AI RESEARCH
SSP-SAM: SAM with Semantic-Spatial Prompt for Referring Expression Segmentation
arXiv CS.CV
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ArXi:2603.18086v1 Announce Type: new The Segment Anything Model (SAM) excels at general image segmentation but has limited ability to understand natural language, which restricts its direct application in Referring Expression Segmentation (RES). Toward this end, we propose SSP-SAM, a framework that fully utilizes SAM's segmentation capabilities by integrating a Semantic-Spatial Prompt (SSP) encoder.