网状上下文意识的光束搜索图像标题
Fengzhi Zhao1,2, Zhezhou Yu1,2,3, Tao Wang1,2
1College of Computer Science and Technology, Jilin University, Changchun 130012, China.
Entropy (Basel, Switzerland)
|October 25, 2024
概括
网状上下文感知光束搜索 (MCBS) 通过动态整合标题上下文和图像注意力来增强图像标题. 这种方法减少了重复性的单词,并提高了标题的整体质量和相关性.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 自然语言处理自然语言处理.
背景情况:
- 梁搜索是一种用于图像标题的标准算法,旨在生成准确和强大的标题.
- 现有的光束搜索方法往往忽略了更广泛的图像上下文,并且可以产生重复性的,不那么多样化的标题.
研究的目的:
- 引入Meshed Context-Aware Beam Search (MCBS),以解决图像标题的标准光束搜索的局限性. 引入网状文本意识光束搜索 (MCBS),以解决图像标题的标准光束搜索的局限性.
- 为了提高标题的连贯性,上下文的适当性和多样性.
主要方法:
- 在解码过程中,MCBS动态地使用生成的标题上下文来影响图像注意力机制.
- 纳入了惩罚系数,以阻止在生成的标题中重复单词.
主要成果:
- 在图像标题任务中,MCBS显著提高了模型的整体性能.
- 该方法通过考虑标题上下文,提高了对相关图像区域的关注度.
结论:
- 对于图像标题,MCBS比传统的光束搜索提供了显著的改进.
- 拟议的方法导致更连贯,上下文相关和多样化的图像字幕.
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