标题： 概念手术刀：基于组成表示移植的图像编辑 显示英文标题

标题： Concept Lancet: Image Editing with Compositional Representation Transplant

摘要： 扩散模型广泛用于图像编辑任务。现有的编辑方法通常通过设计文本嵌入或分数空间中的编辑方向来设计表示操作过程。然而，这种方法面临一个关键挑战：过度估计编辑强度会损害视觉一致性，而低估它则无法完成编辑任务。值得注意的是，每张源图像可能需要不同的编辑强度，并且通过试错法寻找适当的强度成本高昂。为了解决这个挑战，我们提出了Concept Lancet（CoLan），这是一种针对基于扩散的图像编辑中原则性表示操作的零样本即插即用框架。在推理阶段，我们将源输入分解为潜在（文本嵌入或扩散分数）空间中收集的视觉概念表示的稀疏线性组合。这使我们可以准确估计每个图像中概念的存在情况，从而指导编辑过程。根据编辑任务（替换/添加/删除），我们执行自定义的概念移植过程以施加相应的编辑方向。为了充分建模概念空间，我们策划了一个概念表示数据集CoLan-150K，其中包含潜在字典中视觉术语和短语的各种描述和场景。在多个基于扩散的图像编辑基线上的实验表明，配备CoLan的方法在编辑效果和一致性保持方面达到了最先进的性能。 显示英文摘要

摘要： Diffusion models are widely used for image editing tasks. Existing editing methods often design a representation manipulation procedure by curating an edit direction in the text embedding or score space. However, such a procedure faces a key challenge: overestimating the edit strength harms visual consistency while underestimating it fails the editing task. Notably, each source image may require a different editing strength, and it is costly to search for an appropriate strength via trial-and-error. To address this challenge, we propose Concept Lancet (CoLan), a zero-shot plug-and-play framework for principled representation manipulation in diffusion-based image editing. At inference time, we decompose the source input in the latent (text embedding or diffusion score) space as a sparse linear combination of the representations of the collected visual concepts. This allows us to accurately estimate the presence of concepts in each image, which informs the edit. Based on the editing task (replace/add/remove), we perform a customized concept transplant process to impose the corresponding editing direction. To sufficiently model the concept space, we curate a conceptual representation dataset, CoLan-150K, which contains diverse descriptions and scenarios of visual terms and phrases for the latent dictionary. Experiments on multiple diffusion-based image editing baselines show that methods equipped with CoLan achieve state-of-the-art performance in editing effectiveness and consistency preservation.