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

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Thanh-Toan Do, Toan Tran, Ian D. Reid 0001, B. G. Vijay Kumar, Tuan Hoang, Gustavo Carneiro. A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning. In IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2019, Long Beach, CA, USA, June 16-20, 2019. pages 10404-10413, Computer Vision Foundation / IEEE, 2019. [doi]

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