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Single Image Super-Resolution (SISR) is a crucial task in low-level computer vision, aiming to reconstruct high-resolution images from low-resolution counterparts.
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
David Martin, Charless Fowlkes, Doron Tal, and Jitendra Malik · 2001
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The use of super-resolution techniques to reduce slice thickness in functional mri
Ronald R Peeters, Pierre Kornprobst, Mila Nikolova, Stefan Sunaert, Thierry Vieville, Grégoire Malandain, Rachid Deriche, Olivier Faugeras, Michael Ng, and Paul Van Hecke · 2004
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Hallucinating faces: Tensorpatch super-resolution and coupled residue compensation
Wei Liu, Dahua Lin, and Xiaoou Tang · 2005
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Fingerprint image enhancement by super resolution with early stopping
Zhi Yuan, Jiong Wu, Sei-ichiro Kamata, Alireza Ahrary, and Peimin Yan · 2009
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Super resolution mapping of satellite images using hopfield neural networks
C Heltin Genitha and K Vani · 2010
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On single image scale-up using sparse-representations
Roman Zeyde, Michael Elad, and Matan Protter · 2010
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Processing of satellite image using digital image processing
B Sreenivas, B Narasimha Chary, and INDIA KARIMNAGAR · 2011
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Low-complexity single-image super-resolution based on nonnegative neighbor embedding
Marco Bevilacqua, Aline Roumy, Christine Guillemot, and Marie Line Alberi-Morel · 2012
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Super-resolution of hyperspectral images using compressive sensing based approach
Rakesh C Patel and MV Joshi · 2012
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Learning a deep convolutional network for image super-resolution
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2014
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Learning a deep convolutional network for image super-resolution
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Single image super-resolution from transformed self-exemplars
Jia-Bin Huang, Abhishek Singh, and Narendra Ahuja · 2015
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Accelerating the super-resolution convolutional neural network
Chao Dong, Chen Change Loy, and Xiaoou Tang · 2016
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Deeply-recursive convolutional network for image super-resolution
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee · 2016
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Accurate image super-resolution using very deep convolutional networks
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee · 2016
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Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network
Wenzhe Shi, Jose Caballero, Ferenc Huszár, Johannes Totz, Andrew P Aitken, Rob Bishop, Daniel Rueckert, and Zehan Wang · 2016
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Super resolution applications in modern digital image processing
Amanjot Singh and Jagroop Singh Sidhu · 2016
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Ntire 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 2017
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Deep laplacian pyramid networks for fast and accurate super-resolution
Wei-Sheng Lai, Jia-Bin Huang, Narendra Ahuja, and Ming-Hsuan Yang · 2017
Cited alongside, same era.
Enhanced deep residual networks for single image super-resolution
Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 2017
Cited alongside, same era.
Sketch-based manga retrieval using manga109 dataset
Yusuke Matsui, Kota Ito, Yuji Aramaki, Azuma Fujimoto, Toru Ogawa, Toshihiko Yamasaki, and Kiyoharu Aizawa · 2017
Cited alongside, same era.
Fast, accurate, and lightweight super-resolution with cascading residual network
Namhyuk Ahn, Byungkon Kang, and Kyung-Ah Sohn · 2018
Cited alongside, same era.
Image super-resolution using very deep residual channel attention networks
Yulun Zhang, Kunpeng Li, Kai Li, Lichen Wang, Bineng Zhong, and Yun Fu · 2018
Cited alongside, same era.
Attention-based dropout layer for weakly supervised object localization
Learning prior feature and attention enhanced image inpainting
Chenjie Cao, Qiaole Dong, and Yanwei Fu · 2022
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Parameter-free similarity-aware attention module for medical image classification and segmentation
Jie Du, Kai Guan, Yanhong Zhou, Yuanman Li, and Tianfu Wang · 2022
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Aiatrack: Attention in attention for transformer visual tracking
Shenyuan Gao, Chunluan Zhou, Chao Ma, Xinggang Wang, and Junsong Yuan · 2022
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Glamd: Global and local attention mask distillation for object detectors
Younho Jang, Wheemyung Shin, Jinbeom Kim, Simon Woo, and Sung-Ho Bae · 2022
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Residual local feature network for efficient super-resolution
Fangyuan Kong, Mingxi Li, Songwei Liu, Ding Liu, Jingwen He, Yang Bai, Fangmin Chen, and Lean Fu · 2022
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Knn local attention for image restoration
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Junsuk Choe and Hyunjung Shim · 2019
Cited alongside, same era.
Rethinking depthwise separable convolutions: How intra-kernel correlations lead to improved mobilenets
Daniel Haase and Manuel Amthor · 2020
Cited alongside, same era.
Learning on the edge: Investigating boundary filters in cnns
Carlo Innamorati, Tobias Ritschel, Tim Weyrich, and Niloy J Mitra · 2020
Cited alongside, same era.
Lapar: Linearly-assembled pixel-adaptive regression network for single image super-resolution and beyond
Wenbo Li, Kun Zhou, Lu Qi, Nianjuan Jiang, Jiangbo Lu, and Jiaya Jia · 2020
Cited alongside, same era.
Residual feature distillation network for lightweight image super-resolution
Jie Liu, Jie Tang, and Gangshan Wu · 2020
Cited alongside, same era.
Residual feature distillation network for lightweight image super-resolution
Jie Liu, Jie Tang, and Gangshan Wu · 2020
Cited alongside, same era.
Latticenet: Towards lightweight image super-resolution with lattice block
Xiaotong Luo, Yuan Xie, Yulun Zhang, Yanyun Qu, Cuihua Li, and Yun Fu · 2020
Cited alongside, same era.
Hunsang Lee, Hyesong Choi, Kwanghoon Sohn, and Dongbo Min · 2022
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Shufflemixer: An efficient convnet for image super-resolution
Long Sun, Jinshan Pan, and Jinhui Tang · 2022
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Direcformer: A directed attention in transformer approach to robust action recognition
Thanh-Dat Truong, Quoc-Huy Bui, Chi Nhan Duong, Han-Seok Seo, Son Lam Phung, Xin Li, and Khoa Luu · 2022
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Repsr: Training efficient vgg-style super-resolution networks with structural re-parameterization and batch normalization
Xintao Wang, Chao Dong, and Ying Shan · 2022
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Memory-augmented non-local attention for video super-resolution
Jiyang Yu, Jingen Liu, Liefeng Bo, and Tao Mei · 2022
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Ciaosr: Continuous implicit attention-in-attention network for arbitrary-scale image super-resolution
Jiezhang Cao, Qin Wang, Yongqin Xian, Yawei Li, Bingbing Ni, Zhiming Pi, Kai Zhang, Yulun Zhang, Radu Timofte, and Luc Van Gool · 2023
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N-gram in swin transformers for efficient lightweight image super-resolution
Haram Choi, Jeongmin Lee, and Jihoon Yang · 2023
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Lsdir: A large scale dataset for image restoration
Yawei Li, Kai Zhang, Jingyun Liang, Jiezhang Cao, Ce Liu, Rui Gong, Yulun Zhang, Hao Tang, Yun Liu, Denis Demandolx, Rakesh Ranjan, Radu Timofte, and Luc Van Gool · 2023
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Parameter-free channel attention for image classification and super-resolution
Yuxuan Shi, Lingxiao Yang, Wangpeng An, Xiantong Zhen, and Liuqing Wang · 2023
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Spatially-adaptive feature modulation for efficient image super-resolution
Long Sun, Jiangxin Dong, Jinhui Tang, and Jinshan Pan · 2023
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Omni aggregation networks for lightweight image super-resolution
Hang Wang, Xuanhong Chen, Bingbing Ni, Yutian Liu, and Jinfan Liu · 2023
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The ninth NTIRE 2024 efficient super-resolution challenge report
Bin Ren, Yawei Li, Nancy Mehta, Radu Timofte, et al · 2024
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Lightweight image super-resolution with information multi-distillation network
Zheng Hui, Xinbo Gao, Yunchu Yang, and Xiumei Wang · 2032
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Lightweight image super-resolution with information multi-distillation network
Zheng Hui, Xinbo Gao, Yunchu Yang, and Xiumei Wang · 2032
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