Author:
Guo Yao,Wu Yongliang,Wan Changsheng
Publisher
Springer Nature Singapore
Reference36 articles.
1. Ancuti, C.O., Ancuti, C., Sbert, M., Timofte, R.: Dense-haze: a benchmark for image dehazing with dense-haze and haze-free images. In: 2019 IEEE International Conference on Image Processing (ICIP), pp. 1014–1018. IEEE (2019)
2. Ancuti, C.O., Ancuti, C., Timofte, R., De Vleeschouwer, C.: O-HAZE: a dehazing benchmark with real hazy and haze-free outdoor images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 754–762 (2018)
3. Cai, B., Xu, X., Jia, K., Qing, C., Tao, D.: DehazeNet: an end-to-end system for single image haze removal. IEEE Trans. Image Process. 25(11), 5187–5198 (2016)
4. Chen, D., et al.: Gated context aggregation network for image dehazing and deraining. In: 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), pp. 1375–1383. IEEE (2019)
5. Dhariwal, P., Nichol, A.: Diffusion models beat GANs on image synthesis. In: Advances in Neural Information Processing Systems, vol. 34, pp. 8780–8794 (2021)