Addressing Long-Tail Noisy Label Learning Problems: a Two-Stage Solution
with Label Refurbishment Considering Label Rarity
Addressing Long-Tail Noisy Label Learning Problems: a Two-Stage Solution
with Label Refurbishment Considering Label Rarity
Real-world datasets commonly exhibit noisy labels and class imbalance, such as long-tailed distributions. While previous research addresses this issue by differentiating noisy and clean samples, reliance on information from predictions based on noisy long-tailed data introduces potential errors. To overcome the limitations of prior works, we introduce an effective two-stage …