操纵方向:根据图像和文本模式的变化之间的相似性,评估基于文本引导的图像操纵.
Yuto Watanabe1, Ren Togo2, Keisuke Maeda2
1Graduate School of Information Science and Technology, Hokkaido University, N-14, W-9, Kita-ku, Sapporo 060-0814, Hokkaido, Japan.
Sensors (Basel, Switzerland)
|November 25, 2023
概括
本研究介绍了操纵方向 (MD),这是评估文本引导图像操纵的新指标. MD评估图像更改与文本描述的协调程度,提供更强大的性能测量.
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:
- 文本导向图像操纵旨在根据文本输入改变图像,同时保持不变的区域.
- 现有的研究重点是改进操纵技术,但缺乏绩效评估方法.
研究的目的:
- 提出一种新的,逻辑和强大的指标来评估文本引导图像操纵性能.
- 解决目前的绩效评估研究对文本导向图像操纵的不足.
主要方法:
- 该研究介绍了操纵方向 (MD),这是一个指标,重点是操纵前后图像和文本模式之间的变化的一致性.
- MD量化了图像转换与所提供的文本指导保持一致程度.
主要成果:
- 在多模式CelebA-HQ和Caltech-UCSD鸟类数据集上的实验表明MD得分和人类主观评估之间存在强烈的相关性.
- 与现有的评估指标相比,拟议的MD指标显示出更高的性能.
结论:
- 操纵方向 (MD) 提供了一种全面可靠的方法来评估文本引导图像操纵的质量.
- 该指标有效地评估了图像修改和文本说明之间的对齐,超过了当前的标准.
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