OneViewAll achieves 92.5% ADD-0.1 accuracy on LINEMOD for novel object 6D pose estimation using only one real reference view by integrating category, symmetry, and patch-level semantic priors in a projection-equivariant alignment.
Cosypose: Consistent multi-view multi-object 6d pose estimation
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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.
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