1. Arefin, M.R., Michalski, V., St-Charles, P.-L., Kalaitzis, A., Kim, S., Kahou, S.E., Bengio, Y.: Multi-image super-resolution for remote sensing using deep recurrent networks. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, pp. 206–207 (2020)
2. Vavilala, V., Meyer, M.: Deep learned super resolution for feature film production. In: Special Interest Group on Computer Graphics and Interactive Techniques Conference Talks, pp. 1–2 (2020)
3. Fang, H., Deng, W., Zhong, Y., Hu, J.: Generate to adapt: Resolution adaption network for surveillance face recognition. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XV 16, pp. 741–758 (2020). Springer
4. Zhang, Y., Li, K., Li, K., Fu, Y.: Mr image super-resolution with squeeze and excitation reasoning attention network. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 13425–13434 (2021)
5. Gavade, A., Sane, P.: Super resolution image reconstruction by using bicubic interpolation. In: National Conference on Advanced Technologies in Electrical and Electronic Systems, vol. 10 (2014)