RSEdit: Text-Guided Image Editing for Remote Sensing
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Abstract (arXiv)
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 urlhttps://github.com/Bili-Sakura/RSEdit-Preview and checkpoints at urlhttps://huggingface.co/collections/BiliSakura/rsedit.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 47 of its 80 references that are in the map. First posted on arXiv 14 Mar 2026.
Builds on
47 of 80 references.
References · 47
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35 more
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