{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/computer-vision-based-food-calorie-estimation","title":"Computer vision-based food calorie estimation: dataset, method, and experiment","arxiv_id":"1705.07632","date":"2017-05-22","proceeding":null,"authors":["Yanchao Liang","Jianhua Li"],"abstract":"Computer vision has been introduced to estimate calories from food images.\nBut current food image data sets don't contain volume and mass records of\nfoods, which leads to an incomplete calorie estimation. In this paper, we\npresent a novel food image data set with volume and mass records of foods, and\na deep learning method for food detection, to make a complete calorie\nestimation. Our data set includes 2978 images, and every image contains\ncorresponding each food's annotation, volume and mass records, as well as a\ncertain calibration reference. To estimate calorie of food in the proposed data\nset, a deep learning method using Faster R-CNN first is put forward to detect\nthe food. And the experiment results show our method is effective to estimate\ncalories and our data set contains adequate information for calorie estimation.\nOur data set is the first released food image data set which can be used to\nevaluate computer vision-based calorie estimation methods.","url_abs":"http://arxiv.org/abs/1705.07632v3","url_pdf":"http://arxiv.org/pdf/1705.07632v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"computer-vision-based-food-calorie-estimation","repo_url":"https://github.com/Liang-yc/ECUSTFD-resized-","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"unanswered"}},{"paper_slug":"computer-vision-based-food-calorie-estimation","repo_url":"https://github.com/Yiming-Miao/Calorie-Predictor","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[],"methods":[{"method_slug":"convolution","method_name":"Convolution"},{"method_slug":"faster-r-cnn","method_name":"Faster R-CNN"},{"method_slug":"rpn","method_name":"RPN"},{"method_slug":"roipool","method_name":"RoIPool"},{"method_slug":"softmax","method_name":"Softmax"}],"datasets_introduced":[{"slug":"ecustfd","name":"ECUSTFD","full_name":"ECUST Food Dataset"}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1705.07632","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}