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
Summary
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: manifests as over-smoothed or over-sharpened artifacts.
- High-fidelity editing with superior perceptual quality at resolutions up to 4K
- 3.6-8.4x speedup at 2K resolution
- Practical 4K editing completed within 61 seconds
The authors propose EditBridge, a diffusion bridge framework for efficient ultra-high-resolution editing. Unlike conventional diffusion that regenerates from noise, refinement is formulated as a structured data-to-data transformation from the low-resolution (LR) edited result to its HR counterpart, explicitly conditioned 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
Original Abstract
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, where hallucinated details contradict the original high-resolution (HR) source, and texture degradation, manifesting as over-smoothed or over-sharpened artifacts. We propose EditBridge, a diffusion bridge framework for efficient ultra high-resolution editing. Unlike conventional diffusion that regenerates from noise, we formulate refinement as structured data-...
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