2 code implementations • CVPR 2021 • Jingru Tan, Xin Lu, Gang Zhang, Changqing Yin, Quanquan Li
To address the problem of imbalanced gradients, we introduce a new version of equalization loss, called equalization loss v2 (EQL v2), a novel gradient guided reweighing mechanism that re-balances the training process for each category independently and equally.
Ranked #12 on Instance Segmentation on LVIS v1.0 val
1 code implementation • CVPR 2020 • Jingru Tan, Changbao Wang, Buyu Li, Quanquan Li, Wanli Ouyang, Changqing Yin, Junjie Yan
Based on it, we propose a simple but effective loss, named equalization loss, to tackle the problem of long-tailed rare categories by simply ignoring those gradients for rare categories.
Ranked #17 on Long-tail Learning on CIFAR-10-LT (ρ=10)