Few-Shot Classification with Semantic Augmented Activators

Author:

Gao Ruixuan,Su Han,Tang Peisen

Publisher

Springer Nature Singapore

Reference32 articles.

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

2. Chen, W.Y., Liu, Y.C., Kira, Z., Wang, Y.C.F., Huang, J.B.: A closer look at few-shot classification. arXiv preprint arXiv:1904.04232 (2019)

3. Chen, Y., Wang, X., Liu, Z., Xu, H., Darrell, T.: A new meta-baseline for few-shot learning. arXiv preprint arXiv:2003.04390 (2020)

4. Das, R., Wang, Y.X., Moura, J.M.: On the importance of distractors for few-shot classification. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 9030–9040 (2021)

5. Doersch, C., Gupta, A., Zisserman, A.: CrossTransformers: spatially-aware few-shot transfer. In: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M., Lin, H. (eds.) Advances in Neural Information Processing Systems, vol. 33, pp. 21981–21993. Curran Associates, Inc. (2020). https://proceedings.neurips.cc/paper/2020/file/fa28c6cdf8dd6f41a657c3d7caa5c709-Paper.pdf

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