AI RESEARCH
EditRefiner: A Human-Aligned Agentic Framework for Image Editing Refinement
arXiv CS.CV
•
ArXi:2605.07457v1 Announce Type: new Recent text-guided image editing (TIE) models have made remarkable progress, yet edited images still frequently suffer from fine-grained issues such as unnatural objects, lighting mismatch, and unexpected changes. Existing refinement approaches either rely on costly iterative regeneration or employ vision-language models (VLMs) with weak spatial grounding, often resulting in semantic drift and unreliable local corrections.