EditBridge: A Diffusion Bridge Framework for Faithful and Efficient Ultra-High-Resolution Image Editing

Forum topic · 小凯 · 2026-08-20

Summary

EditBridge (arXiv 2608.18063) is a diffusion bridge framework for ultra-high-resolution image editing. Existing diffusion models are limited to below 1K resolution due to quadratic attention complexity and memory costs, so a common workaround edits at low resolution and then applies independent super-resolution. That pipeline, however, causes information divergence (hallucinated details conflicting with the original high-resolution source) and texture degradation (over-smoothed or over-sharpened artifacts). EditBridge instead formulates refinement as a structured data-to-data transformation from the edited low-resolution result to its high-resolution counterpart, explicitly conditioning on the original HR source to preserve authentic details. A prior-guided block sparse attention mechanism exploits semantic correspondences from the first-stage edit to restrict cross-image interaction to spatially aligned regions, greatly reducing computation. Experiments show high-fidelity editing and superior perceptual quality up to 4K, a 3.6-8.4x speedup at 2K resolution, and practical 4K editing within 61 seconds.

Paper Overview

Field: Computer Vision
Authors: Jiayi Song, Shijie Huang, Fangtai Wu, Yubo Huang, Zhenxiong Tan, Songhua Liu, Jiaming Liu, Ruihua Huang
arXiv: 2608.18063

Background

High-resolution image editing is increasingly demanded in professional workflows, yet existing diffusion-based models remain constrained to resolutions below 1K due to quadratic attention complexity and prohibitive memory requirements. A prevalent workaround employs a two-stage pipeline: editing at low resolution followed by independent super-resolution. However, this approach suffers from two critical issues:

Information divergence: hallucinated details contradict the original high-resolution (HR) source.
Texture degradation: over-smoothed or over-sharpened artifacts appear in the refined image.

EditBridge

EditBridge is a diffusion bridge framework for efficient ultra-high-resolution editing. Unlike conventional diffusion that regenerates from noise, it formulates refinement as a structured data-to-data transformation from the low-resolution (LR) edited result to its HR counterpart, explicitly conditioning on the original HR source to preserve authentic details.

To efficiently incorporate HR source guidance, EditBridge introduces a prior-guided block sparse attention mechanism that leverages semantic correspondences from the first-stage edit, constraining cross-image interaction to spatially aligned regions and significantly reducing computational overhead.

Results

High-fidelity editing and superior perceptual quality at resolutions up to 4K.
3.6-8.4x speedup at 2K resolution compared to existing approaches.
Practical 4K editing within 61 seconds.