InstaStyle: Inversion Noise of a Stylized Image is Secretly a Style Adviser

Stylized text-to-image generation focuses on creating images from textual descriptions while adhering to a style specified by a few reference images. However, subtle style variations within different reference images can hinder the model from accurately learning the target style. In this paper, we propose InstaStyle, a novel approach that excels in generating high-fidelity stylized images with only a single reference image. Our approach is based on the finding that the inversion noise from a stylized reference image inherently carries the …

cs.cv hinder image image generation images noise novel paper reference style text text-to-image textual