MAG-VLAQ fuses multi-modal ground and aerial data via ODE-conditioned vector-of-locally-aggregated-queries to nearly double recall@1 on aerial-ground place recognition benchmarks.
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A Learn-and-Dispose memory framework using static satellite anchors and diversity-driven dynamic buffers improves retention in continual aerial visual place recognition by 7.8% over random selection on a new 21-sequence benchmark.
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MAG-VLAQ: Multi-modal Aerial-Ground Query Aggregation for Cross-View Place Recognition
MAG-VLAQ fuses multi-modal ground and aerial data via ODE-conditioned vector-of-locally-aggregated-queries to nearly double recall@1 on aerial-ground place recognition benchmarks.
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Towards Lifelong Aerial Autonomy: Geometric Memory Management for Continual Visual Place Recognition in Dynamic Environments
A Learn-and-Dispose memory framework using static satellite anchors and diversity-driven dynamic buffers improves retention in continual aerial visual place recognition by 7.8% over random selection on a new 21-sequence benchmark.