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Better multiple 3D object track and pose estimate by do it jointly with reconstruction with 3D_MOT

Better multiple 3D object track and pose estimate by do it jointly with reconstruction with 3D_MOT


3D Multi-Object Tracking with Differentiable Pose Estimation

arXiv paper abstract https://arxiv.org/abs/2206.13785



... propose a novel approach for joint 3D multi-object tracking and reconstruction from RGB-D sequences in indoor environments.


... detect and reconstruct objects in each frame while predicting dense correspondences mappings into a normalized object space.


... leverage those correspondences to inform a graph neural network to solve for the optimal, temporally-consistent 7-DoF pose trajectories of all objects.


... novelty ... two-fold: first, ... propose a new graph-based approach for differentiable pose estimation over time to learn optimal pose trajectories;


second, ... present a joint formulation of reconstruction and pose estimation along the time axis for robust and geometrically consistent multi-object tracking.


... method improves the accumulated MOTA score ... show ... yields a significant boost in tracking performance.



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