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PerSeM: Persistent Semantic Memory for Long-Horizon Open-Vocabulary UAV Mapping
Open-vocabulary segmentation enables rich semantic perception for UAVs, but frame-wise predictions can remain temporally inconsistent across repeated observations and changing viewpoints. We present PerSeM, a training-free persistent semantic memory framework for long-horizon open-vocabulary UAV map
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