A two-stage framework, PSLG-SAM, uses visual grounding to locate objects and Segment Anything Model to segment them, with a new RRSIS-M dataset, surpassing prior methods when mask supervision is available.
In Proceedings of the IEEE Con- ference on Computer Vision and Pattern Recognition
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Semantic Localization Guiding Segment Anything Model For Reference Remote Sensing Image Segmentation
A two-stage framework, PSLG-SAM, uses visual grounding to locate objects and Segment Anything Model to segment them, with a new RRSIS-M dataset, surpassing prior methods when mask supervision is available.