2023
Balanced Mixup Loss for Long-Tailed Visual Recognition
ICASSP 2023accepted
In the real world, the data collected naturally are often long-tailed, which inevitably leads to class-imbalanced prediction and performance degradation. As a simple and effective data augmentation method, Mixup has been proven to be beneficial for the tail class in recent long-tail learning studies…