He, H.[Hu],
Kondi, L.P.,
An Image Super-Resolution Algorithm for Different Error Levels Per
Frame,
IP(15), No. 3, March 2006, pp. 592-603.
IEEE DOI
0604
BibRef
Earlier:
A Regularization Framework for Joint Blur Estimation and
Super-Resolution of Video Sequences,
ICIP05(III: 329-332).
IEEE DOI
0512
BibRef
Earlier:
MAP based resolution enhancement of video sequences using a
haber-markov random field image prior model,
ICIP03(II: 933-936).
IEEE DOI
0312
BibRef
Tai, Y.W.[Yu-Wing],
Du, H.[Hao],
Brown, M.S.[Michael S.],
Lin, S.[Stephen],
Correction of Spatially Varying Image and Video Motion Blur Using a
Hybrid Camera,
PAMI(32), No. 6, June 2010, pp. 1012-1028.
IEEE DOI
1004
BibRef
Earlier:
Image/video deblurring using a hybrid camera,
CVPR08(1-8).
IEEE DOI
0806
BibRef
Tai, Y.W.[Yu-Wing],
Liu, S.C.[Shuai-Cheng],
Brown, M.S.[Michael S.],
Lin, S.[Stephen],
Super resolution using edge prior and single image detail synthesis,
CVPR10(2400-2407).
IEEE DOI
1006
BibRef
Dong, W.S.[Wei-Sheng],
Zhang, L.[Lei],
Shi, G.M.[Guang-Ming],
Wu, X.L.[Xiao-Lin],
Image Deblurring and Super-Resolution by Adaptive Sparse Domain
Selection and Adaptive Regularization,
IP(20), No. 7, July 2011, pp. 1838-1857.
IEEE DOI
1107
See also Sparse Representation Based Image Interpolation With Nonlocal Autoregressive Modeling.
BibRef
Lee, D.B.,
Jeong, S.C.[Shin Cheol],
Lee, Y.G.[Yun-Gu],
Song, B.C.[Byung Cheol],
Video Deblurring Algorithm Using Accurate Blur Kernel Estimation and
Residual Deconvolution Based on a Blurred-Unblurred Frame Pair,
IP(22), No. 3, March 2013, pp. 926-940.
IEEE DOI
1302
BibRef
Lee, D.B.[Dong-Bok],
Heo, B.Y.[Bo-Young],
Song, B.C.[Byung Cheol],
Video deblurring based on bidirectional motion compensation and
accurate blur kernel estimation,
ICIP13(895-899)
IEEE DOI
1402
Decision support systems
BibRef
Jeong, S.C.[Shin Cheol],
Lee, T.H.[Tae Hwan],
Song, B.C.[Byung Cheol],
Lee, Y.G.[Yun-Gu],
Choi, Y.L.[Yang-Lim],
Video deblurring algorithm using an adjacent unblurred frame,
VCIP11(1-4).
IEEE DOI
1201
BibRef
Qiao, C.,
Lau, R.W.H.,
Sheng, B.,
Zhang, B.,
Wu, E.,
Temporal Coherence-Based Deblurring Using Non-Uniform Motion
Optimization,
IP(26), No. 10, October 2017, pp. 4991-5004.
IEEE DOI
1708
Cameras, Computational modeling, Image reconstruction, Kernel,
Motion segmentation, Video sequences, Videos, Video deblurring,
image deblurring, non-uniform blur kernel.
BibRef
Kim, T.H.,
Nah, S.,
Lee, K.M.,
Dynamic Video Deblurring Using a Locally Adaptive Blur Model,
PAMI(40), No. 10, October 2018, pp. 2374-2387.
IEEE DOI
1809
BibRef
Earlier: A2, A1, A3:
Deep Multi-scale Convolutional Neural Network for Dynamic Scene
Deblurring,
CVPR17(257-265)
IEEE DOI
1711
Kernel, Cameras, Optical imaging, Motion segmentation, Dynamics,
Adaptive optics, Estimation, Video deblurring, non-uniform blur,
non-uniform blur dataset.
Image restoration, Training
BibRef
Li, J.[Jing],
Gong, W.G.[Wei-Guo],
Zhan, H.M.[Hui-Mei],
Li, W.H.[Wei-Hong],
Combining weighted curvelet accumulation with motion vector duty
cycle for nonuniform video deblurring,
SP:IC(70), 2019, pp. 89-103.
Elsevier DOI
1812
Weighted curvelet accumulation, Motion vector duty cycle,
Nonuniform video deblurring
BibRef
Zhang, K.,
Luo, W.,
Zhong, Y.,
Ma, L.,
Liu, W.,
Li, H.,
Adversarial Spatio-Temporal Learning for Video Deblurring,
IP(28), No. 1, January 2019, pp. 291-301.
IEEE DOI
1810
cameras, convolution, feedforward neural nets, image restoration,
learning (artificial intelligence), neural net architecture,
video deblurring
BibRef
Pan, L.Y.[Li-Yuan],
Dai, Y.C.[Yu-Chao],
Liu, M.M.[Miao-Miao],
Porikli, F.M.[Fatih M.],
Pan, Q.[Quan],
Joint Stereo Video Deblurring, Scene Flow Estimation and Moving
Object Segmentation,
IP(29), No. 1, 2020, pp. 1748-1761.
IEEE DOI
1912
BibRef
Earlier: A1, A2, A3, A4, Only:
Simultaneous Stereo Video Deblurring and Scene Flow Estimation,
CVPR17(6987-6996)
IEEE DOI
1711
Estimation, Cameras, Motion segmentation, Object segmentation,
Image segmentation, Kernel, Semantics, Stereo deblurring,
joint optimization.
Benchmark testing, Estimation, Motion estimation,
Optical imaging,
BibRef
Xiang, X.G.[Xin-Guang],
Wei, H.[Hao],
Pan, J.S.[Jin-Shan],
Deep Video Deblurring Using Sharpness Features From Exemplars,
IP(29), 2020, pp. 8976-8987.
IEEE DOI
2009
Image restoration, Feature extraction, Optical imaging, Decoding,
Estimation, Learning systems, Kernel, Video deblurring, optical flow,
exemplars
BibRef
Pan, J.S.[Jin-Shan],
Xu, B.M.[Bo-Ming],
Bai, H.R.[Hao-Ran],
Tang, J.H.[Jin-Hui],
Yang, M.H.[Ming-Hsuan],
Cascaded Deep Video Deblurring Using Temporal Sharpness Prior and
Non-Local Spatial-Temporal Similarity,
PAMI(45), No. 8, August 2023, pp. 9411-9425.
IEEE DOI
2307
BibRef
Earlier: A1, A3, A4, Only:
Cascaded Deep Video Deblurring Using Temporal Sharpness Prior,
CVPR20(3040-3048)
IEEE DOI
2008
Optical flow, Image restoration, Convolutional neural networks,
Superresolution, Training, Convolution, Computational modeling,
video deblurring.
Optical imaging, Optical computing, Estimation, Optical feedback
BibRef
Yang, Y.X.[Yi-Xin],
Dong, J.X.[Jiang-Xin],
Tang, J.H.[Jin-Hui],
Pan, J.S.[Jin-Shan],
Colormnet: A Memory-based Deep Spatial-temporal Feature Propagation
Network for Video Colorization,
ECCV24(IV: 336-352).
Springer DOI
2412
BibRef
Pan, J.S.[Jin-Shan],
Xu, B.M.[Bo-Ming],
Dong, J.X.[Jiang-Xin],
Ge, J.J.[Jian-Jun],
Tang, J.H.[Jin-Hui],
Deep Discriminative Spatial and Temporal Network for Efficient Video
Deblurring,
CVPR23(22191-22200)
IEEE DOI
2309
BibRef
Wang, T.[Tao],
Zhang, X.Q.[Xiao-Qin],
Jiang, R.[Runhua],
Zhao, L.[Li],
Chen, H.L.[Hui-Ling],
Luo, W.H.[Wen-Han],
Video Deblurring via Spatiotemporal Pyramid Network and Adversarial
Gradient Prior,
CVIU(203), 2021, pp. 103135.
Elsevier DOI
2101
Video deblurring, Spatiotemporal pyramid, Adversarial learning, Image prior
BibRef
Li, Y.[Yawei],
Zhang, H.[Hong],
Wu, Y.J.[Yu-Jie],
Yuan, D.[Ding],
Dynamic Scene Video Deblurring Using Robust Incremental Weighted
Fourier Aggregation,
SPLetters(28), 2021, pp. 1565-1569.
IEEE DOI
2108
Smoothing methods, Signal processing algorithms, Aggregates,
Training, Kernel, Computational complexity, Pipelines,
lucky region
BibRef
Nie, K.M.[Kai-Ming],
Shi, X.P.[Xiao-Pei],
Cheng, S.[Silu],
Gao, Z.Y.[Zhi-Yuan],
Xu, J.T.[Jiang-Tao],
High Frame Rate Video Reconstruction and Deblurring Based on Dynamic
and Active Pixel Vision Image Sensor,
CirSysVideo(31), No. 8, August 2021, pp. 2938-2952.
IEEE DOI
2108
Optical flow, Image reconstruction, Voltage control,
Streaming media, Image sequences, Trajectory, Image restoration,
deblur
BibRef
Zhang, X.Q.[Xiao-Qin],
Jiang, R.[Runhua],
Wang, T.[Tao],
Wang, J.X.[Jin-Xin],
Recursive Neural Network for Video Deblurring,
CirSysVideo(31), No. 8, August 2021, pp. 3025-3036.
IEEE DOI
2108
Image restoration, Task analysis, Convolution, Kernel,
Computational modeling, Recurrent neural networks,
temporal consistency
BibRef
Liang, C.H.[Chih-Hung],
Su, H.T.[Hung-Ting],
Hsu, W.H.[Winston H.],
Learn from the past:
Sequentially one-to-one video deblurring network,
JVCIR(78), 2021, pp. 103159.
Elsevier DOI
2107
Video deblurring, Deblurring, Image quality enhancement
BibRef
Zhang, X.Q.[Xiao-Qin],
Wang, T.[Tao],
Jiang, R.[Runhua],
Zhao, L.[Li],
Xu, Y.[Yuewang],
Multi-Attention Convolutional Neural Network for Video Deblurring,
CirSysVideo(32), No. 4, April 2022, pp. 1986-1997.
IEEE DOI
2204
Task analysis, Image restoration, Feature extraction,
Deep learning, Convolution, Indexes, Video deblurring, MACNN, multi-attention
BibRef
Xu, Q.[Qian],
Pan, J.S.[Jin-Shan],
Qian, Y.T.[Yun-Tao],
Learning an Occlusion-Aware Network for Video Deblurring,
CirSysVideo(32), No. 7, July 2022, pp. 4312-4323.
IEEE DOI
2207
Feature extraction, Optical imaging, Image restoration, Costs,
Nonlinear optics, Kernel, Convolution, Video deblurring,
occlusion
BibRef
Ji, B.[Bo],
Yao, A.[Angela],
Multi-Scale Memory-Based Video Deblurring,
CVPR22(1909-1918)
IEEE DOI
2210
Deep learning, Runtime, Costs, Video sequences, Neural networks,
Information retrieval, Low-level vision,
Deep learning architectures and techniques
BibRef
Cao, M.D.[Ming-Deng],
Fan, Y.B.[Yan-Bo],
Zhang, Y.[Yong],
Wang, J.[Jue],
Yang, Y.[Yujiu],
VDTR: Video Deblurring With Transformer,
CirSysVideo(33), No. 1, January 2023, pp. 160-171.
IEEE DOI
2301
Transformers, Feature extraction, Image restoration,
Computational modeling, Adaptation models, Image reconstruction,
spatio-temporal modeling
BibRef
Wang, C.H.[Chao-Hua],
Dong, W.S.[Wei-Sheng],
Li, X.[Xin],
Wu, F.F.[Fang-Fang],
Wu, J.J.[Jin-Jian],
Shi, G.M.[Guang-Ming],
Memory Based Temporal Fusion Network for Video Deblurring,
IJCV(131), No. 7, July 2023, pp. 1840-1856.
Springer DOI
2307
BibRef
Ren, W.Q.[Wen-Qi],
Deng, S.Y.[Sen-You],
Zhang, K.H.[Kai-Hao],
Song, F.L.[Feng-Long],
Cao, X.C.[Xiao-Chun],
Yang, M.H.[Ming-Hsuan],
Fast Ultra High-Definition Video Deblurring via Multi-scale Separable
Network,
IJCV(132), No. 5, May 2024, pp. 1817-1834.
Springer DOI
2405
See also Ultra-High-Definition Image Dehazing via Multi-Guided Bilateral Learning.
BibRef
Deng, S.Y.[Sen-You],
Ren, W.Q.[Wen-Qi],
Yan, Y.Y.[Yan-Yang],
Wang, T.[Tao],
Song, F.L.[Feng-Long],
Cao, X.C.[Xiao-Chun],
Multi-Scale Separable Network for Ultra-High-Definition Video
Deblurring,
ICCV21(14010-14019)
IEEE DOI
2203
Visualization, Costs, Convolution, Computer architecture,
Streaming media, Real-time systems, Image and video synthesis,
BibRef
Xu, Q.[Qian],
Hu, X.B.[Xia-Bin],
Luo, D.H.[Dong-Hao],
Tai, Y.[Ying],
Wang, C.J.[Cheng-Jie],
Qian, Y.T.[Yun-Tao],
Efficiently Exploiting Spatially Variant Knowledge for Video
Deblurring,
CirSysVideo(34), No. 12, December 2024, pp. 12581-12593.
IEEE DOI
2501
Feature extraction, Image restoration, Convolution, Decoding, Kernel,
Transformers, Optical flow, Video deblurring, temporal information,
spatial information
BibRef
Yang, W.[Wen],
Wu, J.J.[Jin-Jian],
Ma, J.[Jupo],
Li, L.[Leida],
Dong, W.S.[Wei-Sheng],
Shi, G.M.[Guang-Ming],
Learning Frame-Event Fusion for Motion Deblurring,
IP(33), 2024, pp. 6836-6849.
IEEE DOI
2501
Transformers, Event detection, Cameras, Videos, Image restoration,
Convolutional neural networks, Redundancy, Correlation,
vision transformer
BibRef
Rao, C.[Chen],
Li, G.Y.[Guang-Yuan],
Lan, Z.[Zehua],
Sun, J.[Jiakai],
Luan, J.S.[Jun-Sheng],
Xing, W.[Wei],
Zhao, L.[Lei],
Lin, H.Z.[Huai-Zhong],
Dong, J.F.[Jian-Feng],
Zhang, D.L.[Da-Long],
Rethinking Video Deblurring with Wavelet-aware Dynamic Transformer and
Diffusion Model,
ECCV24(XLV: 421-437).
Springer DOI
2412
BibRef
He, J.T.[Jin-Ting],
Tsai, F.J.[Fu-Jen],
Wu, J.H.[Jia-Hao],
Peng, Y.T.[Yan-Tsung],
Tsai, C.C.[Chung-Chi],
Lin, C.W.[Chia-Wen],
Lin, Y.Y.[Yen-Yu],
Domain-adaptive Video Deblurring via Test-time Blurring,
ECCV24(XXX: 125-142).
Springer DOI
2412
BibRef
Zhang, H.C.[Hui-Cong],
Xie, H.Z.[Hao-Zhe],
Yao, H.X.[Hong-Xun],
Blur-Aware Spatio-Temporal Sparse Transformer for Video Deblurring,
CVPR24(3616-3626)
IEEE DOI
2410
DVD, Video sequences, Transformers, Feature extraction,
Computational efficiency, Data mining, Video deblurring,
Transformer
BibRef
Zhong, Z.H.[Zhi-Hang],
Cao, M.[Mingdeng],
Ji, X.[Xiang],
Zheng, Y.Q.[Yin-Qiang],
Sato, I.[Imari],
Blur Interpolation Transformer for Real-World Motion from Blur,
CVPR23(5713-5723)
IEEE DOI
2309
BibRef
Zhu, Q.[Qi],
Zhou, M.[Man],
Zheng, N.[Naishan],
Li, C.Y.[Chong-Yi],
Huang, J.[Jie],
Zhao, F.[Feng],
Exploring Temporal Frequency Spectrum in Deep Video Deblurring,
ICCV23(12394-12403)
IEEE DOI
2401
BibRef
Wang, Y.S.[Yu-Sheng],
Lu, Y.F.[Yun-Fan],
Gao, Y.[Ye],
Wang, L.[Lin],
Zhong, Z.H.[Zhi-Hang],
Zheng, Y.Q.[Yin-Qiang],
Yamashita, A.[Atsushi],
Efficient Video Deblurring Guided by Motion Magnitude,
ECCV22(XIX:413-429).
Springer DOI
2211
BibRef
Zhang, H.C.[Hui-Cong],
Xie, H.Z.[Hao-Zhe],
Yao, H.X.[Hong-Xun],
Spatio-Temporal Deformable Attention Network for Video Deblurring,
ECCV22(XVI:581-596).
Springer DOI
2211
BibRef
Shang, W.[Wei],
Ren, D.W.[Dong-Wei],
Zou, D.Q.[Dong-Qing],
Ren, J.S.[Jimmy S.],
Luo, P.[Ping],
Zuo, W.M.[Wang-Meng],
Bringing Events into Video Deblurring with Non-consecutively Blurry
Frames,
ICCV21(4511-4520)
IEEE DOI
2203
Interpolation, Superresolution, Detectors, Image restoration,
Task analysis, Low-level and physics-based vision,
BibRef
Imani, H.[Hassan],
Islam, M.B.[Md Baharul],
Towards Stereoscopic Video Deblurring Using Deep Convolutional Networks,
ISVC21(II:337-348).
Springer DOI
2112
BibRef
Suin, M.[Maitreya],
Rajagopalan, A.N.,
Gated Spatio-Temporal Attention-Guided Video Deblurring,
CVPR21(7798-7807)
IEEE DOI
2111
Adaptation models, Fuses, Computational modeling,
Logic gates, Computational efficiency
BibRef
Lin, S.N.[Song-Nan],
Zhang, J.W.[Jia-Wei],
Pan, J.S.[Jin-Shan],
Jiang, Z.[Zhe],
Zou, D.Q.[Dong-Qing],
Wang, Y.T.[Yong-Tian],
Chen, J.[Jing],
Ren, J.[Jimmy],
Learning Event-driven Video Deblurring and Interpolation,
ECCV20(VIII:695-710).
Springer DOI
2011
BibRef
Yan, Y.,
Wu, Q.,
Xu, B.,
Zhang, J.,
Ren, W.,
VDFlow: Joint Learning for Optical Flow and Video Deblurring,
UG20(3808-3816)
IEEE DOI
2008
Optical imaging, Adaptive optics, Optical propagation,
Optical fiber networks, Bidirectional control, Kernel, Estimation
BibRef
Brehm, S.,
Scherer, S.,
Lienhart, R.,
High-Resolution Dual-Stage Multi-Level Feature Aggregation for Single
Image and Video Deblurring,
NTIRE20(1872-1881)
IEEE DOI
2008
Image restoration, Kernel, Task analysis, Image resolution, Cameras,
Aggregates, Feature extraction
BibRef
Wu, J.,
Yu, X.,
Liu, D.,
Chandraker, M.,
Wang, Z.,
DAVID: Dual-Attentional Video Deblurring,
WACV20(2365-2374)
IEEE DOI
2006
DVD, Image restoration, Aggregates, Estimation, Cameras, Kernel, Visualization
BibRef
Gast, J.,
Roth, S.,
Deep Video Deblurring: The Devil is in the Details,
CLI19(3824-3833)
IEEE DOI
2004
cameras, convolutional neural nets, image motion analysis,
image restoration, learning (artificial intelligence),
Deep learning
BibRef
Zhou, S.,
Zhang, J.,
Pan, J.,
Zuo, W.,
Xie, H.,
Ren, J.,
Spatio-Temporal Filter Adaptive Network for Video Deblurring,
ICCV19(2482-2491)
IEEE DOI
2004
adaptive filters, cameras, image restoration, image sequences,
motion estimation, video signal processing, video deblurring,
Feature extraction
BibRef
Nah, S.J.[Seung-Jun],
Son, S.[Sanghyun],
Lee, K.M.[Kyoung Mu],
Recurrent Neural Networks With Intra-Frame Iterations for Video
Deblurring,
CVPR19(8094-8103).
IEEE DOI
2002
BibRef
Jin, M.G.[Mei-Guang],
Hu, Z.[Zhe],
Favaro, P.[Paolo],
Learning to Extract Flawless Slow Motion From Blurry Videos,
CVPR19(8104-8113).
IEEE DOI
2002
BibRef
Park, H.,
Lee, K.M.,
Joint Estimation of Camera Pose, Depth, Deblurring, and
Super-Resolution from a Blurred Image Sequence,
ICCV17(4623-4631)
IEEE DOI
1802
cameras, image reconstruction, image resolution, image restoration,
image sequences, optimisation, pose estimation,
BibRef
Kim, T.H.[Tae Hyun],
Lee, K.M.,
Schölkopf, B.[Bernhard],
Hirsch, M.[Michael],
Online Video Deblurring via Dynamic Temporal Blending Network,
ICCV17(4058-4067)
IEEE DOI
1802
cameras, image motion analysis, image restoration, image sequences,
motion estimation, recurrent neural nets,
Streaming media
BibRef
Tan, F.,
Liu, S.,
Zeng, L.,
Zeng, B.,
Kernel-free video deblurring via synthesis,
ICIP16(2683-2687)
IEEE DOI
1610
Cameras
BibRef
Kim, T.H.[Tae Hyun],
Lee, K.M.[Kyoung Mu],
Generalized video deblurring for dynamic scenes,
CVPR15(5426-5434)
IEEE DOI
1510
BibRef
Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Split Bregman Motion Blur, Image Restoration .