| # Citation |
| If you find it useful, please consider citing: |
|
|
| ``` |
| @article{wang2026rsgpnet, |
| title={RSGPNet: Geometric Prompting for Remote Sensing Open-Vocabulary Semantic Segmentation}, |
| author={Wang, Shanwen and Sun, Xin and Wang, Sirui and Zhu, Xiao Xiang}, |
| journal={arXiv preprint arXiv:2606.28410}, |
| year={2026} |
| } |
| ``` |
| # Acknowledgments |
| We sincerely thank the authors of [SAM3](https://github.com/facebookresearch/sam3) and [SegEarth‑OV3](https://github.com/earth-insights/SegEarth-OV-3) for their excellent open‑source work, and we also thank the contributors of the publicly available [LoveDA](https://zenodo.org/records/5706578), [Potsdam](https://www.isprs.org/resources/datasets/benchmarks/UrbanSemLab/2d-sem-label-potsdam.aspx?utm_source=chatgpt.com), [UDD5](https://github.com/MarcWong/UDD?utm_source=chatgpt.com) and [Vaihingen](https://www.isprs.org/resources/datasets/benchmarks/UrbanSemLab/results/vaihingen-2d-semantic-labeling.aspx?utm_source=chat.dogai.vip) datasets. Please follow the licenses and terms of the original models and datasets. |
