Pérez-Pellitero, E.[Eduardo],
Salvador, J.[Jordi],
Ruiz-Hidalgo, J.[Javier],
Rosenhahn, B.[Bodo],
Antipodally Invariant Metrics for Fast Regression-Based
Super-Resolution,
IP(25), No. 6, June 2016, pp. 2456-2468.
IEEE DOI
1605
BibRef
And:
PSyCo: Manifold Span Reduction for Super Resolution,
CVPR16(1837-1845)
IEEE DOI
1612
BibRef
Earlier:
Bayesian region selection for adaptive dictionary-based
Super-Resolution,
BMVC13(xx-yy).
DOI Link
1402
image resolution
See also Patch-based spatio-temporal super-resolution for video with non-rigid motion.
BibRef
Pérez-Pellitero, E.[Eduardo],
Salvador, J.[Jordi],
Torres-Xirau, I.[Iban],
Ruiz-Hidalgo, J.[Javier],
Rosenhahn, B.[Bodo],
Fast Super-Resolution via Dense Local Training and Inverse Regressor
Search,
ACCV14(III: 346-359).
Springer DOI
1504
BibRef
Xu, K.[Ke],
Wang, X.[Xin],
Yang, X.[Xin],
He, S.F.[Sheng-Feng],
Zhang, Q.A.[Qi-Ang],
Yin, B.C.[Bao-Cai],
Wei, X.P.[Xiao-Peng],
Lau, R.W.H.[Rynson W. H.],
Efficient image super-resolution integration,
VC(34), No. 6-8, June 2018, pp. 1065-1076.
Springer DOI
1806
BibRef
Zhang, L.[Lei],
Wang, P.[Peng],
Shen, C.H.[Chun-Hua],
Liu, L.Q.[Ling-Qiao],
Wei, W.[Wei],
Zhang, Y.N.[Yan-Ning],
van den Hengel, A.J.[Anton J.],
Adaptive Importance Learning for Improving Lightweight Image
Super-Resolution Network,
IJCV(128), No. 2, February 2020, pp. 479-499.
Springer DOI
2002
BibRef
Zhang, X.Y.[Xin-Yan],
Gao, P.[Peng],
Liu, S.X.Y.[Sun-Xiang-Yu],
Zhao, K.Y.[Kong-Ya],
Li, G.T.[Gui-Tao],
Yin, L.G.[Liu-Guo],
Chen, C.W.[Chang Wen],
Accurate and Efficient Image Super-Resolution via Global-Local
Adjusting Dense Network,
MultMed(23), 2021, pp. 1924-1937.
IEEE DOI
2107
Feature extraction, Image reconstruction, Computational modeling,
Task analysis, Computational efficiency, Data mining, refinement structure
BibRef
Sun, W.,
Gong, D.,
Shi, Q.,
van den Hengel, A.J.[Anton J.],
Zhang, Y.N.[Yan-Ning],
Learning to Zoom-In via Learning to Zoom-Out: Real-World
Super-Resolution by Generating and Adapting Degradation,
IP(30), 2021, pp. 2947-2962.
IEEE DOI
2102
Degradation, Training, Kernel, Superresolution, Sun, Learning systems,
Cameras, Super resolution (SR), domain adaptation, unpaired learning
BibRef
Wang, Y.T.[Yun-Tao],
Zhao, L.[Lin],
Liu, L.M.[Li-Man],
Hu, H.F.[Huai-Fei],
Tao, W.B.[Wen-Bing],
URNet: A U-Shaped Residual Network for Lightweight Image
Super-Resolution,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link
2110
BibRef
Wang, L.[Li],
Shen, J.[Jie],
Tang, E.,
Zheng, S.N.[Sheng-Nan],
Xu, L.Z.[Li-Zhong],
Multi-scale attention network for image super-resolution,
JVCIR(80), 2021, pp. 103300.
Elsevier DOI
2110
Super-resolution, Multi-scale, Attention mechanism, Lightweight
BibRef
Qin, Z.[Zhu],
Zhang, T.P.[Tai-Ping],
Explore Connection Pattern and Attention Mechanism for
Lightweight Image Super-Resolution,
ICIP21(1799-1803)
IEEE DOI
2201
Convolution, Design methodology, Superresolution, Stacking,
Feature extraction, Convolutional neural networks,
Super-resolution
BibRef
Zhu, X.Y.[Xiang-Yuan],
Guo, K.[Kehua],
Ren, S.[Sheng],
Hu, B.[Bin],
Hu, M.[Min],
Fang, H.[Hui],
Lightweight Image Super-Resolution With Expectation-Maximization
Attention Mechanism,
CirSysVideo(32), No. 3, March 2022, pp. 1273-1284.
IEEE DOI
2203
Superresolution, Feature extraction, Degradation, Task analysis,
Image reconstruction, Convolutional neural networks,
expectation-maximization attention
BibRef
Wang, H.[Huan],
Zhang, Y.[Yulun],
Qin, C.[Can],
Van Gool, L.J.[Luc J.],
Fu, Y.[Yun],
Global Aligned Structured Sparsity Learning for Efficient Image
Super-Resolution,
PAMI(45), No. 9, September 2023, pp. 10974-10989.
IEEE DOI
2309
BibRef
Wang, J.[Jiamian],
Wang, H.[Huan],
Zhang, Y.[Yulun],
Fu, Y.[Yun],
Tao, Z.Q.[Zhi-Qiang],
Iterative Soft Shrinkage Learning for Efficient Image
Super-Resolution,
ICCV23(12556-12565)
IEEE DOI Code:
WWW Link.
2401
BibRef
Xia, B.[Bin],
He, J.W.[Jing-Wen],
Zhang, Y.[Yulun],
Wang, Y.T.[Yi-Tong],
Tian, Y.[Yapeng],
Yang, W.M.[Wen-Ming],
Van Gool, L.J.[Luc J.],
Structured Sparsity Learning for Efficient Video Super-Resolution,
CVPR23(22638-22647)
IEEE DOI
2309
BibRef
Luo, X.T.[Xiao-Tong],
Xie, Y.[Yuan],
Zhang, Y.[Yulun],
Qu, Y.Y.[Yan-Yun],
Li, C.H.[Cui-Hua],
Fu, Y.[Yun],
Latticenet: Towards Lightweight Image Super-resolution with Lattice
Block,
ECCV20(XXII:272-289).
Springer DOI
2011
BibRef
Xie, F.[Feng],
Lu, P.[Pei],
Liu, X.Y.[Xiao-Yong],
Multi-scale convolutional attention network for lightweight image
super-resolution,
JVCIR(95), 2023, pp. 103889.
Elsevier DOI
2309
Image super-resolution, Convolutional neural network,
Lightweight, Attention mechanism
BibRef
Liu, F.Q.[Fei-Qiang],
Yang, X.M.[Xiao-Min],
de Baets, B.[Bernard],
A Deep Recursive Multi-Scale Feature Fusion Network for Image
Super-Resolution,
JVCIR(90), 2023, pp. 103730.
Elsevier DOI
2301
Single Image Super-Resolution (SISR), Recursive networks,
Multi-scale features, Progressive feature fusion
BibRef
Liu, F.Q.[Fei-Qiang],
Yang, X.M.[Xiao-Min],
de Baets, B.[Bernard],
Lightweight image super-resolution with a feature-refined network,
SP:IC(111), 2023, pp. 116898.
Elsevier DOI
2301
Single image super-resolution, Lightweight network,
Feature similarity, Linear transformation, Feature-refined network
BibRef
Chen, Y.Z.[Yu-Zhen],
Wang, G.C.[Gen-Cheng],
Chen, R.[Rong],
Efficient Multi-Scale Cosine Attention Transformer for Image
Super-Resolution,
SPLetters(30), 2023, pp. 1442-1446.
IEEE DOI
2310
BibRef
Wang, Y.[Yan],
Su, T.T.[Tong-Tong],
Li, Y.[Yusen],
Cao, J.W.[Jiu-Wen],
Wang, G.[Gang],
Liu, X.G.[Xiao-Guang],
DDistill-SR: Reparameterized Dynamic Distillation Network for
Lightweight Image Super-Resolution,
MultMed(25), 2023, pp. 7222-7234.
IEEE DOI
2311
BibRef
Xue, L.X.[Li-Xia],
Shen, J.H.[Jun-Hui],
Wang, R.G.[Rong-Gui],
Yang, J.[Juan],
MFFN: Multi-Path Feedback Fusion Network for Lightweight Image Super
Resolution,
IET-IPR(17), No. 14, 2023, pp. 4190-4201.
DOI Link
2312
image reconstruction, image resolution, image restoration
BibRef
Wang, F.[Fengsui],
Chu, X.[Xi],
HorSR: High-order spatial interactions and residual global filter for
efficient image super-resolution,
SP:IC(127), 2024, pp. 117148.
Elsevier DOI
2408
Super-resolution, Lightweight, Recursive gated convolution,
Residual global filtering
BibRef
Khan, A.H.[Asif Hussain],
Micheloni, C.[Christian],
Martinel, N.[Niki],
Lightweight Prompt Learning Implicit Degradation Estimation Network
for Blind Super Resolution,
IP(33), 2024, pp. 4556-4567.
IEEE DOI
2408
Degradation, Kernel, Wiener filters, Deconvolution, Superresolution,
Estimation, Image reconstruction, Image super-resolution, prompt learning
BibRef
Khan, A.H.[Asif Hussain],
Micheloni, C.[Christian],
Martinel, N.[Niki],
IDENet: Implicit Degradation Estimation Network for Efficient Blind
Super Resolution,
NTIRE24(6065-6075)
IEEE DOI
2410
Degradation, Deconvolution, Closed-form solutions, Wiener filters,
Systematics, Image synthesis, Superresolution
BibRef
Khan, A.H.[Asif Hussain],
Umer, R.M.[Rao Muhammad],
Dunnhofer, M.[Matteo],
Micheloni, C.[Christian],
Martinel, N.[Niki],
LBKENET: lightweight Blur Kernel Estimation Network for Blind Image
Super-resolution,
CIAP23(II:209-222).
Springer DOI
2312
BibRef
Xu, K.[Ke],
Pan, L.[Lulu],
Peng, G.H.[Guo-Hua],
Zhang, W.B.[Wen-Bo],
Lv, Y.H.[Yan-Heng],
Li, G.[Guo],
Li, L.X.[Ling-Xiao],
Lei, L.[Le],
Multi-scale strip-shaped convolution attention network for
lightweight image super-resolution,
SP:IC(128), 2024, pp. 117166.
Elsevier DOI
2409
Image super-resolution, Strip convolution, Attention mechanism,
Lightweight, Convolutional neural network
BibRef
Lv, Y.H.[Yan-Heng],
Pan, L.[Lulu],
Xu, K.[Ke],
Li, G.[Guo],
Zhang, W.B.[Wen-Bo],
Li, L.X.[Ling-Xiao],
Lei, L.[Le],
Enhanced local multi-windows attention network for lightweight image
super-resolution,
CVIU(250), 2025, pp. 104217.
Elsevier DOI
2501
Super-resolution, Local multi-windows attention, Spatial gated network
BibRef
He, X.H.[Xuan-Hua],
Cao, K.[Ke],
Hu, T.[Tao],
Zhang, J.[Jie],
Li, R.[Rui],
Spatially-Adaptive Large-Kernel Network for Efficient Image
Super-Resolution,
SPLetters(31), 2024, pp. 2805-2809.
IEEE DOI
2410
Feature extraction, Convolution, Kernel, Superresolution,
Frequency-domain analysis, Filters, Logic gates, lightweight network
BibRef
Guo, Y.[Yong],
Tan, M.K.[Ming-Kui],
Deng, Z.[Zeshuai],
Wang, J.D.[Jing-Dong],
Chen, Q.[Qi],
Cao, J.[Jiezhang],
Xu, Y.[Yanwu],
Chen, J.[Jian],
Towards Lightweight Super-Resolution With Dual Regression Learning,
PAMI(46), No. 12, December 2024, pp. 8365-8379.
IEEE DOI
2411
Redundancy, Image reconstruction, Computational modeling,
Image coding, Task analysis, Superresolution, Training,
lightweight models
BibRef
Cui, Z.S.[Zhi-Sheng],
Yao, Y.B.[Yi-Bing],
Li, S.L.[Shi-Long],
Zhao, Y.C.[Yong-Can],
Xin, M.[Ming],
A lightweight hash-directed global perception and self-calibrated
multiscale fusion network for image super-resolution,
IVC(151), 2024, pp. 105255.
Elsevier DOI
2411
Lightweight, Efficient, Deep learning, Single image, Super-resolution
BibRef
Liu, C.Y.[Chun-Ying],
Gao, G.W.[Guang-Wei],
Wu, F.[Fei],
Guo, Z.H.[Zhen-Hua],
Yu, Y.[Yi],
An Efficient Feature Reuse Distillation Network for Lightweight Image
Super-Resolution,
CVIU(249), 2024, pp. 104178.
Elsevier DOI
2412
Single-image super-resolution, Lightweight network,
Feature reuse, Transformer
BibRef
Yue, Z.S.[Zong-Sheng],
Wang, J.Y.[Jian-Yi],
Loy, C.C.[Chen Change],
Efficient Diffusion Model for Image Restoration by Residual Shifting,
PAMI(47), No. 1, January 2025, pp. 116-130.
IEEE DOI
2412
Diffusion models, Image restoration, Noise, Degradation,
Superresolution, Schedules, Image synthesis, Face restoration, noise schedule
BibRef
Wang, J.Y.[Jian-Yi],
Yue, Z.S.[Zong-Sheng],
Zhou, S.C.[Shang-Chen],
Chan, K.C.K.[Kelvin C. K.],
Loy, C.C.[Chen Change],
Exploiting Diffusion Prior for Real-World Image Super-Resolution,
IJCV(132), No. 12, December 2024, pp. 5929-5949.
Springer DOI
2501
BibRef
Zhang, D.C.[Da-Cheng],
Zhang, W.[Wei],
Lei, W.M.[Wei-Min],
Chen, X.[Xinyi],
Diverse branch feature refinement network for efficient multi-scale
super-resolution,
IET-IPR(18), No. 6, 2024, pp. 1475-1490.
DOI Link
2405
convolutional neural nets, image enhancement, image processing,
image resolution, image restoration
BibRef
Li, F.[Feng],
Cong, R.M.[Run-Min],
Wu, J.J.[Jing-Jing],
Bai, H.H.[Hui-Hui],
Wang, M.[Meng],
Zhao, Y.[Yao],
SRConvNet: A Transformer-Style ConvNet for Lightweight Image
Super-Resolution,
IJCV(133), No. 1, January 2025, pp. 173-189.
Springer DOI
2501
BibRef
Wu, Y.X.[Yu-Xiang],
Wang, X.Y.[Xiao-Yan],
Liu, X.Y.[Xiao-Yan],
Gao, Y.Z.[Yu-Zhao],
Dou, Y.[Yan],
Pixel integration from fine to coarse for lightweight image
super-resolution,
IVC(154), 2025, pp. 105362.
Elsevier DOI
2502
Image super-resolution, Lightweight, Pixel integration,
Transformer, Retractable attention
BibRef
Li, Y.[Yusong],
Xu, L.W.[Long-Wei],
Yang, W.B.[Wei-Bin],
Geng, D.H.[De-Hua],
Xu, M.Y.[Ming-Yuan],
Dong, Z.Q.[Zhi-Qi],
Wang, P.W.[Peng-Wei],
1D kernel distillation network for efficient image super-resolution,
IVC(154), 2025, pp. 105411.
Elsevier DOI Code:
WWW Link.
2502
Image super-resolution, Large kernel attention,
Information distillation, Lightweight
BibRef
Huang, D.[Detian],
Lin, M.X.[Ming-Xin],
Liu, H.[Hang],
Zeng, H.Q.[Huan-Qiang],
CMASR: Lightweight image super-resolution with cluster and match
attention,
IVC(155), 2025, pp. 105457.
Elsevier DOI
2503
Image super-resolution, Transformer, Token clustering, Axial self-attention
BibRef
Wu, C.[Chen],
Wang, L.[Ling],
Su, X.[Xin],
Zheng, Z.R.[Zhuo-Ran],
Adaptive Feature Selection Modulation Network for Efficient Image
Super-Resolution,
SPLetters(32), 2025, pp. 1231-1235.
IEEE DOI
2503
Modulation, Computational efficiency, Superresolution,
Feature extraction, Image reconstruction, Convolution,
light weight network
BibRef
Wang, Y.[Yan],
Li, Y.[Yusen],
Wang, G.[Gang],
Liu, X.G.[Xiao-Guang],
Plainusr: Chasing Faster Convnet for Efficient Super-resolution,
ACCV24(IV: 246-264).
Springer DOI
2412
BibRef
Wan, C.[Cheng],
Yu, H.Y.[Hong-Yuan],
Li, Z.Q.[Zhi-Qi],
Chen, Y.H.[Yi-Hang],
Zou, Y.J.[Ya-Jun],
Liu, Y.Q.[Yu-Qing],
Yin, X.W.[Xuan-Wu],
Zuo, K.L.[Kun-Long],
Swift Parameter-free Attention Network for Efficient Super-Resolution,
NTIRE24(6246-6256)
IEEE DOI Code:
WWW Link.
2410
Image quality, Performance evaluation, Attention mechanisms,
Runtime, Computational modeling, Superresolution, Activation functions
BibRef
Choi, H.[Haram],
Na, C.[Cheolwoong],
Oh, J.[Jihyeon],
Lee, S.[Seungjae],
Kim, J.[Jinseop],
Choe, S.[Subeen],
Lee, J.[Jeongmin],
Kim, T.[Taehoon],
Yang, J.[Jihoon],
Reciprocal Attention Mixing Transformer for Lightweight Image
Restoration,
NTIRE24(5992-6002)
IEEE DOI Code:
WWW Link.
2410
Convolutional codes, Image color analysis, Noise reduction,
Superresolution, Semantics, Gray-scale, image restoration,
lightweight network
BibRef
Yang, Y.Q.[Yu-Qiang],
Zhang, Z.M.[Zhi-Ming],
Du, Y.[Yao],
Yang, J.J.[Jing-Jing],
Bao, L.[Long],
Sun, H.[Heng],
Hybrid Cross-View Attention Network for Lightweight Stereo Image
Super-Resolution,
NTIRE24(6055-6064)
IEEE DOI Code:
WWW Link.
2410
Training, Measurement, Image quality, Visualization, Aggregates,
Superresolution, Transformers
BibRef
Li, Y.X.[Yun-Xiang],
Zou, W.B.[Wen-Bin],
Wei, Q.[Qiaomu],
Huang, F.[Feng],
Wu, J.[Jing],
Multi-Level Feature Fusion Network for Lightweight Stereo Image
Super-Resolution,
NTIRE24(6489-6498)
IEEE DOI Code:
WWW Link.
2410
Source coding, Computational modeling, Superresolution, Redundancy,
Information sharing
BibRef
Jeevan, P.[Pranav],
Srinidhi, A.[Akella],
Prathiba, P.[Pasunuri],
Sethi, A.[Amit],
WaveMixSR:
Resource-efficient Neural Network for Image Super-resolution,
WACV24(5872-5880)
IEEE DOI
2404
Wavelet transforms, Computational modeling, Superresolution,
Neural networks, Training data, Transformers, Data models, Social good
BibRef
Conde, M.V.[Marcos V.],
Vasluianu, F.[Florin],
Timofte, R.[Radu],
BSRAW: Improving Blind RAW Image Super-Resolution,
WACV24(8485-8495)
IEEE DOI
2404
Degradation, Training, Superresolution, Pipelines, Transforms, Cameras,
Optics, Applications, Smartphones / end user devices,
Applications, Embedded sensing / real-time techniques
BibRef
Zheng, M.J.[Ming-Jun],
Sun, L.[Long],
Dong, J.X.[Jiang-Xin],
Pan, J.S.[Jin-Shan],
Smfanet: A Lightweight Self-modulation Feature Aggregation Network for
Efficient Image Super-resolution,
ECCV24(L: 359-375).
Springer DOI
2412
BibRef
Sun, L.[Long],
Dong, J.X.[Jiang-Xin],
Tang, J.H.[Jin-Hui],
Pan, J.S.[Jin-Shan],
Spatially-Adaptive Feature Modulation for Efficient Image
Super-Resolution,
ICCV23(13144-13153)
IEEE DOI Code:
WWW Link.
2401
BibRef
Li, X.[Xiang],
Dong, J.X.[Jiang-Xin],
Tang, J.H.[Jin-Hui],
Pan, J.S.[Jin-Shan],
DLGSANet: Lightweight Dynamic Local and Global Self-Attention Network
for Image Super-Resolution,
ICCV23(12746-12755)
IEEE DOI Code:
WWW Link.
2401
BibRef
Zhang, A.P.[Ai-Ping],
Ren, W.Q.[Wen-Qi],
Liu, Y.[Yi],
Cao, X.C.[Xiao-Chun],
Lightweight Image Super-Resolution with Superpixel Token Interaction,
ICCV23(12682-12691)
IEEE DOI Code:
WWW Link.
2401
BibRef
Liu, G.[Guandu],
Ding, Y.[Yukang],
Li, M.[Mading],
Sun, M.[Ming],
Wen, X.[Xing],
Wang, B.[Bin],
Reconstructed Convolution Module Based Look-Up Tables for Efficient
Image Super-Resolution,
ICCV23(12183-12192)
IEEE DOI Code:
WWW Link.
2401
BibRef
Wang, W.[Wei],
Lei, X.J.[Xue-Jing],
Chen, Y.[Yueru],
Lee, M.S.[Ming-Sui],
Kuo, C.C.J.[C.C. Jay],
LSR: A Light-Weight Super-Resolution Method,
ICIP23(1955-1959)
IEEE DOI
2312
BibRef
Yu, L.[Lei],
Li, X.P.[Xin-Peng],
Li, Y.[Youwei],
Jiang, T.[Ting],
Wu, Q.[Qi],
Fan, H.Q.[Hao-Qiang],
Liu, S.C.[Shuai-Cheng],
DIPNet: Efficiency Distillation and Iterative Pruning for Image
Super-Resolution,
NTIRE23(1692-1701)
IEEE DOI
2309
BibRef
Lin, J.[Jin],
Luo, X.T.[Xiao-Tong],
Hong, M.[Ming],
Qu, Y.[Yanyun],
Xie, Y.[Yuan],
Wu, Z.Z.[Zong-Ze],
Memory-Friendly Scalable Super-Resolution via Rewinding Lottery
Ticket Hypothesis,
CVPR23(14398-14407)
IEEE DOI
2309
BibRef
Li, G.[Gen],
Ji, J.[Jie],
Qin, M.[Minghai],
Niu, W.[Wei],
Ren, B.[Bin],
Afghah, F.[Fatemeh],
Guo, L.[Linke],
Ma, X.L.[Xiao-Long],
Towards High-Quality and Efficient Video Super-Resolution via
Spatial-Temporal Data Overfitting,
CVPR23(10259-10269)
IEEE DOI
2309
BibRef
Mao, Y.[Yanyu],
Zhang, N.H.[Ni-Hao],
Wang, Q.[Qian],
Bai, B.[Bendu],
Bai, W.Y.[Wan-Ying],
Fang, H.N.[Hao-Nan],
Liu, P.[Peng],
Li, M.Y.[Ming-Yue],
Yan, S.[Shengbo],
Multi-level Dispersion Residual Network for Efficient Image
Super-Resolution,
NTIRE23(1660-1669)
IEEE DOI
2309
BibRef
Zamfir, E.[Eduard],
Conde, M.V.[Marcos V.],
Timofte, R.[Radu],
Towards Real-Time 4K Image Super-Resolution,
NTIRE23(1522-1532)
IEEE DOI
2309
BibRef
Guo, J.M.[Jia-Ming],
Zou, X.[Xueyi],
Chen, Y.[Yuyi],
Liu, Y.[Yi],
Hao, J.[Jia],
Liu, J.Z.[Jian-Zhuang],
Yan, Y.[Youliang],
AsConvSR: Fast and Lightweight Super-Resolution Network with
Assembled Convolutions,
NTIRE23(1582-1592)
IEEE DOI
2309
BibRef
Choi, H.[Haram],
Lee, J.[Jeongmin],
Yang, J.[Jihoon],
N-Gram in Swin Transformers for Efficient Lightweight Image
Super-Resolution,
CVPR23(2071-2081)
IEEE DOI
2309
BibRef
Guo, W.J.[Wen-Jin],
Xie, W.Y.[Wei-Ying],
Jiang, K.[Kai],
Li, Y.S.[Yun-Song],
Lei, J.[Jie],
Fang, L.Y.[Le-Yuan],
Toward Stable, Interpretable, and Lightweight Hyperspectral
Super-Resolution,
CVPR23(22272-22281)
IEEE DOI
2309
BibRef
Wang, X.H.[Xiao-Hang],
Chen, X.H.[Xuan-Hong],
Ni, B.B.[Bing-Bing],
Wang, H.[Hang],
Tong, Z.Y.[Zheng-Yan],
Liu, Y.T.[Yu-Tian],
Deep Arbitrary-Scale Image Super-Resolution via Scale-Equivariance
Pursuit,
CVPR23(1786-1795)
IEEE DOI
2309
BibRef
Cao, J.Z.[Jie-Zhang],
Wang, Q.[Qin],
Xian, Y.Q.[Yong-Qin],
Li, Y.W.[Ya-Wei],
Ni, B.B.[Bing-Bing],
Pi, Z.M.[Zhi-Ming],
Zhang, K.[Kai],
Zhang, Y.[Yulun],
Timofte, R.[Radu],
Van Gool, L.J.[Luc J.],
CiaoSR: Continuous Implicit Attention-in-Attention Network for
Arbitrary-Scale Image Super-Resolution,
CVPR23(1796-1807)
IEEE DOI
2309
BibRef
Wang, H.[Hang],
Chen, X.H.[Xuan-Hong],
Ni, B.B.[Bing-Bing],
Liu, Y.T.[Yu-Tian],
Liu, J.F.[Jin-Fan],
Omni Aggregation Networks for Lightweight Image Super-Resolution,
CVPR23(22378-22387)
IEEE DOI
2309
BibRef
Deng, W.J.[Wei-Jian],
Yuan, H.J.[Hong-Jie],
Deng, L.[Lunhui],
Lu, Z.[Zengtong],
Reparameterized Residual Feature Network For Lightweight Image
Super-Resolution,
NTIRE23(1712-1721)
IEEE DOI
2309
BibRef
Yoon, K.[Kihwan],
Gankhuyag, G.[Ganzorig],
Park, J.M.[Jin-Man],
Son, H.[Haengseon],
Min, K.[Kyoungwon],
CASR: Efficient Cascade Network Structure with Channel Aligned method
for 4K Real-Time Single Image Super-Resolution,
AIS24(7911-7920)
IEEE DOI Code:
WWW Link.
2410
Performance evaluation, Headphones, TV, Image coding,
Superresolution, Transforms, Real-time systems,
Reparameterization
BibRef
Gankhuyag, G.[Ganzorig],
Yoon, K.[Kihwan],
Park, J.M.[Jin-Man],
Son, H.S.[Haeng Seon],
Min, K.[Kyoungwon],
Lightweight Real-Time Image Super-Resolution Network for 4K Images,
NTIRE23(1746-1755)
IEEE DOI
2309
BibRef
Gendy, G.[Garas],
Sabor, N.[Nabil],
Hou, J.C.[Jing-Chao],
He, G.H.[Guang-Hui],
Mixer-based Local Residual Network for Lightweight Image
Super-resolution,
NTIRE23(1593-1602)
IEEE DOI
2309
BibRef
And:
A Simple Transformer-style Network for Lightweight Image
Super-resolution,
NTIRE23(1484-1494)
IEEE DOI
2309
BibRef
Dong, T.X.T.[Ting-Xing Tim],
Yan, H.[Hao],
Parasar, M.[Mayank],
Krisch, R.[Raun],
RenderSR: A Lightweight Super-Resolution Model for Mobile Gaming
Upscaling,
MobileAI22(3086-3094)
IEEE DOI
2210
Image quality, Interpolation, Visualization, Image color analysis,
Superresolution, Buildings, Graphics processing units
BibRef
Fang, J.S.[Jin-Sheng],
Lin, H.J.[Han-Jiang],
Chen, X.Y.[Xin-Yu],
Zeng, K.[Kun],
A Hybrid Network of CNN and Transformer for Lightweight Image
Super-Resolution,
NTIRE22(1102-1111)
IEEE DOI
2210
Codes, Superresolution, Memory management, Transformers, Feature extraction
BibRef
Zong, Z.K.[Zhi-Kai],
Zha, L.[Lin],
Jiang, J.[Jiande],
Liu, X.X.[Xiao-Xiao],
Asymmetric Information Distillation Network for Lightweight Super
Resolution,
NTIRE22(1248-1257)
IEEE DOI
2210
Multiplexing, Measurement, Image resolution,
Computational modeling, Feature extraction
BibRef
Li, W.[Wen],
Li, S.M.[Su-Mei],
Liu, A.Q.[An-Qi],
Lightweight Image Super-Resolution Reconstruction With Hierarchical
Feature-Driven Network,
ICIP20(573-577)
IEEE DOI
2011
Europe, Indexes,
Machine vision, Surface treatment, Super resolution,
attention
BibRef
Park, J.Y.,
Choi, D.Y.,
Song, B.C.,
Slice-Based Super-Resolution Using Light-Weight Network With Relation
Loss,
ICIP20(503-507)
IEEE DOI
2011
Convolution, Image resolution, Visualization, Radio frequency,
Degradation, Training, Light-weight,
relation loss
BibRef
Shi, Y.L.[Yong-Lian],
Li, S.M.[Su-Mei],
Li, W.[Wen],
Liu, A.Q.[An-Qi],
Fast and Lightweight Image Super-Resolution Based on Dense Residuals
Two-Channel Network,
ICIP19(2826-2830)
IEEE DOI
1910
Super-resolution reconstruction, grouped convolution,
lightweight construction, residual
BibRef
Ahn, N.[Namhyuk],
Kang, B.[Byungkon],
Sohn, K.A.[Kyung-Ah],
Fast, Accurate, and Lightweight Super-Resolution with Cascading
Residual Network,
ECCV18(X: 256-272).
Springer DOI
1810
BibRef
And:
Image Super-Resolution via Progressive Cascading Residual Network,
Restoration18(904-9048)
IEEE DOI
1812
Training, Image resolution, Task analysis, Convolution,
Image reconstruction, Automobiles
BibRef
Chang, C.Y.[Chia-Yang],
Chien, S.Y.[Shao-Yi],
Back-Projection Lightweight Network for Accurate Image Super Resolution,
ACCV18(V:135-151).
Springer DOI
1906
BibRef
Chapter on Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion continues in
Challenges for Mosaic Generation, Super Resolution and Stabilization .