构建一个中国古代建筑的多式数据集,结合图像,注释和风格模型
Biao Li1,2, Jinyuan Feng3,4,5, Yunxi Yan1,2
1School of Business Administration, Faculty of Business Administration, Southwestern University of Finance and Economics, Chengdu, 611130, China.
Scientific data
|October 16, 2024
概括
本研究介绍了中国古代建筑的第一个多式联络数据集,解决了当前人工智能图像生成的局限性. 该数据集增强了人工智能.
科学领域:
- 计算机视觉和人工智能的人工智能
- 数字人文学科和文化遗产文化遗产
背景情况:
- 扩散模型在多式联网生成方面出色,但由于数据稀缺,在中国古代建筑等专业领域扎.
- 现有的数据集缺乏针对中国独特建筑特征的全面视觉和文本信息.
研究的目的:
- 开发一个广泛的多式联络数据集,用于中国古代建筑,跨越唐朝至元朝.
- 克服数据的局限性,提高AI生成和理解中国古代建筑图像的能力.
主要方法:
- 构建一个多式联络数据集,包括图像,视频和风格模型.
- 根据位置对视觉数据进行分类,并在两个层次 (初始和描述) 上对图像进行注释.
- 包括七个艺术风格的微调模型和Pinyin注释,用于独特的建筑术语.
主要成果:
- 创建首个专门针对中国古代建筑的综合多式联运数据集.
- 该数据集提供了丰富,分类和注释的数据,对于训练AI模型至关重要.
- 率先使用Pinyin用于注释中国专业建筑术语.
结论:
- 开发的数据集在描绘中国古代建筑方面显著提升了多式联络人工智能能力.
- 该资源促进了人工智能驱动的文化遗产应用领域的进一步研究和创新.
- 该数据集是保护和传播中国建筑历史知识的基础资源.
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