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
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Image Classification | SURE(ResNet-50) | SURE: SUrvey REcipes for building … | 2024-03-01 |
| Image Classification | LRA-diffusion (CLIP ViT) | Label-Retrieval-Augmented Diffusion Models for Learning … | 2023-05-31 |
| Image Classification | LongReMix | LongReMix: Robust Learning with High … | 2021-03-06 |
| Image Classification | CleanNet | CleanNet: Transfer Learning for Scalable … | 2017-11-20 |
Recent papers with results on this dataset: