aerial-d
Collection
Generalized Referring Expression Segmentation on Aerial Photos
β’
5 items
β’
Updated
Trained SigLIP2 + SAM checkpoints for referring expression segmentation on aerial imagery from The Aerial-D Dataset.
rsrefseg_combined.pt β Trained on 5 datasets (Aerial-D + RefSegRS + RRSIS-D + NWPU-Refer + Urban1960SatSeg). Uses RSRefSeg-L with facebook/sam-vit-large.rsrefseg_aerial-d.pt β Trained exclusively on Aerial-D. Uses RSRefSeg-Base with facebook/sam-vit-base.# 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.