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State Space Models (SSM), such as Mamba, have shown strong representation ability in modeling long-range dependency with linear complexity, achieving successful applications from high-level to low-level vision tasks.
A new approach to linear filtering and prediction problems
Rudolph Emil Kalman · 1960
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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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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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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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On single image scale-up using sparse-representations
Roman Zeyde, Michael Elad, and Matan Protter · 2012
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Image super-resolution using deep convolutional networks
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2015
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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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Ntire 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 2017
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Photo-realistic single image super-resolution using a generative adversarial network
Christian Ledig, Lucas Theis, Ferenc Huszár, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, et al · 2017
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Enhanced deep residual networks for single image super-resolution
Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 2017
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Sketch-based manga retrieval using manga109 dataset
Yusuke Matsui, Kota Ito, Yuji Aramaki, Azuma Fujimoto, Toru Ogawa, Toshihiko Yamasaki, and Kiyoharu Aizawa · 2017
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Fast, accurate, and lightweight super-resolution with cascading residual network
Namhyuk Ahn, Byungkon Kang, and Kyung-Ah Sohn · 2018
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Image super-resolution using very deep residual channel attention networks
Yulun Zhang, Kunpeng Li, Kai Li, Lichen Wang, Bineng Zhong, and Yun Fu · 2018
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Second-order attention network for single image super-resolution
Tao Dai, Jianrui Cai, Yongbing Zhang, Shu-Tao Xia, and Lei Zhang · 2019
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Ode-inspired network design for single image super-resolution
Xiangyu He, Zitao Mo, Peisong Wang, Yang Liu, Mingyuan Yang, and Jian Cheng · 2019
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Lightweight image super-resolution with information multi-distillation network
Zheng Hui, Xinbo Gao, Yunchu Yang, and Xiumei Wang · 2019
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Deep learning for single image super-resolution: A brief review
Wenming Yang, Xuechen Zhang, Yapeng Tian, Wei Wang, Jing-Hao Xue, and Qingmin Liao · 2019
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Residual non-local attention networks for image restoration
Yulun Zhang, Kunpeng Li, Kai Li, Bineng Zhong, and Yun Fu · 2019
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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
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Latticenet: Towards lightweight image super-resolution with lattice block
Xiaotong Luo, Yuan Xie, Yulun Zhang, Yanyun Qu, Cuihua Li, and Yun Fu · 2020
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Image super-resolution with cross-scale non-local attention and exhaustive self-exemplars mining
Yiqun Mei, Yuchen Fan, Yuqian Zhou, Lichao Huang, Thomas S Huang, and Honghui Shi · 2020
Cited alongside, same era.
Restormer: Efficient transformer for high-resolution image restoration
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Ming-Hsuan Yang · 2022
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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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Spatially-adaptive feature modulation for efficient image super-resolution
Long Sun, Jiangxin Dong, Jinhui Tang, and Jinshan Pan · 2023
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Srformer: Permuted self-attention for single image super-resolution
Yupeng Zhou, Zhen Li, Chun-Le Guo, Song Bai, Ming-Ming Cheng, and Qibin Hou · 2023
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Activating wider areas in image super-resolution
Cheng Cheng, Hang Wang, and Hongbin Sun · 2024
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Single image super-resolution via a holistic attention network
Ben Niu, Weilei Wen, Wenqi Ren, Xiangde Zhang, Lianping Yang, Shuzhen Wang, Kaihao Zhang, Xiaochun Cao, and Haifeng Shen · 2020
Cited alongside, same era.
Glu variants improve transformer
Noam Shazeer · 2020
Cited alongside, same era.
Cross-scale internal graph neural network for image super-resolution
Shangchen Zhou, Jiawei Zhang, Wangmeng Zuo, and Chen Change Loy · 2020
Cited alongside, same era.
Pre-trained image processing transformer
Hanting Chen, Yunhe Wang, Tianyu Guo, Chang Xu, Yiping Deng, Zhenhua Liu, Siwei Ma, Chunjing Xu, Chao Xu, and Wen Gao · 2021
Cited alongside, same era.
Interpreting super-resolution networks with local attribution maps
Jinjin Gu and Chao Dong · 2021
Cited alongside, same era.
Swinir: Image restoration using swin transformer
Jingyun Liang, Jiezhang Cao, Guolei Sun, Kai Zhang, Luc Van Gool, and Radu Timofte · 2021
Cited alongside, same era.
Image super-resolution with non-local sparse attention
Yiqun Mei, Yuchen Fan, and Yuqian Zhou · 2021
Cited alongside, same era.
Rui Deng and Tianpei Gu · 2024
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Mamba: Linear-time sequence modeling with selective state spaces
Albert Gu and Tri Dao · 2024
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Mambair: A simple baseline for image restoration with state-space model
Hang Guo, Jinmin Li, Tao Dai, Zhihao Ouyang, Xudong Ren, and Shu-Tao Xia · 2024
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Dvmsr: Distillated vision mamba for efficient super-resolution
Xiaoyan Lei, Wenlong ZHang, and Weifeng Cao · 2024
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Pointmamba: A simple state space model for point cloud analysis
Dingkang Liang, Xin Zhou, Xinyu Wang, Xingkui Zhu, Wei Xu, Zhikang Zou, Xiaoqing Ye, and Xiang Bai · 2024
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Vmamba: Visual state space model
Yue Liu, Yunjie Tian, Yuzhong Zhao, Hongtian Yu, Lingxi Xie, Yaowei Wang, Qixiang Ye, and Yunfan Liu · 2024
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Cfat: Unleashing triangularwindows for image super-resolution
Abhisek Ray, Gaurav Kumar, and Maheshkumar H Kolekar · 2024
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Vmambair: Visual state space model for image restoration
Yuan Shi, Bin Xia, Xiaoyu Jin, Xing Wang, Tianyu Zhao, Xin Xia, Xuefeng Xiao, and Wenming Yang · 2024
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Frequency-assisted mamba for remote sensing image super-resolution
Yi Xiao, Qiangqiang Yuan, Kui Jiang, Yuzeng Chen, Qiang Zhang, and Chia-Wen Lin · 2024
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Leheng Zhang, Yawei Li, Xingyu Zhou, Xiaorui Zhao, and Shuhang Gu · 2024
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Vision mamba: Efficient visual representation learning with bidirectional state space model
Lianghui Zhu, Bencheng Liao, Qian Zhang, Xinlong Wang, Wenyu Liu, and Xinggang Wang · 2024
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