Supervised Deep Similarity Training (Siamese)

Has anyone worked on deep supervised similarity learning (likes of Siamese for larger datasets of order 30,000 images in total)? The one-shot accuracy we get is too low. Apart from Contrastive and Triplet losses, have you tried any other loss functions? Is there a way to select a good loss margin?