Fetching the paper…
Reading the bibliography…
Video compression artifact reduction aims to recover high-quality videos from low-quality compressed videos.
Nonlinear space-variant postprocessing of block coded images
Bhaskar Ramamurthi and Allen Gersho · 1986
Earlier work this paper cites.
Iterative procedures for reduction of blocking effects in transform image coding
Avideh Zakhor · 1992
Earlier work this paper cites.
An optimization approach for removing blocking effects in transform coding
Shigenobu Minami and Avideh Zakhor · 1995
Earlier work this paper cites.
An efficient wavelet-based deblocking algorithm for highly compressed images
Shuanhu Wu, Hong Yan, and Zheng Tan · 2001
Earlier work this paper cites.
A non-local algorithm for image denoising
Antoni Buades, Bartomeu Coll, and J-M Morel · 2005
Earlier work this paper cites.
Image denoising by sparse 3-d transform-domain collaborative filtering
Kostadin Dabov, Alessandro Foi, Vladimir Katkovnik, and Karen Egiazarian · 2007
Earlier work this paper cites.
Common test conditions and software reference configurations, joint collaborative team on video coding (jct-vc) of itut sg16 wp3 and iso
Frank Bossen · 2012
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
Earlier work this paper cites.
Overview of the high efficiency video coding(hevc) standard
Gary J Sullivan, Jens-Rainer Ohm, Woo-Jin Han, Thomas Wiegand, et al · 2012
Earlier work this paper cites.
Compression artifact reduction by overlapped-block transform coefficient estimation with block similarity
Xinfeng Zhang, Ruiqin Xiong, Xiaopeng Fan, Siwei Ma, and Wen Gao · 2013
Earlier work this paper cites.
Reducing artifacts in jpeg decompression via a learned dictionary
Huibin Chang, Michael K Ng, and Tieyong Zeng · 2014
Earlier work this paper cites.
Characterizing perceptual artifacts in compressed video streams
Kai Zeng, Tiesong Zhao, Abdul Rehman, and Zhou Wang · 2014
Earlier work this paper cites.
Compression artifacts reduction by a deep convolutional network
Chao Dong, Yubin Deng, Chen Change Loy, and Xiaoou Tang · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Data-driven sparsity-based restoration of jpeg-compressed images in dual transform-pixel domain
Xianming Liu, Xiaolin Wu, Jiantao Zhou, and Debin Zhao · 2015
Earlier work this paper cites.
Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, et al · 2015
Earlier work this paper cites.
Convolutional lstm network: A machine learning approach for precipitation nowcasting
SHI Xingjian, Zhourong Chen, Hao Wang, Dit-Yan Yeung, Wai-Kin Wong, and Wang-chun Woo · 2015
Earlier work this paper cites.
Building dual-domain representations for compression artifacts reduction
Jun Guo and Hongyang Chao · 2016
Cited alongside, same era.
Video super-resolution with convolutional neural networks
Armin Kappeler, Seunghwan Yoo, Qiqin Dai, and Aggelos K Katsaggelos · 2016
Cited alongside, same era.
Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections
Xiaojiao Mao, Chunhua Shen, and Yu-Bin Yang · 2016
Cited alongside, same era.
Compression artifacts removal using convolutional neural networks
Pavel Svoboda, Michal Hradis, David Barina, and Pavel Zemcik · 2016
Cited alongside, same era.
Deep mean-shift priors for image restoration
Siavash Arjomand Bigdeli, Matthias Zwicker, Paolo Favaro, and Meiguang Jin · 2017
Cited alongside, same era.
Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising
Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, and Lei Zhang · 2017
Later among the works it cites.
Learning deep cnn denoiser prior for image restoration
Kai Zhang, Wangmeng Zuo, Shuhang Gu, and Lei Zhang · 2017
Later among the works it cites.
Dpw-sdnet: Dual pixel-wavelet domain deep cnns for soft decoding of jpeg-compressed images
Honggang Chen, Xiaohai He, Linbo Qing, Shuhua Xiong, and Truong Q Nguyen · 2018
Later among the works it cites.
Decoder side image quality enhancement exploiting inter-channel correlation in a 3-stage cnn: Submission to clic 2018
Kai Cui and Eckehard Steinbach · 2018
Later among the works it cites.
Quality enhancement for intra frame coding via cnns: An adversarial approach
Zhipeng Jin, Ping An, Chao Yang, and Liquan Shen · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Jose Caballero, Christian Ledig, Andrew Aitken, Alejandro Acosta, Johannes Totz, Zehan Wang, and Wenzhe Shi · 2017
Cited alongside, same era.
One network to solve them all-solving linear inverse problems using deep projection models
Jen-Hao Rick Chang, Chun-Liang Li, Barnabas Poczos, BVK Vijaya Kumar, and Aswin C Sankaranarayanan · 2017
Cited alongside, same era.
A convolutional neural network approach for post-processing in hevc intra coding
Yuanying Dai, Dong Liu, and Feng Wu · 2017
Cited alongside, same era.
Deep generative adversarial compression artifact removal
Leonardo Galteri, Lorenzo Seidenari, Marco Bertini, and Alberto Del Bimbo · 2017
Cited alongside, same era.
One-to-many network for visually pleasing compression artifacts reduction
Jun Guo and Hongyang Chao · 2017
Cited alongside, same era.
An efficient deep convolutional neural networks model for compressed image deblocking
Ke Li, Bahetiyaer Bare, and Bo Yan · 2017
Cited alongside, same era.
Robust video super-resolution with learned temporal dynamics
Ding Liu, Zhaowen Wang, Yuchen Fan, Xianming Liu, Zhangyang Wang, Shiyu Chang, and Thomas Huang · 2017
Cited alongside, same era.
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
Later among the works it cites.
Spatio-temporal transformer network for video restoration
Tae Hyun Kim, Mehdi SM Sajjadi, Michael Hirsch, and Bernhard Schölkopf · 2018
Later among the works it cites.
Non-local recurrent network for image restoration
Ding Liu, Bihan Wen, Yuchen Fan, Chen Change Loy, and Thomas S Huang · 2018
Later among the works it cites.
Deep kalman filtering network for video compression artifact reduction
Guo Lu, Wanli Ouyang, Dong Xu, Xiaoyun Zhang, Zhiyong Gao, and Ming-Ting Sun · 2018
Later among the works it cites.
Blockcnn: A deep network for artifact removal and image compression
Danial Maleki, Soheila Nadalian, Mohammad Mahdi Derakhshani, and Mohammad Amin Sadeghi · 2018
Later among the works it cites.
Frame-recurrent video super-resolution
Mehdi SM Sajjadi, Raviteja Vemulapalli, and Matthew Brown · 2018
Later among the works it cites.
Non-local neural networks
Xiaolong Wang, Ross Girshick, Abhinav Gupta, and Kaiming He · 2018
Later among the works it cites.
Enhancing quality for hevc compressed videos
Ren Yang, Mai Xu, Tie Liu, Zulin Wang, and Zhenyu Guan · 2018
Later among the works it cites.
Multi-frame quality enhancement for compressed video
Ren Yang, Mai Xu, Zulin Wang, and Tianyi Li · 2018
Later among the works it cites.
Image restoration by estimating frequency distribution of local patches
Jaeyoung Yoo, Sang-ho Lee, and Nojun Kwak · 2018
Later among the works it cites.
Mfqe 2.0: A new approach for multi-frame quality enhancement on compressed video
Zhenyu Guan, Qunliang Xing, Mai Xu, Ren Yang, Tie Liu, and Zulin Wang · 2019
Closest in time.
Video enhancement with task-oriented flow
Tianfan Xue, Baian Chen, Jiajun Wu, Donglai Wei, and William T Freeman · 2019
Closest in time.