List of embedding losses

[hbredin]

• [ ] https://arxiv.org/pdf/1712.05015.pdf
• [ ] Exponential Discriminative Metric Embedding in Deep Learning
• [ ] A Discriminative Feature Learning Approach for Deep Face Recognition
• [ ] Ring loss: Convex Feature Normalization for Face Recognition
• [ ] Spoken Language Identification Using LSTM-Based Angular Proximity
• [ ] Focal Loss for Dense Object Detection
• [ ] Magnet Loss: Metric Learning with Adaptive Density Discrimination
• [ ] MTGAN: Speaker Verification through Multitasking Triplet Generative Adversarial Networks
• [ ] Sampling Matters in Deep Embedding Learning
• [ ] Angular Softmax Loss for End-to-end Speaker Verification
• [ ] Angular Softmax for Short-Duration Text-independent Speaker Verification
• [ ] Robust and Discriminative Speaker Embedding via Intra-Class Distance Variance Regularization
• [ ] NormFace: L2 Hypersphere Embedding for Face Verification
• [ ] Improved Large-margin Softmax Loss for Speaker Diarisation
• [ ] Powerful Speaker Embedding Training Framework by Adversarially Disentangled Identity Representation
• [ ] Divide and Conquer the Embedding Space for Metric Learning

Code

• https://github.com/cvqluu/Angular-Penalty-Softmax-Losses-Pytorch Angular penalty loss functions in Pytorch (ArcFace, SphereFace, Additive Margin, CosFace)

[hbredin]

A bunch of losses were added by @juanmc2005. WIP results are available in this paper: https://arxiv.org/abs/1911.01255