RefCap:用引用对象属性进行图像标题.
Seokmok Park1, Joonki Paik2,3
1Department of Image, Chung-Ang University, 84 Heukseok-ro, Seoul, 06974, Republic of South Korea.
Scientific reports
|December 7, 2023
概括
这项研究引入了一种新的引用表达式图像标题模型. 它生成专注于用户选择对象的特定图像描述,增强视觉理解和计算机视觉应用.
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.
- 人工智能的人工智能
背景情况:
- 视觉语言多模式研究已经推进了视觉理解.
- 图像标题是视觉语言理解的一个关键任务.
- 现有的方法可能在生成的标题中缺乏特异性.
研究的目的:
- 开发一个引用表达式的图像标题模型.
- 为了能够生成专注于用户指定的对象的标题.
- 提高图像描述的相关性和具体性.
主要方法:
- 该模型集成了视觉接地,引用对象选择和图像标题模块.
- 用户提供的对象关键字被用作标题生成的前.
- 在RefCOCO和COCO标题数据集上进行了实验.
主要成果:
- 建议的模型有效地产生有意义的标题.
- 标题与用户的特定兴趣和目标对象保持一致.
- 该方法在图像描述中显示了更好的特异性.
结论:
- 开发的模型成功地解决了针对图像标题的需求.
- 用有趣的对象进行监督可以提高标题的相关性.
- 这种方法推进了计算机视觉和多模式人工智能的应用.
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