UniPortrait：一个统一的框架，用于保护身份的单人和多人图像个性化

UniPortrait: A Unified Framework for Identity-Preserving Single- and Multi-Human Image Personalization

August 12, 2024

作者: Junjie He, Yifeng Geng, Liefeng Bo

cs.AI

摘要

本文介绍了UniPortrait，一种创新的人像个性化框架，将单一和多重身份定制统一起来，具有高面部保真度、丰富的面部可编辑性、自由形式输入描述和多样的布局生成。UniPortrait仅由两个即插即用的模块组成：ID嵌入模块和ID路由模块。ID嵌入模块采用解耦策略提取多功能可编辑的面部特征，并将它们嵌入扩散模型的上下文空间。然后，ID路由模块将这些嵌入自适应地组合和分配到合成图像中的各自区域，实现单一和多重身份的定制。通过精心设计的两阶段训练方案，UniPortrait在单一和多重身份定制方面实现了卓越的性能。定量和定性实验展示了我们的方法相对于现有方法的优势，以及其良好的可扩展性，例如与现有生成控制工具的通用兼容性。项目页面位于https://aigcdesigngroup.github.io/UniPortrait-Page/。

English

This paper presents UniPortrait, an innovative human image personalization framework that unifies single- and multi-ID customization with high face fidelity, extensive facial editability, free-form input description, and diverse layout generation. UniPortrait consists of only two plug-and-play modules: an ID embedding module and an ID routing module. The ID embedding module extracts versatile editable facial features with a decoupling strategy for each ID and embeds them into the context space of diffusion models. The ID routing module then combines and distributes these embeddings adaptively to their respective regions within the synthesized image, achieving the customization of single and multiple IDs. With a carefully designed two-stage training scheme, UniPortrait achieves superior performance in both single- and multi-ID customization. Quantitative and qualitative experiments demonstrate the advantages of our method over existing approaches as well as its good scalability, e.g., the universal compatibility with existing generative control tools. The project page is at https://aigcdesigngroup.github.io/UniPortrait-Page/ .