Multi-scale and Context-adaptive Entropy Model for Image Compression

End-to-end optimization of nonlinear transform codes for perceptual quality

Johannes Ballé, Valero Laparra, and Eero P Simoncelli · 2016

Earlier work this paper cites.

Conditional image generation with pixelcnn decoders

Aaron Van den Oord, Nal Kalchbrenner, Lasse Espeholt, Oriol Vinyals, Alex Graves, et al · 2016

Earlier work this paper cites.

Enhanced deep residual networks for single image super-resolution

Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 2017

Earlier work this paper cites.

Real-time adaptive image compression

Oren Rippel and Lubomir Bourdev · 2017

Earlier work this paper cites.

Lossy image compression with compressive autoencoders

Original

Lucas Theis, Wenzhe Shi, Andrew Cunningham, and Ferenc Huszár · 2017

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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.

Generative adversarial networks for extreme learned image compression

Original

Eirikur Agustsson, Michael Tschannen, Fabian Mentzer, Radu Timofte, and Luc Van Gool · 2018

Cited alongside, same era.

Variational image compression with a scale hyperprior

Original

Johannes Ballé, David Minnen, Saurabh Singh, Sung Jin Hwang, and Nick Johnston · 2018

Cited alongside, same era.

Context-adaptive entropy model for end-to-end optimized image compression

Original

Jooyoung Lee, Seunghyum Cho, and Seung-Kwon Beack · 2018

Later among the works it cites.

Conditional probability models for deep image compression

Fabian Mentzer, Eirikur Agustsson, Michael Tschannen, Radu Timofte, and Luc Van Gool · 2018

Later among the works it cites.

Joint autoregressive and hierarchical priors for learned image compression

David Minnen, Johannes Ballé, and George D Toderici · 2018

Later among the works it cites.