1. [1] M. Li, W. Zuo, S. Gu, D. Zhao, and D. Zhang, “Learning convolutional networks for content-weighted image compression,” Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.3214-3223, 2018. 10.1109/CVPR.2018.00339
2. [2] J. Ballé, V. Laparra, and E.P. Simoncelli, “End-to-end optimized image compression,” arXiv preprint arXiv:1611.01704, 2016. 10.48550/arXiv.1611.01704
3. [3] J. Ballé, D. Minnen, S. Singh, S.J. Hwang, and N. Johnston, “Variational image compression with a scale hyperprior,” International Conference on Learning Representations, 2018.
4. [4] D. Minnen, J. Ballé, and G.D. Toderici, “Joint autoregressive and hierarchical priors for learned image compression,” Advances in Neural Information Processing Systems, 2018.
5. [5] F. Mentzer, E. Agustsson, M. Tschannen, R. Timofte, and L. Van Gool, “Conditional probability models for deep image compression,” Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.4394-4402, 2018. 10.1109/CVPR.2018.00462