A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning



Do, Thanh-Toan ORCID: 0000-0002-6249-0848, Tran, Toan, Reid, Ian, Kumar, Vijay, Hoang, Tuan and Carneiro, Gustavo
(2019) A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning. In: 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019-06-15 - 2019-06-20.

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Item Type: Conference or Workshop Item (Unspecified)
Depositing User: Symplectic Admin
Date Deposited: 07 Jun 2019 10:17
Last Modified: 24 Nov 2021 14:10
DOI: 10.1109/cvpr.2019.01065
Open Access URL: https://arxiv.org/abs/1904.08720
URI: https://livrepository.liverpool.ac.uk/id/eprint/3042551