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Recovering sharp video sequence from a motion-blurred image is highly ill-posed due to the significant loss of motion information in the blurring process.
The Nadaraya-Watson Kernel regression function estimator
H. J. Bierens · 1988
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Fast motion deblurring
S. Cho and S. Lee · 2009
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Two-phase kernel estimation for robust motion deblurring
L. Xu and J. Jia · 2010
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Fast removal of non-uniform camera shake
M. Hirsch, C. J. Schuler, S. Harmeling, and B. Schölkopf · 2011
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Dynamic scene deblurring
T. H. Kim, B. Ahn, and K. M. Lee · 2013
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Discriminative non-blind deblurring
U. Schmidt, C. Rother, S. Nowozin, J. Jancsary, and S. Roth · 2013
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Reconstructing surfaces of particle-based fluids using anisotropic kernels
J. Yu and G. Turk · 2013
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Non-uniform camera shake removal using a spatially-adaptive sparse penalty
H. Zhang and D. P. Wipf · 2013
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Blind deblurring using internal patch recurrence
T. Michaeli and M. Irani · 2014
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Flownet: Learning optical flow with convolutional networks
A. Dosovitskiy, P. Fischer, E. Ilg, P. Häusser, C. Hazirbas, V. Golkov, P. van der Smagt, D. Cremers, and T. Brox · 2015
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Convolutional LSTM network: A machine learning approach for precipitation nowcasting
X. Shi, Z. Chen, H. Wang, D.-Y. Yeung, W.-K. Wong, and W.-C. Woo · 2015
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Learning a convolutional neural network for non-uniform motion blur removal
J. Sun, W. Cao, Z. Xu, and J. Ponce · 2015
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Discriminative learning of iteration-wise priors for blind deconvolution
W. Zuo, D. Ren, S. Gu, L. Lin, and L. Zhang · 2015
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Simultaneous optical flow and intensity estimation from an event camera
P. Bardow, A. J. Davison, and S. Leutenegger · 2016
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A neural approach to blind motion deblurring
A. Chakrabarti · 2016
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Blind image deblurring using dark channel prior
J.-S. Pan, D. Sun, H. Pfister, and M.-H. Yang · 2016
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Learning high-order filters for efficient blind deconvolution of document photographs
L. Xiao, J. Wang, W. Heidrich, and M. Hirsch · 2016
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Non-uniform blind deblurring by reblurring
Y. Bahat, N. Efrat, and M. Irani · 2017
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Blind image deblurring with outlier handling
J. Dong, J. Pan, Z. Su, and M.-H. Yang · 2017
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From motion blur to motion flow: A deep learning solution for removing heterogeneous motion blur
D. Gong, J. Yang, L. Liu, Y. Zhang, I. D. Reid, C. Shen, A. Hengel, and Q. Shi · 2017
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Image-to-image translation with conditional adversarial networks
P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros · 2017
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Video frame synthesis using deep voxel flow
Z. Liu, R. A. Yeh, X. Tang, Y. Liu, and A. Agarwala · 2017
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Deep multi-scale convolutional neural network for dynamic scene deblurring
S. Nah, T. H. Kim, and K. M. Lee · 2017
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Blur-invariant deep learning for blind-deblurring
T. M. Nimisha, A. K. Singh, and A. N. Rajagopalan · 2017
Learning blind video temporal consistency
W.-S. Lai, J.-B. Huang, O. Wang, E. Shechtman, E. Yumer, and M.-H. Yang · 2018
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Adaptive time-slice block-matching optical flow algorithm for dynamic vision sensors
M. Liu and T. Delbrück · 2018
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Event-based moving object detection and tracking
A. Mitrokhin, C. Fermüller, C. Parameshwara, and Y. Aloimonos · 2018
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Real-time intensity-image reconstruction for event cameras using manifold regularisation
G. Munda, C. Reinbacher, and T. Pock · 2018
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Learn to See by Events: RGB Frame Synthesis from Event Cameras
S. Pini, G. Borghi, R. Vezzani, and R. Cucchiara · 2018
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Long-term object tracking with a moving event camera
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Motion deblurring in the wild
M. Noroozi, P. Chandramouli, and P. Favaro · 2017
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Learning discriminative data fitting functions for blind image deblurring
J. Pan, J. Dong, Y.-W. Tai, Z. Su, and M.-H. Yang · 2017
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Simultaneous stereo video deblurring and scene flow estimation
L. Pan, Y. Dai, M. Liu, and F. Porikli · 2017
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Joint estimation of camera pose, depth, deblurring, and super-resolution from a blurred image sequence
H. Park and K. M. Lee · 2017
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Video deblurring via semantic segmentation and pixel-wise non-linear kernel
W. Ren, J. Pan, X. Cao, and M.-H. Yang · 2017
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Learning blind motion deblurring
P. Wieschollek, M. Hirsch, B. Schölkopf, and H. P. A. Lensch · 2017
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B. Ramesh, S. Zhang, Z. W. Lee, Z. Gao, G. Orchard, and C. Xiang · 2018
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ESIM: an open event camera simulator
H. Rebecq, D. Gehrig, and D. Scaramuzza · 2018
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Continuous-time intensity estimation using event cameras
C. Scheerlinck, N. Barnes, and R. Mahony · 2018
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Photorealistic Image Reconstruction from Hybrid Intensity and Event based Sensor
P. A. Shedligeri and K. Mitra · 2018
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Scale-recurrent network for deep image deblurring
X. Tao, H. Gao, X. Shen, J. Wang, and J. Jia · 2018
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Unsupervised Learning of Dense Optical Flow, Depth and Egomotion from Sparse Event Data
C. Ye, A. Mitrokhin, C. Fermüller, J. A. Yorke, and Y. Aloimonos · 2018
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Dynamic scene deblurring using spatially variant recurrent neural networks
J. Zhang, J. Pan, J. S. J. Ren, Y. Song, L. Bao, R. W. H. Lau, and M.-H. Yang · 2018
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Realtime time synchronized event-based stereo
A. Z. Zhu, Y. Chen, and K. Daniilidis · 2018
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Event-based High Dynamic Range Image and Very High Frame Rate Video Generation using Conditional Generative Adversarial Networks
Y.-S. Ho L. Wang, S. M. Mostafavi and K.-J. Yoon · 2019
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Bringing a blurry frame alive at high frame-rate with an event camera
L. Pan, C. Scheerlinck, X. Yu, R. Hartley, M. Liu, and Y. Dai · 2019
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Events-to-video: Bringing modern computer vision to event cameras
H. Rebecq, R. Ranftl, V. Koltun, and D. Scaramuzza · 2019
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Deep stacked hierarchical multi-patch network for image deblurring
H. Zhang, Y. Dai, H. Li, and P. Koniusz · 2019
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