[1] Wenming Yang, Xuechen Zhang, Yapeng Tian, Wei Wang, Jing-Hao Xue. Deep Learning for Single Image Super-Resolution: A Brief Review. arxiv, 2018. paper
[2]Saeed Anwar, Salman Khan, Nick Barnes. A Deep Journey into Super-resolution: A survey. arxiv, 2019.paper
[3]Wang, Z., Chen, J., & Hoi, S. C. (2019). Deep learning for image super-resolution: A survey. arXiv preprint arXiv:1902.06068.paper
[4]Hongying Liu and Zhubo Ruan and Peng Zhao and Fanhua Shang and Linlin Yang and Yuanyuan Liu. Video Super Resolution Based on Deep Learning: A comprehensive survey. arXiv preprint arXiv:2007.12928.paper
[5]Honggang Chen, Xiaohai He, Linbo Qing, Yuanyuan Wu, Chao Ren, and Ce Zhu. Real-World Single Image Super-Resolution:A Brief Review. arxiv, 2021. paper
[6]Anran Liu, Yihao Liu, Jinjin Gu, Yu Qiao, Chao Dong. Blind Image Super-Resolution: A Survey and Beyond. arxiv, 2021. paper
[7]Chunwei Tian, Xuanyu Zhang, Jerry Chun-Wen Lin, Wangmeng Zuo, Yanning Zhang. Generative Adversarial Networks for Image Super-Resolution: A Survey. arxiv, 2022. paper
[8]B. B. Moser, F. Raue, S. Frolov, S. Palacio, J. Hees and A. Dengel, "Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 8, pp. 9862-9882, Aug. 2023, doi: 10.1109/TPAMI.2023.3243794. paper
[9]Moser, Brian B. et al. “Diffusion Models, Image Super-Resolution And Everything: A Survey.” ArXiv abs/2401.00736 (2024): n. pag.paper