A transformer network estimates body-frame velocity and uncertainty from raw 4D radar spectral cubes, fused with IMU in a pose graph to achieve lower relative pose error than classical baselines on indoor sequences.
evo: Python package for the evaluation of odometry and SLAM
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Pith papers citing it
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cs.RO 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
MonoEM-GS stabilizes view-dependent geometry from foundation models inside a global Gaussian Splatting representation via EM and adds multi-modal features for in-place open-set segmentation.
citing papers explorer
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UNRIO: Uncertainty-Aware Velocity Learning for Radar-Inertial Odometry
A transformer network estimates body-frame velocity and uncertainty from raw 4D radar spectral cubes, fused with IMU in a pose graph to achieve lower relative pose error than classical baselines on indoor sequences.
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MonoEM-GS: Monocular Expectation-Maximization Gaussian Splatting SLAM
MonoEM-GS stabilizes view-dependent geometry from foundation models inside a global Gaussian Splatting representation via EM and adds multi-modal features for in-place open-set segmentation.