论文标题
多解决文本反演
Multiresolution Textual Inversion
论文作者
论文摘要
我们扩展了文本反演，以学习代表不同分辨率概念的伪字。这使我们能够生成使用具有不同细节级别的概念的图像，并使用语言来操纵不同的分辨率。一旦学习，用户就可以以不同级别的一致性生成与原始概念的图像。 “ $ s^*（0）$的照片”在提示“ $ s^*（0.8）$的照片”中产生确切的对象，仅与粗糙的轮廓和颜色相匹配。我们的框架使我们能够生成图像，这些图像使用图像的不同分辨率（例如详细信息，纹理，样式）作为可以以各种方式组成的单独伪字。我们在以下URL中打开代码：https：//github.com/giannisdaras/multires_textual_inversion
We extend Textual Inversion to learn pseudo-words that represent a concept at different resolutions. This allows us to generate images that use the concept with different levels of detail and also to manipulate different resolutions using language. Once learned, the user can generate images at different levels of agreement to the original concept; "A photo of $S^*(0)$" produces the exact object while the prompt "A photo of $S^*(0.8)$" only matches the rough outlines and colors. Our framework allows us to generate images that use different resolutions of an image (e.g. details, textures, styles) as separate pseudo-words that can be composed in various ways. We open-soure our code in the following URL: https://github.com/giannisdaras/multires_textual_inversion
