We propose Pure and Lightning ID customization (PuLID), a novel tuning-free ID customization method for text-to-image generation. By incorporating a Lightning T2I branch with a standard diffusion one, PuLID introduces both contrastive alignment loss and accurate ID loss, minimizing disruption to the original model and ensuring high ID fidelity. Experiments show that PuLID achieves superior performance in both ID fidelity and editability. Another attractive property of PuLID is that the image elements (e.g., background, lighting, composition, and style) before and after the ID insertion are kept as consistent as possible. Codes and models are available at https://github.com/ToTheBeginning/PuLID

翻译：我们提出了纯净闪电级身份定制（PuLID），一种用于文本到图像生成的新型免调优身份定制方法。通过将闪电级文本到图像分支与标准扩散分支相结合，PuLID引入了对比对齐损失和精确身份损失，从而最小化对原始模型的干扰并确保高身份保真度。实验表明，PuLID在身份保真度和可编辑性方面均取得了卓越性能。PuLID的另一个吸引人特性是，身份嵌入前后的图像元素（如背景、光照、构图和风格）尽可能保持一致。代码和模型可在 https://github.com/ToTheBeginning/PuLID 获取。