Guided Collaborative Training for Pixel-Wise Semi-Supervised Learning

Author:

Ke Zhanghan,Qiu Di,Li Kaican,Yan Qiong,Lau Rynson W. H.

Publisher

Springer International Publishing

Reference48 articles.

1. Abdelhamed, A., Lin, S., Brown, M.S.: A high-quality denoising dataset for smartphone cameras. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1692–1700 (2018)

2. Abdelhamed, A., Timofte, R., Brown, M.S.: Ntire 2019 challenge on real image denoising: methods and results. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (2019)

3. Anwar, S., Barnes, N.: Real image denoising with feature attention. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 3155–3164 (2019)

4. Athiwaratkun, B., Finzi, M., Izmailov, P., Wilson, A.G.: There are many consistent explanations of unlabeled data: why you should average. arXiv preprint arXiv:1806.05594 (2019)

5. Berthelot, D., et al.: Remixmatch: semi-supervised learning with distribution matching and augmentation anchoring. In: International Conference on Learning Representations (2020)

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