Contrastive loss (Chopra et al. 2005) is one of the earliest training objectives used for deep metric learning in a contrastive ... ... <看更多>

PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR ... The loss function SupConLoss in losses.py takes features (L2 normalized) and ... ... <看更多>

I am using the keras implementation given here for the purpose. This is the portion concerning the supervised contrastive loss. I am unsure as ... ... <看更多>

The main point of using a strategy like siamese loss or triplet loss is that you don't have to know all of your classes at training time ... ... <看更多>

In the first phase, the encoder is pretrained to optimize the supervised contrastive loss, described in Prannay Khosla et al. ... <看更多>