Implementing Siamese networks with a contrastive loss for similarity learning
Implementation for the CVPR2019 paper "Graphical Contrastive Losses for Scene Graph Generation"
Experiments with supervised contrastive learning methods with different loss functions
Mean-Shifted Contrastive Loss for Anomaly Detection (AAAI 2023)
PyTorch implementation of Center Loss & Contrastive-Center Loss.
Independent implementation of Supervised Contrastive Loss. Straight to the point and beyond
An implementation of Contrastive Loss in PyTorch using Siamese Networks
Learning to detect fake face images in the wild. We use a deep fully convolutional network based on Siamese network and contrastive loss.
Contrastive PCA
ATL(Angular Triplet Loss):A new loss function based on sphereface & triplet loss
Implementation of some unbalanced loss like focal_loss, dice_loss, DSC Loss, GHM Loss et.al
MS-Loss: Multi-Similarity Loss for Deep Metric Learning
Implementation of SCARF: Self-Supervised Contrastive Learning using Random Feature Corruption in Pytorch, a model learning a representation of tabular data using contrastive learning. It is inspired f...
PyTorch Implementation of Focal Loss and Lovasz-Softmax Loss
PyTorch implementation of Contrastive Learning methods
翻译 - 对比学习方法的PyTorch实施
label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful
PyTorch code for softmax variants: center loss, cosface loss, large-margin gaussian mixture, COCOLoss, ring loss
Equipment Loss Tracking
The Contextual Loss
pytorch structural similarity (SSIM) loss
stable diffusion webui with contrastive prompt tuning
The brief implementation and using examples of object detection usages like, IoU, NMS, soft-NMS, SmoothL1、IoU loss、GIoU loss、 DIoU loss、CIoU loss, cross-entropy、focal-loss、GHM, AP/MAP and so on by Pyt...
Pytorch implementation of Center Loss