Unified approach to learning from noisy labels using auxiliary clean labels.
problem Learning from noisy labels in real-world applications.
method Rotational-Decoupling Consistency Regularization (RDCR) framework integrating consistency-based methods and self-supervised rotation task.
result RDCR achieves comparable or superior performance than state-of-the-art methods under small noise, significantly outperforming existing methods under large noise.