[17] Yonghua Zhang, Jiawan Zhang, and Xiaojie Guo. Kindling the darkness: A practical low-light image enhancer. In Proceedings of the ACM International Conference on Multimedia, pages 1632-1640, 2019.
[18] Yonghua Zhang, Xiaojie Guo, Jiayi Ma, Wei Liu, and Jiawan Zhang. Beyond brightening low-light images. International Journal of Computer Vision, 129(4):1013-1037, 2021.
[19] Chunle Guo, Chongyi Li, Jichang Guo, Chen Change Loy, Junhui Hou, Sam Kwong, and Runmin Cong. Zero-reference deep curve estimation for low-light image enhancement. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 1780-1789, 2020.
[20] Anqi Zhu, Lin Zhang, Ying Shen, Yong Ma, Shengjie Zhao, and Yicong Zhou. Zero-shot restoration of underexposed images via robust Retinex decomposition. In IEEE International Conference on Multimedia and Expo, pages 1-6, 2020.
[21] Ruixing Wang, Qing Zhang, Chi-Wing Fu, Xiaoyong Shen, Wei-Shi Zheng, and Jiaya Jia. Underexposed photo enhancement using deep illumination estimation. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 6849-6857, 2019.
[22] Naishan Zheng, Jie Huang, Qi Zhu, Man Zhou, Feng Zhao, and Zheng-Jun Zha. Enhancement by your aesthetic: An intelligible unsupervised personalized enhancer for low-light images. In Proceedings of the 30th ACM International Conference on Multimedia, pages 6521-6529, 2022.
[23] Naishan Zheng, Man Zhou, Yanmeng Dong, Xiangyu Rui, Jie Huang, Chongyi Li, and Feng Zhao. Empowering low-light image enhancer through customized learnable priors. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), pages 12559-12569, October 2023.
[24] Mahmoud Afifi, Konstantinos G Derpanis, Bjorn Ommer, and Michael S Brown. Learning multiscale photo exposure correction. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 9157-9167, 2021.
[25] Haoyuan Wang, Ke Xu, and Rynson W.H. Lau. Local color distributions prior for image enhancement. In Proceedings of the European Conference on Computer Vision (ECCV), 2022.
[26] Jie Huang, Yajing Liu, Feng Zhao, Keyu Yan, Jinghao Zhang, Yukun Huang, Man Zhou, and Zhiwei Xiong. Deep fourier-based exposure correction network with spatial frequency interaction. In Proceedings of the European Conference on Computer Vision (ECCV), 2022.
[27] Jie Huang, Feng Zhao, Man Zhou, Jie Xiao, Naishan Zheng, Kaiwen Zheng, and Zhiwei Xiong. Learning sample relationship for exposure correction. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pages 9904–9913, June 2023.
[28] Xiangyu Chen, Yihao Liu, Zhengwen Zhang, Yu Qiao, and Chao Dong. HDRUnet: Single image hdr reconstruction with denoising and dequantization. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 354-363, 2021.
[29] Xuan Dong, Xiaoyan Hu, Weixin Li, Xiaojie Wang, and Yunhong Wang. Miehrd cnn: Main image enhancement based ghost-free high dynamic range imaging using dual-lens systems. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 35, pages 1264-1272, 2021.
[30] Xiangyu Chen, Zhengwen Zhang, Jimmy S Ren, Lynhoo Tian, Yu Qiao, and Chao Dong. A new journey from sdrtv to hdrtv. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 4500-4509, 2021.
[31] Soo Ye Kim, Jihyong Oh, and Munchurl Kim. Deep sr-item: Joint learning of super-resolution and inverse tone-mapping for 4k uhd hdr applications. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 3116-3125, 2019.
[32] Jingwen He, Yihao Liu, Yu Qiao, and Chao Dong. Conditional sequential modulation for efficient global image retouching. In European Conference on Computer Vision, pages 679-695. Springer, 2020.