Dongba Painting Portrait Generation Dataset (DongbaPGD)

Collect high-definition scanned images of physical objects and related literature from the collection of Lijiang Museum. In response to the issue of overlapping characters and environments, this article uses manual annotation segmentation to extract character regions, and obtains a total of 93 high-quality, unobstructed portrait samples of Dongba paintings.

Experts familiar with Naxi Dongba culture write prompt words for each image, mainly describing key information such as actions, clothing, and colors. Finally, a Dongba painting portrait image text dataset that can be used for model training and evaluation is constructed.  This paper constructs a functional dataset for the suppression of human body structure artifacts and style constraints: (1) Dongba painting generated portrait artifact segmentation dataset.