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Extreme Channel Prior Embedded Network for Dynamic Scene Deblurring [article]

Jianrui Cai, Wangmeng Zuo, Lei Zhang
2019 arXiv   pre-print
In this work, we propose an Extreme Channel Prior embedded Network (ECPeNet) to plug the extreme channel priors (i.e., priors on dark and bright channels) into a network architecture for effective dynamic  ...  Recent years have witnessed the significant progress on convolutional neural networks (CNNs) in dynamic scene deblurring.  ...  extreme (i.e., dark and bright) channel priors into a deep CNN for dynamic scene deblurring.  ... 
arXiv:1903.00763v1 fatcat:vtko6lhyi5cancefrjhxocflz4

Adaptive Single Image Deblurring [article]

Maitreya Suin, Kuldeep Purohit, A. N. Rajagopalan
2022 arXiv   pre-print
This paper tackles the problem of dynamic scene deblurring.  ...  Extensive qualitative and quantitative comparisons with prior art on deblurring benchmarks demonstrate the superiority of the proposed network.  ...  Deep multi-scale convolutional neural network for dynamic scene deblurring. In CVPR, volume 1, page 3, 2017. Wenjie Luo, Yujia Li, Raquel Urtasun, and Richard Zemel.  ... 
arXiv:2201.00155v1 fatcat:jexcg67nqfgefi63zja27aj2xe

Single Image Deblurring and Camera Motion Estimation with Depth Map [article]

Liyuan Pan, Yuchao Dai, Miaomiao Liu
2019 arXiv   pre-print
~We formulate our joint deblurring and 6 DoF camera motion estimation as an energy minimization problem which is solved in an alternative manner.  ...  ~In the real world, such blur is mainly caused by both the camera motion and the complex scene structure.  ...  [28] and extreme channel prior [44] ).  ... 
arXiv:1903.00231v1 fatcat:lsh664wqfrcr5g6lu5zhrsaegy

Deblurring Turbulent Images via Maximizing L1 Regularization

Lizhen Duan, Shuhan Sun, Jianlin Zhang, Zhiyong Xu
2021 Symmetry  
A blind image deblurring algorithm is needed, and a favorable image prior is the key to solving this problem.  ...  Then, a novel soft suppression strategy is designed for the deblurring algorithm to inhibit artifacts. A coarse-to-fine scheme and a non-blind algorithm are also constructed.  ...  Additionally, a dark and bright channel prior was also embedded into a network for dynamic scene deblurring [29] .  ... 
doi:10.3390/sym13081414 fatcat:peooua72yzegfhb3qkbqevggbm

Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring [article]

Seungjun Nah, Tae Hyun Kim, Kyoung Mu Lee
2018 arXiv   pre-print
Non-uniform blind deblurring for general dynamic scenes is a challenging computer vision problem as blurs arise not only from multiple object motions but also from camera shake, scene depth variation.  ...  With the proposed model trained on this dataset, we demonstrate empirically that our method achieves the state-of-the-art performance in dynamic scene deblurring not only qualitatively, but also quantitatively  ...  Thus, to solve those problems, in this work, we propose a novel end-to-end deep learning approach for dynamic scene deblurring.  ... 
arXiv:1612.02177v2 fatcat:7z735fss4nd5to2wwf7hahzfem

Learning to Extract a Video Sequence from a Single Motion-Blurred Image [article]

Meiguang Jin, Givi Meishvili, Paolo Favaro
2018 arXiv   pre-print
We also address the ill-posedness of deblurring by designing a network with a large receptive field and implemented via resampling to achieve a higher computational efficiency.  ...  This lets a neural network choose during training what frame to output among the possible combinations.  ...  [35] present an extremely effective image prior by combining the bright and dark channel priors of Pan et al. [26] . Michaeli et al.  ... 
arXiv:1804.04065v1 fatcat:cy7xmjzwdfattpza5abczcb2ta

Learning to Extract a Video Sequence from a Single Motion-Blurred Image

Meiguang Jin, Givi Meishvili, Paolo Favaro
2018 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition  
We also address the ill-posedness of deblurring by designing a network with a large receptive field and implemented via resampling to achieve a higher computational efficiency.  ...  This lets a neural network choose during training what frame to output among the possible combinations.  ...  [35] present an extremely effective image prior by combining the bright and dark channel priors of Pan et al. [26] . Michaeli et al.  ... 
doi:10.1109/cvpr.2018.00663 dblp:conf/cvpr/JinMF18 fatcat:dxqqg6oogra5tatqlg3tu3lzja

Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring

Seungjun Nah, Tae Hyun Kim, Kyoung Mu Lee
2017 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)  
Non-uniform blind deblurring for general dynamic scenes is a challenging computer vision problem as blurs arise not only from multiple object motions but also from camera shake, scene depth variation.  ...  With the proposed model trained on this dataset, we demonstrate empirically that our method achieves the state-of-the-art performance in dynamic scene deblurring not only qualitatively, but also quantitatively  ...  Thus, to solve those problems, in this work, we propose a novel end-to-end deep learning approach for dynamic scene deblurring.  ... 
doi:10.1109/cvpr.2017.35 dblp:conf/cvpr/NahKL17 fatcat:x45ep4255vdfnafqrugmtyahyi

Motion deblurring of faces [article]

Grigorios G. Chrysos and Paolo Favaro and Stefanos Zafeiriou
2018 arXiv   pre-print
The proposed model includes two parallel streams (sub-networks): the first deblurs the image, the second implicitly extracts and projects the identity of both the sharp and the blurred image in similar  ...  The averaged images originate from a 2MF2 dataset with 10 million facial frames, which we introduce for the task.  ...  In contrast to the gradient-based priors, Pan et al (2016) introduce a prior based on the sparsity of the dark channel.  ... 
arXiv:1803.03330v1 fatcat:brknallxwndr5dhjag2zellaru

Motion Deblurring of Faces

Grigorios G. Chrysos, Paolo Favaro, Stefanos Zafeiriou
2018 International Journal of Computer Vision  
The averaged images originate from the 2M F 2 dataset with 19 million facial frames, which we introduce for the task.  ...  A much less standing mode of variation is motion deblurring, which however presents substantial challenges in face analysis.  ...  In contrast to the gradient-based priors, Pan et al. (2016) introduce a prior based on the sparsity of the dark channel.  ... 
doi:10.1007/s11263-018-1138-7 fatcat:c74d5teeavhqln7bwmj5uassu4

Phase-only Image Based Kernel Estimation for Single-image Blind Deblurring [article]

Liyuan Pan, Richard Hartley, Miaomiao Liu, Yuchao Dai
2019 arXiv   pre-print
Therefore, the estimation of the blur kernel is essentially important for blind image deblurring.  ...  Unlike existing approaches which focus on approaching the problem by enforcing various priors on the blur kernel and the latent image, we are aiming at obtaining a high quality blur kernel directly by  ...  Acknowledgement This research was supported in part by Australia Centre for Robotic Vision (CE140100016), the Australian Research Council grants (DE140100180, DE180100628) and the Natural Science Foundation  ... 
arXiv:1811.10185v3 fatcat:xted4brixfejhpgufzpciwt4na

Phase-Only Image Based Kernel Estimation for Single Image Blind Deblurring

Liyuan Pan, Richard Hartley, Miaomiao Liu, Yuchao Dai
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)  
Therefore, the estimation of the blur kernel is essentially important for blind image deblurring.  ...  Unlike existing approaches which focus on approaching the problem by enforcing various priors on the blur kernel and the latent image, we are aiming at obtaining a high quality blur kernel directly by  ...  Acknowledgement This research was supported in part by Australia Centre for Robotic Vision (CE140100016), the Australian Research Council grants (DE140100180, DE180100628) and the Natural Science Foundation  ... 
doi:10.1109/cvpr.2019.00619 dblp:conf/cvpr/PanHLD19 fatcat:mbv7uzwcxjhurkrgseczwmmx7a

EDVR: Video Restoration with Enhanced Deformable Convolutional Networks [article]

Xintao Wang, Kelvin C.K. Chan, Ke Yu, Chao Dong, Chen Change Loy
2019 arXiv   pre-print
In this work, we propose a novel Video Restoration framework with Enhanced Deformable networks, termed EDVR, to address these challenges.  ...  Video restoration tasks, including super-resolution, deblurring, etc, are drawing increasing attention in the computer vision community.  ...  We thank Yapeng Tian for providing the core codes of TDAN [40] .  ... 
arXiv:1905.02716v1 fatcat:6bl4zdhvxfhldmfc76ie4gbkoe

Spectral Norm Regularization for Blind Image Deblurring

Shuhan Sun, Zhiyong Xu, Jianlin Zhang
2021 Symmetry  
Therefore, the SN of an image can effectively help image deblurring in various scenes, such as text, face, natural, and saturated images.  ...  BDA-SN builds a deblurring estimator for the image degradation process by investigating the inherent properties of SN and an image gradient.  ...  [33] developed an improved deep multi-patch hierarchical network that has a powerful and complex representation for dynamic scene deblurring. Almansour et al.  ... 
doi:10.3390/sym13101856 fatcat:cw2gd2upg5evbpvjvrvfatr3ia

Learn to model blurry motion via directional similarity and filtering

Wenbin Li, Da Chen, Zhihan Lv, Yan Yan, Darren Cosker
2018 Pattern Recognition  
In this paper we propose a hybrid framework by interleaving a Convolutional Neural Network (CNN) and a traditional optical flow energy.  ...  We thank Gabriel Brostow and the UCL PRISM Group for their helpful comments.  ...  The authors are partially supported by Centre for the Analysis of Motion, Entertainment Research and Applications (CAMERA) EP/M023281/1; and EPSRC projects EP/K023578/1 and EP/K02339X/1.  ... 
doi:10.1016/j.patcog.2017.04.020 fatcat:o4cm2qbmyngtnaukqauyddinx4
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