SPN is a CNN that detects a spacecraft bounding box, classifies then regresses attitude, and optimizes position via Gauss-Newton, achieving degree-level attitude and cm-level position errors on real images after training only on synthetic data.
DeepIM: Deep Iterative Matching for 6D Pose Estima- tion
3 Pith papers cite this work. Polarity classification is still indexing.
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OneViewAll reports 92.5% ADD-0.1 pose accuracy on LINEMOD from a single real reference RGB-D view, using projection-based refinement with mirror-fusion symmetry priors rather than CAD rendering.
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Pose Estimation for Non-Cooperative Rendezvous Using Neural Networks
SPN is a CNN that detects a spacecraft bounding box, classifies then regresses attitude, and optimizes position via Gauss-Newton, achieving degree-level attitude and cm-level position errors on real images after training only on synthetic data.
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Semantic Prior Guided One-View 6D Pose Estimation for Novel Objects
OneViewAll reports 92.5% ADD-0.1 pose accuracy on LINEMOD from a single real reference RGB-D view, using projection-based refinement with mirror-fusion symmetry priors rather than CAD rendering.
- MAPRPose: Mask-Aware Proposal and Amodal Refinement for Multi-Object 6D Pose Estimation