DimSum50: A benchmark dataset of Chinese food

This paper provides an overview of the increasing attention given by the public and government to food health. It also reviews the progress made in the field of image classification over the past decade, with a specific focus on the current state of Chinese food datasets. The DimSum50 dataset is introduced as the first dataset that concentrates on diverse Chinese dim sum among all publicly available datasets. This dataset comprises 50 categories of the most popular dim sum foods, containing a total of 28,884 images. To ensure the accuracy and scalability of DimSum50, a three-step construction process was implemented, including category selection, data collection, and data cleaning. The unique properties of dim sum present challenges in constructing this dataset, as several categories exhibit similar characteristics. Benchmark experiments were conducted on the DimSum50 dataset, offering a horizontal comparison among several common and state-of-the-art models in both CNNs and transformers.