Hard Negative Examples are Hard, but Useful

Author:

Xuan HongORCID,Stylianou Abby,Liu Xiaotong,Pless Robert

Publisher

Springer International Publishing

Reference26 articles.

1. Faghri, F., Fleet, D.J., Kiros, J.R., Fidler, S.: Vse++: improving visual-semantic embeddings with hard negatives. In: Proceedings of the British Machine Vision Conference (BMVC) (2018)

2. Ge, J., Gao, G., Liu, Z.: Visual-textual association with hardest and semi-hard negative pairs mining for person search. arXiv preprint arXiv:1912.03083 (2019)

3. Lecture Notes in Computer Science;W Ge,2018

4. Goldberger, J., Hinton, G.E., Roweis, S.T., Salakhutdinov, R.R.: Neighbourhood components analysis. In: Saul, L.K., Weiss, Y., Bottou, L. (eds.) Advances in Neural Information Processing Systems, vol. 17, pp. 513–520. MIT Press (2005)

5. Harwood, B., Kumar, B., Carneiro, G., Reid, I., Drummond, T., et al.: Smart mining for deep metric learning. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2821–2829 (2017)

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