1. contrastive loss

2. triplet loss

In triplet loss training, a triplet contains two images belonging to the same class, referred to as the anchor and positive samples, and a third image, from a different class, which is referred to as the negative sample. The triplet loss function is given as, [d(a,p)d(a,n)+m]+[d(a, p) - d(a, n) + m]+, where aa, pp and nn are anchor, positive, and negative samples, respectively. d(,)d(\cdot,\cdot) is the learned metric function and mm is a margin term which encourages the negative sample to be further from the anchor than the positive sample.

3. NormSoftmax loss

4. Sampling

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