submit data.zip

Semantic segmentation is a hot area in computer vision (CV) research. The integration of computer vision and the film and television industry has put forward higher requirements for media data. At present, the analysis of film clips integrating high dynamics and continuous frames is one of the hot spots of video semantic segmentation. High-precision, high-volume data is the basis for proposing and improving deep learning models. However, the content labels of existing datasets are disorderly, which is difficult to uniformly evaluate and review, and the label category subjects are blurred, which directly affects the effectiveness of the model. Chinese martial arts films are a genre of films with Chinese national characteristics and the epitome of traditional Chinese culture. The "theme props" in martial arts films not only show various weapons in ancient China, but also integrate the values of "chivalry" and "righteousness" in traditional Chinese culture, becoming an indispensable part of martial arts movies. This study creatively performs artificial semantic segmentation of props in Chinese martial arts films, and establishes prop segmentation rules and general review standards. It includes frame pictures of movie clips at 4 frames per second, improved semi-automatic annotation of 6 props (weapons), and a visual version of pixel (mask) markers. As far as we know, this dataset is the largest semantic segmentation dataset on Chinese movie props to date. This dataset can be used for traditional inspection tasks in computer vision as well as related research on interdisciplinary and interdisciplinary techniques.