Single-image rain removal using deep residual network
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Signal Processing
Link
https://link.springer.com/content/pdf/10.1007/s11760-020-01803-3.pdf
Reference32 articles.
1. Shen, L., Yue, Z., Chen, Q., Feng, F., Ma, J.: Deep joint rain and haze removal from a single image. In: IEEE International Conference on Pattern Recognition, pp. 2821–2826 (2018)
2. Li, X., Wu, J., Lin, Z., Liu, H., Zha, H.: Recurrent squeeze-and-excitation context aggregation net for single image deraining. In: European Conference on Computer Vision, pp. 254–269 (2018)
3. Du, S., Liu, Y., Ye, M., Xu, Z., Li, J., Liu, J.: Single image deraining via decorrelating the rain streaks and background scene in gradient domain. Pattern Recognit. 79, 303–317 (2018)
4. Wang, X., Chen, J., Jiang, K., Han, Z., Ruan, W., Wang, Z., Liang, C.: Single image de-raining via clique recursive feedback mechanism. Neurocomputing 417, 142–154 (2020)
5. Yi, P., Wang, Z., Jiang, K., Shao, Z., Ma, J.: Multi-temporal ultra dense memory network for video super-resolution. IEEE Trans. Circuits Syst. Video Technol. 30(8), 2503–2516 (2020)
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