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.
6d pose estimation with correlation fusion
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MAPRPose: Mask-Aware Proposal and Amodal Refinement for Multi-Object 6D Pose Estimation
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.