113 citations · 229 across the 13 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.CV2021★ 1 cited
Parametric Contrastive Learning
Jiequan Cui, Zhisheng Zhong, Shu Liu +2
In this paper, we propose Parametric Contrastive Learning (PaCo) to tackle long-tailed recognition. Based on theoretical analysis, we observe supervised contrastive loss tends to b…
cs.CV2021★ 9 cited
Improving Calibration for Long-Tailed Recognition
Zhisheng Zhong, Jiequan Cui, Shu Liu +1
Deep neural networks may perform poorly when training datasets are heavily class-imbalanced. Recently, two-stage methods decouple representation learning and classifier learning to…
cs.CV2021★ 13 cited
ResLT: Residual Learning for Long-tailed Recognition
Jiequan Cui, Shu Liu, Zhuotao Tian +2
Deep learning algorithms face great challenges with long-tailed data distribution which, however, is quite a common case in real-world scenarios. Previous methods tackle the proble…