MAPRPose achieves state-of-the-art 76.5% Average Recall on the BOP benchmark for 6D pose estimation, outperforming FoundationPose by 3.1% AR while delivering a 43x speedup in multi-object inference.
Foundpose: Unseen object pose estimation with foundation features
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A factor graph that fuses motion models with uncertainty-aware pose measurements improves temporal consistency and benchmark scores for vision-based robot control.
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