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Transformer-based models have revolutionized the field of image super-resolution (SR) by harnessing their inherent ability to capture complex contextual features.
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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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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Learning a deep convolutional network for image super-resolution
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2014
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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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Accurate image super-resolution using very deep convolutional networks
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee · 2016
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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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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Fast and accurate single image super-resolution via information distillation network
Zheng Hui, Xiumei Wang, and Xinbo Gao · 2018
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challenge on single image super-resolution: Methods and results
R Timofte, S Gu, J Wu, and L NTIRE Van Gool · 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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Residual dense network for image super-resolution
Yulun Zhang, Yapeng Tian, Yu Kong, 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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End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Closed-loop matters: Dual regression networks for single image super-resolution
Yong Guo, Jian Chen, Jingdong Wang, Qi Chen, Jiezhang Cao, Zeshuai Deng, Yanwu Xu, and Mingkui Tan · 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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Swin-unet: Unet-like pure transformer for medical image segmentation
Hu Cao, Yueyue Wang, Joy Chen, Dongsheng Jiang, Xiaopeng Zhang, Qi Tian, and Manning Wang · 2022
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Activating more pixels in image super-resolution transformer. arxiv 2022
Xiangyu Chen, Xintao Wang, Jiantao Zhou, and Chao Dong · 2022
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Swin2sr: Swinv2 transformer for compressed image super-resolution and restoration
Marcos V Conde, Ui-Jin Choi, Maxime Burchi, and Radu Timofte · 2022
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Glance and focus networks for dynamic visual recognition
Gao Huang, Yulin Wang, Kangchen Lv, Haojun Jiang, Wenhui Huang, Pengfei Qi, and Shiji Song · 2022
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Hst: Hierarchical swin transformer for compressed image super-resolution
Bingchen Li, Xin Li, Yiting Lu, Sen Liu, Ruoyu Feng, and Zhibo Chen · 2022
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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.
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.
Twins: Revisiting the design of spatial attention in vision transformers
Xiangxiang Chu, Zhi Tian, Yuqing Wang, Bo Zhang, Haibing Ren, Xiaolin Wei, Huaxia Xia, and Chunhua Shen · 2021
Cited alongside, same era.
Interpreting super-resolution networks with local attribution maps
Jinjin Gu and Chao Dong · 2021
Cited alongside, same era.
Classsr: A general framework to accelerate super-resolution networks by data characteristic
Xiangtao Kong, Hengyuan Zhao, Yu Qiao, and Chao Dong · 2021
Cited alongside, same era.
On efficient transformer and image pre-training for low-level vision
Wenbo Li, Xin Lu, Jiangbo Lu, Xiangyu Zhang, and Jiaya Jia · 2021
Cited alongside, same era.
Bringing locality to vision transformers
Y Li, K Zhang, J Cao, R Timofte, and L LocalViT Van Gool · 2021
Cited alongside, same era.
Transformer for single image super-resolution
Zhisheng Lu, Juncheng Li, Hong Liu, Chaoyan Huang, Linlin Zhang, and Tieyong Zeng · 2022
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Deep constrained least squares for blind image super-resolution
Ziwei Luo, Haibin Huang, Lei Yu, Youwei Li, Haoqiang Fan, and Shuaicheng Liu · 2022
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Adavit: Adaptive vision transformers for efficient image recognition
Lingchen Meng, Hengduo Li, Bor-Chun Chen, Shiyi Lan, Zuxuan Wu, Yu-Gang Jiang, and Ser-Nam Lim · 2022
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Accurate image restoration with attention retractable transformer
Jiale Zhang, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, and Xin Yuan · 2022
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Activating more pixels in image super-resolution transformer
Xiangyu Chen, Xintao Wang, Jiantao Zhou, Yu Qiao, and Chao Dong · 2023
Later among the works it cites.
Uniformer: Unifying convolution and self-attention for visual recognition
Kunchang Li, Yali Wang, Junhao Zhang, Peng Gao, Guanglu Song, Yu Liu, Hongsheng Li, and Yu Qiao · 2023
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Dual circle contrastive learning-based blind image super-resolution
Yajun Qiu, Qiang Zhu, Shuyuan Zhu, and Bing Zeng · 2023
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Enriched cnn-transformer feature aggregation networks for super-resolution
Jinsu Yoo, Taehoon Kim, Sihaeng Lee, Seung Hwan Kim, Honglak Lee, and Tae Hyun Kim · 2023
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Dipnet: Efficiency distillation and iterative pruning for image super-resolution
Lei Yu, Xinpeng Li, Youwei Li, Ting Jiang, Qi Wu, Haoqiang Fan, and Shuaicheng Liu · 2023
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Attention retractable frequency fusion transformer for image super resolution
Qiang Zhu, Pengfei Li, and Qianhui Li · 2023
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