Sanglee Park

SMCL: Saliency Masked Contrastive Learning for Long-Tailed Visual Recognition

Real-world data often follow a long-tailed distribution with a high imbalance in the number of samples between classes. The problem with training from imbalanced data is that some background features, common to all classes, can be unobserved in classes with scarce samples. As a result, this backgrou…