Nutrition5k is a dataset of visual and nutritional data for ~5k realistic plates of food captured from Google cafeterias using a custom scanning rig. We are releasing this dataset alongside our recent CVPR 2021 paper to help promote research in visual nutrition understanding. Please see the paper for more details on the dataset and follow-up experiments.

Manually Segmented Labels Based on the Nutrition5k Dataset

The dataset comprises 31 dishes from Nutrition5k with 1356 annotated frames and 11 dishes from V&F with 2308 annotated frames, totaling 42 dishes with 3664 annotated frames. This curated dataset of masks from Nutrition5K and V& F, which we call FoodMask, forms a robust foundation for rigorous testing and validation of our segmentation framework, facilitating accurate assessment across diverse culinary compositions.