5 datasets found

The dataset used in this paper is a large-scale text-to-image diffusion model, which consists of 35 subjects with unique pets and objects.

Key-locked rank one editing for text-to-image personalization.

The dataset used in this paper for testing the effectiveness of the disguise generation algorithm.

Textual Inversion: An image is worth one word: Personalizing text-to-image generation using textual inversion.

CatVersion allows users to learn the personalized concept through a handful of examples and then utilize text prompts to generate images that embody the personalized concept.