Dunhuang Grottoes Painting Dataset

by Tianxiu Yu,Shijie Zhang,Cong Lin,Shaodi You,Jian Wu,Jiawan Zhang,Xiaohong Ding,Huili AnResearch Only

Dunhuang Grottoes Painting Dataset

In 1970s, the Dunhuang Academy is established to systematically preserve the heritage. From the study, half of them suffer from corrosion and aging. Because the paintings are created by different artists from 10 centuries, it is non-trivial for manual restoration. And therefore, we release the first Dunhuang Challenge with 600 paintings, which enables an open and public attention in the research community on data driven e-heritage restoration. This year, the academy is proposing to collaborate with Microsoft Research and other researchers over the world, aiming to solve the automatic restoration of the wall painting using computer vision and machine learning technology. The Mogao Grottoes, a world cultural heritage, meets all the six United Nations world heritage standards. Over 1,000 years’ continuous construction and expansion that started in AD 366 led to a treasure trove of architecture, more than 45,000 square meters’ murals and 2,000-plus painted sculptures. The murals are of great value for historical, artistic and technological research with the earliest ones dating back to over 1,600 years ago. In recent years, the Academy starts to preserve it digitally. Manually restoring the painting is not trivial, because the painting is created by thousands and thousands of artists over 10 centuries. holistically master the style is impractical. Cave 7 of the Mogao Grottoes was excavated in the Mid-Tang Dynasty (AD 766-835), the murals on the north and south walls feature a range of rich content, such as Buddha statues, bodhisattvas, sponsors, architecture, dance, music, and decorative patterns. Based on the digitization of the south and north walls’ murals of Cave 7 of the Mogao Grottoes, 600 images, with resolutions between 500-800 pixels, from different murals were selected for the data set in line with the principle of image content integrity. Out of these 600 images, 500 are stored in the “train” folder as the training data set while the remaining 100 in the “test” folder as the test data set.

Dataset Attributes

Label SVG
TasksE-Heritage Restoration
Label SVG
CategoriesBuddha, Temple, China, Painting, Art, Restoration, Religious
Label SVG
SensorRGB Camera