低分辨率编辑即是高分辨率编辑的全部所需
Low-Resolution Editing is All You Need for High-Resolution Editing
把高分辨率编辑拆成 patch-wise 测试时优化 + 细节迁移 + 跨块同步，为在显存受限下做 4K 级可控编辑提供了可复用的分块一致性策略。
原文依据 Our method performs patch-wise optimization on high-resolution source images, followed by a fine-grained detail transfer module
摘要译文
由模型翻译 · 术语统一 · 请对照原文核对关键结论高分辨率内容创作正迅速成为视觉与图形学社区的核心挑战。图像是视觉表达最基本的模态，而与用户意图一致的内容生成需要有效、可控的高分辨率图像操控机制。然而，现有方法仍局限于低分辨率设定，通常仅支持最高 1K 分辨率。在本工作中，我们引入了高分辨率图像编辑这一任务，并提出一个测试时优化框架来解决它。我们的方法在高分辨率源图像上进行分块优化，随后通过一个细粒度细节迁移模块和一种新颖的同步策略来维持各块之间的一致性。大量实验表明，我们的方法能够产生高质量的编辑结果，从而促进高分辨率内容创作。
英文原文摘要 899 字符
High-resolution content creation is rapidly emerging as a central challenge in both the vision and graphics communities. Images serve as the most fundamental modality for visual expression, and content generation that aligns with the user intent requires effective, controllable high-resolution image manipulation mechanisms. However, existing approaches remain limited to low-resolution settings, typically supporting only up to 1K resolution. In this work, we introduce the task of high-resolution image editing and propose a test-time optimization framework to address it. Our method performs patch-wise optimization on high-resolution source images, followed by a fine-grained detail transfer module and a novel synchronization strategy to maintain consistency across patches. Extensive experiments show that our method produces high-quality edits, facilitating high-resolution content creation.