RSEdit: Text-Guided Image Editing for Remote Sensing
In this paper, we explore text-guided image editing in the remote sensing domain using generative modeling. We propose \rsedit, a collection of models from U-Net to DiT with various configurations. Specifically, we present the first comprehensive study of conditioning strategies for building image editing models from off-the-shelf text-to-image ones. Our experiments show that \rsedit achieves the best instruction-faithful edits while preserving geospatial structure. We release the code at \url{https://github.com/Bili-Sakura/RSEdit-Preview} and checkpoints at \url{https://huggingface.co/collections/BiliSakura/rsedit}.
| Authors | Chen Zhenyuan, Zhang Zechuan, Zhang Feng |
|---|---|
| Primary category | cs.CV |
| Published | 14 March 2026 |
| Last updated at source | 18 May 2026 |
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