Beyond Learned Metadata-Based Raw Image Reconstruction

Author:

Wang Yufei,Yu Yi,Yang Wenhan,Guo Lanqing,Chau Lap-Pui,Kot Alex C.,Wen BihanORCID

Funder

Ng Teng Fong Charitable Foundation

Key Project of Frontier Science Research of Chinese Academy of Sciences

Major Key Project of PCL

MOE AcRF Tier 1

Start-Up Grant

Publisher

Springer Science and Business Media LLC

Reference48 articles.

1. Abdelhamed, A., Brubaker, MA., & Brown, MS. (2019) Noise flow: Noise modeling with conditional normalizing flows. In Proceedings of the IEEE/CVF international conference on computer vision. pp 3165–3173.

2. Agustsson, E., Mentzer, F., Tschannen, M., Cavigelli, L., Timofte, R., Benini, L., & Gool, L. V. (2017). Soft-to-hard vector quantization for end-to-end learning compressible representations. Advances in neural information processing systems. 30.

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

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

5. Bychkovsky, V., Paris, S., Chan, E., & Durand, F. (2011) Learning photographic global tonal adjustment with a database of input / output image pairs. In The twenty-fourth IEEE conference on computer vision and pattern recognition.

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