Zhen Mao

Learning Label Shift Correction for Test-Agnostic Long-Tailed Recognition

Long-tail learning primarily focuses on mitigating the label distribution shift between long-tailed training data and uniformly distributed test data. However, in real-world applications, we often encounter a more intricate challenge where the test label distribution is agnostic. To address this pro…