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Lossy compression algorithms are typically designed to achieve the lowest possible distortion at a given bit rate.
Coding theorems for a discrete source with a fidelity criteria
Shannon, C · 1959
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Multiscale structural similarity for image quality assessment
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Bovik, A. C., Sheikh, H. R., and Simoncelli, E. P · 2004
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Reduced-reference image quality assessment using a wavelet-domain natural image statistic model
Wang, Z. and Simoncelli, E. P · 2005
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Elements of Information Theory
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Making a completely blind image quality analyzer
Mittal, A., Soundararajan, R., and Bovik, A. C · 2013
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Generative adversarial nets
Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
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Conditional generative adversarial nets
Mirza, M. and Osindero, S · 2014
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Very deep convolutional networks for large-scale image recognition
Simonyan, K. and Zisserman, A · 2015
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End-to-end optimization of nonlinear transform codes for perceptual quality
Ballé, J., Laparra, V., and Simoncelli, E. P · 2016
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Generating images with perceptual similarity metrics based on deep networks
Dosovitskiy, A. and Brox, T · 2016
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Image style transfer using convolutional neural networks
Gatys, L. A., Ecker, A. S., and Bethge, M · 2016
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Perceptual losses for real-time style transfer and super-resolution
Johnson, J., Alahi, A., and Fei-Fei, L · 2016
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Improved techniques for training gans
Salimans, T., Goodfellow, I. J., Zaremba, W., Cheung, V., Radford, A., and Chen, X · 2016
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Variable rate image compression with recurrent neural networks
Toderici, G., O’Malley, S. M., Hwang, S. J., Vincent, D., Minnen, D., Baluja, S., Covell, M., and Sukthankar, R · 2016
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Colorful image colorization
Zhang, R., Isola, P., and Efros, A. A · 2016
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Soft-to-hard vector quantization for end-to-end learning compressible representations
Agustsson, E., Mentzer, F., Tschannen, M., Cavigelli, L., Timofte, R., Benini, L., and Gool, L. V · 2017
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Arjovsky, M., Chintala, S., and Bottou, L · 2017
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End-to-end optimized image compression
Ballé, J., Laparra, V., and Simoncelli, E. P · 2017
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Photographic image synthesis with cascaded refinement networks
Improved lossy image compression with priming and spatially adaptive bit rates for recurrent networks
Johnston, N., Vincent, D., Minnen, D., Covell, M., Singh, S., Chinen, T., Jin Hwang, S., Shor, J., and Toderici, G · 2018
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Learning convolutional networks for content-weighted image compression
Li, M., Zuo, W., Gu, S., Zhao, D., and Zhang, D · 2018
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Deep generative models for distribution-preserving lossy compression
M Tschannen, E Agustsson, M. L · 2018
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Conditional probability models for deep image compression
Mentzer, F., Agustsson, E., Tschannen, M., Timofte, R., and Gool, L. V · 2018
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Joint autoregressive and hierarchical priors for learned image compression
Minnen, D., Ballé, J., and Toderici, G · 2018
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Generative compression
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Chen, Q. and Koltun, V · 2017
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Deep generative adversarial compression artifact removal
Galteri, L., Seidenari, L., Bertini, M., and Bimbo, A. D · 2017
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Improved training of wasserstein gans
Ishaan, G., Faruk, A., Martin, A., Vincent, D., and Courville, A. C · 2017
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Photo-realistic single image super-resolution using a generative adversarial network
Ledig, C., Theis, L., Huszár, F., Caballero, J., Cunningham, A., Acosta, A., Aitken, A., Tejani, A., Totz, J., Wang, Z., and Shi, W · 2017
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Learning a no-reference quality metric for single-image super-resolution
Ma, C., Yang, C., Yang, X., and Yang, M · 2017
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Real-time adaptive image compression
Rippel, O. and Bourdev, L · 2017
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Full resolution image compression with recurrent neural networks
Toderici, G., Vincent, D., Johnston, N., Hwang, S. J., Minnen, D., Shor, J., and Covell, M · 2017
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Santurkar, S., Budden, D. M., and Shavit, N · 2018
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Deformation aware image compression
Shaham, T. R. and Michaeli, T · 2018
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ESRGAN: Enhanced super-resolution generative adversarial networks
Wang, X., Yu, K., Wu, S., Gu, J., Liu, Y., Dong, C., Qiao, Y., and Loy, C. C · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Zhang, R., Isola, P., Efros, A. A., Shechtman, E., and Wang, O · 2018
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Generative adversarial networks for extreme learned image compression
Agustsson, E., Tschannen, M., Mentzer, F., Timofte, R., and Van Gool, L · 2019
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Rethinking lossy compression: The rate-distortion-perception tradeoff
Blau, Y. and Michaeli, T · 2019
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Generating diverse high-fidelity images with VQ-VAE-2
Razavi, A., van den Oord, A., and Vinyals, O · 2019
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Fidelity-controllable extreme image compression with generative adversarial networks
Iwai, S., Miyazaki, T., Sugaya, Y., and Omachi, S · 2020
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High-fidelity generative image compression
Mentzer, F., Toderici, G., Tschannen, M., and Agustsson, E · 2020
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A gan-based tunable image compression system
Wu, L., Huang, K., and Shen, H · 2020
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