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A rate-distortion-perception (RDP) tradeoff has recently been proposed by Blau and Michaeli and also Matsumoto.
C. E. Shannon, “A mathematical theory of communication,” Bell Syst. Tech. J. , vol. 27, pp. 379–423 and 623–656, 1948
1948
Earlier work this paper cites.
——, “Coding theorems for a discrete source with a fidelity criterion,” IRE Nat. Conv. Rec. , vol. 7, no. 4, pp. 142–163, Mar. 1959
1959
Earlier work this paper cites.
T. Berger, Rate Distortion Theory: A Mathematical Basis for Data Compression . Englewood Cliffs, NJ: Prentice Hall, 1971
1971
Earlier work this paper cites.
A. D. Wyner, “The common information of two dependent random variables,” IEEE Trans. Inf. Theory , vol. 21, no. 2, pp. 163–179, 1975
1975
Earlier work this paper cites.
E. J. Delp and O. R. Mitchell, “Moment preserving quantization,” IEEE Trans. Commun. , vol. 37, no. 11, pp. 1549–1558, Nov. 1991
1991
Earlier work this paper cites.
T. S. Han and S. Verdú, “Approximation theory of output statistics,” IEEE Trans. Inf. Theory , vol. 39, no. 3, pp. 752 – 772, 1993
1993
Earlier work this paper cites.
A. György and T. Linder, “Optimal entropy-constrained scalar quantization of a uniform source,” IEEE Trans. Inf. Theory , vol. 46, no. 7, pp. 2704–2711, 2000
2000
Earlier work this paper cites.
M. Hayashi, “General nonasymptotic and asymptotic formulas in channel resolvability and identification capacity and their application to the wiretap channel,” IEEE Trans. Inf. Theory , vol. 52, no. 4, pp. 1562–1575, 2006
2006
Earlier work this paper cites.
T. M. Cover and J. A. Thomas, Elements of Information Theory , 2nd ed. Hoboken: John Wiley & Sons, 2006
2006
Earlier work this paper cites.
W. A. Pearlman and A. Said, Digital Signal Compression: Principles and Practice . Cambridge University Press, 2011
2011
Cited alongside, same era.
K. Sayood, Introduction to Data Compression , 4th ed. Morgan Kaufmann, 2012
2012
Cited alongside, same era.
M. Li, J. Klejsa, A. Ozerov, and W. B. Kleijn, “Audio coding with power spectral density preserving quantization,” in IEEE Conf. Acoust., Speech, and Sig. Proc. , 2012, pp. 413–416
2012
Cited alongside, same era.
P. Cuff, “Distributed channel synthesis,” IEEE Trans. Inf. Theory , vol. 59, no. 11, pp. 7071–7096, 2013
2013
Cited alongside, same era.
M. Arjovsky, S. Chintala, and L. Bottou, “Wasserstein generative adversarial networks,” in Proc. Intl. Conf. Mach. Learn. (ICML) , vol. 70, 2017, pp. 214–223
2017
Cited alongside, same era.
Y. Blau and T. Michaeli, “The perception-distortion tradeoff,” in Proc. IEEE Conf. Comp. Vision and Pattern Recog. (CVPR) , 2018, pp. 6288–6237
2018
Later among the works it cites.
E. Agustsson, M. Tschannen, F. Mentzer, R. Timofte, and L. Van Gool, “Generative adversarial networks for extreme learned image compression,” in Proc. IEEE Conf. Comp. Vision , 2019, pp. 221–231
2019
Later among the works it cites.
Y. Blau and T. Michaeli, “Rethinking lossy compression: The rate-distortion-perception tradeoff,” in Proc. Intl. Conf. Mach. Learn. (ICML) , vol. 97, 2019
2019
Later among the works it cites.
——, “Rate-distortion-perception tradeoff of variable-length source coding for general information sources,” IEICE Comm. Express , vol. 8, no. 2, pp. 38–42, 2019
2019
Later among the works it cites.
L. Theis and A. B. Wagner, “A coding theorem for the rate-distortion-perception function,” in Neural Compression: From Information Theory to Applications – Workshop @ ICLR 2021 , 2021
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I. Gulrajani, F. Ahmed, M. Arjovsky, V. Dumoulin, and A. Courville, “Improved training of Wasserstein GANs,” in Proc. Adv. Neural Inf. Proc. Sys. (NeurIPS) , 2017
2017
Cited alongside, same era.
O. Rippel and L. Bourdev, “Real-time adaptive image compression,” in Proc. Intl. Conf. Mach. Learn. (ICML) , 2017, pp. 2922–2930
2017
Cited alongside, same era.
M. Tschannen, E. Agustsson, and M. Lucic, “Deep generative models for distribution-preserving lossy compression,” in Proc. Adv. Neural Inf. Proc. Sys. (NeurIPS) , 2018
2018
Cited alongside, same era.
R. Matsumoto, “Introducing the perception-distortion tradeoff into the rate-distortion theory of general information sources,” IEICE Comm. Express , vol. 7, no. 11, pp. 427–431, 2018
2018
Cited alongside, same era.
I. J. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” in Proc. Adv. Neural Inf. Proc. Sys. (NeurIPS)
Cited in the paper.
Cited in the paper.
2021
Later among the works it cites.
A. B. Wagner and J. Ballé, “Neural networks optimally compress the sawbridge,” in Proc. Data Comp. Conf. (DCC) , 2021, pp. 143–152
2021
Later among the works it cites.
L. Theis and E. Agustsson, “On the advantages of stochastic encoders,” in Neural Compression: From Information Theory to Applications – Workshop @ ICLR 2021 , 2021
2021
Later among the works it cites.
G. Zhang, J. Qian, J. Chen, and A. Khisti, “Universal rate-distortion-perception representations for lossy compression,” in Proc. Adv. Neural Inf. Proc. Sys. (NeurIPS) , 2021
2021
Later among the works it cites.
A. B. Wagner, “The rate-distortion-perception tradeoff: Perfect realism with randomized codes,” in Proc. IEEE Int. Symp. Inf. Theory (ISIT) , 2022, submitted. [Online]. Available: arXiv
2022
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