Low-Resolution Editing is All You Need for High-Resolution Editing

TL;DR

This paper introduces a novel high-resolution image editing method that uses patch-wise optimization and detail transfer, enabling high-quality edits at resolutions beyond 1K.

Contribution

It presents a new test-time optimization framework for high-resolution editing, overcoming limitations of existing low-resolution approaches.

Findings

Produces high-quality high-resolution edits

Maintains consistency across image patches

Facilitates high-resolution content creation

Abstract

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.