UMPE fuses any subset of HD/SD vector maps, raster SD maps, and satellite imagery into BEV features via alignment-aware vector and raster branches, raising mapping mAP by 5.3-5.9 points and cutting planning L2 error by 0.30 m on nuScenes.
Deep residual learning for image recognition,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
AdaTracker enables zero-shot cross-embodiment active visual tracking by encoding embodiment constraints from history to modulate a context-aware policy.
citing papers explorer
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Unified Map Prior Encoder for Mapping and Planning
UMPE fuses any subset of HD/SD vector maps, raster SD maps, and satellite imagery into BEV features via alignment-aware vector and raster branches, raising mapping mAP by 5.3-5.9 points and cutting planning L2 error by 0.30 m on nuScenes.
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AdaTracker: Learning Adaptive In-Context Policy for Cross-Embodiment Active Visual Tracking
AdaTracker enables zero-shot cross-embodiment active visual tracking by encoding embodiment constraints from history to modulate a context-aware policy.