GAN-Based Image Compression with Improved RDO Process

Author:

Xia Fanxin,Jin Jian,Meng Lili,Ding Feng,Zhang Huaxiang

Publisher

Springer Nature Switzerland

Reference28 articles.

1. Agustsson, E., Tschannen, M., Mentzer, F., Timofte, R., Van Gool, L.: Generative adversarial networks for extreme learned image compression. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 221–231 (2019)

2. Akutsu, H., Suzuki, A., Zhong, Z., Aizawa, K.: Ultra low bitrate learned image compression by selective detail decoding. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 118–119 (2020)

3. Ballé, J., Laparra, V., Simoncelli, E.P.: End-to-end optimized image compression. arXiv preprint arXiv:1611.01704 (2016)

4. Ballé, J., Minnen, D., Singh, S., Hwang, S.J., Johnston, N.: Variational image compression with a scale hyperprior. arXiv preprint arXiv:1802.01436 (2018)

5. Ballé, J., Laparra, V., Simoncelli, E.P.: Density modeling of images using a generalized normalization transformation. arXiv (2015)

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