| # RSRefSeg Model Checkpoints | |
| Trained SigLIP2 + SAM checkpoints for referring expression segmentation on aerial imagery from **[The Aerial-D Dataset](https://huggingface.co/datasets/luisml77/aerial-d)**. | |
| ## Models | |
| - **`rsrefseg_combined.pt`** — Trained on 5 datasets (Aerial-D + RefSegRS + RRSIS-D + NWPU-Refer + Urban1960SatSeg). Uses RSRefSeg-L with `facebook/sam-vit-large`. | |
| - **`rsrefseg_aerial-d.pt`** — Trained exclusively on Aerial-D. Uses RSRefSeg-Base with `facebook/sam-vit-base`. | |
| ## Usage | |
| ```python | |
| # Load and test with the codebase | |
| from model import SigLipSamSegmentator | |
| model = SigLipSamSegmentator(checkpoint_path="rsrefseg_combined.pt") | |
| mask = model.segment(image, "the building in the top left") | |
| ``` | |
| See training/evaluation code at **[GitHub](https://github.com/luisml77/aerialseg)**. | |
| ## Links | |
| - **[📝 Paper](https://arxiv.org/abs/2512.07338)** - arXiv preprint | |
| - **[📊 Aerial-D Dataset](https://huggingface.co/datasets/luisml77/aerial-d)** - Aerial-D dataset | |
| - **[💻 Code](https://github.com/luisml77/aerialseg)** - Training and evaluation scripts | |
| - **[🌐 Project](https://luispl77.github.io/aerial-d/)** - Project page | |
| - **[📦 Complete Collection](https://huggingface.co/collections/luisml77/aerial-d-68a17e2431daebb96218edce)** - All Aerial-D artifacts | |