Text-to-image generation models have seen considerable advancement, catering
to the increasing interest in personalized image creation. Current
customization techniques often necessitate users to provide multiple images
(typically 3-5) for each customized object, along with the classification of
these objects and descriptive textual prompts for scenes. This paper questions
whether the process can be made more user-friendly and the customization more
intricate. We propose a method where users need only provide images along with
text for each customization topic, and necessitates only a single image per
visual concept. We introduce the concept of a ``multi-modal prompt'', a novel
integration of text and images tailored to each customization concept, which
simplifies user interaction and facilitates precise customization of both
objects and scenes. Our proposed paradigm for customized text-to-image
generation surpasses existing finetune-based methods in user-friendliness and
the ability to customize complex objects with user-friendly inputs. Our code is
available at
$\href{https://github.com/zhongzero/Multi-Modal-Prompt}{this https URL}$.

本文提出了一种方法，用户只需提供每个定制主题的图像和文本，而不需要提供多张图像，通过引入 “多模态提示” 概念，将文本和图像相结合，简化用户交互，实现对对象和场景的精确定制。该方法在用户友好性和使用友好输入定制复杂对象方面超过了现有的基于微调方法。