{"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/chinesefoodnet-a-large-scale-image-dataset","title":"ChineseFoodNet: A large-scale Image Dataset for Chinese Food Recognition","arxiv_id":"1705.02743","date":"2017-05-08","proceeding":null,"authors":["Xin Chen","Yu Zhu","Hua Zhou","Liang Diao","Dongyan Wang"],"abstract":"In this paper, we introduce a new and challenging large-scale food image\ndataset called \"ChineseFoodNet\", which aims to automatically recognizing\npictured Chinese dishes. Most of the existing food image datasets collected\nfood images either from recipe pictures or selfie. In our dataset, images of\neach food category of our dataset consists of not only web recipe and menu\npictures but photos taken from real dishes, recipe and menu as well.\nChineseFoodNet contains over 180,000 food photos of 208 categories, with each\ncategory covering a large variations in presentations of same Chinese food. We\npresent our efforts to build this large-scale image dataset, including food\ncategory selection, data collection, and data clean and label, in particular\nhow to use machine learning methods to reduce manual labeling work that is an\nexpensive process. We share a detailed benchmark of several state-of-the-art\ndeep convolutional neural networks (CNNs) on ChineseFoodNet. We further propose\na novel two-step data fusion approach referred as \"TastyNet\", which combines\nprediction results from different CNNs with voting method. Our proposed\napproach achieves top-1 accuracies of 81.43% on the validation set and 81.55%\non the test set, respectively. The latest dataset is public available for\nresearch and can be achieved at https://sites.google.com/view/chinesefoodnet.","url_abs":"http://arxiv.org/abs/1705.02743v3","url_pdf":"http://arxiv.org/pdf/1705.02743v3.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":"chinesefoodnet-a-large-scale-image-dataset","repo_url":"https://github.com/powerli2002/ChineseFoodNet-Resnet50","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"food-recognition","task_name":"Food Recognition"}],"methods":[],"datasets_introduced":[{"slug":"chinesefoodnet","name":"ChineseFoodNet","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1705.02743","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}