深度专利2:用于技术绘图理解的大规模基准测试库
Kehinde Ajayi1, Xin Wei1, Martin Gryder1
1Computer Science, Old Dominion University, Norfolk, Virginia, 23529, US.
Scientific data
|November 7, 2023
概括
研究人员开发了DeepPatent2,一个大型技术图纸数据集,以改善计算机视觉任务,如图像标题和从草图中进行3D重建.
科学领域:
- 计算机视觉 计算机视觉
- 自然语言处理自然语言处理.
- 机器学习 机器学习
- 数据科学数据科学数据科学
背景情况:
- 计算机视觉 (CV) 和自然语言处理 (NLP) 的进步依赖于大型数据集.
- 目前的数据集限制了CV任务,例如技术草图上的图像标题和3D重建.
- 专利中的技术图纸是CV研究中未充分利用的数据源.
研究的目的:
- 介绍DeepPatent2,技术图纸的新型大规模数据集.
- 解决CV任务的现有数据集中的局限性,这些任务涉及科学和技术图像.
- 促进诸如概念标题,3D重建和图像检索等领域的研究.
主要方法:
- 从美国设计专利文件 (14年) 中提取了超过270万张技术图纸.
- 有132,890个物体名称和22,394个独特的视角的注释图纸.
- 开发了一个数据集管道,用于大规模的数据提取和处理.
主要成果:
- 深度专利2包括270万个技术图纸与丰富的元数据.
- 证明了数据集对概念标题任务的实用性.
- 展示了推进3D重建和图像检索的潜力.
结论:
- 深度专利2为CV和NLP技术图像研究提供了宝贵的资源.
- 数据集可以显著提高对需要理解草图和技术视觉图像的任务的性能.
- 未来的研究可以利用DeepPatent2在科学和工程领域的各种应用.
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