Mitigating Content Shift and Hallucination in GenAI Image Editing via Structural Refinement
Generative AI (GenAI) image editors, such as Nano Banana, produce visually compelling results for retouching tasks, enabling non-experts to edit images through text prompts alone. However, the generative nature of these models often introduces spatial misalignment, texture distortion, and content hallucination, all of which are detrimental to downstream workflows that require pixel-level fidelity. We identify a problem setting we call "structure-preserving GenAI fusion" for black-box GenAI image retouching: retain the perceptual enhancements of a GenAI output while enforcing structural faithfulness to the original input image. To address this problem, we propose a post-processing framewor...
| Authors | Luxi Zhao, Michael S. Brown |
|---|---|
| Primary category | cs.CV |
| Published | 28 May 2026 |
| Last updated at source | 10 June 2026 |
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