AI RESEARCH
Geospatial-Reasoning-Driven Vocabulary-Agnostic Remote Sensing Semantic Segmentation
arXiv CS.CV
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ArXi:2602.08206v2 Announce Type: replace Open-vocabulary semantic segmentation has become an important direction in remote sensing, as it enables recognition beyond predefined land-cover categories. However, existing methods mainly depend on passive visual-text matching and often struggle with semantic ambiguity in geographically complex scenes, especially when different classes exhibit similar spectral or structural patterns. To address this issue, we propose a Geospatial Reasoning Chain-of-Thought (GR-CoT) framework for remote sensing open-vocabulary semantic segmentation.