient Adjoint Computation for Wavelet and Convolution Operators [Lecture Notes] , 2016, IEEE Signal Processing Magazine.
[31] Deqing Sun,et al. Blind Image Deblurring Using Dark Channel Prior , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[32] Narendra Ahuja,et al. A Comparative Study for Single Image Blind Deblurring , 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[33] Sebastian Nowozin,et al. Cascades of Regression Tree Fields for Image Restoration , 2014, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[34] Guangyong Chen,et al. An Efficient Statistical Method for Image Noise Level Estimation , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[35] David Zhang,et al. Patch Group Based Nonlocal Self-Similarity Prior Learning for Image Denoising , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[36] Zuowei Shen,et al. Data-Driven Multi-scale Non-local Wavelet Frame Construction and Image Recovery , 2014, Journal of Scientific Computing.
[37] Jian Sun,et al. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[38] Michal Irani,et al. Blind Deblurring Using Internal Patch Recurrence , 2014, ECCV.
[39] Daniele Perrone,et al. Total Variation Blind Deconvolution: The Devil Is in the Details , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[40] Ming-Hsuan Yang,et al. Deblurring Text Images via L0-Regularized Intensity and Gradient Prior , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.
[41] Li Xu,et al. Unnatural L0 Sparse Representation for Natural Image Deblurring , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[42] Sunghyun Cho,et al. Edge-based blur kernel estimation using patch priors , 2013, IEEE International Conference on Computational Photography (ICCP).
[43] Lei Zhang,et al. Nonlocally Centralized Sparse Representation for Image Restoration , 2013, IEEE Transactions on Image Processing.
[44] Kang Wang,et al. Robust Image Deblurring With an Inaccurate Blur Kernel , 2012, IEEE Transactions on Image Processing.
[45] Andrew Zisserman,et al. Deblurring Shaken and Partially Saturated Images , 2011, International Journal of Computer Vision.
[46] Qionghai Dai,et al. Exploring aligned complementary image pair for blind motion deblurring , 2011, CVPR 2011.
[47] Frédo Durand,et al. Efficient marginal likelihood optimization in blind deconvolution , 2011, CVPR 2011.
[48] Charless C. Fowlkes,et al. Contour Detection and Hierarchical Image Segmentation , 2011, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[49] Li Xu,et al. Two-Phase Kernel Estimation for Robust Motion Deblurring , 2010, ECCV.
[50] Rob Fergus,et al. Fast Image Deconvolution using Hyper-Laplacian Priors , 2009, NIPS.
[51] Seungyong Lee,et al. Fast motion deblurring , 2009, ACM Trans. Graph..
[52] Jian-Feng Cai,et al. High-quality curvelet-based motion deblurring from an image pair , 2009, 2009 IEEE Conference on Computer Vision and Pattern Recognition.
[53] Alessandro Foi,et al. Image Denoising by Sparse 3-D Transform-Domain Collaborative Filtering , 2007, IEEE Transactions on Image Processing.
[54] Shree K. Nayar,et al. Motion-based motion deblurring , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.