Datasets › Food-101N

Food-101N

archive 2025-07-28

The Food-101N dataset is introduced in "CleanNet: Transfer Learning for Scalable Image Training with Label Noise (CVPR'18). It is an image dataset containing about 310,009 images of food recipes classified in 101 classes (categories). Food-101N and the Food-101 dataset share the same 101 classes, whereas Food-101N has much more images and is more noisy.

Food-101N is designed for the following two tasks: 1)Learning image classification with label noise 2)Label noise detection

Benchmarks archive 2025-07-28

All 1 leaderboard 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)PaperCode
Image Classification Food-101N LRA-diffusion (CLIP ViT) Accuracy 93.42 Label-Retrieval-Augmented Diffusion Models for Learning... puar-playground/lra-diffusion 4 Compare

Papers archive 2025-07-28

4 shown of 4 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 6. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.

DateSamples run Syntology
SURE: SUrvey REcipes for building reliable and robust deep networks 1 1 1 Mar 2024 ran 5 of 6 samples (1 unverified; 6 pointer-only for licence)
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels 1 1 31 May 2023 ran 7 of 9 samples (2 unverified)
LongReMix: Robust Learning with High Confidence Samples in a Noisy Label Environment 1 1 6 Mar 2021 not harvested
CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise 3 1 20 Nov 2017 not harvested

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

No licence recorded in the archive. Absence here is not a statement about the dataset's terms.

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

No variants listed.

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