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SUFLECA achieves a remarkable 33.4% category accuracy and 42.3% instance accuracy in CAD-to-image alignment, outpacing traditional methods while cutting down computational costs.
Floor plans, rich with semantic information,
Key contribution not extracted.
Robots can now "see" and understand doorways, enabling more robust navigation in complex indoor environments.
Autonomous drones can now navigate race courses with significantly improved accuracy thanks to a novel dual pose-graph SLAM architecture that fuses visual and semantic information.
