Abstract
Multi-object images are prevalent in various real-world scenarios, including augmented reality, advertisement design, and medical imaging. Efficient and precise editing of these images is critical for these applications. With the advent of Stable Diffusion (SD), high-quality image generation and editing have entered a new era. However, existing methods often struggle to consider each object both individually and part of the whole image editing, both of which are crucial for ensuring consistent quantity perception, resulting in suboptimal perceptual performance. To address these challenges, we propose MoEdit, an auxiliary-free multi-object image editing framework. MoEdit facilitates high-quality multi-object image editing in terms of style transfer, object reinvention, and background regeneration, while ensuring consistent quantity perception between inputs and outputs, even with a large number of objects. To achieve this, we introduce the Feature Compensation (FeCom) module, which ensures the distinction and separability of each object attribute by minimizing the in-between interlacing. Additionally, we present the Quantity Attention (QTTN) module, which perceives and preserves quantity consistency by effective control in editing, without relying on auxiliary tools. By leveraging the SD model, MoEdit enables customized preservation and modification of specific concepts in inputs with high quality. Experimental results demonstrate that our MoEdit achieves State-Of-The-Art (SOTA) performance in multi-object image editing. Data and codes will be available at this https URL.
Abstract (translated)
多对象图像在增强现实、广告设计和医学成像等多种实际场景中普遍存在。高效且精准地编辑这些图像对于上述应用至关重要。随着Stable Diffusion（SD）的出现，高质量的图像生成与编辑进入了一个新的时代。然而，现有的方法往往难以同时考虑每个对象的独立性和其作为整体图像的一部分的重要性，而这两种因素对保证一致的数量感知都至关重要，从而导致了次优的感知性能。 为了解决这些问题，我们提出了MoEdit——一种无辅助工具支持的多对象图像编辑框架。MoEdit使高质量的多对象图像编辑成为可能，包括风格转移、对象重新发明和背景再生，并确保输入与输出之间一致的数量感知，即使是在处理大量对象的情况下也是如此。为了实现这一点，我们引入了特征补偿（FeCom）模块，通过最小化中间交叉来保证每个对象属性的区别性和可分离性。此外，我们还提出了数量注意力（QTTN）模块，在编辑过程中有效控制以感知并保持数量的一致性，无需依赖辅助工具。 借助SD模型，MoEdit能够高质量地定制保存和修改输入中的特定概念。实验结果表明，我们的MoEdit在多对象图像编辑方面达到了最先进的性能水平。数据和代码将在以下链接提供：[此URL]（请将括号内的内容替换为实际提供的网址）。
URL
https://arxiv.org/abs/2503.10112
