Abstract: To inherit and protect the traditional blue calico patterns, it is necessary and challenging to protect blue calico in a digital manner. Due to the lack of blue calico pattern datasets with original manual characteristics, which limits the application of powerful deep learning technology on pattern recognition field like the recognition of Blue Calico patters, therefore a large-scale dataset called Blue-Calico pattern dataset is provided, which is the first publicly available benchmark for blue calico pattern recognition. This dataset contains about 50 216 blue calico patterns, covering 85 pattern classes, such as animals, plants, myths and legends. The construction of this dataset will concern the digital construction of blue calico, such as calico image retrieval and caption, and enable researchers to design and validate data-driven algorithms. On the basis of the new dataset, the experimental results of four state-of-the-art networks are provided as a baseline for future work.

Key words: intangible cultural heritage; , blue calico; , image recognition; , benchmark dataset; , deep learning