“…Previous methods [1,2,7,14,20,31,42] in LNL always focus on generic classification (e.g. CIFAR-10 & 100) and artificially construct random label noise [18,20,35,36] and dependent label noise [7,14,31,42,43] to evaluate the performance of their algorithms. In this work, we extend LNL to fine-grained classification, which is a rarely studied task.…”