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Burst super-resolution aims to reconstruct high-resolution images with higher quality and richer details by fusing the sub-pixel information from multiple burst low-resolution frames.
A new approach to linear filtering and prediction problems
Rudolph Emil Kalman · 1960
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Monotone piecewise bicubic interpolation
Ralph E Carlson and Frederick N Fritsch · 1985
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Image deformation using moving least squares
Scott Schaefer, Travis McPhail, and Joe Warren · 2006
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Image super-resolution via sparse representation
Jianchao Yang, John Wright, Thomas S Huang, and Yi Ma · 2010
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Very deep convolutional networks for large-scale image recognition
Karen Simonyan and Andrew Zisserman · 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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Recurrent convolutional neural network for object recognition
Ming Liang and Xiaolin Hu · 2015
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 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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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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Multi-scale residual network for image super-resolution
Juncheng Li, Faming Fang, Kangfu Mei, and Guixu Zhang · 2018
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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
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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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Pixel transposed convolutional networks
Hongyang Gao, Hao Yuan, Zhengyang Wang, and Shuiwang Ji · 2019
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Highres-net: Recursive fusion for multi-frame super-resolution of satellite imagery
Michel Deudon, Alfredo Kalaitzis, Israel Goytom, Md Rifat Arefin, Zhichao Lin, Kris Sankaran, Vincent Michalski, Samira E Kahou, Julien Cornebise, and Yoshua Bengio · 2020
Earlier work this paper cites.
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
Earlier work this paper cites.
Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
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Learning texture transformer network for image super-resolution
Fuzhi Yang, Huan Yang, Jianlong Fu, Hongtao Lu, and Baining Guo · 2020
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Deep unfolding network for image super-resolution
Kai Zhang, Luc Van Gool, and Radu Timofte · 2020
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Lucas-kanade reloaded: End-to-end super-resolution from raw image bursts
Bruno Lecouat, Jean Ponce, and Julien Mairal · 2021
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Swinir: Image restoration using swin transformer
Jingyun Liang, Jiezhang Cao, Guolei Sun, Kai Zhang, Luc Van Gool, and Radu Timofte · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
Gated multi-resolution transfer network for burst restoration and enhancement
Nancy Mehta, Akshay Dudhane, Subrahmanyam Murala, Syed Waqas Zamir, Salman Khan, and Fahad Shahbaz Khan · 2023
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Towards real-world burst image super-resolution: Benchmark and method
Pengxu Wei, Yujing Sun, Xingbei Guo, Chang Liu, Guanbin Li, Jie Chen, Xiangyang Ji, and Liang Lin · 2023
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Rbsr: Efficient and flexible recurrent network for burst super-resolution
Renlong Wu, Zhilu Zhang, Shuohao Zhang, Hongzhi Zhang, and Wangmeng Zuo · 2023
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Ssumamba: Spatial-spectral selective state space model for hyperspectral image denoising
Guanyiman Fu, Fengchao Xiong, Jianfeng Lu, Jun Zhou, and Yuntao Qian · 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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Cited alongside, same era.
Ebsr: Feature enhanced burst super-resolution with deformable alignment
Ziwei Luo, Lei Yu, Xuan Mo, Youwei Li, Lanpeng Jia, Haoqiang Fan, Jian Sun, and Shuaicheng Liu · 2021
Cited alongside, same era.
Ntire 2022 burst super-resolution challenge
Goutam Bhat, Martin Danelljan, Radu Timofte, Yizhen Cao, Yuntian Cao, Meiya Chen, Xihao Chen, Shen Cheng, Akshay Dudhane, Haoqiang Fan, et al · 2022
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Burst image restoration and enhancement
Akshay Dudhane, Syed Waqas Zamir, Salman Khan, Fahad Shahbaz Khan, and Ming-Hsuan Yang · 2022
Cited alongside, same era.
Transformer for single image super-resolution
Zhisheng Lu, Juncheng Li, Hong Liu, Chaoyan Huang, Linlin Zhang, and Tieyong Zeng · 2022
Cited alongside, same era.
Bsrt: Improving burst super-resolution with swin transformer and flow-guided deformable alignment
Ziwei Luo, Youwei Li, Shen Cheng, Lei Yu, Qi Wu, Zhihong Wen, Haoqiang Fan, Jian Sun, and Shuaicheng Liu · 2022
Cited alongside, same era.
Adaptive feature consolidation network for burst super-resolution
Nancy Mehta, Akshay Dudhane, Subrahmanyam Murala, Syed Waqas Zamir, Salman Khan, and Fahad Shahbaz Khan · 2022
Cited alongside, same era.
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Demystify mamba in vision: A linear attention perspective
Dongchen Han, Ziyi Wang, Zhuofan Xia, Yizeng Han, Yifan Pu, Chunjiang Ge, Jun Song, Shiji Song, Bo Zheng, and Gao Huang · 2024
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Fouriermamba: Fourier learning integration with state space models for image deraining
Dong Li, Yidi Liu, Xueyang Fu, Senyan Xu, and Zheng-Jun Zha · 2024
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Simba: Simplified mamba-based architecture for vision and multivariate time series
Badri N Patro and Vijay S Agneeswaran · 2024
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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
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Vmrnn: Integrating vision mamba and lstm for efficient and accurate spatiotemporal forecasting
Yujin Tang, Peijie Dong, Zhenheng Tang, Xiaowen Chu, and Junwei Liang · 2024
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Seesr: Towards semantics-aware real-world image super-resolution
Rongyuan Wu, Tao Yang, Lingchen Sun, Zhengqiang Zhang, Shuai Li, and Lei Zhang · 2024
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A survey on vision mamba: Models, applications and challenges
Rui Xu, Shu Yang, Yihui Wang, Bo Du, and Hao Chen · 2024
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Resshift: Efficient diffusion model for image super-resolution by residual shifting
Zongsheng Yue, Jianyi Wang, and Chen Change Loy · 2024
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Freqmamba: Viewing mamba from a frequency perspective for image deraining
Zou Zhen, Yu Hu, and Zhao Feng · 2024
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Zeyun Zhong, Manuel Martin, Frederik Diederichs, and Juergen Beyerer · 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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