RSEdit: Text-Guided Image Editing for Remote Sensing
计算机视觉与模式识别
2026-05-19 v2
摘要
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}.
引用
@article{arxiv.2603.13708,
title = {RSEdit: Text-Guided Image Editing for Remote Sensing},
author = {Chen Zhenyuan and Zhang Zechuan and Zhang Feng},
journal= {arXiv preprint arXiv:2603.13708},
year = {2026}
}
备注
accepted by IEEE GRSL