CAFe-DINO achieves SOTA open-vocabulary semantic segmentation on remote sensing datasets by leveraging DINOv3 features with cost aggregation and upsampling, fine-tuned solely on an RS-targeted COCO-Stuff subset.
A survey on self- supervised methods for visual representation learning.Ma- chine Learning, 114(4):111
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DINO Soars: DINOv3 for Open-Vocabulary Semantic Segmentation of Remote Sensing Imagery
CAFe-DINO achieves SOTA open-vocabulary semantic segmentation on remote sensing datasets by leveraging DINOv3 features with cost aggregation and upsampling, fine-tuned solely on an RS-targeted COCO-Stuff subset.