Fetching the paper…
Reading the bibliography…
Arbitrary scale super-resolution (ASSR) aims to super-resolve low-resolution images to high-resolution images at any scale using a single model, addressing the limitations of traditional super-resolution methods that are restricted to fixed-scale factors (e.g., $\times2$, $\times4$).
Local texture estimator for implicit representation function
Jaewon Lee and Kyong Hwan Jin · 1938
Earlier work this paper cites.
Local texture estimator for implicit representation function
Jaewon Lee and Kyong Hwan Jin · 1938
Earlier work this paper cites.
A new approach to linear filtering and prediction problems
Rudolph Emil Kalman · 1960
Earlier work this paper cites.
Super-resolution reconstruction of compressed video using transform-domain statistics
Bahadir K Gunturk, Yucel Altunbasak, and Russell M Mersereau · 2004
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
Earlier work this paper cites.
Very low resolution face recognition problem
Wilman WW Zou and Pong C Yuen · 2011
Earlier work this paper cites.
Three-dimensional imaging for creating real-world-like environments
Jung-Young Son, Wook-Ho Son, Sung-Kyu Kim, Kwang-Hoon Lee, and Bahram Javidi · 2012
Earlier work this paper cites.
Cardiac image super-resolution with global correspondence using multi-atlas patchmatch
Wenzhe Shi, Jose Caballero, Christian Ledig, Xiahai Zhuang, Wenjia Bai, Kanwal Bhatia, Antonio M Marvao, Tim Dawes, Declan O’Regan, and Daniel Rueckert · 2013
Earlier work this paper cites.
Learning a deep convolutional network for image super-resolution
Chao Dong, Chen Change Loy, Kaiming He, and Xiaoou Tang · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma · 2014
Earlier work this paper cites.
Accurate image super-resolution using very deep convolutional networks
Jiwon Kim, Jung Kwon Lee, and Kyoung Mu Lee · 2016
Earlier work this paper cites.
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
Earlier work this paper cites.
Ntire 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 2017
Earlier work this paper cites.
Cas-cnn: A deep convolutional neural network for image compression artifact suppression
Lukas Cavigelli, Pascal Hager, and Luca Benini · 2017
Earlier work this paper cites.
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
Earlier work this paper cites.
Enhanced deep residual networks for single image super-resolution
Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 2017
Earlier work this paper cites.
Non-local recurrent network for image restoration
Ding Liu, Bihan Wen, Yuchen Fan, Chen Change Loy, and Thomas S Huang · 2018
Earlier work this paper cites.
Esrgan: Enhanced super-resolution generative adversarial networks
Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy · 2018
Earlier work this paper cites.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
Earlier work this paper cites.
Second-order attention network for single image super-resolution
Tao Dai, Jianrui Cai, Yongbing Zhang, Shu-Tao Xia, and Lei Zhang · 2019
Cited alongside, same era.
Implicit surface representations as layers in neural networks
Mateusz Michalkiewicz, Jhony K Pontes, Dominic Jack, Mahsa Baktashmotlagh, and Anders Eriksson · 2019
Cited alongside, same era.
Scene representation networks: Continuous 3d-structure-aware neural scene representations
Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein · 2019
Cited alongside, same era.
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
Cited alongside, same era.
Implicit geometric regularization for learning shapes
Amos Gropp, Lior Yariv, Niv Haim, Matan Atzmon, and Yaron Lipman · 2020
Ntire 2023 challenge on efficient super-resolution: Methods and results
Yawei Li, Yulun Zhang, Radu Timofte, Luc Van Gool, Lei Yu, Youwei Li, Xinpeng Li, Ting Jiang, Qi Wu, Mingyan Han, et al · 2023
Later among the works it cites.
Super-resolution neural operator
Min Wei and Xuesong Zhang · 2023
Later among the works it cites.
Local implicit normalizing flow for arbitrary-scale image super-resolution
Jie-En Yao, Li-Yuan Tsao, Yi-Chen Lo, Roy Tseng, Chia-Che Chang, and Chun-Yi Lee · 2023
Later among the works it cites.
Real-time 4k super-resolution of compressed avif images. ais 2024 challenge survey
Marcos V Conde, Zhijun Lei, Wen Li, Ioannis Katsavounidis, Radu Timofte, Min Yan, Xin Liu, Qian Wang, Xiaoqian Ye, Zhan Du, et al · 2024
Closest in time.
Qmambabsr: Burst image super-resolution with query state space model
Xin Di, Long Peng, Peizhe Xia, Wenbo Li, Renjing Pei, Yang Cao, Yang Wang, and Zheng-Jun Zha · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
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.
Cumulative rain density sensing network for single image derain
Long Peng, Aiwen Jiang, Qiaosi Yi, and Mingwen Wang · 2020
Cited alongside, same era.
Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien Martel, Alexander Bergman, David Lindell, and Gordon Wetzstein · 2020
Cited alongside, same era.
Deep learning for image super-resolution: A survey
Zhihao Wang, Jian Chen, and Steven CH Hoi · 2020
Cited alongside, same era.
Residual dense network for image restoration
Yulun Zhang, Yapeng Tian, Yu Kong, Bineng Zhong, and Yun Fu · 2020
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.
Hang Guo, Jinmin Li, Tao Dai, Zhihao Ouyang, Xudong Ren, and Shu-Tao Xia · 2024
Closest in time.
Latent modulated function for computational optimal continuous image representation
Zongyao He and Zhi Jin · 2024
Closest in time.
Fouriermamba: Fourier learning integration with state space models for image deraining
Dong Li, Yidi Liu, Xueyang Fu, Senyan Xu, and Zheng-Jun Zha · 2024
Closest in time.
Arbitrary-scale super-resolution via deep learning: A comprehensive survey
Hongying Liu, Zekun Li, Fanhua Shang, Yuanyuan Liu, Liang Wan, Wei Feng, and Radu Timofte · 2024
Closest in time.
Simba: Simplified mamba-based architecture for vision and multivariate time series
Badri N Patro and Vijay S Agneeswaran · 2024
Closest in time.
Vl-mamba: Exploring state space models for multimodal learning
Yanyuan Qiao, Zheng Yu, Longteng Guo, Sihan Chen, Zijia Zhao, Mingzhen Sun, Qi Wu, and Jing Liu · 2024
Closest in time.
The ninth ntire 2024 efficient super-resolution challenge report
Bin Ren, Yawei Li, Nancy Mehta, Radu Timofte, Hongyuan Yu, Cheng Wan, Yuxin Hong, Bingnan Han, Zhuoyuan Wu, Yajun Zou, et al · 2024
Closest in time.
Vmrnn: Integrating vision mamba and lstm for efficient and accurate spatiotemporal forecasting
Yujin Tang, Peijie Dong, Zhenheng Tang, Xiaowen Chu, and Junwei Liang · 2024
Closest in time.
Mamba-unet: Unet-like pure visual mamba for medical image segmentation
Ziyang Wang, Jian-Qing Zheng, Yichi Zhang, Ge Cui, and Lei Li · 2024
Closest in time.
Rethinking image deraining via text-guided detail reconstruction
Chen Wu, Zhuoran Zheng, Pengwen Dai, Chenggang Shan, and Xiuyi Jia · 2024
Closest in time.
Frequency-assisted mamba for remote sensing image super-resolution
Yi Xiao, Qiangqiang Yuan, Kui Jiang, Yuzeng Chen, Qiang Zhang, and Chia-Wen Lin · 2024
Closest in time.
Mambasr: Arbitrary-scale super-resolution integrating mamba with fast fourier convolution blocks
Jin Yan, Zongren Chen, Zhiyuan Pei, Xiaoping Lu, and Hua Zheng · 2024
Closest in time.
Freqmamba: Viewing mamba from a frequency perspective for image deraining
Zou Zhen, Yu Hu, and Zhao Feng · 2024
Closest in time.
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
Closest in time.