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Video denoising aims at removing noise from videos to recover clean ones.
Two deterministic half-quadratic regularization algorithms for computed imaging
Pierre Charbonnier, Laure Blanc-Feraud, Gilles Aubert, and Michel Barlaud · 1994
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Image denoising by sparse 3-d transform-domain collaborative filtering
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian · 2007
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Practical poissonian-gaussian noise modeling and fitting for single-image raw-data
Alessandro Foi, Mejdi Trimeche, Vladimir Katkovnik, and Karen Egiazarian · 2008
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Blind/referenceless image spatial quality evaluator
Anish Mittal, Anush K Moorthy, and Alan C Bovik · 2011
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Video denoising, deblocking, and enhancement through separable 4-d nonlocal spatiotemporal transforms
Matteo Maggioni, Giacomo Boracchi, Alessandro Foi, and Karen Egiazarian · 2012
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Making a “completely blind” image quality analyzer
Anish Mittal, Rajiv Soundararajan, and Alan C Bovik · 2012
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A nonlocal bayesian image denoising algorithm
Marc Lebrun, Antoni Buades, and Jean-Michel Morel · 2013
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Blind image quality evaluation using perception based features
N Venkatanath, D Praneeth, Maruthi Chandrasekhar Bh, Sumohana S Channappayya, and Swarup S Medasani · 2015
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Deep rnns for video denoising
Xinyuan Chen, Li Song, and Xiaokang Yang · 2016
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Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 2016
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Benchmarking denoising algorithms with real photographs
Tobias Plotz and Stefan Roth · 2017
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Optical flow estimation using a spatial pyramid network
Anurag Ranjan and Michael J Black · 2017
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Generalized deep image to image regression
Venkataraman Santhanam, Vlad I Morariu, and Larry S Davis · 2017
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Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang · 2017
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Video denoising via empirical bayesian estimation of space-time patches
Pablo Arias and Jean-Michel Morel · 2018
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Image blind denoising with generative adversarial network based noise modeling
Jingwen Chen, Jiawei Chen, Hongyang Chao, and Ming Yang · 2018
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Non-local video denoising by cnn
Axel Davy, Thibaud Ehret, Jean-Michel Morel, Pablo Arias, and Gabriele Facciolo · 2018
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Video object segmentation with language referring expressions
Anna Khoreva, Anna Rohrbach, and Bernt Schiele · 2018
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Burst denoising with kernel prediction networks
Ben Mildenhall, Jonathan T Barron, Jiawen Chen, Dillon Sharlet, Ren Ng, and Robert Carroll · 2018
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Denoising with kernel prediction and asymmetric loss functions
Thijs Vogels, Fabrice Rousselle, Brian McWilliams, Gerhard Röthlin, Alex Harvill, David Adler, Mark Meyer, and Jan Novák · 2018
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Ffdnet: Toward a fast and flexible solution for cnn-based image denoising
Kai Zhang, Wangmeng Zuo, and Lei Zhang · 2018
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Real image denoising with feature attention
Saeed Anwar and Nick Barnes · 2019
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Unprocessing images for learned raw denoising
Tim Brooks, Ben Mildenhall, Tianfan Xue, Jiawen Chen, Dillon Sharlet, and Jonathan T Barron · 2019
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Seeing motion in the dark
Chen Chen, Qifeng Chen, Minh N Do, and Vladlen Koltun · 2019
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Videnn: Deep blind video denoising
Michele Claus and Jan van Gemert · 2019
Cited alongside, same era.
Generating training data for denoising real rgb images via camera pipeline simulation
Ronnachai Jaroensri, Camille Biscarrat, Miika Aittala, and Frédo Durand · 2019
Cited alongside, same era.
Grdn: Grouped residual dense network for real image denoising and gan-based real-world noise modeling
Dong-Wook Kim, Jae Ryun Chung, and Seung-Won Jung · 2019
Cited alongside, same era.
Ntire 2019 challenge on video deblurring and super-resolution: Dataset and study
Seungjun Nah, Sungyong Baik, Seokil Hong, Gyeongsik Moon, Sanghyun Son, Radu Timofte, and Kyoung Mu Lee · 2019
Cited alongside, same era.
Dvdnet: A fast network for deep video denoising
Matias Tassano, Julie Delon, and Thomas Veit · 2019
Cited alongside, same era.
Noise2score: tweedie’s approach to self-supervised image denoising without clean images
Kwanyoung Kim and Jong Chul Ye · 2021
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Restore from restored: Video restoration with pseudo clean video
Seunghwan Lee, Donghyeon Cho, Jiwon Kim, and Tae Hyun Kim · 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
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Functional neural networks for parametric image restoration problems
Fangzhou Luo, Xiaolin Wu, and Yanhui Guo · 2021
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Efficient multi-stage video denoising with recurrent spatio-temporal fusion
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Xintao Wang, Kelvin CK Chan, Ke Yu, Chao Dong, and Chen Change Loy · 2019
Cited alongside, same era.
Video enhancement with task-oriented flow
Tianfan Xue, Baian Chen, Jiajun Wu, Donglai Wei, and William T Freeman · 2019
Cited alongside, same era.
Deep iterative down-up cnn for image denoising
Songhyun Yu, Bumjun Park, and Jechang Jeong · 2019
Cited alongside, same era.
Deformable convnets v2: More deformable, better results
Xizhou Zhu, Han Hu, Stephen Lin, and Jifeng Dai · 2019
Cited alongside, same era.
Learning camera-aware noise models
Ke-Chi Chang, Ren Wang, Hung-Jin Lin, Yu-Lun Liu, Chia-Ping Chen, Yu-Lin Chang, and Hwann-Tzong Chen · 2020
Cited alongside, same era.
Transfer learning from synthetic to real-noise denoising with adaptive instance normalization
Yoonsik Kim, Jae Woong Soh, Gu Yong Park, and Nam Ik Cho · 2020
Cited alongside, same era.
Ntire 2020 challenge on real-world image super-resolution: Methods and results
Andreas Lugmayr, Martin Danelljan, and Radu Timofte · 2020
Cited alongside, same era.
Matteo Maggioni, Yibin Huang, Cheng Li, Shuai Xiao, Zhongqian Fu, and Fenglong Song · 2021
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Adaptive consistency prior based deep network for image denoising
Chao Ren, Xiaohai He, Chuncheng Wang, and Zhibo Zhao · 2021
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Unsupervised deep video denoising
Dev Yashpal Sheth, Sreyas Mohan, Joshua L Vincent, Ramon Manzorro, Peter A Crozier, Mitesh M Khapra, Eero P Simoncelli, and Carlos Fernandez-Granda · 2021
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Patch craft: Video denoising by deep modeling and patch matching
Gregory Vaksman, Michael Elad, and Peyman Milanfar · 2021
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Patch craft: Video denoising by deep modeling and patch matching
Gregory Vaksman, Michael Elad, and Peyman Milanfar · 2021
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Hi-gan: A hierarchical generative adversarial network for blind denoising of real photographs
Duc My Vo, Duc Manh Nguyen, Thao Phuong Le, and Sang-Woong Lee · 2021
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Real-esrgan: Training real-world blind super-resolution with pure synthetic data
Xintao Wang, Liangbin Xie, Chao Dong, and Ying Shan · 2021
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Multi-stage progressive image restoration
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, and Ling Shao · 2021
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Designing a practical degradation model for deep blind image super-resolution
Kai Zhang, Jingyun Liang, Luc Van Gool, and Radu Timofte · 2021
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An unsupervised deep learning approach for real-world image denoising
Dihan Zheng, Sia Huat Tan, Xiaowen Zhang, Zuoqiang Shi, Kaisheng Ma, and Chenglong Bao · 2021
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Deep convolutional dictionary learning for image denoising
Hongyi Zheng, Hongwei Yong, and Lei Zhang · 2021
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Basicvsr++: Improving video super-resolution with enhanced propagation and alignment
Kelvin CK Chan, Shangchen Zhou, Xiangyu Xu, and Chen Change Loy · 2022
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Investigating tradeoffs in real-world video super-resolution
Kelvin CK Chan, Shangchen Zhou, Xiangyu Xu, and Chen Change Loy · 2022
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On the generalization of basicvsr++ to video deblurring and denoising
Kelvin CK Chan, Shangchen Zhou, Xiangyu Xu, and Chen Change Loy · 2022
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Model-based image signal processors via learnable dictionaries
Marcos V Conde, Steven McDonagh, Matteo Maggioni, Ales Leonardis, and Eduardo Pérez-Pellitero · 2022
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Self-supervision versus synthetic datasets: which is the lesser evil in the context of video denoising?
Valéry Dewil, Arnaud Barral, Gabriele Facciolo, and Pablo Arias · 2022
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Neural compression-based feature learning for video restoration
Cong Huang, Jiahao Li, Bin Li, Dong Liu, and Yan Lu · 2022
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Unidirectional video denoising by mimicking backward recurrent modules with look-ahead forward ones
Junyi Li, Xiaohe Wu, Zhenxing Niu, and Wangmeng Zuo · 2022
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Vrt: A video restoration transformer
Jingyun Liang, Jiezhang Cao, Yuchen Fan, Kai Zhang, Rakesh Ranjan, Yawei Li, Radu Timofte, and Luc Van Gool · 2022
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Noise2noiseflow: Realistic camera noise modeling without clean images
Ali Maleky, Shayan Kousha, Michael S Brown, and Marcus A Brubaker · 2022
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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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Practical blind denoising via swin-conv-unet and data synthesis
Kai Zhang, Yawei Li, Jingyun Liang, Jiezhang Cao, Yulun Zhang, Hao Tang, Radu Timofte, and Luc Van Gool · 2022
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