SOURCE-LINKED INTELLIGENCE
Hi-OPD: Hierarchy-Aware Open-Prompt Detection for Remote Sensing Images
Hi-OPD addresses a failure mode left uncontrolled by flat open-prompt training: descendant retrieval need not persist under ancestor queries when multi-source remote sensing annotations exhibit inconsistent granularity and missing labels. A detector may localize \textit{car} and \textit{van} under atomic prompts yet miss the same instances under \textit{vehicle}; flat AP does not expose this cross-level inconsistency. We propose Hi-OPD, a hierarchy-aware open-prompt detector, and construct RS153-HierOPD from 175,644 retained training image/tile records and 3.48M boxes mapped to 153 atomic cate
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-22T02:30:42.000Z
First collected: 2026-09-23T04:21:13.910Z. This is not the publication date.