AFUN predicts task-conditional functional masks and 3D post-contact motion curves from RGB-D and language, trained via a standardized multi-source data pipeline, and reports large gains over baselines on segmentation, contact prediction, and motion tasks.
Poles of inaccessibility: A calculation algorithm for the remotest places on earth
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A hybrid neural-geometric approach processes tilted LiDAR data to estimate yaw and compute safe position, enabling localization-free navigation in straight and curved tunnels.
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AFUN: Towards an Affordance Foundation Model for Functionality Understanding
AFUN predicts task-conditional functional masks and 3D post-contact motion curves from RGB-D and language, trained via a standardized multi-source data pipeline, and reports large gains over baselines on segmentation, contact prediction, and motion tasks.
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Neural-Geometric Tunnel Traversal: Localization-free UAV Flight with Tilted LiDARs
A hybrid neural-geometric approach processes tilted LiDAR data to estimate yaw and compute safe position, enabling localization-free navigation in straight and curved tunnels.