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Video restoration aims at restoring multiple high-quality frames from multiple low-quality frames.
Two deterministic half-quadratic regularization algorithms for computed imaging
Pierre Charbonnier, Laure Blanc-Feraud, Gilles Aubert, and Michel Barlaud · 1994
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On bayesian adaptive video super resolution
Ce Liu and Deqing Sun · 2013
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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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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Flownet: Learning optical flow with convolutional networks
Alexey Dosovitskiy, Philipp Fischer, Eddy Ilg, Philip Hausser, Caner Hazirbas, Vladimir Golkov, Patrick Van Der Smagt, Daniel Cremers, and Thomas Brox · 2015
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Bidirectional recurrent convolutional networks for multi-frame super-resolution
Yan Huang, Wei Wang, and Liang Wang · 2015
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Video super-resolution via deep draft-ensemble learning
Renjie Liao, Xin Tao, Ruiyu Li, Ziyang Ma, and Jiaya Jia · 2015
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Video super-resolution with convolutional neural networks
Armin Kappeler, Seunghwan Yoo, Qiqin Dai, and Aggelos K Katsaggelos · 2016
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Sgdr: Stochastic gradient descent with warm restarts
Ilya Loshchilov and Frank Hutter · 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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Real-time video super-resolution with spatio-temporal networks and motion compensation
Jose Caballero, Christian Ledig, Andrew Aitken, Alejandro Acosta, Johannes Totz, Zehan Wang, and Wenzhe Shi · 2017
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Real-time video super-resolution with spatio-temporal networks and motion compensation
Jose Caballero, Christian Ledig, Andrew Aitken, Alejandro Acosta, Johannes Totz, Zehan Wang, and Wenzhe Shi · 2017
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Deformable convolutional networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, and Yichen Wei · 2017
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Video super-resolution via bidirectional recurrent convolutional networks
Yan Huang, Wei Wang, and Liang Wang · 2017
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Robust video super-resolution with learned temporal dynamics
Ding Liu, Zhaowen Wang, Yuchen Fan, Xianming Liu, Zhangyang Wang, Shiyu Chang, and Thomas Huang · 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
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Optical flow estimation using a spatial pyramid network
Anurag Ranjan and Michael J Black · 2017
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Deep video deblurring for hand-held cameras
Shuochen Su, Mauricio Delbracio, Jue Wang, Guillermo Sapiro, Wolfgang Heidrich, and Oliver Wang · 2017
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Detail-revealing deep video super-resolution
Xin Tao, Hongyun Gao, Renjie Liao, Jue Wang, and Jiaya Jia · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 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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Deep video super-resolution network using dynamic upsampling filters without explicit motion compensation
Younghyun Jo, Seoung Wug Oh, Jaeyeon Kang, and Seon Joo Kim · 2018
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Video object segmentation with language referring expressions
Anna Khoreva, Anna Rohrbach, and Bernt Schiele · 2018
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Spatio-temporal transformer network for video restoration
Tae Hyun Kim, Mehdi SM Sajjadi, Michael Hirsch, and Bernhard Scholkopf · 2018
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A reimplementation of SPyNet using PyTorch
Simon Niklaus · 2018
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Frame-recurrent video super-resolution
Mehdi SM Sajjadi, Raviteja Vemulapalli, and Matthew Brown · 2018
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Pwc-net: Cnns for optical flow using pyramid, warping, and cost volume
Deqing Sun, Xiaodong Yang, Ming-Yu Liu, and Jan Kautz · 2018
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Scale-recurrent network for deep image deblurring
Xin Tao, Hongyun Gao, Xiaoyong Shen, Jue Wang, and Jiaya Jia · 2018
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Learning a single convolutional super-resolution network for multiple degradations
Kai Zhang, Wangmeng Zuo, and Lei Zhang · 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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Efficient video super-resolution through recurrent latent space propagation
Dario Fuoli, Shuhang Gu, and Radu Timofte · 2019
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Recurrent back-projection network for video super-resolution
Muhammad Haris, Gregory Shakhnarovich, and Norimichi Ukita · 2019
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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
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Recurrent neural networks with intra-frame iterations for video deblurring
Seungjun Nah, Sanghyun Son, 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.
Edvr: Video restoration with enhanced deformable convolutional networks
Xintao Wang, Kelvin CK Chan, Ke Yu, Chao Dong, and Chen Change Loy · 2019
Cited alongside, same era.
R-transformer: Recurrent neural network enhanced transformer
Zhiwei Wang, Yao Ma, Zitao Liu, and Jiliang Tang · 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.
Progressive fusion video super-resolution network via exploiting non-local spatio-temporal correlations
Localvit: Bringing locality to vision transformers
Yawei Li, Kai Zhang, Jiezhang Cao, Radu Timofte, and Luc Van Gool · 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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Hierarchical conditional flow: A unified framework for image super-resolution and image rescaling
Jingyun Liang, Andreas Lugmayr, Kai Zhang, Martin Danelljan, Luc Van Gool, and Radu Timofte · 2021
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Mutual affine network for spatially variant kernel estimation in blind image super-resolution
Jingyun Liang, Guolei Sun, Kai Zhang, Luc Van Gool, and Radu Timofte · 2021
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Flow-based kernel prior with application to blind super-resolution
Jingyun Liang, Kai Zhang, Shuhang Gu, Luc Van Gool, and Radu Timofte · 2021
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Peng Yi, Zhongyuan Wang, Kui Jiang, Junjun Jiang, and Jiayi Ma · 2019
Cited alongside, same era.
Spatio-temporal filter adaptive network for video deblurring
Shangchen Zhou, Jiawei Zhang, Jinshan Pan, Haozhe Xie, Wangmeng Zuo, and Jimmy Ren · 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.
End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 2020
Cited alongside, same era.
Learning temporal coherence via self-supervision for gan-based video generation
Mengyu Chu, You Xie, Jonas Mayer, Laura Leal-Taixé, and Nils Thuerey · 2020
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.
Video super-resolution with recurrent structure-detail network
Takashi Isobe, Xu Jia, Shuhang Gu, Songjiang Li, Shengjin Wang, and Qi Tian · 2020
Cited alongside, same era.
Jiayi Lin, Yan Huang, and Liang Wang · 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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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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Recurrent video deblurring with blur-invariant motion estimation and pixel volumes
Hyeongseok Son, Junyong Lee, Jonghyeop Lee, Sunghyun Cho, and Seungyong Lee · 2021
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Gated spatio-temporal attention-guided video deblurring
Maitreya Suin and AN Rajagopalan · 2021
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Boosting crowd counting with transformers
Guolei Sun, Yun Liu, Thomas Probst, Danda Pani Paudel, Nikola Popovic, and Luc Van Gool · 2021
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Mefnet: Multi-scale event fusion network for motion deblurring
Lei Sun, Christos Sakaridis, Jingyun Liang, Qi Jiang, Kailun Yang, Peng Sun, Yaozu Ye, Kaiwei Wang, and Luc Van Gool · 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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Scaling local self-attention for parameter efficient visual backbones
Ashish Vaswani, Prajit Ramachandran, Aravind Srinivas, Niki Parmar, Blake Hechtman, and Jonathon Shlens · 2021
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Uformer: A general u-shaped transformer for image restoration
Zhendong Wang, Xiaodong Cun, Jianmin Bao, and Jianzhuang Liu · 2021
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Omniscient video super-resolution
Peng Yi, Zhongyuan Wang, Kui Jiang, Junjun Jiang, Tao Lu, Xin Tian, and Jiayi Ma · 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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Towards interpretable video super-resolution via alternating optimization
Jiezhang Cao, Jingyun Liang, Kai Zhang, Wenguan Wang, Qin Wang, Yulun Zhang, Hao Tang, and Luc Van Gool · 2022
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Practical real video denoising with realistic degradation model
Jiezhang Cao, Qin Wang, Jingyun Liang, Yulun Zhang, Kai Zhang, and Luc Van Gool · 2022
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Vdtr: Video deblurring with transformer
Mingdeng Cao, Yanbo Fan, Yong Zhang, Jue Wang, and Yujiu Yang · 2022
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Fast online video super-resolution with deformable attention pyramid
Dario Fuoli, Martin Danelljan, Radu Timofte, and Luc Van Gool · 2022
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Rstt: Real-time spatial temporal transformer for space-time video super-resolution
Zhicheng Geng, Luming Liang, Tianyu Ding, and Ilya Zharkov · 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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Flow-guided sparse transformer for video deblurring
Jing Lin, Yuanhao Cai, Xiaowan Hu, Haoqian Wang, Youliang Yan, Xueyi Zou, Henghui Ding, Yulun Zhang, Radu Timofte, and Luc Van Gool · 2022
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Learning trajectory-aware transformer for video super-resolution
Chengxu Liu, Huan Yang, Jianlong Fu, and Xueming Qian · 2022
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Video super-resolution based on deep learning: a comprehensive survey
Hongying Liu, Zhubo Ruan, Peng Zhao, Chao Dong, Fanhua Shang, Yuanyuan Liu, Linlin Yang, and Radu Timofte · 2022
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Maxim: Multi-axis mlp for image processing
Zhengzhong Tu, Hossein Talebi, Han Zhang, Feng Yang, Peyman Milanfar, Alan Bovik, and Yinxiao Li · 2022
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Maxvit: Multi-axis vision transformer
Zhengzhong Tu, Hossein Talebi, Han Zhang, Feng Yang, Peyman Milanfar, Alan Bovik, and Yinxiao Li · 2022
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Bringing old films back to life
Ziyu Wan, Bo Zhang, Dongdong Chen, and Jing Liao · 2022
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Vision transformer with deformable attention
Zhuofan Xia, Xuran Pan, Shiji Song, Li Erran Li, and Gao Huang · 2022
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Coarse-to-fine video denoising with dual-stage spatial-channel transformer
Wulian Yun, Mengshi Qi, Chuanming Wang, Huiyuan Fu, and Huadong Ma · 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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