OVRSISBenchV2 is a realistic benchmark expanding scene and category coverage for open-vocabulary remote sensing segmentation, with Pi-Seg baseline showing strong transfer via positive-incentive noise perturbations.
Annotation-free open-vocabulary segmentation for remote-sensing images
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SAM 3 can be applied training-free to remote sensing open-vocabulary segmentation and change detection by fusing its semantic and instance heads and filtering with presence scores.
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Towards Realistic Open-Vocabulary Remote Sensing Segmentation: Benchmark and Baseline
OVRSISBenchV2 is a realistic benchmark expanding scene and category coverage for open-vocabulary remote sensing segmentation, with Pi-Seg baseline showing strong transfer via positive-incentive noise perturbations.
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SegEarth-OV3: Exploring SAM 3 for Open-Vocabulary Semantic Segmentation in Remote Sensing Images
SAM 3 can be applied training-free to remote sensing open-vocabulary segmentation and change detection by fusing its semantic and instance heads and filtering with presence scores.