models/README.md

# References 📚



[1] Y. Wang, “[AAAI 2022 Oral] Low-Light Image Enhancement with Normalizing Flow.” Nov. 23, 2022. Accessed: Nov. 24, 2022. [Online]. Available: https://github.com/wyf0912/LLFlow
[2] L. Wang and K.-J. Yoon, “Deep Learning for HDR Imaging: State-of-the-Art and Future Trends.” arXiv, Nov. 07, 2021. Accessed: Nov. 24, 2022. [Online]. Available: http://arxiv.org/abs/2110.10394
[3] Y. WANG, “Neural Color Operators for Sequential Image Retouching (ECCV2022).” Nov. 10, 2022. Accessed: Nov. 24, 2022. [Online]. Available: https://github.com/amberwangyili/neurop
[4] jwhe, “Conditional Sequential Modulation for Efficient Global Image Retouching Paper Link.” Nov. 23, 2022. Accessed: Nov. 24, 2022. [Online]. Available: https://github.com/hejingwenhejingwen/CSRNet
[5] Why, “Local Color Distributions Prior for Image Enhancement [ECCV2022].” Nov. 21, 2022. Accessed: Nov. 23, 2022. [Online]. Available: https://github.com/onpix/LCDPNet
[6] “Towards Efficient and Scale-Robust Ultra-High-Definition Image Demoiréing.” CVMI Lab, Nov. 21, 2022. Accessed: Nov. 21, 2022. [Online]. Available: https://github.com/CVMI-Lab/UHDM
[7] Z. Wang, “Uformer: A General U-Shaped Transformer for Image Restoration (CVPR 2022).” Nov. 20, 2022. Accessed: Nov. 21, 2022. [Online]. Available: https://github.com/ZhendongWang6/Uformer
[8] B. Zheng, “Learnbale_Bandpass_Filter.” Nov. 21, 2022. Accessed: Nov. 21, 2022. [Online]. Available: https://github.com/zhenngbolun/Learnbale_Bandpass_Filter
[9] K. Team, “Keras documentation: Enhanced Deep Residual Networks for single-image super-resolution.” https://keras.io/examples/vision/edsr/ (accessed Nov. 21, 2022).
[10] B. Lim, S. Son, H. Kim, S. Nah, and K. M. Lee, “Enhanced Deep Residual Networks for Single Image Super-Resolution.” arXiv, Jul. 10, 2017. doi: 10.48550/arXiv.1707.02921.
[11] C. Dong, C. C. Loy, K. He, and X. Tang, “Image Super-Resolution Using Deep Convolutional Networks.” arXiv, Jul. 31, 2015. doi: 10.48550/arXiv.1501.00092.
[12] Z. Anvari and V. Athitsos, “A Survey on Deep learning based Document Image Enhancement.” arXiv, Jan. 03, 2022. doi: 10.48550/arXiv.2112.02719.