RealCustom++:将图像表示为实时文本单词,用于实时定制
IEEE transactions on pattern analysis and machine intelligence
|October 17, 2025
概括
RealCustom++引入了一个新的真实词范式,用于文本到图像的定制,克服伪词的局限性. 这种方法增强了对象的相似性和文本的可控性,从而产生更优质的图像.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 图像生成 图像生成
背景情况:
- 文本到图像定制旨在将生成的图像与文本描述和源图像主题对齐.
- 现有的方法使用伪词范式,在主题相似性和文本可控性之间产生冲突.
- 这种伪词方法导致了双最佳悖论,阻碍了对所需图像属性的同时优化.
研究的目的:
- 提出RealCustom++,一个新的真实词范式,用于文本到图像定制.
- 解开文本和主题的影响,同时优化图像生成.
- 为了提高主题相似性,文本可控性和整体图像质量,在定制图像生成中.
主要方法:
- 推出了RealCustom++,一个使用非冲突的真实单词进行对象表示的真实单词范式.
- 开发了一种训练-推断脱的框架,用于一般视觉-文本对齐学习和专业推断.
- 在推断过程中采用双分支架构:用于主题面具生成的指导分支和用于特定区域定制的生成分支.
主要成果:
- RealCustom++显著提高了可控性7.48%,相似性3.04%,质量提高了76.43%.
- 在多主题定制任务的可控性 (4.6%) 和多主题相似性 (6.34%) 中取得了进一步的改进.
- 在文本到图像定制方面,在现有方法上表现出优异的性能.
结论:
- 拟议的真实词范式有效地解决了伪词方法在文本到图像定制方面的局限性.
- RealCustom++可以同时优化主题相似性,文本可控性和图像质量.
- 该方法显示了高级图像生成和多主题定制应用程序的巨大潜力.
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