Datasets › Clothing1M

Clothing1M

Introduced by Tong Xiao et al. in Learning From Massive Noisy Labeled Data for Image Classification1 Jan 2015 archive 2025-07-28

Clothing1M contains 1M clothing images in 14 classes. It is a dataset with noisy labels, since the data is collected from several online shopping websites and include many mislabelled samples. This dataset also contains 50k, 14k, and 10k images with clean labels for training, validation, and testing, respectively.

Source: Label-Noise Robust Generative Adversarial Networks Image Source: https://openaccess.thecvf.com/content_cvpr_2015/papers/Xiao_Learning_From_Massive_2015_CVPR_paper.pdf

Homepage Benchmarks Papers JSON

Benchmarks archive 2025-07-28

All 4 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.

		First row (archive order)	Paper	Code
Image Classification	Clothing1M	LRA-diffusion (CC) Accuracy 75.7%	Label-Retrieval-Augmented Diffusion Models for Learning...	puar-playground/lra-diffusion	51	Compare
Image Classification	Clothing1M (using clean data)	CurriculumNet Accuracy 81.5%	CurriculumNet: Weakly Supervised Learning from...	MalongTech/CurriculumNet +1	9	Compare
Learning with noisy labels	Clothing1M	Knockoffs-SPR Test Accuracy 75.20	Knockoffs-SPR: Clean Sample Selection in Learning with...	yikai-wang/knockoffs-spr	5	Compare
Learning with noisy labels	Clothing1M (using clean data)	ResNet50 1:1 Accuracy 74.98	UNICON: Combating Label Noise Through Uniform Selection...	nazmul-karim170/unicon-noisy-label	1	Compare

Papers archive 2025-07-28

30 shown of 60 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 288. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

			Date	Samples run Syntology
SST: Self-training with Self-adaptive Thresholding for Semi-supervised Learning	0	1	31 May 2025	not harvested
CLIPCleaner: Cleaning Noisy Labels with CLIP	1	1	19 Aug 2024	not harvested
Cross-to-merge training with class balance strategy for learning with noisy labels	1	2	1 Apr 2024	not harvested
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels	1	1	31 May 2023	ran 7 of 9 samples (2 unverified)
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations	1	1	22 May 2023	not harvested
Enhanced Meta Label Correction for Coping with Label Corruption	1	1	22 May 2023	not harvested
Learning with Noisy labels via Self-supervised Adversarial Noisy Masking	1	1	14 Feb 2023	ran 0 of 1 samples (1 unverified; 1 pointer-only for licence)
Learning from Noisy Labels with Decoupled Meta Label Purifier	1	1	14 Feb 2023	not harvested
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels	1	2	2 Jan 2023	not harvested
Class Prototype-based Cleaner for Label Noise Learning	1	1	21 Dec 2022	not harvested
Learning advisor networks for noisy image classification	1	1	8 Nov 2022	not harvested
Instance-Dependent Noisy Label Learning via Graphical Modelling	1	1	2 Sep 2022	not harvested
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels	1	1	29 Jul 2022	ran 4 of 9 samples (5 unverified)
Jigsaw-ViT: Learning Jigsaw Puzzles in Vision Transformer	1	1	25 Jul 2022	not harvested
Compressing Features for Learning with Noisy Labels	1	1	27 Jun 2022	not harvested
UNICON: Combating Label Noise Through Uniform Selection and Contrastive Learning	1	1	28 Mar 2022	ran 7 of 15 samples (8 unverified)
Scalable Penalized Regression for Noise Detection in Learning with Noisy Labels	1	2	15 Mar 2022	ran 1 of 3 samples (2 unverified; 3 pointer-only for licence)
L2B: Learning to Bootstrap Robust Models for Combating Label Noise	1	1	9 Feb 2022	not harvested
Sample Prior Guided Robust Model Learning to Suppress Noisy Labels	1	1	2 Dec 2021	not harvested
Learning with Noisy Labels by Efficient Transition Matrix Estimation to Combat Label Miscorrection	1	1	29 Nov 2021	not harvested
SSR: An Efficient and Robust Framework for Learning with Unknown Label Noise	1	1	22 Nov 2021	not harvested
Adaptive Sample Selection for Robust Learning under Label Noise	1	2	29 Jun 2021	ran 2 of 3 samples (1 unverified; 3 pointer-only for licence)
To Smooth or Not? When Label Smoothing Meets Noisy Labels	1	1	8 Jun 2021	ran 3 of 3 samples (0 unverified; 3 pointer-only for licence)
Training Classifiers that are Universally Robust to All Label Noise Levels	1	1	27 May 2021	not harvested
Boosting Co-teaching with Compression Regularization for Label Noise	1	1	28 Apr 2021	ran 2 of 14 samples (12 unverified)
Contrastive Learning Improves Model Robustness Under Label Noise	1	3	19 Apr 2021	ran 1 of 13 samples (12 unverified)
Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels	1	1	25 Mar 2021	ran 6 of 7 samples (1 unverified)
LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment	1	1	6 Mar 2021	not harvested
Augmentation Strategies for Learning with Noisy Labels	1	1	3 Mar 2021	not harvested
FINE Samples for Learning with Noisy Labels	1	1	23 Feb 2021	ran 5 of 7 samples (2 unverified; 7 pointer-only for licence)

The full list of 60 is in the JSON twin.

Dataset loaders archive 2025-07-28

Cysu/noisy_label

1 loader as listed in the archive; links are outbound and not re-checked here.

Tasks archive 2025-07-28

Image Classification Learning with noisy labels

License archive 2025-07-28

Unknown

Modalities archive 2025-07-28

Images

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

Clothing1M
Clothing1M (using clean data)

2 variant names, as the archive lists them.

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