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Improving Tail-Class Representation with Centroid Contrastive Learning
[article]
2021
arXiv
pre-print
In vision domain, large-scale natural datasets typically exhibit long-tailed distribution which has large class imbalance between head and tail classes. This distribution poses difficulty in learning good representations for tail classes. Recent developments have shown good long-tailed model can be learnt by decoupling the training into representation learning and classifier balancing. However, these works pay insufficient consideration on the long-tailed effect on representation learning. In
arXiv:2110.10048v1
fatcat:p3iroctzs5hflfu3zbob6mnwyy