Clothing-1M

The 'Clothing1M' dataset is a large-scale benchmark containing 1 million clothing images with noisy labels, used to evaluate the robustness of models in the presence of label noise in federated learning.

Papers using Clothing-1M (2)

FedCova: Robust Federated Covariance Learning Against Noisy Labels2026Towards Federated Learning against Noisy Labels via Local Self-Regularization2022