1. Lu, R., Gao, F., Yang, X., Fan, J., Li, D.: A novel infrared and visible image fusion method based on multi-level saliency integration. Vis. Comput. 1, 1–15 (2022)
2. Wang, X., Hua, Z., Li, J.: Cross-UNet: dual-branch infrared and visible image fusion framework based on cross-convolution and attention mechanism. Vis. Comput. 1, 1–18 (2022)
3. Liu, J., Jiang, Z., Wu, G., Liu, R., Fan, X.: A unified image fusion framework with flexible bilevel paradigm integration. Vis. Comput. 1, 1–18 (2022)
4. Ma, J., Ma, Y., Li, C.: Infrared and visible image fusion methods and applications: a survey. Inf. Fusion. 45, 153–178 (2019). https://doi.org/10.1016/j.inffus.2018.02.004
5. Zhang, X., Ye, P., Xiao, G.: VIFB: A visible and infrared image fusion benchmark. In: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR Workshops 2020, Seattle, WA, USA, June 14–19, 2020. pp. 468–478. Computer Vision Foundation/IEEE (2020)