Clothing1M

Overview edit

Variants: Clothing1M, Clothing1M (using clean data)

Associated Benchmarks

This dataset is used in 1 benchmark:

• Image Classification - Metrics: Accuracy

Recent Benchmark Submissions

Research Papers

Recent papers with results on this dataset:

• SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning (2025) -
• Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels (2023) -
• Learning with Noisy labels via Self-supervised Adversarial Noisy Masking (2023) -
• Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels (2023) -
• Class Prototype-based Cleaner for Label Noise Learning (2022) -
• Learning advisor networks for noisy image classification (2022) -
• Instance-Dependent Noisy Label Learning via Graphical Modelling (2022) -
• Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels (2022) -
• Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer (2022) -
• Compressing Features for Learning with Noisy Labels (2022) -
• Scalable Penalized Regression for Noise Detection in Learning with Noisy Labels (2022) -
• Sample Prior Guided Robust Model Learning to Suppress Noisy Labels (2021) -
• SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise (2021) -
• Adaptive Sample Selection for Robust Learning under Label Noise (2021) -
• To Smooth or Not? When Label Smoothing Meets Noisy Labels (2021) -
• Boosting Co-teaching with Compression Regularization for Label Noise (2021) -
• Contrastive Learning Improves Model Robustness Under Label Noise (2021) -
• Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels (2021) -
• LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment (2021) -
• Augmentation Strategies for Learning with Noisy Labels (2021) -