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Deep state-space models (SSMs), like recent Mamba architectures, are emerging as a promising alternative to CNN and Transformer networks.
Removing camera shake from a single photograph
Rob Fergus, Barun Singh, Aaron Hertzmann, Sam T Roweis, and William T Freeman · 2006
Earlier work this paper cites.
Image deblurring and denoising using color priors
Neel Joshi, C Lawrence Zitnick, Richard Szeliski, and David J Kriegman · 2009
Earlier work this paper cites.
Making a “completely blind” image quality analyzer
Anish Mittal, Rajiv Soundararajan, and Alan C Bovik · 2012
Earlier work this paper cites.
Multi-image blind deblurring using a coupled adaptive sparse prior
Haichao Zhang, David Wipf, and Yanning Zhang · 2013
Earlier work this paper cites.
Learning a convolutional neural network for non-uniform motion blur removal
Jian Sun, Wenfei Cao, Zongben Xu, and Jean Ponce · 2015
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Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
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Blind image deblurring using dark channel prior
Jinshan Pan, Deqing Sun, Hanspeter Pfister, and Ming-Hsuan Yang · 2016
Earlier work this paper cites.
Image deblurring via enhanced low-rank prior
Wenqi Ren, Xiaochun Cao, Jinshan Pan, Xiaojie Guo, Wangmeng Zuo, and Ming-Hsuan Yang · 2016
Earlier work this paper cites.
Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Deep multi-scale convolutional neural network for dynamic scene deblurring
Seungjun Nah, Tae Hyun Kim, and Kyoung Mu Lee · 2017
Earlier work this paper cites.
Swish: a self-gated activation function
Prajit Ramachandran, Barret Zoph, and Quoc V. Le · 2017
Earlier work this paper cites.
Image deblurring via extreme channels prior
Yanyang Yan, Wenqi Ren, Yuanfang Guo, Rui Wang, and Xiaochun Cao · 2017
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Mikołaj Bińkowski, Danica J Sutherland, Michael Arbel, and Arthur Gretton · 2018
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The perception-distortion tradeoff
Yochai Blau and Tomer Michaeli · 2018
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Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
Stefan Elfwing, Eiji Uchibe, and Kenji Doya · 2018
Earlier work this paper cites.
Deblurgan: Blind motion deblurring using conditional adversarial networks
Orest Kupyn, Volodymyr Budzan, Mykola Mykhailych, Dmytro Mishkin, and Jiří Matas · 2018
Earlier work this paper cites.
Scale-recurrent network for deep image deblurring
Xin Tao, Hongyun Gao, Xiaoyong Shen, Jue Wang, and Jiaya Jia · 2018
Earlier work this paper cites.
Rethinking lossy compression: The rate-distortion-perception tradeoff
Yochai Blau and Tomer Michaeli · 2019
Cited alongside, same era.
Blind image deblurring with local maximum gradient prior
Liang Chen, Faming Fang, Tingting Wang, and Guixu Zhang · 2019
Cited alongside, same era.
Deblurgan-v2: Deblurring (orders-of-magnitude) faster and better
Orest Kupyn, Tetiana Martyniuk, Junru Wu, and Zhangyang Wang · 2019
Cited alongside, same era.
Human-aware motion deblurring
Ziyi Shen, Wenguan Wang, Xiankai Lu, Jianbing Shen, Haibin Ling, Tingfa Xu, and Ling Shao · 2019
Cited alongside, same era.
Deep stacked hierarchical multi-patch network for image deblurring
Hongguang Zhang, Yuchao Dai, Hongdong Li, and Piotr Koniusz · 2019
Cited alongside, same era.
On aliased resizing and surprising subtleties in gan evaluation
Gaurav Parmar, Richard Zhang, and Jun-Yan Zhu · 2022
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Simplified state space layers for sequence modeling
Jimmy TH Smith, Andrew Warrington, and Scott W Linderman · 2022
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Stripformer: Strip transformer for fast image deblurring
Fu-Jen Tsai, Yan-Tsung Peng, Yen-Yu Lin, Chung-Chi Tsai, and Chia-Wen Lin · 2022
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Uformer: A general u-shaped transformer for image restoration
Zhendong Wang, Xiaodong Cun, Jianmin Bao, Wengang Zhou, Jianzhuang Liu, and Houqiang Li · 2022
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Deblurring via stochastic refinement
Jay Whang, Mauricio Delbracio, Hossein Talebi, Chitwan Saharia, Alexandros G Dimakis, and Peyman Milanfar · 2022
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Anastasia Zvezdakova, Dmitriy Kulikov, Denis Kondranin, and Dmitriy Vatolin · 2019
Cited alongside, same era.
Hippo: Recurrent memory with optimal polynomial projections
Albert Gu, Tri Dao, Stefano Ermon, Atri Rudra, and Christopher Ré · 2020
Cited alongside, same era.
Real-world blur dataset for learning and benchmarking deblurring algorithms
Jaesung Rim, Haeyun Lee, Jucheol Won, and Sunghyun Cho · 2020
Cited alongside, same era.
Spatially-attentive patch-hierarchical network for adaptive motion deblurring
Maitreya Suin, Kuldeep Purohit, and AN Rajagopalan · 2020
Cited alongside, same era.
Deblurring by realistic blurring
Kaihao Zhang, Wenhan Luo, Yiran Zhong, Lin Ma, Bjorn Stenger, Wei Liu, and Hongdong Li · 2020
Cited alongside, same era.
Rethinking coarse-to-fine approach in single image deblurring
Sung-Jin Cho, Seo-Won Ji, Jun-Pyo Hong, Seung-Won Jung, and Sung-Jea Ko · 2021
Cited alongside, same era.
Single-image deblurring with neural networks: A comparative survey
Jaihyun Koh, Jangho Lee, and Sungroh Yoon · 2021
Cited alongside, same era.
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Ming-Hsuan Yang · 2022
Later among the works it cites.
Self-supervised non-uniform kernel estimation with flow-based motion prior for blind image deblurring
Zhenxuan Fang, Fangfang Wu, Weisheng Dong, Xin Li, Jinjian Wu, and Guangming Shi · 2023
Later among the works it cites.
Mamba: Linear-time sequence modeling with selective state spaces
Albert Gu and Tri Dao · 2023
Later among the works it cites.
Efficient frequency domain-based transformers for high-quality image deblurring
Lingshun Kong, Jiangxin Dong, Jianjun Ge, Mingqiang Li, and Jinshan Pan · 2023
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Real-world image deblurring via unsupervised domain adaptation
Hanzhou Liu, Binghan Li, Mi Lu, and Yucheng Wu · 2023
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Intriguing findings of frequency selection for image deblurring
Xintian Mao, Yiming Liu, Fengze Liu, Qingli Li, Wei Shen, and Yan Wang · 2023
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Hyena hierarchy: Towards larger convolutional language models
Michael Poli, Stefano Massaroli, Eric Nguyen, Daniel Y Fu, Tri Dao, Stephen Baccus, Yoshua Bengio, Stefano Ermon, and Christopher Ré · 2023
Later among the works it cites.
Q-align: Teaching lmms for visual scoring via discrete text-defined levels
Haoning Wu, Zicheng Zhang, Weixia Zhang, Chaofeng Chen, Liang Liao, Chunyi Li, Yixuan Gao, Annan Wang, Erli Zhang, Wenxiu Sun, et al · 2023
Later among the works it cites.
Learning enriched features via selective state spaces model for efficient image deblurring
Hu Gao, Bowen Ma, Ying Zhang, Jingfan Yang, Jing Yang, and Depeng Dang · 2024
Closest in time.
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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Loformer: Local frequency transformer for image deblurring
Xintian Mao, Jiansheng Wang, Xingran Xie, Qingli Li, and Yan Wang · 2024
Closest in time.
Badri Narayana Patro and Vijay Srinivas Agneeswaran · 2024
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