用低分辨率编辑解决高分辨率图像修改难题，效果更优。
Low-Resolution Editing is All You Need for High-Resolution Editing
- 分块优化高分辨率图像，逐块调整再融合
- 实现超过1K分辨率的高质量图像编辑
- 适合需要精细控制高分辨率图像的创作者
高分辨率内容生成正成为视觉与图形领域核心挑战。图像作为最基础的视觉表达形式，符合用户意图的内容生成需依赖高效可控的高分辨率图像操作机制。然而，现有方法仍局限于低分辨率场景，通常仅支持至1K分辨率。本文提出高分辨率图像编辑任务，并设计一种测试时优化框架。该方法对高分辨率源图像进行分块优化，随后通过细粒度细节传递模块和新颖同步策略，保持各块间一致性。大量实验证明，本方法能生成高质量编辑结果，有效推动高分辨率内容创作。
原文摘要 · Abstract (English)
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.
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