EnDKF combines ensemble Kalman filtering with directional statistics and unit quaternions to achieve lower pose tracking error than raw measurements in synthetic constant-velocity tests and FoundationPose-based head tracking.
Foundationpose: Unified 6d pose estimation and tracking of novel objects
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OMNI-PoseX presents a unified vision model using open-vocabulary perception and SO(3)-aware reflected flow matching to deliver state-of-the-art 6D pose estimation with real-time performance for embodied tasks.
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Pose Tracking with a Foundation Pose Model and an Ensemble Directional Kalman Filter
EnDKF combines ensemble Kalman filtering with directional statistics and unit quaternions to achieve lower pose tracking error than raw measurements in synthetic constant-velocity tests and FoundationPose-based head tracking.
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OMNI-PoseX: A Fast Vision Model for 6D Object Pose Estimation in Embodied Tasks
OMNI-PoseX presents a unified vision model using open-vocabulary perception and SO(3)-aware reflected flow matching to deliver state-of-the-art 6D pose estimation with real-time performance for embodied tasks.