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2020 – today
- 2024
[j16]Bahjat Kawar, Noam Elata, Tomer Michaeli, Michael Elad:
GSURE-Based Diffusion Model Training with Corrupted Data. Trans. Mach. Learn. Res. 2024 (2024)- [j15]Hila Chefer, Shiran Zada, Roni Paiss, Ariel Ephrat, Omer Tov, Michael Rubinstein, Lior Wolf, Tali Dekel, Tomer Michaeli, Inbar Mosseri:
Still-Moving: Customized Video Generation without Customized Video Data. ACM Trans. Graph. 43(6): 244:1-244:11 (2024) - [c64]Amitay Bar, Rotem Mulayoff, Tomer Michaeli, Ronen Talmon:
The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank. AAAI 2024: 20328-20336 - [c63]Rotem Mulayoff, Tomer Michaeli:
Exact Mean Square Linear Stability Analysis for SGD. COLT 2024: 3915-3969 - [c62]Omer Yair, Elias Nehme, Tomer Michaeli:
Uncertainty Visualization via Low-Dimensional Posterior Projections. CVPR 2024: 11041-11051 - [c61]Inbar Huberman-Spiegelglas, Vladimir Kulikov, Tomer Michaeli:
An Edit Friendly DDPM Noise Space: Inversion and Manipulations. CVPR 2024: 12469-12478 - [c60]Noam Elata
, Tomer Michaeli, Michael Elad:
Adaptive Compressed Sensing with Diffusion-Based Posterior Sampling. ECCV (78) 2024: 290-308 - [c59]René Haas, Inbar Huberman-Spiegelglas, Rotem Mulayoff, Stella Graßhof, Sami S. Brandt, Tomer Michaeli:
Discovering Interpretable Directions in the Semantic Latent Space of Diffusion Models. FG 2024: 1-9 - [c58]Noa Cohen, Hila Manor, Yuval Bahat, Tomer Michaeli:
From Posterior Sampling to Meaningful Diversity in Image Restoration. ICLR 2024 - [c57]Hila Manor, Tomer Michaeli:
On the Posterior Distribution in Denoising: Application to Uncertainty Quantification. ICLR 2024 - [c56]Nathaniel Cohen, Vladimir Kulikov, Matan Kleiner, Inbar Huberman-Spiegelglas, Tomer Michaeli:
Slicedit: Zero-Shot Video Editing With Text-to-Image Diffusion Models Using Spatio-Temporal Slices. ICML 2024 - [c55]Hila Manor, Tomer Michaeli:
Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion. ICML 2024 - [c54]Guy Ohayon, Tomer Michaeli, Michael Elad:
The Perception-Robustness Tradeoff in Deterministic Image Restoration. ICML 2024 - [c53]Omer Bar-Tal, Hila Chefer, Omer Tov, Charles Herrmann, Roni Paiss, Shiran Zada, Ariel Ephrat, Junhwa Hur, Guanghui Liu, Amit Raj, Yuanzhen Li, Michael Rubinstein, Tomer Michaeli, Oliver Wang, Deqing Sun, Tali Dekel, Inbar Mosseri:
Lumiere: A Space-Time Diffusion Model for Video Generation. SIGGRAPH Asia 2024: 94:1-94:11 - [c52]Noam Elata, Bahjat Kawar, Tomer Michaeli, Michael Elad:
Nested Diffusion Processes for Anytime Image Generation. WACV 2024: 4995-5004 - [i60]Omer Bar-Tal, Hila Chefer, Omer Tov, Charles Herrmann, Roni Paiss, Shiran Zada, Ariel Ephrat, Junhwa Hur, Yuanzhen Li, Tomer Michaeli, Oliver Wang, Deqing Sun, Tali Dekel, Inbar Mosseri:
Lumiere: A Space-Time Diffusion Model for Video Generation. CoRR abs/2401.12945 (2024) - [i59]Hila Manor, Tomer Michaeli:
Zero-Shot Unsupervised and Text-Based Audio Editing Using DDPM Inversion. CoRR abs/2402.10009 (2024) - [i58]Shahar Yadin, Noam Elata, Tomer Michaeli:
Classification Diffusion Models. CoRR abs/2402.10095 (2024) - [i57]Amitay Bar, Rotem Mulayoff, Tomer Michaeli, Ronen Talmon:
The Expected Loss of Preconditioned Langevin Dynamics Reveals the Hessian Rank. CoRR abs/2402.13810 (2024) - [i56]Nathaniel Cohen, Vladimir Kulikov, Matan Kleiner, Inbar Huberman-Spiegelglas, Tomer Michaeli:
Slicedit: Zero-Shot Video Editing With Text-to-Image Diffusion Models Using Spatio-Temporal Slices. CoRR abs/2405.12211 (2024) - [i55]Guy Ohayon, Michael Elad, Tomer Michaeli:
Perceptual Fairness in Image Restoration. CoRR abs/2405.13805 (2024) - [i54]Elias Nehme, Rotem Mulayoff, Tomer Michaeli:
Hierarchical Uncertainty Exploration via Feedforward Posterior Trees. CoRR abs/2405.15719 (2024) - [i53]Nurit Spingarn-Eliezer, Tomer Michaeli:
Stealing Image-to-Image Translation Models With a Single Query. CoRR abs/2406.00828 (2024) - [i52]Noam Elata, Tomer Michaeli, Michael Elad:
Adaptive Compressed Sensing with Diffusion-Based Posterior Sampling. CoRR abs/2407.08256 (2024) - [i51]Hila Chefer, Shiran Zada, Roni Paiss, Ariel Ephrat, Omer Tov, Michael Rubinstein, Lior Wolf, Tali Dekel, Tomer Michaeli, Inbar Mosseri:
Still-Moving: Customized Video Generation without Customized Video Data. CoRR abs/2407.08674 (2024) - [i50]Noam Elata, Tomer Michaeli, Michael Elad:
Zero-Shot Image Compression with Diffusion-Based Posterior Sampling. CoRR abs/2407.09896 (2024) - [i49]Matan Kleiner, Lior Michaeli, Tomer Michaeli:
Coherence Awareness in Diffractive Neural Networks. CoRR abs/2408.06681 (2024) - [i48]Guy Ohayon, Tomer Michaeli, Michael Elad:
Posterior-Mean Rectified Flow: Towards Minimum MSE Photo-Realistic Image Restoration. CoRR abs/2410.00418 (2024) - 2023
- [c51]Noa Alkobi, Tamar Rott Shaham, Tomer Michaeli:
Internal Diverse Image Completion. CVPR Workshops 2023: 648-658 - [c50]Hagay Michaeli, Tomer Michaeli, Daniel Soudry:
Alias-Free Convnets: Fractional Shift Invariance via Polynomial Activations. CVPR 2023: 16333-16342 - [c49]Mor Shpigel Nacson, Rotem Mulayoff, Greg Ongie, Tomer Michaeli, Daniel Soudry:
The Implicit Bias of Minima Stability in Multivariate Shallow ReLU Networks. ICLR 2023 - [c48]Vladimir Kulikov, Shahar Yadin, Matan Kleiner, Tomer Michaeli:
SinDDM: A Single Image Denoising Diffusion Model. ICML 2023: 17920-17930 - [c47]Guy Ohayon, Theo Joseph Adrai, Michael Elad, Tomer Michaeli:
Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality. ICML 2023: 26474-26494 - [c46]Theo Adrai, Guy Ohayon, Michael Elad, Tomer Michaeli:
Deep Optimal Transport: A Practical Algorithm for Photo-realistic Image Restoration. NeurIPS 2023 - [c45]Dror Freirich, Tomer Michaeli, Ron Meir:
Perceptual Kalman Filters: Online State Estimation under a Perfect Perceptual-Quality Constraint. NeurIPS 2023 - [c44]Elias Nehme, Omer Yair, Tomer Michaeli:
Uncertainty Quantification via Neural Posterior Principal Components. NeurIPS 2023 - [e8]Leonid Karlinsky, Tomer Michaeli, Ko Nishino:
Computer Vision - ECCV 2022 Workshops - Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part I. Lecture Notes in Computer Science 13801, Springer 2023, ISBN 978-3-031-25055-2 [contents] - [e7]Leonid Karlinsky, Tomer Michaeli, Ko Nishino:
Computer Vision - ECCV 2022 Workshops - Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part II. Lecture Notes in Computer Science 13802, Springer 2023, ISBN 978-3-031-25062-0 [contents] - [e6]Leonid Karlinsky, Tomer Michaeli, Ko Nishino:
Computer Vision - ECCV 2022 Workshops - Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part III. Lecture Notes in Computer Science 13803, Springer 2023, ISBN 978-3-031-25065-1 [contents] - [e5]Leonid Karlinsky, Tomer Michaeli, Ko Nishino:
Computer Vision - ECCV 2022 Workshops - Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part IV. Lecture Notes in Computer Science 13804, Springer 2023, ISBN 978-3-031-25068-2 [contents] - [e4]Leonid Karlinsky, Tomer Michaeli, Ko Nishino:
Computer Vision - ECCV 2022 Workshops - Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part V. Lecture Notes in Computer Science 13805, Springer 2023, ISBN 978-3-031-25071-2 [contents] - [e3]Leonid Karlinsky, Tomer Michaeli, Ko Nishino:
Computer Vision - ECCV 2022 Workshops - Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part VI. Lecture Notes in Computer Science 13806, Springer 2023, ISBN 978-3-031-25074-3 [contents] - [e2]Leonid Karlinsky, Tomer Michaeli, Ko Nishino:
Computer Vision - ECCV 2022 Workshops - Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part VII. Lecture Notes in Computer Science 13807, Springer 2023, ISBN 978-3-031-25081-1 [contents] - [e1]Leonid Karlinsky, Tomer Michaeli, Ko Nishino:
Computer Vision - ECCV 2022 Workshops - Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part VIII. Lecture Notes in Computer Science 13808, Springer 2023, ISBN 978-3-031-25084-2 [contents] - [i47]Hagay Michaeli, Tomer Michaeli, Daniel Soudry:
Alias-Free Convnets: Fractional Shift Invariance via Polynomial Activations. CoRR abs/2303.08085 (2023) - [i46]René Haas, Inbar Huberman-Spiegelglas, Rotem Mulayoff, Tomer Michaeli:
Discovering Interpretable Directions in the Semantic Latent Space of Diffusion Models. CoRR abs/2303.11073 (2023) - [i45]Inbar Huberman-Spiegelglas, Vladimir Kulikov, Tomer Michaeli:
An Edit Friendly DDPM Noise Space: Inversion and Manipulations. CoRR abs/2304.06140 (2023) - [i44]Bahjat Kawar, Noam Elata, Tomer Michaeli, Michael Elad:
GSURE-Based Diffusion Model Training with Corrupted Data. CoRR abs/2305.13128 (2023) - [i43]Noam Elata, Bahjat Kawar, Tomer Michaeli, Michael Elad:
Nested Diffusion Processes for Anytime Image Generation. CoRR abs/2305.19066 (2023) - [i42]Theo Adrai, Guy Ohayon, Tomer Michaeli, Michael Elad:
Deep Optimal Transport: A Practical Algorithm for Photo-realistic Image Restoration. CoRR abs/2306.02342 (2023) - [i41]Dror Freirich, Tomer Michaeli, Ron Meir:
Perceptual Kalman Filters: Online State Estimation under a Perfect Perceptual-Quality Constraint. CoRR abs/2306.02400 (2023) - [i40]Rotem Mulayoff, Tomer Michaeli:
Exact Mean Square Linear Stability Analysis for SGD. CoRR abs/2306.07850 (2023) - [i39]Mor Shpigel Nacson, Rotem Mulayoff, Greg Ongie, Tomer Michaeli, Daniel Soudry:
The Implicit Bias of Minima Stability in Multivariate Shallow ReLU Networks. CoRR abs/2306.17499 (2023) - [i38]Hila Manor, Tomer Michaeli:
On the Posterior Distribution in Denoising: Application to Uncertainty Quantification. CoRR abs/2309.13598 (2023) - [i37]Elias Nehme, Omer Yair, Tomer Michaeli:
Uncertainty Quantification via Neural Posterior Principal Components. CoRR abs/2309.15533 (2023) - [i36]Noa Cohen, Hila Manor, Yuval Bahat, Tomer Michaeli:
From Posterior Sampling to Meaningful Diversity in Image Restoration. CoRR abs/2310.16047 (2023) - [i35]Guy Ohayon, Tomer Michaeli, Michael Elad:
The Perception-Robustness Tradeoff in Deterministic Image Restoration. CoRR abs/2311.09253 (2023) - [i34]Omer Yair, Elias Nehme, Tomer Michaeli:
Uncertainty Visualization via Low-Dimensional Posterior Projections. CoRR abs/2312.07804 (2023) - 2022
- [c43]Nurit Spingarn-Eliezer, Ron Banner, Hilla Ben-Yaacov, Elad Hoffer, Tomer Michaeli:
Power Awareness in Low Precision Neural Networks. ECCV Workshops (7) 2022: 67-83 - [c42]Bassel Hamoud, Yuval Bahat, Tomer Michaeli:
Beyond Local Processing: Adapting CNNs for CT Reconstruction. ECCV Workshops (3) 2022: 513-526 - [i33]Nurit Spingarn-Eliezer, Ron Banner, Elad Hoffer, Hilla Ben-Yaacov, Tomer Michaeli:
Energy awareness in low precision neural networks. CoRR abs/2202.02783 (2022) - [i32]Guy Ohayon, Theo Adrai, Michael Elad, Tomer Michaeli:
Reasons for the Superiority of Stochastic Estimators over Deterministic Ones: Robustness, Consistency and Perceptual Quality. CoRR abs/2211.08944 (2022) - [i31]Vladimir Kulikov, Shahar Yadin, Matan Kleiner, Tomer Michaeli:
SinDDM: A Single Image Denoising Diffusion Model. CoRR abs/2211.16582 (2022) - [i30]Idan Kligvasser, Tamar Rott Shaham, Noa Alkobi, Tomer Michaeli:
BlendGAN: Learning and Blending the Internal Distributions of Single Images by Spatial Image-Identity Conditioning. CoRR abs/2212.01589 (2022) - [i29]Noa Alkobi, Tamar Rott Shaham, Tomer Michaeli:
Internal Diverse Image Completion. CoRR abs/2212.10280 (2022) - 2021
- [j14]Michael Peleg, Tomer Michaeli, Shlomo Shamai:
On Information Rates Over a Binary-Input Filtered Gaussian Channel. IEEE Open J. Commun. Soc. 2: 2265-2272 (2021) - [j13]Elias Nehme, Boris Ferdman, Lucien E. Weiss, Tal Naor, Daniel Freedman, Tomer Michaeli, Yoav Shechtman:
Learning Optimal Wavefront Shaping for Multi-Channel Imaging. IEEE Trans. Pattern Anal. Mach. Intell. 43(7): 2179-2192 (2021) - [c41]Idan Kligvasser, Tomer Michaeli:
Sparsity Aware Normalization for GANs. AAAI 2021: 8181-8190 - [c40]Yuval Bahat, Tomer Michaeli:
What's in the Image? Explorable Decoding of Compressed Images. CVPR 2021: 2908-2917 - [c39]Tamar Rott Shaham, Michaël Gharbi, Richard Zhang, Eli Shechtman, Tomer Michaeli:
Spatially-Adaptive Pixelwise Networks for Fast Image Translation. CVPR 2021: 14882-14891 - [c38]Nurit Spingarn, Ron Banner, Tomer Michaeli:
GAN "Steerability" without optimization. ICLR 2021 - [c37]Omer Yair, Tomer Michaeli:
Contrastive Divergence Learning is a Time Reversal Adversarial Game. ICLR 2021 - [c36]Idan Kligvasser, Tamar Rott Shaham, Yuval Bahat, Tomer Michaeli:
Deep Self-Dissimilarities as Powerful Visual Fingerprints. NeurIPS 2021: 3939-3951 - [c35]Rotem Mulayoff, Tomer Michaeli, Daniel Soudry:
The Implicit Bias of Minima Stability: A View from Function Space. NeurIPS 2021: 17749-17761 - [c34]Gal Greshler, Tamar Rott Shaham, Tomer Michaeli:
Catch-A-Waveform: Learning to Generate Audio from a Single Short Example. NeurIPS 2021: 20916-20928 - [c33]Dror Freirich, Tomer Michaeli, Ron Meir:
A Theory of the Distortion-Perception Tradeoff in Wasserstein Space. NeurIPS 2021: 25661-25672 - [i28]Idan Kligvasser, Tomer Michaeli:
Sparsity Aware Normalization for GANs. CoRR abs/2103.02458 (2021) - [i27]Michael Peleg, Tomer Michaeli, Shlomo Shamai:
On information rates over a binary input channel. CoRR abs/2105.06187 (2021) - [i26]Gal Greshler, Tamar Rott Shaham, Tomer Michaeli:
Catch-A-Waveform: Learning to Generate Audio from a Single Short Example. CoRR abs/2106.06426 (2021) - [i25]Dror Freirich, Tomer Michaeli, Ron Meir:
A Theory of the Distortion-Perception Tradeoff in Wasserstein Space. CoRR abs/2107.02555 (2021) - 2020
- [c32]Yuval Bahat, Tomer Michaeli:
Explorable Super Resolution. CVPR 2020: 2713-2722 - [c31]Rotem Mulayoff, Tomer Michaeli:
Unique Properties of Flat Minima in Deep Networks. ICML 2020: 7108-7118 - [i24]Rotem Mulayoff, Tomer Michaeli:
Unique Properties of Wide Minima in Deep Networks. CoRR abs/2002.04710 (2020) - [i23]Yuval Bahat, Tomer Michaeli:
Explorable Decoding of Compressed Images. CoRR abs/2006.09332 (2020) - [i22]Elias Nehme, Boris Ferdman, Lucien E. Weiss, Tal Naor, Daniel Freedman, Tomer Michaeli, Yoav Shechtman:
Learning an optimal PSF-pair for ultra-dense 3D localization microscopy. CoRR abs/2009.14303 (2020) - [i21]Tamar Rott Shaham, Michaël Gharbi, Richard Zhang, Eli Shechtman, Tomer Michaeli:
Spatially-Adaptive Pixelwise Networks for Fast Image Translation. CoRR abs/2012.02992 (2020) - [i20]Omer Yair, Tomer Michaeli:
Contrastive Divergence Learning is a Time Reversal Adversarial Game. CoRR abs/2012.03295 (2020) - [i19]Nurit Spingarn-Eliezer, Ron Banner, Tomer Michaeli:
GAN Steerability without optimization. CoRR abs/2012.05328 (2020)
2010 – 2019
- 2019
- [j12]Rotem Mulayoff, Tomer Michaeli:
On the Minimal Overcompleteness Allowing Universal Sparse Representation. IEEE Trans. Inf. Theory 65(6): 3585-3599 (2019) - [c30]Tamar Rott Shaham, Tali Dekel, Tomer Michaeli:
SinGAN: Learning a Generative Model From a Single Natural Image. ICCV 2019: 4569-4579 - [c29]Adar Elad, Doron Haviv, Yochai Blau, Tomer Michaeli:
Direct Validation of the Information Bottleneck Principle for Deep Nets. ICCV Workshops 2019: 758-762 - [c28]Nirit Nussbaum Hoffer, Tomer Michaeli:
Multispectral Reconstruction From Reference Objects in the Scene. ICCV Workshops 2019: 4350-4358 - [c27]Yochai Blau, Tomer Michaeli:
Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff. ICML 2019: 675-685 - [i18]Yochai Blau, Tomer Michaeli:
Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff. CoRR abs/1901.07821 (2019) - [i17]Tamar Rott Shaham, Tali Dekel, Tomer Michaeli:
SinGAN: Learning a Generative Model from a Single Natural Image. CoRR abs/1905.01164 (2019) - [i16]Yuval Bahat, Tomer Michaeli:
Explorable Super Resolution. CoRR abs/1912.01839 (2019) - 2018
- [c26]Idan Kligvasser, Tamar Rott Shaham, Tomer Michaeli:
xUnit: Learning a Spatial Activation Function for Efficient Image Restoration. CVPR 2018: 2433-2442 - [c25]Tamar Rott Shaham, Tomer Michaeli:
Deformation Aware Image Compression. CVPR 2018: 2453-2462 - [c24]Tamar Rott Shaham, Tomer Michaeli:
Deformation Aware Image Compression. CVPR Workshops 2018: 2583-2586 - [c23]Noam Yair, Tomer Michaeli:
Multi-Scale Weighted Nuclear Norm Image Restoration. CVPR 2018: 3165-3174 - [c22]Yochai Blau, Tomer Michaeli:
The Perception-Distortion Tradeoff. CVPR 2018: 6228-6237 - [c21]Tal Tlusty, Tomer Michaeli, Tali Dekel, Lihi Zelnik-Manor:
Modifying Non-Local Variations Across Multiple Views. CVPR 2018: 6276-6285 - [c20]Yochai Blau, Roey Mechrez, Radu Timofte, Tomer Michaeli, Lihi Zelnik-Manor:
The 2018 PIRM Challenge on Perceptual Image Super-Resolution. ECCV Workshops (5) 2018: 334-355 - [c19]Andrey Zhitnikov, Rotem Mulayoff, Tomer Michaeli:
Revealing Common Statistical Behaviors in Heterogeneous Populations. ICML 2018: 5945-5954 - [c18]Baruch Epstein, Ron Meir, Tomer Michaeli:
Joint Autoencoders: A Flexible Meta-learning Framework. ECML/PKDD (1) 2018: 494-509 - [i15]Tamar Rott Shaham, Tomer Michaeli:
Deformation Aware Image Compression. CoRR abs/1804.04593 (2018) - [i14]Rotem Mulayoff, Tomer Michaeli:
On the Minimal Overcompleteness Allowing Universal Sparse Representation. CoRR abs/1804.04897 (2018) - [i13]Yochai Blau, Roey Mechrez, Radu Timofte, Tomer Michaeli, Lihi Zelnik-Manor:
2018 PIRM Challenge on Perceptual Image Super-resolution. CoRR abs/1809.07517 (2018) - [i12]Idan Kligvasser, Tomer Michaeli:
Dense xUnit Networks. CoRR abs/1811.11051 (2018) - 2017
- [c17]Yochai Blau, Tomer Michaeli:
Non-redundant Spectral Dimensionality Reduction. ECML/PKDD (1) 2017: 256-271 - [i11]Baruch Epstein, Ron Meir, Tomer Michaeli:
Joint auto-encoders: a flexible multi-task learning framework. CoRR abs/1705.10494 (2017) - [i10]Yochai Blau, Tomer Michaeli:
The Perception-Distortion Tradeoff. CoRR abs/1711.06077 (2017) - [i9]Idan Kligvasser, Tamar Rott Shaham, Tomer Michaeli:
xUnit: Learning a Spatial Activation Function for Efficient Image Restoration. CoRR abs/1711.06445 (2017) - 2016
- [c16]Tamar Rott Shaham, Tomer Michaeli:
Visualizing Image Priors. ECCV (6) 2016: 136-153 - [c15]Tomer Michaeli, Weiran Wang, Karen Livescu:
Nonparametric Canonical Correlation Analysis. ICML 2016: 1967-1976 - [i8]Yochai Blau, Tomer Michaeli:
Non-Redundant Spectral Dimensionality Reduction. CoRR abs/1612.03412 (2016) - 2015
- [j11]Tali Dekel, Tomer Michaeli, Michal Irani, William T. Freeman:
Revealing and modifying non-local variations in a single image. ACM Trans. Graph. 34(6): 227:1-227:11 (2015) - [i7]Tomer Michaeli, Weiran Wang, Karen Livescu:
Nonparametric Canonical Correlation Analysis. CoRR abs/1511.04839 (2015) - 2014
- [j10]Daniel Sigalov, Tomer Michaeli, Yaakov Oshman:
LMMSE Filtering in Feedback Systems With White Random Modes: Application to Tracking in Clutter. IEEE Trans. Autom. Control. 59(9): 2549-2554 (2014) - [c14]Tomer Michaeli, Michal Irani:
Blind Deblurring Using Internal Patch Recurrence. ECCV (3) 2014: 783-798 - [c13]