19.4.3.24.1 Video Super-Resolution, Resolution Enhancement

Tian, J.[Jing], Ma, K.K.[Kai-Kuang],
Stochastic super-resolution image reconstruction,
JVCIR(21), No. 3, April 2010, pp. 232-244.
Elsevier DOI 1003
Super-resolution, Image reconstruction, Bayesian inference, Markov chain Monte Carlo, Sample generation, Gibbs sampler; Metropolis-Hastings algorithm, Bilateral filter BibRef

Belekos, S.P.[Stefanos P.], Galatsanos, N.P.[Nikolaos P.], Katsaggelos, A.K.[Aggelos K.],
Maximum a Posteriori Video Super-Resolution Using a New Multichannel Image Prior,
IP(19), No. 6, June 2010, pp. 1451-1464.
IEEE DOI 1006
BibRef

Belekos, S.P.[Stefanos P.], Galatsanos, N.P.[Nikolaos P.], Babacan, S.D.[S. Derin], Katsaggelos, A.K.[Aggelos K.],
Maximum a posteriori super-resolution of compressed video using a new multichannel image prior,
ICIP09(2797-2800).
IEEE DOI 0911
BibRef

Song, B.C.[Byung Cheol], Jeong, S.C.[Shin-Cheol], Choi, Y.L.[Yang-Lim],
Video Super-Resolution Algorithm Using Bi-Directional Overlapped Block Motion Compensation and On-the-Fly Dictionary Training,
CirSysVideo(21), No. 3, March 2011, pp. 274-285.
IEEE DOI 1104
BibRef
Earlier:
Key frame-based video super-resolution using bi-directional overlapped block motion compensation and trained dictionary,
IPTA10(181-186).
IEEE DOI 1007
BibRef

Kang, Y.U., Jeong, S.C., Song, B.C.,
Fast super-resolution algorithms using one-dimensional patch-based training and directional interpolation,
IET-IPR(6), No. 5, 2012, pp. 548-557.
DOI Link 1210
BibRef

Keller, S.H.[Sune Høgild], Lauze, F.[François], Nielsen, M.[Mads],
Video Super-Resolution Using Simultaneous Motion and Intensity Calculations,
IP(20), No. 7, July 2011, pp. 1870-1884.
IEEE DOI 1107
BibRef
Earlier:
Motion Compensated Video Super Resolution,
SSVM07(801-812).
Springer DOI 0705

See also Deinterlacing Using Variational Methods. BibRef

Pelletier, S.[Stéphane], Cooperstock, J.R.[Jeremy R.],
Preconditioning for Edge-Preserving Image Super Resolution,
IP(21), No. 1, January 2012, pp. 67-79.
IEEE DOI 1112
BibRef
Earlier:
Fast Super-Resolution for Rational Magnification Factors,
ICIP07(II: 65-68).
IEEE DOI 0709
BibRef
Earlier:
Preconditioning for temporal video superresolution,
BMVC06(II:719).
PDF File. 0609

See also Toward Dynamic Image Mosaic Generation With Robustness to Parallax. BibRef

Pelletier, S.[Stéphane], Spackman, S.P.[Stephen P.], Cooperstock, J.R.[Jeremy R.],
High-Resolution Video Synthesis from Mixed-Resolution Video Based on the Estimate-and-Correct Method,
WACV05(I: 172-177).
IEEE DOI 0502
BibRef

Chen, J.[Jin], Nunez-Yanez, J.[Jose], Achim, A.[Alin],
Video Super-Resolution Using Generalized Gaussian Markov Random Fields,
SPLetters(19), No. 2, February 2012, pp. 63-66.
IEEE DOI 1201
BibRef

Chen, J.[Jin], Nunez-Yanez, J.[Jose], Achim, A.[Alin],
Joint video fusion and super resolution based on Markov random fields,
ICIP14(2150-2154)
IEEE DOI 1502
Bayes methods BibRef

Chen, J., Nunez-Yanez, J.L., Achim, A.,
Bayesian Video Super-Resolution With Heavy-Tailed Prior Models,
CirSysVideo(24), No. 6, June 2014, pp. 905-914.
IEEE DOI 1407
Approximation methods BibRef

Hung, E.M., de Queiroz, R.L.[Ricardo L.], Brandi, F.[Fernanda], de Oliveira, K.F., Mukherjee, D.[Debargha],
Video Super-Resolution Using Codebooks Derived From Key-Frames,
CirSysVideo(22), No. 9, September 2012, pp. 1321-1331.
IEEE DOI 1209
BibRef

Brandi, F.[Fernanda], de Queiroz, R.L.[Ricardo L.], Mukherjee, D.[Debargha],
Super-resolution of video using key frames and motion estimation,
ICIP08(321-324).
IEEE DOI 0810
BibRef

Garcia, D.C.[Diogo C.], Dorea, C.[Camilo], de Queiroz, R.L.[Ricardo L.],
Super-Resolution for Multiview Images Using Depth Information,
CirSysVideo(22), No. 9, September 2012, pp. 1249-1256.
IEEE DOI 1209
BibRef
Earlier: ICIP10(1793-1796).
IEEE DOI 1009
BibRef

Haseyama, M.[Miki], Izumi, D.[Daisuke], Takizawa, M.[Makoto],
Super-Resolution Reconstruction for Spatio-Temporal Resolution Enhancement of Video Sequences,
IEICE(E95-D), No. 9, September 2012, pp. 2355-2358.
WWW Link. 1209
BibRef

Zhang, X.H.[Xiao-Hong], Tang, M.[Min], Tong, R.F.[Ruo-Feng],
Robust super resolution of compressed video,
VC(27), No. 12, December 2011, pp. 1167-1180.
WWW Link. 1211
BibRef

Zhang, X., Jiang, J., Peng, S.,
Commutability of Blur and Affine Warping in Super-Resolution With Application to Joint Estimation of Triple-Coupled Variables,
IP(21), No. 4, April 2012, pp. 1796-1808.
IEEE DOI 1204
BibRef

Ning, Q., Chen, K., Yi, L., Fan, C., Lu, Y., Wen, J.,
Image Super-Resolution Via Analysis Sparse Prior,
SPLetters(20), No. 4, April 2013, pp. 399-402.
IEEE DOI 1303
BibRef

Salvador, J.[Jordi], Kochale, A.[Axel], Schweidler, S.[Siegfried],
Patch-based spatio-temporal super-resolution for video with non-rigid motion,
SP:IC(28), No. 5, May 2013, pp. 483-493.
Elsevier DOI 1305
Video super-resolution, Non-rigid motion, Optical flow, Single-image; Cross-scale self-similarity, Parallelization
See also Antipodally Invariant Metrics for Fast Regression-Based Super-Resolution. BibRef

Salvador, J.[Jordi], Pérez-Pellitero, E.[Eduardo],
Naive Bayes Super-Resolution Forest,
ICCV15(325-333)
IEEE DOI 1602
Dictionaries BibRef

Salvador, J.[Jordi], Rivero, D.[Daniel], Kochale, A.[Axel], Ruiz-Hidalgo, J.[Javier],
Variational reconstruction and restoration for video Super-Resolution,
ICPR12(1047-1051).
WWW Link. 1302
BibRef

Liu, C.[Ce], Sun, D.Q.[De-Qing],
On Bayesian Adaptive Video Super Resolution,
PAMI(36), No. 2, February 2014, pp. 346-360.
IEEE DOI 1402
BibRef
Earlier: Liu, C.[Ce], Sun, D.Q.[De-Qing],
A Bayesian approach to adaptive video super resolution,
CVPR11(209-216).
IEEE DOI 1106
Bayes methods BibRef

Suo, J.L.[Jin-Li], Deng, Y.[Yue], Bian, L.H.[Li-Heng], Dai, Q.H.[Qiong-Hai],
Joint Non-Gaussian Denoising and Superresolving of Raw High Frame Rate Videos,
IP(23), No. 3, March 2014, pp. 1154-1168.
IEEE DOI 1403
Gaussian processes BibRef

Lu, J.[Jian], Zhang, H.[HongRan], Sun, Y.[Yi],
Video super resolution based on non-local regularization and reliable motion estimation,
SP:IC(29), No. 4, 2014, pp. 514-529.
Elsevier DOI 1404
Super-resolution BibRef

Freitas, P.G.[Pedro Garcia], Farias, M.C.Q.[Mylene C. Q.],
A Parallel Framework for Video Super-resolution,
ELCVIA(13), No. 2, 2014, pp. xx-yy.
DOI Link 1407
Ph.D.. Thesis. BibRef

Liu, Y., Lin, Y., Huang, Y., Chien, S.,
Algorithm and Architecture Design of High-Quality Video Upscaling Using Database-Free Texture Synthesis,
CirSysVideo(24), No. 7, July 2014, pp. 1221-1234.
IEEE DOI 1407
Algorithm design and analysis BibRef

Zhu, Y.M.[Yan-Ming], Li, K.[Kun], Jiang, J.M.[Jian-Min],
Video super-resolution based on automatic key-frame selection and feature-guided variational optical flow,
SP:IC(29), No. 8, 2014, pp. 875-886.
Elsevier DOI 1410
Video super-resolution BibRef

Pournaghi, R., Wu, X.L.[Xiao-Lin],
Coded Acquisition of High Frame Rate Video,
IP(23), No. 12, December 2014, pp. 5670-5682.
IEEE DOI 1412
cameras BibRef

Anbarjafari, G.[Gholamreza], Izadpanahi, S.[Sara], Demirel, H.[Hasan],
Video resolution enhancement by using discrete and stationary wavelet transforms with illumination compensation,
SIViP(9), No. 1, January 2015, pp. 87-92.
Springer DOI 1503
BibRef

Demirel, H.[Hasan], Anbarjafari, G.[Gholamreza], Ozcinar, C.[Cagn], Izadpanahi, S.[Sara],
Video resolution enhancement by using complex wavelet transform,
ICIP11(2093-2096).
IEEE DOI 1201
BibRef

Shi, R.[Rui], Yin, S.Y.[Shou-Yi], Liu, L.[Leibo], Liu, Q.B.[Qiong-Bing], Liang, S.[Shuang], Wei, S.J.[Shao-Jun],
The Implementation of Texture-Based Video Up-Scaling on Coarse-Grained Reconfigurable Architecture,
IEICE(E98-D), No. 2, February 2015, pp. 276-287.
WWW Link. 1503
BibRef

Zhang, X.F.[Xin-Feng], Xiong, R.Q.[Rui-Qin], Ma, S.W.[Si-Wei], Li, G.[Ge], Gao, W.[Wen],
Video super-resolution with registration-reliability regulation and adaptive total variation,
JVCIR(30), No. 1, 2015, pp. 181-190.
Elsevier DOI 1507
Super-resolution
See also New image coding scheme with hierarchical representation and adaptive interpolation. BibRef

Ge, J.[Jing], Liu, J.[Ju], Zhao, Y.L.[Yun-Long], Zhang, B.Y.[Bo-Yang],
A resolution enhancement algorithm for an asymmetric resolution stereo video,
JIVP(2015), No. 1, 2015, pp. 23.
DOI Link 1508
BibRef

Hayashi, Y.[Yusuke], Kawai, N.[Norihiko], Sato, T.[Tomokazu], Okumoto, M.[Miyuki], Yokoya, N.[Naokazu],
Generation of a Zoomed Stereo Video Using Two Synchronized Videos with Different Magnifications,
IEICE(E98-D), No. 9, September 2015, pp. 1691-1701.
WWW Link. 1509
BibRef
Earlier:
Generation of a Super-Resolved Stereo Video Using Two Synchronized Videos with Different Magnifications,
PSIVT13(194-205).
Springer DOI 1402
BibRef

Faramarzi, E., Rajan, D., Fernandes, F.C.A., Christensen, M.P.,
Blind Super Resolution of Real-Life Video Sequences,
IP(25), No. 4, April 2016, pp. 1544-1555.
IEEE DOI 1604
Markov processes BibRef

Wood, S.L., Lan, H.B.[Hsueh-Ban], Rajan, D.[Dinesh], Christensen, M.P.,
Improved Multiplexed Image Reconstruction Performance Through Optical System Diversity Design,
ICIP06(2717-2720).
IEEE DOI 0610
High resolution from low resolution images. Better results when magnification of originals are diverse. BibRef

Barzigar, N., Roozgard, A., Verma, P., Cheng, S.,
A Video Super-Resolution Framework Using SCoBeP,
CirSysVideo(26), No. 2, February 2016, pp. 264-277.
IEEE DOI 1602
Cameras BibRef

Georgis, G., Lentaris, G., Reisis, D.,
Reduced Complexity Superresolution for Low-Bitrate Video Compression,
CirSysVideo(26), No. 2, February 2016, pp. 332-345.
IEEE DOI 1602
Bit rate BibRef

Jin, Z., Tillo, T., Yao, C., Xiao, J., Zhao, Y.,
Virtual-View-Assisted Video Super-Resolution and Enhancement,
CirSysVideo(26), No. 3, March 2016, pp. 467-478.
IEEE DOI 1603
Decoding BibRef

Héas, P., Drémeau, A., Herzet, C.,
An Efficient Algorithm for Video Superresolution Based on a Sequential Model,
SIIMS(9), No. 2, 2016, pp. 537-572.
DOI Link 1608
BibRef

Thelen, B.J.[Brian J.], Valenzuela, J.R.[John R.], Le Blanc, J.W.[Joel W.],
Theoretical performance assessment and empirical analysis of super-resolution under unknown affine sensor motion,
JOSA-A(33), No. 4, April 2016, pp. 519-526.
DOI Link 1604
Image reconstruction techniques BibRef

Szeliski, R.S.[Richard S.],
Technical Perspective: Magnifying Motions the Right Way,
CACM(60), No. 1, January 2017, pp. 86.
DOI Link 1612
Intro to the next paper BibRef

Wadhwa, N.[Neal], Wu, H.Y.[Hao-Yu], Davis, A.[Abe], Rubinstein, M.[Michael], Shih, E.[Eugene], Mysore, G.J.[Gautham J.], Chen, J.G.[Justin G.], Buyukozturk, O.[Oral], Guttag, J.V.[John V.], Freeman, W.T.[William T.], Durand, F.[Frédo],
Eulerian Video Magnification and Analysis,
CACM(60), No. 1, January 2017, pp. 87-95.
DOI Link 1612
Computational technique for visualizing subtle color and motion variations in ordinary videos by making the variations larger. BibRef

Dai, Q.Q.[Qi-Qin], Yoo, S.[Seunghwan], Kappeler, A.[Armin], Katsaggelos, A.K.[Aggelos K.],
Sparse Representation-Based Multiple Frame Video Super-Resolution,
IP(26), No. 2, February 2017, pp. 765-781.
IEEE DOI 1702
BibRef
Earlier:
Dictionary-based multiple frame video super-resolution,
ICIP15(83-87)
IEEE DOI 1512
image representation. Video super-resolution BibRef

Li, Y.W.[Ya-Wei], Li, X.F.[Xiao-Feng], Fu, Z.Z.[Zhi-Zhong],
Modified non-local means for super-resolution of hybrid videos,
CVIU(168), 2018, pp. 64-78.
Elsevier DOI 1804
Adaptive parameters, Hybrid video, Non-local means, Non-local self similarity, Super-resolution BibRef

Li, Y.W.[Ya-Wei], Li, X.F.[Xiao-Feng], Fu, Z.Z.[Zhi-Zhong], Yin, X.X.[Xiu-Xia], Zhao, Y.F.[Yu-Fei],
Bilateral video super-resolution using non-local means with adaptive parameters,
ICIP16(1155-1159)
IEEE DOI 1610
Hafnium BibRef

Li, Y.W.[Ya-Wei], Li, X.F.[Xiao-Feng], Yao, C.[Cui], Fu, Z.Z.[Zhi-Zhong], Yin, X.X.[Xiu-Xia],
Video Super Resolution Using Non-Local Means with Adaptive Decaying Factor and Searching Window,
NTIRE16(I: 177-190).
Springer DOI 1704
BibRef

Li, Y.W.[Ya-Wei], Li, X.F.[Xiao-Feng], Fu, Z.Z.[Zhi-Zhong], Niu, T.T.[Ting-Ting], Long, K.Y.[Ke-Yu],
Spatiotemporal super-resolution for multiview video in transform domain,
VCIP16(1-4)
IEEE DOI 1701
Algorithm design and analysis BibRef

Yang, W.H.[Wen-Han], Feng, J.S.[Jia-Shi], Xie, G.S.[Guo-Sen], Liu, J.Y.[Jia-Ying], Guo, Z.M.[Zong-Ming], Yan, S.C.[Shui-Cheng],
Video super-resolution based on spatial-temporal recurrent residual networks,
CVIU(168), 2018, pp. 79-92.
Elsevier DOI 1804
Spatial residue, Temporal residue, Video super-resolution, Inter-frame motion context, Intra-frame redundancy BibRef

Huang, Y.[Yan], Wang, W.[Wei], Wang, L.[Liang],
Video Super-Resolution via Bidirectional Recurrent Convolutional Networks,
PAMI(40), No. 4, April 2018, pp. 1015-1028.
IEEE DOI 1804
computational complexity, image resolution, image sequences, recurrent neural nets, video signal processing, Single-Image SR, video super-resolution BibRef

Zhang, T.H.[Ting-Hua], Gao, K.[Kun], Ni, G.Q.[Guo-Qiang], Fan, G.H.[Gui-Hua], Lu, Y.[Yan],
Spatio-temporal super-resolution for multi-videos based on belief propagation,
SP:IC(68), 2018, pp. 1-12.
Elsevier DOI 1810
Super resolution, Spatio-temporal, MAP-MRF, SIFT flow BibRef

Borsoi, R.A., Costa, G.H., Bermudez, J.C.M.,
A New Adaptive Video Super-Resolution Algorithm With Improved Robustness to Innovations,
IP(28), No. 2, February 2019, pp. 673-686.
IEEE DOI 1811
image reconstruction, image resolution, iterative methods, least mean squares methods, Monte Carlo methods, outliers BibRef

Borsoi, R.A., Imbiriba, T., Bermudez, J.C.M.,
Super-Resolution for Hyperspectral and Multispectral Image Fusion Accounting for Seasonal Spectral Variability,
IP(29), No. 1, 2020, pp. 116-127.
IEEE DOI 1910
geophysical image processing, hyperspectral imaging, image resolution, remote sensing, super-resolution, image fusion BibRef

Imbiriba, T., Borsoi, R.A., Bermudez, J.C.M.,
Low-Rank Tensor Modeling for Hyperspectral Unmixing Accounting for Spectral Variability,
GeoRS(58), No. 3, March 2020, pp. 1833-1842.
IEEE DOI 2003
Hyperspectral imaging, Environmental management, Additives, Parametric statistics, Electrical engineering, ULTRA accounting for EM variability (ULTRA-V) BibRef

Prévost, C.[Clémence], Borsoi, R.A.[Ricardo A.], Usevich, K.[Konstantin], Brie, D.[David], Bermudez, J.C.M.[José C. M.], Richard, C.[Cédric],
Hyperspectral Super-resolution Accounting for Spectral Variability: Coupled Tensor LL1-Based Recovery and Blind Unmixing of the Unknown Super-resolution Image,
SIIMS(15), No. 1, 2022, pp. 110-138.
DOI Link 2204
BibRef

Li, D.Y.[Ding-Yi], Liu, Y.[Yu], Wang, Z.F.[Zeng-Fu],
Video Super-Resolution Using Non-Simultaneous Fully Recurrent Convolutional Network,
IP(28), No. 3, March 2019, pp. 1342-1355.
IEEE DOI 1812
BibRef
Earlier:
Video super-resolution using motion compensation and residual bidirectional recurrent convolutional network,
ICIP17(1642-1646)
IEEE DOI 1803
Motion compensation, Visualization, Computer architecture, Image resolution, Convolutional codes, Image restoration, model ensemble. Image restoration, Motion estimation, Spatial resolution, Testing, Video super-resolution, recurrent neural networks (RNNs) BibRef

Purica, A., Boyadjis, B., Pesquet-Popescu, B., Dufaux, F., Bergeron, C.,
A Convex Optimization Framework for Video Quality and Resolution Enhancement From Multiple Descriptions,
IP(28), No. 4, April 2019, pp. 1661-1674.
IEEE DOI 1901
convex programming, data compression, image enhancement, image reconstruction, image resolution, image sampling, HEVC BibRef

Wang, Z.Y.[Zhong-Yuan], Yi, P.[Peng], Jiang, K.[Kui], Jiang, J.J.[Jun-Jun], Han, Z.[Zhen], Lu, T.[Tao], Ma, J.Y.[Jia-Yi],
Multi-Memory Convolutional Neural Network for Video Super-Resolution,
IP(28), No. 5, May 2019, pp. 2530-2544.
IEEE DOI 1903
Image resolution, Optical imaging, Optical fiber networks, Feature extraction, Image reconstruction, Correlation, multi-memory residual block BibRef

Zhou, L.G.[Li-Guo], Wang, Z.Y.[Zhong-Yuan], Wang, S.[Shu], Luo, Y.M.[Yi-Min],
Coarse-to-Fine Image Super-Resolution Using Convolutional Neural Networks,
MMMod18(II:73-81).
Springer DOI 1802
BibRef

Yi, P.[Peng], Wang, Z.Y.[Zhong-Yuan], Jiang, K.[Kui], Shao, Z.F.[Zhen-Feng], Ma, J.Y.[Jia-Yi],
Multi-Temporal Ultra Dense Memory Network for Video Super-Resolution,
CirSysVideo(30), No. 8, August 2020, pp. 2503-2516.
IEEE DOI 2008
Correlation, Feature extraction, Image reconstruction, Neural networks, Motion estimation, multi-temporal fusion BibRef

Lucas, A.[Alice], López-Tapia, S.[Santiago], Molina, R.[Rafael], Katsaggelos, A.K.[Aggelos K.],
Generative Adversarial Networks and Perceptual Losses for Video Super-Resolution,
IP(28), No. 7, July 2019, pp. 3312-3327.
IEEE DOI 1906
BibRef
Earlier: A1, A4, A2, A3: ICIP18(51-55)
IEEE DOI 1809
image resolution, image restoration, learning (artificial intelligence), mean square error methods, image generation. Training, Spatial resolution, Mathematical model, Loss measurement, Neural networks, Video, Superresolution, Perceptual Loss Functions BibRef

Kim, Y., Choi, J., Kim, M.,
A Real-Time Convolutional Neural Network for Super-Resolution on FPGA With Applications to 4K UHD 60 fps Video Services,
CirSysVideo(29), No. 8, August 2019, pp. 2521-2534.
IEEE DOI 1908
Hardware, Quantization (signal), Streaming media, UHDTV, Real-time systems, Field programmable gate arrays, Interpolation, FPGA BibRef

Howie, R.M.[Robert M.], Paxman, J.[Jonathan], Bland, P.A.[Philip A.], Towner, M.C.[Martin C.],
Absolute time encoding for temporal super-resolution using de Bruijn coded exposures,
MVA(31), No. 1, January 2020, pp. Article1.
Springer DOI 2001
BibRef

Wang, L.G.[Long-Guang], Guo, Y.L.[Yu-Lan], Liu, L., Lin, Z.P.[Zai-Ping], Deng, X.P.[Xin-Pu], An, W.[Wei],
Deep Video Super-Resolution Using HR Optical Flow Estimation,
IP(29), 2020, pp. 4323-4336.
IEEE DOI 2002
BibRef
Earlier: A1, A2, A4, A5, A6, Only:
Learning for Video Super-Resolution Through HR Optical Flow Estimation,
ACCV18(I:514-529).
Springer DOI 1906
Video super-resolution, optical flow estimation, temporal consistency, scale-recurrent architecture BibRef

Mu, Y.[Yang], Wang, P.[Ping], Lu, L.F.[Liang-Fu], Zhang, X.[Xuyun], Qi, L.Y.[Lian-Yong],
Weighted tensor nuclear norm minimization for tensor completion using tensor-SVD,
PRL(130), 2020, pp. 4-11.
Elsevier DOI 2002
Tensor completion, Tensor-SVD, Weighted nuclear norm, KKT conditions, Video completion BibRef

Li, F., Bai, H., Zhao, Y.,
Learning a Deep Dual Attention Network for Video Super-Resolution,
IP(29), 2020, pp. 4474-4488.
IEEE DOI 2003
Video super-resolution, motion compensation, detail components, attention mechanisms, high-frequency details BibRef

Lai, Q.X.[Qiu-Xia], Nie, Y.W.[Yong-Wei], Sun, H.Q.[Han-Qiu], Xu, Q.A.[Qi-Ang], Zhang, Z.S.[Zhen-Song], Xiao, M.Y.[Ming-Yu],
Video super-resolution via pre-frame constrained and deep-feature enhanced sparse reconstruction,
PR(100), 2020, pp. 107139.
Elsevier DOI 2005
Video super resolution, Sparse representation, Deep features, Temporal coherence BibRef

Liu, X., Kong, L., Zhou, Y., Zhao, J., Chen, J.,
End-To-End Trainable Video Super-Resolution Based on a New Mechanism for Implicit Motion Estimation and Compensation,
WACV20(2405-2414)
IEEE DOI 2006
Motion estimation, Dynamics, Spatial resolution, Feature extraction, Tensile stress, Motion compensation BibRef

Ying, X., Wang, L., Wang, Y., Sheng, W., An, W., Guo, Y.,
Deformable 3D Convolution for Video Super-Resolution,
SPLetters(27), 2020, pp. 1500-1504.
IEEE DOI 2009
Convolution, Motion compensation, Feature extraction, Image resolution, Signal resolution, deformable convolution BibRef

Takeda, S.[Shoichiro], Isogai, M.[Megumi], Shimizu, S.[Shinya], Kimata, H.[Hideaki],
Local Riesz Pyramid for Faster Phase-Based Video Magnification,
IEICE(E103-D), No. 10, October 2020, pp. 2036-2046.
WWW Link. 2010
BibRef

Zhu, X.O.[Xia-Obin], Li, Z.Z.[Zhuang-Zi], Lou, J.G.[Jun-Gang], Shen, Q.[Qing],
Video super-resolution based on a spatio-temporal matching network,
PR(110), 2021, pp. 107619.
Elsevier DOI 2011
Deep matching, Wavelet domain, Non-local matching, Residual learning, Video super-resolution BibRef

Liu, H., Gu, Y., Wang, T., Li, S.,
Satellite Video Super-Resolution Based on Adaptively Spatiotemporal Neighbors and Nonlocal Similarity Regularization,
GeoRS(58), No. 12, December 2020, pp. 8372-8383.
IEEE DOI 2012
Satellites, Motion estimation, Spatiotemporal phenomena, Adaptation models, Image reconstruction, Degradation, super-resolution (SR) BibRef

Lu, S.P.[Shao-Ping], Li, S.M.[Sen-Mao], Wang, R.[Rong], Lafruit, G.[Gauthier], Cheng, M.M.[Ming-Ming], Munteanu, A.[Adrian],
Low-Rank Constrained Super-Resolution for Mixed-Resolution Multiview Video,
IP(30), 2021, pp. 1072-1085.
IEEE DOI 2012
Multiview video, mixed-resolution, super-resolution, low-rank, ADMM optimization BibRef

Lu, S.P.[Shao-Ping], You, J.[Jie], Ceulemans, B.[Beerend], Wang, M.[Miao], Munteanu, A.[Adrian],
Synthesis of Shaking Video Using Motion Capture Data and Dynamic 3D Scene Modeling,
ICIP18(1438-1442)
IEEE DOI 1809
Cameras, Trajectory, Dynamics, Solid modeling, video rendering BibRef

Guan, Z.Y.[Zhen-Yu], Xing, Q.L.[Qun-Liang], Xu, M.[Mai], Yang, R.[Ren], Liu, T.[Tie], Wang, Z.L.[Zu-Lin],
MFQE 2.0: A New Approach for Multi-Frame Quality Enhancement on Compressed Video,
PAMI(43), No. 3, March 2021, pp. 949-963.
IEEE DOI 2102
Transform coding, Image coding, Databases, MPEG 1 Standard, Task analysis, Video recording, Quality enhancement, deep learning BibRef

Yang, R.[Ren], Xu, M.[Mai], Wang, Z.L.[Zu-Lin], Li, T.Y.[Tian-Yi],
Multi-frame Quality Enhancement for Compressed Video,
CVPR18(6664-6673)
IEEE DOI 1812
Transform coding, Image coding, Standards, Video sequences, Support vector machines, Encoding, Visualization BibRef

Song, H., Xu, W., Liu, D., Liu, B., Liu, Q., Metaxas, D.N.,
Multi-Stage Feature Fusion Network for Video Super-Resolution,
IP(30), 2021, pp. 2923-2934.
IEEE DOI 2102
Visualization, Convolution, Superresolution, Task analysis, Fuses, Feature extraction, Modulation, Video super-resolution, feature fusion BibRef

Liu, X., Shi, K., Wang, Z., Chen, J.,
Exploit Camera Raw Data for Video Super- Resolution via Hidden Markov Model Inference,
IP(30), 2021, pp. 2127-2140.
IEEE DOI 2102
convolutional neural nets, hidden Markov model inference, deep learning (artificial intelligence), hidden Markov models. BibRef

Jagdale, R.H.[Rohita H.], Shah, S.K.[Sanjeevani K.],
Modified Rider Optimization-Based V Channel Magnification for Enhanced Video Super Resolution,
IJIG(21), No. 1 2021, pp. 2150003.
DOI Link 2102
BibRef

Xiao, Z.J.[Zhi-Jiao], Zhang, Z.[Zhikai], Hung, K.W.[Kwok-Wai], Lui, S.[Simon],
Real-time video super-resolution using lightweight depthwise separable group convolutions with channel shuffling,
JVCIR(75), 2021, pp. 103038.
Elsevier DOI 2103
Super-resolution, Lightweight alignment module, Channel shuffle, Residual networks BibRef

Zeng, Y.[Yubin], Xiao, Z.J.[Zhi-Jiao], Hung, K.W.[Kwok-Wai], Lui, S.[Simon],
Real-time video super resolution network using recurrent multi-branch dilated convolutions,
SP:IC(93), 2021, pp. 116167.
Elsevier DOI 2103
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Zhou, C.[Chao], Chen, C.[Can], Ding, F.[Fei], Zhang, D.Y.[Deng-Yin],
Video Super-Resolution with Non-Local Alignment Network,
IET-IPR(15), No. 8, 2021, pp. 1655-1667.
DOI Link 2106
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Cheng, M.[Ming], Ma, Z.[Zhan], Asif, M.S.[M. Salman], Xu, Y.L.[Yi-Ling], Liu, H.J.[Hao-Jie], Bao, W.[Wenbo], Sun, J.[Jun],
A Dual Camera System for High Spatiotemporal Resolution Video Acquisition,
PAMI(43), No. 10, October 2021, pp. 3275-3291.
IEEE DOI 2109
Cameras, Spatial resolution, Spatiotemporal phenomena, Data models, Dual camera system, high spatiotemporal resolution, end-to-end learning BibRef

Zhang, D.Y.[Dong-Yang], Shao, J.[Jie], Liang, Z.W.[Zhen-Wen], Liu, X.L.[Xue-Liang], Shen, H.T.[Heng Tao],
Multi-Branch Networks for Video Super-Resolution With Dynamic Reconstruction Strategy,
CirSysVideo(31), No. 10, October 2021, pp. 3954-3966.
IEEE DOI 2110
Convolution, Optical imaging, Image reconstruction, Feature extraction, video super-resolution BibRef

Ghassab, V.K.[Vahid Khorasani], Bouguila, N.[Nizar],
Plug-and-Play video super-resolution using edge-preserving filtering,
CVIU(216), 2022, pp. 103359.
Elsevier DOI 2202
Video super-resolution, Student-t mixture models, Edge preserving filtering, Plug-and-Play BibRef

Wen, W.L.[Wei-Lei], Ren, W.Q.[Wen-Qi], Shi, Y.H.[Ying-Huan], Nie, Y.F.[Yun-Feng], Zhang, J.G.[Jin-Gang], Cao, X.C.[Xiao-Chun],
Video Super-Resolution via a Spatio-Temporal Alignment Network,
IP(31), 2022, pp. 1761-1773.
IEEE DOI 2202
Superresolution, Motion compensation, Estimation, Integrated optics, Optical imaging, Image reconstruction, spatio-temporal adaptive filters BibRef

He, Z.[Zhi], Li, X.F.[Xiao-Fang], Qu, R.[Rongning],
Video Satellite Imagery Super-Resolution via Model-Based Deep Neural Networks,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Ding, D.D.[Dan-Dan], Wang, W.Y.[Wen-Yu], Tong, J.C.[Jun-Chao], Gao, X.B.[Xin-Bo], Liu, Z.[Zoe], Fang, Y.[Yong],
Biprediction-Based Video Quality Enhancement via Learning,
Cyber(52), No. 2, February 2022, pp. 1207-1220.
IEEE DOI 2202
Motion estimation, Correlation, Computational complexity, Video recording, Quality assessment, Optical imaging, video enhancement BibRef

Tong, J.C.[Jun-Chao], Wu, X.L.[Xi-Lin], Ding, D.D.[Dan-Dan], Zhu, Z.[Zheng], Liu, Z.[Zoe],
Learning-Based Multi-Frame Video Quality Enhancement,
ICIP19(929-933)
IEEE DOI 1910
CNN, video compression, enhancement, optical flow, multi-frame BibRef

Song, H.H.[Hui-Hui], Jin, Y.T.[Yu-Tong], Cheng, Y.[Yong], Liu, B.[Bo], Liu, D.[Dong], Liu, Q.S.[Qing-Shan],
Learning interlaced sparse Sinkhorn matching network for video super-resolution,
PR(124), 2022, pp. 108475.
Elsevier DOI 2203
Video super-resolution, Multi-scale feature, Interlaced sparse sinkhorn attention, Bidirectional fusion, Dynamic reconstruction BibRef

Yang, J.[Jian], Pham, C.D.K.[Chi Do-Kim], Zhou, J.J.[Jin-Jia],
JVCSR: Video Compressive Sensing Reconstruction with Joint In-Loop Reference Enhancement and Out-Loop Super-Resolution,
MMMod22(I:455-466).
Springer DOI 2203
BibRef

Yi, P.[Peng], Wang, Z.Y.[Zhong-Yuan], Jiang, K.[Kui], Jiang, J.J.[Jun-Jun], Lu, T.[Tao], Ma, J.Y.[Jia-Yi],
A Progressive Fusion Generative Adversarial Network for Realistic and Consistent Video Super-Resolution,
PAMI(44), No. 5, May 2022, pp. 2264-2280.
IEEE DOI 2204
Training, Convolution, Image reconstruction, Neural networks, Generative adversarial networks, Convolutional neural network, generative adversarial network BibRef

Yi, P.[Peng], Wang, Z.Y.[Zhong-Yuan], Jiang, K.[Kui], Jiang, J.J.[Jun-Jun], Lu, T.[Tao], Tian, X.[Xin], Ma, J.Y.[Jia-Yi],
Omniscient Video Super-Resolution,
ICCV21(4409-4418)
IEEE DOI 2203
Measurement, Superresolution, Visual effects, Generators, Robustness, Real-time systems, Low-level and physics-based vision, Image and video synthesis BibRef

Sun, W.[Wei], Gong, D.[Dong], Shi, J.Q.F.[Javen Qin-Feng], van den Hengel, A.J.[Anton J.], Zhang, Y.N.[Yan-Ning],
Video super-resolution via mixed spatial-temporal convolution and selective fusion,
PR(126), 2022, pp. 108577.
Elsevier DOI 2204
Video super-Resolution, Mixed spatial-Temporal convolution, Selective feature fusion BibRef

Sun, K.[Kaicong], Koch, M.[Maurice], Wang, Z.[Zhe], Jovanovic, S.[Slavisa], Rabah, H.[Hassan], Simon, S.[Sven],
An FPGA-Based Residual Recurrent Neural Network for Real-Time Video Super-Resolution,
CirSysVideo(32), No. 4, April 2022, pp. 1739-1750.
IEEE DOI 2204
Convolution, Field programmable gate arrays, Real-time systems, Streaming media, UHDTV, Image reconstruction, Superresolution, hardware-efficient BibRef

Tekalp, A.M.[A. Murat],
Deep Learning for Image/Video Restoration and Super-Resolution,
FTCGV(13), No. 1, 2022, pp. 1-110.
DOI Link 2206
Survey, Video Super-Resolution. BibRef

Nasiri, F.[Fatemeh], Hamidouche, W.[Wassim], Morin, L.[Luce], Cocherel, G.[Gildas], Dhollande, N.[Nicolas],
A Study on the Impact of Training Data in CNN-Based Super-Resolution for Low Bitrate End-to-End Video Coding,
IPTA20(1-5)
IEEE DOI 2206
Training, Video coding, Image coding, Bit rate, Training data, Bandwidth, Convolutional neural networks, Low Bitrate Video Coding BibRef

Wang, J.Y.[Jian-Yi], Xu, M.[Mai], Deng, X.[Xin], Shen, L.Q.[Li-Quan], Song, Y.H.[Yu-Hang],
MW-GAN+ for Perceptual Quality Enhancement on Compressed Video,
CirSysVideo(32), No. 7, July 2022, pp. 4224-4237.
IEEE DOI 2207
Image coding, Measurement, Transform coding, Image restoration, Distortion, Video recording, Quality assessment, generative adversarial network BibRef

Wang, J.Y.[Jian-Yi], Deng, X.[Xin], Xu, M.[Mai], Chen, C.Y.[Cong-Yong], Song, Y.H.[Yu-Hang],
Multi-level Wavelet-based Generative Adversarial Network for Perceptual Quality Enhancement of Compressed Video,
ECCV20(XIV:405-421).
Springer DOI 2011
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Zhang, Y.H.[Yu-Hang], Chen, Z.Z.[Zhen-Zhong], Liu, S.[Shan],
A multi-stage spatio-temporal adaptive network for video super-resolution,
JVCIR(87), 2022, pp. 103555.
Elsevier DOI 2208
BibRef
Earlier:
Video Super Resolution Using Temporal Encoding ConvLSTM and Multi-Stage Fusion,
VCIP20(298-301)
IEEE DOI 2102
Video super-resolution, ConvLSTM, Inter-frame correlation, Residual stacked bidirectional architecture. Feature extraction, Correlation, Encoding, Image reconstruction, Training, Task analysis, Decoding, video super resolution, convLSTM BibRef

Chen, Y.X.[Yan-Xiang], Zhao, P.C.[Peng-Cheng], Qi, M.[Meibin], Zhao, Y.[Yang], Jia, W.[Wei], Wang, R.G.[Rong-Gang],
Audio Matters in Video Super-Resolution by Implicit Semantic Guidance,
MultMed(24), 2022, pp. 4128-4142.
IEEE DOI 2208
Semantics, Visualization, Task analysis, Superresolution, Image reconstruction, Face recognition, Streaming media, implicit semantic guidance BibRef

Zheng, M.S.[Mei-Song], Xing, Q.L.[Qun-Liang], Qiao, M.L.[Ming-Lang], Xu, M.[Mai], Jiang, L.[Lai], Liu, H.[Huaida], Chen, Y.[Ying],
Progressive Training of A Two-Stage Framework for Video Restoration,
NTIRE22(1023-1030)
IEEE DOI 2210
Training, Recurrent neural networks, Fluctuations, Superresolution, Transfer learning, Transformers, Quality assessment BibRef

Lu, M.X.[Ming-Xuan], Zhang, P.[Peng],
Grouped Spatio-Temporal Alignment Network for Video Super-Resolution,
SPLetters(29), 2022, pp. 2193-2197.
IEEE DOI 2212
Convolution, Information filters, Logic gates, Superresolution, Optical flow, Image restoration, Video super-resolution, inter-group fusion BibRef

Huang, Z.Q.[Zhi-Qiang], Li, Y.J.[Yu-Jia], Bai, M.H.[Meng-Hao], Wei, Q.[Qing], Gu, Q.[Qian], Mou, Z.J.[Zhi-Jun], Zhang, L.P.[Li-Ping], Lei, D.J.[Da-Jiang],
A Multiscale Spatiotemporal Fusion Network Based on an Attention Mechanism,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
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Zhang, D.C.[Da-Cheng], Lei, W.M.[Wei-Min], Zhang, W.[Wei], Chen, X.Y.[Xin-Yi],
Non-local neural networks combined with local importance-based pooling for space-time video super-resolution,
IET-IPR(17), No. 4, 2023, pp. 1097-1110.
DOI Link 2303
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Liu, M.Q.[Mei-Qin], Jin, S.[Shuo], Yao, C.[Chao], Lin, C.Y.[Chun-Yu], Zhao, Y.[Yao],
Temporal Consistency Learning of Inter-Frames for Video Super-Resolution,
CirSysVideo(33), No. 4, April 2023, pp. 1507-1520.
IEEE DOI 2304
Superresolution, Circuit stability, Optical flow, Image restoration, Image reconstruction, Degradation, Convolution, video super-resolution BibRef

Zhang, Y.T.[Yuan-Tong], Wang, H.R.[Huai-Rui], Zhu, H.[Han], Chen, Z.Z.[Zhen-Zhong],
Optical Flow Reusing for High-Efficiency Space-Time Video Super Resolution,
CirSysVideo(33), No. 5, May 2023, pp. 2116-2128.
IEEE DOI 2305
Optical flow, Superresolution, Spatial resolution, Interpolation, Task analysis, Estimation, Convolution, Video super-resolution, optical flow BibRef

Zhang, H.[Huan], Cao, Y.H.[Yi-Hao], Cai, J.[Jianghui], Cai, X.[Xingjuan], Zhang, W.[Wensheng],
Dual feature enhanced video super-resolution network based on low-light scenarios,
SP:IC(115), 2023, pp. 116984.
Elsevier DOI 2306
Video super-resolution (VSR), Feature enhancement, Information re-fusion, Attention mechanism BibRef

Hu, M.S.[Meng-Shun], Jiang, K.[Kui], Wang, Z.[Zheng], Bai, X.[Xiang], Hu, R.M.[Rui-Min],
CycMuNet+: Cycle-Projected Mutual Learning for Spatial-Temporal Video Super-Resolution,
PAMI(45), No. 11, November 2023, pp. 13376-13392.
IEEE DOI 2310
BibRef

Xiao, Y.[Yi], Yuan, Q.Q.[Qiang-Qiang], Jiang, K.[Kui], Jin, X.Y.[Xian-Yu], He, J.[Jiang], Zhang, L.P.[Liang-Pei], Lin, C.W.[Chia-Wen],
Local-Global Temporal Difference Learning for Satellite Video Super-Resolution,
CirSysVideo(34), No. 4, April 2024, pp. 2789-2802.
IEEE DOI Code:
WWW Link. 2404
Satellites, Optical flow, Convolution, Estimation, Superresolution, Remote sensing, Satellite video BibRef

Hu, M.S.[Meng-Shun], Jiang, K.[Kui], Liao, L.[Liang], Xiao, J.[Jing], Jiang, J.J.[Jun-Jun], Wang, Z.[Zheng],
Spatial-Temporal Space Hand-in-Hand: Spatial-Temporal Video Super-Resolution via Cycle-Projected Mutual Learning,
CVPR22(3564-3573)
IEEE DOI 2210
Correlation, Codes, Superresolution, Benchmark testing, Pattern recognition, Iterative methods, Image and video synthesis and generation BibRef

Zhang, F.[Fan], Chen, G.G.[Gong-Guan], Wang, H.[Hua], Li, J.J.[Jin-Jiang], Zhang, C.M.[Cai-Ming],
Multi-Scale Video Super-Resolution Transformer With Polynomial Approximation,
CirSysVideo(33), No. 9, September 2023, pp. 4496-4506.
IEEE DOI 2310
BibRef

Feng, Z.C.[Zi-Cheng], Zhang, W.L.[Wen-Long], Liang, S.[Shunkun], Yu, Q.F.[Qi-Feng],
Deep Video Super-Resolution Using Hybrid Imaging System,
CirSysVideo(33), No. 9, September 2023, pp. 4855-4867.
IEEE DOI 2310
BibRef

Chen, R.[Rui], Mu, Y.[Yang], Zhang, Y.[Yan],
High-order relational generative adversarial network for video super-resolution,
PR(146), 2024, pp. 110059.
Elsevier DOI 2311
Video super-resolution, Motion compensation, Generative adversarial network, High-order relations BibRef

Wang, H.[Hai], Yang, W.M.[Wen-Ming], Liao, Q.M.[Qing-Min], Zhou, J.[Jie],
Bi-RSTU: Bidirectional Recurrent Upsampling Network for Space-Time Video Super-Resolution,
MultMed(25), 2023, pp. 4742-4751.
IEEE DOI 2311
BibRef

Zhu, J.[Jian], Zhang, Q.W.[Qing-Wu], Fei, L.[Lunke], Cai, R.[Ruichu], Xie, Y.[Yuan], Sheng, B.[Bin], Yang, X.K.[Xiao-Kang],
FFFN: Frame-By-Frame Feedback Fusion Network for Video Super-Resolution,
MultMed(25), 2023, pp. 6821-6835.
IEEE DOI 2311
BibRef

Fu, C.R.[Cong-Rui], Yuan, H.[Hui], Xu, H.J.[Hong-Ji], Zhang, H.[Hao], Shen, L.Q.[Li-Quan],
Cuboid-Net: A multi-branch convolutional neural network for joint space-time video super resolution,
IET-IPR(17), No. 14, 2023, pp. 4089-4101.
DOI Link 2312
image enhancement, image resolution, video signal processing BibRef

Baniya, A.A.[Arbind Agrahari], Lee, T.K.[Tsz-Kwan], Eklund, P.W.[Peter W.], Aryal, S.I.[Sun-Il],
Omnidirectional Video Super-Resolution Using Deep Learning,
MultMed(26), 2024, pp. 540-554.
IEEE DOI 2402
Superresolution, Feature extraction, Streaming media, Spatial resolution, Solid modeling, Optimization, Distortion, weighted spherically smooth L1 loss function BibRef

Liang, J.Y.[Jing-Yun], Cao, J.Z.[Jie-Zhang], Fan, Y.C.[Yu-Chen], Zhang, K.[Kai], Ranjan, R.[Rakesh], Li, Y.[Yawei], Timofte, R.[Radu], Van Gool, L.J.[Luc J.],
VRT: A Video Restoration Transformer,
IP(33), 2024, pp. 2171-2182.
IEEE DOI Code:
WWW Link. 2404
Image restoration, Feature extraction, Transformers, Image reconstruction, Superresolution, Task analysis, spacetime video super-resolution BibRef

Yin, G.H.[Guang-Hao], Qu, Z.[Zefan], Jiang, X.Y.[Xin-Yang], Jiang, S.[Shan], Han, Z.H.[Zhen-Hua], Zheng, N.[Ningxin], Yang, H.[Huan], Liu, X.H.[Xiao-Hong], Yang, Y.Q.[Yu-Qing], Li, D.S.[Dong-Sheng], Qiu, L.[Lili],
Online Streaming Video Super-Resolution With Convolutional Look-Up Table,
IP(33), 2024, pp. 2305-2317.
IEEE DOI Code:
WWW Link. 2404
Streaming media, Table lookup, Degradation, Bandwidth, WebRTC, Bit rate, Superresolution, Adaptive online bitstream, look-up table BibRef

Park, T.N.[Tony Nokap], Jeon, Y.H.[Yun-Ho], Na, T.[Taeyoung],
RealPixVSR: Pixel-Level Visual Representation Informed Super-Resolution of Real-World Videos,
VAQuality24(412-421)
IEEE DOI 2404
Degradation, Visualization, Sensitivity, Superresolution, Self-supervised learning BibRef

Bai, H.R.[Hao-Ran], Pan, J.S.[Jin-Shan],
Self-Supervised Deep Blind Video Super-Resolution,
PAMI(46), No. 7, July 2024, pp. 4641-4653.
IEEE DOI 2406
Kernel, Estimation, Image restoration, Self-supervised learning, Optical flow, Training, Superresolution, Self-supervised learning, deep learning BibRef

Pan, J.S.[Jin-Shan], Bai, H.R.[Hao-Ran], Dong, J.X.[Jiang-Xin], Zhang, J.W.[Jia-Wei], Tang, J.H.[Jin-Hui],
Deep Blind Video Super-resolution,
ICCV21(4791-4800)
IEEE DOI 2203
Degradation, Deconvolution, Superresolution, Feature extraction, Image restoration, Data mining, BibRef

Yoo, J.[Jinsu], Nam, J.[Jihoon], Baik, S.[Sungyong], Kim, T.H.[Tae Hyun],
Looking beyond input frames: Self-supervised adaptation for video super-resolution,
PR(154), 2024, pp. 110602.
Elsevier DOI Code:
WWW Link. 2406
Video super-resolution, Test-time adaptation, Knowledge distillation, Patch-recurrence BibRef

Tang, J.[Jun], Lu, C.Y.[Chen-Yan], Liu, Z.X.[Zheng-Xue], Li, J.[Jiale], Dai, H.[Hang], Ding, Y.[Yong],
CTVSR: Collaborative Spatial-Temporal Transformer for Video Super-Resolution,
CirSysVideo(34), No. 6, June 2024, pp. 5018-5032.
IEEE DOI 2406
Transformers, Computational modeling, Superresolution, Optical imaging, Fuses, Image restoration, Collaboration, trajectory BibRef

Lin, X.[Xin], Chen, J.L.[Jun-Li], Ai, S.J.[Shao-Jie], Liu, J.[Jing], Li, B.[Bochao], Li, Q.Y.[Qing-Ying], Ma, R.[Rui],
MSTG: Multi-Scale Transformer with Gradient for joint spatio-temporal enhancement,
JVCIR(102), 2024, pp. 104209.
Elsevier DOI 2407
Video Bit-Depth Enhancement, Video super-resolution, Deep learning, Transformer BibRef

Luo, L.G.[Lai-Gan], Yi, B.S.[Ben-Shun], Wang, Z.Y.[Zhong-Yuan], He, Z.[Zheng], Zhu, C.[Chao],
Bidirectional scale-aware upsampling network for arbitrary-scale video super-resolution,
IVC(148), 2024, pp. 105116.
Elsevier DOI 2407
Video super-resolution, Arbitrary-scale factor, Bidirectional module, Upsampling module BibRef

Shi, Z.Q.[Zi-Qiang], Liu, R.J.[Ru-Jie],
Conditional Velocity Score Estimation for Image Restoration,
WACV24(178-187)
IEEE DOI 2404
Training, Degradation, Monte Carlo methods, Current measurement, Superresolution, Estimation, Differential equations, Algorithms, Image recognition and understanding BibRef

Li, F.[Fei], Zhang, L.F.[Lin-Feng], Liu, Z.[Zikun], Lei, J.[Juan], Li, Z.B.[Zhen-Bo],
Multi-Frequency Representation Enhancement with Privilege Information for Video Super-Resolution,
ICCV23(12768-12779)
IEEE DOI 2401
BibRef

Chen, Y.H.[Yi-Hsin], Chen, S.C.[Si-Cun], Chen, Y.H.[Yi-Hsin], Lin, Y.Y.[Yen-Yu], Peng, W.H.[Wen-Hsiao],
MoTIF: Learning Motion Trajectories with Local Implicit Neural Functions for Continuous Space-Time Video Super-Resolution,
ICCV23(23074-23084)
IEEE DOI Code:
WWW Link. 2401
BibRef

Rahimi, N.[Nasrin], Tekalp, A.M.[A. Murat],
Spatio-Temporal Perception-Distortion Trade-Off in Learned Video SR,
ICIP23(1400-1404)
IEEE DOI 2312
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Huang, Y.N.[Yu-Ning], Wang, T.Q.[Tian-Qi], Lin, Q.[Qian], Allebach, J.P.[Jan P.], Zhu, F.Q.[Feng-Qing],
Efficient Joint Video Denoising and Super-Resolution,
ICIP23(1865-1869)
IEEE DOI Code:
WWW Link. 2312
BibRef

Yang, X.[Xi], Zhang, X.D.[Xin-Dong], Zhang, L.[Lei],
Flow-Guided Deformable Attention Network for Fast Online Video Super-Resolution,
ICIP23(390-394)
IEEE DOI Code:
WWW Link. 2312
BibRef

Kai, D.[Dachun], Zhang, Y.[Yueyi], Sun, X.Y.[Xiao-Yan],
Video Super-Resolution Via Event-Driven Temporal Alignment,
ICIP23(2950-2954)
IEEE DOI Code:
WWW Link. 2312
BibRef

Kim, S.[Sijung], Lee, U.[Ungwon], Jeon, M.[Minyong],
Encoding-Aware Deep Video Super-Resolution Framework,
ICIP23(356-360)
IEEE DOI 2312
BibRef

Jeelani, M.[Mehran], Sadbhawna, Cheema, N.[Noshaba], Illgner-Fehns, K.[Klaus], Slusallek, P.[Philipp], Jaiswal, S.I.[Sun-Il],
Expanding Synthetic Real-World Degradations for Blind Video Super Resolution,
NTIRE23(1199-1208)
IEEE DOI 2309
BibRef

Wang, R.[Ruohao], Liu, X.H.[Xiao-Hui], Zhang, Z.[Zhilu], Wu, X.H.[Xiao-He], Feng, C.M.[Chun-Mei], Zhang, L.[Lei], Zuo, W.M.[Wang-Meng],
Benchmark Dataset and Effective Inter-Frame Alignment for Real-World Video Super-Resolution,
NTIRE23(1168-1177)
IEEE DOI 2309
BibRef

Sun, Y.X.[Yi-Xuan], Zhao, D.Y.[Dong-Yang], Yin, Z.Y.[Zhang-Yue], Huang, Y.[Yiwen], Gui, T.[Tao], Zhang, W.Q.[Wen-Qiang], Ge, W.F.[Wei-Feng],
Correspondence Transformers with Asymmetric Feature Learning and Matching Flow Super-Resolution,
CVPR23(17787-17796)
IEEE DOI 2309
BibRef

Wang, Y.W.[Ying-Wei], Isobe, T.[Takashi], Jia, X.[Xu], Tao, X.[Xin], Lu, H.C.[Hu-Chuan], Tai, Y.W.[Yu-Wing],
Compression-Aware Video Super-Resolution,
CVPR23(2012-2021)
IEEE DOI 2309
BibRef

Lu, Y.F.[Yun-Fan], Wang, Z.P.[Zi-Peng], Liu, M.J.[Min-Jie], Wang, H.J.[Hong-Jian], Wang, L.[Lin],
Learning Spatial-Temporal Implicit Neural Representations for Event-Guided Video Super-Resolution,
CVPR23(1557-1567)
IEEE DOI 2309
BibRef

Gao, Y.X.[Yi-Xuan], Cao, Y.Q.[Yu-Qin], Kou, T.C.[Teng-Chuan], Sun, W.[Wei], Dong, Y.L.[Yun-Long], Liu, X.H.[Xiao-Hong], Min, X.K.[Xiong-Kuo], Zhai, G.T.[Guang-Tao],
VDPVE: VQA Dataset for Perceptual Video Enhancement,
NTIRE23(1474-1483)
IEEE DOI 2309
BibRef

Feng, Y.[Yu], Hansen, P.[Patrick], Whatmough, P.N.[Paul N.], Lu, G.Y.[Guo-Yu], Zhu, Y.H.[Yu-Hao],
Fast and Accurate: Video Enhancement Using Sparse Depth,
WACV23(4481-4489)
IEEE DOI 2302
Point cloud compression, Laser radar, Fuses, Superresolution, Noise reduction, Buildings, Algorithms: 3D computer vision, Embedded sensing/real-time techniques BibRef

Lee, E.[Eugene], Hsu, L.F.[Lien-Feng], Chen, E.[Evan], Lee, C.Y.[Chen-Yi],
Cross-Resolution Flow Propagation for Foveated Video Super-Resolution,
WACV23(1766-1775)
IEEE DOI 2302
Visualization, Solid modeling, Additives, Gaussian noise, Superresolution, Virtual reality, Streaming media, Virtual/augmented reality BibRef

Kim, Y.[Youngrae], Lim, J.[Jinsu], Cho, H.[Hoonhee], Lee, M.J.[Min-Ji], Lee, D.[Dongman], Yoon, K.J.[Kuk-Jin], Choi, H.J.[Ho-Jin],
Efficient Reference-based Video Super-Resolution (ERVSR): Single Reference Image Is All You Need,
WACV23(1828-1837)
IEEE DOI 2302
Runtime, Correlation, Computational modeling, Superresolution, Memory management, Graphics processing units, image and video synthesis BibRef

Yue, H.[Huanjing], Zhang, Z.M.[Zhi-Ming], Yang, J.Y.[Jing-Yu],
Real-RawVSR: Real-World Raw Video Super-Resolution with a Benchmark Dataset,
ECCV22(VI:608-624).
Springer DOI 2211
BibRef

Zhang, H.S.[Heng-Sheng], Zou, X.[Xueyi], Guo, J.M.[Jia-Ming], Yan, Y.L.[You-Liang], Xie, R.[Rong], Song, L.[Li],
A Codec Information Assisted Framework for Efficient Compressed Video Super-Resolution,
ECCV22(XVII:220-235).
Springer DOI 2211
BibRef

Suzuki, K.[Keito], Ikehara, M.[Masaaki],
Multi-Stage Feature Alignment Network for Video Super-Resolution,
ICIP22(2001-2005)
IEEE DOI 2211
Image quality, Fuses, Convolution, Superresolution, Neural networks, Spatial resolution, Optical flow, Video Super-Resolution, Convolutional Neural Networks BibRef

Ni, N.[Ning], Wu, H.L.[Han-Lin], Zhang, L.[Libao],
Deformable Alignment And Scale-Adaptive Feature Extraction Network For Continuous-Scale Satellite Video Super-Resolution,
ICIP22(2746-2750)
IEEE DOI 2211
Satellites, Image communication, Superresolution, Wheels, Routing, Feature extraction, Multitasking, Video super-resolution, feature-adaptive walk BibRef

Cao, J.Z.[Jie-Zhang], Liang, J.Y.[Jing-Yun], Zhang, K.[Kai], Wang, W.G.[Wen-Guan], Wang, Q.[Qin], Zhang, Y.[Yulun], Tang, H.[Hao], Van Gool, L.J.[Luc J.],
Towards Interpretable Video Super-Resolution via Alternating Optimization,
ECCV22(XVIII:393-411).
Springer DOI 2211
BibRef

Lee, J.Y.[Jun-Yong], Lee, M.[Myeonghee], Cho, S.Y.[Sungh-Yun], Lee, S.Y.[Seung-Yong],
Reference-Based Video Super-Resolution Using Multi-Camera Video Triplets,
CVPR22(17803-17812)
IEEE DOI 2210
Training, Adaptation models, Fuses, Computational modeling, Superresolution, Video sequences, Memory management, Low-level vision BibRef

Yu, J.Y.[Ji-Yang], Liu, J.G.[Jin-Gen], Bo, L.F.[Lie-Feng], Mei, T.[Tao],
Memory-Augmented Non-Local Attention for Video Super-Resolution,
CVPR22(17813-17822)
IEEE DOI 2210
Training, Codes, Superresolution, Performance gain, Benchmark testing, Pattern recognition, Image and video synthesis and generation BibRef

Geng, Z.C.[Zhi-Cheng], Liang, L.[Luming], Ding, T.Y.[Tian-Yu], Zharkov, I.[Ilya],
RSTT: Real-time Spatial Temporal Transformer for Space-Time Video Super-Resolution,
CVPR22(17420-17430)
IEEE DOI 2210
Interpolation, Dictionaries, Superresolution, Streaming media, Transformers, Feature extraction, Real-time systems, Computational photography BibRef

Chan, K.C.K.[Kelvin C.K.], Zhou, S.C.[Shang-Chen], Xu, X.Y.[Xiang-Yu], Loy, C.C.[Chen Change],
Investigating Tradeoffs in Real-World Video Super-Resolution,
CVPR22(5952-5961)
IEEE DOI 2210
Degradation, Training, Codes, Computational modeling, Superresolution, Video sequences, Low-level vision BibRef

Chan, K.C.K.[Kelvin C.K.], Zhou, S.C.[Shang-Chen], Xu, X.Y.[Xiang-Yu], Loy, C.C.[Chen Change],
BasicVSR++: Improving Video Super-Resolution with Enhanced Propagation and Alignment,
CVPR22(5962-5971)
IEEE DOI 2210
Computational modeling, Superresolution, Spatiotemporal phenomena, Pattern recognition, Task analysis, Low-level vision BibRef

Cho, H.M.[Hyun Min], Choi, K.[Kiho],
Super-Resolution based Video Coding Scheme,
CLIC22(1777-1779)
IEEE DOI 2210
Video coding, Visualization, Image coding, Superresolution, Encoding, Decoding, Pattern recognition BibRef

Yang, J.Y.[Jia-Yu], Yang, C.H.[Chun-Hui], Xiong, F.[Fei], Wang, F.[Feng], Wang, R.G.[Rong-Gang],
Learned Low Bitrate Video Compression with Space-Time Super-Resolution,
CLIC22(1785-1789)
IEEE DOI 2210
Convolution, Computational modeling, Superresolution, Bit rate, Video compression BibRef

Imani, H.[Hassan], Islam, M.B.[Md Baharul], Wong, L.K.[Lai-Kuan],
A New Dataset and Transformer for Stereoscopic Video Super-Resolution,
NTIRE22(705-714)
IEEE DOI 2210
Stereo image processing, Superresolution, Transformers, Optical imaging, Pattern recognition, Task analysis BibRef

Chen, Z.[Zeyuan], Chen, Y.[Yinbo], Liu, J.W.[Jing-Wen], Xu, X.Q.[Xing-Qian], Goel, V.[Vidit], Wang, Z.Y.[Zhang-Yang], Shi, H.[Humphrey], Wang, X.L.[Xiao-Long],
VideoINR: Learning Video Implicit Neural Representation for Continuous Space-Time Super-Resolution,
CVPR22(2037-2047)
IEEE DOI 2210
Visualization, Interpolation, Costs, Codes, Superresolution, Pattern recognition, Low-level vision, Representation learning BibRef

Chiche, B.N.[Benjamin Naoto], Woiselle, A.[Arnaud], Frontera-Pons, J.[Joana], Starck, J.L.[Jean-Luc],
Stable Long-Term Recurrent Video Super-Resolution,
CVPR22(827-836)
IEEE DOI 2210
Deep learning, Computational modeling, Superresolution, Video sequences, Video surveillance, Stability analysis, Machine learning BibRef

Chiche, B.N.[Benjamin Naoto], Frontera-Pons, J.[Joana], Woiselle, A.[Arnaud], Starck, J.L.[Jean-Luc],
Deep Unrolled Network for Video Super-Resolution,
IPTA20(1-6)
IEEE DOI 2206
Degradation, Deep learning, Neural networks, Image restoration, Iterative methods, Task analysis, Optimization, unrolled optimization algorithm BibRef

Khani, M.[Mehrdad], Sivaraman, V.[Vibhaalakshmi], Alizadeh, M.[Mohammad],
Efficient Video Compression via Content-Adaptive Super-Resolution,
ICCV21(4501-4510)
IEEE DOI 2203
Computational modeling, Superresolution, Neural networks, Video compression, Streaming media, Quality assessment, Internet, Machine learning architectures and formulations BibRef

Li, Y.X.[Yin-Xiao], Jin, P.C.[Peng-Chong], Yang, F.[Feng], Liu, C.[Ce], Yang, M.H.[Ming-Hsuan], Milanfar, P.[Peyman],
COMISR: Compression-Informed Video Super-Resolution,
ICCV21(2523-2532)
IEEE DOI 2203
Performance evaluation, Laplace equations, Computational modeling, Superresolution, Estimation, Image and video synthesis BibRef

Yang, X.[Xi], Xiang, W.M.[Wang-Meng], Zeng, H.[Hui], Zhang, L.[Lei],
Real-world Video Super-resolution: A Benchmark Dataset and A Decomposition based Learning Scheme,
ICCV21(4761-4770)
IEEE DOI 2203
Degradation, Training, Visualization, Laplace equations, Superresolution, Video sequences, Benchmark testing, Datasets and evaluation BibRef

You, C.Y.[Chen-Yu], Han, L.Y.[Lian-Yi], Feng, A.[Aosong], Zhao, R.[Ruihan], Tang, H.[Hui], Fan, W.[Wei],
MEGAN: Memory Enhanced Graph Attention Network for Space-Time Video Super-Resolution,
WACV22(3946-3956)
IEEE DOI 2202
Adaptation models, Correlation, Aggregates, Video sequences, Superresolution, Spatial resolution, Large-scale Vision Applications BibRef

Huang, Y.L.[Yu-Lin], Chen, J.[Junying],
Improved EDVR Model for Robust and Efficient Video Super-Resolution,
VAQuality22(103-111)
IEEE DOI 2202
Training, Solid modeling, Convolution, Computational modeling, Superresolution BibRef

Ghassab, V.K.[Vahid Khorasani], Bouguila, N.[Nizar],
Hyperspectral Video Super-Resolution Using Beta Process and Bayesian Dictionary Learning,
ISVC21(II:251-262).
Springer DOI 2112
BibRef

Xiang, L.[Lichuan], Lee, R.[Royson], Abdelfattah, M.S.[Mohamed S.], Lane, N.D.[Nicholas D.], Wen, H.K.[Hong-Kai],
Temporal Kernel Consistency for Blind Video Super-Resolution,
RLQ21(3470-3479)
IEEE DOI 2112
Degradation, Visualization, Superresolution, Estimation, Motion compensation BibRef

Jing, Y.C.[Yong-Cheng], Yang, Y.D.[Yi-Ding], Wang, X.C.[Xin-Chao], Song, M.L.[Ming-Li], Tao, D.C.[Da-Cheng],
Turning Frequency to Resolution: Video Super-resolution via Event Cameras,
CVPR21(7768-7777)
IEEE DOI 2111
Performance evaluation, Interpolation, Image color analysis, Superresolution, Streaming media, Cameras, Turning BibRef

Chan, K.C.K.[Kelvin C.K.], Wang, X.[Xintao], Yu, K.[Ke], Dong, C.[Chao], Loy, C.C.[Chen Change],
BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond,
CVPR21(4945-4954)
IEEE DOI 2111
Systematics, Superresolution, Pipelines, Noise reduction, Computer architecture, Pattern recognition BibRef

Liu, S.L.[Shao-Li], Zheng, C.J.[Cheng-Jian], Lu, K.D.[Kai-Di], Gao, S.[Si], Wang, N.[Ning], Wang, B.F.[Bo-Fei], Zhang, D.K.[Dian-Kai], Zhang, X.F.[Xiao-Feng], Xu, T.Y.[Tian-Yu],
EVSRNet: Efficient Video Super-Resolution with Neural Architecture Search,
MAI21(2480-2485)
IEEE DOI 2109
Visualization, Superresolution, Video sequences, Neural networks, Computer architecture, Streaming media, Real-time systems BibRef

Zheng, H.[He], Li, X.[Xin], Liu, F.L.[Fang-Long], Jiang, L.L.[Lie-Lin], Zhang, Q.[Qi], Li, F.[Fu], Dang, Q.Q.[Qing-Qing], He, D.L.[Dong-Liang],
Adaptive Spatial-Temporal Fusion of Multi-Objective Networks for Compressed Video Perceptual Enhancement,
NTIRE21(268-275)
IEEE DOI 2109
Training, Adaptation models, Adaptive systems, Fuses, Pattern recognition BibRef

Dutta, S.[Saikat], Shah, N.A.[Nisarg A.], Mittal, A.[Anurag],
Efficient Space-time Video Super Resolution using Low-Resolution Flow and Mask Upsampling,
NTIRE21(314-323)
IEEE DOI 2109
Interpolation, Superresolution, Refining, Pattern recognition, Videos BibRef

Tseng, M.Y.[Min-Yuan], Chen, Y.C.[Yen-Chung], Lee, Y.L.[Yi-Lun], Lai, W.S.[Wei-Sheng], Tsai, Y.H.[Yi-Hsuan], Chiu, W.C.[Wei-Chen],
Dual-Stream Fusion Network for Spatiotemporal Video Super-Resolution,
WACV21(2683-2692)
IEEE DOI 2106
Deep learning, Visualization, Interpolation, Fuses, Superresolution BibRef

Lee, S.Y.[Su-Young], Choi, M.[Myungsub], Lee, K.M.[Kyoung Mu],
DynaVSR: Dynamic Adaptive Blind Video Super-Resolution,
WACV21(2092-2101)
IEEE DOI 2106
Adaptation models, Computational modeling, Superresolution, Estimation, Performance gain BibRef

Wang, H., Sun, W., Chen, Z., Yang, D.,
DOVE: Decomposition Oriented Video super-rEsolution,
VCIP20(375-378)
IEEE DOI 2102
Convolution, Feature extraction, Computer architecture, Training, Optical imaging, non-local attention BibRef

Li, W.B.[Wen-Bo], Tao, X.[Xin], Guo, T.[Taian], Qi, L.[Lu], Lu, J.B.[Jiang-Bo], Jia, J.Y.[Jia-Ya],
MuCAN: Multi-correspondence Aggregation Network for Video Super-resolution,
ECCV20(X:335-351).
Springer DOI 2011
BibRef

Kang, J.Y.[Jae-Yeon], Jo, Y.H.[Young-Hyun], Oh, S.W.[Seoung Wug], Vajda, P.[Peter], Kim, S.J.[Seon Joo],
Deep Space-time Video Upsampling Networks,
ECCV20(X:701-717).
Springer DOI 2011
BibRef

Isobe, T.[Takashi], Jia, X.[Xu], Gu, S.H.[Shu-Hang], Li, S.J.[Song-Jiang], Wang, S.J.[Sheng-Jin], Tian, Q.[Qi],
Video Super-resolution with Recurrent Structure-detail Network,
ECCV20(XII: 645-660).
Springer DOI 2010
BibRef

Tian, Y.P.[Ya-Peng], Zhang, Y.L.[Yu-Lun], Fu, Y.[Yun], Xu, C.L.[Chen-Liang],
TDAN: Temporally-Deformable Alignment Network for Video Super-Resolution,
CVPR20(3357-3366)
IEEE DOI 2008
Optical imaging, Image resolution, Image reconstruction, Convolution, Feature extraction, Optical fiber networks, Kernel BibRef

Xiang, X., Tian, Y., Zhang, Y., Fu, Y., Allebach, J.P., Xu, C.,
Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution,
CVPR20(3367-3376)
IEEE DOI 2008
Interpolation, Spatial resolution, Feature extraction, Convolution, Video sequences, Image reconstruction BibRef

Isobe, T.[Takashi], Jia, X.[Xu], Tao, X.[Xin], Li, C.[Changlin], Li, R.[Ruihuang], Shi, Y.J.[Yong-Jie], Mu, J.[Jing], Lu, H.C.[Hu-Chuan], Tai, Y.W.[Yu-Wing],
Look Back and Forth: Video Super-Resolution with Explicit Temporal Difference Modeling,
CVPR22(17390-17399)
IEEE DOI 2210
Convolution, Computational modeling, Superresolution, Optical distortion, Feature extraction, Distortion, Image and video synthesis and generation BibRef

Isobe, T., Li, S., Jia, X., Yuan, S., Slabaugh, G., Xu, C., Li, Y., Wang, S., Tian, Q.,
Video Super-Resolution With Temporal Group Attention,
CVPR20(8005-8014)
IEEE DOI 2008
Spatial resolution, Motion compensation, Optical distortion, Feature extraction, Motion estimation BibRef

Singh, V., Sharma, A., Devanathan, S., Mittal, A.,
High-Frequency Refinement for Sharper Video Super-Resolution,
WACV20(3288-3297)
IEEE DOI 2006
Spatial resolution, Training, Signal resolution, Feature extraction, Task analysis, Generative adversarial networks BibRef

Kim, S., Li, G., Fuoli, D., Danelljan, M., Huang, Z., Gu, S., Timofte, R.,
The Vid3oC and IntVID Datasets for Video Super Resolution and Quality Mapping,
AIM19(3609-3616)
IEEE DOI 2004
cameras, image enhancement, image resolution, smart phones, stereo image processing, video signal processing, Video Quality Mapping BibRef

Park, B., Yu, S., Jeong, J.,
Robust Temporal Super-Resolution for Dynamic Motion Videos,
AIM19(3494-3502)
IEEE DOI 2004
Code, Super Resolution.
WWW Link. image motion analysis, image resolution, image sequences, learning (artificial intelligence), neural nets, Deep learning BibRef

Yi, P., Wang, Z., Jiang, K., Jiang, J., Ma, J.,
Progressive Fusion Video Super-Resolution Network via Exploiting Non-Local Spatio-Temporal Correlations,
ICCV19(3106-3115)
IEEE DOI 2004
image fusion, image resolution, motion compensation, motion estimation, video signal processing, consecutive frames, Fuses BibRef

Li, S.[Sheng], He, F.X.[Feng-Xiang], Du, B.[Bo], Zhang, L.F.[Le-Fei], Xu, Y.H.[Yong-Hao], Tao, D.C.[Da-Cheng],
Fast Spatio-Temporal Residual Network for Video Super-Resolution,
CVPR19(10514-10523).
IEEE DOI 2002
BibRef

Lopez-Tapia, S., Lucas, A., Molina, R., Katsaggelos, A.K.,
GAN-Based Video Super-Resolution With Direct Regularized Inversion of the Low-Resolution Formation Model,
ICIP19(2886-2890)
IEEE DOI 1910
Video, Super-resolution, Convolutional Neuronal Networks, Generative Adversarial Networks, Perceptual Loss Functions BibRef

Meng, X., Deng, X., Zhu, S., Zeng, B.,
Enhancing Quality for VVC Compressed Videos by Jointly Exploiting Spatial Details and Temporal Structure,
ICIP19(1193-1197)
IEEE DOI 1910
versatile video coding, spatial-temporal structure, motion compensation, quality enhancement BibRef

Lu, M., Cheng, M., Xu, Y., Pu, S., Shen, Q., Ma, Z.,
Learned Quality Enhancement via Multi-Frame Priors for HEVC Compliant Low-Delay Applications,
ICIP19(934-938)
IEEE DOI 1910
Video quality enhancement, multi-scale spatial priors, multi-frame temporal priors, post-processing, HEVC BibRef

Lu, S.[Si],
High-Speed Video from Asynchronous Camera Array,
WACV19(2196-2205)
IEEE DOI 1904
Similart to HDR, but for High Time Resolution -- multiple cameras. Jitter, paralax, etc. cameras, image motion analysis, image segmentation, Markov processes, rendering (computer graphics), Sensor arrays BibRef

Sajjadi, M.S.M.[Mehdi S. M.], Vemulapalli, R., Brown, M.,
Frame-Recurrent Video Super-Resolution,
CVPR18(6626-6634)
IEEE DOI 1812
Spatial resolution, Training, Computer architecture, Optical losses, Image reconstruction, Optical imaging BibRef

Jo, Y., Oh, S.W., Kang, J., Kim, S.J.,
Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation,
CVPR18(3224-3232)
IEEE DOI 1812
Image resolution, Dynamics, Motion compensation, Motion estimation, Convolution, Neural networks BibRef

Chen, L., Dan, W., Cao, L., Wang, C., Li, J.,
Joint Denoising and Super-Resolution via Generative Adversarial Training,
ICPR18(2753-2758)
IEEE DOI 1812
Image resolution, Noise reduction, Signal resolution, Generators, White noise, Task analysis, Generative adversarial networks, GAN BibRef

Geiping, J.[Jonas], Dirks, H.[Hendrik], Cremers, D.[Daniel], Moeller, M.[Michael],
Multiframe Motion Coupling for Video Super Resolution,
EMMCVPR17(123-138).
Springer DOI 1805
BibRef

Papadopoulos, M.A., Rai, Y., Katsenou, A.V., Agrafiotis, D., Le Callet, P., Bull, D.R.[David R.],
Video quality enhancement via QP adaptation based on perceptual coding maps,
ICIP17(2741-2745)
IEEE DOI 1803
Bit rate, Encoding, Feature extraction, Sensitivity, Standards, Video coding, Visualization, HEVC, Perceptual coding maps, subjective quality BibRef

Tao, X., Gao, H., Liao, R., Wang, J., Jia, J.,
Detail-Revealing Deep Video Super-Resolution,
ICCV17(4482-4490)
IEEE DOI 1802
image resolution, motion compensation, neural nets, video signal processing, Optical variables control BibRef

Toutounchi, F., Izquierdo, E.,
Advanced Super-Resolution Using Lossless Pooling Convolutional Networks,
WACV19(1562-1568)
IEEE DOI 1904
convolutional neural nets, image enhancement, image fusion, image resolution, learning (artificial intelligence), Correlation BibRef

Ebadi, S.E., Ones, V.G., Izquierdo, E.,
UHD Video Super-Resolution Using Low-Rank and Sparse Decomposition,
RSL-CV17(1889-1897)
IEEE DOI 1802
Adaptation models, Computational modeling, Dictionaries, Image resolution, Minimization, Redundancy, Testing BibRef

Zhang, Z., Sze, V.,
FAST: A Framework to Accelerate Super-Resolution Processing on Compressed Videos,
NTIRE17(1015-1024)
IEEE DOI 1709
Acceleration, Correlation, Image resolution, Interpolation, Motion compensation, Videos, Visualization BibRef

Yu, W.J.[Wen-Jing], Zhang, M.J.[Ming-Jun],
A mixed particle swarm optimization algorithm's application in image/video super-resolution reconstruction,
ICIVC17(526-530)
IEEE DOI 1708
Algorithm design and analysis, Convergence, Image reconstruction, Image resolution, Image sequences, Optimization, Particle swarm optimization, PSO, image/video, super-resolution, reconstruction BibRef

Makansi, O.[Osama], Ilg, E.[Eddy], Brox, T.[Thomas],
End-to-End Learning of Video Super-Resolution with Motion Compensation,
GCPR17(203-214).
Springer DOI 1711
BibRef

Dai, M.H.[Mao-Hua], He, X.H.[Xiao-Hai], Wang, Z.Y.[Zheng-Yong], Chen, H.G.[Hong-Gang], Tao, Q.C.[Qing-Chuan],
Video super-resolution using multiple complementary priors,
ICIVC17(510-515)
IEEE DOI 1708
Data mining, Image edge detection, Image reconstruction, Information filtering, Kernel, Spatial resolution, inter-correlation, intra-correlation, multiple priors, residual framework, video, super-resolution BibRef

Komatsu, T., Kondou, S., Saito, T.,
Restoration of a Poissonian-Gaussian color moving-image sequence with virtual multiplex imaging and super-resolution deblurring,
ICIP16(1963-1967)
IEEE DOI 1610
Color BibRef

Hsiao, P.H.[Pai-Heng], Chang, P.L.[Ping-Lin],
Video Enhancement via Super-Resolution Using Deep Quality Transfer Network,
ACCV16(III: 184-200).
Springer DOI 1704
BibRef

Chen, Y.T., Tu, W.C., Chien, S.Y.,
Fast video super-resolution via approximate nearest neighbor search,
ICIP16(1141-1144)
IEEE DOI 1610
Computer vision BibRef

Kappeler, A., Yoo, S., Dai, Q., Katsaggelos, A.K.,
Super-resolution of compressed videos using convolutional neural networks,
ICIP16(1150-1154)
IEEE DOI 1610
Databases BibRef

Bercea, C., Maier, A., Köhler, T.,
Confidence-aware Levenberg-Marquardt optimization for joint motion estimation and super-resolution,
ICIP16(1136-1140)
IEEE DOI 1610
Estimation BibRef

Ma, Z.Y.[Zi-Yang], Liao, R.J.[Ren-Jie], Tao, X.[Xin], Xu, L.[Li], Jia, J.Y.[Jia-Ya], Wu, E.[Enhua],
Handling motion blur in multi-frame super-resolution,
CVPR15(5224-5232)
IEEE DOI 1510
BibRef

Liao, R., Tao, X., Li, R., Ma, Z., Jia, J.,
Video Super-Resolution via Deep Draft-Ensemble Learning,
ICCV15(531-539)
IEEE DOI 1602
Deconvolution BibRef

Shen, Y.X.[Yu-Xiang], Wu, X.L.[Xiao-Lin], Deng, X.W.[Xiao-Wei],
GPU-aided real-time image/video super resolution based on error feedback,
VCIP14(286-290)
IEEE DOI 1504
error compensation BibRef

Lengyel, R.[Robert], Soroushmehr, S.M.R.[S.M.Reza], Shirani, S.[Shahram],
Multi-view video super-resolution for hybrid cameras using modified NLM and adaptive thresholding,
ICIP14(5437-5441)
IEEE DOI 1502
Cameras BibRef

Matsushita, Y.[Yuki], Kawasaki, H.[Hiroshi], Ono, S.[Shintaro], Ikeuchi, K.[Katsushi],
Simultaneous deblur and super-resolution technique for video sequence captured by hand-held video camera,
ICIP14(4562-4566)
IEEE DOI 1502
Cameras BibRef

You, J.Y.[Jun-Yong], Tai, X.C.[Xue-Cheng],
Enhancing coded video quality with perceptual foveation driven bit allocation strategy,
VCIP13(1-6)
IEEE DOI 1402
data compression BibRef

Chen, J.[Jin], Nunez-Yanez, J.[Jose], Achim, A.[Alin],
Video super-resolution using low rank matrix completion,
ICIP13(1376-1380)
IEEE DOI 1402
Low-rank Matrix Completion BibRef

Jain, A.K.[Ankit K.], Nguyen, T.Q.[Truong Q.],
Video super-resolution for mixed resolution stereo,
ICIP13(962-966)
IEEE DOI 1402
Cameras BibRef

Lee, C.M.[Chang-Ming], Lee, C.J.[Chien-Jung], Hsieh, C.Y.[Chia-Yung], Lie, W.N.[Wen-Nung],
Super-resolution reconstruction of video sequences based on wavelet-domain spatial and temporal processing,
ICPR12(194-197).
WWW Link. 1302
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Ayvaci, A.[Alper], Jin, H.L.[Hai-Lin], Lin, Z.[Zhe], Cohen, S.[Scott], Soatto, S.[Stefano],
Video upscaling via spatio-temporal self-similarity,
ICPR12(2190-2193).
WWW Link. 1302
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Le Montagner, Y.[Yoann], Angelini, E.[Elsa], Olivo-Marin, J.C.[Jean-Christophe],
Video reconstruction using compressed sensing measurements and 3d total variation regularization for bio-imaging applications,
ICIP12(917-920).
IEEE DOI 1302
BibRef

Matsuo, Y.[Yasutaka], Iwasaki, S.[Shinya], Yamamura, Y.[Yuta], Katto, J.[Jiro],
Wavelet domain image super-resolution from digital cinema to ultrahigh definition television by dividing noise component,
VCIP12(1-6).
IEEE DOI 1302
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Liu, Y.[Ying], Wong, A.[Alexander], Fieguth, P.W.[Paul W.],
A structure-guided conditional sampling model for video resolution enhancement,
ICIP11(1169-1172).
IEEE DOI 1201
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Lakshman, H.[Haricharan], Schwarz, H.[Heiko], Blu, T.[Thierry], Wiegand, T.[Thomas],
Generalized interpolation for motion compensated prediction,
ICIP11(1213-1216).
IEEE DOI 1201
BibRef

Su, H.[Heng], Wu, Y.[Ying], Zhou, J.[Jie],
Adaptive incremental video super-resolution with temporal consistency,
ICIP11(1149-1152).
IEEE DOI 1201
BibRef

Takahashi, K.[Keita], Naemura, T.[Takeshi], Tanaka, M.[Masayuki],
Rate-distortion analysis of super-resolution image/video decoding,
ICIP11(1629-1632).
IEEE DOI 1201
BibRef

Shimano, M.[Mihoko], Cheung, G.[Gene], Sato, I.[Imari],
Adaptive frame and QP selection for temporally super-resolved full-exposure-time video,
ICIP11(2253-2256).
IEEE DOI 1201
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An, Y.Z.[Yao-Zu], Lu, Y.[Yao], Yan, Z.[Ziye],
Spatial-Temporal Motion Compensation Based Video Super Resolution,
ACCV10(II: 282-292).
Springer DOI 1011
BibRef

Bagnato, L.[Luigi], Frossard, P.[Pascal], Vandergheynst, P.[Pierre],
Plenoptic spherical sampling,
ICIP12(357-360).
IEEE DOI 1302
BibRef

Bagnato, L.[Luigi], Boursier, Y.[Yannick], Frossard, P.[Pascal], Vandergheynst, P.[Pierre],
Plenoptic based super-resolution for omnidirectional image sequences,
ICIP10(2829-2832).
IEEE DOI 1009

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Anantrasirichai, N., Canagarajah, C.N.,
Spatiotemporal super-resolution for low bitrate H.264 video,
ICIP10(2809-2812).
IEEE DOI 1009
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Sv, B.[Basavaraja], Bopardikar, A.S.[Ajit S.], Velusamy, S.[Sudha],
Detail warping based video super-resolution using image guides,
ICIP10(2009-2012).
IEEE DOI 1009
BibRef

Cho, Y.H.[Yang-Ho], Hwang, K.Y.[Kyu-Young], Lee, H.Y.[Ho-Young], Park, D.S.[Du-Sik],
Generation of high resolution image based on accumulated feature trajectory,
ICIP10(1997-2000).
IEEE DOI 1009
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Lee, I.H.[I-Hsien], Bose, N.K.[Nirmal K.], Lin, C.W.[Chih-Wei],
Locally adaptive regularized super-resolution on video with arbitrary motion,
ICIP10(897-900).
IEEE DOI 1009
BibRef

Islam, M.M.[Mohammad Moinul], Asari, V.K.[Vijayan K.], Islam, M.N.[Mohammed Nazrul], Karim, M.A.[Mohammad A.],
Video Super-Resolution by Adaptive Kernel Regression,
ISVC09(II: 799-806).
Springer DOI 0911
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Colombe, J.B., Necioglu, B.,
Super-Resolution of Video Sequences Using Local Motion Estimates,
AIPR07(95-100).
IEEE DOI 0710
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Vaka, D.[Dileep], Narayanan, P.J., Jawahar, C.V.,
Attention-Based Super Resolution from Videos,
ICCVGIP08(406-412).
IEEE DOI 0812
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Sroubek, F.[Filip], Sorel, M.[Michal], Horackova, I.[Irena], Flusser, J.[Jan],
Patch-based blind deconvolution with parametric interpolation of convolution kernels,
ICIP13(577-581)
IEEE DOI 1402
Cameras BibRef

Sroubek, F.[Filip], Flusser, J.[Jan], Sorel, M.[Michal],
Superresolution and blind deconvolution of video,
ICPR08(1-4).
IEEE DOI 0812
BibRef

Watanabe, K.[Kiyotaka], Iwai, Y.[Yoshio], Haga, T.[Tetsuji], Yachida, M.[Masahiko],
A fast algorithm of video super-resolution using dimensionality reduction by DCT and example selection,
ICPR08(1-5).
IEEE DOI 0812
BibRef

Omer, O.A.[Osama A.], Tanaka, T.[Toshihisa],
Region-Based Super Resolution for Video Sequences Considering Registration Error,
PSIVT09(944-954).
Springer DOI 0901
BibRef

An, Y.Z.[Yao-Zu], Lu, Y.[Yao], Zhai, Z.G.[Zhen-Gang],
Spatially Varying Regularization of Image Sequences Super-Resolution,
ACCV09(III: 475-484).
Springer DOI 0909
BibRef

Simonyan, K., Grishin, S., Vatolin, D., Popov, D.,
Fast video super-resolution via classification,
ICIP08(349-352).
IEEE DOI 0810
BibRef

Prendergast, R.S.[Ryan S.], Nguyen, T.Q.[Truong Q.],
A block-based super-resolution for video sequences,
ICIP08(1240-1243).
IEEE DOI 0810
BibRef

Kondo, S., Toma, T.,
Video Coding with Super-Resolution Post-Processing,
ICIP06(3141-3144).
IEEE DOI 0610
BibRef

Costa, G.H., Bermudez, J.C.M.,
On the Design of the LMS Algorithm for Robustness to Outliers in Super-Resolution Video Reconstruction,
ICIP06(1737-1740).
IEEE DOI 0610
BibRef

Patanavijit, V.[Vorapoj],
A robust iterative multiframe SRR based on Hampel stochastic estimation with Hampel-Tikhonov regularization,
ICPR08(1-4).
IEEE DOI 0812
SRR: Superresolution reconstruction BibRef

Patanavijit, V., Tae-o-sot, S., Jitapunkul, S.,
A Robust Iterative Super-Resolution Reconstruction of Image Sequences using a Lorentzian Bayesian Approach with Fast Affine Block-Based Registration,
ICIP07(V: 393-396).
IEEE DOI 0709
BibRef

Sinha, A.[Abhijit], Wu, X.L.[Xiao-Lin],
Fast Generalized Motion Estimation and Superresolution,
ICIP07(V: 413-416).
IEEE DOI 0709
BibRef

Sankaran, H.E., Gotchev, A., Egiazarian, K.O.,
Efficient Super-Resolution Reconstruction for Translational Motion using a Near Least Squares Resampling Method,
ICIP06(1745-1748).
IEEE DOI 0610
BibRef

Patanavijit, V., Jitapunkul, S.,
An Iterative Super-Resolution Reconstruction of Image Sequences using a Bayesian Approach with BTV prior and Affine Block-Based Registration,
CRV06(45-45).
IEEE DOI 0607
BibRef

Chan, R.H., Shen, Z.[Zuowei], Xia, T.[Tao],
Resolution enhancement for video clips: tight frame approach,
AVSBS05(406-410).
IEEE DOI 0602
BibRef

Hazen, D.[Daniel], Puri, R.[Rohit], Ramchandran, K.[Kannan],
Multi-camera Video Resolution Enhancement by Fusion of Spatial Disparity and Temporal Motion fields,
CVS06(38).
IEEE DOI 0602
BibRef

Vazquez, C., Aly, H.A., Dubois, E., Mitiche, A.,
Motion compensated super-resolution of video by level sets evolution,
ICIP04(III: 1767-1770).
IEEE DOI 0505

See also Approximation of Images by Basis Functions for Multiple Region Segmentation with Level Sets. BibRef

Wu, J.W.[Jun-Wen], Trivedi, M.M., Rao, B.[Bhaskar],
Resolution enhancement by AdaBoost,
ICPR04(IV: 893-896).
IEEE DOI 0409
BibRef
And:
High frequency component compensation based super-resolution algorithm for face video enhancement,
ICPR04(III: 598-601).
IEEE DOI 0409
BibRef

Zhao, W.Y.[Wen-Yi],
Super-resolving compressed video with large artifacts,
ICPR04(I: 516-519).
IEEE DOI 0409
BibRef

Rudin, L.[Lenny], Guichard, F.[Frederic],
Velocity estimation from images sequence and application to super-resolution,
ICIP99(III:527-531).
IEEE DOI contrast-invariant motion segmentation and frame fusion applied to forensic video evidence BibRef 9900

Shin, J.H.[Jeoung Ho], Yoon, J.S.[Joon Shik], Paik, J.K.[Joon Ki], Abidi, M.A.[Mongi A.],
Fast Superresolution for Image Sequences Using Motion Adaptive Relaxation Parameters,
ICIP99(III:676-680).
IEEE DOI BibRef 9900

Avrin, V.[Vadim], Dinstein, I.[Its'hak],
Local Motion Estimation and Resolution Enhancement of Video Sequences,
ICPR98(Vol I: 539-541).
IEEE DOI 9808
BibRef

Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Video Denoising .

Last update:Aug 28, 2024 at 16:02:19