# Computer vision-based food calorie estimation: dataset, method, and experiment

arXiv: https://arxiv.org/abs/1705.07632 · HTML: https://mlsanity.com/paper/1705.07632/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 May 2017.

## Built on by (most cited first, 8 of 8)

- [Nutrition5k: Towards Automatic Nutritional Understanding of Generic Food](https://mlsanity.com/paper/2103.03375/) (2021)
- [NutriBench: A Dataset for Evaluating Large Language Models on Nutrition Estimation from Meal Descriptions](https://mlsanity.com/paper/2407.12843/) (2024)
- [DPF-Nutrition: Food Nutrition Estimation via Depth Prediction and Fusion](https://mlsanity.com/paper/2310.11702/) (2023)
- [A Comprehensive Survey of Image-Based Food Recognition and Volume Estimation Methods for Dietary Assessment](https://mlsanity.com/paper/2106.11776/) (2021)
- [NutritionVerse: Empirical Study of Various Dietary Intake Estimation Approaches](https://mlsanity.com/paper/2309.07704/) (2023)
- [NutritionVerse-Direct: Exploring Deep Neural Networks for Multitask Nutrition Prediction from Food Images](https://mlsanity.com/paper/2405.07814/) (2024)
- [Leveraging Human Salience to Improve Calorie Estimation](https://mlsanity.com/paper/2306.09527/) (2023)
- [Open-KNEAD: Knowledge-grounded Nutrition Estimation via Agentic Decomposition](https://mlsanity.com/paper/2607.12911/) (2026)

## Abstract (arXiv)

Computer vision has been introduced to estimate calories from food images. But current food image data sets don't contain volume and mass records of foods, which leads to an incomplete calorie estimation. In this paper, we present a novel food image data set with volume and mass records of foods, and a deep learning method for food detection, to make a complete calorie estimation. Our data set includes 2978 images, and every image contains corresponding each food's annotation, volume and mass records, as well as a certain calibration reference. To estimate calorie of food in the proposed data set, a deep learning method using Faster R-CNN first is put forward to detect the food. And the experiment results show our method is effective to estimate calories and our data set contains adequate information for calorie estimation. Our data set is the first released food image data set which can be used to evaluate computer vision-based calorie estimation methods.