Fetching the paper…
Reading the bibliography…
We propose a context-adaptive entropy model for use in end-to-end optimized image compression.
Kodak lossless true color image suite (photocd pcd0992), 1993
Eastman Kodak · 1993
Earlier work this paper cites.
Multiscale structural similarity for image quality assessment
Zhou Wang, Eero P. Simoncelli, and Alan C. Bovik · 2003
Earlier work this paper cites.
Information technology – high efficiency coding and media delivery in heterogeneous environments – part 2: High efficiency video coding
ISO/IEC 23008-2, ITU-T H.265 · 2013
Earlier work this paper cites.
Bpg image format, 2014
Fabrice Bellard · 2014
Earlier work this paper cites.
Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
Earlier work this paper cites.
Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
Earlier work this paper cites.
Stochastic backpropagation and approximate inference in deep generative models
Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
Earlier work this paper cites.
Compression artifacts reduction by a deep convolutional network
Chao Dong, Yubin Deng, Chen Change Loy, and Xiaoou Tang 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.
Pixel recurrent neural networks
Aaron van den Oord, Nal Kalchbrenner, and Koray Kavukcuoglu · 2016
Cited alongside, same era.
Context encoders: Feature learning by inpainting
Deepak Pathak, Philipp Krähenbühl, Jeff Donahue, Trevor Darrell, and Alexei A. Efros · 2016
Cited alongside, same era.
Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2016
Cited alongside, same era.
Compression artifacts removal using convolutional neural networks
Pavel Svoboda, Michal Hradis, David Barina, and Pavel Zemcík · 2016
Cited alongside, same era.
The new data in multimedia research
Bart Thomee, David A. Shamma, Gerald Friedland, Benjamin Elizalde, Karl Ni, Douglas Poland, Damian Borth, and Li-Jia Li · 2016
Cited alongside, same era.
High-resolution image inpainting using multi-scale neural patch synthesis
Chao Yang, Xin Lu, Zhe Lin, Eli Shechtman, Oliver Wang, and Hao Li · 2017
Later among the works it cites.
Semantic image inpainting with deep generative models
Raymond A. Yeh, Chen Chen, Teck-Yian Lim, Alexander G. Schwing, Mark Hasegawa-Johnson, and Minh N. Do · 2017
Later among the works it cites.
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.
Energy-based generative adversarial network
Junbo Jake Zhao, Michaël Mathieu, and Yann LeCun · 2017
Later among the works it cites.
Generative adversarial networks for extreme learned image compression
Eirikur Agustsson, Michael Tschannen, Fabian Mentzer, Radu Timofte, and Luc Van Gool · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
End-to-end optimized image compression
Johannes Ballé, Valero Laparra, and Eero P. Simoncelli · 2017
Cited alongside, same era.
Real-time adaptive image compression
Oren Rippel and Lubomir Bourdev · 2017
Cited alongside, same era.
Lossy image compression with compressive autoencoders
Lucas Theis, Wenzhe Shi, Andrew Cunningham, and Ferenc Huszár · 2017
Cited alongside, same era.
Full resolution image compression with recurrent neural networks
George Toderici, Damien Vincent, Nick Johnston, Sung Jin Hwang, David Minnen, Joel Shor, and Michele Covell · 2017
Cited alongside, same era.
Closest in time.
Variational image compression with a scale hyperprior
Johannes Ballé, David Minnen, Saurabh Singh, Sung Jin Hwang, and Nick Johnston · 2018
Closest in time.
Improved lossy image compression with priming and spatially adaptive bit rates for recurrent networks
Nick Johnston, Damien Vincent, David Minnen, Michele Covell, Saurabh Singh, Troy Chinen, Sung Jin Hwang, Joel Shor, and George Toderici · 2018
Closest in time.
Shibani Santurkar, David M. Budden, and Nir Shavit · 2018
Closest in time.