MNN: Mixed nearest-neighbors for self-supervised learning

Author:

Long Xianzhong,Peng ChenORCID,Li YunORCID

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Reference40 articles.

1. T. Chen, S. Kornblith, M. Norouzi, G. Hinton, A simple framework for contrastive learning of visual representations, in: International Conference on Machine Learning, 2020, pp. 1597–1607.

2. K. He, H. Fan, Y. Wu, S. Xie, R. Girshick, Momentum contrast for unsupervised visual representation learning, in: IEEE Conference on Computer Vision and Pattern Recognition, 2020, pp. 9729–9738.

3. R. Zhang, P. Isola, A.A. Efros, Colorful image colorization, in: European Conference on Computer Vision, 2016, pp. 649–666.

4. C. Doersch, A. Gupta, A.A. Efros, Unsupervised visual representation learning by context prediction, in: International Conference on Computer Vision, 2015, pp. 1422–1430.

5. J.D.M.-W.C. Kenton, L.K. Toutanova, Bert: Pre-training of deep bidirectional transformers for language understanding, in: Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019, pp. 4171–4186.

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