Rethinking Where to Edit: Task-Aware Localization for Instruction-Based Image Editing
Instruction-based image editing (IIE) aims to modify an image according to a natural language instruction. Despite recent advances in diffusion transformers, existing methods often introduce unintended changes to regions unrelated to the requested edit. We attribute this limitation to the absence of an explicit mechanism for edit localization. Different editing operations (e.g., subject addition, removal, and replacement) induce distinct spatial patterns, yet existing IIE models typically perform localization in a task-agnostic manner. To address this limitation, we propose a training-free, task-aware edit localization framework that exploits the intrinsic source and target image streams ...
| Authors | Jingxuan He, Xiyu Wang, Mengyu Zheng et al. |
|---|---|
| Primary category | cs.CV |
| Published | 22 April 2026 |
| Last updated at source | 28 September 2026 |
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